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The analytical calculation of winding loss in gapped magnetic components is complex, and numerical analysis tools, such as finite elements analysis (FEA) tools, are commonly needed to characterize the windings. As FEA tools are used, the required design time of these types of components increases greatly when many simulations are needed to select the appropriate component for a given application, and simple analytical models become necessary to reduce the design time. In this paper, some analytical approaches for winding loss calculation in gapped magnetic components are reviewed and a general two-dimensional equivalent method, which aims to consider the frequency effects in conductors in a simplified manner, is proposed afterward. Due to its simplicity, it can be integrated into design and optimization tools in order to evaluate the influence of the air gap over the winding loss even at the early stages of the design process. The presented model shows good agreement with FEA simulations and measurements.

This work presents a hybrid converter combining soft-charged switched capacitors and an autotransformer with DC current in the windings, optimized for 4:1 fixed voltage gain conversion (DCX) for high output current. By adding an additional output inductor, it can also regulate the output voltage to lower than of the input voltage by changing the duty cycle. The switched capacitors voltage and the two winding currents in the transformer are auto-balanced. Non-resonant operation of the circuit enables DC current in the windings and simplifies both transformer and circuit design. Experimental results for 48V-12V DCX operation achieve 98% peak efficiency and 97.8% full load (250W) efficiency. Regulation by using the output inductor is verified experimentally up to 48V-6V (8:1) voltage step down.

This paper reviews and classifies representative types of ?Differential Power Processing, DPP? architectures, focusing on the aspect of how the processed power is reduced with DPP. Comparing to existing review works on this topic, this paper provides new viewpoints from three perspectives: (1) the differential power Pdiff at both architecture level and converter level is discussed. For the calculation of the total processed power in a power architecture, instead of summing up the output power Pout delivered by the DPP converters, we account for Pdiff inside the DPP converters, because direct power exists not only at the architecture level, but also at the converter level, so the power processed in a converter may be lower than Pout. (2) The VA area modeling is applied to the DPP architectures to illustrate and visualize the processed power in the power architectures and converters, thus analyzing and comparing them at high level. (3) The processed power of different DPP architectures is compared quantitively with statistical analysis for varied operating situations.

Over the last decade, hundreds of thousands of volunteers have contributed to science by collecting or analyzing data. This public participation in science, also known as citizen science, has contributed to significant discoveries and led to publications in major scientific journals. However, little attention has been paid to data quality issues. In this work we argue that being able to determine the accuracy of data obtained by crowdsourcing is a fundamental question and we point out that, for many real-life scenarios, mathematical tools and processes for the evaluation of data quality are missing. We propose a probabilistic methodology for the evaluation of the accuracy of labeling data obtained by crowdsourcing in citizen science. The methodology builds on an abstract probabilistic graphical model formalism, which is shown to generalize some already existing label aggregation models. We show how to make practical use of the methodology through a comparison of data obtained from different citizen science communities analyzing the earthquake that took place in Albania in 2019.

© 2017 The Authors Polymerization-based amplification (PBA) uses a visible-light photopolymerization reaction for rapid, low-cost signal amplification and colorimetric detection in disease diagnostics. PBA is particularly useful for point-of-care testing (POCT) in the developing world where laboratory infrastructure and access to advanced technologies may be limited. To date, PBA has required expensive (∼5K USD), desktop-based light sources to drive these photopolymerization reactions, which has limited its use in limited-resource areas and for POCT applications. Here, we present a portable, lightweight, and low-cost device that can generate light of the intensity and wavelengths required to perform the PBA reactions rapidly (<100 s) with minimal energy consumption. We developed analog and digital versions of the device that meet these criteria and can operate on their own without the requirement of a computer to run necessary software. Lastly, they both have the added functionality to dim the intensity of the LED to allow customization of the reaction conditions to the needs of individual assays.

The earth-abundant quaternary compound Cu(2)BaSnS(4)is being currently studied as a candidate for photovoltaics and as a photocathode for water splitting. However, the chemical stability of this phase during synthesis is unclear. The synthesis of other quaternary tin-sulphur-based absorbers (e.g., Cu2ZnSnS4) involves an annealing step at high temperature under sulphur gas atmosphere, which can lead to decomposition into secondary phases involving Sn loss from the sample. As the presence of secondary phases can be detrimental for device performance, it is crucial to identify secondary phase chemical, structural and optoelectronic properties. Here we used a combination ofin situEDXRD/XRF and TEM to identify a decomposition pathway for Cu2BaSnS4. Our study reveals that, while Cu(2)BaSnS(4)remains stable at high sulphur partial pressure, the material decomposes at high temperatures into Cu(4)BaS(3)and the hitherto unknown compound Cu(2)Ba(3)Sn(2)S(8)if the synthesis is performed under low partial pressure of sulphur. The presence of Cu(4)BaS(3)in devices could be harmful due to its high conductivity and relatively lower band gap compared to Cu2BaSnS4. The analysis of powder diffraction data reveals that the newly identified compound Cu(2)Ba(3)Sn(2)S(8)crystallizes in the cubic system (space groupI4x304;3d) with a lattice parameter ofa= 14.53(1) angstrom. A yellow powder of Cu(2)Ba(3)Sn(2)S(8)has been synthesized, exhibiting an absorption onset at 2.19 eV.

