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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.
Overview of FLASHlab@PITZ: the new R&D platform for FLASH radiation therapy and radiation biology
(2024)
An R&D platform for electron FLASH radiation therapy and radiation biology is being prepared at the Photo Injector Test facility at DESY in Zeuthen (FLASHlab@PITZ). This platform is based on the unique beam parameters available at PITZ: ps scale electron bunches of up to 22 MeV with up to 5 nC bunch charge at MHz bunch repetition rate in bunch trains of up to 1 ms in length repeating at 1 to 10 Hz. It works together with the Technical University of Applied Sciences Wildau (TH Wildau) as partner in close vicinity for the biological resources.
A startup beamline has been installed to allow dosimetry studies and irradiation experiments on chemical, biochemical and biological samples after a 60-degree dispersive arm. The measured dose and dose rates under different beam conditions and first experimental results will be reported in this paper. In addition, a dedicated beamline for FLASHlab@PITZhas been designed for better control of the high brightness electron beams. This includes a dogleg to translate the beam and a 2D kicker system to scan the tiny beam focused by quadrupoles across the samples within less than 1 ms. Simulation studies will be presented to demonstrate the extremely flexible dose parameters with various irradiation options for electron FLASH radiation therapy and radiation biology studies.
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.
Dieser Beitrag beschreibt zwei Studien zur Akzeptanz eines Messroboters zur Durchführung von dermatologischen In-Vivo-Messungen. Die erste Studie ist eine quantitative Online-Umfrage mit 745 Teilnehmern. Die Studie gliedert sich in drei Bereiche mit insgesamt 24 Fragen. Die Teilnehmer werden zu ihren Erfahrungen und Ängsten in Bezug auf Roboter befragt und insbesondere zu einem möglichen Einsatz eines Messroboters für dermatologische In-Vivo-Studien. Für die qualitative Studie werden insgesamt 17 Studienteilnehmer jeweils einzeln für ein zweistündiges Interview, welches in 4 Phasen gegliedert ist, eingeladen. In Phase 2 dieser Studie werden die ersten robotergestützten In-Vivo-Messungen an Hautarealen auf dem Unterarm der Teilnehmer durchgeführt. Bereits aus der quantitativen Umfrage geht hervor das die meisten (75 %) Teilnehmer der Idee von Robotern im Messbetrieb offen gegenüber stehen, 55,7% befürworten den Einsatz sogar. Während des quantitativen Interviews werden Ängste und Unsicherheiten vor und während der ersten Messung genannt und beobachtet. Alle Teilnehmer waren zur Wiederholungsmessung sehr viel sicherer im Umgang mit dem Roboter und können sich einen zukünftigen Einsatz vorstellen. Besondere Herausforderungen stellen sich hinsichtlich der Positionierung der Studienteilnehmer zum Roboter heraus. Die Sicherstellung einer ergonomischen Gestaltung der Roboterumgebung ist für physische Mensch-Roboter-Kollaboration entscheidend und wird zur Weiterentwicklung des Systems stärker berücksichtigt. Weiter wurde ein 3-Stufen-Zustimmschalter zur Absicherung der Roboterbewegungen verwendet, dieser fand allerdings wenig Anklang und wurde stark kritisiert. Für den zukünftigen Einsatz wird eine alternative Überwachung des direkten Arbeitsbereiches erarbeitet.
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.
Der technische Fortschritt hat dazu geführt, dass die Kosten für das automatisierte Drucken von Emblemen, Anhängern sowie allgemein gedruckten Prototypen stark gefallen sind. Dies geschah insbesondere auch vor dem Hintergrund eines Wandels der Industrie hin zu einer modernen Industrie 4.0. In dieser Arbeit wird ein neuer Ansatz für das automatische 3D-Drucken eines Logos präsentiert, welches als Pixelgrafik vorliegt. Die vorgeschlagene Prozesskette erzeugt hierbei final den G-code zum Drucken. Dabei sind seitens des Users wenige Eingaben erforderlich.
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.
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.
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.
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.
Die Industrie 5.0 fordert neue Lernansätze und zeitgleich auch passende Lernumgebungen. Parallel müssen diese neben den didaktischen Herausforderungen auch den Transfer- und Übertragungsgedanken auf die industriellen Anwendungen gerecht werden. Durch die täglich steigende Anzahl vielfältiger KI-Tools insbesondere textgenerierenden Tools, braucht es Systeme mit einem breiten Anwendungsbereich. Im Rahmen des vorliegenden Beitrags geben die Autoren einen Einblick in die Wildauer Smart Production, welche den transdisziplinären Gedanken von Lern- und Transferumgebungen Rechnung trägt, Möglichkeiten der Gestaltung komplexer Produktionssysteme widerspiegelt, die Integration menschzentrierter Ansätze ermöglicht und als Forschungsumgebung eingesetzt wird.
