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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.
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.
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.
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 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%.
Background. There are many questions regarding the peculiarities of the course of odontogenic maxillary sinusitis, the likelihood of complications and the correct dosage of load during dental implantation. Purpose – to identify changes in minimal bone density in chronic odontogenic maxillary sinusitis and to compare it with chronic rhinogenic catarrhal maxillary sinusitis and physiological state of maxillary sinus. Materials and Methods. Our study involved 10 patients with chronic odontogenic maxillary sinusitis, 10 patients with chronic maxillary non-polyposis sinusitis of rhinogenic etiology, combined with hyperplasia of the sinus mucosa up to 1 cm. The control group comprised 10 patients with physiological condition of maxillary sinuses. In all subjects minimal bone density of superior, medial and inferior walls of maxillary sinus was analyzed. Results. The study showed that the maximum in physiological conditions is the minimal density of the upper wall of the maxillary sinus, the minimum is the lower wall. The minimal density of the lower wall was shown to undergo a statistically significant reduction in chronic catarrhal maxillary sinusitis only by 2%, the upper by 5%, the medial by 4% compared with the intact sinus, but with the odontogenic nature of maxillary sinusitis, this figure was 31% in the lower wall, 27% in the medial region. Only the density of the upper wall of the maxillary sinus remained quite stable, it decreased relative to the physiological one only by 6%. Conclusions. Minimal physiological densitometric parameters of lower, medial and upper walls were calculated. The reduction of minimal density of bone tissue in the cases of rhinogenic chronic catarrhal maxillary sinusitis. In the cases of chronic odontogenic maxillary sinusitis, maximum significant decrease of minimal density of both lower and medial walls is determined.
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%.
Evaluation of medical images is of key importance in the work of medical staff today. Especially this problem pays important role in otolaryngology.
The aim of our work was to develop an automatic complex method for assessing the state of the human paranasal sinuses.
Our research included 10 people of different sex and age, who were divided into groups, taking into account the recommendations of the WHO for 2019-2021. The structure of the mucous membrane of the maxillary sinus were calculated and compared.
In the course of our research, an algorithm was developed for the automatic assessment of the state of the mucous membrane of the maxillary sinus and its bone walls according to the data of the spiral computed tomography. The difference between obtained data in the manual and automatic mode is minimal.
Solutions to the 3D Model Problem of Pressure Measurement in the Area of Maxillary Sinus Anastomosis
(2020)
The ostiomeatal complex (OMC) is a key area that determines the occurrence of inflammatory processes in the paranasal sinuses (PNSs). The aim of our work was to develop a procedure for studying the OMC components in the preoperative period that allows for identification the impact of anatomical peculiarities on change of physiological pressure in the maxillary sinus. Materials and methods: The study was carried out on the basis of the otorhinolaryngological department of Kharkiv Regional Clinical Hospital in 2019-2020. It involved 100 patients of both sexes aged 20-59 years with chronic non-polyposis maxillary sinusitis. Results: The sizes of the uncinate process, the middle turbinate and the natural anastomosis were determined using the calculation of uncertainty. Basing on the data obtained, all the patients were divided into three groups. Conclusions: Changes in the size of the natural anastomosis (both an increase and its narrowing) lead to changes in pressure in the area of the anastomosis, and a decrease in ventilation in the paranasal sinuses. SCT study with subsequent 3D modeling is an informative, accurate and effective method for assessment of OMC and PNSs condition. It allows surgeons to presume the method and volume of surgery as early as at the preoperative stage, without resorting to invasive research methods.
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.
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.
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.
FrostByte Dataset
(2021)
It is with great pleasure that we announce the release of the “Frost Byte” dataset. The dataset was collected during research on fault detection and diagnosis (FDD) approaches and their transferability to heterogeneous systems of industrial refrigeration systems at the Technical University of Applied Sciences Wildau. The data collection took place between 2018 and 2019 and is intended to supplement the ASHRAE 1043-RP dataset (Comstock & Braun, 1999), which has been the only publicly available data source in this area to date. For comparison purposes, the method of data collection was chosen similarly, whereby this dataset collection was carried out using a ~ 100 kW refrigeration capacity ammonia system with plate heat exchangers.
The dataset contains steady-state data equally sampled from five classes:
1. Normal (fault-free operating condition)
2. Reduced Condenser Water Flow
3. Reduced Evaporator Water Flow
4. Non-Condensable Gases
5. Refrigeration Leak
Each class was investigated under changing operational conditions and varying fault severity levels (SL).
The MAC end-station at the ELI Beamlines facility is a multipurpose user's station for atomic, molecular, and optical sciences and coherent diffractive imaging. The technical design of the station, the available instruments, and an overview of the whole beamline have been published in Eur. Phys. J. Spec. Top. 230, 4183 (2021). Here, we address ongoing upgrades of the MAC end-station that will provide users with advanced capabilities for beam manipulation and electron/ion detection. The upgrades include (i) the installation of a beam preparation chamber in front of the MAC chamber, (ii) a magnetic bottle electron spectrometer with high collection and detection efficiency and high energy resolution, and (iii) an event-driven TPX3CAM detector for velocity map imaging spectrometer, which provides both spatial and temporal information for each pixel. We present results from the first commissioning measurements with these instruments, confirming their performance for state-of-the-art experiments in atomic, molecular, and optical sciences.
