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Micro-Transfer printing (µTP) is a promising technique for hetero-integration of III-V materials into Si-based photonic platforms. To enhance the print yield by increasing the adhesion between the III-V material and Si or SiO2 surface, an adhesion promoter like Benzocyclobutene is typically used as interlayer. In this work, we demonstrate µTP of InP based coupons on SiO2 interlayer without any adhesive interlayer and investigate the mechanism of adhesive free bonding. Source coupons are InP-based coupon stacks on a sacrificial layer that is removed by a chemical wet etch with FeCl3. For the target we fabricated amorphous-Si waveguides on 8” wafer encapsulated by a High Density Plasma SiO2 which was planarized by a chemical mechanical polishing procedure. We used O2 plasma to activate both source and target to increase adhesion between coupon and substrate. To get a better understanding of the bonding mechanism we applied several surface characterization methods. Root mean square roughness of InP and SiO2 was measured by atomic force microscopy before and after plasma activation. The step height of the micro-transfer printed source coupon on the target wafer is estimated by optical step profiler. We used Raman peak position mappings of InP to analyze possible strain and contact angle measurements on SiO2, before and after plasma activation to observe a change in the hydrophilicity of the surface. X-ray Photoelectron Spectroscopy analysis was used to characterize the surface energy states of P2p, In3d, O1s for InP source and Si2p, O1s for SiO2 target. Our results demonstrate direct bonding of InP coupons by means of µTP without the need of a strain-compensation layer. In this way, a promising route towards Complementary Metal-Oxide-Semiconductor compatible use of µTP for the hetero-integration of InP is provided.
Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management.
Background. There are many questions regarding the peculiarities of the course of odontogenic maxillary sinusitis, the likelihood of complications and the correct dosage of load during dental implantation. Purpose – to identify changes in minimal bone density in chronic odontogenic maxillary sinusitis and to compare it with chronic rhinogenic catarrhal maxillary sinusitis and physiological state of maxillary sinus. Materials and Methods. Our study involved 10 patients with chronic odontogenic maxillary sinusitis, 10 patients with chronic maxillary non-polyposis sinusitis of rhinogenic etiology, combined with hyperplasia of the sinus mucosa up to 1 cm. The control group comprised 10 patients with physiological condition of maxillary sinuses. In all subjects minimal bone density of superior, medial and inferior walls of maxillary sinus was analyzed. Results. The study showed that the maximum in physiological conditions is the minimal density of the upper wall of the maxillary sinus, the minimum is the lower wall. The minimal density of the lower wall was shown to undergo a statistically significant reduction in chronic catarrhal maxillary sinusitis only by 2%, the upper by 5%, the medial by 4% compared with the intact sinus, but with the odontogenic nature of maxillary sinusitis, this figure was 31% in the lower wall, 27% in the medial region. Only the density of the upper wall of the maxillary sinus remained quite stable, it decreased relative to the physiological one only by 6%. Conclusions. Minimal physiological densitometric parameters of lower, medial and upper walls were calculated. The reduction of minimal density of bone tissue in the cases of rhinogenic chronic catarrhal maxillary sinusitis. In the cases of chronic odontogenic maxillary sinusitis, maximum significant decrease of minimal density of both lower and medial walls is determined.
With the growing urbanized population, vertical farming becomes indispensable in eradicating hunger and ensuring food security for the future. Food security has become a major challenge for the future owing to the scarcity of land, rising global population, urbanization, and polluted soil and water resources. In this scenario, vertical farming as an innovative food production technology caters increased productivity with limited resources and improved carbon footprint. The review begins with a brief introduction to the concept of vertical farming, its opportunities and implications on the economy, environment, and society as a whole, following with an in-depth qualitative analysis of the cutting-edge innovations/technologies are presented in detail. Contrary to the numerous research focusing on mere analysis of economic viability and statistical analysis, the aim is to introduce real cutting-edge technologies that address the challenges of vertical farms such as lack of technical skills or energy requirements. The recent advances of vertical farms includes construction of outer vertical structure and growing shelves using light weight and transparent polymer composites, engineered and tunable LEDs lightings, 3-D printed and recyclable growing substrates, AI-integrated IoTs for environment control, harvesting materials for renewable energy storage etc. Such material innovations with inclusion of AI and robotics transform automated vertical farming into ‘state of the art’ agricultural technology. Production shelf fabricated using UV cured GBOV-glass fiber composite with 60% transparency can overcome the material weight limitation, corrosion, light obstructions etc. associated with the conventional steel shelves. Replacing non-renewable fossil fuels using renewable energy harvested using carbon dots, florescent materials, and perovskite solar cells is recommended to minimize the high capital investments associated with energy as well as to reduce the environmental impact. Smart materials such as phase change materials and thermoresponsive windows control the amount of energy expended whereas smart substrate promotes resource management. Application of the newest technology AI in vertical farming facilitates precise control of environment, early pest detection, automation of farming processes, data-driven decision making and precision agriculture. In short, vertical farms utilizing modern innovations of science and technology caters enhanced productivity, improved quality, reduced cost, resource management and sustainability. Hence, automated and sustainable vertical farms promoting global food security and circularity have the potential to transform into burgeoning technology of future.
The MAC end-station at the ELI Beamlines facility is a multipurpose user's station for atomic, molecular, and optical sciences and coherent diffractive imaging. The technical design of the station, the available instruments, and an overview of the whole beamline have been published in Eur. Phys. J. Spec. Top. 230, 4183 (2021). Here, we address ongoing upgrades of the MAC end-station that will provide users with advanced capabilities for beam manipulation and electron/ion detection. The upgrades include (i) the installation of a beam preparation chamber in front of the MAC chamber, (ii) a magnetic bottle electron spectrometer with high collection and detection efficiency and high energy resolution, and (iii) an event-driven TPX3CAM detector for velocity map imaging spectrometer, which provides both spatial and temporal information for each pixel. We present results from the first commissioning measurements with these instruments, confirming their performance for state-of-the-art experiments in atomic, molecular, and optical sciences.
The application of a biocompatible polymer nanocarrier can provide target delivery to tumor tissues, improved pharmacokinetics, controlled drug release, etc. Therefore, the proposed strategy was to use the water-soluble star-like copolymers with a Dextran core and Poly(N-isopropylacrylamide) grafts (D-g-PNIPAM) for conjugation with the widely used chemotherapy drugs in oncology–Cisplatin (Cis-Pt) and Doxorubicin (Dox). The molecular characteristics of the copolymer were received using size-exclusion chromatography. The physicochemical characterization of the D-g-PNIPAM-Cis-Pt (or Dox) nanosystem was conducted using dynamic light scattering and FTIR spectroscopy. Using traditional biochemical methods, a comparative analysis of the enhancement of the cytotoxic effect of free Cis-Pt and Dox in combination with D-g-PNIPAM copolymers was performed in cancer cells of the Lewis lung carcinoma line, which are both sensitive and resistant to Dox; in addition, the mechanism of their action in vitro was evaluated.
In modern electrochemical coating technology, it is common practice to create uniform layers. However, this study focuses on the deposition of non-uniform layers achieved through a deliberate arrangement of micro structured electrodes on the anode side. The "dog bone effect” was employed as the primary approach [1]. When electroplating on an otherwise uniform surface, this effect selectively processes an area influenced by the geometric edge effect (figure 1 left). The coating within this area is intended to be (i) unevenly distributed and (ii) non-reproducible. Process data was obtained through electrochemical simulations and subsequently applied to a specially designed micro-galvanic setup. This enabled the production of suitable micro structured anodes, validation of coating parameters, and the deposition of visually imperceptible structured areas with inhomogeneous properties using "adhesive gold" on appropriate substrates such as silver and nickel. The layers and their local topography were characterized and analyzed using confocal laser microscopy, X-Ray fluorescence analysis (XRF), as well as a self-designed and constructed laser interference device. As a result, this specific galvanic process technology successfully produced metallic layers that (i) cannot be visually confirmed by the naked eye, (ii) exhibit varied microstructural anode geometries, (iii) display unique differences in layer thickness, (iv) possess non-reproducible and chaotic topographies, and (v) can be detected and identified using conventional analysis techniques or a simple interference setup.
Blood sampling as well as sample preparation are time consuming and requires a strict procedure, which is generally performed by medical trained personal. Not carrying out the procedure correctly could result in an infection of the patient or contamination of the sample itself. These limitations should be especially considered in case of pandemic outbreaks. In order to handle such a high number of patients a novel sample preparation system paired with modern blood sampling procedure is necessary. For this reason, a new device for blood sampling and preparation is designed containing an integrated microfluidic system. The fabrication is carried out by utilizing micro moulding of PDMS as well as micro milling. A first set of initial experiments as part of a first-generation study shows promising results. However, further steps of optimisation considering flow time and preparation cycle are part of a second-generation study.
The current state of technology for 3D printing with biomaterials is based on the extrusion of viscous materials. Mostly, extrusion heads utilize pneumatic pressure systems or stepper motors to force the substrate onto a surface. These methods are well developed for high viscouse materials. However, processing low viscous liquids may cause leakages in the system. This could be solved by applying continuous extrusion. Additionally, in order to process gelable substrates, such as gelatine and agar, tempered print heads in combination with a multi stage tempering system are required to prevent the system from clogging. The ongoing work presented in this paper focuses on the development of an extrusion system, which should be able to process multiple viscosities of gelatine sequentially. In order to achieve this, several measurements to examine the properties, as well as the material parameters of different biomaterials are performed. In this process gel point, force resistance and elasticity are the factors of particularly interest. Due to their ability to gel and their availability, the most relevant biomaterials are gelatine and agar. Using this data, an extrusion system involving a peristaltic pump, a heated tube and a nozzle, has been developed. The next step envisaged is to calibrate the extruder based on the obtained data and finally to validate the printing process by printing simple geometric structures. Assuming that a positive evaluation is obtained, the printing system will be tested for printing first organic test structures from patient data using the examined biomaterials.
Over the course of the last decade 3D printing has become a more established technology in terms of prototype development (rapid prototyping). The current effort is focused on transferring this knowhow into a product driven approach in order to manufacture even small batch sizes more economic. In terms of this work, this idea is adapted for the development of injection molds (rapid manufacturing). Hereby, a hardened polymer is used to create a forming cavity instead of tool-steel. In order to fulfil the mechanical process requirements of micro injection molding such as form stability under temperature and pressure this cavity is nevertheless integrated into a metal housing. A first set of experiments has been carried out using this develop mold to verify the capabilities of the developed prototype as well as molding process. Based on these first results, an optimization is carried out to improve the next iteration of this molding tool.
Processing biological materials with 3-dimensional (3D) printers has attracted increasing interest in several research areas. At the same time, off-the-shelf solutions are increasingly available in a wider variety to meet the current market demand. However, most of the available bioprinters are closed source, thus, modifications are quite challenging or require an avoidable consultation process with the manufacturer. Furthermore, the entry prices for basic machines amount to several thousands of euros. Whereas, high-end 3D bio printers with a vast array of features are available for several hundred thousand euros. Due to the immense potential of this tool in the field of biotechnology it is important to extend the availability of this technology for research purposes in terms of adaptability and price. This ongoing work focuses on open-source 3D printer heads with the ability to extrude biological materials. The print heads include several techniques to process low as well as high viscose biomaterials such as agar and gelatin. Additionally, obstacles such as continuous substrate tempering or integration into existing 3D printers are addressed. The work presented is open source and thus freely adaptable to any user’s specific needs. Our goal is to process a diverse range of biomaterials with different print techniques.
The novel approach of an individualized medicine affects nowadays various areas of therapeutic treatment. Primarily, these include the application of pharmaceuticals, private point-of-care solutions, surgical procedures as well as steps of rehabilitation. However, beside these existing strategies the development of patient specific models for the training of clinical personal is currently insufficient. Such models are essential to prepare a personalized approach of medical care. One possible solution to address this problem could be the adaption of the established 3d printing technology for the processing of suitable biopolymers. The presented work is focused on the development of a printing system utilizing collagen. Therefore, it is intended to design multiple extrusion heads in accordance with the material parameters. In order to achieve the aspired physiological properties of the final model, a first set of experiments will be performed with several compositions of collagen to validate the fundamental mechanical characteristics. Hereby, the elasticity, thermal stability, force resistance as well as the haptic behaviour are of most interest. Afterwards, these obtained experimental results should be used to simulate the extrusion process and to validate the extruder concepts. In case of a positive evaluation these concepts are realized by using rapid prototyping technologies. Finally, this novel 3d printer will be used to print first organic test structures with collagen.
