bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assigning Secondary Structure in Proteins using AI
Authors: Antony Jisna Vellara , Madhu Prayagh , Balakrishnan Jayaraj Pottekkattuvalappil 
Published: February 2021

AbstractKnowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the ’80s various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by Machine Learning, have been employed in protein structure assignment. However, the assignment process becomes challenging when missing atoms are present in protein files. Our model develops a multi-class classifier program named DLFSA for assigning protein Secondary Structure Elements(SSE) using Convolutional Neural Networks(CNN). A fast and efficient GPU based parallel procedure extracts fragments from protein files. The model implemented in this work is trained with a subset of protein fragments and achieves 88.1% and 82.5% train and test accuracy, respectively. Our model uses only Cαcoordinates for secondary structure assignments. The model is successfully tested on a few full-length proteins also. Results from the fragment-based studies demonstrate the feasibility of applying deep learning solutions for structure assignment problems.
System Analysis of the Sequencing Quality of Human Whole Exome Samples on Bgi Ngs Platform
Authors: Belova Vera , Pavlova Anna , Afasizhev Robert , Moskalenko Viktoria , Korzhanova Margarita , Cheranev Valery , Krivoy Andrey , Nikashin Boris , Bulusheva Irina , Rebrikov Denis , Korostin Dmitriy 
Published: February 2021

AbstractHuman whole exome sequencing (WES) is now the standard for most medical genetics applications worldwide. The leaders are manufacturers of enrichment kits that base their protocols on a hybridization approach using cRNA or cDNA biotinylated samples specific to regions of interest in the genome. Recently, platforms from the Chinese company MGI Tech have been successfully promoted in the markets of many countries in Europe and Asia. There is no longer any question about their reliability and the quality of the data obtained. However, very few task-specific kits for WES, in particular, are presented for these sequencers. We have developed our solution for library pre-capture pooling and exome enrichment using Agilent probes. In this work, we demonstrate on a set of standard benchmark samples from the Platinum Genome Collection that our protocol, called “RSMU_exome”, is superior to the kit from MGI Tech in qualitative and quantitative terms. It allows detecting more SNVs and CNVs with superior sensitivity and specificity values, generates fewer PCR duplicates, allows more samples to be pooled in a single enrichment, and requires less raw data to produce results comparable to the MGI Tech solution. Also, our protocol is significantly cheaper than the kit from the Chinese manufacturer.
INCORPORATING A DYNAMIC GENE-BASED PROCESS MODULE INTO A CROP SIMULATION MODEL
Authors: Oliveira Fabio A.A. , Jones James W. , Pavan Willingthon , Bhakta Mehul , Vallejos C. Eduardo , Correll Melanie J. , Boote Kenneth J. , Fernandes José M.C. , Hölbig Carlos A. , Hoogenboom Gerrit 
Published: February 2021

AbstractDynamic crop simulation models are tools that predict plant phenotype grown in specific environments for genotypes using genotype-specific parameters (GSPs), often referred to as “genetic coefficients.” These GSPs are estimated using phenotypic observations and may not represent “true” genetic information. Instead, estimating GSPs requires experiments to measure phenotypic responses when new cultivars are released. The goal of this study was to evaluate a new approach that incorporates a dynamic gene-based module for simulating time-to-flowering for common bean (Phaseolus vulgarisL.) into an existing dynamic crop model. A multi-environment study conducted in 2011 and 2012 included 187 recombinant inbred lines (RILs) from a bi-parental bean family to measure the effects of quantitative trait loci (QTL), environment (E), and QTL×E interactions across five sites. The dynamic mixed linear model from Vallejos et al. (2020) was modified in this study to create a dynamic module that was then integrated into the CSM-CROPGRO-Drybean model. This new hybrid crop model, with the gene-based flowering module replacing the original flowering component, requires allelic makeup of each genotype being simulated and daily E data. The hybrid model was compared to the original CSM model using the same E data and previously estimated GSPs to simulate time-to-flower. The integrated gene-based module simulated days of first flower agreed closely with observed values (root mean square error of 2.73 days and model efficiency of 0.90) across the five locations and 187 genotypes. The hybrid model with its gene-based module also described most of the G, E and G×E effects on time-to-flower and was able to predict final yield and other outputs simulated by the original CSM. These results provide the first evidence that dynamic crop simulation models can be transformed into gene-based models by replacing an existing process module with a gene-based module for simulating the same process.
Identification of the SHREK family of proteins as broad-spectrum host antiviral factors
Authors: Dabbagh Deemah , He Sijia , Hetrick Brian , Chilin Linda , Andalibi Ali , Wu Yuntao 
Published: February 2021

