bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved Method of Local Feeder Automation Considering Small Hydro-power Connection
Authors: Li Kewen , Chen Qianyi , Ou Shifeng , Yan Lijuan , Chen Shaonan 
Published: March 2021

Abstract
With the access of small hydro-power stations (SHS), the distribution system presents a multiple power supply pattern, which has a negative impact on the original local feeder automation (LFA) which is suitable for single side power supply system. In view of this effect, the phase to phase short-circuit fault (PPF) and single-phase grounding fault (SPGF) are treated differently, and an improved LFA method (IMLFA) considering SHS’s access based on low-frequency load shedding (LFLS) and high-frequency generator tripping (HFGT) is proposed. In case of SPGF, the section switch (SSW) and the outgoing circuit breaker of the substation shall be opened in sequence, and the isolated network (IN) generated in the process can be operated stably by cooperating with LFLS or HFGT while the fault is preliminary isolated. The SSW and the breaker are added with the function of no-voltage detection and synchronization detection. In case of instantaneous fault, the power supply in the fault area can be restored after a series of operations, and the IN can be connected to the grid. If it is a permanent fault, the section switches (SSWs) around the fault area will be locked to close in order to isolate the fault effectively, and the IN, not separated by the fault area from the grid, can be connected to the grid. Analysis and simulation show that the method is correct and feasible.
Burst pulses for positive corona discharges in atmospheric air: the collective movement of charged species
Authors: PENG Yongkang , CHEN Xiaoyue , LAN Lei , ZHAN Haoyu , LIU Yongcong , HE Wangling , WEN Xishan 
Published: March 2021

Abstract
Positive corona burst pulses are an unstable pulse mode. They appear in a small range of the onset stage, and their current pulses result from the collective movement of charged species. This paper focused on the connections between these pulses and the collective movement of charged species. The movement of species is divided into four parts with respect to time: the (1) initial growth of species, (2) formation and development of the streamer region and negative ion sheath, (3) dead time (the time interval between the pulses), and (4) rapid re-growth of species. The movement of the species in the four parts and the correspondence with the current pulse were analyzed. The numerical results indicated the following: the rapid rising of the species matched the rising edge of the pulses, the streamer region, and negative ion sheath appeared in the falling edge of the primary pulse, and the rapid re-growth of species matched the re-ignition of the pulses. The results were in qualitative agreement with deductions and experimental observations in the literature.
Generating two-mode squeezing with multimode measurement-induced nonlinearity
Authors: Riabinin M , Sharapova P R , Bartley T J , Meier T 
Published: March 2021

Abstract
Measurement-induced nonclassical effects in a two-mode interferometer are investigated theoretically using numerical simulations and analytical results. We demonstrate that for certain parameters measurements within the interferometer lead to the occurrence of two-mode squeezing. The results strongly depend on the detection probability, the phase inside the interferometer, and the choice of the input states. The appropriate parameters for maximized squeezing are obtained. We analyze the influence of losses and confirm that the predicted effects are within reach of current experimental techniques.
Composite electrolytes based on electrospun PVDF and ionic plastic crystal matrices for Na-metal battery applications
Authors: Makhlooghiazad Faezeh , Nti Frederick , Sun Ju , Mendes Tiago Correia , Malunavar Sneha Subhas , Pringle Jennifer M , Forsyth Maria 
Published: March 2021

Abstract
Sodium ion batteries are widely considered to be a feasible, cost-effective, and sustainable energy storage alternative to Lithium, especially for large-scale energy storage applications. Next generation, safer electrolytes based on ionic liquid (IL) and organic ionic plastic crystals (OIPCs) have been demonstrated as electrochemically stable systems which show superior performance in both Li and Na applications. In particular, phosphonium‐based systems outperform most studied nitrogen‐based ILs and OIPCs. In this study triisobutyl(methyl)phosphonium bis(fluorosulfonyl)imide ([P1i444][FSI]) OIPC mixed with 20 mol% of NaFSI or NaTFSI were combined with an electrospun polyvinylidene fluoride (PVDF) support to create self-standing electrolyte membranes, and their thermal phase behaviour and ionic conductivity were investigated and compared with the bulk electrolytes. The ability of the solid-state composite electrolytes to support the cycling of sodium metal with good efficiency and without breakdown were examined in sodium metal symmetrical coin cells. The sodium transference number was determined to be 0.21. The electrochemical performance of Na/Na3V2(PO4)3 cells incorporating the composite electrolytes, including good cycling stability and rate capability, is also reported. Interestingly, the mixed anion systems appear to outperform the composite electrolyte containing only FSI anions, which may relate to electrolyte interactions with the PVDF fibres.
Optimizing geometry of low-Q all-metal Fabry-Pérot microcavity for fluorescence spectroscopy
Authors: Dutta Arpan , Tiainen Ville , Toppari J Jussi 
Published: March 2021