The object of the study is the process of identifying the state of a computer network. The subject of the study are the methods of identifying the state of computer networks. The purpose of the paper is to improve the efficacy of intrusion detection in computer networks by developing a method based on transformer models. The results obtained. The work analyzes traditional machine learning algorithms, deep learning methods and considers the advantages of using transformer models. A method for detecting intrusions in computer networks is proposed. This method differs from known approaches by utilizing the Vision Transformer for Small-size Datasets (ViTSD) deep learning algorithm. The method incorporates procedures to reduce the correlation of input data and transform data into a specific format required for model operations. The developed methods are implemented using Python and the GOOGLE COLAB cloud service with Jupyter Notebook. Conclusions. Experiments confirmed the efficiency of the proposed method. The use of the developed method based on the ViTSD algorithm and the data preprocessing procedure increases the model's accuracy to 98.7%. This makes it possible to recommend it for practical use, in order to improve the accuracy of identifying the state of a computer system.
The sample preparation for biological and chemical probes involves following a strict workflow to eliminate any contamination to the sample beforehand. Furthermore, it is time consuming and must be carried out by trained personnel such as a nurse or other supervisors, making it therefore expensive. The development of novel sample preparation techniques paired with modern sample analysis systems is focused on improving the operability while keeping a constant quality of results. This is important to analyse samples, which cannot be determined with current screening conditions. The analysis of analytes is required to receive a more detailed picture of the patient and to fully understand its complexity. Possible samples for in-depth analysis of chemical origin can be cholesterol or glucose. More complex samples, such as blood or saliva, require a sophisticated system, which analyses the samples for their individual compounds.
In-vitro cell culture offers the ability to grow individual cells and monitor their behaviour in a controlled environment over a certain time. During culture, different parameters have to be controlled to ensure a vital growth of cells. The most important parameters are temperature, pH-value, oxygen and carbon dioxide levels as well as the glucose concentration. All of these parameters influence the growth ability of the cell culture and should be monitored online. The online monitoring of glucose was achieved with a novel GOD based sensor which enabled a real-time measurement of glucose during cell culture. A first-time characterisation of the sensor was carried out in the culture medium DMEM. In addition, material properties of the culture system were investigated. At first to establish a baseline measurement, the sensor was placed in different glucose concentrations dissolved in Water-KCl mixture at 25 °C inside a batch chamber under constant stirring. Afterwards, the temperature was increased to 37 °C to simulate a cell culture environment. In addition, the system was transferred into a flow-through reaction chamber. The highest response signal and the most stable signal was achieved at 37 °C with DMEM during flow-through measurement. Based on these measurements online glucose monitoring in cell culture was possible to determine the glucose consumption for each cell which is important for future human-on-a-chip devices to prevent diabetic metabolisms.
Modern medical science delivers through innovative chemical or mechanical/physical means new strategies to treat patients mildly and fight diseases accurately. In line with this development a screening procedure for tissue samples under usage of the electronic speckle pattern interferometry is developed at the University of Applied Science Wildau. The paper at hand provides the corner stone for such a procedure in form of an incubation system that is adapted to the properties of an electronic speckle pattern interferometer and allows the incubation as well as study of samples over time. As a result the developed system can regulate its own temperature and is constructed for use in an electronic speckle pattern interferometry (ESPI) setup. Its design allows a simple modular approach for further development.
3 dimensional (3D) printing evolved during the last decade to a consumer friendly and affordable craft. Furthermore, implementations of this techniques in the field of biotechnological research and development within laboratories is a very expansive process. Bio-printers’ prices cover a wide spectrum and most basic models are available for around 5000€. On the other end, high-end printer machines with a vast variety of features are available for several hundreds of thousands of euros. Thus, due to the immense potential in the field of Biotechnology the availability of this technology for research purpose should be enhanced. A developed ecological syringe extruder prototype for processing of biological based gels has been further improved. The original prototype was capable to processing multiple layers of agar with concentrations of 1% and 2.5%. Based on these results the prototype was revised regarding printing process parameter, which include among others applied forces to the substrate, air-ventilation, and heating of the substrate. The process behavior will be simulated with computational fluid dynamics for the processing of biological based substrate. After a concluding validation these results are intended to be implemented into a new design for improved processing of a variety of bioinks.
Bioreactor systems for cultivating cells in Life Sciences have been widely used for decades. Recently, there is a trend towards miniaturization, disposables and even micro platforms that fulfill increasing demands strongly aiming for production and testing of novel pharmaceutical products. Miniaturized bioreactors allow low power consumption, portability and reduced space requirements and utilize smaller volumes of reagents and samples [1,2]. A recursive strategy is necessary for optimizing the design and the manufacture of such miniaturized bioreactors. For the fabrication of these prototypes utilized micro-milling. Micro milling is a mechanical process which is commonly applied to create micro-structures in metals, e.g. aluminum and steel, or polymers, e.g. poly carbonate substrates. The structures and geometries are generated by utilizing computer aided design. By means of computer-aided manufacturing, the machining operations are implemented and then transferred to the machine tool. The machine tool moves the cutting tools with certain speeds, feeds and traverse ranges to the substrate. Micro milling has the advantage that the materials are generally not degraded by chemical substances, heating procedures or electromagnetic radiation.
Development of a Smartphone Based Reader for the Quantitative Analysis of Lateral Flow Assays
(2018)
Smartphones are developing into all-purposes devices. In the present work, the employment/application of smartphones as medical devices in home care and point-of-care (POC) diagnostics are investigated in the analysis of Lateral Flow Assays (LFA). A smartphone-based LFA reader was developed for the quantitative analysis of D-Dimer – a biomarker indicating e.g. thrombotic event or danger of embolism.The proof-of-concept has been shown with multiple smartphones in establishing: (I) Optimal dimensions of the LFA cell of 72.11mm distance of smartphone to D-Dimer test leading to a coefficients of variances (CV) between 0.8% and 4.2%. (II) Inter-device investigations: CVs around 13.5%; a limit of detection (LOD) of 100ng/ml (DDU) D-Dimer. (III) Inter-smartphone investigations: CV about 16%, a limit of detection (LOD) at 66.4ng/ml (DDU). (IV) Calibrations: CV and LOD of three smartphones are comparable to the commercial available LFA reader. Further development to put the multiple smartphone-based LFA reader on the market.
Modern cell culture as well as sophisticated bio-applications involve complex biochemical processes, which are required to induce growth, product development or material degradation. Tracking the reaction processes inside the application presents a major challenge due to its complexity. The development of new analysis and tracking mechanisms for such application presents a solution to fully understand the process. In addition, the applied sensors are required to monitor the reactions enable a live tracking of the process. Furthermore, this gives the opportunity to influence and manipulate reactions to further enhance the application of the process. Possible analytes for tracking during processes can be chemical origin such as glucose, cytokines, antibiotics and growth factors, which are included in the culture medium. Based on the complexity of the culture or bio-application the sensor tracking mechanism has to be adapted to ensure full process control. A variety of different approaches can be used for the tracking mechanism.
Synthetic substances like many pharmaceuticals, preservatives or other chemical compounds are actually very difficult to handle in sewage treatment. These compounds are very stable in aqueous solution and their degradation reactions are insufficient. Therefore, to eliminate these substances from wastewater additional afford is necessary. Extreme conditions like pH value, redox potential, chemical or physical energy need to be present. With our study we try to show that the use of plasma discharge could be a solution to this problem. Using the example of methylparaben, a preservative, we could show, that the physical energy of plasma discharge is able to initialize the degradation reaction in aqueous environment. The concentration was reduced by up to 70 percent in our setting depending on the treatment duration. Overall, the system showed potential to optimize wastewater treatment. Further examinations are necessary for example regarding undesirable by-products.
Heavy wire bonding is one of the most common interconnection technologies in manufacturing of high-power electronics. For industrial applications, the long-term reliability of these connections is crucial. Besides the selection of the wire material and the loop geometry itself, the loop forming process parameters also have an influence on the reliability of the wire bond. In this work, the influence of the backward bond head movement during wire bonding process on the quality of wire bond connections was systematically investigated and qualified by cyclic mechanical lifetime tests, surface roughness measurements of the heel area by laser confocal microscopy and static pull tests. The wire bond loops were fabricated with 300 μm aluminum H11 and H14CR wires with different hardness values. The lifetime at low frequency cycle and high frequency cycle regime was determined by means of two different mechanical cyclic test methods operating at 5 Hz and at 60 kHz respectively. The results have shown, that the surface topology of the heel region caused by the initial plastic deformation during the loop forming process has a significant effect on the wire bond failure due to heel cracking. The number of loading cycles to failure shows an inverse correlation with the degree of surface roughness in a so called wrinkling analysis in the low and high frequency cycle regime. The soft wire exhibits different lifetimes compared to the hard ones depending on the testing conditions, while a significant decrease of the lifetime is observed with >30 % reverse movement during bonding in all cases.
The rise of Fe magnetic moment, changes in Al electronic structure and a variation of Al magnetic polarization in thin films of transition metal aluminide Fe60Al40 have been probed through the order-disorder phase transition by soft X-ray absorption spectroscopy and X-ray resonant magnetic reflectivity in the extreme ultraviolet regime. In a course of the transition induced by 20 keV Ne+ irradiation with low fluences (1014 ions·cm-2), X-ray magnetic circular dichroism spectra taken at the Fe L2,3 absorption edges at room and low temperatures revealed a pronounced increase of Fe 3d states spin-polarization. X-ray resonant magnetic reflectivity applied to the Al L2,3 and Fe M2,3 edges allowed to detect the magnetic polarization of Al atoms in the films. The changes in Al electronic structure have been seen by alteration of Al K edge X-ray absorption near edge structure. A difference in anisotropy fields for films before and after irradiation has been observed by element-specific hysteresis loops recorded at low temperatures in absorption and reflection geometries at the Fe L2,3 and M2,3 edges, respectively. An attempt to reduce the top oxide layer by an inductively coupled hydrogen plasma has shown a possibility to recover the chemically ordered phase.
Ultrafast electron dynamics drive phenomena such as photochemical reactions, catalysis, and light harvesting. To capture such dynamics in real-time, femtosecond to attosecond light sources are extensively used. However, an exact match between the excitation photon energy and a characteristic resonance is crucial. High-harmonic generation sources are advantageous in terms of pulse duration but limited in spectral tunability in the vacuum ultraviolet range. Here, we present a monochromatic femtosecond source continuously tunable around 21eV photon energy utilizing the second harmonic of an optical parametric chirped pulse amplification laser system to drive high-harmonic generation. The unique tunability of the source is verified in an experiment probing the interatomic Coulombic decay in doped He nanodroplets across the He absorption bands. Moreover, we achieved intensities sufficient for driving collective processes in multiply excited helium nanodroplets, which have been previously observed only at free electron lasers.
The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This rapid development with a constant need for new developments and integration of new features require efforts into compile, catalog and classify these tools to create infrastructures and services with easy, transparent, and trustable standards. Here we review the state-of-the-art for ML tools applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities. This scoping review focuses on ML based software and framework resources currently available for the analysis of microbiome data in humans. The aim is to support microbiologists and biomedical scientists to go deeper into specialized resources that integrate ML techniques and facilitate future benchmarking to create standards for the analysis of microbiome data. The software resources are organized based on the type of analysis they were developed for and the ML techniques they implement. A description of each software with examples of usage is provided including comments about pitfalls and lacks in the usage of software based on ML methods in relation to microbiome data that need to be considered by developers and users. This review represents an extensive compilation to date, offering valuable insights and guidance for researchers interested in leveraging ML approaches for microbiome analysis.
Das ASTONRail-Handbook ist eine webbasierte, interaktive Informationssammlung für künftige Nachwuchskräfte der Eisenbahnbranche und Lehrende in der eisenbahnrelevanten Hochschulbildung. Es soll u.a. die Suche nach passenden Studienmöglichkeiten erleichtern und Anregungen für eine modernere Hochschulbildung im Eisenbahnsektor bieten. Es ist einfach zu bedienen und um weitere Funktionen erweiterbar.
