bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-carbon economic dispatching model of electric-heating combined system considering multi-type energy storage
Authors: Pan Xiao , Liang Yi , Deng Xinyang , Li Minchao , Cui Jia , Yang Junyou 
Published: August 2020

Abstract
In order to reduce the wind abandonment rate during the winter heating period in the “Three North” region and the environmental pollution caused by carbon emissions during power generation, this paper proposes a low-carbon economic dispatching model that takes into account multiple types of energy storage for electric-heating combined systems. First, a multi-type energy storage model with electric boilers, electric energy storage, and heat storage as the core is proposed, and its internal energy conversion, storage, and output links are refined. Then, a carbon trading mechanism is introduced into electric heating. The combined system, taking into account the cost of carbon trading, and aiming at the lowest overall operating cost of the system, construct a low-carbon economic dispatching model for wind-power, conventional thermal power units, combined heat and power units, and multiple types of energy-storage combined heat and power systems. Yalmip/Gurobi solved the model and analysed the wind power consumption effect and carbon emission situation in the dispatching mode through numerical simulation. Simulation results show that under carbon trading, participation of multiple types of energy storage can effectively improve wind power utilization and the economic and environmental benefits of the system.
Research on the business model of power retail market under the energy Internet
Authors: Li Yongbo , Qian Hanhan , Liu Dunnan , Li Genzhu 
Published: August 2020

Abstract
With the continuous development of the energy Internet, small and micro market entities are given the right to choose independently. Multiple new entities such as distributed energy, virtual power plants, electric vehicles, interactive energy use enter the power market and participate in power trading, creating an open and shared power market environment. At the same time, with the deepening of China’s power system reform, the focus of market construction will shift from wholesale side to retail side. Therefore, it is urgent to study the business model of power retail market, so as to take necessary preventive measures and avoidance measures as early as possible to avoid and reduce the pressure and risk faced by grid companies.
Feasibility study of typhoon disaster economic loss assessment based on random forest
Authors: Wang Fei 
Published: August 2020

Abstract
Based on the disaster-causing factors and the actual disaster-causing factors of typhoon disasters, this paper selects 9 assessment indicators, obtains an effective sample set through noise processing, and uses a random forest algorithm to set up a typhoon disaster economic loss assessment model. The model verification and results show that the random forest model has very obvious advantages in both single-level evaluation accuracy and total evaluation accuracy, and can meet the consistency with the actual evaluation standards. The GINI index reduction value obtained through model feedback can be used as an indicator of importance, and the indicator of the number of disaster victims is the most important factor of economic loss.
Correlation study on environmental performance of Chengdu and economic development
Authors: Wei Wei , Shang Yingnan , Zhou Xiaoying , Wen Bo , Wang Jiecai , Jiang Yijing , Li Zuocheng 
Published: August 2020

Abstract
This paper evaluated the environmental performance from 2013 to 2018 based on establishing environmental performance assessment system of Chengdu and the correlation of environmental performance increasing rate and GDP increasing rate was analyzed. In addition, Pearson’s correlation analysis on environmental performance index and GDP was carried out by using SPSS and we can see from the results that environmental performance shows an increasing tendency with the growth of GDP, environmental performance increasing rate is lower than GDP increasing rate. And there was no obvious correlation between environmental performance index and GDP (some high economical areas have low environmental performance levels). In another word, the rapid development of the economy does little help to rapidly improve environmental performance level. So Chengdu should pay more attention to protect environment, and be a coordinated development relationship between economy and environment.
Field investigation on rural domestic sewage discharge in a typical village of the Taihu Lake Basin
Authors: Xu Yuye , Lu Xiwu , Chen Fangkui 
Published: August 2020