ABSTRACTMucins and mucin-like molecules are highly glycosylated, high-molecular-weight cell surface proteins that possess a semi-rigid and highly extended extracellular domain. P-selectin glycoprotein ligand-1 (PSGL-1), a mucin-like glycoprotein, has recently been found to restrict HIV-1 infectivity through virion incorporation that sterically hinders virus particle attachment to target cells. Here, we report the identification of a family of antiviral cellular proteins, named the Surface-Hinged, Rigidly-Extended Killer (SHREK) family of virion inactivators (PSGL-1, CD43, TIM-1, CD34, PODXL1, PODXL2, CD164, MUC1, MUC4, and TMEM123), that share similar structural characteristics with PSGL-1. We demonstrate that SHREK proteins block HIV-1 infectivity by inhibiting virus particle attachment to target cells. In addition, we demonstrate that SHREK proteins are broad-spectrum host antiviral factors that block the infection of diverse viruses such as influenza A. Furthermore, we demonstrate that a subset of SHREKs also blocks the infectivity of a hybrid alphavirus-SARS-CoV-2 virus-like particle. These results suggest that SHREK proteins may be a part of host innate immunity against enveloped viruses.
Structure of plant PSI-plastocyanin complex reveals strong hydrophobic interactions
Authors: Caspy Ido , Fadeeva Mariia , Kuhlgert Sebastian , Borovikova-Sheinker Anna , Klaiman Daniel , Masrati Gal , Drepper Friedel , Ben-Tal Nir , Hippler Michael , Nelson Nathan 
Published: February 2021

AbstractPhotosystem I is defined as plastocyanin-ferredoxin oxidoreductase. Taking advantage of genetic engineering, kinetic analyses and cryo-EM, our data provide novel mechanistic insights into binding and electron transfer between PSI and Pc. Structural data at 2.74 Å resolution reveals strong hydrophobic interactions in the plant PSI-Pc ternary complex, leading to exclusion of water molecules from PsaA-PsaB / Pc interface once the PSI-Pc complex forms. Upon oxidation of Pc, a slight tilt of bound oxidized Pc allows water molecules to accommodate the space between Pc and PSI to drive Pc dissociation. Such a scenario is consistent with the six times larger dissociation constant of oxidized as compared to reduced Pc and mechanistically explains how this molecular machine optimized electron transfer for fast turnover.One Sentence SummaryGenetic engineering, kinetics and cryo-EM structural data reveal a mechanism in a major step of oxygenic photosynthesis
Bacterial expression and purification of functional recombinant SARS-CoV-2 spike receptor binding domain
Authors: Prahlad Janani , Struble Lucas R. , Lutz William E. , Wallin Savanna A. , Khurana Surender , Schnaubelt Andy , Broadhurst Mara J. , Bayles Kenneth W. , Borgstahl Gloria E. O. 
Published: February 2021

AbstractThe COVID-19 pandemic caused by SARS-CoV-2 has applied significant pressure on overtaxed healthcare around the world, underscoring the urgent need for rapid diagnosis and treatment. We have developed a bacterial strategy for the expression and purification of the SARS-CoV-2 spike protein receptor binding domain using the CyDisCo system to create and maintain the correct disulfide bonds for protein integrity and functionality. We show that it is possible to quickly and inexpensively produce functional, active antigen in bacteria capable of recognizing and binding to the ACE2 (angiotensin-converting enzyme) receptor as well as antibodies in COVID-19 patient sera.
Unpacking the effects of star architecture projects
Authors: Alaily-Mattar Nadia , Bartmanski Dominik , Dreher Johannes , Koch Michael , Löw Martina , Pape Timothy , Thierstein Alain 
Published: February 2021

PurposeTo explain the process of how star architecture projects generate impact, one must first describe the outputs of such projects and then unpack the wide array of potential effects, which are generated by these outputs. This requires the application of multi-disciplinary research perspectives. Only then can one begin to systematically analyse the long-term impacts. The purpose of this paper is to illustrate how the complexity of such multi-disciplinary research exercise can be managed through the application of a methodological strategy aided by a conceptual impact model.Design/methodology/approachA conceptual impact model is presented, which describes the process of the development of star architecture projects, the various outputs of these projects and the possible effects generated by these outputs. The effects of three case study star architecture projects are discussed.FindingsEmpirical research findings indicate that while the isolation of effects serves the operationalisation of research, the investigation of the impact of star architecture projects on their respective cities must draw on the intertwinement of the fields of urban economy, society and morphology. The paper concludes by arguing for the application of the described methodological strategy as the basis for understanding in which dimensions a star architecture project generates impacts.Practical implicationsThe potential of the proposed impact model for urban analysis when considered as a field of intertwined relations is demonstrated in this article. It helps to reveal how particular local developments change the city significantly in socio-cultural and spatial terms.Originality/valueThe transformative impact of star architecture projects and the role of economic and other effects in this process has hardly been studied, particularly in small and medium-sized cities. This article presents a unique multi-disciplinary research project approached consecutively in the aforementioned fields.
Developing a methodology to create nutritionally balanced meals
Authors: Giazitzi Katerina , Boskou George 
Published: February 2021