Patients with congenital heart defects and cardiovascular diseases are required new approaches to surgical intervention. The use of biological cardiac implants, which are made from the extracellular matrix, is a promising trend in modern regenerative medicine. These bioimplants can completely replace defective tissue or organs, and when manufactured with strict protocols and quality control measures, can be safe and effective for therapeutic applications. The process of manufacturing bioimplants involves various risks that need to be assessed and mitigated with ongoing monitoring and evaluation necessary to ensure the highest standards of quality. Overall, this study was successfully evaluated the requirements for introducing a new medical device into practice and created a technical file that meets all necessary documentation for certification.
Cancer sonodynamic therapy (SDT) is the therapeutic strategy of a high-frequency ultrasound (US) combined with a special sonosensitizer that becomes cytotoxic upon US exposure. The growing number of newly discovered sonosensitizers and custom US in vitro treatment solutions push the SDT field into a need for systemic studies and reproducible in vitro experimental set-ups. In the current research, we aimed to compare two of the most used and suitable SDT in vitro set-ups—“sealed well” and “transducer in well”—in one systematic study. We assessed US pressure, intensity, and temperature distribution in wells under US irradiation. Treatment efficacy was evaluated for both set-ups towards cancer cell lines of different origins, treated with two promising sonosensitizer candidates—carbon nanoparticle C60 fullerene (C60) and herbal alkaloid berberine. C60 was found to exhibit higher sonotoxicity toward cancer cells than berberine. The higher efficacy of sonodynamic treatment with a “transducer in well” set-up than a “sealed well” set-up underlined its promising application for SDT in vitro studies. The “transducer in well” set-up is recommended for in vitro US treatment investigations based on its US-field homogeneity and pronounced cellular effects. Moreover, SDT with C60 and berberine could be exploited as a promising combinative approach for cancer treatment.
Ellipsometrically obtained spectral dependences of ordinary αxy and extra-ordinary αz extinction/attenuation coefficients within the spectral range λ = 300…980 nm of uniaxially anisotropic polytetrafluoroethylene (PTFE) films were analyzed. We considered the capabilities and specific features of the graphical representation technique for determining the contribution of Rayleigh scattering and Urbach absorption to light attenuation in the spectral range beyond fundamental absorption. It has been shown that the graphical approach enables to estimate these contributions qualitatively, semi-quantitatively or quantitatively, depending on the situation. The conclusions made using the analysis of graphical representation are confirmed by numerical solution of the inverse problem via simulation of the αxy (λ), αz (λ) experimental dependences within the framework of a best-fit procedure. Being based on both of these approaches, we have ascertained that, in the as-prepared PTFE films, the so-called anomalous light scattering (ALS) with the spectral dependence of scattering coefficient αs ≈ as λ–p (p > 4) takes place. Transformation of scattering from ALS to the Rayleigh one with p ≈ 4 due to annealing is accompanied by an increase of Urbach (subband) absorption. Both of these factors cause narrowing the dynamic range of extinction coefficient values. Both scattering and absorption coefficients are higher for the component of light polarized along the normal to the substrate as compared to the component polarized in parallel to it. The relationship between observed behavior of the scattering and absorption coefficients and the film structure has been discussed.
Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action
(2023)
The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.
Photoacoustic imaging through skull bone causes strong attenuation and distortion of the acoustic wavefront, which diminishes image contrast and resolution. As a result, transcranial photoacoustic measurements in humans have been challenging to demonstrate. In this study, we investigated the acoustic transmission through the human skull to design an ultrasound sensor suitable for transcranial PA imaging and sensing. We measured the frequency dependent losses of human cranial bones ex vivo, compared the performance of a range of piezoelectric and optical ultrasound sensors, and imaged skull phantoms using a PA tomograph based on a planar Fabry–Perot sensor. All transcranial photoacoustic measurements show the typical effects of frequency and thickness dependent attenuation and aberration associated with acoustic propagation through bone. The performance of plano-concave optical resonator ultrasound sensors was found to be highly suitable for transcranial photoacoustic measurements.
Background and objective: Accurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.
Patients and methods: FOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.
Results: In total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.
Conclusions: With the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician.
Background
Diabetes mellitus type 2 is a common disease that poses a challenge to the healthcare system. The disease is very often diagnosed late. A better understanding of the relationship between the gut microbiome and type 2 diabetes can support early detection and form an approach for therapies. Microbiome analysis offers a potential opportunity to find markers for this disease. Next-generation sequencing methods can be used to identify the bacteria present in the stool sample and to generate a microbiome profile through an analysis pipeline. Statistical analysis, e.g., using Student’s t-test, allows the identification of significant differences. The investigations are not only focused on single bacteria, but on the determination of a comprehensive profile. Also, the consideration of the functional microbiome is included in the analyses. The dataset is not from a clinical survey, but very extensive.
Results
By examining 946 microbiome profiles of diabetes mellitus type 2 sufferers (272) and healthy control persons (674), a large number of significant genera (25) are revealed. It is possible to identify a large profile for type 2 diabetes disease. Furthermore, it is shown that the diversity of bacteria per taxonomic level in the group of persons with diabetes mellitus type 2 is significantly reduced compared to a healthy control group. In addition, six pathways are determined to be significant for type 2 diabetes describing the fermentation to butyrate. These parameters tend to have high potential for disease detection.
Conclusions
With this investigation of the gut microbiome of persons with diabetes type 2 disease, we present significant bacteria and pathways characteristic of this disease.
The identification of biomarkers is crucial for cancer diagnosis, understanding the underlying biological mechanisms, and developing targeted therapies. In this study, we propose a machine learning approach to predict ovarian cancer patients’ outcomes and platinum resistance status using publicly available gene expression data. Six classical machine-learning algorithms are compared on their predictive performance. Those with the highest score are analyzed by their feature importance using the SHAP algorithm. We were able to select multiple genes that correlated with the outcome and platinum resistance status of the patients and validated those using Kaplan–Meier plots. In comparison to similar approaches, the performance of the models was higher, and different genes using feature importance analysis were identified. The most promising identified genes that could be used as biomarkers are TMEFF2, ACSM3, SLC4A1, and ALDH4A1.
We study the dynamics of avalanche ionization of pure helium nanodroplets activated by a weak extreme-ultraviolet (XUV) pulse and driven by an intense near-infrared (NIR) pulse. In addition to a transient enhancement of ignition of a nanoplasma at short delay times ${\sim}200$ fs, long-term activation of the nanodroplets lasting up to a few nanoseconds is observed. Molecular dynamics simulations suggest that the short-term activation is caused by the injection of seed electrons into the droplets by XUV photoemission. Long-term activation appears due to electrons remaining loosely bound to photoions which form stable 'snowball' structures in the droplets. Thus, we show that XUV irradiation can induce long-lasting changes of the strong-field optical properties of nanoparticles, potentially opening new routes to controlling avalanche-ionization phenomena in nanostructures and condensed-phase systems.
Plasma-enhanced atomic layer deposition of silicon nitride for front-end-of-line applications
(2023)
SiN deposition at low temperatures using the plasma-enhanced atomic layer deposition (PEALD) process is gaining momentum. A high-quality SiN layer deposited using a lower thermal budget and low wet etch rates are desired for front-end-of-line applications in semiconductor industries. In this study, deposition of PEALD SiN is investigated by utilizing a highly reactive trisilylamine silicon precursor and three different reaction partners for a nitrogen precursor. The quality of PEALD SiN layers is compared with the reference standard, low-pressure chemical vapor deposition SiN layers. The properties of different SiN layers are interpreted using FTIR and XPS material characterization techniques. Furthermore, the wet etch rates of as-deposited and annealed PEALD SiN layers are investigated. Finally, the conformality of PEALD SiN layers is assessed in trench and horizontal high aspect ratio structures.
Thin polytetrafluoroethylene (PTFE) films are produced by deposition from a gas phase by two methods: electron-enhanced vacuum deposition (EVD) and EVD + low-temperature plasma (LTP). Structure, morphology, and composition of the films are studied by IR spectroscopy, atomic force microscopy, and X-ray photoelectron spectroscopy. They are close to the structure of bulk PTFE. The roughness of the films’ surface is changed with gas pressure and LTP power variations. Films are transparent from UV to near-infrared regions. Refractive and extinction indices and their anisotropy are measured by spectral ellipsometry. They are tuned by variations of deposition conditions. Hardness and Young modulus of the films are increased if EVD + low power LTP is used for film deposition. Use of EVD + LTP also increases thermal stability of the films. Contact angle of the films corresponds to the bulk PTFE. The PTFE molecules oriented are preferentially in perpendicular direction to the substrate surface.
Awareness about climate change has led to policies and regulations but also customer preferences favoring sustainable production. Thus, producing businesses are confronted by this, as they consume a large share of resources. Therefore, when producing, additional dimensions beyond commercial feasibility ought to be considered. Here, literature on sustainability from the field of engineering science is systematically searched and analyzed for approaches leading to actual recommendations for action. Hence, this bottom-up approach, incorporating the production engineers’ point of view, represents an inside view of how the topic of sustainability has arrived at production companies. The focus on commercial feasibility ensures high relevance to practice, as production needs to become both sustainable and competitive. Even though exemplary collections of different approaches addressing the topic of sustainability in production can be found in literature, novelty is provided by the structured manner literature was collected and the special focus on approaches leading to practice-relevant recommendations for action. Thus, a comprehensive overview of approaches applicable to the manufacturing domain is presented.
Background
Type 2 diabetes mellitus is a prevalent disease that contributes to the development of various health issues, including kidney failure and strokes. As a result, it poses a significant challenge to the worldwide healthcare system. Research into the gut microbiome has enabled the identification and description of various diseases, with bacterial pathways playing a critical role in this context. These pathways link individual bacteria based on their biological functions. This study deals with the classification of microbiome pathway profiles of type 2 diabetes mellitus patients.
Methods
Pathway profiles were determined by next-generation sequencing of 16S rDNA from stool samples, which were subsequently assigned to bacteria. Then, the involved pathways were assigned by the identified gene families. The classification of type 2 diabetes mellitus is enabled by a constructed neural network. Furthermore, a feature importance analysis was performed via a game theoretic approach (SHapley Additive exPlanations). The study not only focuses on the classification using neural networks, but also on identifying crucial bacterial pathways.
Results
It could be shown that a neural network classification of type 2 diabetes mellitus and a healthy comparison group is possible with an excellent prediction accuracy. It was possible to create a ranking to identify the pathways that have a high impact on the model prediction accuracy. In this way, new associations between the alteration of, e.g. a biosynthetic pathway and the presence of diabetes mellitus type 2 disease can also be discovered. The basis is formed by 946 microbiome pathway profiles from diabetes mellitus type 2 patients (272) and healthy comparison persons (674).
Conclusion
With this study of the gut microbiome, we present an approach using a neural network to obtain a classification of healthy and type 2 diabetes mellitus and to identify the critical features. Intestinal bacteria pathway profiles form the basis.
The assessment of dietary carotenoids via blood measurements has been widely used as a marker for fruit and vegetable consumption. In the present study, modern, non-invasive approaches to assess dietary carotenoids, such as skin measurements and an app-based short dietary record (ASDR), were compared with conventional methods such as plasma status and handwritten 3-day dietary records. In an 8-week observational study, 21 healthy participants aged 50–65 years recorded their daily consumption of carotenoid-rich fruits and vegetables via a specially developed ASDR. Anthropometry, blood samplings and assessment of skin carotenoids via Raman and reflection spectroscopy were performed at baseline, after four weeks and at the end of the study. App-based intake data showed good correlations with plasma α-carotene (r = 0.74, p < 0.0001), β-carotene (r = 0.71, p < 0.0001), and total plasma carotenoids (r = 0.65, p < 0.0001); weak correlations with plasma lutein/zeaxanthin and β-cryptoxanthin (both r = 0.34, p < 0.05); and no correlation with plasma lycopene. Skin measurements via reflection and Raman spectroscopy correlated well with total plasma carotenoids (r = 0.81 and 0.72, respectively; both p < 0.0001), α-carotene (r = 0.75–0.62, p < 0.0001), and β-carotene (r = 0.79–0.71, p < 0.0001); moderately with plasma lutein/zeaxanthin (both r = 0.51, p < 0.0001); weakly with plasma β-cryptoxanthin (r = 0.40–0.31, p < 0.05); and showed no correlation with plasma lycopene. Skin measurements could provide a more convenient and noninvasive approach of estimating a person’s fruit and vegetable consumption compared to traditional methods, especially in studies that do not intend blood sampling. ASDR records might function as a suitable, convenient tool for dietary assessment in nutritional intervention studies.
