Direct deposit of catalyst on the membrane of direct feed fuel cells

An improved direct liquid-feed fuel cell having a solid membrane electrolyte for electrochemical reactions of an organic fuel. Catalyst utilization and catalyst/membrane interface improvements are disclosed. Specifically, the catalyst layer is applied directly onto the membrane electrolyte

Standing together for reproducibility in large-scale computing: report on reproducibility@XSEDE

This is the final report on reproducibility@xsede, a one-day workshop held in conjunction with XSEDE14, the annual conference of the Extreme Science and Engineering Discovery Environment (XSEDE). The workshop's discussion-oriented agenda focused on reproducibility in large-scale computational research. Two important themes capture the spirit of the workshop submissions and discussions: (1) organizational stakeholders, especially supercomputer centers, are in a unique position to promote, enable, and support reproducible research; and (2) individual researchers should conduct each experiment as though someone will replicate that experiment. Participants documented numerous issues, questions, technologies, practices, and potentially promising initiatives emerging from the discussion, but also highlighted four areas of particular interest to XSEDE: (1) documentation and training that promotes reproducible research; (2) system-level tools that provide build- and run-time information at the level of the individual job; (3) the need to model best practices in research collaborations involving XSEDE staff; and (4) continued work on gateways and related technologies. In addition, an intriguing question emerged from the day's interactions: would there be value in establishing an annual award for excellence in reproducible research? Overvie

Data on ADME parameters of bisphenol A and its metabolites for use in physiologically based pharmacokinetic modelling

The paper presents the collection of physicochemical parameters of bisphenol A (BPA) and its sulfate (BPAS) and glucuronide (BPAG) conjugates, accompanied by data characterizing their absorption, distribution, metabolism and excretion (ADME) behavior following oral administration of BPA. The data were collected from open literature sources and publicly available databases. Additionally, data calculated by using the MarvinSketch 18.30.0 software or predicted by relevant QSAR models built in Simcyp® Simulator were also used. All data were analysed and are fit for purpose if necessary to ensure a reliable prediction of pharmacokinetics of BPA and its conjugates. The data selection process and reasoning for fitting is provided to allow critical assessment and to ensure data transparency. Finally, the sensitivity analysis was performed to assess the influence of the selected parameters on the PBPK model predictions

Reusable unit process life cycle inventory for manufacturing: high speed laser directed energy deposition

The unit process life cycle inventory is a modeling approach to estimate the energy demand and resource requirements of a unit process. Thus, a model of the unit process life cycle inventory for a specific manufacturing process can be used for quantifying the environmental impacts of specific products manufactured by that process. Within the approach, reusable models are developed for specific manufacturing processes. In this paper, the development and validation of a unit process life cycle inventory model for high-speed laser directed energy deposition is presented. This additive manufacturing process offers great potential for the industry due to its fast process speed. However, high-speed laser directed energy deposition has a high energy consumption and resource demand. Assessing the energy demand for individual manufactured products is a time-intensive process that requires expert knowledge. Thus, the development of an adaptable unit process life cycle inventory model enables more convenient assessment and improvement of its energy and resource efficiencies for producing different products. For the development of the model, the subsystems of a high-speed laser directed energy deposition machine are analyzed separately, e. g. the laser generator, the trajectory system, the powder feeder, and the suction system. Afterward, the energy and material demand of these subsystems are described in mathematical models. Finally, the model is validated by comparing the energy demands of three demonstration parts, measured by experiments, and predicted by the model

Aesthetics and Gloss of Ground Surfaces: A Review on Measurement and Generation

Visual appearance of an object significantly influences a consumer's choice and largely controls the market economy. The perceived quality of products is governed by surface's optical properties (reflection, refraction, etc.), geometrical properties (roughness, waviness, etc.), and chemical properties (oxide layer formation, thermal variation, etc.). Surface shininess attracts researchers from many different disciplines, in particular manufacturing, metrology, psychology, physiology, and computer science. Unfortunately, there are still huge knowledge gaps on characterizing and appraising shiny surfaces in a reproducible way. This paper introduces the main definitions and physics of shininess and gloss, methods of gloss sensing, and relates these definitions and methods to surface generation by grinding. Automated gloss measurement is difficult in particular for free-form surfaces, and optical quality is still often evaluated by human workers. Gloss models are often based on the bidirectional reflection distribution function (BRDF) of the surface, but the models are commonly not connected with the manufacturing process. This study proposes to consider the geometrical features (defects, waviness, lay, and roughness) of metal surfaces as well as the physical and chemical features (grain structure and microlayers) to understand surface appearance and manufacturing in a holistic way. Preliminary tests show that 2D roughness measurements are not connected well with measured gloss units (GUs) and subjective, perceived quality. More fundamental research on the generation and measurement of surface appearance is needed and would benefit many industries

