Framework for the Integration of Mobile Device Features in PLM

Currently, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows using mobile device features. The objective is a framework that can be used to model and control business applications for PLM processes using mobile device features to allow a totally new user experience

Integration of Virtualized Environments in PDM Systems for Embedded Software Product Development

AbstractThe number of products with embedded software increases across all application areas continuously. Thus, the complexity between the hardware and software is steadily increasing. This leads to an increment of software defects. Therefore, new approaches are needed to ensure the product quality. In the context of PLM, virtualization can support crucial stages of the product development and test automation by providing virtual environments. This paper shows an architectural approach, and how to perform an integration of virtualization software in PDM systems

Integrating curvature: from Umlaufsatz to J^+ invariant

Hopf's Umlaufsatz relates the total curvature of a closed immersed plane curve to its rotation number. While the curvature of a curve changes under local deformations, its integral over a closed curve is invariant under regular homotopies. A natural question is whether one can find some non-trivial densities on a curve, such that the corresponding integrals are (possibly after some corrections) also invariant under regular homotopies of the curve in the class of generic immersions. We construct a family of such densities using indices of points relative to the curve. This family depends on a formal parameter q and may be considered as a quantization of the total curvature. The linear term in the Taylor expansion at q=1 coincides, up to a normalization, with Arnold's J^+ invariant. This leads to an integral expression for J^+.Comment: 6 pages, 5 figure

Spatiotemporal dynamics of feature-based attention spread: evidence from combined electroencephalographic and magnetoencephalographic recordings

Attentional selection on the basis of nonspatial stimulus features induces a sensory gain enhancement by increasing the firing-rate of individual neurons tuned to the attended feature, while responses of neurons tuned to opposite feature-values are suppressed. Here we recorded event-related potentials (ERPs) and magnetic fields (ERMFs) in human observers to investigate the underlying neural correlates of feature-based attention at the population level. During the task subjects attended to a moving transparent surface presented in the left visual field, while task-irrelevant probe stimuli executing brief movements into varying directions were presented in the opposite visual field. ERP and ERMF amplitudes elicited by the unattended task-irrelevant probes were modulated as a function of the similarity between their movement direction and the task-relevant movement direction in the attended visual field. These activity modulations reflecting globally enhanced processing of the attended feature were observed to start not before 200 ms poststimulus and were localized to the motion-sensitive area hMT. The current results indicate that feature-based attention operates in a global manner but needs time to spread and provide strong support for the feature-similarity gain model

Framework for the Integration of Mobile Device Features in PLM

Currently, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows using mobile device features. The objective is a framework that can be used to model and control business applications for PLM processes using mobile device features to allow a totally new user experience

Characterization of nanoparticles in aerosolized photocatalytic and regular cement

Photocatalytic cement containing nano-TiO2 has been introduced to the construction industry because of its biocidal and self-cleaning properties. Although, TiO2 is classified as possibly carcinogenic to humans, the cancer risk among cement workers is currently unknown. This is partly because an assessment of exposures to airborne photocatalytic cement is missing. We characterized airborne photocatalytic cement in an experimental aerosolization set-up and compared it to regular cement. Aerosolized nanoparticle size distributions and concentrations were measured with a scanning mobility particle sizer (SMPS) and a portable aerosol spectrometer (PAS). Particle morphology was analyzed with a scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Energy dispersive X-ray analysis (SEM-EDX) was used for elemental determination. The aerosolized photocatalytic cement powder contained 5% nanosized particles in number concentration while regular cement had only a negligible amount. Airborne photocatalytic cement concentration was 14,900 particles per cubic centimeter (pt/cm3) with a geometric mean diameter (GMD) of 249 nm (geometric standard deviation; GSD ±2 nm). Airborne regular cement concentration and GMD (GSD) were 9,700 pt/cm3 and 417 nm (±2 nm), respectively. Photocatalytic cement contained 18.5 times more airborne nano-TiO2 (37%) compare to bagged powder (2%). Aerosolized photocatalytic cement had a significantly smaller particle size distribution and greater particle concentration compared to regular cement. Both types of cement had 99% of the particles with sizes less than 1 μm. Nano-TiO2 was directly aerosolized from the cement, followed with a coagulation/agglomeration process. Future studies should evaluate workers’ exposures associated with the use of photocatalytic cement. Copyright © 2019 American Association for Aerosol Research</p

Retreatment with interferon-alpha and ribavirin in primary interferon-alpha non-responders with chronic hepatitis C