Microbiomic analysis of human gut samples is a beneficial tool to examine the general well-being and various health conditions. The balance of the intestinal flora is important to prevent chronic gut infections and adiposity, as well as pathological alterations connected to various diseases. The evaluation of microbiome data based on next-generation sequencing (NGS) is complex and their interpretation is often challenging and can be ambiguous. Therefore, we developed an innovative approach for the examination and classification of microbiomic data into healthy and diseased by visualizing the data as a radial heatmap in order to apply deep learning (DL) image classification. The differentiation between 674 healthy and 272 type 2 diabetes mellitus (T2D) samples was chosen as a proof of concept. The residual network with 50 layers (ResNet-50) image classification model was trained and optimized, providing discrimination with 96% accuracy. Samples from healthy persons were detected with a specificity of 97% and those from T2D individuals with a sensitivity of 92%. Image classification using DL of NGS microbiome data enables precise discrimination between healthy and diabetic individuals. In the future, this tool could enable classification of different diseases and imbalances of the gut microbiome and their causative genera.
The share of chronic odontogenic rhinosinusitis is 40% among all chronic rhinosinusitis. Using automated information systems for differential diagnosis will improve the efficiency of decision-making by doctors in diagnosing chronic odontogenic rhinosinusitis. Therefore, this study aimed to develop an intelligent decision support system for the differential diagnosis of chronic odontogenic rhinosinusitis based on computer vision methods. A dataset was collected and processed, including 162 MSCT images. A deep learning model for image segmentation was developed. A 23 convolutional layer U-Net network architecture has been used for the segmentation of multi-spiral computed tomography (MSCT) data with odontogenic maxillary sinusitis. The proposed model is implemented in such a way that each pair of repeated 3 × 3 convolutions layers is followed by an Exponential Linear Unit instead of a Rectified Linear Unit as an activation function. The model showed an accuracy of 90.09%. To develop a decision support system, an intelligent chatbot allows the user to conduct an automated patient survey and collect patient examination data from several doctors of various profiles. The intelligent information system proposed in this study made it possible to combine an image processing model with a patient interview and examination data, improving physician decision-making efficiency in the differential diagnosis of Chronic Odontogenic Rhinosinusitis. The proposed solution is the first comprehensive solution in this area.
Refrigeration applications consume a significant share of total electricity demand, with a high indirect impact on global warming through greenhouse gas emissions. Modern technology can help reduce the high power consumption and optimize the cooling control. This paper presents a case study of machine-learning for controlling a commercial refrigeration system. In particular, an approach to reinforcement learning is implemented, trained and validated utilizing a model of a real chiller plant. The reinforcement-learning controller learns to operate the plant based on its interactions with the modeled environment. The validation demonstrates the functionality of the approach, saving around 7% of the energy demand of the reference control. Limitations of the approach were identified in the discretization of the real environment and further model-based simplifications and should be addressed in future research.
Extensive pastoral livestock systems in Central Europe provide multiple ecosystem services and support biodiversity in agricultural landscapes but their viability is challenged by livestock depredation (LD) associated with the recovery of wolf populations. Variation in the spatial distribution of LD depends on a suite of factors, most of which are unavailable at the appropriate scales. To assess if LD patterns can be predicted sufficiently with land use data alone at the scale of one federal state in Germany, we employed a machine-learning-supported resource selection approach. The model used LD monitoring data, and publicly available land use data to describe the landscape configuration at LD and control sites (resolution 4 km * 4 km). We used SHapley Additive exPlanations to assess the importance and effects of landscape configuration and cross-validation to evaluate the model performance. Our model predicted the spatial distribution of LD events with a mean accuracy of 74%. The most influential land use features included grassland, farmland and forest. The risk of livestock depredation was high if these three landscape features co-occurred with a specific proportion. A high share of grassland, combined with a moderate proportion of forest and farmland, increased LD risk. We then used the model to predict the LD risk in five regions; the resulting risk maps showed high congruence with observed LD events. While of correlative nature and lacking specific information on wolf and livestock distribution and husbandry practices, our pragmatic modelling approach can guide spatial prioritisation of damage prevention or mitigation practices to improve livestock-wolf coexistence in agricultural landscapes.
One restriction for biohybrid photovoltaics is the limited conversion of green light by most natural photoactive components. The present study aims to fill the green gap of photosystem I (PSI) with covalently linked fluorophores, ATTO 590 and ATTO 532. Photobiocathodes are prepared by combining a 20 μm thick 3D indium tin oxide (ITO) structure with these constructs to enhance the photocurrent density compared to setups based on native PSI. To this end, two electron transfer mechanisms, with and without a mediator, are studied to evaluate differences in the behavior of the constructs. Wavelength-dependent measurements confirm the influence of the additional fluorophores on the photocurrent. The performance is significantly increased for all modifications compared to native PSI when cytochrome c is present as a redox-mediator. The photocurrent almost doubles from −32.5 to up to −60.9 μA cm−2. For mediator-less photobiocathodes, interestingly, drastic differences appear between the constructs made with various dyes. While the turnover frequency (TOF) is doubled to 10 e−/PSI/s for PSI-ATTO590 on the 3D ITO compared to the reference specimen, the photocurrents are slightly smaller since the PSI-ATTO590 coverage is low. In contrast, the PSI-ATTO532 construct performs exceptionally well. The TOF increases to 31 e−/PSI/s, and a photocurrent of −47.0 μA cm−2 is obtained. This current is a factor of 6 better than the reference made with native PSI in direct electron transfer mode and sets a new record for mediator-free photobioelectrodes combining 3D electrode structures and light-converting biocomponents.
Dislocation free local SiGe-on-insulator (SGOI) virtual substrate is fabricated using lateral selective SiGe growth by reduced pressure chemical vapor deposition. The lateral selective SiGe growth is performed around a ∼1.25 μm square Si (001) pillar in a cavity formed by HCl vapor phase etching of Si at 850 °C from side of SiO2/Si mesa structure on buried oxide. Smooth root mean square roughness of SiGe surface of 0.14 nm, which is determined by interface roughness between the sacrificially etched Si and the SiO2 cap, is obtained. Uniform Ge content of ∼40% in the laterally grown SiGe is observed. In the Si pillar, tensile strain of ∼0.65% is found which could be due to thermal expansion difference between SiO2 and Si. In the SiGe, tensile strain of ∼1.4% along 〈010〉 direction, which is higher compared to that along 〈110〉 direction, is observed. The tensile strain is induced from both [110] and [−110] directions. Threading dislocations in the SiGe are located only ∼400 nm from Si pillar and stacking faults are running towards 〈110〉 directions, resulting in the formation of a wide dislocation-free area in SiGe along 〈010〉 due to horizontal aspect ratio trapping.
We have investigated the possibility to track and control correlation dynamics of valence electrons in krypton (Kr) initiated by the absorption of one extreme ultraviolet (XUV) photon. In this investigation, pump-probe experiments have been performed where monochromatized single high-harmonics at photon energies 29.6, 32.8, and 35.9 eV have been used as pump to populate different intermediate excited states. A temporally delayed near-infrared (NIR) pulse probes the population of various decay channels via the detection of Kr²⁺ ion yields and its transient profiles. We observe that by varying the NIR pulse intensity within a range from 0.3 x 10¹³ to 2.6 x 10¹³ W cm⁻², the shape of the Kr²+ transient profile changes significantly. We show that by varying the intensity of the NIR pulse, it is possible—(i) to control the ratio between sequential and non-sequential double ionization of Kr; (ii) to selectively probe quantum beating oscillations between Kr+* satellite states that are coherently excited within the bandwidth of the XUV pulse; and (iii) to specifically probe the relaxation dynamics of doubly excited (Kr**) decay channels. Our studies show that the contribution of different ionization and decay channels (i)–(iii) can be altered by the NIR pulse intensity, thus demonstrating an efficient way to control the ionization dynamics in rare gas atoms.
The use of explosives has led to a widespread distribution of 2,4,6-trinitrotoluene (TNT) and its by- and degradation products in the soil on former production and testing sites. The investigation of those large contaminated sites is so far based on a few selected soil samples, due to high costs of conventional HPLC and GC analysis, although huge differences in concentrations can already be found in small areas and different collection depths. We introduce a novel high-throughput screening system for those areas, which combines a smartphone-based collection of GPS data and soil characteristics with a fast MALDI-TOF MS quantification of explosives in soil sample extracts and finally a heatmap visualization of the explosives’ spread in soil and an analysis of correlation between concentrations and soil characteristics. The analysis of a 400 m2 area presented an extensive contamination with TNT and lower concentrations of the degradation and by-products aminodinitrotoluenes (ADNT) and dinitrotoluenes (DNT) next to a former production facility for TNT. The contamination decreased in deeper soil levels and depended on the soil type. Pure humus samples showed significantly lower contaminations compared to sand and humus/sand mixtures, which is likely to be caused by an increased binding potential of the humic material. No correlation was found between the vegetation and the concentration of explosives. Since the results were obtained and visualized within several hours, the MALDI-TOF MS based comprehensive screening and heatmap analysis might be valuable for a fast and high-throughput characterization of contaminated areas.
The acoustic pressure waves of ultrasound (US) not only penetrate biological tissues deeper than light, but they also generate light emission, termed sonoluminescence. This promoted the idea of its use as an alternative energy source for photosensitizer excitation. Pristine C60 fullerene (C60), an excellent photosensitizer, was explored in the frame of cancer sonodynamic therapy (SDT). For that purpose, we analyzed C60 effects on human cervix carcinoma HeLa cells in combination with a low-intensity US treatment. The time-dependent accumulation of C60 in HeLa cells reached its maximum at 24 h (800 ± 66 ng/106 cells). Half of extranuclear C60 is localized within mitochondria. The efficiency of the C60 nanostructure’s sonoexcitation with 1 MHz US was tested with cell-based assays. A significant proapoptotic sonotoxic effect of C60 was found for HeLa cells. C60′s ability to induce apoptosis of carcinoma cells after sonoexcitation with US provides a promising novel approach for cancer treatment.
This study aimed to evaluate the probiotic strain Lacticaseibacillus (L.) paracasei subsp. paracasei F19 (F19) with the yeast Saccharomyces cerevisiae US-05 (US-05), using Spondias mombin L. (‘taperebá’ or ‘cajá’) juice and by-product, in four sour-type beer formulations: control, with bagasse, juice, and juice and bagasse. The viability of F19 was evaluated by pour-plating and PMA-qPCR. Fermentability, in addition to physicochemical and sensory parameters, and aroma and flavor, were evaluated during brewery by using Headspace Solid-Phase Microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC–MS). F19 was successful in fermenting bagasse in a MRS medium (9.28 log CFU/mL in 24 h) but had a low viability in hopped wort, growing better in formulations without bagasse or juice. No difference between formulations was observed regarding sensory acceptability, and the HS-SPME/GC-MS revealed different flavors and aroma compounds. In conclusion, the production of a potential probiotic sour beer with F19 and US-05 is feasible regarding probiotic viability. However, S. mombin, as juice or bagasse, threatened probiotic survival. Different flavors and aroma compounds were detected, whereas no difference between formulations was found regarding sensory acceptability. The moderate alcohol content achieved is important for bacterial survival and for the development of a probiotic beer with health claims.