PurposeThe purpose of the present study was to develop a methodology for the creation of nutritionally balanced (NB) recipes and meals.Design/methodology/approachNutritional criteria were set for energy, fats, saturated fats, carbohydrates, sugars and salt. A sample of 50 main courses and 29 salads was evaluated and nutritionally reformulated to meet the criteria. One sample t-test, paired sample t-test, Pearson correlation coefficient and linear regression analysis were performed.FindingsThe original main courses and salads did not meet the nutritional criteria for fats and energy. Both original and NB main courses had high mean protein content. The reformulation of recipes caused a significant change on the provided energy (−50.2%), fats (−57.6%), saturated fats (−58.8%), carbohydrates (−24.2%), proteins (−35.6%) and salt (−53.8%) for the salads (p = 0.001). Accordingly, reformulation of recipes caused a significant change on provided energy (−38.4%), fats (−55.2%), saturated fats (−58.3%), proteins (−25.9%) and salt (−50%) for the main courses (p < 0.001). Predictive models (linear regression analysis) for fats (R2 = 0.345), proteins (R2 = 0.876) and carbohydrates (R2 = 0.797) on the NB recipes were performed.Originality/valueThis is the first attempt to improve the nutritional value of cooking recipes, based on specific nutritional criteria. A methodological procedure for the creation of NB meals is proposed. This methodology could be a useful tool for the nutritionists and chefs, which, in a context of cooperation, could create databases and cooking books with NB recipes easily accessed to public and caterers. The recipes that constitute NB meals could guarantee the standardization of the recipes' reformulation, within a certification standard for restaurants.
Digital divide in the major regions of the world and the possibility of convergence
Authors: Inegbedion Henry Egbezien 
Published: February 2021

Purpose
The purpose of this paper is to investigate the nature of the inequalities in the usage of the internet and inequalities in the growth rate in the usage of the internet, and thus ascertain the possibility of convergence of the digital divide between the major regions of the world.

Design/methodology/approach
The design was a longitudinal study of the usage of internet and growth rate in the usage of the internet in the different regions of the world for the period 2009–2019. The quantitative research method was used. Simple percentages and F-test were used in data analysis.

Findings
The usage of internet in Asia and Europe is higher than all the other regions in the world but there is no significant difference in usage between the other regions. The results further showed that some of the digitally disadvantaged regions had higher growth rates in the usage of the internet and these digitally disadvantage states are not disadvantaged in access to smartphones and the emerging 5G technology, thus suggesting the possibility of imminent convergence in access to the internet given the increasing usage of smartphones for the internet subscription.

Research limitations/implications
The focus on internet usage in the major regions of the world without recourse to the variability of the usage and growth rate of internet usage within the regions. The dearth of the empirical literature on quantitative research on the research problem was another constraint. Finally, restriction in available statistics on digital divide constrained the use of 2009–2019 as the periodic scope of the study.

Practical implications
Inclusion of ICT in the school curricula of the component states to acquaint them with information and communication technology (ICT) usage at an early stage, as well as provision of the enabling environment for business to thrive and through a national culture that will encourage businesses to be vibrant, and thus lay a foundation for future convergence.

Social implications
Enhancement in employment opportunities through the increased investment in the ICT facilities and the subsequent reduction in social vices.

Originality/value
Use of secondary data through a longitudinal design to categorically indicate the differences between the different regions of the world in terms of internet usage, as well as the empirical determination of the discrepancies between the growth rates in the access to internet and usage of internet by different regions of the world, especially as regard some of the digitally disadvantaged regions having higher growth rates in the usage of the internet than the perceived digitally advantaged regions.
Artificial neural networks applied for solidified soils data prediction: a bibliometric and systematic review
Authors: Pacheco Vinicius Luiz , Bragagnolo Lucimara , Thomé Antonio 
Published: February 2021

Purpose
The purpose of this article is to analyze the state-of-the art in a systematic way, identifying the main research groups and their related topics. The types of studies found are fundamental for understanding the application of artificial neural networks (ANNs) in cemented soils and the potential for using the technique, as well as the feasibility of extrapolation to new geotechnical or civil and environmental engineering segments.

