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The rail business is challenged by long product life cycles and a broad spectrum of assembly groups and single parts. When spare part obsolescence occurs, quick solutions are needed. A reproduction of obsolete parts is often connected to long waiting times and minimum lot quantities that need to be purchased and stored. Spare part storage is therefore challenged by growing stocks, bound capital and issues of part ageing. A possible solution could be a virtual storage of spare parts which will be 3D printed through additive manufacturing technologies in case of sudden demand. As mechanical properties of additive manufactured parts are neither guaranteed by machine manufacturers nor by service providers, the utilization of this relatively young technology is impeded and research is required to address these issues. This paper presents an examination of mechanical properties of specimens manufactured from stainless steel through the selective laser melting (SLM) process. The specimens were produced in multiple batches. This paper interrogates the question if the test results follow a normal distribution pattern and if mechanical property predictions can be made. The results will be put opposite existing threshold values provided as the industrial standard. Furthermore, probability predictions will be made in order to examine the potential of the SLM process to maintain state-of-the-art mechanical property requirements.
The pharmacokinetics and metabolism of diclofenac in chimeric humanized and murinized FRG mice
(2018)
The pharmacokinetics of diclofenac were investigated following single oral doses of 10 mg/kg to chimeric liver humanized and murinized FRG and C57BL/6 mice. In addition, the metabolism and excretion were investigated in chimeric liver humanized and murinized FRG mice. Diclofenac reached maximum blood concentrations of 2.43 ± 0.9 µg/mL (n = 3) at 0.25 h post-dose with an AUCinf of 3.67 µg h/mL and an effective half-life of 0.86 h (n = 2). In the murinized animals, maximum blood concentrations were determined as 3.86 ± 2.31 µg/mL at 0.25 h post-dose with an AUCinf of 4.94 ± 2.93 µg h/mL and a half-life of 0.52 ± 0.03 h (n = 3). In C57BL/6J mice, mean peak blood concentrations of 2.31 ± 0.53 µg/mL were seen 0.25 h post-dose with a mean AUCinf of 2.10 ± 0.49 µg h/mL and a half-life of 0.51 ± 0.49 h (n = 3). Analysis of blood indicated only trace quantities of drug-related material in chimeric humanized and murinized FRG mice. Metabolic profiling of urine, bile and faecal extracts revealed a complex pattern of metabolites for both humanized and murinized animals with, in addition to unchanged parent drug, a variety of hydroxylated and conjugated metabolites detected. The profiles in humanized mice were different to those of both murinized and wild-type animals, e.g., a higher proportion of the dose was detected in the form of acyl glucuronide metabolites and much reduced amounts as taurine conjugates. Comparison of the metabolic profiles obtained from the present study with previously published data from C57BL/6J mice and humans revealed a greater, though not complete, match between chimeric humanized mice and humans, such that the liver humanized FRG model may represent a model for assessing the biotransformation of such compounds in humans.
Motivation-based Learning: Teaching Fundamentals of Electrical Engineering with an LED Spinning Top
(2018)
Many efforts are made worldwide to establish magnetic fluid hyperthermia (MFH) as a treatment for organ-confined tumors. However, translation to clinical application hardly succeeds as it still lacks of understanding the mechanisms determining MFH cytotoxic effects. Here, we investigate the intracellular MFH efficacy with respect to different parameters and assess the intracellular cytotoxic effects in detail. For this, MiaPaCa-2 human pancreatic tumor cells and L929 murine fibroblasts were loaded with iron-oxide magnetic nanoparticles (MNP) and exposed to MFH for either 30 min or 90 min. The resulting cytotoxic effects were assessed via clonogenic assay. Our results demonstrate that cell damage depends not only on the obvious parameters bulk temperature and duration of treatment, but most importantly on cell type and thermal energy deposited per cell during MFH treatment. Tumor cell death of 95% was achieved by depositing an intracellular total thermal energy with about 50% margin to damage of healthy cells. This is attributed to combined intracellular nanoheating and extracellular bulk heating. Tumor cell damage of up to 86% was observed for MFH treatment without perceptible bulk temperature rise. Effective heating decreased by up to 65% after MNP were internalized inside cells.
