Topography simulation of sputtering using an algorithm with second order approximation in space

For the efficient simulation of topography evolution due to, e.g., focused ion beam processes, continuum surface advancement algorithms are commonly used. In this work we present a two-dimensional surface advancement algorithm that uses circular arcs between nodes and allows kinks in the surface. The algorithm is based on the method of characteristics, which yields the motion of the points and the slope of the surface. By the interpolation with circular arcs not only the final result is better represented, but also more accurate simulation is possible after insertion of new points as the surface evolves. Kinks in the surface (shocks) are detected by the generation of loops in the surface string or by a new criterion based on the analysis of infinitesimally separated characteristics. It requires the curvature of the surface, which may readily be determined from the radii of the circular arcs. The proposed algorithm uses a second order approximation in space and therefore requires fewer data points during calculation than first order methods. It is shown to converge with third order as a function of node number. The method is demonstrated by examples of trench formation including the effect of redeposition and of facet formation from a step-like surface.     

Design für Kostentransparenz in Anlageberatungsgespr?chen

Investment advisory services of financial service providers (FSPs) exhibit several characteristics that are detrimental to advisory quality. The interaction of advisor and client is strained by a lack of transparency regarding the advisory process (what activities are performed and why) and the information used therein (what information is used for what purpose and with what effect), as well as regarding the precise costs of the service and the recommended products. In prior research, we suggested that process and information transparency issues may be appropriately addressed with collaborative information technology (IT) artifacts. In this paper, we argue that collaborative, transparent artifacts may also be a premise of enabling cost transparency. To this end, we describe a complete research cycle of designing, implementing, and evaluating a shared cost-transparent IT artifact to support client-advisor interaction in investment advisory encounters. Evaluation results suggest the efficacy of our design in improving the clients?? perceived cost transparency as well as increase their satisfaction and their willingness to pay for the received investment advice. These findings may also challenge the common belief of FSPs that transparent, fee-based advisory services would neither be accepted by clients nor be economically viable. Practical implications of these findings for designing advisory encounters with supportive IT are discussed.     

Phytochemical composition and antioxidant capacity of various botanical parts of the fruits of Prunus × domestica L. from the Lorraine region of Europe

Mirabelle plums represent a famous fruit from the Lorraine region, however little is known about their phytochemical composition. The oil of the fruit contained predominantly oleic acid (59%) and linoleic acid (29%). The total content of phenolic antioxidants in the whole fruits was 5.338 g/kg with 456 mg/kg (9%), 701 mg/kg (13%) and 4159 mg/kg (78%) detected in the peels, flesh and pits respectively. The peels contained solely 3,4-dihydroxybenzoic acid (270 mg/kg) and rutin (186 mg/kg), the flesh exclusively echinoids (723 mg/kg), whereas the pits contained a rich variety of phenolic compounds (4.2 g/kg) dominated by amygdalin (3.8 g/kg), but with significant contributions from vanillin (102 mg/kg), guajacyl-glycerin-coniferyl aldehyde isomers (87 mg/kg), dehydro-diconiferyl aldehyde (52 mg/kg), and vanillin diglucoside (48 mg/kg). Of the major phenolic compounds tested across a range of in vitro assays, rutin was the superior antioxidant.     

TcdB of Clostridioides difficile Mediates RAS-Dependent Necrosis in Epithelial Cells

A Clostridioides difficile infection (CDI) is the most common nosocomial infection worldwide. The main virulence factors of pathogenic C. difficile are TcdA and TcdB, which inhibit small Rho-GTPases. The inhibition of small Rho-GTPases leads to the so-called cytopathic effect, a reorganization of the actin cytoskeleton, an impairment of the colon epithelium barrier function and inflammation. Additionally, TcdB induces a necrotic cell death termed pyknosis in vitro independently from its glucosyltransferases, which are characterized by chromatin condensation and ROS production. To understand the underlying mechanism of this pyknotic effect, we conducted a large-scale phosphoproteomic study. We included the analysis of alterations in the phosphoproteome after treatment with TcdA, which was investigated for the first time. TcdA exhibited no glucosyltransferase-independent necrotic effect and was, thus, a good control to elucidate the underlying mechanism of the glucosyltransferase-independent effect of TcdB. We found RAS to be a central upstream regulator of the glucosyltransferase-independent effect of TcdB. The inhibition of RAS led to a 68% reduction in necrosis. Further analysis revealed apolipoprotein C-III (APOC3) as a possible crucial factor of CDI-induced inflammation in vivo.     

Manufacturing‐induced surface contaminations

In the course of classical optics manufacturing glass components are in permanent direct contact with aqueous operating materials. Such contact leads to a certain absorption of water and hydrogenous compounds that may induce severe glass defects. In this contribution, absorption of hydrogen and other contaminants during grinding of glass was observed and qualitatively detected via laser‐induced breakdown spectroscopy. It is shown that hydrogen, calcium, magnesium, and carbon are implanted into the glass surface where the contaminant concentration increases over grinding time or contact time of the glass surface with water and the grinding tool, respectively. The contaminants hydrogen, calcium, and magnesium can be attributed to the water used as lubricant. In contrast, carbon most likely originates from wear debris of the used silicon carbide grinding pads. Several possible mechanisms that lead to such surface contamination of glasses during grinding – diffusion, accumulation in micro cracks as well as the formation of hydrated silica – are finally introduced.     

Exploring design trade-offs for achieving social inclusion in multi-tiered design problems

ABSTRACT

The digital age of the future is ‘not out there to be discovered’, but it needs to be ‘designed’. The design challenge has to address questions about how we want to live, work, and learn (as individuals and as communities) and what we value and appreciate, e.g.: reflecting on quality of life and creating inclusive societies. An overriding design trade-off for the digital age is whether new developments will increase the digital divide or will create more inclusive societies. Sustaining inclusive societies means allowing people of all ages and all abilities to exploit information technologies for personally meaningful activities. Meta-design fosters the design of socio-technical environments that end-user developers can modify and evolve at use time to improve their quality of life and favour their inclusion in the society. This paper describes three case studies in the domain of assistive technologies in which end users themselves cannot act as end-user developers, but someone else (e.g.: a caregiver or a clinician) must accept this role requiring multi-tiered architectures. The design trade-offs and requirements for meta-design identified in the context of the case studies and other researchers’ projects are described to inform the development of future socio-technical environments focused on social inclusion.     

Consumer credit risk: Individual probability estimates using machine learning

Consumer credit scoring is often considered a classification task where clients receive either a good or a bad credit status. Default probabilities provide more detailed information about the creditworthiness of consumers, and they are usually estimated by logistic regression. Here, we present a general framework for estimating individual consumer credit risks by use of machine learning methods. Since a probability is an expected value, all nonparametric regression approaches which are consistent for the mean are consistent for the probability estimation problem. Among others, random forests (RF), k-nearest neighbors (kNN), and bagged k-nearest neighbors (bNN) belong to this class of consistent nonparametric regression approaches. We apply the machine learning methods and an optimized logistic regression to a large dataset of complete payment histories of short-termed installment credits. We demonstrate probability estimation in Random Jungle, an RF package written in C++ with a generalized framework for fast tree growing, probability estimation, and classification. We also describe an algorithm for tuning the terminal node size for probability estimation. We demonstrate that regression RF outperforms the optimized logistic regression model, kNN, and bNN on the test data of the short-term installment credits.