The application of a biocompatible polymer nanocarrier can provide target delivery to tumor tissues, improved pharmacokinetics, controlled drug release, etc. Therefore, the proposed strategy was to use the water-soluble star-like copolymers with a Dextran core and Poly(N-isopropylacrylamide) grafts (D-g-PNIPAM) for conjugation with the widely used chemotherapy drugs in oncology–Cisplatin (Cis-Pt) and Doxorubicin (Dox). The molecular characteristics of the copolymer were received using size-exclusion chromatography. The physicochemical characterization of the D-g-PNIPAM-Cis-Pt (or Dox) nanosystem was conducted using dynamic light scattering and FTIR spectroscopy. Using traditional biochemical methods, a comparative analysis of the enhancement of the cytotoxic effect of free Cis-Pt and Dox in combination with D-g-PNIPAM copolymers was performed in cancer cells of the Lewis lung carcinoma line, which are both sensitive and resistant to Dox; in addition, the mechanism of their action in vitro was evaluated.
In modern electrochemical coating technology, it is common practice to create uniform layers. However, this study focuses on the deposition of non-uniform layers achieved through a deliberate arrangement of micro structured electrodes on the anode side. The "dog bone effect” was employed as the primary approach [1]. When electroplating on an otherwise uniform surface, this effect selectively processes an area influenced by the geometric edge effect (figure 1 left). The coating within this area is intended to be (i) unevenly distributed and (ii) non-reproducible. Process data was obtained through electrochemical simulations and subsequently applied to a specially designed micro-galvanic setup. This enabled the production of suitable micro structured anodes, validation of coating parameters, and the deposition of visually imperceptible structured areas with inhomogeneous properties using "adhesive gold" on appropriate substrates such as silver and nickel. The layers and their local topography were characterized and analyzed using confocal laser microscopy, X-Ray fluorescence analysis (XRF), as well as a self-designed and constructed laser interference device. As a result, this specific galvanic process technology successfully produced metallic layers that (i) cannot be visually confirmed by the naked eye, (ii) exhibit varied microstructural anode geometries, (iii) display unique differences in layer thickness, (iv) possess non-reproducible and chaotic topographies, and (v) can be detected and identified using conventional analysis techniques or a simple interference setup.
Blood sampling as well as sample preparation are time consuming and requires a strict procedure, which is generally performed by medical trained personal. Not carrying out the procedure correctly could result in an infection of the patient or contamination of the sample itself. These limitations should be especially considered in case of pandemic outbreaks. In order to handle such a high number of patients a novel sample preparation system paired with modern blood sampling procedure is necessary. For this reason, a new device for blood sampling and preparation is designed containing an integrated microfluidic system. The fabrication is carried out by utilizing micro moulding of PDMS as well as micro milling. A first set of initial experiments as part of a first-generation study shows promising results. However, further steps of optimisation considering flow time and preparation cycle are part of a second-generation study.
The current state of technology for 3D printing with biomaterials is based on the extrusion of viscous materials. Mostly, extrusion heads utilize pneumatic pressure systems or stepper motors to force the substrate onto a surface. These methods are well developed for high viscouse materials. However, processing low viscous liquids may cause leakages in the system. This could be solved by applying continuous extrusion. Additionally, in order to process gelable substrates, such as gelatine and agar, tempered print heads in combination with a multi stage tempering system are required to prevent the system from clogging. The ongoing work presented in this paper focuses on the development of an extrusion system, which should be able to process multiple viscosities of gelatine sequentially. In order to achieve this, several measurements to examine the properties, as well as the material parameters of different biomaterials are performed. In this process gel point, force resistance and elasticity are the factors of particularly interest. Due to their ability to gel and their availability, the most relevant biomaterials are gelatine and agar. Using this data, an extrusion system involving a peristaltic pump, a heated tube and a nozzle, has been developed. The next step envisaged is to calibrate the extruder based on the obtained data and finally to validate the printing process by printing simple geometric structures. Assuming that a positive evaluation is obtained, the printing system will be tested for printing first organic test structures from patient data using the examined biomaterials.
Over the course of the last decade 3D printing has become a more established technology in terms of prototype development (rapid prototyping). The current effort is focused on transferring this knowhow into a product driven approach in order to manufacture even small batch sizes more economic. In terms of this work, this idea is adapted for the development of injection molds (rapid manufacturing). Hereby, a hardened polymer is used to create a forming cavity instead of tool-steel. In order to fulfil the mechanical process requirements of micro injection molding such as form stability under temperature and pressure this cavity is nevertheless integrated into a metal housing. A first set of experiments has been carried out using this develop mold to verify the capabilities of the developed prototype as well as molding process. Based on these first results, an optimization is carried out to improve the next iteration of this molding tool.
Processing biological materials with 3-dimensional (3D) printers has attracted increasing interest in several research areas. At the same time, off-the-shelf solutions are increasingly available in a wider variety to meet the current market demand. However, most of the available bioprinters are closed source, thus, modifications are quite challenging or require an avoidable consultation process with the manufacturer. Furthermore, the entry prices for basic machines amount to several thousands of euros. Whereas, high-end 3D bio printers with a vast array of features are available for several hundred thousand euros. Due to the immense potential of this tool in the field of biotechnology it is important to extend the availability of this technology for research purposes in terms of adaptability and price. This ongoing work focuses on open-source 3D printer heads with the ability to extrude biological materials. The print heads include several techniques to process low as well as high viscose biomaterials such as agar and gelatin. Additionally, obstacles such as continuous substrate tempering or integration into existing 3D printers are addressed. The work presented is open source and thus freely adaptable to any user’s specific needs. Our goal is to process a diverse range of biomaterials with different print techniques.