Magnetic nanoparticles (MNPs) are used as therapeutic and diagnostic agents for local delivery of heat and image contrast enhancement in diseased tissue. Besides magnetization, the most important parameter that determines their performance for these applications is their magnetic relaxation, which can be affected when MNPs immobilize and agglomerate inside tissues. In this letter, we investigate different MNP agglomeration states for their magnetic relaxation properties under excitation in alternating fields and relate this to their heating efficiency and imaging properties. With focus on magnetic fluid hyperthermia, two different trends in MNP heating efficiency are measured: an increase by up to 23% for agglomerated MNP in suspension and a decrease by up to 28% for mixed states of agglomerated and immobilized MNP, which indicates that immobilization is the dominant effect. The same comparatively moderate effects are obtained for the signal amplitude in magnetic particle spectroscopy.
Impaired cerebral autoregulation and neurovascular coupling (NVC) contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). Retinal vessel analysis (RVA) allows non-invasive assessment of vessel dimension and NVC hereby demonstrating a predictive value in the context of various neurovascular diseases. Using RVA as a translational approach, we aimed to assess the retinal vessels in patients with SAH. RVA was performed prospectively in 24 patients with acute SAH (group A: day 5–14), in 11 patients 3 months after ictus (group B: day 90 ± 35), and in 35 age-matched healthy controls (group C). Data was acquired using a Retinal Vessel Analyzer (Imedos Systems UG, Jena) for examination of retinal vessel dimension and NVC using flicker-light excitation. Diameter of retinal vessels—central retinal arteriolar and venular equivalent—was significantly reduced in the acute phase (p < 0.001) with gradual improvement in group B (p < 0.05). Arterial NVC of group A was significantly impaired with diminished dilatation (p < 0.001) and reduced area under the curve (p < 0.01) when compared to group C. Group B showed persistent prolonged latency of arterial dilation (p < 0.05). Venous NVC was significantly delayed after SAH compared to group C (A p < 0.001; B p < 0.05). To our knowledge, this is the first clinical study to document retinal vasoconstriction and impairment of NVC in patients with SAH. Using non-invasive RVA as a translational approach, characteristic patterns of compromise were detected for the arterial and venous compartment of the neurovascular unit in a time-dependent fashion. Recruitment will continue to facilitate a correlation analysis with clinical course and outcome.
Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.
In this work, a spore-based biosensor is evaluated to monitor the microbicidal efficacy of sterilization processes applying gaseous hydrogen peroxide (H2O2). The sensor is based on interdigitated electrode structures (IDEs) that have been fabricated by means of thin-film technologies. Impedimetric measurements are applied to study the effect of sterilization process on spores of Bacillus atrophaeus. This resilient microorganism is commonly used in industry to proof the sterilization efficiency. The sensor measurements are accompanied by conventional microbiological challenge tests, as well as morphological characterizations with scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The sensor measurements are correlated with the microbiological test routines. In both methods, namely the sensor-based and microbiological one, a tailing effect has been observed. The results are evaluated and discussed in a three-dimensional calibration plot demonstrating the sensor's suitability to enable a rapid process decision in terms of a successfully performed sterilization.
After a liver tumor intervention the medical doctor has to compare both pre and postoperative CT acquisitions to ensure that all carcinogenic cells are destroyed. A correct assessment of the intervention is of vital importance, since it will reduce the probability of tumor recurrence. Some methods have been proposed to support the medical doctors during the assessment process, however, all of them focus on secondary tumors. In this paper a tool is presented that enables the outcome validation for both primary and secondary tumors. Therefore, a multiphase registration (preoperative arterial and portal phases) followed by a registration between the pre and postoperative CT images is carried out. The first registration is in charge of the primary tumors that are only visible in the arterial phase. The secondary tumors will be incorporated in the second registration step. Finally, the part of the tumor that was not covered by the necrosis is quantified and visualized. The method has been tested in 9 patients, with an average registration error of 1.41 mm.
