bluuebunny/crossref_metadata_2025_split huggingface dataset:
Upscaling Water Flow in Composite Nanoporous Shale Matrix Using Lattice Boltzmann Method
Authors: Zhang Tao , Javadpour Farzam , Yin Ying , Li Xiangfang 
Published: January 2020

AbstractWater flow in nanoporous structures in shale strongly depends on water‐pore wall interactions; specifically, water‐pore wall interactions may influence flow more than water‐water interactions. Because of strong water‐pore wall interactions, the models that govern flow in nanoporous structures deviate from conventional continuum flow models such as the Darcy equation. We develop a novel lattice Boltzmann model to study water flow in nanoporous structures rendered from shale samples. First, we reconstruct three‐dimensional (3‐D) stochastic digital models based on composite shale samples that include hydrophobic organic matter (OM) and hydrophilic clay minerals. In the reconstructed digital models, we use pore size/shape distributions, porosity, and mineralogy from experiments. Then we use lattice Boltzmann models to model water flow through nanoporous structures (OM and clay) of the reconstructed shale sample, and we upscale the results to a microporous structure of composite shale containing OM, clay, and interpores associated to other minerals. The results show contraction/expansion effects of pore‐throat‐pore systems in nanoporous OM weaken the hydrophobicity‐induced slippage effect on total water flow. In nanoporous clay, the swelling effect predominates and diminishes water slippage effects on water flow. The work also highlights the importance of (1) the accuracy of reconstructed 3‐D pore networks in terms of pore connectivity, shape, and tortuosity in individual systems of OM and clay and (2) the role of OM nanopores in connecting isolated micropores to total water flow through the composite shale system.
A Tree‐Based Direct Sampling Method for Stochastic Surface and Subsurface Hydrological Modeling
Authors: Zuo Chen , Yin Zhen , Pan Zhibin , MacKie Emma J. , Caers Jef 
Published: January 2020

AbstractDirect sampling (DS) is a versatile multiple‐point statistics method for generating spatial‐temporal geostatistical models. DS is known for being able to address a variety of training images and hence spatiotemporal stochastic modeling problems. One limitation of DS is the central processing unit (CPU) time, mostly attributed to the use of a random search for patterns in the training image. To improve CPU performance, we propose a tree‐based direct sampling (TDS) method. In our method, training patterns are grouped according to their similarities combined with a clustering tree for fast lookup. Rather than patterns, we store locations in our database. During the simulation, TDS applies a tree‐driven search approach. Two objectives, similarity and diversity, are used to rapidly retrieve patterns and prevent trapping into local optima. We also introduce a way to speed up simulation by means of pasting patterns with adaptive size. The performance of our TDS is investigated using a 2‐D benchmark training image. Moreover, we apply the proposed method to two real cases including gap filling the bedrock topography in Antarctica from radar to better understand subglacial hydrology and creating 3‐D groundwater models in the Danish aquifer system. Based on several quantitative evaluations, we find the proposed TDS is comparable to DS in terms of simulation quality, while significantly saves CPU time.
Adaptive introgression from indicine cattle into white cattle breeds from Central Italy
Authors: Barbato Mario , Hailer Frank , Upadhyay Maulik , Del Corvo Marcello , Colli Licia , Negrini Riccardo , Kim Eui-Soo , Crooijmans Richard P. M. A. , Sonstegard Tad , Ajmone-Marsan Paolo 
Published: January 2020

AbstractCattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies.
Surface charge accumulation and pre‐flashover characteristics induced by metal particles on the insulator surfaces of 1100 kV GILs under AC voltage
Authors: Xing Li , Weidong Liu , Yuan Xu , Weijiang Chen , Jiangang Bi 
Published: January 2020

With the increase in the voltage and capacitance of gas‐insulated transmission lines (GILs), the insulation failure of GIL has attracted more and more attention. Further understanding of the partial discharge (PD) and flashover characteristics of metal particles on the insulator surface, as well as the flashover mechanism, is necessary to reduce the failure rate and improve the reliability of the equipment. In this study, an ultra‐high voltage (UHV) AC insulator PD test and measurement system based on the cross‐reference pulse current (PC) and ultra‐high frequency (UHF) methods were established. The PD development and flashover characteristics of 5 mm‐long metal particles at different positions on the surface of a UHV AC insulator, as well as the surface charge accumulation, were studied. The results show that the discharge of millimetre‐scale metal particles on the insulator surface under PD test conditions is relatively low (generally lower than 2PC), and it is difficult to be detected by the conventional PC and UHF methods due to their insufficient sensitivity. Moreover, it is found that the weak PDs of the millimetre‐scale metal particles will result in a charge accumulation on the insulator surface under AC voltage, which eventually will lead to the insulator flashover. The PDs of the UHV AC insulator before flashover are generally small, which will make it difficult for online monitoring systems to give an effective alarm before flashover.
Intelligent energy management in microgrid using prediction errors from uncertain renewable power generation
Authors: Majumder Irani , Dhar Snehamoy , Dash Pradipta Kishore , Mishra Sthita Prajna 
Published: January 2020

