bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic bifurcation for a three-species cooperating model
Authors: Li Junyan , Wu Ruili 
Published: July 2021

Abstract
A dynamic bifurcation analysis on a three-species cooperating model was presented and it was proved that the problem bifurcated an attractor as the parameter λ crossed the critical value λ0. The analysis was based on the attractor bifurcation theory together with the central manifold reduction.
Comparison study in statistical estimation of gene effects based on a real data set
Authors: Sheng Xiaona , Ma Yuqiu , Zhou Jiabin , Zhou Jingjing 
Published: July 2021

Abstract
Gene mapping study is very important task in current biostatistics and real life science. Most biological traits are mainly controlled by the genetic factors, i.e., the function of genes in the genome, and also affected by some environment factors. Reasonable statistical theory and methods should be used in the gene mapping study, so that the gene effects can be inferred precisely and reliable evidence can be further provided to practical domains of genetics and medicine. In this paper, we compare two statistical methods (conventional LSE method and the Dantzig Selector method) on estimating gene effects in the framework of linear model, and make some comparison on them. The two methods are illustrated by applying to a real data set. The analyzing results show that the Dantzig Selector method has some advantagement although the two methods give similar parameter estimates.
Assessing the role of voluntary nucleic acid testing with mandatory isolation in the control of COVID-19 using a household epidemic model
Authors: Liang Yan 
Published: July 2021

Abstract
The COVID-19 epidemic has had a major impact on people’s lives around the world, and many countries and regions have adopted voluntary nucleic acid testing with mandatory isolation for confirmed household to control COVID-19. Based on the method of branching process, this paper analyzes the influence of related factors on the control effect of voluntary nucleic acid testing with mandatory isolation for confirmed household by establishing a specific household model. Through numerical simulation and comparative analysis, we found that increasing the proportion of voluntary nucleic acid testing and shortening the start time of voluntary testing could enhance the epidemic control effect of this measure. At the same time, the proportion of the symptomatic will also have an impact on the effectiveness of the measure.
Analysis of climate change characteristics of wind in Baoshan —Based on annual data from 2011 to 2020
Authors: Zheng Zhibo , Gao Jingjing , Deng Jianyi , Sun Jiangjie 
Published: July 2021

Abstract
Based on the meteorological data of Baoshan from 2011 to 2020, this paper used SPSS software to fit the climate change characteristics of dominant wind direction and wind force in Baoshan City in recent 10 years. The results show that the wind direction and wind data of Baoshan from 2011 to 2020 are processed. The main wind force is light wind, accounting for 72.7%. The wind force of 5-6 occurred during February 11-13, 2012 and March 10, 2012. The main wind direction was non-continuous wind direction, accounting for 69.2%. The ARIMA(3,0,1) model in time series analysis theory was used to fit the wind data, and the validity was good.
Image encryption based on Kronecker inner product over finite fields and adversarial neural network
Authors: Zou Shengliang , Xia Weixia , Zhu Gailin , Liang Yaru , Wu Jianhua 
Published: July 2021

Abstract
An image encryption algorithm based on Kronecker inner product matrix over the finite field and adversarial neural network (ANN) is designed. The Kronecker inner product matrix transform and the ANN fulfil the tasks of confusion and diffusion simultaneously. In addition, the look-up table method is used to complete the addition and multiplication operations over GF(2
B
) finite fields, which can effectively improve the finite field computation speed while retaining its performance of non rounding errors. At the same time, relying on the secure hash function SHA-256 of the plain image to control the Logistic-Sine map greatly improves the diffusion and security of the encryption system. The simulation results verify that the proposed algorithm not only has high security and sufficient sensitivity, but also has a good resistance to various common attacks.
Pre-training and multi-task training for federated keyword extraction
Authors: Guo Lingqi , Sun Haifeng , Shi Zhizhong , Lei Tao 
Published: July 2021

Abstract
The generalization ability of supervised model is relatively weak in keyword extraction technology. In order to effectively improve the robustness and accuracy of the model, the key to overcome this problem is collect more data for training process. However, the text as an privacy information, it is harder and harder to collect. To solve this problem, we apply federal learning to use user privacy data locally to improve the keyword extraction performance. In order to integrate the unlabeled user utterances to the semantic parsing model, we proposed a Pre-training and multi-task based federated keyword extraction model. The user models learn local information via unsupervised setting and the core model learns the supervised setting.
Network estimation of multi-dimensional binary variables with application to divorce data
Authors: Yang Yihe , Luo Renwen , Guo Bing , Luo Yingting , Pan Jianxin 
Published: July 2021