Facing an inexorable growth of the human population along with substantial environmental changes, the assurance of food security is a major challenge of the present century. To ensure responsible food consumption and production (SDG 12), new approaches in the food system are required. Thus, environmentally controlled, sustainable production of alternative food sources are of key interest for both urban agriculture and food research. To face the current challenge of integrating food production systems within existing structures, multidisciplinary discourses are required. Here, we bring together novel technologies and indoor farming techniques with the aim of supporting the development of sustainable food production systems. For this purpose, we investigated the feasibility of 10 composite materials for their innovative use as structural support in macroalgal cultivation (settlement substrates) and cricket rearing (housing). Considering material resistance, rigidity, and direct material-organism interactions, the bio-based composite polylactic acid (PLA) was identified as a suitable material for joint farming. For macroalgae cultivation, PLA sustained the corrosive cultivation conditions and provided a suitable substrate without affecting the macroalgal physiology or nutritional composition (carotenoids and chlorophylls). For cricket rearing, PLA provided a suitable and recyclable shelter, which was quickly accepted by the animals without any observed harm. In contrast, other common composite components like phenolic resin or aramid were found to be unsuitable due to being harmful for the cultivated organisms or instable toward the applied sterilization procedure. This multidisciplinary study not only provides profound insights in the developing field of urban indoor food production from a new perspective, but also bridges material science and farming approaches to develop new sustainable and resilient food production systems.
Bio-inorganic hybrid structures for direct electron transfer to photosystem I in photobioelectrodes
(2022)
Synthetic materials can be combined with biological components in many ways. One example that provides scientists with multiple challenges is a photobioelectrode that converts sunlight into electrons in a biohybrid approach. In the present study several key parameters are evaluated concerning their influence on the direct electron transfer from a 3D indium tin oxide (ITO) electrode material to photosystem I (PSI) as a light-harvesting biomolecule. In contrast to previous investigations, no mediating molecule is added to shuttle the electrons to the luminal side of PSI. Thus, this setup is less complex than foregoing ones. The solution composition drastically influences the interaction of PSI with the ITO surface. Here, the application of higher buffer concentrations and the addition of salts are advantageous, whereas the nature of the buffer ions plays a minor role. The artificial electrode material's thickness is adjustable since a spin-coating procedure is used for preparation. With a 30 μm thick structure and immobilized PSI cathodic photocurrents up to 10.1 μA cm−2 are obtained at 100 mW cm−2 illumination intensity and an applied potential of −0.1V vs. Ag/AgCl. Over a period of three days the photobioelectrodes are illuminated for a total of 90 min and stored between the measurements at ambient temperature. The stability of the setup is noteworthy as still about 90% of the photocurrent is retained. The photocathode described here offers many positive features, including a high onset potential for the photocurrent starting sligthly above the redox potentail of P700, and applicability in a wide pH range from pH 5 to 8.
Photobioelectrodes represent one of the examples where artificial materials are combined with biological entities to undertake semi-artificial photosynthesis. Here, an approach is described that uses reduced graphene oxide (rGO) as an electrode material. This classical 2D material is used to construct a three-dimensional structure by a template-based approach combined with a simple spin-coating process during preparation. Inspired by this novel material and photosystem I (PSI), a biophotovoltaic electrode is being designed and investigated. Both direct electron transfer to PSI and mediated electron transfer via cytochrome c from horse heart as redox protein can be confirmed. Electrode preparation and protein immobilization have been optimized. The performance can be upscaled by adjusting the thickness of the 3D electrode using different numbers of spin-coating steps during preparation. Thus, photocurrents up to ∼14 μA/cm2 are measured for 12 spin-coated layers of rGO corresponding to a turnover frequency of 30 e– PSI–1 s–1 and external quantum efficiency (EQE) of 0.07% at a thickness of about 15 μm. Operational stability has been analyzed for several days. Particularly, the performance at low illumination intensities is very promising (1.39 μA/cm2 at 0.1 mW/cm2 and −0.15 V vs Ag/AgCl; EQE 6.8%).
The development of precision cancer medicine relies on novel formulation strategies for targeted drug delivery to increase the therapeutic outcome. Biocompatible polymer nanoparticles, namely dextran-graft-polyacrylamide (D-g-PAA) copolymers, represent one of the innovative non-invasive approaches for drug delivery applications in cancer therapy. In this study, the star-like D-g-PAA copolymer in anionic form (D-g-PAAan) was developed for pH-triggered targeted drug delivery of the common chemotherapeutic drugs – doxorubicin (Dox) and cisplatin (Cis). The initial D-g-PAA copolymer was synthesized by the radical graft polymerization method, and then alkaline-hydrolyzed to get this polymer in anionic form for further use for drug encapsulation. The acidification of the buffer promoted the release of loaded drugs. D-g-PAAan nanoparticles increased the toxic potential of the drugs against human and mouse lung carcinoma cells (A549 and LLC), but not against normal human lung cells (HEL299). The drug-loaded D-g-PAAan-nanoparticles promoted further oxidative stress and apoptosis induction in LLC cells. D-g-PAAan-nanoparticles improved Dox accumulation and drugs’ toxicity in a 3D LLC multi-cellular spheroid model. The data obtained indicate that the strategy of chemotherapeutic drug encapsulation within the branched D-g-PAAan nanoparticle allows not only to realize pH-triggered drug release but also to potentiate its cytotoxic, prooxidant and proapoptotic effects against lung carcinoma cells.
Dieser Fragestellung geht das EU-Projekt ASTONRail in einem ersten Projektteil nach. In einer Umfrage wurde die Eisenbahnbranche in Deutschland und Europa hinsichtlich ihrer Erwartungen an die Hochschulausbildung neueingestellter Eisenbahningenieurinnen und -ingenieure befragt. Erkenntnisse und Schlussfolgerungen für die Hochschulausbildung werden nachfolgend vorgestellt.
Entsprechend aktueller wissenschaftlicher Studien ist das Risiko, sich mit SARS-CoV-2 im öffentlichen Verkehr zu infizieren, nicht höher als im häuslichen Umfeld. Besonders in Verkehrsmittelinnenräumen kann durch eine ausreichende Frischluftzufuhr, Umluftfilterung, Einhaltung von Abständen und dem richtigen Tragen von geeigneten Schutzmasken das Ansteckungsrisiko effektiv reduziert werden.
Von 2005 bis 2008 war es gelungen, für mehrere Netze des Schienenpersonenverkehrs durch den Einsatz mathematischer Optimierungsverfahren Verbesserungen in den Fahrplänen zu erzielen. Seither stehen weitere solche Einsätze aus. Der vorliegende Beitrag reflektiert daher, ob die eingesetzten Methoden und nicht zuletzt ggf. sogar die Zielgruppe(n) einer Justierung bedürfen.
Wettbewerb prägt den liberalisierten Eisenbahnmarkt in Europa und macht unternehmerisches Denken und Handeln der Eisenbahnverkehrsunternehmen im Fern-, Nah- und Güterverkehr erforderlich. Dabei ist der Umgang mit der Fahrzeuginstandhaltung ein wichtiger Erfolgsfaktor. Der vorliegende Artikel fokussiert sich auf die außerplanmäßige Instandhaltung und beschreibt die methodische Herleitung eines mathematischen Modells um den Schädigungszustand, also den Grad der Schädigung einer Flotte von Eisenbahnfahrzeugen, in eine valide Korrelation mit vorhandenen betrieblichen Ressourcen zu bringen. Diese Wechselbeziehung wird in eine allgemeingültige Kennzahl, dem Schadindex überführt und mittels eines geeigneten Prognosemodells in seinem zeitlichen Verlauf vorhersagbar dargestellt. Die Prognose berücksichtigt auch die Möglichkeit zur iterativen Anpassung der betrieblichen Ressourcen. So kann beispielsweise das zukünftige Schädigungsverhalten einer Eisenbahnfahrzeugflotte in Abhängigkeit einer veränderten Fahrzeugzahl oder einer Umstellung der Mitarbeiterbesetztzeiten in den Instandhaltungswerken simuliert werden. Mit einer systematischen Anwendung des Schadindex erhalten Eisenbahnverkehrsunternehmen mehr Handlungsspielräume zur Verfolgung ihrer strategischen und wirtschaftlichen Ziele. Aus einem Reagieren auf unerwartete Fahrzeugausfälle, wird ein Agieren bereits im Vorfeld dieser Ausfälle.
From Lab-on-chip to Lab-in-App: Challenges towards silicon photonic biosensors product developments
(2022)
This work presents and evaluates different approaches of integrated optical sensors based on photonic integrated circuit (PIC) technologies for refractive index sensing. Bottlenecks in the fabrication flow towards an applicable system are discussed that hinder a cost-effective mass-production for disposable sensor chips. As sensor device, a waveguide coupled micro-ring based approach is chosen which is manufactured in an 8” wafer level process. We will show that the co-integration with a reproducible, scalable and low-cost microfluidic interface is the main challenge which needs to be overcome for future application of silicon technology based PIC sensor chips.
Dieser Ausschnitt aus einer Masterarbeit dient der Betrachtung der Aufnahme und Verarbeitung von Informationen durch den Menschen im Straßenverkehr. Dazu werden unter anderem die Prozesse der Informationsaufnahme, Informationsverarbeitung und die Überführung der Informationen in eine Handlung genauer betrachtet, um erkennen zu können, welchen Nutzen Fahrerassistenzsysteme erzielen können, indem sie dem Menschen die Fahraufgabe entweder teilweise oder sogar vollständig abnehmen.
Single Pilot Operations is a current topic with the potential to significantly affect the future of commercial aviation. While financially attractive for airlines, Single Pilot Operations bring forth important safety concerns, especially regarding the lack of human redundancy in the flight deck, an increased workload for the single pilot, reduced situational awareness and a higher risk of human error.
It is assumed that potential problems affecting Single Pilot Operations could be addressed by implementing an Augmented Reality (AR) device in the flight deck, by presenting additional information and supporting hints within the pilot’s field of view. Concretely, AR could be used to help reduce the single pilot’s workload, improve situational awareness and reduce the risk of human error.
This paper sets out to demonstrate two use cases for augmented reality in the flight deck. A system, called Pilot Assist, was developed that allows pilots to conduct checklists interactively with a Microsoft HoloLens. The system also provides a holographic Head-up-Display. Pilot Assist was developed and demonstrated with a fixed base Airbus A320 simulator at the Technical University of Wildau.
With the HoloLens’ spatial mapping capabilities – scanning and recognizing the environment around the user – it was possible to create a system that guides the pilot through the conduction of checklists. This is done by prompting the user towards the location of each checklist item in the cockpit, where information regarding necessary actions is projected. Furthermore, Pilot Assist is integrated with the aircraft systems, making it possible to obtain aircraft status data in real time, thus allowing error-checking of the pilot’s actions as well as automating the progress through checklists.
The holographic Head-up-Display allows the user to look at the surrounding environment while presenting critical flight data within the user’s field of view. The holographic Head-up-Display is intended to contribute to the pilot’s situational awareness.
Experts in the aviation field, including pilots, researchers and engineers had the chance to qualitatively assess the Pilot Assist tool. They pointed to limitations of both Pilot Assist and the HoloLens itself, but shared optimism as to how this technology and similar applications could indeed impact the future of flight operations. Concerns regarding the HoloLens’ weight, comfort and narrow field of view were expressed. However, continued development of head mounted devices (e.g. HoloLens 2) is expected in the coming years.
Further research into augmented reality applications in the flight deck is needed to advance this and other use cases. Nonetheless, the experts agreed Pilot Assist provides beneficial support during single pilot operation considering the current prototypical nature of the system.
The possibility of exploiting the enormous potential of graphene for microelectronics and photonics must go through the optimization of the graphene–metal contact. Achieving low contact resistance is essential for the consideration of graphene as a candidate material for electronic and photonic devices. This work has been carried out in an 8′′ wafer pilot-line for the integration of graphene into a CMOS environment. The main focus is to study the impact of the patterning of graphene and passivation on metal–graphene contact resistance. The latter is measured by means of transmission line measurement (TLM) with several contact designs. The presented approaches enable reproducible formation of contact resistivity as low as 660 Ω μm with a sheet resistance of 1.8 kΩ/□ by proper graphene patterning, passivation of the channel and a post-processing treatment such as annealing.
Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world’s population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and introduction of personalized medicine in healthcare institutions, including at the individual level when designing smart houses. Therefore, this study aims to analyze short 10-s electrocardiogram measurements taken from 12 leads. In addition, the task is to classify patients with suspected myocardial infarction using machine learning methods. We have developed four models based on the k-nearest neighbor classifier, radial basis function, decision tree, and random forest to do this. An analysis of time parameters showed that the most significant parameters for diagnosing myocardial infraction are SDNN, BPM, and IBI. An experimental investigation was conducted on the data of the open PTB-XL dataset for patients with suspected myocardial infarction. The results showed that, according to the parameters of the short ECG, it is possible to classify patients with a suspected myocardial infraction as sick and healthy with high accuracy. The optimized Random Forest model showed the best performance with an accuracy of 99.63%, and a root mean absolute error is less than 0.004. The proposed novel approach can be used for patients who do not have other indicators of heart attacks.