Urbane Mobilität insbesondere der innerstädtischen Personentransport wird auch zukünftig ein besonderes Augenmerk unter dem Eindruck nachhaltiger Nutzung von Energiesystemen haben. Hierbei besitzt der öffentliche Personennahverkehr(ÖPNV) ein großes Potential zur großskaligen Minderung des Kohlendioxid ausstoßes. Ein sehr wichtiges Konzept hierbei ist der Oberleitungsbus der ganz analog zu einer Straßenbahn über eine Oberleitung fahrbahnbegleitend mit Strom versorgt wird. Da der Bus naturgemäß nicht schienengebunden fährt und somit ein gewisses Maß an Positionsungenauigkeit besitzt, ist das Eindrahten an die Oberleitung allerdings erschwert. In dieser Arbeit präsentieren wir einen Regelungsansatz basierend auf einer neuartigen Sensorkonfiguration, der das automatische Eindrahten eines Stromabnehmers auf einem Bus ermöglichen kann.
The two main features of the memristive devices which makes them the promising candidates for neuromorphic applications are low power consumption and CMOS compatibility. The monolithic integration of memristive devices with CMOS circuitry paves the way for in-memory computing. This chapter focuses on the factors governing the CMOS integration process. Firstly, the influence of CMOS baseline technology selection on the memristor module is briefly discussed. Secondly, the selection of metal level interconnects and their effect on the memristive device performance is explained. Further, the widely used deposition technique for the CMOS compatible memristive switching layers is presented. Finally, the implementation of the optimized process for the fabrication of the memristive module and its influence on the device performance is presented in terms of electrical characterization results.
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.
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.
Dieses Paper präsentiert das Forschungsprojekt „Intelligent Camera Unit“ (ICU) der Technischen Hochschule Wildau in Kooperation mit der Beiersdorf AG zur Verbesserung von Portraitaufnahmen in Probandenstudien für Kosmetikprodukte. Das Hauptziel des Projekt besteht darin, Ausrichtungsfehler zu minimieren und die Vergleichbarkeit von Vorher-Nachher-Bildern zu erhöhen. Dies wird durch die Verwendung eines kollaborativen Roboters und KI-gestützter Bildanalyse erreicht, um präzise Ausrichtung und Gesichtspositionen der Probanden zu gewährleisten. Das entwickelte System ermöglicht effiziente und reproduzierbare Aufnahmen aus verschiedenen Winkeln und Entfernungen und bietet eine benutzerfreundliche, web-basierte Bedienoberfläche.
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.
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.
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.
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.
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.
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.
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.
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.
Plasmonics includes the fundamentals of surface plasmon polaritons in metals, and its rapidly increasing applications in biochemistry, nanotechnology, optical communication, sensing, and medicine. Surface plasmon polaritons have become popular because of their ultrasensitive optical measurement capabilities, and in recent years they have also been employed for ultra-high-speed data transfer. This book presents recent advances in the broad field of plasmonics, covering not only current progress and the latest breakthroughs in emergent applications but also geometry optimizations and the fundamentals of physical interactions.
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.
The Peculiarities of Measuring Bone Density in Males and Females Using Uncertainty Calculation
(2023)
The article discusses the approach to solving the problem of reducing time spent on the preparation of medical images for teaching neural networks, by reducing the time of creating masks for images. The task is considered on the example of processing images of the mucous membrane of the paranasal sinus. The specifics of the task did not allow effectively using existing software solutions. During the study, a software solution was proposed, which made it possible to radically reduce the time of creating masks for images. The article also analyzes the shortcomings of the automated creation of masks, as well as the directions of their solution. The loss of time due to the adjustment of the color palette can be reduced even more to 1-2 minutes, the average deviation is 7.61%.
The research on the new generation mobile networks is currently in the phase of defining the key technologies to make 6G successful. Hereby, the research project 6G NeXt is aiming to provide a tight integration between the communication network, consisting of the radio access as well as backbone network, and processing facilities. By the concept of split computing, the processing facilities are distributed over the entire backbone network, from centralised cloud to the edge cloud at a base station. Based on two demanding use cases, Smart Drones and Hologradic Communication, we investigate a joint communication and compute architecture that will make the application of tomorrow become reality.