BACKGROUND: Muscle stretch reflexes are widely considered to beneficially influence joint stability and power generation in the lower limbs. While in the upper limbs and especially in the muscles surrounding the shoulder joint such evidence is lacking. OBJECTIVE: To quantify the electromyographical response in the muscles crossing the shoulder of specifically trained overhead athletes to an anterior perturbation force. METHODS: Twenty healthy male participants performed six sets of different external shoulder rotation stretches on an isokinetic dynamometer over a range of amplitudes and muscle pre-activation moment levels. All stretches were applied with a dynamometer acceleration of 10,000∘/s2 and a velocity of 150∘/s. Electromyographical response was measured via sEMG. RESULTS: Consistent reflexes were not observed in all experimental conditions. The reflex latencies revealed a significant muscle main effect (F (2,228) = 99.31, p< 0.001; η2= 0.466; f= 0.934) and a pre-activation main effect (F (1,228) = 142.21, p< 0.001; η2= 0.384; f= 1.418). The stretch reflex amplitude yielded a significant pre-activation main effect (F (1,222) = 470.373, p< 0.001; η2= 0.679; f= 1.454). CONCLUSION: Short latency muscle reflexes showed a tendency to an anterior to posterior muscle recruitment whereby the main internal rotator muscles of the shoulder revealed the most consistent results.
Slot die coating is applied to deposit thin and homogenous films in roll-to-roll and sheet-to-sheet applications. The critical step in operation is to choose suitable process parameters within the process window. In this work, we investigate an upper limit for stripe coatings. This maximum film thickness is characterized by stripe merging which needs to be avoided in a stable process. It is shown that the upper limit reduces the process window for stripe coatings to a major extent. As a result, stripe coatings at large coating gaps and low viscosities are only possible for relatively thick films. Explaining the upper limit, a theory of balancing the side pressure in the gap region in the cross-web direction has been developed.
In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted.
This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the
system’s resilience can be engineered
To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
Resilience as a concept has found its way into different disciplines to describe the ability of an individual or system to withstand and adapt to changes in its environment. In this paper, we provide an overview of the concept in different communities and extend it to the area of mechanical engineering. Furthermore, we present metrics to measure resilience in technical systems and illustrate them by applying them to load-carrying structures. By giving application examples from the Collaborative Research Centre (CRC) 805, we show how the concept of resilience can be used to control uncertainty during different stages of product life.
The overall energy efficiency of ventilation systems can be improved by considering not only single components, but by considering as well the interplay between every part of the system. With the help of the method "TOR" ("Technical Operations Research"), which was developed at the Chair of Fluid Systems at TU Darmstadt, it is possible to improve the energy efficiency of the whole system by considering all possible design choices programmatically. We show the ability of this systematic design approach with a ventilation system for buildings as a use case example.
Based on a Mixed-Integer Nonlinear Program (MINLP) we model the ventilation system. We use binary variables to model the selection of different pipe diameters. Multiple fans are model with the help of scaling laws. The whole system is represented by a graph, where the edges represent the pipes and fans and the nodes represents the source of air for cooling and the sinks, that have to be cooled. At the beginning, the human designer chooses a construction kit of different suitable fans and pipes of different diameters and different load cases. These boundary conditions define a variety of different possible system topologies. It is not possible to consider all topologies by hand. With the help of state of the art solvers, on the other side, it is possible to solve this MINLP.
Next to this, we also consider the effects of malfunctions in different components. Therefore, we show a first approach to measure the resilience of the shown example use case. Further, we compare the conventional approach with designs that are more resilient. These more resilient designs are derived by extending the before mentioned model with further constraints, that consider explicitly the resilience of the overall system. We show that it is possible to design resilient systems with this method already in the early design stage and compare the energy efficiency and resilience of these different system designs.
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
The UN sets the goal to ensure access to water and sanitation for all people by 2030. To address this goal, we present a multidisciplinary approach for designing water supply networks for slums in large cities by applying mathematical optimization. The problem is modeled as a mixed-integer linear problem (MILP) aiming to find a network describing the optimal supply infrastructure. To illustrate the approach, we apply it on a small slum cluster in Dhaka, Bangladesh.
Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data.