This study proposes an efficient local energy management system (LEMS) based on the generalised power prediction model for the uncertain operation of renewable distributed generations (DGs)‐based microgrid. Photovoltaic with battery energy storage, and wind power generation are considered as primary DGs to compensate intermittency. Conventional direct power prediction models are limited to specific DG applications, where the plant data acquisition system is a necessity. Solar irradiance and wind speed are considered here as prediction targets to cope with such additional expenditure for a microgrid. To ensure a robust reduction in prediction error (ep), a short‐term prediction model is developed by virtue of the proposed robust regularised random vector functional link network. A maximum‐likelihood estimator using Huber's cost function is employed to attain the robustness of this model. Further, a direct renewable energy source‐power calculation is opted to address model accuracy under local uncertainties. The LEMS operation is completed by compensating ep with distributed adaptive droop‐based primary controllers for multi‐DG based microgrid. To ensure the performance of the prediction model, solar irradiance, wind speed and power at different atmospheric conditions (seasonal volatility) and time span (i.e. 5, 10 and 60 min) have been implemented in MATLAB and real time.
Design of a gate driver for SiC MOSFET module for applications up to 1200 V
Authors: Batard Christophe , Ginot Nicolas , Bouguet Christophe 
Published: January 2020

Nowadays new silicon carbide (SiC) metal‐oxide‐semiconductor field‐effect transistors (MOSFETs) are available in the market and they are expected to replace, in the next few years, the insulated gate bipolar transistor (IGBT) and Si‐MOSFET in power electronic converters. SiC MOSFET transistors must be controlled by a dedicated circuit called ‘gate driver’ which ensures the switching orders transmission, the users’ safety and the switching cell integrity. The design of a gate driver dedicated to a SiC MOSFET module for applications up to 1200 V is described in this study. Galvanic isolation of control signals and power supplies, the power supply structure, SiC MOSFET switching orders and protection functions are detailed. Essential functions such as the short circuit detection and the implementation of the soft shut down are expanded. The developed gate driver is tested and validated. Experimental measurements allow for the validation of the good functioning of the developed gate driver in a highly disturbed environment.
Automatic generation control of a large hydropower plant with head‐sensitive forbidden and restricted zones
Authors: Shen Jianjian , Hu Lin , Cheng Chuntian , Wang Sen 
Published: January 2020

Head‐sensitive forbidden and restricted zones of large hydropower units are challenging the automatic generation control (AGC) as admissible operating zones are discontinuous and variational. This study focuses on the AGC of such a large hydropower plant to ensure the stability, security and timeliness of power grids. A methodology is developed to solve the unit commitment (UC) and load distribution in AGC. This methodology identifies in advance all feasible unit combinations under different water heads and determines admissible operating zones using combinatorial mathematics techniques. A fast strategy that includes the accurate estimation of varying water heads helps to eliminate infeasible unit combinations. Minimising the number of units working in restricted zones and times of unit output passing through forbidden zones is used to optimise the UC, where priority orders of units are introduced to evaluate UC schemes with the same objective value. Finally, a dynamic programming based model is formulated to solve an economic load distribution among operating units. The methodology is applied to the AGC of the Nuozhadu with nine 650 MW units of two different types. Three cases indicate that the number of units working in restricted zones and times of unit output passing through forbidden zones is significantly reduced.
Radar signals classification using energy‐time‐frequency distribution features
Authors: Seddighi Zahra , Ahmadzadeh Mohammad Reza , Taban Mohammad Reza 
Published: January 2020

In this research, the authors extract features from intermediate frequency band radar signals in the time–frequency domain for classification. The extracted features are classified via support vector machine and K‐nearest neighbour classifiers. They show the accuracy of classification is above 99% for different classes of radar signals except for frequency shift keying signal with accuracy 83% in negative signal‐to‐noise ratio (SNR). To identify the radars with the same class, the classification accuracy is 91% for SNR between 5 to 15 dB and 64% in the worst case for SNR between −1 to 10 dB. The proposed method is compared with some methods based on the empirical mode decomposition (EMD), cumulant and Zhao Atlas Mark Distribution (ZAMD). The results show that the classification error in the proposed method is less than that of EMD method 55% in the best case and 9% in the worst case. The performance of the cumulant‐based method is weaker than that of the proposed method in common designed scenarios becoming almost similar only in one scenario. The ZAMD‐based method could only distinguish the signals with different modulations in high SNR while it is unable to classify the signals with the same modulation but different parameters.
Horizontal connection method for glass microfluidic devices
Authors: Yalikun Yaxiaer , Ota Nobutoshi , Ma Doudou , Tanaka Yo 
Published: January 2020