Additive manufacturing, also known as 3D printing, has gained tremendous importance in recent years. One of the areas where additive manufacturing is particularly useful is in the fabrication of electrodes. Electrodes are an important component of a wide range of applications, including electrochemistry, biomedical engineering, energy storage, analytics, electronics as well as life sciences. Traditionally, electrodes have been manufactured through costly processes such as etching, electroplating or cutting and milling. Additive manufacturing offers a new way to fabricate electrodes by depositing materials layer by layer (Yap et al., 2015). This opens up new possibilities for designing electrodes with complex geometries and structures that would not be possible using conventional methods. As a result, 3D printed electrodes are gaining interest in fields such as electromobility, water disinfection, manufacturing, and life sciences, which will be presented in this paper.
A conductivity-based, batch-optimized system for analyzing the total of carbon parameter in water
(2023)
In cooperation with the company Purification Membranes Analytics GmbH (PMA), a prototype has been developed that analyzes the total organic carbon (TOC) content of water samples based on a complex conductivity measurement. In the process, a batchoptimized system was developed that delivers qualitative results even in highly polluted waters. This method requires small sample volumes and was assembled using an ultrapure water system, a sample mixing system, various electronic control units and a miniTOC system that uses a UV light source to decompose organic carbons and outputs differential values using two conductivity sensors. During the project, a fully automated prototype was developed and is ready for use. In the future, this method could support common methods and lead to more accurate statements on water quality in a cost-effective manner.
The concept of this thesis is to optimize the manufacturing process of injection moulding tools by using additive manufacturing and thus contribute to environmental protection. For this purpose, the individual steps of the traditional manufacturing process are identified and analysed to determine which steps can be replaced by additive manufacturing. The first step is to clarify which mould components can benefit from additive manufacturing. In particular, the capabilities and limitations of additive manufacturing technologies must be considered.
Furthermore, another focus is on how to optimize the cooling and temperature control of the tools. Potential savings through the use of lightweight or insulating surfaces will be examined. In addition to the technical feasibility, the cost-effectiveness of the concept will also be considered. Finally, the contribution of the concept to the reduction of the environmental impact will be evaluated. In particular, energy savings and the reduction of CO2 emissions are taken into account.
The potential to optimize the injection mould manufacturing process and reduce environmental impact is significant. Using additive manufacturing can be an economic and environmental advantage.
In this paper, different concepts for mixing sample and master mix by means of simulation are discussed. The main focus was on mixers with a low dead volume, because of their relevance to PCR. In addition, a concept for aliquoting the mixed solution was elaborated and simulated. The simulation showed very good mixing with serpentineand tesla-mixers at flow rates of 1-16 µL/s. Furthermore, a uniform distribution with aliquoting could be achieved, while a slight dependence between flow rate and pressure was observed. In the further course, these concepts are to be combined and tested on a microfluidic chip. This can then be integrated into the workflow of existing PCR protocols.
The aim of our study is to develop a new, simple, and effective method for identification of personality based on the characteristics of the sphenoid sinus structure, using machine learning for subsequent implementation into routine medical practice in Ukraine. The study involved 200 multislice computed tomography (MSCT) scans of individuals of various genders and ages. During the study, we obtained results with an accuracy exceeding 70%.
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.
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.
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.
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.
Fabry-Perot (FP) sensors are typically read out using a raster scan to acquire tomographic Photoacoustic (PA) images. To speed up the recording time, wide-field illumination of the sensor in combination with a camera as detector can be used. In this study, an sCMOS camera and wavelengths around 517 nm are used to interrogate a FP sensor with a homogeneous optical thickness over a 4 cm2 aperture. The recorded time series show PA signals are acquired over the entire area of the interrogation beam. The performance of the system, such as the noise equivalent pressure, is evaluated.
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.
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.
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.
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.
