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This paper presents the first part of a research-work conducted at the University of Applied Sciences (HFT- Stuttgart). The aim of the research was to investigate the potential of low-cost renewable energy systems to reduce the energy demand of the building sector in hot and dry areas. Radiative cooling to the night sky represents a low-cost renewable energy source. The dry desert climate conditions promote radiative cooling applications. The system technology adopted in this work is based on uncovered solar thermal collectors integrated into the building’s hydronic system. By implementing different control strategies, the same system could be used for cooling as well as for heating applications. This paper focuses on identifying the collector parameters which are required as the coefficients to configure such an unglazed collector for calibrating its mathematical model within the simulation environment. The parameter identification process implies testing the collector for its thermal performance. This paper attempts to provide an insight into the dynamic testing of uncovered solar thermal collectors (absorbers), taking into account their prospective operation at nighttime for radiative cooling applications. In this study, the main parameters characterizing the performance of the absorbers for radiative cooling applications are identified and obtained from standardized testing protocol. For this aim, a number of plastic solar absorbers of different designs were tested on the outdoor test-stand facility at HFT-Stuttgart for the characterization of their thermal performance. The testing process was based on the quasi-dynamic test method of the international standard for solar thermal collectors EN ISO 9806. The test database was then used within a mathematical optimization tool (GenOpt) to determine the optimal parameter settings of each absorber under testing. Those performance parameters were significant to compare the thermal performance of the tested absorbers. The coefficients (identified parameters) were used then to plot the thermal efficiency curves of all absorbers, for both the heating and cooling modes of operation. Based on the intended main scope of the system utilization (heating or cooling), the tested absorbers could be benchmarked. Hence, one of those absorbers was selected to be used in the following simulation phase as was planned in the research-project.
During the first years of the last decade, Egypt used to face recurrent electricity cut-offs in summer. In the past few years, the electricity tariff dramatically increased. Radiative cooling to the clear night sky is a renewable energy source that represents a relative solution. The dry desert climate promotes nocturnal radiative cooling applications. This study investigates the potential of nocturnal radiative cooling systems (RCSs) to reduce the energy consumption of the residential building sector in Egypt. The system technology proposed in this work is based on uncovered solar thermal collectors integrated into the building hydronic system. By implementing different control strategies, the same system could be used for both cooling and heating applications. The goal of this paper is to analyze the performance of RCSs in residential buildings in Egypt. The dynamic simulation program TRNSYS was used to simulate the thermal behavior of the system. The relevant issues of Egypt as a case-study are firstly overviewed. Then the paper introduces the work done to develop a building model that represents a typical residential apartment in Egypt. Typical occupancy profiles were developed to define the internal thermal gains. The adopted control strategy to optimize the system operation is presented as well. To fully understand and hence evaluate the operation of the proposed RCS, four simulation cases were considered: 1. a reference case (fully passive), 2. the stand-alone operation of the RCS, 3. ideal heating & cooling operation (fully-active), and 4. the hybrid-operation (when the active cooling system is supported by the proposed RCS). The analysis considered the main three distinct climates in Egypt, represented by the cities of Alexandria, Cairo and Asyut. The hotter and drier weather conditions resulted in a higher cooling potential and larger temperature differences. The simulated cooling power in Asyut was 28.4 W/m² for a 70 m² absorber field. For a smaller field area of 10 m², the cooling power reached 109 W/m² but with humble temperature differences. To meet the rigorous thermal comfort conditions, the proposed sensible RCS cannot fully replace conventional air-conditioning units, especially in humid areas like Alexandria. When working in a hybrid system, a 10% reduction in the active cooling energy demand could be achieved in Asyut to keep the cooling set-point at 24 °C. This percentage reduction was nearly doubled when the thermal comfort set-point was increased by two degrees (26 °C). In a sensitivity analysis, external shading devices as a passive measure as well as the implementation of the Egyptian code for buildings (ECP306/1–2005) were also investigated. The analysis of this study raised other relevant aspects to discuss, e.g. system-sizing, environmental effects, limitations and recommendations.
In the last decade, numerous learning factories for education, training, and research have been built up in industry and academia. In recent years learning factory initiatives were elevated from a local to a European and then to a worldwide level. In 2014 the CIRP Collaborative Working Group (CWG) on Learning Factories enables a lively exchange on the topic "Learning Factories for future oriented research and education in manufacturing". In this paper results of discussions inside the CWG are presented. First, what is meant by the term Learning Factory is outlined. Second, based on the definition a description model (morphology) for learning factories is presented. The morphology covers the most relevant characteristics and features of learning factories in seven dimensions. Third, following the morphology the actual variance of learning factory manifestations is shown in six learning factory application scenarios from industrial training over education to research. Finally, future prospects of the learning factory concept are presented.
The physicochemical properties of synthetically produced bone substitute materials (BSM) have a major impact on biocompatibility. This affects bony tissue integration, osteoconduction, as well as the degradation pattern and the correlated inflammatory tissue responses including macrophages and multinucleated giant cells (MNGCs). Thus, influencing factors such as size, special surface morphologies, porosity, and interconnectivity have been the subject of extensive research. In the present publication, the influence of the granule size of three identically manufactured bone substitute granules based on the technology of hydroxyapatite (HA)-forming calcium phosphate cements were investigated, which includes the inflammatory response in the surrounding tissue and especially the induction of MNGCs (as a parameter of the material degradation). For the in vivo study, granules of three different size ranges (small = 0.355–0.5 mm; medium = 0.5–1 mm; big = 1–2 mm) were implanted in the subcutaneous connective tissue of 45 male BALB/c mice. At 10, 30, and 60 days post implantationem, the materials were explanted and histologically processed. The defect areas were initially examined histopathologically. Furthermore, pro- and anti-inflammatory macrophages were quantified histomorphometrically after their immunohistochemical detection. The number of MNGCs was quantified as well using a histomorphometrical approach. The results showed a granule size-dependent integration behavior. The surrounding granulation tissue has passivated in the groups of the two bigger granules at 60 days post implantationem including a fibrotic encapsulation, while a granulation tissue was still present in the group of the small granules indicating an ongoing cell-based degradation process. The histomorphometrical analysis showed that the number of proinflammatory macrophages was significantly increased in the small granules at 60 days post implantationem. Similarly, a significant increase of MNGCs was detected in this group at 30 and 60 days post implantationem. Based on these data, it can be concluded that the integration and/or degradation behavior of synthetic bone substitutes can be influenced by granule size.
As fuel prices climb and the global automotive sector migrates to more sustainable vehicle technologies, the future of South Africa’s minibus taxis is in flux. The authors’ previous research has found that battery electric technology struggles to meet all the mobility requirements of minibus taxis. They investigate the technical feasibility of powering taxis with hydrogen fuel cells instead. The following results are projected using a custom-built simulator, and tracking data of taxis based in Stellenbosch, South Africa. Each taxi requires around 12 kg of hydrogen gas per day to travel an average distance of 360 km. 465 kWh of electricity, or 860 m2 of solar panels, would electrolyse the required green hydrogen. An economic analysis was conducted on the capital and operational expenses of a system of ten hydrogen taxis and an electrolysis plant. Such a pilot project requires a minimum investment of € 3.8 million (R 75 million), for a 20 year period. Although such a small scale roll-out is technically feasible and would meet taxis’ performance requirements, the investment cost is too high, making it financially unfeasible. They conclude that a large scale solution would need to be investigated to improve financial feasibility; however, South Africa’s limited electrical generation capacity poses a threat to its technical feasibility. The simulator is uploaded at: https://gitlab.com/eputs/ev-fleet-sim-fcv-model.
With the expansion of cyber-physical systems (CPSs) across critical and regulated industries, systems must be continuously updated to remain resilient. At the same time, they should be extremely secure and safe to operate and use. The DevOps approach caters to business demands of more speed and smartness in production, but it is extremely challenging to implement DevOps due to the complexity of critical CPSs and requirements from regulatory authorities. In this study, expert opinions from 33 European companies expose the gap in the current state of practice on DevOps-oriented continuous development and maintenance. The study contributes to research and practice by identifying a set of needs. Subsequently, the authors propose a novel approach called Secure DevOps and provide several avenues for further research and development in this area. The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
Implementation of product-service systems (PSS) requires structural changes in the way that business in manufacturing industries is traditionally conducted. Literature frequently mentions the importance of human resource management (HRM), since people are involved in the entire process of PSS development and employees are the primary link to customers. However, to this day, no study has provided empirical evidence whether and in what way HRM of firms that implement PSS differs from HRM of firms that solely run a traditional manufacturing based business model. The aim of this study is to contribute to closing this gap by investigating the particular HR components of manufacturing firms that implement PSS and compare it with the HRM of firms that do not. The context of this study is the fashion industry, which is an ideal setting since it is a mature and highly competitive industry that is well-documented for causing significant environmental impact. PSS present a promising opportunity for fashion firms to differentiate and mitigate the industry’s ecological footprint. Analysis of variance (ANOVA) was conducted to analyze data of 102 international fashion firms. Findings reveal a significant higher focus on nearly the entire spectrum of HRM components of firms that implement PSS compared with firms that do not. Empirical findings and their interpretation are utilized to propose a general framework of the role of HRM for PSS implementation. This serves as a departure point for both scholars and practitioners for further research, and fosters the understanding of the role of HRM for managing PSS implementation.
In recent years the share economy has gained widespread success across different industries. Since small firms and new ventures obtain fewer resources, an increased focus on service allows them to differentiate and compete with cost pressure in traditionally manufacturing based industries. There still is a lack of understanding how these firms manage to successfully shift towards service-oriented business models. This paper adopts a dynamic capabilities approach to examine the particular microfoundations that underlie sensing, seizing and reconfiguring dynamic capabilities of early-stage service firms within a traditional retail market. The context of this study is the fashion industry. It is an ideal setting since it is characterized by severe competition, short life cycles, strong cost pressure and high volatility. There are few but increasing examples of entrepreneurial initiatives that try to compete by providing offers to resell, rent or swap clothes. Qualitative data of five early stage fashion ventures is analyzed. Findings reveal that the ability to develop and maintain long-term relationships is essential. It has also been found crucial to acquire knowledge from external network partners, delegate tasks and share information. Furthermore, skills for interacting with customers and adopting consumer feedback are critical. This study provides empirical evidence of dynamic capabilities of early-stage firms and contributes to knowledge on the factors that facilitate servitization in traditionally manufacturing based industries. For practitioners, the presented microfoundations provide a framework of critical tasks that allow them to develop and maintain a service oriented business model.