Design/methodology/approach
This work is characterized as being bibliometric and systematic research of an exploratory perspective of state-of-the-art. It also persuades the qualitative and quantitative data analysis of cemented soil improvement, biocemented or microbially induced calcite precipitation (MICP) soil improvement by prediction/modeling by ANN. This study sought to compile and study the state of the art of the topic which possibilities to have a critical view about the theme. To do so, two main databases were analyzed: Scopus and Web of Science. Systematic review techniques, as well as bibliometric indicators, were implemented.

Findings
This paper connected the network between the achievements of the researches and illustrated the main application of ANNs in soil improvement prediction, specifically on cemented-based soils and biocemented soils (e.g. MICP technique). Also, as a bibliometric and systematic review, this work could achieve the key points in the absence of researches involving soil-ANN, and it provided the understanding of the lack of exploratory studies to be approached in the near future.

Research limitations/implications
Because of the research topic the article suggested other applications of ANNs in geotechnical engineering, such as other tests not related to geomechanical resistance such as unconfined compression test test and triaxial test.

Practical implications
This article systematically and critically presents some interesting points in the direction of future research, such as the non-approach to the use of ANNs in biocementation processes, such as MICP.

Social implications
Regarding the social environment, the paper brings approaches on methods that somehow mitigate the computational use, or elements necessary for geotechnical improvement of the soil, thereby optimizing the same consequently.

Originality/value
Neural networks have been studied for a long time in engineering, but the current computational power has increased the implementation for several engineering applications. Besides that, soil cementation is a widespread technique and its prediction modes often require high computational strength, such parameters can be mitigated with the use of ANNs, because artificial intelligence seeks learning from the implementation of the data set, reducing computational cost and increasing accuracy.
Do different genders' knowledge sharing behaviors drive different innovative behavior? The moderating effect of social capital
Authors: Fatemi Seyedeh Zahra , Sadeghian Samaneh , Ganji S. Fatemeh Ghasempour , Johnson Lester W. 
Published: February 2021

PurposeConsidering the importance of innovation in organizations and the formation of innovative behaviors (IBs) in the life of the organization, the authors study the effect of moderating social capital (SC) and gender in the link between knowledge sharing (KS), including sharing best practices and sharing mistakes with IB.Design/methodology/approachIn this research, a random sampling method was used. A questionnaire was completed by 310 employees working in five prestigious companies in the energy sector located in Mashhad province, Iran.FindingsThe findings of the research indicate the influence of KS on IB. Also, SC moderates the effect of KS on IB. However, the moderating effect of gender was not significant, sharing best practices more likely to lead IB in women. Moreover, the men are more likely to show IB as they share their mistakes in comparison with women.Originality/valueThis research aims to break the black box on the link between employee KS and his/her own innovativeness, which is not frequently investigated. To the authors' best knowledge, there is a lack of deep empirical study that has delved into analyzing the impact of gender-groups and SC on this relation.
Prioritizing factors influencing the selection of a suitable quarantine facility for COVID-19 patients using Pareto-enhanced analytical hierarchy process
Authors: Zeferino Emanuel Fernando Samasseca , Makinde Olasumbo Ayodeji , Mpofu Khumbulani , Ramatsetse Boitumelo Innocent , Daniyan Ilesanmi Afolabi 
Published: February 2021

Purpose
Selection of a suitable location for a quarantine infrastructure represents a complex decision problem, which requires a systematic appraisal of myriads of factors. Quarantine facility in this study is a facility that intends to harbour and treat individuals diagnosed with COVID-19 to prevent the widespread of the virus. COVID-19 is a very contagious pandemic disease, hence, the establishment of critical factors that will embrace the selection of a suitable quarantine facility is of high importance. This paper aims to ascertain the vital few factors that must be considered by decision makers in selecting a suitable quarantine facility.

Design/methodology/approach
The aim of this study was achieved through the numerical assessment of identified quarantine location selection factors using the analytical hierarchy process (AHP) and Pareto techniques. The factors, which influences the selection of a suitable quarantine facility for COVID-19 patients were first identified from the literature followed by the pairwise comparison of the factors and random consistency analyses, as well as the ranking of the alternatives based on facility location experts’ opinions.

Findings
The study revealed that security, skills availability, cost, readiness, proximity to necessary medical facilities and distance to border, with percentage weight scores of 18%, 16.7%, 15.6%, 10.3%, 9.8% and 6.6% were the critical factors that must be considered during the selection of a quarantine facility for COVID-19 patients.

Practical implications
The results of this paper will help the government and decision makers in locating the quarantine sites for people who tested positive for the COVID-19 virus.

Originality/value
The present study focuses on the application of the decision technique to ascertain critical factors that embrace suitable quarantine facility selection. Combination of AHP and Pareto techniques for prioritization of conflicting factors to be considered in selecting the most suitable location for a quarantine facility has not been reported by existing literature.