AbstractThe cross-integration of statistics with social and scientific applications is one of the most popular topics in the past decade. Motivated by divorce data collected from the rural areas of Sichuan Province, China, we propose a new method to estimate the network of multiple binary variables, which specifies the dependence structures of multiple binary variables through the Gaussian copula model. Method of moments is employed to estimate the latent correlation matrix of the multiple binary variables. Alternating direction method of multipliers algorithm is then used to estimate the corresponding latent Gaussian network from the empirical latent correlation matrix. This method modifies the traditional estimation of latent Gaussian network from the perspectives of computational efficiency and positive definite guarantee. Analysis of the divorce data is conducted for illustration.
Improvement of the population competition model
Authors: Chen Bowen 
Published: July 2021

Abstract
Classic population competition model with fixed parameters can only be used under the condition of constant living environment, which is impossible in real life. So it has little practical significance in some cases. In this paper, the model will be improved so that it can be used in a changeable living environment. The objective is to establish the relationship between model parameters and independent variables of external conditions with multivariate regression. Growth curves of populations competing with each other are obtained by piecewise prediction. The data used in the regression are obtained by doing experiments. This paper will take wood rot fungus as an example to explain how to establish the relationship by doing experiments, and apply the new model and the classic one with artificial simulation data, so that two groups of predicted population competition curves are obtained. It has been found that the new model can more accurately describe population competition in the case of severe fluctuations in external environment, while the classic model has obvious errors. Finally, this paper briefly describes other advantages of the new model.
Forecasting Thailand inbound tourist flow association for tourism demand
Authors: Jiang Danhua , Liu Jianxu , Sirisrisakulchai Jirakom , Sriboonchitta Songsak 
Published: July 2021

Abstract
The purpose of this paper is to study the tourism demand of Thailand from six major source countries (CN, JP, KO, MAS, SG and LA) in two regions of Asia (East Asia and Southeast Asia). The data is from 1997q1 to 2020q1, which can also provide some advice for the recovery of Thailand tourism post COVID-19. Compared with previous studies, we consider the dependence of tourist flow in the same region. Precisely, we estimated the impact of tourism flows between pairwise countries in each region. This also provides a complement to the subsequent research on the structure of tourism dependence for tourism demand of Thailand. The Copula-based approaches are increasingly being used for tourism demand, we apply the copula-ARDL (ECM) framework to forecast tourist arrivals from two regions. Using the characteristics of correlation matrix in the trivariate Gaussian copula model, we have innovatively performed unconstrained parametric optimization of these two models to ensure the accuracy of the forecasting.
A comparative analysis on the import and export trade patterns of China’s mechanical and electrical products
Authors: Hong Yu , Qu Bingbing , Wang Yuan , Liu Ting 
Published: July 2021

Abstract
This study uses annual data from 1985 to 2019 to analyze the export and import trade patterns of mechanical and electrical products of China. We employ H-index, or the difference between net export capability and symmetric revealed comparative advantage, to assess the trade policies in exports and imports. The results reveal that China has comparative advantage in the imports, and has had comparative disadvantage in the exports before 1999. In recent years, the policy of trade protectionism has been adopted, which promotes exports in terms of exports and restricts imports in terms of imports.
The linkage between tourism development and quality of life: A Copula-based Seemingly Unrelated Regression (SUR) model
Authors: Xue Yuting , Liu Jianxu , Piboonrungroj Pairach , Buranasiri Benjenop , Sriboonchitta Songsak 
Published: July 2021

Abstract
This paper investigates relationships between international tourist arrivals to China and local residents’ quality of life (QOL). We employed Seemingly Unrelated Regression (SUR) model based on the Gaussian Copula approach. Data on international tourist arrivals from Japan, South Korea, and Russia to China during 1994 and 2018 were employed in the model. Findings show direct impacts of inbound tourism on resident’s QOL. Moreover, result reveals an intrinsically reciprocal linkage between national economic growth and residents’ QOL across origins of tourists. Novel contributions of this paper include the robust and objective approach to estimate relationship between international tourism and QOL of local residents.
Comparison of photon-pair generation rate between the sideband and fundamental modes of spontaneous four-wave mixing
Authors: Lee Dongjin , Park Kyungdeuk , Shin Heedeuk 
Published: July 2021

Abstract
Spontaneous four-wave mixing (SpFWM) in fiber optics has been investigated due to its high photon-pair generation rate and negligible connection loss to fiber optic systems. Photon pairs generated in the fundamental or sideband modes satisfy SpFWM’s phase matching condition, and the pair-generation efficiency of both modes has been considered nearly identical. Here, we directly compare the pair-generation efficiency of the fundamental and sideband modes. Dispersion in optical fiber varies unevenly, and SpFWM in the sideband mode is more sensitive to the medium’s dispersion properties than in the fundamental mode, inducing lower pair-generation efficiency. These strong non-uniformity effects in the sideband mode will affect the photon-pair generation and four-wave mixing based quantum and nonlinear applications.
Tribocorrosion investigation of 316L stainless steel: the synergistic effect between chloride ion and sulfate ion
Authors: Tan Liwen , Wang Zhongwei , Ma Yanlong , Yan Yu , Qiao Lijie 
Published: July 2021