Background/Aims: Combination therapy with interferon-alpha (IFN-alpha) plus ribavirin is more efficacious than IFN-alpha monotherapy in previously untreated patients with chronic hepatitis C and patients with IFN-alpha relapse. Only limited data are available in IFN-alpha non-responders. In a multicenter trial we therefore evaluated the efficacy of combination therapy in IFN-alpha-resistant chronic hepatitis C. Methods: Eighty-two patients (mean age 46.8 years, 54 males, 28 females) with chronic hepatitis C were treated with IFN-alpha-2a (3 x 6 MIU/week) and ribavirin (14 mg/kg daily) for 12 weeks. Thereafter, treatment was continued only in virological responders (undetectable serum HCV RNA at week 12) with an IFN-alpha dose of 3 x 3 MIU/week and without ribavirin for a further 9 months. The primary study endpoint was an undetectable HCV RNA by RT-PCR at the end of the 24-week follow-up period. Results: After 12 weeks of combination therapy, an initial virological response was observed in 29 of 82 (35.4%) patients. Due to a high breakthrough rate after IFN-a dose reduction and ribavirin discontinuation, an end-of-treatment response was only achieved in 12 of 82 (14.6%) patients. After the follow-up period, a sustained virological response was observed in 8 of 82 (9.8%) patients. Infection with HCV genotype 3 was the only pretreatment parameter, which could predict a sustained response (HCV-1, 5%; HCV-3, 57.1%; p < 0.001). Conclusions: Despite a high initial response rate of 35.4%, sustained viral clearance was achieved only in 9.8% of the retreated primary IFN-alpha non-responders. Higher IFN-alpha induction and maintenance dose, as well as prolonged ribavirin treatment may possibly increase the virological response rates in non-responders, particularly in those infected by HCV-1

Airborne reactive oxygen species (ROS) is associated with nano TiO2 concentrations in aerosolized cement particles during simulated work activities

Photocatalytic cement is self-cleaning due to the addition of titanium dioxide (TiO2) nanoparticles, which react with sunlight (UV) and produce reactive oxygen species (ROS). Construction workers using photocatalytic cement are exposed not only to cement particles that are irritants but also to nano TiO(2)and UV, both carcinogens, as well as the generated ROS. Quantifying ROS generated from added nano TiO(2)in photocatalytic cement is necessary to efficiently assess combined health risks. We designed and built an experimental setup to generate, under controlled environmental conditions (i.e., temperature, relative humidity, UV irradiance), both regular and photocatalytic cement aerosols. In addition, cement working activities-namely bag emptying and concrete cutting-were simulated in an exposure chamber while continuously measuring particle size distribution/concentration with a scanning mobility particle sizer (SMPS). ROS production was measured with a newly developed photonic sensing system based on a colorimetric assay. ROS production generated from the photocatalytic cement aerosol exposed to UV (3.3.10(-9) nmol/pt) was significantly higher than for regular cement aerosol, either UV-exposed (0.5.10(-9) nmol/pt) or not (1.1.10(-9) nmol/pt). Quantitatively, the level of photocatalytic activity measured for nano TiO2-containing cement aerosol was in good agreement with the one obtained with only nano TiO(2)aerosol at similar experimental conditions of temperature and relative humidity (around 60%). As a consequence, we recommend that exposure reduction strategies, in addition to cement particle exposures, also consider nano TiO(2)and in situ-generated ROS, in particular if the work is done in sunny environment

A Decision Support System for Photovoltaic Potential Estimation

With knowledge on the photovoltaic potential of individual residential buildings, solar companies, energy service providers and electric utilities can identify suitable customers for new PV installations and directly address them in renewable energy rollout and maintenance campaigns. However, many currently used solutions for the simulation of energy generation require detailed information about houses (roof tilt, shading, etc.) that is usually not available at scale. On the other hand, the methodologies enabling extraction of such details require costly remote-sensing data from three-dimensional (3D) laser scanners or aerial images. To bridge this gap, we present a decision support system (DSS) that estimates the potential amount of electric energy that could be generated at a given location if a photovoltaic system would be installed. The DSS automatically generates insights about photovoltaic yields of individual roofs by analyzing freely available data sources, including the crowdsourced volunteered geospatial information systems OpenStreetMap and climate databases. The resulting estimates pose a valuable foundation for selecting the most prospective households (e.g., for personal visit and screening by an expert) and targeted solar panel kit offerings, ultimately leading to significant reduction of manual human efforts, and to cost-effective personalized renewables adoption