Dieser Beitrag schlägt ein Bildverarbeitungsmodell zur automatisierten Bestimmung von Messarealen bei robotergestützten In Vivo Messungen vor. Es wird angenommen, dass moderne Verfahren der Deep-Learning-Objekterkennung in der Lage sind die einzelnen Areale wiederholbar genau genug zu erkennen, um die benötigten Messareale im dreidimensionalen Raum einzupassen. Für das Einpassen werden Tiefeninformationen aus einer stereoskopischen Kamera verwendet. Weiter wird untersucht inwiefern diese Tiefeninformationen als zusätzlicher Eingang für die Deep-Learning-Modelle verwendet werden können. Hierfür wird ein Konzept ausgearbeitet, ein Datensatz erstellt und Modelle zur Objekterkennung in verschiedenen Implementierungen trainiert. Das Verwenden von Tiefeninformationen führt zu einer besseren Generalisierbarkeit der Modelle, insbesondere auf tätowierten Hautarealen. Das Bildverarbeitungsmodell erreicht beim Einpassen der Messareale eine gemittelte Wiederholgenauigkeit bzw. Abweichung von 6, 1 mm bei einer Bildwiederholrate von 2, 3 bis 3, 3 Bildern die Sekunde.
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.
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.
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.
Biomedical photoacoustics is usually used to image absorption-based contrast in soft tissues up to depths of several centimeters and with sub-millimeter resolution. By contrast, measuring Photoacoustic (PA) signals through hard bone tissue shows severe signal degradation due to aberration and high attenuation of high frequency acoustic signal components. This is particularly noticeable when measuring through thicker, human, skull bone. Which is the main reason why transcranial PA imaging in humans has so far proved challenging to implement. To tackle this challenge, we developed an optical resonator sensor based on a previous planar-concave design. This sensor was found to be highly suitable for measuring the low-pressure amplitude and low acoustic frequency signals that are transmitted through human cranial bone. A plano-concave optical resonator sensor was fabricated to provide high sensitivity in the acoustic frequency range of DC to around 2 MHz, a low noise equivalent pressure and a small active element size enabling it to significantly outperform conventional piezoelectric transducers when measuring PA waves transmitted through ex vivo human cranial bones.
We consider maintenance sites for urban rail systems, where unavailable tracks typically require changes to the regular timetable, and often even to the line plan. In this paper, we present an integrated mixed-integer linear optimization model to compute an optimal line plan that makes best use of the available tracks, together with a periodic timetable, including its detailed routing on the tracks within the stations. The key component is a flexible, turn-sensitive event-activity network that allows to integrate line planning and train routing using a track choice extension of the Periodic Event Scheduling Problem (PESP). Major goals are to maintain as much of the regular service as possible, and to keep the necessary changes rather local. Moreover, we present computational results on real construction site scenarios on the S-Bahn Berlin network. We demonstrate that this integrated problem is indeed solvable on practically relevant instances.
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.
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.
Entwicklung einer mobilen automatisierten Prozesserweiterung für einen Etikettierarbeitsplatz
(2023)
Die Corona-Pandemie und der stetig steigende Fachkräftemangel zwingen viele Unternehmen zum Umdenken. Kollaborative Roboter finden immer mehr Einzug in kleine und mittelständische Unternehmen und übernehmen sich wiederholende, nicht ergonomische und monotone Arbeiten und heben das bestehende Personal in ganz neue Verantwortungsaufgaben. Die Automatisierung hält immer mehr Einzug und gewinnt branchenweit deutlich mehr an Bedeutung. In diesem Projekt, entstanden im Rahmen einer Bachelorarbeit [1], wird nach der Klärung der Grundlagen die Implementierung eines kollaborativen Roboters in einem Applizierprozess beschrieben und auf die Schritte von Aufbau bis hin zum funktionierenden, vollautomatischen Prozess eingegangen. Der Cobot wird anhand von mehreren Testszenarien auf seine Funktion hin evaluiert und auf Prozesstauglichkeit erprobt.
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.
The aim of our study was to investigate the impact of insulin resistance on the bone density of the upper wall of the maxillary sinus. Materials and Methods: The study included 100 female participants aged 18 to 44 years, divided into two groups. The first group consisted of individuals with insulin resistance, while the control group comprised individuals without signs of insulin resistance. In each group, we conducted an investigation of the radiological density of the upper wall of the maxillary sinus using uncertainty calculations. Results of the study suggest a potential influence of insulin resistance on the density of bone tissue around the nasal sinuses, specifically the upper wall of the maxillary sinus in our case. This parameter was found to be minimal in the group of individuals with insulin resistance. It is particularly noteworthy that both minimum and maximum bone density decreased in this group. Conclusions. The research focused on how insulin resistance affects the density of the upper wall of the maxillary sinus. By employing uncertainty calculations, the study revealed that insulin resistance is associated with a decrease in the minimum density of the upper wall of the maxillary sinus. This tendency may act as a catalyst for the emergence of significant inflammatory alterations in the nasal sinuses, serving as a foundation for the initiation of complications.