Abstract
Tribocorrosion is a failure phenomenon which involves synergistic effect of electrochemical corrosion and mechanical wear. It usually results into early failure of mechanical components than simple wear and corrosion. Chloride (Cl−) and sulfate ions

SO

4

2
−

are often found together in corrosive media. In this study, the synergistic effect of Cl− and

SO

4

2
−

on tribocorrosion of 316L stainless steel was studied by changing the ratio of

SO

4

2
−

/Cl− in corrosive solution from 0.31 M : 0 to 0 : 0.62 M. The stainless steel was worn against with a ZrO2 sphere. The coefficient of friction (COF), material loss volume, surface micro-topographies and surface chemical composition in different solutions were compared to explore the synergism between

SO

4

2
−

and Cl−. The results indicated that the mix of Cl− and

SO

4

2
−

reduced material loss volume by a quarter when compared with that in pure Na2SO4 or NaCl solution. More than half of material loss was caused by the synergism between wear and corrosion in mixing solutions. The synergistic effect between

SO

4

2
−

and Cl− could promote the transmission of metal into oxides. This had two effects on tribocorrosion. First, the existence of oxides would cause abrasion which accelerated wear-affected corrosion and enhanced mechanical wear (corrosion-affected wear). On the other side, the transmission of metal into oxides benefited for the formation of tribo-film. The flexible stainless steel needed to coordinate deformation with the tribo-film which had relatively low deformability. This aggravated deformation of stainless steel and promoted surface work-hardening effect. It was helpful for stainless steel to resist wear, thus, the corrosion-affected wear was decreased.
Temporal characterization of two-octave infrared pulses by frequency resolved optical switching
Authors: Leblanc Adrien , Longa Adrien , Kumar Mayank , Laramée Antoine , Dansereau Charles , Ibrahim Heide , Lassonde Philippe , Légaré François 
Published: July 2021

Abstract
We present the temporal characterization of infrared pulses with spectra extending from 0.55 to 2.5 μm by using the frequency resolved optical switching (FROSt) technique. The pulses are obtained by broadening femtosecond pulses at 1.75 μm central wavelength in a two-stage hollow core fiber setup. This work demonstrates the capability of the FROSt technique to temporally characterize pulses with ultra-broadband spectra. Being free of phase-matching constraints, it enables the characterization of pulses with very low energy at the limit of the detection threshold and with arbitrary long pulse duration. This strength of the FROSt technique is illustrated by the characterization of supercontinua pulses whose spectra span over two octaves and with only 150 nJ energy that is spread temporally over almost 40 ps. The FROSt capabilities provide a versatile tool for the characterization of sub-cycle pulses and to study nonlinear processes such as supercontinuum generation.
2021 roadmap for sodium-ion batteries
Authors: Tapia-Ruiz Nuria , Armstrong A Robert , Alptekin Hande , Amores Marco A , Au Heather , Barker Jerry , Boston Rebecca , Brant William R , Brittain Jake M , Chen Yue , Chhowalla Manish , Choi Yong-Seok , Costa Sara I R , Crespo Ribadeneyra Maria , Cussen Serena A , Cussen Edmund J , David William I F , Desai Aamod V , Dickson Stewart A M , Eweka Emmanuel I , Forero-Saboya Juan D , Grey Clare P , Griffin John M , Gross Peter , Hua Xiao , Irvine John T S , Johansson Patrik , Jones Martin O , Karlsmo Martin , Kendrick Emma , Kim Eunjeong , Kolosov Oleg V , Li Zhuangnan , Mertens Stijn F L , Mogensen Ronnie , Monconduit Laure , Morris Russell E , Naylor Andrew J , Nikman Shahin , O’Keefe Christopher A , Ould Darren M C , Palgrave R G , Poizot Philippe , Ponrouch Alexandre , Renault Stéven , Reynolds Emily M , Rudola Ashish , Sayers Ruth , Scanlon David O , Sen S , Seymour Valerie R , Silván Begoña , Sougrati Moulay Tahar , Stievano Lorenzo , Stone Grant S , Thomas Chris I , Titirici Maria-Magdalena , Tong Jincheng , Wood Thomas J , Wright Dominic S , Younesi Reza 
Published: July 2021

