bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of dispersity of reinforcing polymer to the polymer-fiber composite materials’ rigidity
Authors: Kornilova N L , Koksharov S A , Shammut U A , Radchenko O V , Nikiforova E N 
Published: September 2020

Abstract
This research aims at validation of the technological approaches to the provision of penetrating the polymer binder into the structure of the filament carrier in order to construct a developed interfacial layer in the form of molecular brushes. Brush “bristles”, enshrined by the outer end in the layer of the copolymer binder, can give elastic properties to the composite material obtained by duplicating the shell material with reinforced adhesive interlining materials.
As a large part of the interlining materials range comprises a mixture of polyester fiber with cotton or viscose, the problem of accessibility of textile liner web for reinforcing polymer is originally considered in relation to the cellulosic component, which has a developed system of pore spaces.
This work defines the technical possibility of regulating the elastic-deformation properties of the fused panels of garment by changing the degree of reinforcing polymer (RP) dispersion fineness, providing different terms for penetration into the structure of fiber material. To change the capacity of the RP to penetrate into the fiber structure a method of ultra-dispergation was used by the mechanical activation of hydrosols in a colloid mill. There is an experimental prove of the decisive role of the reinforcing polymer penetration into the pore spaces of the cellulose component of the interlining material for the formation the branched comb structure of interfacial layer, which provides a comprehensive improvement in the ability of materials to form the bulk shape of the garment and its preservation while distorting.
Asymmetric CPW Fed Miniaturized dual polarized monopole Antenna for WLAN/WiMAX Applications
Authors: Naresh Kumar D. 
Published: September 2020

Abstract
An Asymmetric coplanar waveguide (CPW) Fed Miniaturized dual polarized (linear Polarized and Circularly Polarized) monopole Antenna Implemented. The Inverted-L Strip monopole antenna and the asymmetric ground plane for WLAN/Wi MAX applications are presented. Monopole antenna mainly icludes asymmetric ground plane which are fed with Coplanar Wave inverted L-shape strip and a slit embedded on the ground plane providing an orthogonal phase difference were designed to generate CP radiation. Inverted-L shape strip resonance and matching condition are examined by high-frequency structure simulator (HFSS) and the prototype is designed and measured. The measure simulated results shows that the monopole antenna impedance band-width with at −10 dB of 92.5 %( 3.36-6.66GHz) and a 3-dB axial-ratio bandwidth of 53.9 %( 5.4 -6.39 GHz) could be completed which could absolutely cover the WLAN (5.725 GHz - 5.85 GHz) band. Meanwhile, a linear polarization is also bought which could absolutely cover the WiMAX (3.3 GHz -3.7 GHz) bands. Orthogonal phase difference and average peak gain for lower band 1.9 dB and upper band 2.48 dB have been achieved, respectively.
Construction of the difference problem and error estimation of the approximate solution of the nonlocal problem for the nonlinear equation.
Authors: Aliyev AY , Aliyev AA , Kazimov JK 
Published: September 2020

Abstract
In this paper, we consider a nonlocal problem. It is used in the rectangular area. For this problem, a difference problem is constructed, based on a rectangular grid. The error of theapproximatesolutionsfor a nonlocal problemis estimated. Many applied problems, in particular heat conductivity [1], [2], fluid mechanics [3], the theory of elasticity and shells [4], etc. are reduced to solving nonlocal boundary value problems for elliptical type equations. When solving nonlocal boundaryvalueproblems, nonlocal boundaryconditions complicate the justification of finite difference schemes due to the complexity of matrices obtained from systemsof equation.This complexity is especially evident for numerical methods, fornon-linear equations[5]. Here we consider a nonlocal boundary value problem for a quasi-linear equation. To solve the problem numerically we use the finite difference method. The error estimate of the approximate solution of the nonlocal problem is found.
Step-Up Resonant Converter For Induction Motor Drive Applications
Authors: Chandran Lekha , Manogna B , Sridhar P 
Published: September 2020