The aim was to implement uncertainty calculation for detecting the negative effects of smoking on the bone density of the paranasal sinus. Materials and Methods: A total of 100 male participants aged 20 to 44 were included in the study and divided into two groups. The first group comprised individuals with minimal harmful habits, while the second group consisted of individuals who had been smoking for at least 10 years, consuming 1 to 2 packs of cigarettes per day. Results Bone density has a negative impact on the bone tissue of the upper wall of the maxillary sinus. The findings suggest that individuals with a pronounced decrease in minimum density, as well as those with a marked difference between minimum and maximum density values, may require heightened medical attention due to potential associations with undiagnosed diseases or specific structural characteristics in the skull. Conclusions. The uncertainty calculation was implemented for the detection of negative effect of smoking on the bone density of paranasal sinuses. The calculated difference between maximum and minimum density during the research suggests significant medical implications, especially considering the heterogeneity of the trabecular bone structure in the skull. Individuals with a marked difference may require heightened medical attention, potentially associated with undiagnosed diseases or specific structural characteristics in the skull.
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.
Durch die Menschzentrierung in der Industrie 5.0 sollten bestehende Ansätze hinterfragt und geprüft werden. Gerade der, durch die Digitalisierung hervorgerufene, Technostress sollte neben dem Fachkräftemangel einen zunehmenden Betrachtungsfaktor im Produktionsumfeld erhalten. Da trotz bisheriger Maßnahmen eine stetige Zunahme von Stress zu verzeichnen ist. Auffällig sind dabei die Arbeitsunfähigkeits-Fehltage, welche im letzten Jahr um weitere 6 % bzw. um 18,2 Fehltage gestiegen sind. Womit durchschnittlich jede Erwerbsperson 3,17 Tage unter der Diagnose „psychische Störung“ krankgeschrieben wurde. Um diesen Trend entgegenzuwirken, betrachtet der Beitrag die Möglichkeiten der Software-Ergonomie, womit die Gestaltung von HMIs (Mensch-Maschinen-Interfaces) den Menschen gezielter berücksichtigt um etwaige Belastungen zu reduzieren. Im Rahmen der komplementären Industrie 4.0 und der einhergehenden Informationsflut, bestimmen immer komplexer werdende Schnittstellen und Bedienoberflächen einen Großteil des Arbeitsalltags. Diese ermöglichen den Anwenderinnen und Anwendern neben einem schnellen Überblick über Maschinendaten, Prozessabläufe und Handlungsempfehlungen die Möglichkeit zur einfachen Bedienung der technischen Anlagen. Der hier vorgestellte Ansatz betrachtet am Beispiel einer Bestandsanlage, wo sich Potenziale in der Stressreduzierung im Bereich der visuellen Benutzerschnittstellen befinden und welche Auswirkungen eine Veränderung der Leitführung ermöglicht. Hierfür wurde eine mehrphasige Studie durchgeführt dessen Ergebnisse im Bereich des Eye-Trackings sowie anhand von Vitalwerten im vorliegenden Beitrag diskutiert werden.
Fabry-Pèrot (FP) interferometer sensors enable highly sensitive backward mode acoustic detection in Photoacoustic (PA) imaging. They are transparent to the excitation wavelength, can be placed directly next to the PA source, and offer a broadband frequency response and high acoustic sensitivity. PA tomography using parallelized detection requires high spatial uniformity of the optical and acoustic properties, which can be hampered by contaminations during fabrication that lead to the formation of inhomogeneities and artefacts. The quality and homogeneity of the dielectric and polymer layers have a direct effect on the maximum optical phase sensitivity, and hence acoustic sensitivity. In this study, cross-sectional images of FP sensors were obtained using focused ion beam milling and ultramicrotomy followed by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) to evaluate different fabrication methods.