Abstract
Rural sewage is an important non-point pollution that aggravates eutrophication of the Taihu Lake. Practically grasping the characteristics of local villages’ sewage treatment demand, sewage flow and sewage quality has far-reaching significance for constructing suitable and efficient rural sewage treatment systems, and ultimately improving the water environment of the lake basin. To this end, the study conducted a field investigation in a typical village of the Taihu Lake Basin in July and continuously monitored sewage flow and sewage quality in the mode of sewage classification. The sewage quality test included chemical oxygen demand (COD), total nitrogen (TN), ammonia nitrogen (NH3-N), and total phosphorus (TP). This paper reviewed the development status of the typical village and demonstrated the rules of rural domestic water consumption and sewage discharge. It was found that the total sewage discharge flow in summer was around 88.90 L/(cap . d) and the hourly variation coefficient was around 3.92. Kitchen sewage, washing sewage, and toilet sewage had significant differences in sewage quality. Particularly, the nitrogen and phosphorus nutrients in toilet sewage were quite rich, accounting for 84.42% and 61.90% of the corresponding total load, respectively. Thus, the ideas of properties-classified treatment and resource treatment were worth being introduced into the rural sewage treatment process.
Analysis of chlorinated hydrocarbon source of groundwater in the eastern part of a city
Authors: Liu Shusen , Ma Zhenmin , Zhang Shuaiji 
Published: August 2020

Abstract
In order to control the pollution of chlorinated hydrocarbons in groundwater, it is necessary to analyze the source of chlorinated hydrocarbons in groundwater. Therefore, this paper uses the method of factor analysis and multiple linear regression equation to analyze the source of the study area. The results show that the pollution sources in the study area can be summarized as chemical enterprise pollution sources, electromechanical manufacturing pollution sources, chemical fiber pollution sources and pesticide pollution sources.
Experimental Study on Thermal Runaway of LiFePO4/C Battery under Heating Condition
Authors: Gao Fei , Kai Yang , Wang Congjie , Liu Wei , Zhu Yanli 
Published: August 2020

Abstract
The safety of lithium ion batteries is a hot topic in battery application and research at present. LiFePO4/C batteries are generally believed to be safe and have been widely used. The LiFePO4/C batteries are taken as the research object, the thermal runaway characteristics of the LiFePO4/C batteries are analyzed from the changes of battery temperature and voltage during the test process. The results show that the battery volatge fluctuated greatly before the thermal runaway occurred for the battery under one side heating, however, the battery voltage did not fluctuate and dropt to 0 V for the battery under two sides heating. For the battery group under one side heating, the thermal runaway chain reaction did not occur, which meant that the LiFePO4/C battery possessed good safety.
Degradation of Orange I by the zero-valent iron/hydrogen peroxide system
Authors: Zhou Jian , Hou Meifang 
Published: August 2020

Abstract
The zero-valent iron/hydrogen peroxide system was very effective for the oxidative degradation of high concentration Orange I solution. The effects of Orange I initial concentration, hydrogen peroxide concentration, zero-valent iron dosage and pH value of solution on the degradation of Orange I were studied in this article. The concentration of iron ion, pH value and the content of Orange I in the reaction solution were determined by UV-VIS spectrophotometer and pH meter, respectively. The intermediate degradation products were determined by LC-MS. The experimental results showed that the Orange I solution with high concentration could be effectively degraded with low hydrogen peroxide concentration and iron powder dosage under acid condition. In addition, it can be speculated that in the process of degradation, Orange I was first dissociated into 4-(4-hydroxy-1-naphthylazo) benzenesulfonate, and then its chromophore was oxidized and broken, decoloring the reaction solution, followed by the generation to benzene sulfonate, nitrogen and 1, 4-naphthoquinone. After that, 1, 4-naphthoquinone was further oxidized to phthalate.
Experimental Study on the Mechanical Properties of C40 Self-Compacting Solid Ferrous Tailings Concrete
Authors: Zhou Shuangshuang , Liu Jinghong 
Published: August 2020