Venture capital and the innovative power of a state : econometric study including Google data
(2015)
This article focuses on venture capital investments and the innovative power of a state defined by its public infrastructure. The economic implications are evaluated by estimating several panel regression models. The novelty is twofold: on the one hand the research approach and on the other hand the new data set. The data ranges from 1995 to 2014 and consists of 10 European countries plus the US and Canada. For the first time we include Google search data on Venture Capital. The results show a significant increase in Venture Capital is mainly determined by economic conditions such as real GDP growth. The impact of the innovative power of a state is not significant. We find that Google data is positively related and significant in respect to Venture Capital investments too. Consequently, we confirm that private business investments cannot be created by government policy alone rather via solid macroeconomic conditions.
This study is about estimating the reproducibility of finding palpation points of three different anatomical landmarks in the human body (Xiphoid Process and the 2 Hip Crests) to support a navigated ultrasound application. On 6 test subjects with different body mass index the three palpation points were located five times by two examiners. The deviation from the target position was calculated and correlated to the fat thickness above each palpation point. The reproducibility of the measurements had a mean error of ≈13.5 mm +- 4 mm, which seems to be sufficient for the desired application field.
Most Question-answering (QA) systems rely on training data to reach their optimal performance. However, acquiring training data for supervised systems is both time-consuming and resource-intensive. To address this, in this paper, we propose TFCSG, an unsupervised similar question retrieval approach that leverages pre-trained language models and multi-task learning. Firstly, topic keywords in question sentences are extracted sequentially based on a latent topic-filtering algorithm to construct unsupervised training corpus data. Then, the multi-task learning method is used to build the question retrieval model. There are three tasks designed. The first is a short sentence contrastive learning task. The second is the question sentence and its corresponding topic sequence similarity judgment task. The third is using question sentences to generate their corresponding topic sequence task. The three tasks are used to train the language model in parallel. Finally, similar questions are obtained by calculating the cosine similarity between sentence vectors. The comparison experiment on public question datasets that TFCSG outperforms the comparative unsupervised baseline method. And there is no need for manual marking, which greatly saves human resources.
Different types of raw cotton were investigated by a commercial ultraviolet-visible/near infrared (UV-Vis/NIR) spectrometer (210–2200 nm) as well as on a home-built setup for NIR hyperspectral imaging (NIR-HSI) in the range 1100–2200 nm. UV-Vis/NIR reflection spectroscopy reveals the dominant role proteins, hydrocarbons and hydroxyl groups play in the structure of cotton. NIR-HSI shows a similar result. Experimentally obtained data in combination with principal component analysis (PCA) provides a general differentiation of different cotton types. For UV-Vis/NIR spectroscopy, the first two principal components (PC) represent 82 % and 78 % of the total data variance for the UV-Vis and NIR regions, respectively. Whereas, for NIR-HSI, due to the large amount of data acquired, two methodologies for data processing were applied in low and high lateral resolution. In the first method, the average of the spectra from one sample was calculated and in the second method the spectra of each pixel were used. Both methods are able to explain ≥90 % of total variance by the first two PCs. The results show that it is possible to distinguish between different cotton types based on a few selected wavelength ranges. The combination of HSI and multivariate data analysis has a strong potential in industrial applications due to its short acquisition time and low-cost development. This study opens a novel possibility for a further development of this technique towards real large-scale processes.
Hyperspectral imaging and reflectance spectroscopy in the range from 200–380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with R2c = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.
UV hyperspectral imaging (225 nm–410 nm) was used to identify and quantify the honey- dew content of real cotton samples. Honeydew contamination causes losses of millions of dollars annually. This study presents the implementation and application of UV hyperspectral imaging as a non-destructive, high-resolution, and fast imaging modality. For this novel approach, a reference sample set, which consists of sugar and protein solutions that were adapted to honeydew, was set-up. In total, 21 samples with different amounts of added sugars/proteins were measured to calculate multivariate models at each pixel of a hyperspectral image to predict and classify the amount of sugar and honeydew. The principal component analysis models (PCA) enabled a general differentiation between different concentrations of sugar and honeydew. A partial least squares regression (PLS-R) model was built based on the cotton samples soaked in different sugar and protein concentrations. The result showed a reliable performance with R2cv = 0.80 and low RMSECV = 0.01 g for the valida- tion. The PLS-R reference model was able to predict the honeydew content laterally resolved in grams on real cotton samples for each pixel with light, strong, and very strong honeydew contaminations. Therefore, inline UV hyperspectral imaging combined with chemometric models can be an effective tool in the future for the quality control of industrial processing of cotton fibers.
Due to its wide-ranging endocrine functions, adipose tissue influences the whole body’s metabolism. Engineering long-term stable and functional human adipose tissue is still challenging due to the limited availability of suitable biomaterials and adequate cell maturation. We used gellan gum (GG) to create manual and bioprinted adipose tissue models because of its similarities to the native extracellular matrix and its easily tunable properties. Gellan gum itself was neither toxic nor monocyte activating. The resulting hydrogels exhibited suitable viscoelastic properties for soft tissues and were stable for 98 days in vitro. Encapsulated human primary adipose-derived stem cells (ASCs) were adipogenically differentiated for 14 days and matured for an additional 84 days. Live-dead staining showed that encapsulated cells stayed viable until day 98, while intracellular lipid staining showed an increase over time and a differentiation rate of 76% between days 28 and 56. After 4 weeks of culture, adipocytes had a univacuolar morphology, expressed perilipin A, and secreted up to 73% more leptin. After bioprinting establishment, we demonstrated that the cells in printed hydrogels had high cell viability and exhibited an adipogenic phenotype and function. In summary, GG-based adipose tissue models show long-term stability and allow ASCs maturation into functional, univacuolar adipocytes.
Adipose tissue is related to the development and manifestation of multiple diseases, demonstrating the importance of suitable in vitro models for research purposes. In this study, adipose tissue lobuli were explanted, cultured, and used as an adipose tissue control to evaluate in vitro generated adipose tissue models. During culture, lobule exhibited a stable weight, lactate dehydrogenase, and glycerol release over 15 days. For building up in vitro adipose tissue models, we adapted the biomaterial gelatin methacryloyl (GelMA) composition and handling to homogeneously mix and bioprint human primary mature adipocytes (MA) and adipose-derived stem cells (ASCs), respectively. Accelerated cooling of the bioink turned out to be essential for the homogeneous distribution of lipid-filled MAs in the hydrogel. Last, we compared manual and bioprinted GelMA hydrogels with MA or ASCs and the explanted lobules to evaluate the impact of the printing process and rate the models concerning the physiological reference. The viability analyses demonstrated no significant difference between the groups due to additive manufacturing. The staining of intracellular lipids and perilipin A suggest that GelMA is well suited for ASCs and MA. Therefore, we successfully constructed physiological in vitro models by bioprinting MA-containing GelMA bioinks.
Sol-Gel basierte Flammschutzmittel stellen einen vielversprechenden Ansatz für Textilien dar, gerade im Bereich des Ersatzes von derzeit etablierten halogenhaltigen Flammschutzmitteln. Letztere sind aufgrund ihrer toxikologisch Bedenklichkeit sowie ihrer mitunter bioakkumulierenden Eigenschaften in die Kritik geraten. In diesem Forschungsvorhaben wurde daher untersucht wie aus Phosphor- und stickstoffhaltige Silane halogenfreie Flammschutzmittel verwirklicht werden können. Die Sol-Gel-Schicht fungierte dabei zum einen als nicht brennbarer Binder, zum anderen konnten über das Anbinden von Phosphorgruppen in an kommerziell verfügbare Silane Flammschutz aktive Gruppen direkt mit eingebunden werden. Verschiedene Syntheseansätze wurden dabei verfolgt, wobei durch alle hergestellten N-P-Silane ein Flammschutz nach DIN EN ISO 15025 (Schutzkleidung – Schutz gegen Hitze und Flammen) erhalten wurden. Dabei hängt die Flammschutzwirkung stark von den funktionellen Gruppen und der Oxidationsstufe des Phosphors ab, dabei konnte ein entsprechender Flammschutz bei Auflagen von 5 % erzielt werden. Es konnte gezeigt werden, dass ein Mechanismus auf Basis der Bildung einer Schutzschicht hauptsächlich verantwortlich für den Flammschutz ist. Dieses Ergebnis ist für eine zukünftige, weitere Optimierung entsprechender Ausrüstungen nicht zu unterschätzen. Durch Ausrüstungsversuche im semi-industriellen Maßstab konnte weiterhin gezeigt werden, dass einer großtechnischen Umsetzung der angewandten Ausrüstungen prinzipiell nichts im Wege steht. Je nach funktioneller Gruppe am Phosphor konnte die Wasserlöslichkeit und die Waschstabilität kontrolliert werden. Dabei konnte zum einen gezeigt werden, dass hydrophobes N-P-Silane eine bessere Waschbeständigkeit aufweisen, hydrophile N-P-Silane erhalten diese erst bei Fixierungstemperaturen von 180 °C. Ausgehend von den Ergebnissen konnten sticktstoffgenerierende und cyanursäure-basierte N-P-Silane entwickelt werden, welche sich besonders in einer guten Flammschutzwirkung bei Mischgeweben auszeichnen. Insgesamt konnte innerhalb des Forschungsvorhabens gezeigt werden, dass N-P-Silane hervorragende permanente Flammschutzmittel für Textilien sind und auf welchem Mechanismus dieser Flammschutz begründet ist.
Flame-retardant finishing of cotton fabrics using DOPO functionalized alkoxy- and amido alkoxysilane
(2023)
In the present study, DOPO-based alkoxysilane (DOPO-ETES) and amido alkoxysilane (DOPO-AmdPTES) were synthesized by one-step and without by-products as halogen-free flame retardants. The flame retardants were applied on cotton fabric utilizing sol–gel method and pad-dry-cure finishing process. The flame retardancy, the thermal stability and the combustion ehaviour of treated cotton were evaluated by surface and bottom edge ignition flame test (according to EN ISO 15025), thermogravimetric analysis (TGA) and micro-scale combustion calorimeter (MCC). Unlike CO/DOPO-ETES sample, cotton treated with DOPO-AmdPTES nanosols exhibits self-extinguishing ehaviour with high char residue, an improvement of the LOI value and a significant reduction of the PHRR, HRC and THR compared to pristine cotton. Cotton finished with DOPO-AmdPTES reveals a semi-durability after ten laundering cycles keeping the flame-retardant properties unchanged. According to the results obtained from TGA-FTIR, Py-GC/MS and XPS, the major activity of flame retardant occurs in the condensed phase via catalytic induced char formation as physical barrier along with the activity in the gas phase derived mainly from the dilution effect. The early degradation of CO/DOPO-AmdPTES compared to CO/DOPO-ETES, triggered by the cleavage of the weak bond between P and C=O, as the DFT study indicated, provides the beneficial effect of this flame retardant on the fire resistance of cellulose.