Der Produktlebenszyklus von Kleidung ist vor allem durch lange Lieferketten von Niedriglohnländern in Hochlohnländer gekennzeichnet. Die Eliminierung solcher Transportwege könnte dazu führen, dass der komplette Lebenszyklus von Kleidungsware nachhaltiger und umweltfreundlicher wird. Der Aufbau von Produktionsstätten in Hochlohnländern wird aktuell durch technische Herausforderungen des Produktionsprozesses von Kleidung bzw. allgemein biegeschlaffen Materialien verhindert. Aufgrund der Eigenschaften biegeschlaffer Materialien können die Entnahme bzw. definierte Ablage von Textilteilen heutzutage nur teilautomatisiert bzw. mit einem hohen Anteil manueller Tätigkeiten gelöst werden. Das Hydroadhäsive Greifen könnte eine Lösung sein, die oben genannten Prozesse zu automatisieren und die Produktion für Hochlohnländer zu vergünstigen. Jedoch verfügt das Verfahren noch über lange Zykluszeiten und die Haltekräfte sind nicht reproduzierbar. Weiterhin ist die Findung von Einstellparametern sehr zeitaufwendig und komplex. Die Lösung könnte eine intelligente Steuerung sein, dessen Kernstück ein datengetriebenes Modell für die Parameteroptimierung und -findung ist. Im Rahmen der Forschungsarbeiten wird ein Modellansatz zur Optimierung der Taktzeit beim hydroadhäsiven Greifen erarbeitet. Dabei wird die Gewinnung der Datengrundlage, das zu entwickelnde Modell sowie die eigentliche Validierung diskutiert.
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.
Zur Lösung des Problems der Einführung einer Brandfrüherkennung an einer Anlage mit erheblichen Flächen an Wärmestrahlung und Temperaturen um 1.100 Grad Celsius, wird der Einsatz von infraroter und visueller Kameratechnik und Bildverarbeitungssystemen in einer Machbarkeitsstudie erörtert und als Vorlage zur Umsetzung gebracht. Hierfür müssen alle technischen Randbedingungen der baulichen Anlage, die Kosten und auch die organisatorischen Aspekte ermittelt und bewertet werden. Auf Basis von Störfallszenarien wurden Brandversuche durchgeführt und in thermographischer und visueller Bildgebung ausgewertet. Entscheidend war die signifikante Abgrenzung eines Feuers vom anlagenspezifischen ungestörten Zustand.
Individualisierbare, webbasierte Benutzerschnittstelle zur Überwachung von Industrieprozessen
(2023)
Im Rahmen eines Projektes zur Applikation der Präskriptiven Analytik für die dynamische Prozessführung von intelligenten Kälteanlagen wurde eine webbasierte Software mit einer anwenderfreundlichen und individualisierbaren Benutzerschnittstelle zur Überwachung und Regelung umgesetzt. Als Teilprojekt wurde ein Softwarepaket entwickelt, welches eine konfigurierbare Anlagenvisualisierung für diese Benutzerschnittstelle umsetzt. Beim Entwurf und der Implementierung der Software wurde auf einen modularen Aufbau geachtet, sodass die Software leicht erweiterbar und aus auswechselbaren, unabhängigen Komponenten zusammengesetzt ist.
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.
According to the drinking water regulation, drinking water systems must be tested for harmful contamination at specified intervals. To meet the legal requirements and save costs and time, a portable analysis method is to be developed. For this purpose, a concept study was conducted. It describes a portable measuring device for the quantitative detection of legionella using real-time PCR. The study includes the construction elements and conditions that are necessary for the collection, processing, and evaluation of the sample. It was found that commercially available PCR systems do not meet the size requirements and can only be represented by an in-house development. In addition, a microfluidic system must be developed that is designed for one-time use and low production cost.
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.
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.
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.
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.
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.
The new coronavirus COVID-19 has been spreading worldwide for almost three years. The global community has developed effective measures to contain and control the pandemic. However, new factors are emerging that are driving the dynamics of COVID-19. One of these factors was the escalation of Russia's war in Ukraine. This study aims to test the hypothesis of the influence of migration flows caused by the Russian war in Ukraine on the dynamics of the epidemic process in Germany. For this, a model of the COVID-19 epidemic process was built based on the polynomial regression method. The model's adequacy was tested 30 days before the start of the escalation of the Russian war in Ukraine. To assess the impact of the war on the dynamics of COVID-19, the model was used to calculate the forecast of cumulative new and fatal cases of COVID-19 in Germany in the first 30 days after the start of the escalation of the Russian war in Ukraine. Modeling showed that migration flows from Ukraine are not a critical factor in the growth of the dynamics of the incidence of COVID-19 in Germany, but they influenced the number of cases. The next stage of the study is the development of more complex models for a detailed analysis of population dynamics, identifying factors influencing the epidemic process in the context of the Russian war in Ukraine, and assessing their information content.
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.