The present study investigates basic features of a photoelectrochemical system based on CeO2 nanoparticles fixed on gold electrodes. Since photocurrent generation is limited to the absorption range of the CeO2 in the UV range, the combination with metal nanoparticles has been studied. It can be shown that the combination of silver nanoparticles with the CeO2 can shift the excitation range into the visible light wavelength range. Here a close contact between both components has been found to be essential and thus, hybrid CeO2@Ag nanoparticles have been prepared and analyzed. We have collected arguments that electron transfer occurs between both compositional elements of the hybrid nanoparticles.The photocurrent generation can be rationalized on the basis of an energy diagram underlying the necessity of surface plasmon excitation in the metal nanoparticles, which is also supported by wavelength-dependent photocurrent measurements. However, electrochemical reactions seem to occur at the CeO2 surface and consequently, the catalytic properties of this material can be exploited as exemplified with the photoelectrochemical reduction of hydrogen peroxide. It can be further demonstrated that the layer-by layer technique can be exploited to create a multilayer system on top of a gold electrode which allows the adjustment of the sensitivity of the photoelectrochemical system. Thus, with a 5-layer electrode with hybrid CeO2@Ag nanoparticles submicromolar hydrogen peroxide concentrations can be detected.
Rheumatologists in Europe and the USA increasingly rely on fluorescence optical imaging (FOI, Xiralite) for the diagnosis of inflammatory diseases. Those include rheumatoid arthritis, psoriatic arthritis, and osteoarthritis, among others. Indocyanine green (ICG)-based FOI allows visualization of impaired microcirculation caused by inflammation in both hands in one examination. Thousands of patients are now documented and most literature focuses on inflammatory arthritides, which affect synovial joints and their related structures, making it a powerful tool in the diagnostic process of early undifferentiated arthritis and rheumatoid arthritis. However, it has become gradually clear that this technique has the potential to go even further than that. FOI allows visualization of other types of tissues. This means that FOI can also support the diagnostic process of vasculopathies, myositis, collagenoses, and other connective tissue diseases. This work summarizes the most prominent imaging features found in FOI examinations of inflammatory diseases, outlines the underlying anatomical structures, and introduces a nomenclature for the features and, thus, supports the idea that this tool is a useful part of the imaging repertoire in rheumatology clinical practice, particularly where other imaging methods are not easily available.
The resistive switching properties of HfO₂ based 1T-1R memristive devices are electrically modified by adding ultra-thin layers of Al₂O₃ into the memristive device. Three different types of memristive stacks are fabricated in the 130 nm CMOS technology of IHP. The switching properties of the memristive devices are discussed with respect to forming voltages, low resistance state and high resistance state characteristics and their variabilities. The experimental I–V characteristics of set and reset operations are evaluated by using the quantum point contact model. The properties of the conduction filament in the on and off states of the memristive devices are discussed with respect to the model parameters obtained from the QPC fit.
Background
Cutaneous leishmaniasis (CL) is a vector-borne parasitic diseases of public health importance that is prevalent in the West Bank but not in the Gaza Strip. The disease caused by parasitic protozoans from the genus Leishmania and it is transmitted by infected phlebotomine sand flies. The aim of our study is to investigate the eco-epidemiological parameters and spatiotemporal projections of CL in Palestine over a 30-years period from 1990 through 2020 and to explore future projections until 2060.
Methodology/Principal findings
This long-term descriptive epidemiological study includes investigation of demographic characteristics of reported patients by the Palestinian Ministry of Health (PMoH). Moreover, we explored spatiotemporal distribution of CL including future projection based on climate change scenarios. The number of CL patients reported during this period was 5855 cases, and the average annual incidence rate (AAIR) was 18.5 cases/105 population. The male to female ratio was 1.25:1. Patients-age ranged from 2 months to 89 years (mean = 22.5, std 18.67, and the median was 18 years). More than 65% of the cases came from three governates in the West Bank; Jenin 29% (1617 cases), Jericho 25% (1403), and Tubas 12% (658) with no cases reported in the Gaza Strip. Seasonal occurrence of CL starts to increase in December and peaked during March and April of the following year. Current distribution of CL indicate that Jericho, Tubas, Jenin and Nablus have the most suitable climatic settings for the sandfly vectors. Future projections until 2060 suggest an increasing incidence from northwest of Jenin down to the southwest of Ramallah, disappearance of the foci in Jericho and Tubas throughout the Jordan Vally, and possible emergence of new foci in Gaza Strip.
Conclusions/Significance
The future projection of CL in Palestine until 2060 show a tendency of increasing incidence in the north western parts of the West Bank, disappearance from Jericho and Tubas throughout the Jordan Vally, and emergence of new CL endemic foci in the Gaza Strip. These results should be considered to implement effective control and surveillance systems to counteract spatial expansion of CL vectors.
Due to the high share of industry in total electricity consumption, industrial demand-side management can make a relevant contribution to the stability of power systems. At the same time, companies get the opportunity to reduce their electricity procurement costs by taking advantage of increasingly fluctuating prices on short-term electricity markets, the provision of system services on balancing power markets, or by increasing the share of their own consumption from on-site generated renewable energy. Demand-side management requires the ability to react flexibly to the power supply situation without negatively affecting production targets. It also means that the management and operation of production must consider not only production-related parameters but also parameters of energy availability, which further increase the complexity of decision-making. Although simulation studies are a recognized tool for supporting decision-making processes in production and logistics, the simultaneous simulation of material and energy flows has so far been limited mainly to issues of energy efficiency as opposed to energy flexibility, where application-oriented experience is still limited. We assume that the consideration of energy flexibility in the simulation of manufacturing systems will amplify already known pitfalls in conducting simulation studies. Based on five representative industrial use cases, this article provides practitioners with application-oriented experiences of the coupling of energy and material flows in simulation modeling of energy-flexible manufacturing, identifies challenges in the simulation of energy-flexible production systems, and proposes approaches to face these challenges. Seven pitfalls that pose a particular challenge in simulating energy-flexible manufacturing have been identified, and possible solutions and measures for avoiding them are shown. It has been found that, among other things, consistent management of all parties involved, early clarification of energy-related, logistical, and resulting technical requirements for models and software, as well as the application of suitable methods for validation and verification are central to avoiding these pitfalls. The identification and characterization of challenges and the derivation of recommendations for coping with them can raise awareness of typical pitfalls. This paper thus helps to ensure that simulation studies of energy-flexible production systems can be carried out more efficiently in the future.
Laboratory plasmas inherently exhibit temperature and density gradients leading to complex investigations. We show that plasmas generated by laser ablation can constitute a robust exception to this. Supported by emission features not observed with other sources, we achieve plasmas of various compositions which are both uniform and in local thermodynamic equilibrium. These properties characterize an ideal radiation source opening multiple perspectives in plasma spectroscopy. The finding also constitutes a breakthrough in the analytical field as fast analyses of complex materials become possible.
BACKGROUND:
After excitation with light photoacids can change the pH in a solution by release of a proton. They have been used mostly for excited state proton transfer studies. In this review the general functionality and mechanisms and the subdivision of photoacids is explained.
STATE OF THE ART:
Different uses of photoacids are described, covering a wide range of various biochemical topics, focusing on biochemical applications. Examples for the introduced subdivisions are covered.
CONCLUSIONS AND OUTLOOK:
The areas in which photoacids can be employed are diverse. Photoacids have a promising future in biotechnology and biochemistry and should be considered for upcoming applications, especially in non-invasive control of biochemical reactions.
The isoquinoline quaternary alkaloid Berberine possesses a variety of pharmacological properties that suggests its promising application for an anticancer delivery system design utilizing its ability to intercalate DNA. In the current work, we have investigated the effects of Berberine on the human T cell leukemia cell line in vitro. Fluorescent microscopy of leukemic cells revealed Berberine nuclear localization. The results showed that Berberine inhibited leukemic cell growth in a time- and dose-dependent manner, that was associated with reactive oxygen species production intensification and caspase 3/7 activity increase with followed apoptosis induction. Berberine was used as a toxic and phototoxic agent for triple system synthesis along with DNA as a carrier and nanosilver as a plasmonic accelerator of Berberine electronic transitions and high energy emission absorbent centers. The proposed method allows to obtain the complex of DNA with Berberine molecules and silver nanoparticles. The optical properties of free components as well as their various combinations, including the final triple system DNA-Nanosilver-Berberine, were investigated. Obtained results support the possibility to use the triple system DNA-Nanosilver-Berberine as an alternative therapeutic agent for cancer treatment.
Through Silicon Via (TSV) technology is a key in 3D integration of circuits by the creation of interconnects using vias, which go through the full silicon wafer. Typically, a highly-selective Bosch Si etch process is used. It is characterized by a high etch rate at a high aspect ratio, whereby scallops on the sidewalls are generated. In this work, square via arrays with dimensions from 3 to 50 μm and up to 300 μm depth were fabricated and analyzed by spectroscopic reflectometry. The reflectometric data are compared to simulations by a novel theoretical approach. In order to simulate the reflectance spectra of TSV arrays, a combination of 2D and 3D rigorous coupled wave analysis was applied. Besides the via depth, the sidewall angle and the corner radius of the bottom profile were considered in the model. The general requirements on spectral resolution in TSV metrology are discussed.
Comprehensive diagnostics is a prerequisite for the application of graphene in semiconductor technologies. Here, the authors present long-term investigations of graphene on 200-mm Ge(100)/Si(100) wafers under clean room environmental conditions. Diagnostic of graphene was performed by a fast and nondestructive metrology method based on the combination of spectroscopic ellipsometry and reflectometry (SE/R), realized within a wafer optical metrology tool. A robust procedure for unambiguous thickness monitoring of a multilayer film stack, including graphene, interface layer GeOx underneath graphene, and surface roughness is developed and applied for process control. The authors found a relationship between the quality of graphene and the growth of GeOx beneath graphene. Enhanced oxidation of Ge beneath graphene was registered as a long-term process. SE/R measurements were validated and complemented using atomic force microscopy, scanning electron microscopy, Raman spectroscopy, and secondary ion mass spectrometry. This comparative study shows a high potential for optical metrology of graphene deposited on Ge/Si structures, due to its great sensitivity, repeatability, and flexibility, realized in a nondestructive way.
The first atomic layer deposition process for a ternary oxide is reported, which contains a metal of the platinum group, the delafossite PtCoO2. The deposition with the precursors trimethyl-Pt-methylcyclopentadienyl, Co-bis(N-t-butyl-N′-ethylpropanimidamidate), and oxygen plasma results in a process with a nearly constant growth rate and stoichiometric composition over a wide temperature window from 100 to 320 °C. Annealing of the as-deposited amorphous films in an oxygen atmosphere in a temperature window from 700 to 800 °C leads to the formation of the delafossite phase. Very thin films show a pronounced preferred orientation with the Pt sheets being almost parallel to the substrate surface while arbitrary orientation is observed for thicker films. The conformal coating of narrow trenches highlights the potential of this atomic-layer-deposition process. Moreover, heterostructures with magnetic films are fabricated to demonstrate the potential of PtCoO2 for spintronic applications.
We propose a new mixed integer programming based heuristic for computing new benchmark primal solutions for instances of the PESPlib. The PESPlib is a collection of instances for the Periodic Event Scheduling Problem (PESP), comprising periodic timetabling problems inspired by real-world railway timetabling settings, and attracting several international research teams during the last years. We describe two strategies to merge a set of good periodic timetables. These make use of the instance structure and minimum weight cycle bases, finally leading to restricted mixed integer programming formulations with tighter variable bounds. Implementing this timetable merging approach in a concurrent solver, we improve the objective values of the best known solutions for the smallest and largest PESPlib instances by 1.7 and 4.3 percent, respectively.