The chemical recycling of used motor oil via catalytic cracking to convert it into secondary diesel-like fuels is a sustainable and technically attractive solution for managing environmental concerns associated with traditional disposal. In this context, this study was conducted to screen basic and acidic-aluminum silicate catalysts doped with different metals, including Mg, Zn, Cu, and Ni. The catalysts were thoroughly characterized using various techniques such as N2 adsorption–desorption isotherms, FT-IR spectroscopy, and TG analysis. The liquid and gaseous products were identified using GC, and their characteristics were compared with acceptable ranges from ASTM characterization methods for diesel fuel. The results showed that metal doping improved the performance of the catalysts, resulting in higher conversion rates of up to 65%, compared to thermal (15%) and aluminum silicates (≈20%). Among all catalysts, basic aluminum silicates doped with Ni showed the best catalytic performance, with conversions and yields three times higher than aluminum silicate catalysts. These findings significantly contribute to developing efficient and eco-friendly processes for the chemical recycling of used motor oil. This study highlights the potential of basic aluminum silicates doped with Ni as a promising catalyst for catalytic cracking and encourages further research in this area.
Fast pyrolysis as a valorization mechanism for banana rachis and low-density polyethylene waste
(2021)
Banana rachis and low-density polyethylene (LDPE) were selected as secondary feedstocks for the study of fast pyrolysis in a free-fall reactor. The experiments were performed at 600 °C for banana rachis and 450 °C for LDPE, based on literature and thermogravimetric analysis. The gaseous products of both feedstocks present similar composition in the C1-C2 compounds, while C3 compounds are only found in LDPE. The liquid products from banana and LDPE correspond to functional groups and shorter hydrocarbons, respectively. Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) analyses of the char showed important morphological changes to spheres in LDPE and structural changes due to thermal decomposition in the biomass. The pyrolysis char has high potential as adsorbent, encapsulation, or catalyst.
Characterization of low density polyethylene greenhouse films during the composting of rose residues
(2022)
This study presents an evaluation of a potential alternative to plastic degradation in the form of organic composting. It stems from the urgent need of finding solutions to the plastic residues and focuses on the compost-based degradation of greenhouse film covers in an important rose exporter company in Ecuador. Thus, this study analyzes the physical, chemical, and biological changes of rose wastes composting, and also evaluates the stability of new and aged agricultural plastic under these conditions. Interestingly, results of compost characterization show a slow degradation rate of organic matter and total organic carbon, along with a significant increase in pH and rise of bacterial populations. However, the results demonstrate that despite these findings, composting conditions had no significant influence on plastic degradation, and while deterioration of aged plastic samples was reported in some tests, it may be the result of environmental conditions and a prolonged exposure to solar radiation. Importantly, these factors could facilitate the adhesion of microorganisms and promote plastic biodegradation. Hence, it is encouraged for future studies to analyze the ecotoxicity of plastics in the compost, as well as isolate, identify, and evaluate the possible biodegradative potential of these microorganisms as an alternative to plastic waste management.
While there has been increased digitization of private homes, only little has been done to understand these specific home technologies, how they serve consumers, among other issues. “Smart home technology” (SHT) refer to a wide range of artifacts from cleaning aids to energy advisors. Given this breadth, clarity surrounding the key characteristics and the multi-faceted impact of SHT is needed to conduct more directed research on SHT. We propose a taxonomy to help outline the salient intended outcomes of SHT. Through a process involving five iterations, we analyzed and classified 79 technologies (gathered from literature and industry reports). This uncovered seven dimensions encompassing 20 salient characteristics. We believe these dimensions/characteristics will help researchers and organizations better design and study the impacts of these technologies. Our long-term agenda is to use the proposed taxonomy for an exploratory inquiry to understand tensions occurring when personal and sustainability-related outcomes compete.
Facing ever-looming climate change, studying the drivers for individuals' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use.
In times of climate change and growing urbanization, the way food is produced and consumed also changes. Meanwhile, digitization is transforming farming practices, which also applies to the domestic growing of crops. More and more so-called smart home farms (SHF) are finding their way into private households. This paper conceptualizes the unique nature of enabled smart services and their underlying technology. Following an inductive interpretive approach, this study explores the antecedents of smart home farming practices. Our sample consists of eleven actual smart home farmers. We found six constructs to be of salient importance: expected outcomes related to harvesting, positive feelings, and sustainability; a combination of one's affinity for green and novel technologies; and the smartness and visibility of the enabled services. In the outlook, we present some preliminary thoughts for testing our qualitative findings.
The proliferation of smart technologies transforms the way individual consumers perform tasks. Considerable research alludes that smart technologies are often related to domestic energy consumption. However, it remains unclear how such technologies transform tasks and thereby impact our planet. We explore the role of technological smartness in personal day-to-day tasks that help create a more sustainable future. In the absence of theory, but facing extensive changes in everyday life enabled by smart technologies, we draw on phenomenon-based theorizing (PBT) guidelines. As anchor, we refer to task endogeneity related to task-technology fit theory (TTF). As infusion, we employ theory on public goods. Our model proposes novel relations between the concepts of smart autonomy and -transparency with sustainable task outcomes, mediated by task convenience and task significance. We discuss some implications, limitations, and future research opportunities.
The effect of Hofmeister anions on the surface properties of polyelectrolyte multilayers built from hyaluronan and chitosan by layer-by-layer deposition is studied by ellipsometry and atomic force microscopy. The thickness, roughness and morphology of the resulting coatings were found to depend on the type of the anion. Relationship between the surface properties and the biological response of the polyelectrolyte multilayers is established by assessing the degree of protein (albumin) adsorption.
Controlling the surface properties and structure of thin nanosized coatings is of primary importance in diverse engineering and medical applications. Here we report on how the nanostructure, growth mechanism, thickness, roughness, and hydrophilicity of nanocomposites composed of weak natural or strong synthetic polyelectrolytes (PE) can be tailored by graphene oxide (GO) doping. GO reverses the build‐up mechanism affecting the internal structure and the hydrophilicity in a way depending on the type of the PE‐matrix. The extent of GO‐adsorption and its impact on the surface morphology was found to be independent on the type of the underlying PE‐matrix. The nanostructure of the hybrid films is not significantly altered when a single surface‐exposed GO‐layer is deposited, while increasing the number of embedded GO‐layers leads to pronounced surface heterogeneity. These results are expected to have valuable impact on the construction strategies of coatings with tunable surface properties.
The proper selection of a demand forecasting method is directly linked to the success of supply chain management (SCM). However, today’s manufacturing companies are confronted with uncertain and dynamic markets. Consequently, classical statistical methods are not always appropriate for accurate and reliable forecasting. Algorithms of Artificial intelligence (AI) are currently used to improve statistical methods. Existing literature only gives a very general overview of the AI methods used in combination with demand forecasting. This paper provides an analysis of the AI methods published in the last five years (2017-2021). Furthermore, a classification is presented by clustering the AI methods in order to define the trend of the methods applied. Finally, a classification of the different AI methods according to the dimensionality of data, volume of data, and time horizon of the forecast is presented. The goal is to support the selection of the appropriate AI method to optimize demand forecasting.
The early involvement of experiences gained through intelligence and data analysis is becoming increasingly important in order to develop new products, leading to a completely different conception of product creation, development and engineering processes using the advantages that the dedication of the digital twin entails. Introducing a novel stage gate process in order to be holistically anchored in learning factories adopting idea generation and idea screening in an early stage, beta testing of first prototypes, technical implementation in real production scenarios, business analysis, market evaluation, pricing, service models as well as innovative social media portals. Corresponding product modelling in the sense of sustainability, circular economy, and data analytics forecasts the product on the market both before and after market launch with the interlinking of data interpretation nearby in real-time. The digital twin represents the link between the digital model and the digital shadow. Additionally, the connection of the digital twin with the product provides constantly updated operating status and process data as well as mapping of technical properties and real-world behaviours. A future-networking product, by embedded information technology with the ability to initiate and carry out one's own further development, is able to interact with people and environments and thus is relevant to the way of life of future generations. In today's development work for this new product creation approach, on one hand, "Werk150" is the object of the development itself and on the other hand the validation environment. In the next step, new learning modules and scenarios for trainings at master level will be derived from these findings.
Das Ziel dieser Arbeit war die Umsetzung eines Wahrnehmungsensors für Softwareagenten, die über ein virtuelles Menschmodell in einer dreidimensionalen Umgebung agieren. Hierbei sollen die Agenten über den Sensor in der Lage sein, semantische Informationen zu geometrischen Objekten in der Umgebung zu erhalten. Hierfür wurden zwei Verfahren umgesetzt, die das menschliche Sehen simulieren, indem Objekte erkannt werden, wenn diese innerhalb eines Sichtfelds liegen. Ein Problem, das dabei gelöst werden muss, ist die Identifizierung möglicher Verdeckungen der Objekte. Ein Ansatz, dieses Problem zu lösen, ist der Ray-Tracing Ansatz, welcher für das erste Verfahren umgesetzt wurde. Das zweite Verfahren verwendet den Occlusion-Culling Ansatz. Auswertungen beider Verfahren haben gezeigt, dass der Ray-Tracing Ansatz eine schnellere Laufzeit aufweist, der Occlusion-Culling Ansatz jedoch mehr unverdeckte Objekte im Sichtfeld erkennt.
This paper is concerned with the study, optimization and control of the moisture sorption kinetics of agricultural products at temperatures typically found in processing and storage. A nonlinear autoregressive with exogenous inputs (NARX) neural network was developed to predict moisture sorption kinetics and consequently equilibrium moisture contents of shiitake mushrooms (Lentinula edodes (Berk.) Pegler) over a wide range of relative humidity and different temperatures. Sorption kinetic data of mushroom caps was separately generated using a continuous, gravimetric dynamic vapour sorption analyser at emperatures of 25-40 °C over a stepwise variation of relative humidity ranging from 0 to 85%. The predictive power of the neural network was based on physical data, namely relative humidity and temperature. The model was fed with a total of 4500 data points by dividing them into three subsets, namely, 70% of the data was used for training, 15% of the data for testing and 15% of the data for validation, randomly selected from the whole dataset. The NARX neural network was capable of precisely simulating equilibrium moisture contents of mushrooms derived from the dynamic vapour sorption kinetic data throughout the entire range of relative humidity.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
Being exposed to compulsory religious education in school can have long-run consequences for students’ lives. At different points in time since the 1970s, German states terminated compulsory religious education in public schools and replaced it by a choice between ethics classes and religious education. This article shows that the reform not only led to reduced religiosity in students’ later life, but also eroded traditional attitudes towards gender roles and increased labor-market participation and earnings.