Abstract
A new approach for resonant step-up converter which is connected to hybrid micro grid is discussed in this paper. A micro grid has a local source of supply and loads to function as an electrical network either independently or when connected to a grid.A micro grid can integrate effectively distributed generation sources and renewable generation systems like PV, wind and fuel cell generation systems to the existing distribution system. A hybrid micro grid can be connected to DC and AC grids with the help of power electronic interfaces and manage effective power flow throughout the sub grid. The proposed DC–DC converter can be coupled to a AC-DC micro grid with solar energy and when the system operates in isolated mode battery connected to the DC bus maintain the energy requirement. The key principle of power flow control of these devices helps in increase of system stability. The system is simulated in Matlab/Simulink.
Spatial patterning of nanofibrous collagen scaffolds modulates fibroblast morphology
Authors: Suter Naiana , Stebel Sophie , Rianna Carmela , Radmacher Manfred , Brüggemann Dorothea 
Published: September 2020

Abstract
Current knowledge about cell-biomaterial interactions is often based on two-dimensional (2D) cell culture systems like protein-coated glass slides. However, such smooth surfaces cannot mimic the nanofibrous environment of the native extracellular matrix (ECM). It is therefore a major challenge to transfer the results from 2D surfaces to 3D protein scaffolds with biomimetic nanofiber architecture. To understand the influence of different protein topographies on the cell response we introduce a new process to fabricate binary collagen scaffolds of variable thickness with spatially controlled regions of nanofibrous and smooth topography. We used pH-induced self-assembly to prepare collagen nanofibers with diameters between 130 and 150 nm on glass surfaces, which were partly covered with a polymer mask. After cross-linking with glutaraldehyde, smooth collagen films were prepared on the remaining glass regions. Atomic force microscopy revealed a much lower surface roughness of smooth collagen compared to nanofibers. Subsequently, we studied the viability, morphology and migration of 3T3 fibroblasts on both collagen topographies. We found small, elongated fibroblasts with few, long filopodia on collagen nanofibers whereas large, flat fibroblasts with many short filopodia were observed on smooth collagen. Actin stress fibers on collagen nanofibers were substantially reduced in comparison to smooth collagen. Live cell tracking revealed that fibroblasts on thin nanofibrous collagen migrated faster than on smooth collagen. In summary, binary collagen scaffolds enabled us for the first time to study cell responses to topographical cues on a single protein scaffold. In future, it will be intriguing to transfer our patterning process to other proteins to study fundamental principles of topography-dependent cell recognition processes.
The 2021 quantum materials roadmap
Authors: Giustino Feliciano , Lee Jin Hong , Trier Felix , Bibes Manuel , Winter Stephen M , Valentí Roser , Son Young-Woo , Taillefer Louis , Heil Christoph , Figueroa Adriana I , Plaçais Bernard , Wu QuanSheng , Yazyev Oleg V , Bakkers Erik P A M , Nygård Jesper , Forn-Díaz Pol , De Franceschi Silvano , McIver J W , Torres L E F Foa , Low Tony , Kumar Anshuman , Galceran Regina , Valenzuela Sergio O , Costache Marius V , Manchon Aurélien , Kim Eun-Ah , Schleder Gabriel R , Fazzio Adalberto , Roche Stephan 
Published: September 2020

AbstractIn recent years, the notion of ‘Quantum Materials’ has emerged as a powerful unifying concept across diverse fields of science and engineering, from condensed-matter and coldatom physics to materials science and quantum computing. Beyond traditional quantum materials such as unconventional superconductors, heavy fermions, and multiferroics, the field has significantly expanded to encompass topological quantum matter, two-dimensional materials and their van der Waals heterostructures, Moiré materials, Floquet time crystals, as well as materials and devices for quantum computation with Majorana fermions. In this Roadmap collection we aim to capture a snapshot of the most recent developments in the field, and to identify outstanding challenges and emerging opportunities. The format of the Roadmap, whereby experts in each discipline share their viewpoint and articulate their vision for quantum materials, reflects the dynamic and multifaceted nature of this research area, and is meant to encourage exchanges and discussions across traditional disciplinary boundaries. It is our hope that this collective vision will contribute to sparking new fascinating questions and activities at the intersection of materials science, condensed matter physics, device engineering, and quantum information, and to shaping a clearer landscape of quantum materials science as a new frontier of interdisciplinary scientific inquiry. We stress that this article is not meant to be a fully comprehensive review but rather an up-to-date snapshot of different areas of research on quantum materials with a minimal number of references focusing on the latest developments.
Effects of magnetite and titania nanoparticles on properties of transformer insulating oil
Authors: Pillai S Savitha , Aarathy A R , Gopinath Dinesh , Aryanandiny B , Sankar Binu 
Published: September 2020