Abstract
Through the experiments on the mechanical properties of the self-compacting solid ferrous tailings concrete, it studied the effect of tailings powders under various substitution rates upon the mechanical properties of C40 self-compacting solid ferrous tailings concrete. By experiments on the slump expansibility and expansion time T500 of the self-compacting solid tailings concrete, it also studied the effect on the workability of the ferrous tailings powder under various substitution rates. In the light of the experimental results, it provided that, the slump expansibility of the self-compacting solid ferrous tailings concrete enlarged by degrees with the increase of substitution rate of the ferrous tailings powder; the expansion time T500 shortened as the substitution rate of the ferrous tailings powder increased. The cubic compressive strength, the axis compressive strength, the splitting tensile strength as well as the plastic modulus of the self-compacting solid ferrous tailings concrete all inclined to decrease with the swell of substitution rate of the ferrous tailings powder.
Dynamic disturbance damage of rock mass in layered blasting of deep underground plant
Authors: Liang Wu , Tianci Li , Xiaorui Xiang , Jiayi HU 
Published: August 2020

Abstract
This paper established a constitutive model for rock dynamic tension based on HJC and TCK, and achieved the material model embedding through the LS-DYNA UMAT secondary development module analyzed the effect of blasting load, in-situ stress unloading and coupled load on damage distribution of surrounding rock of factory building during layered excavation. Studies have shown that the damage degree of the surrounding rock near the outline of the plant is the largest during the blasting excavation of deep underground powerhouses; when the in-situ stress level is low, the surrounding rock damage near the excavation surface is mainly affected by the blasting load, when the in-situ stress level is high, the surrounding rock damage near the excavation surface caused by the blasting load will be squeezed by the ground stress; in the remote excavated area, the surrounding rock damage is mainly caused by the redistribution of in-situ stress.
The improved analytic hierarchy process (ahp) based on accident tree is applied to the study of community gas risk assessment
Authors: Wen Zhang Zheng 
Published: August 2020

Abstract
Gas safety is related to every family in the community. In this paper, the structural importance in the accident tree is taken as the basis of analytic hierarchy process (ahp) judgment matrix. The improved ahp reduces human subjectivity. It is hoped to provide some reference for the risk assessment of gas leakage accident.
Simulation Verification of Phased Array Ultrasonic Detection Scheme for Wind Turbine Main Shaft in Service
Authors: Xu Zhengbin 
Published: August 2020

Abstract
The main shaft is the key link in the wind turbine drive. Based on the previous scheme design of phased array ultrasonic testing of wind turbine and the results of transducer parameter range determined, simulation verification is carried out in this study. It is verified that the preliminary theoretical design scheme can effectively detect the early defects of the main shaft shoulder position of the wind turbine, which lays a good foundation for the field implementation in the future.
Analysis of micro-friction stir welding surfaces using fractal methodologies
Authors: Prajapati Deepak K , Ahmed Shuja 
Published: August 2020

Abstract
The weld surface produced by micro-friction stir welding (micro-FSW) exhibit multi-scale nature. The surface topography of weld surfaces affects the overall strength of components and significantly changes with process parameters. In this work, multi-scale surface characterization techniques are used to study the surface topography of micro-FSW surfaces. The relation between process parameters and topography parameters is discussed in detail. Length-scale fractal analysis is employed on micro-FSW surfaces, and it is concluded that surface complexity increases with an increase in tool rotational speed. Within the range of process parameters studied, smoothening takes place at higher tool feed. The Hurst coefficient (H), which is an important descriptor of fractal geometry is found to increase with an increase in tool feed.
Fractional quantum Hall effect in CVD-grown graphene
Authors: Schmitz M , Ouaj T , Winter Z , Rubi K , Watanabe K , Taniguchi T , Zeitler U , Beschoten B , Stampfer C 
Published: August 2020

Abstract
We show the emergence of fractional quantum Hall states in graphene grown by chemical vapor deposition (CVD) for magnetic fields from below 3 T to 35 T where the CVD-graphene was dry-transferred. Effective composite-fermion filling factors up to ν
* = 4 are visible and higher order composite-fermion states (with four flux quanta attached) start to emerge at the highest fields. Our results show that the quantum mobility of CVD-grown graphene is comparable to that of exfoliated graphene and, more specifically, that the p/3 fractional quantum Hall states have energy gaps of up to 30 K, well comparable to those observed in other silicon-gated devices based on exfoliated graphene.
Reducing autocorrelation times in lattice simulations with generative adversarial networks
Authors: Pawlowski Jan M , Urban Julian M 
Published: August 2020