Abstract
Increasing concerns regarding the sustainability of lithium sources, due to their limited availability and consequent expected price increase, have raised awareness of the importance of developing alternative energy-storage candidates that can sustain the ever-growing energy demand. Furthermore, limitations on the availability of the transition metals used in the manufacturing of cathode materials, together with questionable mining practices, are driving development towards more sustainable elements. Given the uniformly high abundance and cost-effectiveness of sodium, as well as its very suitable redox potential (close to that of lithium), sodium-ion battery technology offers tremendous potential to be a counterpart to lithium-ion batteries (LIBs) in different application scenarios, such as stationary energy storage and low-cost vehicles. This potential is reflected by the major investments that are being made by industry in a wide variety of markets and in diverse material combinations. Despite the associated advantages of being a drop-in replacement for LIBs, there are remarkable differences in the physicochemical properties between sodium and lithium that give rise to different behaviours, for example, different coordination preferences in compounds, desolvation energies, or solubility of the solid–electrolyte interphase inorganic salt components. This demands a more detailed study of the underlying physical and chemical processes occurring in sodium-ion batteries and allows great scope for groundbreaking advances in the field, from lab-scale to scale-up. This roadmap provides an extensive review by experts in academia and industry of the current state of the art in 2021 and the different research directions and strategies currently underway to improve the performance of sodium-ion batteries. The aim is to provide an opinion with respect to the current challenges and opportunities, from the fundamental properties to the practical applications of this technology.
A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes
Authors: VanOeffelen Margo , Nguyen Marcus , Aytan-Aktug Derya , Brettin Thomas , Dietrich Emily M , Kenyon Ronald W , Machi Dustin , Mao Chunhong , Olson Robert , Pusch Gordon D , Shukla Maulik , Stevens Rick , Vonstein Veronika , Warren Andrew S , Wattam Alice R , Yoo Hyunseung , Davis James J 
Published: July 2021

Abstract
Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. We demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low. This AMR metadata collection is freely available and maintained on the Bacterial and Viral Bioinformatics Center (BV-BRC) FTP site ftp://ftp.bvbrc.org/RELEASE_NOTES/PATRIC_genomes_AMR.txt.
RefRGim: an intelligent reference panel reconstruction method for genotype imputation with convolutional neural networks
Authors: Shi Shuo , Qian Qiheng , Yu Shuhuan , Wang Qi , Wang Jinyue , Zeng Jingyao , Du Zhenglin , Xiao Jingfa 
Published: July 2021

Abstract
Genotype imputation is a statistical method for estimating missing genotypes from a denser haplotype reference panel. Existing methods usually performed well on common variants, but they may not be ideal for low-frequency and rare variants. Previous studies showed that the population similarity between study and reference panels is one of the key factors influencing the imputation accuracy. Here, we developed an imputation reference panel reconstruction method (RefRGim) using convolutional neural networks (CNNs), which can generate a study-specified reference panel for each input data based on the genetic similarity of individuals from current study and references. The CNNs were pretrained with single nucleotide polymorphism data from the 1000 Genomes Project. Our evaluations showed that genotype imputation with RefRGim can achieve higher accuracies than original reference panel, especially for low-frequency and rare variants. RefRGim will serve as an efficient reference panel reconstruction method for genotype imputation. RefRGim is freely available via GitHub: https://github.com/shishuo16/RefRGim
GdClean: removal of Gadolinium contamination in mass cytometry data
Authors: Liu Junwei , Liu Lulu , Qu Saisi , Zhang Tongtong , Wang Danyang , Ji Qinghua , Wang Tian , Shi Hongyu , Song Kaichen , Fang Weijia , Chen Wei , Yin Weiwei 
Published: July 2021

Abstract

Motivation
Mass cytometry (Cytometry by Time-Of-Flight, CyTOF) is a single-cell technology that is able to quantify multiplex biomarker expressions and is commonly used in basic life science and translational research. However, the widely used Gadolinium (Gd)-based contrast agents (GBCAs) in magnetic resonance imaging (MRI) scanning in clinical practice can lead to signal contamination on the Gd channels in the CyTOF analysis. This Gd contamination greatly affects the characterization of the real signal from Gd-isotope-conjugated antibodies, severely impairing the CyTOF data quality and ruining downstream single-cell data interpretation.

Results
We first in-depth characterized the signals of Gd isotopes from a control sample that was not stained with Gd-labeled antibodies but was contaminated by Gd isotopes from GBCAs, and revealed the collinear intensity relationship across Gd contamination signals. We also found that the intensity ratios of detected Gd contamination signals to the reference Gd signal were highly correlated with the natural abundance ratios of corresponding Gd isotopes. We then developed a computational method named by GdClean to remove the Gd contamination signal at the single-cell level in the CyTOF data. We further demonstrated that the GdClean effectively cleaned up the Gd contamination signal while preserving the real Gd-labeled antibodies signal in Gd channels. All of these shed lights on the promising applications of the GdClean method in preprocessing CyTOF datasets for revealing the true single-cell information.

Availability and implementation
The R package GdClean is available on GitHub at https://github.com/JunweiLiu0208/GdClean.

Supplementary information
Supplementary data are available at Bioinformatics online.