In a conventional glass microfluidic system, the vertical connection is the most frequently used for connections between a microfluidic device and its peripheral equipment. However, it leads to a significant pressure drop at the inlet of a microfluidic device, decreases the flow velocity, and can introduce few samples than expected. To overcome these problems, a horizontal connection method for glass microfluidic devices, which have advantages such as keeping pressure/flow velocity, compatible with small space, reduced sample loss and convenience for modularisation is reported. These advantages are important for high‐speed analysis on precious samples such as single‐cell flow cytometry. In this work, they proposed a horizontal connection method which showed compatibility with high pressure (at least 0.6 MPa) at inlet without leakage, small loss of injected samples (<0.11%), and 22% faster flow velocity along the direction of applied pressure than that of vertical connection.
Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging
Authors: Hou Ying-Chen Claire , Yu Hung-Chun , Martin Rick , Cirulli Elizabeth T. , Schenker-Ahmed Natalie M. , Hicks Michael , Cohen Isaac V. , Jönsson Thomas J. , Heister Robyn , Napier Lori , Swisher Christine Leon , Dominguez Saints , Tang Haibao , Li Weizhong , Perkins Bradley A. , Barea Jaime , Rybak Christina , Smith Emily , Duchicela Keegan , Doney Michael , Brar Pamila , Hernandez Nathaniel , Kirkness Ewen F. , Kahn Andrew M. , Venter J. Craig , Karow David S. , Caskey C. Thomas 
Published: January 2020

Significance
To understand the value and clinical impact of surveying genome-wide disease-causing genes and variants, we used a prospective cohort study design that enrolled volunteers who agreed to have their whole genome sequenced and to participate in deep phenotyping using clinical laboratory tests, metabolomics technologies, and advanced noninvasive imaging. The genomic results are integrated with the phenotype results. Approximately 1 in 6 adult individuals (17.3%) had genetic findings and, when integrated with deep phenotyping data, including family/medical histories with genetic findings, 1 in 9 (11.5%) had genotype and phenotype associations. Genomics and metabolomics association analysis revealed 5.1% of heterozygotes with phenotype manifestations affecting serum metabolite levels. We report observations from our study in which health outcomes and benefits were not measured.
Allosteric activation of MALT1 by its ubiquitin-binding Ig3 domain
Authors: Schairer Rebekka , Hall Gareth , Zhang Ming , Cowan Richard , Baravalle Roberta , Muskett Frederick W. , Coombs Peter J. , Mpamhanga Chido , Hale Lisa R. , Saxty Barbara , Iwaszkiewicz Justyna , Décaillet Chantal , Perroud Mai , Carr Mark D. , Thome Margot 
Published: January 2020

Significance
The protease MALT1 has been shown to play an essential role in the adaptive immune response and the development of lymphoma. The catalytic activity of MALT1 is tightly regulated by monoubiquitination, however, how ubiquitin is conjugated to MALT1 and the manner by which this modification regulates MALT1 activity remains poorly understood. Our data suggest that the Ig3 domain of MALT1 physically recruits ubiquitin to enable monoubiquitination and that ubiquitin conjugation to MALT1 activates the protease by inducing conformational changes in the Ig3 domain that are communicated to the active site. These findings identify the Ig3 domain of MALT1 as a novel ubiquitin-binding domain and provide insight into the molecular requirements for MALT1 activation that could be of therapeutic interest.
Actigraphy-Based Assessment of Sleep Parameters
Authors: Fekedulegn Desta , Andrew Michael E , Shi Mingming , Violanti John M , Knox Sarah , Innes Kim E 
Published: January 2020

Abstract
Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used.
decorate: differential epigenetic correlation test
Authors: Hoffman Gabriel E , Bendl Jaroslav , Girdhar Kiran , Roussos Panos 
Published: January 2020

Abstract

Motivation
Identifying correlated epigenetic features and finding differences in correlation between individuals with disease compared to controls can give novel insight into disease biology. This framework has been successful in analysis of gene expression data, but application to epigenetic data has been limited by the computational cost, lack of scalable software and lack of robust statistical tests.