Abstract
Transformer oil-based nanofluids have become popular research topic due to their enhanced dielectric and thermal properties. Considering the sustainability aspects of extending the life of transformer oil, it is imperative to conduct research on the effect of transformer oil with nanofillers. In the present work, the influence of conducting magnetite (Fe3O4), semiconducting titania (TiO2) nanoparticles and combination of Fe3O4 and TiO2 nanoparticles (multi-nanoparticle) on AC breakdown voltage are investigated for various concentrations. Nanofluid prepared using multi-nanoparticle shows enhanced AC breakdown voltage (BDV) of transformer oil compared with unfilled oil. Enhancement in BDV of 22% is observed with combination of 0.0025 wt% Fe3O4 and 0.0075 wt% TiO2. In addition, the effect of titania nanoparticles dispersed into service-aged transformer oil with a weight percentage of 0.01% is investigated. Comparative study of breakdown strength and viscosity of nanofluid with unfilled oil is performed. Service-aged oil sample shows increased BDV of 15% with TiO2 nanoparticles. The degradation in service-aged transformer oil is analyzed using UV–vis and Fourier Transform Infrared (FTIR) spectroscopy. The characteristics of oil samples are analyzed using fluorescence spectroscopy.
Knockoff boosted tree for model-free variable selection
Authors: Jiang Tao , Li Yuanyuan , Motsinger-Reif Alison A 
Published: September 2020

AbstractMotivationThe recently proposed knockoff filter is a general framework for controlling the false discovery rate (FDR) when performing variable selection. This powerful new approach generates a ‘knockoff’ of each variable tested for exact FDR control. Imitation variables that mimic the correlation structure found within the original variables serve as negative controls for statistical inference. Current applications of knockoff methods use linear regression models and conduct variable selection only for variables existing in model functions. Here, we extend the use of knockoffs for machine learning with boosted trees, which are successful and widely used in problems where no prior knowledge of model function is required. However, currently available importance scores in tree models are insufficient for variable selection with FDR control.ResultsWe propose a novel strategy for conducting variable selection without prior model topology knowledge using the knockoff method with boosted tree models. We extend the current knockoff method to model-free variable selection through the use of tree-based models. Additionally, we propose and evaluate two new sampling methods for generating knockoffs, namely the sparse covariance and principal component knockoff methods. We test and compare these methods with the original knockoff method regarding their ability to control type I errors and power. In simulation tests, we compare the properties and performance of importance test statistics of tree models. The results include different combinations of knockoffs and importance test statistics. We consider scenarios that include main-effect, interaction, exponential and second-order models while assuming the true model structures are unknown. We apply our algorithm for tumor purity estimation and tumor classification using Cancer Genome Atlas (TCGA) gene expression data. Our results show improved discrimination between difficult-to-discriminate cancer types.Availability and implementationThe proposed algorithm is included in the KOBT package, which is available at https://cran.r-project.org/web/packages/KOBT/index.html.Supplementary informationSupplementary data are available at Bioinformatics online.
FBA reveals guanylate kinase as a potential target for antiviral therapies against SARS-CoV-2
Authors: Renz Alina , Widerspick Lina , Dräger Andreas 
Published: September 2020

Abstract

Motivation
The novel coronavirus (SARS-CoV-2) currently spreads worldwide, causing the disease COVID-19. The number of infections increases daily, without any approved antiviral therapy. The recently released viral nucleotide sequence enables the identification of therapeutic targets, e.g. by analyzing integrated human-virus metabolic models. Investigations of changed metabolic processes after virus infections and the effect of knock-outs on the host and the virus can reveal new potential targets.