Label-free direct-optical biosensors such as surface-plasmon resonance (SPR) spectroscopy has become a gold standard in biochemical analytics in centralized laboratories. Biosensors based on photonic integrated circuits (PIC) are based on the same physical sensing mechanism: evanescent field sensing. PIC-based biosensors can play an important role in healthcare, especially for point-of-care diagnostics, if challenges for a transfer from research laboratory to industrial applications can be overcome. Research is at this threshold, which presents a great opportunity for innovative on-site analyses in the health and environmental sectors. A deeper understanding of the innovative PIC technology is possible by comparing it with the well-established SPR spectroscopy. In this work, we shortly introduce both technologies and reveal similarities and differences. Further, we review some latest advances and compare both technologies in terms of surface functionalization and sensor performance.
Direct optical detection methods such as surface plasmon resonance imaging (SPRi) and photonic-integrated-circuits (PIC)-based biosensors provide a fast label-free detection of COVID-19 antibodies in real-time. Each technology, i.e., SPRi and PIC, has advantages and disadvantages in terms of throughput, miniaturization, multiplexing, system integration, and cost-effective mass production. However, both technologies share similarities in terms of sensing mechanism and both can be used as high-content diagnostics at or near to point of care, where the analyte is not just quantified but comprehensively characterized. This is significant because recent results suggest that not only the antibody concentration of the three isotypes IgM, IgG, and IgA but also the strength of binding (affinity) gives an indication of potential COVID-19 severity. COVID-19 patients with high titers of low affinity antibodies are associated with disease severity. In this perspective, we provide some insights into how SPR and PIC technologies can be effectively combined and complementarily used for a comprehensive COVID-19 severity monitoring. This opens a route toward an immediate therapy decision to provide patients a treatment in an early stage of the infection, which could drastically lowers the risk of a severe disease course.
Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and labor intensive. The development of a point-of-care system based on a mobile microscope and powerful algorithms would be beneficial for providing care directly at the patient's bedside. For this purpose human blood samples were visualized using a low-cost mobile microscope, an ocular camera and a smartphone. Training and optimisation of different deep learning methods for instance segmentation are used to detect and count the different blood cells. The accuracy of the results is assessed using quantitative and qualitative evaluation standards.
Endophytic fungi that colonize the plant root live in an environment with relative high concentrations of different sugars. Analyses of genome sequences indicate that such endophytes can secrete carbohydrate-related enzymes to compete for these sugars with the surrounding plant cells. We hypothesized that typical plant sugars can be used as carbon source by root endophytes and that these sugars also serve as signals to induce the expression and secretion of glycolytic enzymes. The plant-growth-promoting endophytes Serendipita indica and Serendipita herbamans were selected to first determine which sugars promote their growth and biomass formation. Secondly, particular sugars were added to liquid cultures of the fungi to induce intracellular and extracellular enzymatic activities which were measured in mycelia and culture supernatants. The results showed that both fungi cannot feed on melibiose and lactose, but instead use glucose, fructose, sucrose, mannose, arabinose, galactose and xylose as carbohydrate sources. These sugars regulated the cytoplasmic activity of glycolytic enzymes and also their secretion. The levels of induction or repression depended on the type of sugars added to the cultures and differed between the two fungi. Since no conventional signal peptide could be detected in most of the genome sequences encoding the glycolytic enzymes, a non-conventional protein secretory pathway is assumed. The results of the study suggest that root endophytic fungi translocate glycolytic activities into the root, and this process is regulated by the availability of particular plant sugars.
In this work, the fabrication and characterization of a simple, inexpensive, and effective microfluidic paper analytic device (µPAD) for monitoring DNA samples is reported. The glass microfiber-based chip has been fabricated by a new wax-based transfer-printing technique and an electrode printing process. It is capable of moving DNA effectively in a time-dependent fashion. The nucleic acid sample is not damaged by this process and is accumulated in front of the anode, but not directly on the electrode. Thus, further DNA processing is feasible. The system allows the DNA to be purified by separating it from other components in sample mixtures such as proteins. Furthermore, it is demonstrated that DNA can be moved through several layers of the glass fiber material. This proof of concept will provide the basis for the development of rapid test systems, e.g., for the detection of pathogens in water samples.
The etching of high aspect ratio structures in silicon via the Bosch process is essential in modern technologies such as microelectromechanical systems (MEMS) and through‑silicon vias (TSV) fabrication. The process can be very demanding on the mask selectivity due to long etching times, and it has been shown that an Al2O3 hard mask is very suitable in this regard, as it offers significantly higher selectivity compared to the conventional SiO2 or resist masks. In this work, we employ a combination of Scanning Electron Microscopy (SEM), Spectroscopic Ellipsometry (SE) and X-Ray Photoelectron Spectroscopy (XPS) depth profiling to scrutinize the Al2O3 mask etching mechanism and therefore the origin of the extraordinary high selectivity. We demonstrate that by increasing the passivation step time, a thicker fluorocarbon polymer layer is formed on the Al2O3, and Al2O3 is then removed with a minuscule average etch rate of 0.01 nm/min. XPS depth profiling reveals that during Deep Reactive Ion Etching (DRIE) using the Bosch process, an AlFx layer is formed between the polymer and Al2O3. As AlFx is non-volatile, it requires sputtering to be removed. If the polymer layer is thick enough to attenuate the incoming ions such that their energy is not sufficient to lead to desorption of AlFx, such as when using a longer passivation time, the mask is not eroded. By investigating the surface after different amounts of DRIE cycles, we also obtained information about the formation rate of AlFx and the changes in the Al2O3 and polymer thicknesses over the course of a DRIE process. These findings further expand the knowledge of DRIE and can help process engineers to tailor the processes accordingly.
Knowledge of optical constants, i.e. refractive index n and extinction coefficient k, and light scattering properties of optical polymers are required to optimize micro-optics for light-emitting diodes in terms of efficiency, color properties and light distribution. We present here a model-based diagnostic approach to determine the optical properties of polymers, which should be particularly useful in the development of plastics for optical applications. Optical constants and scattering coefficients were obtained from transmission and reflection measurements in a wavelength range from UV to NIR taking into account scattering effects due to rough surfaces and volume inhomogeneity. Based on the models for the dielectric function, the molecular optical transition energies Eg, critical point energies, Urbach energies and exciton transition energies were determined. Rayleigh and Mie scattering model and van de Hulst's anomalous diffraction theory were applied to characterize scattering due to volume inhomogeneities. Scalar diffraction theory was applied to account for surface roughness scattering. Atomic force microscopy with nanomechanical characterization was used to characterize domains in size and shape and to assign optical scattering to a suitable morphological model. The combined optical and mechanical characterization help to improve the qualification of new polymer materials for optical applications.
Summary In the course of classical optics manufacturing glass components are in permanent direct contact with aqueous operating materials. Such contact leads to a certain absorption of water and hydrogenous compounds that may induce severe glass defects. In this contribution, absorption of hydrogen and other contaminants during grinding of glass was observed and qualitatively detected via laser-induced breakdown spectroscopy. It is shown that hydrogen, calcium, magnesium, and carbon are implanted into the glass surface where the contaminant concentration increases over grinding time or contact time of the glass surface with water and the grinding tool, respectively. The contaminants hydrogen, calcium, and magnesium can be attributed to the water used as lubricant. In contrast, carbon most likely originates from wear debris of the used silicon carbide grinding pads. Several possible mechanisms that lead to such surface contamination of glasses during grinding – diffusion, accumulation in micro cracks as well as the formation of hydrated silica – are finally introduced.
Besides invasive mosquito species also several native species are proven or suspected vectors of arboviruses as West Nile or Usutu virus in Western Europe. Habitat models of these native vectors can be a helpful tool for assessing the risk of autochthonous occurrence, outbreaks and spread of diseases caused by such arboviruses. Modelling native mosquitoes is complicated because of the perfect adaptation to the climatic and landscape conditions and their high abundance in contrast to invasive species. Here we present a new approach for such a habitat model for native mosquito species in Germany, which are considered as vectors of West Nile virus (WNV). Epizootic emergence of WNV was registered in Germany since 2018. The models are based on surveillance data of mosquitoes from the German citizen science project “Mückenatlas” complemented by data from systematic trap monitoring in Germany, and on data freely available from the Deutscher Wetterdienst (DWD) and OpenStreetMap (OSM). While climatic factors still play an important role, we could show that habitat suitability is predictable only by the combination of the climate model with a regional model. Both models were based on a machine-learning approach using XGBoost. Evaluation of the accuracy of the models was done by statistical analysis, determining among others feature importances using the SHAP-Library. Final output of the combined climatic and regional models are maps showing the superposed habitat suitability which are generated through a number of steps described in detail. These maps also include the registered cases of WNV infections in the selected region of Germany.
El capital humano en el marco de la Industria 4.0 debe sufrir una transformación necesaria, adquiriendo competencias de alta cognición que garanticen la asimilación de las tecnologías habilitadoras en la Industria 4.0 para la mejora sustancial de los procesos en cualquier Industria. El objetivo de este trabajo es reseñar parte de las tecnologías habilitadoras en la Industria 4.0, junto a otros elementos, y su implementación posible en la práctica del aprendizaje experiencial, en ruta para el desarrollo del concepto de una Educación 4.0 en la Ingeniería Industrial. Se identifican, además, elementos que influyen en la inserción de las mismas en un entorno de aprendizaje en un laboratorio, que garantice el componente vivencial en la enseñanza. Se documenta un caso de intervención con estudiantes de Ingeniería Industrial de la CUJAE, donde a partir de la experiencia vivencial de un grupo de estudiantes con las tecnologías mencionadas, se identifica una asimilación más rápida y consolidada de estas competencias cuando se compara con estudiantes que están sometidos a una educación tradicional.
The operation of manufacturing systems is increasingly accompanied by data-driven continuous improvement processes and product traceability is required. Commonly, radio-frequency identification (RFID) technology is applied to track the flow of a uniquely-identifiable workpiece along various stations or waypoints within a factory. Based on an automotive use case, this paper describes how to analyze the resulting traceability data in order to identify several properties of a manufacturing system. The acquired knowledge can support performance evaluation and facilitate model building for material flow simulation as a foundation for digital twins and cyber-physical production systems.
Nile tilapia (Oreochromis niloticus) is a species of worldwide importance for aquaculture. A crossbred lineage was developed through introgressive backcross breeding techniques and combines the high growth performance of the Chitralada (CHIT) lwith attractive reddish color of the Red Stirling (REDS) strains. Since the crossbreed has an unknown genetically improved background, the objective of this work was to characterize expression signatures that portray the advantageous phenotype of the crossbreeds. We characterized the microRNA transcriptome by high throughput sequencing (RNA-seq) and the proteome through mass spectrometry (ESI-Q-TOF-MS) and applied bioinformatics for the comparative analysis of such molecular data on the three strains. Crossbreed expressed a distinct set of miRNAs and proteins compared to the parents. They comprised several microRNAs regulate traits of economic interest. Proteomic profiles revealed differences between parental and crossbreed in expression of proteins associated with glycolisis. Distinctive miRNA and protein signatures contribute to the phenotype of crossbreed.
Silver halide polycrystalline infrared fibers (PIR) have unique properties such as excellent transmittance in the spectral range from 3 to 17 µm, while also being highly flexible, non-toxic, and non-hygroscopic. They are used in industry and medicine for CO2-laser power delivery, flexible infrared imaging, and remote process spectroscopy. While PIR fibers possess a quite low attenuation (0.1-0.5 dB/m) in the 8-12 µm range, their total transmittance is limited by significant Fresnel reflections at the fiber end faces due to the high refractive index of silver halide (>2.1). Functionalization of these surfaces with specially designed Anti-Reflective Microstructures (ARMs) enables a striking enhancement of fiber transmittance. In this work, direct imprinting (or embossing) of microstructures to fiber ends and their profiling with a microstructured knife was applied to fabricate such ARMs. The resulting two-dimensional Moth-eye microstructures and one-dimensional microgrooves at the PIR-fiber ends enable to an increase of fiber transmittance in a broadband range of (5-17 µm) as well as to reach up to 20% improvement for PIR-fiber laser cables used for power delivery of CO2-lasers at 10.6 µm.