Nowadays, the importance of early active patient mobilization in the recovery and rehabilitation phase has increased significantly. One way to involve patients in the treatment is a gamification-like approach, which is one of the methods of motivation in various life processes. This article shows a system prototype for patients who require physical activity because of active early mobilization after medical interventions or during illness. Bedridden patients and people with a sedentary lifestyle (predominantly lying in bed) are also potential users. The main idea for the concept was non-contact system implementation for the patients making them feel effortless during its usage. The system consists of three related parts: hardware, software, and game application. To test the relevance and coherence of the system, it was used by 35 people. The participants were asked to play a video game requiring them to make body movements while lying down. Then they were asked to take part in a small survey to evaluate the system's usability. As a result, we offer a prototype consisting of hardware and software parts that can increase and diversify physical activity during active early mobilization of patients and prevent the occurrence of possible health problems due to predominantly low activity. The proposed design can be possibly implemented in hospitals, rehabilitation centers, and even at home.
Monitoring heart rate and breathing is essential in understanding the physiological processes for sleep analysis. Polysomnography (PSG) system have traditionally been used for sleep monitoring, but alternative methods can help to make sleep monitoring more portable in someone's home. This study conducted a series of experiments to investigate the use of pressure sensors placed under the bed as an alternative to PSG for monitoring heart rate and breathing during sleep. The following sets of experiments involved the addition of small rubber domes - transparent and black - that were glued to the pressure sensor. The resulting data were compared with the PSG system to determine the accuracy of the pressure sensor readings. The study found that the pressure sensor provided reliable data for extracting heart rate and respiration rate, with mean absolute errors (MAE) of 2.32 and 3.24 for respiration and heart rate, respectively. However, the addition of small rubber hemispheres did not significantly improve the accuracy of the readings, with MAEs of 2.3 bpm and 7.56 breaths per minute for respiration rate and heart rate, respectively. The findings of this study suggest that pressure sensors placed under the bed may serve as a viable alternative to traditional PSG systems for monitoring heart rate and breathing during sleep. These sensors provide a more comfortable and non-invasive method of sleep monitoring. However, the addition of small rubber domes did not significantly enhance the accuracy of the readings, indicating that it may not be a worthwhile addition to the pressure sensor system.
Sleep analysis using a Polysomnography system is difficult and expensive. That is why we suggest a non-invasive and unobtrusive measurement. Very few people want the cables or devices attached to their bodies during sleep. The proposed approach is to implement a monitoring system, so the subject is not bothered. As a result, the idea is a non-invasive monitoring system based on detecting pressure distribution. This system should be able to measure the pressure differences that occur during a single heartbeat and during breathing through the mattress. The system consists of two blocks signal acquisition and signal processing. This whole technology should be economical to be affordable enough for every user. As a result, preprocessed data is obtained for further detailed analysis using different filters for heartbeat and respiration detection. In the initial stage of filtration, Butterworth filters are used.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
Thermoplastic polycarbonate urethane elastomers (TPCU) are potential implant materials for treating degenerative joint diseases thanks to their adjustable rubber-like properties, their toughness, and their durability. We developed a water-containing high-molecular-weight sulfated hyaluronic acid-coating to improve the interaction of TPCU with the synovial fluid. It is suggested that trapped synovial fluid can act as a lubricant that reduces the friction forces and thus provides an enhanced abrasion resistance of TPCU implants. Aims of this work were (i) the development of a coating method for novel soft TPCU with high-molecular sulfated hyaluronic acid to increase the biocompatibility and (ii) the in vitro validation of the functionalized TPCUs in cell culture experiments.
Knee osteoarthritis is a common complication and can lead to total loss of joint function in patients. Treatment by either partial or total knee replacement with appropriate UHMWPE based implantsis highly invasive, may cause complications and may show unsatisfying results. Alternatively, treatment may be done by insertion of an elastic interpositional knee spacer with optimized material characteristics.
We report the development of high performance polyurethane-based polymers modified with bioactive molecules for fabrication of such knee spacers. In order to tailor mechanical and tribological properties and to improve resist to enzymatic degradation we propose a core-shell model for the spacer with specifically adapted properties.
Polyurethane-bases block copolymers (TPCUs) are block-copolymers with systematically varied soft and hard segments. They have been suggested to serve as material for chondral implants in joint regeneration. Such applications may require the adhesion of chondrocytes to the implant surface, facilitating cell growth while keeping their phenotype. Thus, aims of this work were (1) to modify the surface of soft biostable polyurethane-based model implants (TPCU and TSiPCU) with high-molecular weight hyaluronic acid (HA) using an optimized multistep strategy of immobilization, and (2) to evaluate bioactivity of the modified TPCUs in vitro. Our results show no cytotoxic potential of the TPCUs. HAbioactive molecules (Mw =700kDa) were immobilized onto the polyurethane surface via polyethylenimine (PEI) spacers, and modifications were confirmed by several characterization methods. Tests with porcine chondrocytes indicated the potential of the TPCU-HA for inducing enhanced cell proliferation.
Die pharmazeutische Verpackungsindustrie ist durch umfangreiche Regularien geprägt und daher in der Innovationsdynamik etwas eingeschränkt. In einem sechsmonatigen Projekt zur Entwicklung von Zukunftsszenarien für die Pharmaverpackung wurde aufgezeigt, dass zwar neue Technologien, wie E-Labels oder Kindersicherungen, die Marktreife erreicht haben oder in Kürze erreichen werden, neue Anforderungen in absehbarer Zukunft aber weiteren Entwicklungsbedarf erfordern. Die pharmazeutische Verpackungsindustrie muss sich zusammen mit ihren Kunden und Technologielieferanten enger und intensiver austauschen, um die nächste Verpackungsgeneration, Smart Packaging 2.0, auf den Weg zu bringen.
Die OLED-Technologie wurde vor über zehn Jahren als Revolution in der Verpackungs-industrie gefeiert, die jedoch in der Praxis ausblieb. In einem industriellen Kooperations-projekt zur Zukunftsszenarienentwicklung der pharmazeutischen Verpackungsindustrie stellt sich die OLED-Technologie als Schlüsseltechnologie für das Zukunftsszenario Smart Packaging 2.0 dar.
Sichtprüfungen von Produktoberflächen werden überwiegend von Mitarbeitern ausgeführt, wobei Automatisierungsansätze mit Kamera- und Bildverarbeitungssystemen großes Potenzial zeigen. Auch Cobots werden in Qualitätssicherungsprozesse einbezogen.Im Folgenden werden die Integrationsmöglichkeiten von Cobots in die Sichtprüfung diskutiert und ein Entscheidungsmodell dargestellt, mit dem Sichtprüfungsprozesse auf ihre Cobot-Tauglichkeit überprüft werden können. Das Entscheidungsmodell ist für die direkte Integration in bereits existierende Cobot-Eignungsuntersuchungsverfahren konzipiert und dient als erste strategische Entscheidungshilfe.
Mangels durchgängiger Datenstandards für Planungssysteme der Digitalen Fabrik müssen systemspezifische Datenaustauschlösungen implementiert werden. Zur Unterstützung der Planung ist ein durchgängiger Fabrikplanungsprozess mit integrierter Routenplanung sowohl prozess- als auch systemtechnisch erforderlich. Dafür werden beispielhaft ein Fabrik- und ein Routenplanungssystem auf ihre Kompatibilität untersucht, erforderliche Anforderungen abgeleitet und eine Datenaustausch-möglichkeit für den Anwender aufgezeigt.
Für die digitale 3D-VR-Fabrikplanung sind unterschiedliche Soft- und Hardwaresysteme am Markt verfügbar, die teilweise erhebliche Kompatibilitätsprobleme aufweisen. Für die Bewertung der Hardwareeignung für die 3D-VR-Fabrikplanung wird ein Bewertungssystem vorgestellt, das anhand konkreter Softwareapplikationen und einem passiven 3D-Stereo-Monitor mit Head-Tracking erläutert wird. Es wird dazu auch die Notwendigkeit des Einsatzes von Software-Middleware zur Nutzungssteigerung diskutiert.
Background
Alzheimer’s disease (AD) is diagnosed based upon medical history, neuropsychiatric examination, cerebrospinal fluid analysis, extensive laboratory analyses and cerebral imaging. Diagnosis is time consuming and labour intensive. Parkinson’s disease (PD) is mainly diagnosed on clinical grounds.
Objective
The primary aim of this study was to differentiate patients suffering from AD, PD and healthy controls by investigating exhaled air with the electronic nose technique. After demonstrating a difference between the three groups the secondary aim was the identification of specific substances responsible for the difference(s) using ion mobility spectroscopy. Thirdly we analysed whether amyloid beta (Aβ) in exhaled breath was causative for the observed differences between patients suffering from AD and healthy controls.
Methods
We employed novel pulmonary diagnostic tools (electronic nose device/ion-mobility spectrometry) for the identification of patients with neurodegenerative diseases. Specifically, we analysed breath pattern differences in exhaled air of patients with AD, those with PD and healthy controls using the electronic nose device (eNose). Using ion mobility spectrometry (IMS), we identified the compounds responsible for the observed differences in breath patterns. We applied ELISA technique to measure Aβ in exhaled breath condensates.
Results
The eNose was able to differentiate between AD, PD and HC correctly. Using IMS, we identified markers that could be used to differentiate healthy controls from patients with AD and PD with an accuracy of 94%. In addition, patients suffering from PD were identified with sensitivity and specificity of 100%. Altogether, 3 AD patients out of 53 participants were misclassified. Although we found Aβ in exhaled breath condensate from both AD and healthy controls, no significant differences between groups were detected.
Conclusion
These data may open a new field in the diagnosis of neurodegenerative disease such as Alzheimer’s disease and Parkinson’s disease. Further research is required to evaluate the significance of these pulmonary findings with respect to the pathophysiology of neurodegenerative disorders.
With the progress of technology in modern hospitals, an intelligent perioperative situation recognition will gain more relevance due to its potential to substantially improve surgical workflows by providing situation knowledge in real-time. Such knowledge can be extracted from image data by machine learning techniques but poses a privacy threat to the staff’s and patients’ personal data. De-identification is a possible solution for removing visual sensitive information. In this work, we developed a YOLO v3 based prototype to detect sensitive areas in the image in real-time. These are then deidentified using common image obfuscation techniques. Our approach shows that it is principle suitable for de-identifying sensitive data in OR images and contributes to a privacyrespectful way of processing in the context of situation recognition in the OR.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
Organisationen sind immer mehr gefragt, auch digitale Arbeitsumgebungen bewusst zu formen. Neue Technologien und digitale Arbeitspraktiken verlagern den Ort, an dem eine gemeinsame Identität gebildet wird, zunehmend in virtuelle Räume. Bislang fokussieren sich Führungskräfte und Change Manager jedoch zu sehr auf Dinge, die sie anfassen und plastisch gestalten können. Die Autoren erörtern daher, wie Unternehmen auch in virtuellen Arbeitswelten die organisationale Identität gestalten und aufrechterhalten können, um auf diese Weise das Change Management zu unterstützen.
