949 research outputs found

    Cost-Benefit Analysis of Phase Balancing Solution for Data-scarce LV Networks by Cluster-Wise Gaussian Process Regression

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    Protein quality control and aggregation in the endoplasmic reticulum: From basic to bedside

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    Endoplasmic reticulum (ER) is the largest membrane-bound compartment in all cells and functions as a key regulator in protein biosynthesis, lipid metabolism, and calcium balance. Mammalian endoplasmic reticulum has evolved with an orchestrated protein quality control system to handle defective proteins and ensure endoplasmic reticulum homeostasis. Nevertheless, the accumulation and aggregation of misfolded proteins in the endoplasmic reticulum may occur during pathological conditions. The inability of endoplasmic reticulum quality control system to clear faulty proteins and aggregates from the endoplasmic reticulum results in the development of many human disorders. The efforts to comprehensively understand endoplasmic reticulum quality control network and protein aggregation will benefit the diagnostics and therapeutics of endoplasmic reticulum storage diseases. Herein, we overview recent advances in mammalian endoplasmic reticulum protein quality control system, describe protein phase transition model, and summarize the approaches to monitor protein aggregation. Moreover, we discuss the therapeutic applications of enhancing endoplasmic reticulum protein quality control pathways in endoplasmic reticulum storage diseases

    Efficient wide-bandgap perovskite solar cells with open-circuit voltage deficit below 0.4 V via hole-selective interface engineering

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    Wide-bandgap mixed-halide perovskite solar cells (WBG-PSCs) are promising top cells for efficient tandem photovoltaics to achieve high power conversion efficiency (PCE) at low cost. However, the open-circuit voltage (VOC) of WBG-PSCs is still unsatisfactory as the VOC-deficit is generally larger than 0.45 V. Herein, we report a buried interface engineering strategy that substantially improves the VOC of WBG-PSCs by inserting amphophilic molecular hole-selective materials featuring with a cyanovinyl phosphonic acid (CPA) anchoring group between the perovskite and substrate. The assembly and redistribution of CPA-based amphiphilic molecules at the perovskite-substrate buried interface not only promotes the growth of a low-defect crystalline perovskite thin film, but also suppresses the photo-induced halide phase separation. The energy level alignment between wide-bandgap perovskite and the hole-selective layer is further improved by modulating the substituents on the triphenylamine donor moiety (methoxyls for MPA-CPA, methyls for MePA-CPA, and bare TPA-CPA). Using a 1.68 eV bandgap perovskite, the MePA-CPA-based devices achieved an unprecedentedly high VOC of 1.29 V and PCE of 22.3% under standard AM 1.5 sunlight. The VOC-deficit (&lt;0.40 V) is the lowest value reported for WBG-PSCs. This work not only provides an effective approach to decreasing the VOC-deficit of WBG-PSCs, but also confirms the importance of energy level alignment at the charge-selective layers in PSCs.</p

    Learning Segment Similarity and Alignment in Large-Scale Content Based Video Retrieval

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    With the explosive growth of web videos in recent years, large-scale Content-Based Video Retrieval (CBVR) becomes increasingly essential in video filtering, recommendation, and copyright protection. Segment-level CBVR (S-CBVR) locates the start and end time of similar segments in finer granularity, which is beneficial for user browsing efficiency and infringement detection especially in long video scenarios. The challenge of S-CBVR task is how to achieve high temporal alignment accuracy with efficient computation and low storage consumption. In this paper, we propose a Segment Similarity and Alignment Network (SSAN) in dealing with the challenge which is firstly trained end-to-end in S-CBVR. SSAN is based on two newly proposed modules in video retrieval: (1) An efficient Self-supervised Keyframe Extraction (SKE) module to reduce redundant frame features, (2) A robust Similarity Pattern Detection (SPD) module for temporal alignment. In comparison with uniform frame extraction, SKE not only saves feature storage and search time, but also introduces comparable accuracy and limited extra computation time. In terms of temporal alignment, SPD localizes similar segments with higher accuracy and efficiency than existing deep learning methods. Furthermore, we jointly train SSAN with SKE and SPD and achieve an end-to-end improvement. Meanwhile, the two key modules SKE and SPD can also be effectively inserted into other video retrieval pipelines and gain considerable performance improvements. Experimental results on public datasets show that SSAN can obtain higher alignment accuracy while saving storage and online query computational cost compared to existing methods.Comment: Accepted by ACM MM 202

    Exploring the interaction between renewables and energy storage for zero-carbon electricity systems

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    Many countries have set ambitious targets to achieve zero-carbon electricity systems by the Mid-21st Century. In their pathways, the renewable mix and the energy storage mix have been considered as two important facets. Current literature mostly focuses on how the storage mix is affected by the renewable mix, but few studied the inverse impact and the dynamic interaction between the storage and renewable mixes. We, therefore, developed an electricity system optimisation model with hourly resolution to investigate how the interaction between renewable and storage mixes could accelerate the decarbonisation in future 30 years. This study considered the decarbonisation roadmap in the UK designed by the National Grid with variable factors such as cost structure of renewables and storages, annual investment budget, and load growth. Our research finds that short-duration energy storages with duration time at 6–8 h are preferred for providing cheap and rapid ramping power to meet the daily fluctuation in the early stage (2020–2030) of the decarbonisation process. In the late stage of retiring fossil fuels (2040–2050), high-share wind energy plus with long-duration storages (with duration time longer than 38 h) can solve the problem of great-quantity and long-lasting energy shortage caused by renewables, thereby achieving high-renewable penetration.</p

    Specific, simple and rapid detection of porcine circovirus type 2 using the loop-mediated isothermal amplification method

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    <p>Abstract</p> <p>Background</p> <p>Porcine circovirus type 2 (PCV2) is the causative agent of postweaning multisystemic wasting syndrome (PMWS), and porcine dermatitis and nephropathy syndrome (PDNS). It has caused heavy losses in global agriculture in recent decades. Rapid detection of PCV2 is very important for the effective prophylaxis and treatment of PMWS.</p> <p>Results</p> <p>A loop-mediated isothermal amplification (LAMP) assay was used to detect PCV2 in this study. Three pairs of primers were specially designed for recognizing eight distinct sequences of the ORF2 gene. This gene lies in the PCV2 virus genome sequence, and encodes the Rep protein that is involved in virus replication. Time and temperature conditions for amplification of PCV2 genes were optimized to be 55 min at 59°C. The analysis of clinical samples indicated that the LAMP method was highly sensitive. The detection limit for PCV2 by the LAMP assay was 10 copies, whereas the limit by conventional PCR was 1000 copies. The assay did not cross-react with PCV1, porcine reproductive and respiratory syndrome virus, porcine epidemic diarrhea virus, transmissible gastroenteritis of pigs virus or rotavirus. When 110 samples were tested using the established LAMP system, 95 were detected as positive.</p> <p>Conclusion</p> <p>The newly developed LAMP detection method for PCV2 was more specific, sensitive, rapid and simple than before. It complements and extends previous methods for PCV2 detection and provides an alternative approach for detection of PCV2.</p
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