Abstract
Fluorescence spectroscopy is commonly employed to study the excited-state photophysics of organic molecules. Planar Fabry-Pérot microcavities play an essential role in such studies and a strategic cavity design is necessary to attain an enhanced light-matter interaction. In this work, we computationally study different geometries for a planar metallic Fabry-Pérot microcavity tuned for the absorption of Sulforhodamine 101, a typical dye for fluorescence spectroscopy. The cavity consists of a polymer layer enclosed between two silver mirrors, where the thicknesses of all the three layers are varied to optimize the cavity. Our transfer-matrix and finite-difference time-domain simulations suggest that a cavity with 30 nm thin top mirror and 200 nm fully reflective thick bottom mirror, thus having only reflection and absorption and no transmission, is an optimal design for maximizing the Purcell factor and spectral overlap between the cavity and molecule, while still sustaining an efficient measurability of the fluorescence.
Deep drug-target binding affinity prediction with multiple attention blocks
Authors: Zeng Yuni , Chen Xiangru , Luo Yujie , Li Xuedong , Peng Dezhong 
Published: March 2021

Abstract
Drug-target interaction (DTI) prediction has drawn increasing interest due to its substantial position in the drug discovery process. Many studies have introduced computational models to treat DTI prediction as a regression task, which directly predict the binding affinity of drug-target pairs. However, existing studies (i) ignore the essential correlations between atoms when encoding drug compounds and (ii) model the interaction of drug-target pairs simply by concatenation. Based on those observations, in this study, we propose an end-to-end model with multiple attention blocks to predict the binding affinity scores of drug-target pairs. Our proposed model offers the abilities to (i) encode the correlations between atoms by a relation-aware self-attention block and (ii) model the interaction of drug representations and target representations by the multi-head attention block. Experimental results of DTI prediction on two benchmark datasets show our approach outperforms existing methods, which are benefit from the correlation information encoded by the relation-aware self-attention block and the interaction information extracted by the multi-head attention block. Moreover, we conduct the experiments on the effects of max relative position length and find out the best max relative position length value $k \in \{3, 5\}$. Furthermore, we apply our model to predict the binding affinity of Corona Virus Disease 2019 (COVID-19)-related genome sequences and $3137$ FDA-approved drugs.
Integrating multi-scale neighbouring topologies and cross-modal similarities for drug–protein interaction prediction
Authors: Xuan Ping , Zhang Yu , Cui Hui , Zhang Tiangang , Guo Maozu , Nakaguchi Toshiya 
Published: March 2021

Abstract

Motivation
Identifying the proteins that interact with drugs can reduce the cost and time of drug development. Existing computerized methods focus on integrating drug-related and protein-related data from multiple sources to predict candidate drug–target interactions (DTIs). However, multi-scale neighboring node sequences and various kinds of drug and protein similarities are neither fully explored nor considered in decision making.