On obligations in the development process of resilient systems with algorithmic design methods
(2018)
Advanced computational methods are needed both for the design of large systems and to compute high accuracy solutions. Such methods are efficient in computation, but the validation of results is very complex, and highly skilled auditors are needed to verify them. We investigate legal questions concerning obligations in the development phase, especially for technical systems developed using advanced methods. In particular, we consider methods of resilient and robust optimization. With these techniques, high performance solutions can be found, despite a high variety of input parameters. However, given the novelty of these methods, it is uncertain whether legal obligations are being met. The aim of this paper is to discuss if and how the choice of a specific computational method affects the developer’s product liability. The review of legal obligations in this paper is based on German law and focuses on the requirements that must be met during the design and development process.
The continuing growth of scientific publications raises the question how research processes can be digitalized and thus realized more productively. Especially in information technology fields, research practice is characterized by a rapidly growing volume of publications. For the search process various information systems exist. However, the analysis of the published content is still a highly manual task. Therefore, we propose a text analytics system that allows a fully digitalized analysis of literature sources. We have realized a prototype by using EBSCO Discovery Service in combination with IBM Watson Explorer and demonstrated the results in real-life research projects. Potential addressees are research institutions, consulting firms, and decision-makers in politics and business practice.
Because of customer churn, strong competition, and operational inefficiencies, the telecommunications operator ME Telco (fictitious name due to confidentiality) launched a strategic transformation program that included a Business Process Management (BPM) project. Major problems were silo-oriented process management and missing cross-functional transparency. Process improvements were not consistently planned and aligned with corporate targets. Measurable inefficiencies were observed on an operational level, e.g., high lead times and reassignment rates of the incident management process.
Malaria infection remains a significant risk for much of the population of tropical and subtropical areas, particularly in developing countries. Therefore, it is of high importance to develop sensitive, accurate and inexpensive malaria diagnosis tests. Here, we present a novel aptamer-based electrochemical biosensor (aptasensor) for malaria detection by impedance spectroscopy, through the specific recognition between a highly discriminatory DNA aptamer and its target Plasmodium falciparum lactate dehydrogenase (PfLDH). Interestingly, due to the isoelectric point (pI) of PfLDH, the aptasensor response showed an adjustable detection range based on the different protein net-charge at variable pH environments. The specific aptamer recognition allows sensitive protein detection with an expanded detection range and a low detection limit, as well as a high specificity for PfLDH compared to analogous proteins. The specific feasibility of the aptasensor is further demonstrated by detection of the target PfLDH in human serum. Furthermore, the aptasensor can be easily regenerated and thus applied for multiple usages. The robustness, sensitivity, and reusability of the presented aptasensor make it a promising candidate for point-of-care diagnostic systems.
The chemical imaging sensor is a semiconductor-based chemical sensor capable of visualizing pH and ion distributions. The spatial resolution depends on the lateral diffusion of photocarriers generated by illumination of the semiconductor substrate. In this study, two types of optical setups, one based on a bundle of optical fibers and the other based on a binocular tube head, were developed to project a hybrid illumination of a modulated light beam and a ring-shaped constant illumination onto the sensor plate. An improved spatial resolution was realized by the ring-shaped constant illumination, which suppressed lateral diffusion of photocarriers by enhanced recombination due to the increased carrier concentration.
Synthetic mimics of natural high-performance structural materials have shown great and partly unforeseen opportunities for the design of multifunctional materials. For nacre-mimetic nanocomposites, it has remained extraordinarily challenging to make ductile materials with high stretchability at high fractions of reinforcements, which is however of crucial importance for flexible barrier materials. Here, highly ductile and tough nacre-mimetic nanocomposites are presented, by implementing weak, but many hydrogen bonds in a ternary nacre-mimetic system consisting of two polymers (poly(vinyl amine) and poly(vinyl alcohol)) and natural nanoclay (montmorillonite) to provide efficient energy dissipation and slippage at high nanoclay content (50 wt%). Tailored interactions enable exceptional combinations of ductility (close to 50% strain) and toughness (up to 27.5 MJ m⁻³). Extensive stress whitening, a clear sign of high internal dynamics at high internal cohesion, can be observed during mechanical deformation, and the materials can be folded like paper into origami planes without fracture. Overall, the new levels of ductility and toughness are unprecedented in highly reinforced bioinspired nanocomposites and are of critical importance to future applications, e.g., as barrier materials needed for encapsulation and as a printing substrate for flexible organic electronics.