The powder coating of veneered particle boards by the sequence electrostatic powder application -powder curing via hot pressing is studied in order to create high gloss surfaces. To obtain an appealingaspect, veneer Sheets were glued by heat and pressure on top of particle boards and the resulting surfaceswere used as carrier substrates for powder coat finishing. Prior to the powder coating, the veneeredparticle board surfaces were pre-treated by sanding to obtain good uniformity and the boards werestored in a climate chamber at controlled temperature and humidity conditions to adjust an appropriate electrical surface resistance. Characterization of surface texture was done by 3D microscopy. The surfaceelectrical resistance was measured for the six veneers before and after their application on the particleboard surface. A transparent powder top-coat was applied electrostatically onto the veneered particleboard surface. Curing of the powder was done using a heated press at 130◦C for 8 min and a smooth, glossy coating was obtained on the veneered surfaces. By applying different amounts of powder thecoating thickness could be varied and the optimum amount of powder was determined for each veneer type.
In the powder coating of veneered particle boards the highly reactive hybrid epoxy/polyester powder transparent Drylac 530 Series from TIGER Coatings GmbH & Co. KG, Wels, Austria was used. Curing is accelerated by a mixture of catalysts reaching curing times of 3 min at 150 °C or 5 min at 135 °C which allows for energy and time savings making Drylac Series 530 powder suitable for the coating of temperaturesensitive substrates such as MDF and wood.
Decorative laminates based on melamine formaldehyde (MF) resin impregnated papers are used at great extent for surface finishing of engineered wood that is used for furniture, kitchen, and working surfaces, flooring and exterior cladding. In all these applications, optically flawless appearance is a major issue. The work described here is focused on enhancing the cleanability and antifingerprint properties of smooth, matt surface-finished melamine-coated particleboards for furniture fronts, without at the same time changing or deteriorating other important surface parameters such as hardness, roughness or gloss. In order to adjust the surface polarity of a low pressure melamine film, novel interface-active macromolecular compounds were prepared and tested for their suitability as an antifingerprint additive. Two hydroxy-functional surfactants (polydimethysiloxane, PDMS-OH and perfluoroether, PF-OH) were oxidized under mild conditions to the corresponding aldehydes (PDMS-CHO and PF-CHO) using a pyridinium chlorochromate catalyst. With the most promising oxidized polymeric additive, PDMS-CHO, the contact angles against water, n-hexadecane, and squalene increased from 79.8°, 26.3° and 31.4° for the pure MF surface to 108.5°, 54.8°, and 59.3°, respectively, for the modified MF surfaces. While for the laminated MF surface based on the oxidized fluoroether the gloss values were much higher than required, for the surfaces based on oxidized polydimethylsiloxane the technological values as well as the lower gloss values were in agreement with the requirements and showed much improved surface cleanability, as was also confirmed by colorimetric measurements.
The tale of 1000 cores: an evaluation of concurrency control on real(ly) large multi-socket hardware
(2020)
In this paper, we set out the goal to revisit the results of “Starring into the Abyss [...] of Concurrency Control with [1000] Cores” and analyse in-memory DBMSs on today’s large hardware. Despite the original assumption of the authors, today we do not see single-socket CPUs with 1000 cores. Instead multi-socket hardware made its way into production data centres. Hence, we follow up on this prior work with an evaluation of the characteristics of concurrency control schemes on real production multi-socket hardware with 1568 cores. To our surprise, we made several interesting findings which we report on in this paper.
In this paper, we propose a radical new approach for scale-out distributed DBMSs. Instead of hard-baking an architectural model, such as a shared-nothing architecture, into the distributed DBMS design, we aim for a new class of so-called architecture-less DBMSs. The main idea is that an architecture-less DBMS can mimic any architecture on a per-query basis on-the-fly without any additional overhead for reconfiguration. Our initial results show that our architecture-less DBMS AnyDB can provide significant speedup across varying workloads compared to a traditional DBMS implementing a static architecture.
In our initial DaMoN paper, we set out the goal to revisit the results of “Starring into the Abyss [...] of Concurrency Control with [1000] Cores” (Yu in Proc. VLDB Endow 8: 209-220, 2014). Against their assumption, today we do not see single-socket CPUs with 1000 cores. Instead, multi-socket hardware is prevalent today and in fact offers over 1000 cores. Hence, we evaluated concurrency control (CC) schemes on a real (Intel-based) multi-socket platform. To our surprise, we made interesting findings opposing results of the original analysis that we discussed in our initial DaMoN paper. In this paper, we further broaden our analysis, detailing the effect of hardware and workload characteristics via additional real hardware platforms (IBM Power8 and 9) and the full TPC-C transaction mix. Among others, we identified clear connections between the performance of the CC schemes and hardware characteristics, especially concerning NUMA and CPU cache. Overall, we conclude that no CC scheme can efficiently make use of large multi-socket hardware in a robust manner and suggest several directions on how CC schemes and overall OLTP DBMS should evolve in future.
In this paper, we present a new approach for achieving robust performance of data structures making it easier to reuse the same design for different hardware generations but also for different workloads. To achieve robust performance, the main idea is to strictly separate the data structure design from the actual strategies to execute access operations and adjust the actual execution strategies by means of so-called configurations instead of hard-wiring the execution strategy into the data structure. In our evaluation we demonstrate the benefits of this configuration approach for individual data structures as well as complex OLTP workloads.
This booklet will give you an overview of the development of CSR from a (brief) historic point of view and will examine the underlying concepts and research. Furthermore, examples of contemporary CSR management will be explored to show how companies Interpret the issue and how they face the challenges of managing the new demands placed upon them. Business, in the end, comes down to figures and numbers which give management, shareholders and stakeholders a chance to measure a company’s success. Therefore, modern methods and approaches for measuring, rating and ranking a company’s CSR management will be presented. Finally, an attempt will be made to evaluate CSR as a tool for increasing global welfare and as a business and management strategy for companies and entrepreneurs.
Die öffentliche Verwaltung und die in ihr lebenden und arbeitenden Menschen sehen sich häufig mit einer institutionalisierten Dilemma-Situation konfrontiert. Die Ursachen hierfür sind darin zu sehen, dass öffentliches Verwaltungshanden mit sehr wenigen Ausnahmen keinem Selbstzweck dient. Stattdessen dient es anderen Funktionssystmen und wird mit deren binären (Funktions-)Codes beobachtet und zwangsnotwendig bewertet. Die Möglichkeiten des Einzelnen, steuernd und gegebenenfalls korrigieren einzugreifen, sind in einer modernen durch extrem hohe Komplexität und (internationale) Verflechtung bestimmten Gesellschaft gering.
Die Einführung CSR- und wertebasierter Unternehmensziele und Managementmethoden wird von Führungskräften und Mitarbeitern häufig als Überforderung empfunden und löst Bedenken und teilweise Ängste aus. Diesem Phänomen kann alleine durch eine gelungene Schulung in den Theorien und Methoden entgegengetreten werden. Das hier vorgeschlagene Sechs-Schritte-Programm zur Schulung dieser Theorien und Methoden weckt das Bewusstsein für die Notwendigkeit eines Paradigmenwechsels und vermittelt den betroffenen Individuen die erforderlichen Kenntnisse und Werkzeuge, sich dieser Herausforderung zu stellen. In sechs Arbeitsschritten wird von der Phänomenologie der derzeitigen Unternehmenswelt über die theoretische Analyse der Situation bis hin zur Vorstellung geeigneter Tools und der möglichen Risiken ein Weg zur erfolgreichen Schulung gezeigt.
The present publication reports the purification effort of two natural bone blocks, that is, an allogeneic bone block (maxgraft®, botiss biomaterials GmbH, Zossen, Germany) and a xenogeneic block (SMARTBONE®, IBI S.A., Mezzovico Vira, Switzerland) in addition to previously published results based on histology. Furthermore, specialized scanning electron microscopy (SEM) and in vitro analyses (XTT, BrdU, LDH) for testing of the cytocompatibility based on ISO 10993-5/-12 have been conducted. The microscopic analyses showed that both bone blocks possess a trabecular structure with a lamellar subarrangement. In the case of the xenogeneic bone block, only minor remnants of collagenous structures were found, while in contrast high amounts of collagen were found associated with the allogeneic bone matrix. Furthermore, only island-like remnants of the polymer coating in case of the xenogeneic bone substitute seemed to be detectable. Finally, no remaining cells or cellular remnants were found in both bone blocks. The in vitro analyses showed that both bone blocks are biocompatible. Altogether, the purification level of both bone blocks seems to be favorable for bone tissue regeneration without the risk for inflammatory responses or graft rejection. Moreover, the analysis of the maxgraft® bone block showed that the underlying purification process allows for preserving not only the calcified bone matrix but also high amounts of the intertrabecular collagen matrix.
Introduction: Bioresorbable collagenous barrier membranes are used to prevent premature soft tissue ingrowth and to allow bone regeneration. For volume stable indications, only non-absorbable synthetic materials are available. This study investigates a new bioresorbable hydrofluoric acid (HF)-treated magnesium (Mg) mesh in a native collagen membrane for volume stable situations. Materials and Methods: HF-treated and untreated Mg were compared in direct and indirect cytocompatibility assays. In vivo, 18 New Zealand White Rabbits received each four 8 mm calvarial defects and were divided into four groups: (a) HF-treated Mg mesh/collagen membrane, (b) untreated Mg mesh/collagen membrane (c) collagen membrane and (d) sham operation. After 6, 12 and 18 weeks, Mg degradation and bone regeneration was measured using radiological and histological methods. Results: In vitro, HF-treated Mg showed higher cytocompatibility. Histopathologically, HF-Mg prevented gas cavities and was degraded by mononuclear cells via phagocytosis up to 12 weeks. Untreated Mg showed partially significant more gas cavities and a fibrous tissue reaction. Bone regeneration was not significantly different between all groups. Discussion and Conclusions: HF-Mg meshes embedded in native collagen membranes represent a volume stable and biocompatible alternative to the non-absorbable synthetic materials. HF-Mg shows less corrosion and is degraded by phagocytosis. However, the application of membranes did not result in higher bone regeneration.
Analog-/Mixed-Signal (AMS) design verification is one of the most challenging and time consuming tasks of todays complex system on chip (SoC) designs. In contrast to digital system design, AMS designers have to deal with a continuous state space of conservative quantities, highly nonlinear relationships, non-functional influences, etc. enlarging the number of possibly critical scenarios to infinity. In this special session we demonstrate the verification of functional properties using simulative and formal methods. We combine different approaches including automated abstraction and refinement of mixed-level models, state-space discretization as well as affine arithmetic. To reach sufficient verification coverage with reasonable time and effort, we use enhanced simulation schemes to avoid conventional simulation drawbacks.