Immune Imbalance in Nasal Polyps of Caucasian Chronic Rhinosinusitis Patients Is Associated with a Downregulation of E-Selectin

Chronic rhinosinusitis with nasal polyps (CRSwNP) in Caucasians is a chronic Th2 inflammatory disease of the nasal and paranasal mucosa and the recruitment of leukocytes to the site of inflammation is poorly understood. We studied mRNA and protein expression profiles of adhesion molecules in nasal polyp and associated inferior turbinate tissues using molecular, biochemical, and immunohistological methods. Analysis showed a strongly decreased E-selectin expression in nasal polyps with a significant difference between eosinophil and neutrophil counts in nasal polyps and balanced counts in inferior turbinates. E-selectin expression is known to be downregulated in a Th2 milieu and has an essential role in immunosurveillance by locally activating neutrophil arrest and migratory function. A downregulation of E-selectin may come along with an immune imbalance in Caucasian nasal polyps due to a significant inhibition of neutrophil recruitment. Therefore, we suggest that an upregulation of E-selectin and the associated influx of neutrophils may play a significant role in the resolution of inflammation as well as for the pathophysiology of nasal polyps of Caucasian chronic rhinosinusitis patients

Implementing an Insect Brain Computational Circuit Using III–V Nanowire Components in a Single Shared Waveguide Optical Network

Recent developments in photonics include efficient nanoscale optoelectronic components and novel methods for sub-wavelength light manipulation. Here, we explore the potential offered by such devices as a substrate for neuromorphic computing. We propose an artificial neural network in which the weighted connectivity between nodes is achieved by emitting and receiving overlapping light signals inside a shared quasi 2D waveguide. This decreases the circuit footprint by at least an order of magnitude compared to existing optical solutions. The reception, evaluation and emission of the optical signals are performed by a neuron-like node constructed from known, highly efficient III-V nanowire optoelectronics. This minimizes power consumption of the network. To demonstrate the concept, we build a computational model based on an anatomically correct, functioning model of the central-complex navigation circuit of the insect brain. We simulate in detail the optical and electronic parts required to reproduce the connectivity of the central part of this network, using experimentally derived parameters. The results are used as input in the full model and we demonstrate that the functionality is preserved. Our approach points to a general method for drastically reducing the footprint and improving power efficiency of optoelectronic neural networks, leveraging the superior speed and energy efficiency of light as a carrier of information.Comment: 28 pages, 6 figures; supplementary information 15 pages, 8 figure

Assoziative Zuordnung und Suche von Wissen in einer thematisch strukturierten Wissensbasis

Gängler B, Greten M, Linke T, Wachsmuth I. Assoziative Zuordnung und Suche von Wissen in einer thematisch strukturierten Wissensbasis. MOSYS Report. Vol 11.; 1992.Von einer thematischen Strukturierung der Wissensbasis sind zwei Funktionen eines sprachverstehenden Systems betroffen: Bei der Wissensakquisition aus Texten können die gegebenen Fakten dem geeigneten Teil der Wissensbasis zugeordnet werden; für die Bearbeitung von Anfragen kann die Suche auf thematisch eingeschränkte Teilbereiche der Wissensbasis fokussiert werden. In beiden Fällen muß vom System der für die zu bearbeitenden Texte (und Anfragen) relevante Wissensbasis-Ausschnitt erkannt werden. In dem vorliegenden Papier werden erste Versuche mit einem subsymbolischen Klassifizierungsmodul beschrieben, das Texte aufgrund wortbezogener Merkmale Teilbereichen einer strukturierten Wissensbasis thematisch zuordnet. Ausgangspunkt war die Annahme, daß das Vokabular faktenübermittelnder Informationstexte kumulativ auf den in einem Text angesprochenen Weltausschnitt hinweist. Verschiedene Typen künstlicher neuronaler Netze wurden in einer Lernphase mit vorbereiteten Paaren von textspezifischen Merkmalskombinationen und assoziierten Wissensbereichen trainiert. In Tests mit neuen Texten wurden von einem derart trainierten Backpropagation-Netzwerk in den meisten Fällen plausible Bereichszuordnungen vorgeschlagen