Results
We generated an integrated host–virus genome-scale metabolic model of human alveolar macrophages and SARS-CoV-2. Analyses of stoichiometric and metabolic changes between uninfected and infected host cells using flux balance analysis (FBA) highlighted the different requirements of host and virus. Consequently, alterations in the metabolism can have different effects on host and virus, leading to potential antiviral targets. One of these potential targets is guanylate kinase (GK1). In FBA analyses, the knock-out of the GK1 decreased the growth of the virus to zero, while not affecting the host. As GK1 inhibitors are described in the literature, its potential therapeutic effect for SARS-CoV-2 infections needs to be verified in in-vitro experiments.

Availability and implementation
The computational model is accessible at https://identifiers.org/biomodels.db/MODEL2003020001.
Fold recognition by scoring protein maps using the congruence coefficient
Authors: Di Lena Pietro , Baldi Pierre 
Published: September 2020

Abstract

Motivation
Protein fold recognition is a key step for template-based modeling approaches to protein structure prediction. Although closely related folds can be easily identified by sequence homology search in sequence databases, fold recognition is notoriously more difficult when it involves the identification of distantly related homologs. Recent progress in residue–residue contact and distance prediction opens up the possibility of improving fold recognition by using structural information contained in predicted distance and contact maps.

Results
Here we propose to use the congruence coefficient as a metric of similarity between maps. We prove that this metric has several interesting mathematical properties which allow one to compute in polynomial time its exact mean and variance over all possible (exponentially many) alignments between two symmetric matrices, and assess the statistical significance of similarity between aligned maps. We perform fold recognition tests by recovering predicted target contact/distance maps from the two most recent Critical Assessment of Structure Prediction editions and over 27 000 non-homologous structural templates from the ECOD database. On this large benchmark, we compare fold recognition performances of different alignment tools with their own similarity scores against those obtained using the congruence coefficient. We show that the congruence coefficient overall improves fold recognition over other methods, proving its effectiveness as a general similarity metric for protein map comparison.

Availability and implementation
The congruence coefficient software CCpro is available as part of the SCRATCH suite at: http://scratch.proteomics.ics.uci.edu/.

Supplementary information
Supplementary data are available at Bioinformatics online.
A potential role of fatty acid binding protein 4 in the pathophysiology of autism spectrum disorder
Authors: Maekawa Motoko , Ohnishi Tetsuo , Toyoshima Manabu , Shimamoto-Mitsuyama Chie , Hamazaki Kei , Balan Shabeesh , Wada Yuina , Esaki Kayoko , Takagai Shu , Tsuchiya Kenji J , Nakamura Kazuhiko , Iwata Yasuhide , Nara Takahiro , Iwayama Yoshimi , Toyota Tomoko , Nozaki Yayoi , Ohba Hisako , Watanabe Akiko , Hisano Yasuko , Matsuoka Shigeru , Tsujii Masatsugu , Mori Norio , Matsuzaki Hideo , Yoshikawa Takeo 
Published: September 2020