An integrated synchronous buck converter with a high resolution dead time control for input voltages up to 48V and 10MHz switching frequency is presented. The benefit of an enhanced dead time control at light loads to enable zero voltage switching at both the high-side and low-side switch at low output load is studied. This way, compact multi-MHz DCDC converters can be implemented at high efficiency over a wide load current range. The concept also eliminates body diode forward conduction losses and minimizes reverse recovery losses. A dead time resolution of 125 ps is realized by an 8-bit differential delay chain. A further efficiency enhancement by soft switching at the high-side switch at light load is achieved with a voltage boost of the switching node by dead time control in forced continuous conduction mode. The monolithic converter is implemented in an 180nm high-voltage BiCMOS technology. At V IN = 48V, V OUT = 5V, 50mA load, 10MHz switching frequency and 500 nH output inductance, the efficiency is measured to be increased by 14.4% compared to a conventional predictive dead time control. A peak efficiency of 80.9% is achieved at 12V input.
Different sensor types using chemical and biochemical principles are described. The former are mainly gas sensors, the latter are applied especially to liquids. Those label-free direct detection methods are compared with applications where assays take advantage of labeled receptors.
Furthermore, selected applications in the area of gas sensors are discussed, and sensors for process control, point-of-care diagnostics, environmental analytics, and food analytics are reviewed. In addition, multiplexing approaches used in microplates and microarrays are described.
On account of the huge number of sensor types and the wide range of possible applications, only the most important ones are selected here.
Der Anteil mittelständischer Unternehmen, die Standorte im Ausland unterhalten, nimmt seit einigen Jahren zu. Oft finden Auslandsaktivitäten dieser Art in Niedriglohnländern statt. Dort ergeben sich u.a durch die infrastrukturellen Gegebenheiten und durch die verfügbaren Personalressourcen diverse Herausforderungen, insbesondere für die Produktivitätsermittlung und -bewertung innerhalb der Produktion. Dieser Beitrag soll für diese Herausforderungen geeignete Technologien und eine mögliche Vorgehensweise für deren Auswahl vor dem Hintergrund der ländertypischen Herausforderungen aufzeigen.
Alle DAX30-Unternehmen kommunizieren ihre Kapitalkosten, ausgelöst einerseits aus IFRS-Vorgaben, andererseits, weil sie ihre wertorientierte Performancemessung und -steuerung belegen wollen. Bei der Berechnung der Kapitalkosten verwenden die Unternehmen i. d. R. den WACC-Ansatz. Die Tiefe der Angaben variiert von der bloßen Bekanntgabe eines Prozentsatzes bis hin zur vollständigen Offenlegung aller Inputfaktoren für deren Berechnung. Die Autoren argumentieren, dass die Transparenz der Kapitalkosten jedoch wenig Mehrwert schafft, da die in die Berechnung einfließenden Parameter wie z. B. risikoloser Zins, Marktrendite oder unternehmensindividuelles Beta stark schwanken bzw. nahezu willkürlich ermittelt werden. Die von den DAX30 Konzernen zurzeit praktizierte Form der Transparenz schafft für die Adressaten der Geschäftsberichte daher nur einen geringen Erkenntnisgewinn.
Der eine Eingliederungsvereinbarung ersetzende Verwaltungsakt ist rechtswidrig, wenn die gesetzlich vorgesehene Geltungsdauer ohne Ermessenserwägungen überschritten wird.
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
Glioblastoma WHO IV belongs to a group of brain tumors that are still incurable. A promising treatment approach applies photodynamic therapy (PDT) with hypericin as a photosensitizer. To generate a comprehensive understanding of the photosensitizer-tumor interactions, the first part of our study is focused on investigating the distribution and penetration behavior of hypericin in glioma cell spheroids by fluorescence microscopy. In the second part, fluorescence lifetime imaging microscopy (FLIM) was used to correlate fluorescence lifetime (FLT) changes of hypericin to environmental effects inside the spheroids. In this context, 3D tumor spheroids are an excellent model system since they consider 3D cell–cell interactions and the extracellular matrix is similar to tumors in vivo. Our analytical approach considers hypericin as probe molecule for FLIM and as photosensitizer for PDT at the same time, making it possible to directly draw conclusions of the state and location of the drug in a biological system. The knowledge of both state and location of hypericin makes a fundamental understanding of the impact of hypericin PDT in brain tumors possible. Following different incubation conditions, the hypericin distribution in peripheral and central cryosections of the spheroids were analyzed. Both fluorescence microscopy and FLIM revealed a hypericin gradient towards the spheroid core for short incubation periods or small concentrations. On the other hand, a homogeneous hypericin distribution is observed for long incubation times and high concentrations. Especially, the observed FLT change is crucial for the PDT efficiency, since the triplet yield, and hence the O2 activation, is directly proportional to the FLT. Based on the FLT increase inside spheroids, an incubation time 30 min is required to achieve most suitable conditions for an effective PDT.
The early detection of head and neck cancer is a prolonged challenging task. It requires a precise and accurate identification of tissue alterations as well as a distinct discrimination of cancerous from healthy tissue areas. A novel approach for this purpose uses microspectroscopic techniques with special focus on hyperspectral imaging (HSI) methods. Our proof-of-principle study presents the implementation and application of darkfield elastic light scattering spectroscopy (DF ELSS) as a non-destructive, high-resolution, and fast imaging modality to distinguish lingual healthy from altered tissue regions in a mouse model. The main aspect of our study deals with the comparison of two varying HSI detection principles, which are a point-by-point and line scanning imaging, and whether one might be more appropriate in differentiating several tissue types. Statistical models are formed by deploying a principal component analysis (PCA) with the Bayesian discriminant analysis (DA) on the elastic light scattering (ELS) spectra. Overall accuracy, sensitivity, and precision values of 98% are achieved for both models whereas the overall specificity results in 99%. An additional classification of model-unknown ELS spectra is performed. The predictions are verified with histopathological evaluations of identical HE-stained tissue areas to prove the model’s capability of tissue distinction. In the context of our proof-of-principle study, we assess the Pushbroom PCA-DA model to be more suitable for tissue type differentiations and thus tissue classification. In addition to the HE-examination in head and neck cancer diagnosis, the usage of HSI-based statistical models might be conceivable in a daily clinical routine.
Hybride Arbeitsmodelle gelten als Zukunft der Arbeit. Demnach beschäftigt sich die vorliegende Forschungsarbeit mit der Untersuchung hybrider Arbeitsmodelle im Hinblick auf deutsche kleine und mittlere Unternehmen (KMU) im Vergleich zu Großbetrieben. Mithilfe einer multi-methodischen Studie, bestehend aus einer Umfrage und qualitativen Experteninterviews, wird evaluiert, in welchem Maß hybride Arbeitsmodelle in KMU bereits etabliert sind und welche Herausforderungen sie dabei bewältigen müssen. Zusätzlich wird betrachtet, ob soziodemografische Faktoren wie Alter, Geschlecht oder Rolle im Unternehmen einen Einfluss auf hybrides Arbeiten haben.Die Ergebnisse zeigen, dass die Etablierung von hybriden Arbeitsmodellen in KMU im Gegensatz zu Großbetrieben weniger vorangeschritten ist. KMUs stehen vor vielfältigen Herausforderungen, die beispielsweise auf unzureichende Digitalisierung oder traditionellere Strukturen zurückzuführen sind. Insbesondere die Unternehmenskultur sowie die Rolle im Unternehmen und der Einfluss der Führungskraft spielen eine wichtige Rolle.Praktische Relevanz: Der Großteil vorliegender Literatur zum Thema New Work und Hybride Arbeit legt den Fokus auf die Gesamtbetrachtung aller Unternehmensgrößen oder auf Großbetriebe. Aufgrund der spezifischen Merkmale, wie beispielsweise eingeschränkter Ressourcenzugang, können Ergebnisse von Großbetrieben kaum auf KMU übertragen werden. Demnach gibt diese Arbeit eine Orientierung, wie hybride Arbeitsmodelle in KMU sinnvoll und gewinnbringend umgesetzt werden und welche Herausforderungen auftreten.
Changing requirements and qualification profiles of employees, increasingly complex digital systems up to artificial intelligence, missing standards for the seamless embedding of existing resources and unpredictable return on investments are just a few examples of the challenges of an SME in the age of digitalisation. In most cases there is a lack of suitable tools and methods to support companies in the digital transformation process in the value creation processes, but also of training and learning materials. A European research project (BITTMAS - Business Transformation towards Digitalisation and Smart systems, ERASMUS+, 2016-1 DE02-KA202-003437) with international partners from science, associations and industry has addressed this issue and developed various methods and instruments to support SMEs. Within the scope of a literature search, 16 suitable digitalisation concepts for production and logistics were identified. In the following, a learning platform with a literature database with multivariable sorting options according to branches and keywords of digitalisation, a video gallery with basic and advanced knowledge and a glossary were created in order to provide the user with consolidated and structured specialist knowledge. The 16 identifying concepts for transforming value-added processes in the context of digitalisation were transferred to a learning platform using developed learning paths in coaching and training to online course modules including test questions. A maturity model was developed and implemented in a self assessment tool for the analysis to identify the potential of digitalisation in production and logistics in relation to the current technological digitalisation level of the company. As a result, the user receives one or more of the 16 potential digitalisation concepts suggested or the delta for the necessary, not yet available enabler technologies is presented as a spider diagram. For a successful implementation of the identified suitable digitalisation concepts in production and logistics, a further tool was developed to identify supplementary requirements for all company divisions and stakeholders in relation to the "digital transformation" in the form of a self-evaluation. This paper presents the methods and tools developed, the accompanying learning materials and the learning platform.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
Im Rahmen der wissenschaftlichen Vertiefung an der Hochschule Reutlingen befasst sich diese Arbeit mit der Untersuchung der Anforderungen und der Machbarkeit zur computergestützten Erkennung der Deutschen Gebärdensprache (DGS) und des deutschen Fingeralphabets. Die Erkenntnisse aus dieser Arbeit dienen als Grundlage zur Entwicklung eines Systems zur Übersetzung von Gebärden der DGS oder des Fingeralphabets in die deutsche Schriftsprache. Zunächst werden grundlegende Informationen zu Geschichte, Aufbau und Grammatik der DGS und des Fingeralphabets aufgeführt. Die Erkennung der Gebärden soll durch optische Bewegungssensoren erfolgen. Hierfür werden unterschieliche Sensortypen betrachtet und verglichen. Im weiteren Verlauf erfolgt die Analyse der benutzerspezifischen und technischen Anforderungen. Erstere basieren auf der Befragung einer Fokusgruppe aus gehörlosen und hörenden Menschen aus dem Bereich der Gehörlosen-, Schwerhörigen- und Sprachbehindertenpädagogik. Abgeleitet aus den Informationen der Anforderungsanalyse ergibt sich, bis zu einem gewissen Grad, die Machbarkeit aus technischer und benutzerspezifischer Sicht. Abschließend erfolgen die Zusammenfassung der Anforderungen, welche an das zu entwickelnde System gestllt werden, sowie eine Handlungsempfehlung für die Entwicklung eines Prototyps.
