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This paper proposes a boost converter with coupled inductors and a buck-boost type of active clamp. In the converter, the active-clamp circuit is used to eliminate the voltage spike that is induced by the trapped energy in the leakage inductor of the coupled inductors. The active switch in the converter can still sustain a proper duty ratio even under high step-up applications, reducing voltage and current stresses significantly. Moreover, since both main and auxiliary switches can be turned on with zero-voltage switching, switching loss can be reduced, and conversion efficiency therefore can be improved significantly. A 200-W prototype of the proposed boost converter was built, from which experiment results have shown that efficiency can reach as high as 92% and surge can be suppressed effectively. It is relatively feasible for low-input-voltage applications, such as fuel cell and battery power conversion. Index Terms--Active clamp, boost converter, coupled inductors, zero-voltage switching (ZVS).

This investigation presents a novel approach to semantic segment extraction and matching for retrieving information from Internet FAQs with natural language queries. Two semantic segments, the question category segment (QS) and the keyword segment (KS), are extracted from the input queries and the FAQ questions with a semiautomaticatly derived question-semantic grammar. A semantic matching method is presented to estimate the similarity between the semantic segments of the query and the questions in the FAQ collection. Additionally, the vector space model (VSM) is adopted to measure the similarity between the query and the answers of the QA pairs. Finally, a multistage ranking strategy is adopted to determine the optimally performing combination of similarity metrics. The experimental results illustrate that the proposed method achieves an average rank of 4.52 and a top-10 recall rate of 90.89 percent. Compared with the query-expansion method, this method improves the performance by 4.82 places in the average rank of correct answers, 25.34 percent in the top-5 recall rate, and 5.21 percent in the top-10 recall rate. Index Terms--Natural language processing, retrieval models, query formulation, deduction and theorem proving, knowledge processing.

Simple Summary: Personalized drug cocktails have been widely implemented in cancer treatment, due to their merits of using a drug synergistic combination rather than a single effector. Through the incorporation of a cell microarray chip, the usage of both cell amount and reagent can be optimized and effectively reduced in cost. Herein, we present a laser direct writing strategy to fabricate a microcrater-arrayed (µCA) chip incorporated with an automatic liquid handling platform. Each cell droplet with a critical volume of 200 nL containing 100 SK-N-DZ or MCF-7 cells was utilized. The drug synergy screening took less than 30 s for a total of 81 tests. The results show that the potent drug prediction of the µCA chip is more accurate than the conventional 96-well plate assay, which are all compared using zebrafish DiI-labelled tumor xenograft models. Taken together, these findings may impact high-throughput drug screening and personalized drug medicine. Purpose: The aim of this study was to develop a rapid and automatic drug screening platform using microcrater-arrayed (µCA) cell chips. Methods: The µCA chip was fabricated using a laser direct writing technique. The fabrication time required for one 9 × 9 microarray wax chip was as quick as 1 min. On a nanodroplet handling platform, the chip was pre-coated with anti-cancer drugs, including cyclophosphamide, cisplatin, doxorubicin, oncovin, etoposide, and 5-fluorouracil, and their associated mixtures. Cell droplets containing 100 SK-N-DZ or MCF-7 cells were then loaded onto the chip. Cell viability was examined directly through a chemiluminescence assay on the chip using the CellTiter-Glo assay. Results: The time needed for the drug screening assay was demonstrated to be less than 30 s for a total of 81 tests. The prediction of optimal drug synergy from the µCA chip was found by matching it to that of the zebrafish MCF-7 tumor xenograft model, instead of the conventional 96-well plate assay. In addition, the critical reagent volume and cell number for each µCA chip test were 200 nL and 100 cells, respectively, which were significantly lower than 100 µL and 4000 cells, which were achieved using the 96-well assay. Conclusion: Our study for the µCA chip platform could improve the high-throughput drug synergy screening targeting the applications of tumor cell biology. [ABSTRACT FROM AUTHOR]