Abstract
Autism spectrum disorder is a neurodevelopmental disorder characterized by difficulties in social communication and interaction, as well as repetitive and characteristic patterns of behaviour. Although the pathogenesis of autism spectrum disorder is unknown, being overweight or obesity during infancy and low weight at birth are known as risks, suggesting a metabolic aspect. In this study, we investigated adipose tissue development as a pathophysiological factor of autism spectrum disorder by examining the serum levels of adipokines and other metabolic markers in autism spectrum disorder children (n = 123) and typically developing children (n = 92) at 4–12 years of age. Among multiple measures exhibiting age-dependent trajectories, the leptin levels displayed different trajectory patterns between autism spectrum disorder and typically developing children, supporting an adipose tissue-dependent mechanism of autism spectrum disorder. Of particular interest, the levels of fatty acid binding protein 4 (FABP4) were significantly lower in autism spectrum disorder children than in typically developing subjects, at preschool age (4–6 years old: n = 21 for autism spectrum disorder and n = 26 for typically developing). The receiver operating characteristic curve analysis discriminated autism spectrum disorder children from typically developing children with a sensitivity of 94.4% and a specificity of 75.0%. We re-sequenced the exons of the FABP4 gene in a Japanese cohort comprising 659 autism spectrum disorder and 1000 control samples, and identified two rare functional variants in the autism spectrum disorder group. The Trp98Stop, one of the two variants, was transmitted to the proband from his mother with a history of depression. The disruption of the Fabp4 gene in mice evoked autism spectrum disorder-like behavioural phenotypes and increased spine density on apical dendrites of pyramidal neurons, which has been observed in the postmortem brains of autism spectrum disorder subjects. The Fabp4 knockout mice had an altered fatty acid composition in the cortex. Collectively, these results suggest that an ‘adipo-brain axis’ may underlie the pathophysiology of autism spectrum disorder, with FABP4 as a potential molecule for use as a biomarker.
Walking the financialized city: confronting capitalist urbanization through mobile popular education
Authors: Silver Jonathan , Fields Desiree , Goulding Rich , Rose Isaac , Donnachie Siobhan 
Published: September 2020

Abstract
How do communities understand the highly abstract process of housing financialization? In this paper we argue that walking tours offer the capacity to develop new forms of mobile, public education to learn about the capitalist urbanization process, especially as the financialization of housing accelerates. Based on walking the city of Manchester we show that this type of learning may improve public literacy concerning the opaque and extended ways in which housing in central areas has increasingly been shaped by new types of real estate finance. Although many people in Manchester have understood the outline of these dramatic transformations, and could connect the new skyscrapers to their struggles for everyday survival, there remained a gap in detailed literacy of the actors, finances and dynamics that had changed the city so quickly. We contextualize the rapidly changing global landscape of housing since the global financial crisis of 2008 before showing how these transformations have reshaped housing in Manchester. We then describe the motivations for developing the tour, and the details of the walk itself. We conclude by suggesting that the walking tour offers new types of possibility in necessary learning and subsequent action to address capitalist urbanization.
CircR2Cancer: a manually curated database of associations between circRNAs and cancers
Authors: Lan Wei , Zhu Mingrui , Chen Qingfeng , Chen Baoshan , Liu Jin , Li Min , Chen Yi-Ping Phoebe 
Published: September 2020

AbstractAccumulating evidences have shown that the deregulation of circRNA has close association with many human cancers. However, these experimental verified circRNA–cancer associations are not collected in any database. Here, we develop a manually curated database (circR2Cancer) that provides experimentally supported associations between circRNAs and cancers. The current version of the circR2Cancer contains 1439 associations between 1135 circRNAs and 82 cancers by extracting data from existing literatures and databases. In addition, circR2Cancer contains the information of cancer exacted from Disease Ontology and basic biological information of circRNAs from circBase. At the same time, circR2Cancer provides a simple and friendly interface for users to conveniently browse, search and download the data. It will be a useful and valuable resource for researchers to understanding the regulation mechanism of circRNA in cancers.Database URLhttp://www.biobdlab.cn:8000
CRISPR sequences are sometimes erroneously translated and can contaminate public databases with spurious proteins containing spaced repeats
Authors: Rubio Alejandro , Mier Pablo , Andrade-Navarro Miguel A , Garzón Andrés , Jiménez Juan , Pérez-Pulido Antonio J 
Published: September 2020

AbstractThe genomics era is resulting in the generation of a plethora of biological sequences that are usually stored in public databases. There are many computational tools that facilitate the annotation of these sequences, but sometimes they produce mistakes that enter the databases and can be propagated when erroneous data are used for secondary analyses, such as gene prediction or homology searching. While developing a computational gene finder based on protein-coding sequences, we discovered that the reference UniProtKB protein database is contaminated with some spurious sequences translated from DNA containing clustered regularly interspaced short palindromic repeats. We therefore encourage developers of prokaryotic computational gene finders and protein database curators to consider this source of error.