The unprecedented acceleration in the dynamics of economic development and its dependence on global interactions makes predicting the future especially difficult. Nevertheless, an examination of long-term trends provides an opportunity to begin a discussion about what reality could await us tomorrow and how we want to deal with it. With this food-for-thought paper, the member institutes of the Fraunhofer Group for Innovation Research wish to present a selection of the trends that are destined to have a significant impact on innovation systems in the period leading up to 2030. Based on these trends, the paper derives theses for innovation in the year 2030 and describes the resulting tasks for business, politics, science and society.
Die Dynamik der wirtschaftlichen Entwicklung und deren Abhängigkeit von globalen Wechselwirkungen wachsen heute schneller denn je. Das macht Zukunftsprognosen besonders schwierig. Dennoch bietet der Blick auf langfristig prägende Trends die Chance, eine Diskussion darüber zu eröffnen, welche Realität uns morgen erwarten könnte und wie wir damit umgehen wollen.
Dieses Impulspapier stellt aus Sicht der Mitgliedsinstitute des Fraunhofer Verbunds Innovationsforschung eine Auswahl derjenigen Trends dar, die Innovationssysteme im Zeitraum bis 2030 wesentlich beeinflussen werden. Auf dieser Grundlage werden Thesen für Innovation im Jahr 2030 abgeleitet und beschrieben, welche Aufgaben sich daraus für Wirtschaft, Politik, Wissenschaft und Gesellschaft ergeben.
Purpose: The purpose of this study was to investigate the value of the web representation of certain fashion hot spots and how these results can be shown on fashion maps in an illustrated way.
Design/methodology/approach: A new ranking was created, which was evaluated with a self-instructed index, to gain solid results. Numbers were collected from Google, Instagram, Facebook, Twitter and web.alert.io. Additionally, fashion maps were created for an illustrative visualization of the results.
Findings: Compared with the ranking of a trend forecasting agency, called Global Language Monitor, which concepted a ranking of non-virtual fashion cities, the web representation and therefore the ranking of the research project, differs mainly in the situation of the cities among the first 10, viz. the rank on which a city occurs, but fewer in the actual cities mentioned.
Research limitations: The research was limited to subjective analysis of data, leading to partly subjective results, as well as the selected number of social media platforms, that had been used.
Originality/value: This is the first study to explore the web representation value of fashion metropolises in comparison to their non-virtual ranking. The results are partly based on results that already existed, concerning transformations of fashion cities or in general which cities own the status of a fashion city.
The basic idea behind a wearable robotic grasp assistancesystem is to support people that suffer from severe motor impairments in daily activities. Such a system needs to act mostly autonomously and according to the user’s intent. Vision-based hand pose estimation could be an integral part of a larger control and assistance framework. In this paper we evaluate the performance of egocentric monocular hand pose estimation for a robot-controlled hand exoskeleton in a simulation. For hand pose estimation we adopt a Convolutional Neural Network (CNN). We train and evaluate this network with computer graphics, created by our own data generator. In order to guide further design decisions we focus in our experiments on two egocentric camera viewpoints tested on synthetic data with the help of a 3D-scanned hand model, with and without an exoskeleton attached to it.We observe that hand pose estimation with a wrist-mounted camera performs more accurate than with a head-mounted camera in the context of our simulation. Further, a grasp assistance system attached to the hand alters visual appearance and can improve hand pose estimation. Our experiment provides useful insights for the integration of sensors into a context sensitive analysis framework for intelligent assistance.
Die Ionenmobilitätsspektrometrie ist eine gasanalytische Methode, die analytisch zwischen Sensoren auf der einen Seite und Spektrometern auf der anderen angesiedelt ist. Ihre Vorteile liegen darin, auch komplexere Gasgemische als Sensoren erfolgreich vor Ort und online sowie bettseitig im Krankenhaus analysieren zu können. Beispiele als dem Bereich Bio- und Prozessanalytik sollen die jeweiligen Ansätze und das Potential von der Fragestellung über die jeweils spezifische Lösung bis hin zum Ergebnis am Prozess exemplarisch zusammenstellen. Hierbei werden sowohl die analytische Sicht als auch die Marktsicht thematisiert.
Background: Conventional methods for lung cancer detection including computed tomography (CT) and bronchoscopy are expensive and invasive. Thus, there is still a need for an optimal lung cancer detection technique. Methods: The exhaled breath of 50 patients with lung cancer histologically proven by bronchoscopic biopsy samples (32 adenocarcinomas, 10 squamous cell carcinomas, 8 small cell carcinomas), were analyzed using ion mobility spectrometry (IMS) and compared with 39 healthy volunteers. As a secondary assessment, we compared adenocarcinoma patients with and without epidermal growth factor receptor (EGFR) mutation. Results: A decision tree algorithm could separate patients with lung cancer including adenocarcinoma, squamous cell carcinoma and small cell carcinoma. One hundred-fifteen separated volatile organic compound (VOC) peaks were analyzed. Peak-2 noted as n-Dodecane using the IMS database was able to separate values with a sensitivity of 70.0% and a specificity of 89.7%. Incorporating a decision tree algorithm starting with n-Dodecane, a sensitivity of 76% and specificity of 100% was achieved. Comparing VOC peaks between adenocarcinoma and healthy subjects, n-Dodecane was able to separate values with a sensitivity of 81.3% and a specificity of 89.7%. Fourteen patients positive for EGFR mutation displayed a significantly higher n-Dodecane than for the 14 patients negative for EGFR (p<0.01), with a sensitivity of 85.7% and a specificity of 78.6%. Conclusion: In this prospective study, VOC peak patterns using a decision tree algorithm were useful in the detection of lung cancer. Moreover, n-Dodecane analysis from adenocarcinoma patients might be useful to discriminate the EGFR mutation.
Um sich in einem schnelllebigen und globalen Markt nachhaltig wettbewerbsfähig aufzustellen, bedarf es innovativer Ansätze, Produkte sichtbar zu machen. Vorreiter wie Apple oder Microsoft stehen mit ihren Marketingstrategien und der Präsentation ihrer Produkte für eine neue Denkweise. Doch wie kann ein klein- oder mittelständiges Unternehmen (KMU) mit solchen Strategien konkurrieren und sich und die eigenen Produkte am Markt erfolgreich platzieren? Der vorliegende Beitrag zeigt auf, wie ein Markteinführungskonzept mithilfe des Design-Thinking-Ansatzes auf Basis der Kundenbedürfnisse modular und skalierbar ausgestaltet werden kann, um auf die jeweiligen Anforderungen des einzuführenden Produktes adaptierbar zu sein.
Additive Manufacturing is increasingly used in the industrial sector as a result of continuous development. In the Production Planning and Control (PPC) system, AM enables an agile response in the area of detailed and process planning, especially for a large number of plants. For this purpose, a concept for a PPC system for AM is presented, which takes into account the requirements for integration into the operational enterprise software system. The technical applicability will be demonstrated by individual implemented sections. The presented solution approach promises a more efficient utilization of the plants and a more elastic use.
Development work within an experimental environment, in which certain properties are investigated and optimized, requires many test runs and is therefore often associated with long execution times, costs and risks. This can affect product, material and technology development in industry and research. New digital driver technologies offer the possibility to automate complex manual work steps in a cost-effective way, to increase the relevance of the results and to accelerate the processes many times over. In this context, this article presents a low-cost, modular and open-source machine vision system for test execution and evaluates it on the basis of a real industrial application. For this purpose a methodology for the automated execution of the load intervals, the process documentation and for the evaluation of the generated data by means of machine learning to classify wear levels. The software and the mechanical structure are designed to be adaptable to different conditions, components and for a variety of tasks in industry and research. The mechanical structure is required for tracking the test object and represents a motion platform with independent positioning by machine vision operators or machine learning. An evaluation of the state of the test object is performed by the transfer learning after the initial documentation run. The manual procedure for classifying the visually recorded data on the state of the test object is described for the training material. This leads to an increased resource efficiency on the material as well as on the personnel side since on the one hand the significance of the tests performed is increased by the continuous documentation and on the other hand the responsible experts can be assigned time efficiently. The presence and know-how of the experts are therefore only required for defined and decisive events during the execution of the experiments. Furthermore, the generated data are suitable for later use as an additional source of data for predictive maintenance of the developed object.
Additive manufacturing (AM) is a promising manufacturing method for many industrial sectors. For this application, industrial requirements such as high production volumes and coordinated implementation must be taken into account. These tasks of the internal handling of production facilities are carried out by the Production Planning and Control (PPC) information system. A key factor in the planning and scheduling is the exact calculation of manufacturing times. For this purpose we investigate the use of Machine Learning (ML) for the prediction of manufacturing times of AM facilities.
The use of additive manufacturing technologies for industrial production is constantly growing. This technology differs from the known production proecdures. The areas for scheduling, detailed and sequence planning are particularly important for additive production due to the long print times and flexible use of the production area. Therefore, production-relevant variables are considered and used for the production planning and control (PPC) of additive manufacturing machines. For this purpose, an optimization model is presented which shows a time-oriented build space utilization. In the implementation, a nesting algorithm is used to check the combinability of different models for each individual print job.
The promise of immutable documents to make it easier and less expensive for consumers and producers to collaborate in a verifiable way would represent an enormous progress, especially as companies strive for establish service contracts which are based on the flow of many small transactions using machine-to-machine communication. The blockchain technology logs these data, verifies the authenticity and make them available for service offers. This work deals with an architecture enabling to setup order processing between consumers and produceers using blockchain. In this way, the technical feasibility is shown and the special characteristics of blockchain production networks will be discussed.
The blockchain technology enables a common data basis between the participants. Entries are logged and the authenticity of the participants is guaranteed. In the case of a relationship between customers and producers, this would lead to verifiable cooperation, which would be a major step as companies enter into service contracts based on the flow of many small transactions through communication. This paper proposes an architecture that enables the creation and processing of orders between the customer and producers via a blockchain based production network. The handling of larger files which are traceable via the blockchain is also shown and the use of a public or permissioned blockchain for an application case is also considered.