This study investigated how touching and being touched by a humanoid robot affects human physiology, impressions of the interaction, and attitudes towards humanoid robots. 21 healthy adult participants completed a 3 (touch style: touching, being touched, pointing) × 2 (body part: hand vs buttock) within-subject design using a Pepper robot. Skin conductance response (SCR) was measured during each interaction. Perceived impressions of the interaction (i.e., friendliness, comfort, arousal) were measured per questionnaire after each interaction. Participants’ demographics and their attitude towards robots were also considered. We found shorter SCR rise times in the being touched compared to the touching condition, possibly reflecting psychological alertness to the unpredictability of robot-initiated contacts. The hand condition had shorter rise times than the buttock condition. Most participants evaluated the hand condition as most friendly and comfortable and the robot-initiated interactions as most arousing. Interacting with Pepper improved attitudes towards robots. Our findings require future studies with larger samples and improved procedures. They have implications for robot design in all domains involving tactile interactions, such as caring and intimacy.
Electro-optical properties of doped polymers with high transparency in the visible wavelength range
(2021)
The electro-optical (EO) properties of poly(methyl methacrylate) and the photopolymer poly(vinyl cinnamate) doped with varying concentrations of the EO chromophore 2-Methyl-4-nitroaniline were measured. The EO polymers were embedded in Fabry-Pérot etalons for the simultaneous determination of the Pockels and Kerr coefficients from measurements of the fringe shift induced by an external electric field. It was found that the host polymer has a significant impact on the EO performance and that the undoped host polymers exhibit a significant Pockels effect. Moreover, the Kerr effect provides a substantial contribution of 27% to the total change of the refractive index at relatively high electric field strengths of E = 91.2 MV m−1.
Polycrystalline infrared (PIR) fibers are used for numerous applications, one of those being power delivery for CO2 lasers. However, the fiber tip surface's transmittance cannot be increased with conventional antireflection coatings due to the surface unevenness. Antireflection microstructures (ARMs) offer an alternative way of increasing transmittance. In this work, ARMs were fabricated on the fiber tip surface of an AgClBr fiber by single-pulse femtosecond laser ablation. A single-surface transmittance of 92.8% at 10.6 μm, a CO2 laser operation wavelength, was achieved. The proposed method can help significantly improve the systems' efficiency, where power delivery for CO2 lasers or sources operating in the wide wavelength range is required.
AbstractThe introduction of nucleic acid amplification techniques has revolutionized the field of medical diagnostics in the last decade. The advent of PCR catalyzed the increasing application of DNA, not just for molecular cloning but also for molecular based diagnostics. Since the introduction of PCR, a deeper understanding of molecular mechanisms and enzymes involved in DNA/RNA replication has spurred the development of novel methods devoid of temperature cycling. Isothermal amplification methods have since been introduced utilizing different mechanisms, enzymes, and conditions. The ease with which isothermal amplification methods have allowed nucleic acid amplification to be carried out has had a profound impact on the way molecular diagnostics are being designed after the turn of the millennium. With all the advantages isothermal amplification brings, the issues or complications surrounding each method are heterogeneous making it difficult to identify the best approach for an end-user. This review pays special attention to the various isothermal amplification methods by classifying them based on the mechanistic characteristics which include reaction formats, amplification information, promoter, strand break, and refolding mechanisms. We would also compare the efficiencies and usefulness of each method while highlighting the potential applications and detection methods involved. This review will serve as an overall outlook on the journey and development of isothermal amplification methods as a whole.
Determination of thermo-mechanical properties of recycled polyurethane from glycolysis polyol
(2021)
Polyurethane foam is one of the most versatile polymers widely used in the automotive industry. However, due to the rising amount of polyurethane foam waste in the environment, there is growing research attention focusing on circular economy solutions to closing the material loop. This study aimed to determine the possible changes in thermo-mechanical properties between rigid polyurethane prepared using polyols derived from depolymerization of commercial polyurethane foam with benchmark rigid polyurethane (Ben PU). Polyurethane foams containing dispersion polyol were reacted with dipropylene glycol (DPG) and diethylene glycol (DEG) with a ratio of DPG: DEG of 1:1 in the presence of a consumable catalyst (Di-n-butyl amine). The recovered polyol was used as a raw material replacing 100% benchmark rigid polyurethane petroleum-based polyester polyol to produce the recycled polyurethane (Rec PU). Thermal analysis was conducted to measure the recycled polyurethane's glass transition temperatures (Tg) using differential scanning calorimetry (DSC). Tensile strength, elastic modulus, toughness, and hardness test of the recycled polyurethane were conducted under three different temperatures; 24°C, 40°C, and 60°C. From the DSC results, the glass transition temperatures for the recycled and the benchmark rigid polyurethane occurred at 43°C and 50.4°C, respectively. Both polymers showed the brittle-ductile transition from 24°C to 40°C. Tensile strength for recycled polyurethane was lower than that of benchmark rigid polyurethane by 29-43% and a corresponding 24-50% decrease in elastic modulus. Recycled polyurethane recorded lower toughness than petroleum-based pure polyurethane by 13-16%. However, the recycled polymer recorded high shored D values than the benchmark rigid polyurethane by 9-29%. This study reveals that recycled polyol could be used as feedstock for polyurethane production with applications tailored to its mechanical properties.
Decoration with Pd clusters increases the magnetic heating ability of cobalt ferrite (CFO) nanoparticles by a factor of two. The origin of this previous finding is unraveled by element-specific X-ray absorption spectroscopy (XAS) and magnetic circular dichroism (XMCD) combined with atomic multiplet simulations and density functional theory (DFT) calculations. While the comparison of XAS spectra with atomic multiplet simulations show that the inversion degree is not affected by Pd decoration and, thus, can be excluded as a reason for the improved heating performance, XMCD reveals two interrelated responsible sources: significantly larger Fe and Co magnetic moments verify an increased total magnetization which enhances the magnetic heating ability. This is accompanied by a remarkable change in the field-dependent magnetization particularly for Co ions which exhibit an increased low-field susceptibility and a reduced spin canting behavior in higher magnetic fields. Using DFT calculations, these findings are explained by reduced superexchange between ions on octahedral lattice sites via oxygen in close vicinity of Pd, which reinforces the dominating antiparallel superexchange interaction between ions on octahedral and tetrahedral lattice sites and thus reduces spin canting. The influence of the delocalized nature of Pd 4d electrons on the neighboring ions is discussed and the conclusions are illustrated with spin density isosurfaces of the involved ions. The presented results pave the way to design nanohybrids with tailored electronic structure and magnetic properties.
Background
Berberine (Ber) is a herbal alkaloid with pharmacological activity in general and a high anticancer potency in particular. However, due to its low bioavailability, the difficulty in reaching a target and choosing the right dose, there is a need to improve approaches of Ber use in anticancer therapy. In this study, Ber, noncovalently bound to a carbon nanostructure C60 fullerene (C60) at various molar ratios of the components, was explored against Lewis lung carcinoma (LLC).
Methods
C60–Ber noncovalent nanocomplexes were synthesized in 1:2, 1:1 and 2:1 molar ratios. Ber release from the nanocomplexes was studied after prolonged incubation at different pH with the liquid chromatography–mass spectrometry analysis of free Ber content. Biological effects of the free and C60-complaxated Ber were studied in vitro towards LLC cells with phase-contrast and fluorescence microscopy, flow cytometry, MTT reduction, caspase activity and wound closure assays. The treatment with C60–Ber nanocomplex was evaluated in vivo with the LLC-tumored C57Bl mice. The mice body weight, tumor size, tumor weight and tumor weight index were assessed for four groups, treated with saline, 15 mg C60/kg, 7.5 mg Ber/kg or 2:1 C60-Ber nanocomplex (15 mg C60/kg, 7.5 mg Ber/kg).
Results
Ber release from C60–Ber nanocomplexes was promoted with medium acidification. LLC cells treatment with C60–Ber nanocomplexes was followed by enhanced Ber intracellular uptake as compared to free Ber. The cytotoxicity of the studied agents followed the order: free Ber < 1:2 < 1:1 < 2:1 C60–Ber nanocomplex. The potency of cytotoxic effect of 2:1 C60–Ber nanocomplex was confirmed by 21.3-fold decrease of IC50 value (0.8 ± 0.3 µM) compared to IC50 for free Ber (17 ± 2 µM). C60–Ber nanocomplexes induced caspase 3/7 activation and suppressed the migration activity of LLC cells. The therapeutic potency of 2:1 C60–Ber nanocomplex was confirmed in a mouse model of LLC. The tumor growth in the group treated with 2:1 C60–Ber nanocomplex is suppressed by approximately 50% at the end of experiment, while in the tumor-bearing group treated with free Ber no therapeutic effect was detected.
Conclusions
This study indicates that complexation of natural alkaloid Ber with C60 may be a novel therapeutic strategy against lung carcinoma.
Optical-resolution photoacoustic microscopy (OR-PAM) combines high spatial resolution and strong absorption-based contrast in tissue, which has enabled structural and spectroscopic imaging of endogenous chromophores, primarily hemoglobin. Conventional piezoelectric ultrasound transducers are typically placed far away from the photoacoustic source due to their opacity, which reduces acoustic sensitivity. Optical ultrasound sensors are an alternative as their transparency allows them to be positioned close to the sample with minimal source-detector distances. In this work, a backward-mode OR-PAM system based on a planar Fabry-Pérot ultrasound sensor and coaxially aligned excitation and interrogation beams was developed. Two 3D imaging modes, using raster-scanning for enhanced image quality and continuous-scanning for fast imaging, were implemented and tested on a leaf skeleton phantom. In fast imaging mode, a scan-rate of 100,000 A-lines/s was achieved. 3D images of a zebrafish embryo were acquired in vivo in raster-scanning mode. The transparency of the FP sensor in the visible and near-infrared wavelength region makes it suitable for combined functional and molecular imaging applications using OR-PAM and multi-photon fluorescence microscopy.
The investigation of the crack propagation in as-extruded and heat-treated Mg-Dy-Nd-Zn-Zr alloy with a focus on the interaction of long-period stacking-ordered (LPSO) structures is the aim of this study. Solution heat treatment on a hot extruded Mg-Dy-Nd-Zn-Zr (RESOLOY®) was done to change the initial fine-grained microstructure, consisting of grain boundary blocky LPSO and lamellar LPSO structures within the matrix, into coarser grains of less lamellar and blocky LPSO phases. C-ring compression tests in Ringer solution were used to cause a fracture. Crack initiation and propagation is influenced by twin boundaries and LPSO lamellae. The blocky LPSO phases also clearly hinder crack growth, by increasing the energy to pass either through the phase or along its interface. The microstructural features were characterized by micro- and nanohardness as well as the amount and location of LPSO phases in dependence on the heat treatment condition. By applying nanoindentation, blocky LPSO phases show a higher hardness than the grains with or without lamellar LPSO phases and their hardness decreases with heat treatment time. On the other hand, the matrix increases in hardness by solid solution strengthening. The microstructure consisting of a good balance of grain size, matrix and blocky LPSO phases and twins shows the highest fracture energy.
One of the limiting factors of graphene integration into electronic, photonic, or sensing devices is the unavailability of large-scale graphene directly grown on the isolators. Therefore, it is necessary to transfer graphene from the donor growth wafers onto the isolating target wafers. In the present research, graphene was transferred from the chemical vapor deposited 200 mm Germanium/Silicon (Ge/Si) wafers onto isolating (SiO2/Si and Si3N4/Si) wafers by electrochemical delamination procedure, employing poly(methylmethacrylate) as an intermediate support layer. In order to influence the adhesion properties of graphene, the wettability properties of the target substrates were investigated in this study. To increase the adhesion of the graphene on the isolating surfaces, they were pre-treated with oxygen plasma prior the transfer process of graphene. The wetting contact angle measurements revealed the increase of the hydrophilicity after surface interaction with oxygen plasma, leading to improved adhesion of the graphene on 200 mm target wafers and possible proof-of-concept development of graphene-based devices in standard Si technologies.
A reliable energy supply for the economy of every country is a matter of national importance. Powerful simulation tools for natural gas networks are essential for operators of gas networks. In this paper, enhancement algorithms of previous developed node potential analysis algorithm are presented. These enhancement algorithms are used for a reasonable setting of initial values in the numerical gas net simulation algorithm. The setting of the initial values has a significant influence on the convergence behavior of the numerical simulation. The presented enhancement algorithms are explained and simulation results are evaluated.