Results
We propose a drug-target interaction prediction method, DTIP, to encode and integrate multi-scale neighbouring topologies, multiple kinds of similarities, associations, interactions related to drugs and proteins. We firstly construct a three-layer heterogeneous network to represent interactions and associations across drug, protein, and disease nodes. Then a learning framework based on fully-connected autoencoder is proposed to learn the nodes’ low-dimensional feature representations within the heterogeneous network. Secondly, multi-scale neighbouring sequences of drug and protein nodes are formulated by random walks. A module based on bidirectional gated recurrent unit is designed to learn the neighbouring sequential information and integrate the low-dimensional features of nodes. Finally, we propose attention mechanisms at feature level, neighbouring topological level and similarity level to learn more informative features, topologies and similarities. The prediction results are obtained by integrating neighbouring topologies, similarities and feature attributes using a multiple layer CNN. Comprehensive experimental results over public dataset demonstrated the effectiveness of our innovative features and modules. Comparison with other state-of-the-art methods and case studies of five drugs further validated DTIP’s ability in discovering the potential candidate drug-related proteins.
Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19
Authors: Auwul Md Rabiul , Rahman Md Rezanur , Gov Esra , Shahjaman Md , Moni Mohammad Ali 
Published: March 2021

Abstract
Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical trials of vaccines and drugs are currently being conducted around the world; however, till now no effective drug is available for COVID-19. Identification of key genes and perturbed pathways in COVID-19 may uncover potential drug targets and biomarkers. We aimed to identify key gene modules and hub targets involved in COVID-19. We have analyzed SARS-CoV-2 infected peripheral blood mononuclear cell (PBMC) transcriptomic data through gene coexpression analysis. We identified 1520 and 1733 differentially expressed genes (DEGs) from the GSE152418 and CRA002390 PBMC datasets, respectively (FDR &lt; 0.05). We found four key gene modules and hub gene signature based on module membership (MMhub) statistics and protein–protein interaction (PPI) networks (PPIhub). Functional annotation by enrichment analysis of the genes of these modules demonstrated immune and inflammatory response biological processes enriched by the DEGs. The pathway analysis revealed the hub genes were enriched with the IL-17 signaling pathway, cytokine–cytokine receptor interaction pathways. Then, we demonstrated the classification performance of hub genes (PLK1, AURKB, AURKA, CDK1, CDC20, KIF11, CCNB1, KIF2C, DTL and CDC6) with accuracy &gt;0.90 suggesting the biomarker potential of the hub genes. The regulatory network analysis showed transcription factors and microRNAs that target these hub genes. Finally, drug–gene interactions analysis suggests amsacrine, BRD-K68548958, naproxol, palbociclib and teniposide as the top-scored repurposed drugs. The identified biomarkers and pathways might be therapeutic targets to the COVID-19.
iSMNN: batch effect correction for single-cell RNA-seq data via iterative supervised mutual nearest neighbor refinement
Authors: Yang Yuchen , Li Gang , Xie Yifang , Wang Li , Lagler Taylor M , Yang Yingxi , Liu Jiandong , Qian Li , Li Yun 
Published: March 2021

AbstractBatch effect correction is an essential step in the integrative analysis of multiple single-cell RNA-sequencing (scRNA-seq) data. One state-of-the-art strategy for batch effect correction is via unsupervised or supervised detection of mutual nearest neighbors (MNNs). However, both types of methods only detect MNNs across batches of uncorrected data, where the large batch effects may affect the MNN search. To address this issue, we presented a batch effect correction approach via iterative supervised MNN (iSMNN) refinement across data after correction. Our benchmarking on both simulation and real datasets showed the advantages of the iterative refinement of MNNs on the performance of correction. Compared to popular alternative methods, our iSMNN is able to better mix the cells of the same cell type across batches. In addition, iSMNN can also facilitate the identification of differentially expressed genes (DEGs) that are relevant to the biological function of certain cell types. These results indicated that iSMNN will be a valuable method for integrating multiple scRNA-seq datasets that can facilitate biological and medical studies at single-cell level.
Reactive microglia enhance the transmission of exosomal α-synuclein via toll-like receptor 2
Authors: Xia Yun , Zhang Guoxin , Kou Liang , Yin Sijia , Han Chao , Hu Junjie , Wan Fang , Sun Yadi , Wu Jiawei , Li Yunna , Huang Jinsha , Xiong Nian , Zhang Zhentao , Wang Tao 
Published: March 2021