Context: The success of software crowdsourcing depends on steady tasks supply and active worker pool. Existing analysis reveals an average task failure ratio of 15.7% in software crowdsourcing market. Goal: The objective of this study is to empirically investigate patterns and effect of task diversity in software crowdsourcing platform in order to improve the success and efficiency of software crowdsourcing. Method: We propose a conceptual task diversity model, and develop an approach to measuring and analyzing task diversity.More specifically, this includes grouping similar tasks, ranking them based on their competition level and identifying the dominant attributes that distinguish among these levels, and then studying the impact of task diversity on task success and worker performance in crowdsourcing platform. The empirical study is conducted on more than one year's real-world data from TopCoder, the leading software crowdsourcing platform. Results: We identified that monetary prize and task complexity are the dominant attributes that differentiate among different competition levels. Based on these dominant attributes, we found three task diversity patterns (configurations) from workers behavior perspective: responsive to prize, responsive to prize and complexity and over responsive to prize. This study supports that1) responsive to prize configuration provides highest level of task density and workers' reliability in a platform; 2) responsive to prize and complexity configuration leads to attracting high level of trustworthy workers; 3) over responsive to prize configuration results in highest task stability and the lowest failure ratio in the platform for not high similar tasks., Comment: 10 pages, 8 figures, 3 tables

Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, social distancing, and other hard-to-measure quantities. In this paper we investigate whether it is possible to obtain such data by aggregating information from images posted to social media. The paper presents VisualCit, a pipeline for image-based social sensing combining recent advances in image recognition technology with geocoding and crowdsourcing techniques. Our aim is to discover in which countries, and to what extent, people are following COVID-19 related policy directives. We compared the results with the indicators produced within the CovidDataHub behavior tracker initiative. Preliminary results shows that social media images can produce reliable indicators for policy makers., Comment: 10 pages, 9 figures, to be published in Proceedings of ICSE Software Engineering in Society, May 2021

Point-of-care (POC) diagnostics such as lateral flow and dipstick immunoassays use gold nanoparticle (NP)-antibody conjugates for visual readout. We investigated the effects of NP conjugation, surface chemistries, and antibody immobilization methods on dipstick performance. We compared orientational, covalent conjugation, electrostatic adsorption, and a commercial conjugation kit for dipstick assays to detect dengue virus NS1 protein. Assay performance depended significantly on their conjugate properties. We also tested arrangements of multiple test lines within strips. Results show that orientational, covalent conjugation with PEG shield could improve NS1 detection. These approaches can be used to optimize immunochromatographic detection for a range of biomarkers.

The design and fabrication of reconfigurable, modular paperfluidics driven by a prefabricated reusable block library, asynchronous modular paperfluidic linear instrument‐free (Ampli) block, are reported. The blocks are inspired by the plug‐and‐play modularity of electronic breadboards that lower prototyping barriers in circuit design. The resulting biochemical breadboard is a paperfluidic construction set that can be functionalized with chemical, biological, and electrical elements. Ampli blocks can form standard paperfluidic devices without any external instrumentation. Furthermore, their modular nature enhances fluidics in ways that fixed devices cannot. The blocks' ability to start, stop, modify, and reverse reaction flows, reagents, and rates in real time is demonstrated. These enhancements allow users to increase colorimetric signals, fine tune reaction times, and counter check multiplexed diagnostics for false positives or negatives. The modular construction demonstrates that field‐ready, distributed fabrication of paper analytical systems can be standardized without requiring the “black box” of craft and technique inherent in paper‐based systems. Ampli assembly and point‐of‐care redesign extends the usability of paper analytical systems and invites user‐driven prototyping beyond the lab setting demonstrating “Design for Hack” in diagnostics. Keyword: Pharmaceutical Science; Biomaterials; Biomedical Engineering, United States. Public Health Service (Grant AI100190)