False spectra formation in the differential two-channel scheme of the laser Doppler flowmeter
(2018)
Noise in the differential two-channel scheme of a classic laser Doppler flowmetry (LDF) instrument was studied. Formation of false spectral components in the output signal due to beating of electrical signals in the differential amplifier was found out. The improved block-diagram of the flowmeter was developed allowing to reduce the noise.
Monitoring of organic acids (OA) and volatile fatty acids (VFA) is crucial for the control of anaerobic digestion. In case of unstable process conditions, an accumulation of these intermediates occurs. In the present work, two different enzyme-based biosensor arrays are combined and presented for facile electrochemical determination of several process-relevant analytes. Each biosensor utilizes a platinum sensor chip (14 × 14 mm²) with five individual working electrodes. The OA biosensor enables simultaneous measurement of ethanol, formate, d- and l-lactate, based on a bi-enzymatic detection principle. The second VFA biosensor provides an amperometric platform for quantification of acetate and propionate, mediated by oxidation of hydrogen peroxide. The cross-sensitivity of both biosensors toward potential interferents, typically present in fermentation samples, was investigated. The potential for practical application in complex media was successfully demonstrated in spiked sludge samples collected from three different biogas plants. Thereby, the results obtained by both of the biosensors were in good agreement to the applied reference measurements by photometry and gas chromatography, respectively. The proposed hybrid biosensor system was also used for long-term monitoring of a lab-scale biogas reactor (0.01 m³) for a period of 2 months. In combination with typically monitored parameters, such as gas quality, pH and FOS/TAC (volatile organic acids/total anorganic carbonate), the amperometric measurements of OA and VFA concentration could enhance the understanding of ongoing fermentation processes.
Algal polysaccharides (extracellular polysaccharides) and carbon nanotubes (CNTs) were adsorbed on dioctadecyldimethylammonium bromide Langmuir monolayers to serve as a matrix for the incorporation of urease. The physicochemical properties of the supramolecular system as a monolayer at the air–water interface were investigated by surface pressure–area isotherms, surface potential–area isotherms, interfacial shear rheology, vibrational spectroscopy, and Brewster angle microscopy. The floating monolayers were transferred to hydrophilic solid supports, quartz, mica, or capacitive electrolyte–insulator–semiconductor (EIS) devices, through the Langmuir–Blodgett (LB) technique, forming mixed films, which were investigated by quartz crystal microbalance, fluorescence spectroscopy, and field emission gun scanning electron microscopy. The enzyme activity was studied with UV–vis spectroscopy, and the feasibility of the thin film as a urea sensor was essayed in an EIS sensor device. The presence of CNT in the enzyme–lipid LB film not only tuned the catalytic activity of urease but also helped to conserve its enzyme activity. Viability as a urease sensor was demonstrated with capacitance–voltage and constant capacitance measurements, exhibiting regular and distinctive output signals over all concentrations used in this work. These results are related to the synergism between the compounds on the active layer, leading to a surface morphology that allowed fast analyte diffusion owing to an adequate molecular accommodation, which also preserved the urease activity. This work demonstrates the feasibility of employing LB films composed of lipids, CNT, algal polysaccharides, and enzymes as EIS devices for biosensing applications.
Background
Impairment of neurovascular coupling (NVC) was recently reported in the context of subarachnoid hemorrhage and may correlate with disease severity and outcome. However, previous techniques to evaluate NVC required invasive procedures. Retinal vessels may represent an alternative option for non-invasive assessment of NVC.
Methods
A prototype of an adapted retinal vessel analyzer was used to assess retinal vessel diameter in mice. Dynamic vessel analysis (DVA) included an application of monochromatic flicker light impulses in predefined frequencies for evaluating NVC. All retinae were harvested after DVA and electroretinograms were performed.
Results
A total of 104 retinal scans were conducted in 21 male mice (90 scans). Quantitative arterial recordings were feasible only in a minority of animals, showing an emphasized reaction to flicker light impulses (8 mice; 14 scans). A characteristic venous response to flicker light, however, could observed in the majority of animals. Repeated measurements resulted in a significant decrease of baseline venous diameter (7 mice; 7 scans, p < 0.05). Ex-vivo electroretinograms, performed after in-vivo DVA, demonstrated a significant reduction of transretinal signaling in animals with repeated DVA (n = 6, p < 0.001).