Results
Decorate, differential epigenetic correlation test, identifies correlated epigenetic features and finds clusters of features that are differentially correlated between two or more subsets of the data. The software scales to genome-wide datasets of epigenetic assays on hundreds of individuals. We apply decorate to four large-scale datasets of DNA methylation, ATAC-seq and histone modification ChIP-seq.

Availability and implementation
decorate R package is available from https://github.com/GabrielHoffman/decorate.

Supplementary information
Supplementary data are available at Bioinformatics online.
Wild bootstrap for fuzzy regression discontinuity designs: obtaining robust bias-corrected confidence intervals
Authors: He Yang , Bartalotti Otávio 
Published: January 2020

Summary
This paper develops a novel wild bootstrap procedure to construct robust bias-corrected valid confidence intervals for fuzzy regression discontinuity designs, providing an intuitive complement to existing robust bias-corrected methods. The confidence intervals generated by this procedure are valid under conditions similar to the procedures proposed by Calonico et al. (2014) and related literature. Simulations provide evidence that this new method is at least as accurate as the plug-in analytical corrections when applied to a variety of data-generating processes featuring endogeneity and clustering. Finally, we demonstrate its empirical relevance by revisiting Angrist and Lavy (1999) analysis of class size on student outcomes.
Daily Dynamics of an Ant Community in a Mountaintop Ecosystem
Authors: Calazans Eloá Gonçalves , Costa Fernanda Vieira da , Cristiano Maykon Passos , Cardoso Danon Clemes 
Published: January 2020

Abstract
Abiotic conditions have a great influence on the structure of biological communities, especially considering ectothermic organisms, such as ants. In this study, we tested whether the daily temporal dynamics of an ant community in a tropical mountainous ecosystem is driven by daily fluctuations of abiotic factors, such as temperature and humidity. We also investigated whether the strong oscillation in daily temperature leads to high heterogeneity in ant species thermal responses. We have found that air and soil temperatures positively influenced the richness and frequency of foraging ants, while air humidity caused the opposite effect. Ant activity followed daily temperature fluctuations, which resulted in subtle differences in foraging patterns featured by heat-tolerant and heat-intolerant species. Moreover, the studied ant community exhibited broad and highly overlapped thermal responses, suggesting a likely resilience under temperature oscillations. Lastly, identifying how species traits are linked to oscillations in abiotic conditions is a necessary step to predict the effects of future climatic changes on biological community dynamics and ecosystem functioning.
Cardiovascular mortality following liver transplantation: predictors and temporal trends over 30 years
Authors: Koshy Anoop N , Gow Paul J , Han Hui-Chen , Teh Andrew W , Jones Robert , Testro Adam , Lim Han S , McCaughan Geoffrey , Jeffrey Gary P , Crawford Michael , Macdonald Graeme , Fawcett Jonathan , Wigg Alan , Chen John W C , Gane Edward J , Munn Stephen R , Clark David J , Yudi Matias B , Farouque Omar 
Published: January 2020

Abstract

Aims
There has been significant evolution in operative and post-transplant therapies following liver transplantation (LT). We sought to study their impact on cardiovascular (CV) mortality, particularly in the longer term.

Methods and results
A retrospective cohort study was conducted of all adult LTs in Australia and New Zealand across three 11-year eras from 1985 to assess prevalence, modes, and predictors of early (≤30 days) and late (&gt;30 days) CV mortality. A total of 4265 patients were followed-up for 37 409 person-years. Overall, 1328 patients died, and CV mortality accounted for 228 (17.2%) deaths. Both early and late CV mortality fell significantly across the eras (P &lt; 0.001). However, CV aetiologies were consistently the leading cause of early mortality and accounted for ∼40% of early deaths in the contemporary era. Cardiovascular deaths occurred significantly later than non-cardiac aetiologies (8.8 vs. 5.2 years, P &lt; 0.001). On multivariable Cox regression, coronary artery disease [hazard ratio (HR) 4.6, 95% confidence interval (CI) 1.2–21.6; P = 0.04] and era of transplantation (HR 0.44; 95% CI 0.28–0.70; P = 0.01) were predictors of early CV mortality, while advancing age (HR 1.05, 95% CI 1.02–1.10; P = 0.005) was an independent predictors of late CV mortality. Most common modes of CV death were cardiac arrest, cerebrovascular events, and myocardial infarction.

Conclusion
Despite reductions in CV mortality post-LT over 30 years, they still account for a substantial proportion of early and late deaths. The late occurrence of CV deaths highlights the importance of longitudinal follow-up to study the efficacy of targeted risk-reduction strategies in this unique patient population.