Abstract
Short autocorrelation times are essential for a reliable error assessment in Monte Carlo simulations of lattice systems. In many interesting scenarios, the decay of autocorrelations in the Markov chain is prohibitively slow. Generative samplers can provide statistically independent field configurations, thereby potentially ameliorating these issues. In this work, the applicability of neural samplers to this problem is investigated. Specifically, we work with a generative adversarial network (GAN). We propose to address difficulties regarding its statistical exactness through the implementation of an overrelaxation step, by searching the latent space of the trained generator network. This procedure can be incorporated into a standard Monte Carlo algorithm, which then permits a sensible assessment of ergodicity and balance based on consistency checks. Numerical results for real, scalar φ
4-theory in two dimensions are presented. We achieve a significant reduction of autocorrelations while accurately reproducing the correct statistics. We discuss possible improvements to the approach as well as potential solutions to persisting issues.
Unsupervised protein embeddings outperform hand-crafted sequence and structure features at predicting molecular function
Authors: Villegas-Morcillo Amelia , Makrodimitris Stavros , van Ham Roeland C H J , Gomez Angel M , Sanchez Victoria , Reinders Marcel J T 
Published: August 2020

Abstract

Motivation
Protein function prediction is a difficult bioinformatics problem. Many recent methods use deep neural networks to learn complex sequence representations and predict function from these. Deep supervised models require a lot of labeled training data which are not available for this task. However, a very large amount of protein sequences without functional labels is available.

Results
We applied an existing deep sequence model that had been pretrained in an unsupervised setting on the supervised task of protein molecular function prediction. We found that this complex feature representation is effective for this task, outperforming hand-crafted features such as one-hot encoding of amino acids, k-mer counts, secondary structure and backbone angles. Also, it partly negates the need for complex prediction models, as a two-layer perceptron was enough to achieve competitive performance in the third Critical Assessment of Functional Annotation benchmark. We also show that combining this sequence representation with protein 3D structure information does not lead to performance improvement, hinting that 3D structure is also potentially learned during the unsupervised pretraining.

Availability and implementation
Implementations of all used models can be found at https://github.com/stamakro/GCN-for-Structure-and-Function.

Supplementary information
Supplementary data are available at Bioinformatics online.
Mechanistic insights into SARS-CoV-2 epidemic via revealing the features of SARS-CoV-2 coding proteins and host responses upon its infection
Authors: Qin Shijie , Xia Xinyi , Shi Xuejia , Ji Xinglai , Ma Fei , Chen Liming 
Published: August 2020

ABSTRACT

Summary
There are seven known coronaviruses that infect humans: four mild coronaviruses, including HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1, only cause mild respiratory diseases, and three severe coronaviruses, including SARS-CoV, MERS-CoV and SARS-CoV-2, can cause severe respiratory diseases even death of infected patients. Both infection and death caused by SARS-CoV-2 are still rapidly increasing worldwide. In this study, we demonstrate that viral coding proteins of SARS-CoV-2 have distinct features and are most, medium and least conserved with SARS-CoV, MERS-CoV and the rest four mild coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1), respectively. Moreover, expression of host responsive genes (HRG), HRG-enriched biological processes and HRG-enriched KEGG pathways upon infection of SARS-CoV-2 shows slightly overlapping with SARS-CoV and MERS-CoV but distinctive to the four mild coronaviruses. Interestingly, enrichment of overactivation of neutrophil by HRGs is only and commonly found in infections of severe SARS-CoV-2, SARS-CoV and MERS-CoV but not in the other four mild coronaviruses, and the related gene networks show different patterns. Clinical data support that overactivation of neutrophil for severe patients can be one major factor for the similar clinical symptoms observed in SARS-CoV-2 infection compared to infections of the other two severe coronavirus (SARS-CoV and MERS-CoV). Taken together, our study provides a mechanistic insight into SARS-CoV-2 epidemic via revealing the conserved and distinct features of SARS-CoV-2, raising the critical role of dysregulation of neutrophil for SARS-CoV-2 infection.