Abstract
Increasing evidence suggests that microglial activation is strongly linked to the initiation and progression of Parkinson’s disease. Cell-to-cell propagation of α-synuclein pathology is a highlighted feature of Parkinson’s disease, and the focus of such research has been primarily on neurons. However, recent studies as well as the data contained herein suggest that microglia, the primary phagocytes in the brain, play a direct role in the spread of α-synuclein pathology. Recent data revealed that plasma exosomes derived from Parkinson’s disease patients (PD-EXO) carry pathological α-synuclein and target microglia preferentially. Hence, PD-EXO are likely a key tool for investigating the role of microglia in α-synuclein transmission. We showed that intrastriatal injection of PD-EXO resulted in the propagation of exosomal α-synuclein from microglia to neurons following microglia activation. Toll-like receptor 2 (TLR2) in microglia was activated by exosomal α-synuclein and acted as a crucial mediator of PD-EXO-induced microglial activation. Additionally, partial microglia depletion resulted in a significant decrease of exogenous α-synuclein in the substantia nigra. Furthermore, exosomal α-synuclein internalization was initiated by binding to TLR2 of microglia. Excessive α-synuclein phagocytosis may induce the inflammatory responses of microglia and provide the seed for microglia-to-neuron transmission. Consistently, TLR2 silencing in microglia mitigated α-synuclein pathology in vivo. Overall, the present data support the idea that the interaction of exosomal α-synuclein and microglial TLR2 contribute to excessive α-synuclein phagocytosis and microglial activation, which lead to the further propagation and spread of α-synuclein pathology, thereby highlighting the pivotal roles of reactive microglia in α-synuclein transmission.
Organ-on-a-chip technology: a novel approach to investigate cardiovascular diseases
Authors: Paloschi Valentina , Sabater-Lleal Maria , Middelkamp Heleen , Vivas Aisen , Johansson Sofia , van der Meer Andries , Tenje Maria , Maegdefessel Lars 
Published: March 2021

Abstract
The development of organs-on-chip (OoC) has revolutionized in vitro cell-culture experiments by allowing a better mimicry of human physiology and pathophysiology that has consequently led researchers to gain more meaningful insights into disease mechanisms. Several models of hearts-on-chips and vessels-on-chips have been demonstrated to recapitulate fundamental aspects of the human cardiovascular system in the recent past. These 2D and 3D systems include synchronized beating cardiomyocytes in hearts-on-chips and vessels-on-chips with layer-based structures and the inclusion of physiological and pathological shear stress conditions. The opportunities to discover novel targets and to perform drug testing with chip-based platforms have substantially enhanced, thanks to the utilization of patient-derived cells and precise control of their microenvironment. These organ models will provide an important asset for future approaches to personalized cardiovascular medicine and improved patient care. However, certain technical and biological challenges remain, making the global utilization of OoCs to tackle unanswered questions in cardiovascular science still rather challenging. This review article aims to introduce and summarize published work on hearts- and vessels-on chips but also to provide an outlook and perspective on how these advanced in vitro systems can be used to tailor disease models with patient-specific characteristics.
Is the local wheat market a ‘market for lemons’? Certifying the supply of individual wheat farmers in Ethiopia
Authors: Anissa Banawe Plambou , Abate Gashaw , Bernard Tanguy , Bulte Erwin 
Published: March 2021

AbstractBulking and mixing of smallholder supply dilutes incentives to supply high quality. We introduce wheat ‘grading and certification shops’ in Ethiopia and use an auction design to gauge willingness-to-pay (WTP) for certification. Bids correlate positively with wheat quality, and ex ante notification of the opportunity of certification improves wheat quality. These findings suggest that local wheat markets resemble a ‘market for lemons’, crippled by asymmetric information. However, aggregate WTP for grading and certification services does not re-coup the sum of fixed, flow and variable costs associated with running a single certification shop.
The varied role, scope of practice, and education of cardiovascular nurses in ESC-affiliated countries: an ACNAP survey
Authors: Fitzsimons Donna , Carson Matthew A , Hansen Tina B , Neubeck Lis , Tanash Mu’ath I , Hill Loreena 
Published: March 2021

Abstract

Aims
Cardiovascular disease burden is increasing globally, pressuring nursing staff to deliver high-quality care across a diverse range of treatment areas. As such, an evaluation of the educational preparation of nurses is needed. To determine the current role, scope of practice, education level, and needs of cardiovascular nurses working across the European Society of Cardiology (ESC)-affiliated countries.