Die Verkehrswende bedingt einen Ausbau des Schienen-Personenverkehrs. Eine in situ Schadenserkennung während des Betriebs kann einen Beitrag zur Kapazitätserhöhung und Sicherheit im Schienenverkehr liefern. Im Vortrag werden Forschungen bezüglich einer schwingungsbasierten, zerstörungsfreien Methode zur Detektion von Radreifenschäden vorgestellt. Über eine Transferpfadanalyse (TPA) wird auf den Körperschall jedes Rades während der Überfahrt rückberechnet. Mit dem synthetisierten Körperschall wird mittels des akustischen Resonanztests die Schadensidentifikation durchgeführt.
Der Fachkräftemangel im Gesundheitssektor beschleunigt die Digitalisierung, wodurch die Anforderungen an das Personal steigen. Die zunehmenden technischen Möglichkeiten verändern die notwendigen Kompetenzen an die Ärzte in Richtung Digitalisierung. Daher sollten im Personal-Recruitment digitale Kompetenzen bereits in den Stellenausschreibungen berücksichtigt werden, um die zukünftigen Herausforderungen bewältigen zu können. Dieser Beitrag untersucht, inwieweit a) digitale Kompetenzen bereits in den am Markt befindlichen Stellenprofilen von Ärzten Eingang gefunden haben und b) ob diese durch einen datengetriebenen methodischen Ansatz sinnvoll extrahiert werden können. Dabei werden 1707 Stellenanzeige mit der Latent Semantic Analysis (LSA) ausgewertet. Die unterschiedlichen methodischen Ansätze innerhalb der LSA zeigen, dass kaum ein Fokus auf digitale Kompetenzen im Gesundheitssektor bei Stellenausschreibungen besteht.
Zur Herstellung von langfristig stabilen Metall-Kautschuk-Verbunden sind chemische Haftvermittler notwendig. Nach Auftrag dieser wird Kautschuk mittels Gummispritzgießen auf die metallischen Grundkörper aufgebracht. In Klein- und Kleinstserien kann der Haftvermittler in präzisen Volumina händisch mit Hilfe eines Fluid-Dispensers aufgetragen werden. Allerdings verhindert dies eine Homogenität und Gleichheit der Schichtdicke, wodurch die Zuverlässigkeit und Stärke der Haftung variieren können. Als technische Lösung wurde ein Pipettierroboter avisiert. Mit Hilfe mehrerer mechanischer und elektrischer Adaptionen – so auch einer neuen Steuerungstechnik – wurden verschiedene Fluid-Dispenser auf 3-Achs-Portalfräsen integriert. Somit konnte die volle Funktionsfähigkeit erreicht werden.
Das Ziel des Projekts ist, den Zustand der Haut von Neurodermitis-Patienten bei verschiedenen Bedingungen und Belastungszuständen erfassen zu können. Dazu wurde ein Prototyp gefertigt, in den ein Mikrosensor zur Bestimmung der Umgebungsfeuchtigkeit, ein Controller mit Bluetooth zur Datenübertragung, sowie ein Lithium-Akku zur Energieversorgung verbaut wurden.
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.
Die Programmierung von SPS-Systemen erfolgt hauptsächlich händisch, obwohl große Teile des Programmcodes sehr ähnlich sind und sich häufig nur durch die eingesetzten Variablen unterscheiden. Der Beitrag befasst sich mit der Entwicklung und Testung einer Codegenerierungssoftware für das TIA Portal, um den Zeitaufwand der Programmierung zu reduzieren und Flüchtigkeitsfehler zu vermeiden.
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.
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.
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.
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.
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.
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.
Model based Configuration of Platforms for Managing Cross- Organizational (Business) Processes
(2022)
In this contribution interoperability is considered from the perspective of platforms, which have to manage cross-organisational business processes. A model-based approach for configuring a cloud platform for managing complex processes and their dependencies across different organisations is provided. The approach is applied on using FIWARE, which provides a framework of open source software platform components. The core concept is to extend the open source core data model of FIWARE by using the artefacts of an Enterprise model, describing the dependencies of processes, roles, object data and application interfaces. Based on a given use case the principal configuration was applied and validated.
Das Ziel dieses Projektes war es eine automatisierte Lösung für das Auftragen von Haftvermittlern auf metallische Grundkörper im Nanoliterbereich zu ermöglichen. Für die automatisierte Auftragung von Haftvermittler wurde eine neue Steuerungseinheit auf Grundlage eines Mainboards für die Ansteuerung von 3D-Druckern verwendet, als Firmware diente Marlin. Notwendig waren Anpassungen im Bereich der Motorströme, Geschwindigkeiten, Beschleunigung, Sensitivität, Druckbettgröße und Auswahl von Mainboard und Display. Für die Verfahrwege wurde G-Code mittels eines Programms in Python generiert. Für eine homogene und gleichmäßige Benetzung werden die einzelnen zu benetzenden Objekte angefahren und der Pipettiervorgang gesteuert. Es war möglich die vollständige Funktionsfähigkeit herzustellen.