Availability and Implementation
All data sources and analysis methods related to this manuscript are available in the methods, supplementary materials and GEO database (https://www.ncbi.nlm.nih.gov/geo/).

Supplementary information
Supplementary data are available at Bioinformatics online.
ipDMR: identification of differentially methylated regions with interval P-values
Authors: Xu Zongli , Xie Changchun , Taylor Jack A , Niu Liang 
Published: August 2020

Abstract

Summary
ipDMR is an R software tool for identification of differentially methylated regions (DMRs) using auto-correlated P-values for individual CpGs from epigenome-wide association analysis using array or bisulfite sequencing data. It summarizes P-values for adjacent CpGs, identifies association peaks and then extends peaks to find boundaries of DMRs. ipDMR uses BED format files as input and is easy to use. Simulations guided by real data found that ipDMR outperformed current available methods and provided slightly higher true positive rates and much lower false discovery rates.

Availability and implementation
ipDMR is available at https://bioconductor.org/packages/release/bioc/html/ENmix.html.

Supplementary information
Supplementary data are available at Bioinformatics online.
Integrating genomic correlation structure improves copy number variations detection
Authors: Luo Xizhi , Qin Fei , Cai Guoshuai , Xiao Feifei 
Published: August 2020

Abstract

Motivation
Copy number variation plays important roles in human complex diseases. The detection of copy number variants (CNVs) is identifying mean shift in genetic intensities to locate chromosomal breakpoints, the step of which is referred to as chromosomal segmentation. Many segmentation algorithms have been developed with a strong assumption of independent observations in the genetic loci, and they assume each locus has an equal chance to be a breakpoint (i.e. boundary of CNVs). However, this assumption is violated in the genetics perspective due to the existence of correlation among genomic positions, such as linkage disequilibrium (LD). Our study showed that the LD structure is related to the location distribution of CNVs, which indeed presents a non-random pattern on the genome. To generate more accurate CNVs, we proposed a novel algorithm, LDcnv, that models the CNV data with its biological characteristics relating to genetic dependence structure (i.e. LD).

Results
We theoretically demonstrated the correlation structure of CNV data in SNP array, which further supports the necessity of integrating biological structure in statistical methods for CNV detection. Therefore, we developed the LDcnv that integrated the genomic correlation structure with a local search strategy into statistical modeling of the CNV intensities. To evaluate the performance of LDcnv, we conducted extensive simulations and analyzed large-scale HapMap datasets. We showed that LDcnv presented high accuracy, stability and robustness in CNV detection and higher precision in detecting short CNVs compared to existing methods. This new segmentation algorithm has a wide scope of potential application with data from various high-throughput technology platforms.

Availability and implementation
https://github.com/FeifeiXiaoUSC/LDcnv.

Supplementary information
Supplementary data are available at Bioinformatics online.
Racial Microaggressions at Work: Reflections from Black African Professionals in Australia
Authors: Gatwiri Kathomi 
Published: August 2020

Abstract
Theorising how race and Africanness intersect in the professional lives of African immigrants can provide a nuanced understanding of how racial identities shape the professional identities of Black Africans in Australia. This article is contextualised within a larger study that sought to explore the Afro-diasporic experiences of highly skilled Black African immigrants in South Australia. Particularly, it examines how Black African professionals experience their workplace. Data were collected through face-to-face semi-structured interviews with twenty-seven Black African professionals in South Australia. The findings from this study reveal that the often-accepted narrative of race-free workplaces is not one that is supported by Black African immigrants’ experiences, as they report constant, subtle and covert patterns of racial microaggressions in the workplace. Utilising critical race theories, this article makes the invisibility of microaggressions visible by probing how the Black body is worn as a burden in the workplace, which consequently produces psychological distress and racial battle fatigue. This study will provide social work practitioners with a critical understanding of the various challenges facing African professionals in the workplace, and how processes of racialisation at work may impact on psychological safety in this environment.