Methods and results
A short survey was distributed in paper (EuroHeartCare 2018) or electronic format to nurses delivering cardiovascular care. A total of 876 cardiovascular nurses from 26 ESC-affiliated countries completed the survey. Most respondents (79%), were educated to at least bachelor level, with 46% having a masters or doctorate, and were highly motivated to continue their educational development. Despite this, a large number (44.3%) of respondents believed they were not fully prepared for their job. The main areas where further education was requested included acute care in cardiovascular disease (CVD) and CVD risk factor management. Face-to-face courses/training were the most requested delivery mode, followed by E-learning—which appears to be underutilized in this population. Awareness of the existing curricula for cardiovascular nurse education was minimal, and therefore these resources require further promotion and implementation.

Conclusions
This international sample of cardiovascular nurses was generally educated to degree level and motivated to improve their cardiovascular knowledge. Many believed they were underprepared for their role, highlighting the need for increased investment in education. This should be focused on specific needs and delivered using a face-to-face, E-learning, or blended-learning format. Furthermore, increased signposting of existing resources is required.
MetaPrism: A versatile toolkit for joint taxa/gene analysis of metagenomic sequencing data
Authors: Kim Jiwoong , Jiang Shuang , Wang Yiqing , Xiao Guanghua , Xie Yang , Liu Dajiang J , Li Qiwei , Koh Andrew , Zhan Xiaowei 
Published: March 2021

Abstract
In microbiome research, metagenomic sequencing generates enormous amounts of data. These data are typically classified into taxa for taxonomy analysis, or into genes for functional analysis. However, a joint analysis where the reads are classified into taxa-specific genes is often overlooked. To enable the analysis of this biologically meaningful feature, we developed a novel bioinformatic toolkit, MetaPrism, which can analyze sequence reads for a set of joint taxa/gene analyses to: 1) classify sequence reads and estimate the abundances for taxa-specific genes; 2) tabularize and visualize taxa-specific gene abundances; 3) compare the abundances between groups; and 4) build prediction models for clinical outcome. We illustrated these functions using a published microbiome metagenomics dataset from patients treated with immune checkpoint inhibitor therapy and showed the joint features can serve as potential biomarkers to predict therapeutic responses. MetaPrism is a toolkit for joint taxa and gene analysis. It offers biological insights on the taxa-specific genes on top of the taxa-alone or gene-alone analysis.
MetaPrism is open-source software and freely available at https://github.com/jiwoongbio/MetaPrism. The example script to reproduce the manuscript is also provided in the above code repository.
Do efficiency gains really translate into more budget for health? An assessment framework and country applications
Authors: Barroy Hélène , Cylus Jonathan , Patcharanarumol Walaiporn , Novignon Jacob , Evetovits Tamás , Gupta Sanjeev 
Published: March 2021

AbstractEfficiency has historically been considered a key mechanism to increase the amount of available revenues to the health sector, enabling countries to expand services and benefits to progress towards universal health coverage (UHC). Country experience indicates, however, that efficiency gains do not automatically translate into greater budget for health, to additional revenues for the sector. This article proposes a framework to assess whether and how efficiency interventions are likely to increase budgetary space in health systems Based on a review of the literature and country experiences, we suggest three enabling conditions that must be met in order to transform efficiency gains into budgetary gains for health. First there must be well-defined efficiency interventions that target health system inputs, implemented over a medium-term time frame. Second, efficiency interventions must generate financial gains that are quantifiable either pre- or post-intervention. Third, public financial management systems must allow those gains to be kept within the health sector and repurposed towards priority health needs. When these conditions are not met, efficiency gains do not lead to more budgetary space for health. Rather, the gains may instead result in budget cuts that can be detrimental to health systems’ outputs and ultimately disincentivize further attempts to improve efficiency in the sector. The framework, when applied, offers an opportunity for policymakers to reconcile efficiency and budget expansion goals in health.