New technologies leading to better and more efficient light emitting diodes. The emitted radiation reaches higher energy levels and lower wavelengths especially in the UV-C spectrum. UV-C light has a cancer inducing effect on human cells. Therefore it is necessary to work in a safe way with those devices.
This work is focused on an open-source solution for rapid 3D printing of an safe UV-C radiation measuring device. Especially for research groups or universities which can not afford big safety labs.
After modeling and printing the prototype, a series of tests has shown the functionality of that UV-C Diode test system. By using black printing filaments and infill rates over 50 %, the transmission of light could be prevented and the system worked well.
Industrie 4.0 Ansätze haben sich in der fertigenden Industrie vielerorts etabliert. Big Data, IIoT und Künstliche Intelligenz (KI) ermöglichen neue Geschäftsmodelle und wirken sich dadurch auch verändernd auf Produktionssysteme aus. Mit dem Begriff der Industrie 5.0 formuliert sich ein menschzentrierter Ansatz. Die Praxisrelevanz dieser und ähnlicher Innovationen hängt maßgeblich davon ab, wie derartige Einsatzmöglichkeiten neuer, digitaler Technologien in die bestehenden Unternehmensstrukturen Einzug halten. Hierbei kommt es also auf Transfer und Akzeptanz neuer Technologien an. Digitalisierung gestaltet sich somit als sozio-technisches Problem. Dieser Beitrag gibt Einblick in aktuell verfolgte Transferansätze für Digitalisierung im Mittelstand und leistet einen Teil zu Theoriebildung, als dass er auch einen Ausblick auf weitere Aktivitäten in dem Umfeld liefert.
There are already several tools available to generate traffic demand for the microscopic simulation suite SUMO. This paper focuses on setting up a simulation scenario for the peak hour in a small conurbation when there are vehicle counts available for the major streets. We describe tools which are part of SUMO or available as open source and compare their results with the real traffic counts as well as with the outcome of countless demand generation.
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.
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.
The article discusses the approach to solving the problem of reducing time spent on the preparation of medical images for teaching neural networks, by reducing the time of creating masks for images. The task is considered on the example of processing images of the mucous membrane of the paranasal sinus. The specifics of the task did not allow effectively using existing software solutions. During the study, a software solution was proposed, which made it possible to radically reduce the time of creating masks for images. The article also analyzes the shortcomings of the automated creation of masks, as well as the directions of their solution. The loss of time due to the adjustment of the color palette can be reduced even more to 1-2 minutes, the average deviation is 7.61%.
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.
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.
The most common cause of incidents and accidents in aviation is linked to the category “Loss of Control Inflight” [1]. Remarkably in consequence this means that aircraft without any technical defect or such with manageable defects according to certification requirements are involved. The research project “Virtual Instructor for General Aviation” (VIGA) was aimed to validate an idea that addresses this problem by an entirely different approach. The idea can be best described by looking at the way a flight instructor takes decisions to intervene. A human pilot has an expectation of the maneuvers and the corresponding trajectories that can be flown in the future based on the present flight conditions. Decision making is based on the analysis of the consequences of the expectations. This approach is one of the key principles of the project, and is completely different to any known AFCS system.
Yet technical implementation requires considerable effort. Essentially it comprises a faster than real time simulation with an adequately accurate aerodynamic model of the particular aircraft in combination with a module to evaluate the results of the simulated exit trajectories. In consequence this idea requires an autopilot module capable of tracking the calculated three-dimensional trajectories which then resulted in the need to design and develop a completely new type of autopilot algorithm.
The objective of this project was to test and demonstrate principle functionality thereby also finding pathways determining future developments as well as to analyze system behavior. Therefore, the project was deliberately designed to help the pilot by depicting the solutions on the PFD. Direct intervention of the system with aircraft flight controls did not take place. This also raised the question of how to design an effective visual human interface.
Fortunately, all results proved to be very satisfying. The underlying idea could be validated and was demonstrated both in a simulation environment and in flight test. The path tracking algorithm was developed in a parallel project and also showed very satisfactory results, meeting all requirements.
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.
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.
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.