Conclusions
To the best of our knowledge, this is the first non-invasive study assessing murine retinal vessel response to flicker light with characteristic changes in NVC. The imaging system can be used for basic research and enables the investigation of retinal vessel dimension and function in control mice and genetically modified animals.
For fuel flexibility enhancement hydrogen represents a possible alternative gas turbine fuel within future low emission power generation, in case of hydrogen production by the use of renewable energy sources such as wind energy or biomass. Kawasaki Heavy Industries, Ltd. (KHI) has research and development projects for future hydrogen society; production of hydrogen gas, refinement and liquefaction for transportation and storage, and utilization with gas turbine / gas engine for the generation of electricity. In the development of hydrogen gas turbines, a key technology is the stable and low NOx hydrogen combustion, especially Dry Low Emission (DLE) or Dry Low NOx (DLN) hydrogen combustion. Due to the large difference in the physical properties of hydrogen compared to other fuels such as natural gas, well established gas turbine combustion systems cannot be directly applied for DLE hydrogen combustion. Thus, the development of DLE hydrogen combustion technologies is an essential and challenging task for the future of hydrogen fueled gas turbines. The DLE Micro-Mix combustion principle for hydrogen fuel has been in development for many years to significantly reduce NOx emissions. This combustion principle is based on cross-flow mixing of air and gaseous hydrogen which reacts in multiple miniaturized “diffusion-type” flames. The major advantages of this combustion principle are the inherent safety against flashback and the low NOx-emissions due to a very short residence time of the reactants in the flame region of the micro-flames.
BACKGROUND
Immunosuppression is often considered as an indication for antibiotic prophylaxis to prevent surgical site infections (SSI) while performing skin surgery. However, the data on the risk of developing SSI after dermatologic surgery in immunosuppressed patients are limited.
PATIENTS AND METHODS
All patients of the Department of Dermatology and Allergology at the University Hospital of RWTH Aachen in Aachen, Germany, who underwent hospitalization for a dermatologic surgery between June 2016 and January 2017 (6 months), were followed up after surgery until completion of the wound healing process. The follow-up addressed the occurrence of SSI and the need for systemic antibiotics after the operative procedure. Immunocompromised patients were compared with immunocompetent patients. The investigation was conducted as a retrospective analysis of patient records.
RESULTS
The authors performed 284 dermatologic surgeries in 177 patients. Nineteen percent (54/284) of the skin surgery was performed on immunocompromised patients. The most common indications for surgical treatment were nonmelanoma skin cancer and malignant melanomas. Surgical site infections occurred in 6.7% (19/284) of the cases. In 95% (18/19), systemic antibiotic treatment was needed. Twenty-one percent of all SSI (4/19) were seen in immunosuppressed patients.
CONCLUSION
According to the authors' data, immunosuppression does not represent a significant risk factor for SSI after dermatologic surgery. However, larger prospective studies are needed to make specific recommendations on the use of antibiotic prophylaxis while performing skin surgery in these patients.
The available data on complications after dermatologic surgery have improved over the past years. Particularly, additional risk factors have been identified for surgical site infections (SSI). Purulent surgical sites, older age, involvement of head, neck, and acral regions, and also the involvement of less experienced surgeons have been reported to increase the risk of the SSI after dermatologic surgeries.1 In general, the incidence of SSI after skin surgery is considered to be low.1,2 However, antibiotics in dermatologic surgeries, especially in the perioperative setting, seem to be overused,3,4 particularly regarding developing antibiotic resistances and side effects.
Immunosuppression has been recommended to be taken into consideration as an additional indication for antibiotic prophylaxis to prevent SSI after skin surgery in special cases.5,6 However, these recommendations do not specify the exact dermatologic surgeries, and were not specifically developed for dermatologic surgery patients and treatments, but adopted from other surgical fields.6 According to the survey conducted on American College of Mohs Surgery members in 2012, 13% to 29% of the surgeons administered antibiotic prophylaxis to immunocompromised patients to prevent SSI while performing dermatologic surgery on noninfected skin,3 although this was not recommended by Journal of the American Academy of Dermatology Advisory Statement. Indeed, the data on the risk of developing SSI after dermatologic surgery in immunosuppressed patients are limited. However, it is possible that due to the insufficient evidence on the risk of SSI occurrence in this patient group, dermatologic surgeons tend to overuse perioperative antibiotic prophylaxis.