Sowohl bei den industriellen als auch wissenschaftlichen Institutionen nimmt die Anwendung der additiven Fertigung stetig zu und ist insbesondere in den Bereichen der Prototypenentwicklung nicht mehr wegzudenken. Die werkzeuglose Herstellung von Teilen ermöglicht eine dynamische Nutzung der Produktionsressourcen bis unmittelbar zum Fertigungsstart. Dies erlaubt, einerseits in den Bereichen der Feinterminierung und Ablaufplanung, agil auf Veränderungen zu reagieren und andererseits Modelle unterschiedlicher Fertigungsaufträge miteinander zu kombinieren, um somit eine hohe Effizienz der Fertigungsanlagen zu erreichen. Bei der Nutzung von multiplen Anlagen in einem Unternehmen oder im Partnerverbund stellt die vorhandene Intransparenz Unternehmen und Unternehmensnetzwerke vor viele Herausforderungen. Die Blockchain Technologie ermöglicht eine gemeinsame Datenbasis zwischen den Teilnehmern. Die Einträge werden protokolliert und die Authentizität der Teilnehmer wird gewährleistet. Dies führt, im Falle der Beziehung zwischen Kunden und Produzenten, zu einer nachprüfbaren Zusammenarbeit, da Unternehmen Dienstleistungsverträge abschließen, die auf dem Fluss vieler kleiner Transaktionen basieren. In diesem Beitrag wird dargestellt, wie verfügbare additive Fertigungsressourcen erkannt werden, sowie, unter der Verwendung der Blockchain-Technologie, in einem dezentralen Produktionsnetzwerk angeboten und von unterschiedlichen Akteuren genutzt werden können.
Pre-clinical evaluation of advanced nerve guide conduits using a novel 3D in vitro testing model
(2018)
Autografts are the current gold standard for large peripheral nerve defects in clinics despite the frequently occurring side effects like donor site morbidity. Hollow nerve guidance conduits (NGC) are proposed alternatives to autografts, but failed to bridge gaps exceeding 3 cm in humans. Internal NGC guidance cues like microfibres are believed to enhance hollow NGCs by giving additional physical support for directed regeneration of Schwann cells and axons. In this study, we report a new 3D in vitro model that allows the evaluation of different intraluminal fibre scaffolds inside a complete NGC. The performance of electrospun polycaprolactone (PCL) microfibres inside 5 mm long polyethylene glycol (PEG) conduits were investigated in neuronal cell and dorsal root ganglion (DRG) cultures in vitro. Z-stack confocal microscopy revealed the aligned orientation of neuronal cells along the fibres throughout the whole NGC length and depth. The number of living cells in the centre of the scaffold was not significantly different to the tissue culture plastic (TCP) control. For ex vivo analysis, DRGs were placed on top of fibre-filled NGCs to simulate the proximal nerve stump. In 21 days of culture, Schwann cells and axons infiltrated the conduits along the microfibres with 2.2 ± 0.37 mm and 2.1 ± 0.33 mm, respectively. We conclude that this in vitro model can help define internal NGC scaffolds in the future by comparing different fibre materials, composites and dimensions in one setup prior to animal testing.
In thermopervaporation the same economically favorable driving force as in membrane distillation, i.e., a temperature difference between feed and permeate for the transport, is used but with non-porous thin-film composite membranes. Membrane pores cannot be wetted and long-term operational stability can be achieved with the appropriate coating layer, but normally with a decrease of the flux compared to membrane distillation with porous hydrophobic membranes.
Porous asymmetric PVDF membranes were made to achieve low permeation resistance and pores which could be overcoated with polyelectrolyte polymers. This coating prohibits pore wetting and strongly reduces adsorption of organic substances.
Those membranes showed a high permeation rate for water due to a structure of phase-separated hydrophilic and hydrophobic three-dimensional domains. The permeation rates of these composite membranes for water is between 6 and 12 l/(h m²) at a feed temperature of 60 °C and permeate at a temperature of 40 °C of a 2% saline solution feed depending on the operational parameters. This is only a slight reduction of 10–15% in permeation rate compared to membrane distillation with porous hydrophobic membranes.
In whey dewatering experiment this membrane showed a constant performance over 4 days in intermittent operation mode and stability in cleaning with strong alkaline solution.
A vapor permeation processes for the separation of aromatic compounds from aliphatic compounds
(2014)
A number of rubbery and glassy membranes have been prepared and evaluated in vapor permeation experiments for separation of aromatic/aliphatic mixtures, using 5/95 (wt:wt) toluene/methylcyclohexane (MCH) as a model solution. Candidate membranes that met the required toluene/MCH selectivity of ≥ 10 were identified. The stability of the candidate membranes was tested by cycling the experiment between higher toluene concentrations and the original 5 wt% level. The best membrane produced has a toluene permeance of 280 gpu and a toluene/MCH selectivity of 13 when tested with a vapor feed of the model mixture at its boiling point and at atmospheric pressure. When a series of related membrane materials are compared, there is a sharp trade-off between membrane permeance and membrane selectivity. A process design study based on the experimental results was conducted. The best preliminary membrane design uses 45% of the energy of a conventional distillation process.
Die Ausrüstung von Textilien mit Sol-Gel-Beschichtungen wird seit einigen Jahren intensiv verfolgt. Eine Vielzahl von bekannten, aber auch neuen Ausrüstungseffekten können über diesen Ansatz realisiert werden. Besonders interessant ist die Sol-Gel-Technik wegen der Möglichkeiten, multifunktionelle Ausrüstungen zu synthetisieren. Problematisch ist eine in vielen Fällen geringe Beständigkeit solcher Ausrüstungen, insbesondere gegenüber Waschprozessen. Ziel des Projektes war es davon ausgehend, Vorbehandlungsstrategien für textile Fasermaterialien, basierend auf synthetischen Polymeren oder aus Naturfasern, zu entwickeln, die die Haltbarkeit von Sol-Gel-basierten Ausrüstungen verbessern. Im Rahmen der Arbeiten wurden, angepasst an die jeweiligen Faserpolymere - Polyethylenterephthalat, Polyamid, Polypropylen und Baumwolle - funktionelle Gruppen über geeignete Anker auf den Polymeren etabliert, die in der Lage sind, kovalente Bindungen zu Sol-Gel-basierten Beschichtungssystemen auszubilden. Als Anker wurden primär Trialkoxysilane verwendet, die zusätzlich z.B. Epoxy-, Isocyanato-, Azido- oder Amino-funktionelle Reste besitzen. Mit diesen Resten können die Anker kovalent an die Polymere angebunden werden. Die meisten Sol-Gel-basierten Systeme enthalten zumindest zu einem gewissen Anteil SiOx und/oder MexOy-Cluster. Die zur Funktionalisierung der Oberflächen eingesetzten Alkoxysilane können generell an solche Systeme/Cluster per Kondensation gebunden werden und dienen daher für die effektive Anbindung verschiedenster funktioneller Sol-Gel-Schichten. Entsprechend vorfunktionalisierte Substrate wurden in der Folge mit exemplarisch ausgewählten Sol-Gel-Ausrüstungen beschichtet. Dabei wurden für den Großteil der Untersuchungen hydrophobierende Sole appliziert. Vorteilhaft ist, dass sich der mit hydrophobierenden Solen erzielte Ausrüstungseffekt genau wie dessen Beständigkeit mit vergleichsweise überschaubarem Aufwand über die Untersuchung der Benetzbarkeit (DuPont-Noten, Kontaktwinkel, Tropfeneinsinkzeiten) charakterisieren lässt. Die Wirksamkeit der Vorbehandlungen wurde dann vor allem anhand von Untersuchungen zur Waschbeständigkeit der Ausrüstungen überprüft. Im Rahmen der Arbeiten konnte gezeigt werden, dass sich über die Etablierung geeigneter Anker die Beständigkeit von Sol-Gel-Ausrüstungen bzw. der daraus hervorgehenden Effekte verbessern lässt. Es zeigt sich gleichzeitig, dass die erzielten Verbesserungen sehr stark vom jeweiligen Sol abhängen. D.h., dass sich erzielte Verbesserungen nicht zwangsläufig auf andere Sol übertragen lassen. Analytische Charakterisierungen weisen darauf hin, dass in vielen Fällen die Beständigkeit der Beschichtungsnetzwerke selbst einen weit größeren Einfluss besitzt als die Anbindung an das Substrat. So zeigt sich bei verschiedenen Untersuchungen, dass die Auflage der Sol-Gel-Beschichtung vor allem nach einer ersten Wäsche, aber auch darüber hinaus, signifikant sinkt, oftmals aber ohne dass der durch Ausrüstung erzielte Effekt verloren geht. Dies deutet auf ein (Auf-)Lösen der Beschichtungsmatrizes hin, wovor die Anker nicht schützen können, da deren Wirkung auf die Grenzfläche zum Substrat beschränkt ist. Neben den hydrophobierenden Ausrüstungen wurden exemplarisch auch antibakterielle Ausrüstungen nach den entsprechenden Vorbehandlungen appliziert. Auch hier konnten Verbesserungen in der Beständigkeit des Effektes erzielt werden. Abschließend wurde untersucht inwieweit sich die Vorbehandlungen im Vergleich zur einfachen Ausrüstung negativ auf die textilen Produkte auswirken. Hierzu wurden relevante textile Parameter wie z.B. Höchstzugkräfte, Weißgrade, Steifigkeit oder Luftdurchlässigkeiten bestimmt. Diese Parameter wurden in der überwiegenden Zahl der Vorbehandlungen nicht oder nur geringfügig beeinflusst.
Military organizations have special features like following different organizational laws in times of peace and war and their specific embeddedness in society and politics. Especially the latter aspect has made the military an important object of study since the beginnings of modern sociology. In the wake of establishing specific sociological accounts, military sociology has been developed, dedicated to the different facets of the military. This research is based on different theoretical perspectives, but has hardly embraced the frameworks from economics and sociology of conventions (EC/SC) so far. The aim of the chapter is to explore and demonstrate the potentials of this approach. In a first step, the state of the art of military sociology research is outlined, and potential avenues for analyzing military forces based on EC/SC are identified. It is argued that especially the connection to organizational theory (military as organization) and civil-military relations, including leadership and professionalism, offer starting points. After introducing existing studies addressing military-related topics with reference to EC/SC, relevant concepts and approaches of convention theory that prove to be particularly enriching for military research are discussed. An outlook on possible further fields and topics of research is given to concretize how an inclusion of the perspective of EC/SC could look like.
The performance and scalability of modern data-intensive systems are limited by massive data movement of growing datasets across the whole memory hierarchy to the CPUs. Such traditional processor-centric DBMS architectures are bandwidth- and latency-bound. Processing-in-Memory (PIM) designs seek to overcome these limitations by integrating memory and processing functionality on the same chip. PIM targets near- or in-memory data processing, leveraging the greater in-situ parallelism and bandwidth.
In this paper, we introduce pimDB and provide an initial comparison of processor-centric and PIM-DBMS approaches under different aspects, such as scalability and parallelism, cache-awareness, or PIM-specific compute/bandwidth tradeoffs. The evaluation is performed end-to-end on a real PIM hardware system from UPMEM.