To make specific recommendations on the use of antibiotic prophylaxis in immunosuppressed patients in the field of skin surgery, more information about the incidence of SSI after dermatologic surgery in these patients is needed. The aim of this study was to fill this data gap by investigating whether there is an increased risk of SSI after skin surgery in immunocompromised patients compared with immunocompetent patients.
We present and discuss an exploration of the possibilities and properties of 3D printing with a printing space of 1 cubic meter, and how those can be integrated into architectural education through an experimental design and research course with students of architecture.We expand on issues presented at the eCAADe conference 2017 in Rome [Ref 6] by increasing the complexity and size of our prints, printing not a model to scale, but a full scale funtional prototype of a usable architectural object: A coffee bar.
Manufacturing process simulation (MPS) has become more and more important for aviation and the automobile industry. A highly competitive market requires the use of high performance metals and composite materials in combination with reduced manufacturing cost and time as well as a minimization of the time to market for a new product. However, the use of such materials is expensive and requires sophisticated manufacturing processes. An experience based process and tooling design followed by a lengthy trial-and-error optimization is just not contemporary anymore. Instead, a tooling design process aided by simulation is used more often. This paper provides an overview of the capabilities of MPS in the fields of sheet metal forming and prepreg autoclave manufacturing of composite parts summarizing the resulting benefits for tooling design and manufacturing engineering. The simulation technology is explained briefly in order to show several simplification and optimization techniques for developing industrialized simulation approaches. Small case studies provide examples of an efficient application on an industrial scale.
The Kremer-Grest (KG) bead-spring model is a near standard in Molecular Dynamic simulations of generic polymer properties. It owes its popularity to its computational efficiency, rather than its ability to represent specific polymer species and conditions. Here we investigate how to adapt the model to match the universal properties of a wide range of chemical polymers species. For this purpose we vary a single parameter originally introduced by Faller and Müller-Plathe, the chain stiffness. Examples include polystyrene, polyethylene, polypropylene, cis-polyisoprene, polydimethylsiloxane, polyethyleneoxide and styrene-butadiene rubber. We do this by matching the number of Kuhn segments per chain and the number of Kuhn segments per cubic Kuhn volume for the polymer species and for the Kremer-Grest model. We also derive mapping relations for converting KG model units back to physical units, in particular we obtain the entanglement time for the KG model as function of stiffness allowing for a time mapping. To test these relations, we generate large equilibrated well entangled polymer melts, and measure the entanglement moduli using a static primitive-path analysis of the entangled melt structure as well as by simulations of step-strain deformation of the model melts. The obtained moduli for our model polymer melts are in good agreement with the experimentally expected moduli.
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
68Ga-radiopharmaceuticals are common in the field of Nuclear Medicine to visualize receptor-mediated processes. In contrast to straightforward labeling procedures for clinical applications, preclinical in vitro and in vivo applications are hampered for reasons like e.g. volume
restriction, activity concentration, molar activity and osmolality. Therefore, we developed a semiautomatic system specifically to overcome these problems. A difficulty appeared unexpectedly, as intrinsic trace metals derived from eluate (Zn, Fe and Cu) are concentrated as well in amounts that influence radiochemical yield and thus lower molar activity.
Often, research results from collaboration projects are not transferred into productive environments even though approaches are proven to work in demonstration prototypes. These demonstration prototypes are usually too fragile and error-prone to be transferred
easily into productive environments. A lot of additional work is required.
Inspired by the idea of an incremental delivery process, we introduce an architecture pattern, which combines the approach of Metrics Driven Research Collaboration with microservices for the ease of integration. It enables keeping track of project goals over the course of the collaboration while every party may focus on their expert skills: researchers may focus on complex algorithms,
practitioners may focus on their business goals.
Through the simplified integration (intermediate) research results can be introduced into a productive environment which enables
getting an early user feedback and allows for the early evaluation of different approaches. The practitioners’ business model benefits throughout the full project duration.