bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virtual modelling of the crash cushion operation with projected destruction
Authors: Demyanushko I V , Karpov I A , Mikheev P S , Mukhametova A A 
Published: April 2021

Abstract
The article discusses a technique for virtual modeling of the process of deformation and fracture of the structure of a crash cushion, which is used to protect the places of road works, which occurs when a car hits the device during a road accident. The peculiarity of the approach consists in taking into account and modeling the processes of fracture of special energy-absorbing elements used in devices for absorbing impact energy due to the directional destruction of these elements.
Carbon-graphite preparation for impregnation with aluminum alloy
Authors: Yu Miroshkin N , Gulevskii V A , Kidalov N A 
Published: April 2021

Abstract
The possibility of increasing the efficiency of gasostat-free impregnation of porous carbon-graphite materials with aluminum alloys by applying thin high-purity metal alloying coatings by galvanic method to the surface of the pores of a carbon-graphite specimen is studied. It is shown that the preliminary application of such coatings by an electroplating method allows obtaining the effect of alloying with highly pure elements, increases the filling of pores with matrix melt and decreases the impregnation temperature (750°C). This technology makes it possible to obtain high-quality composite materials using simple technological equipment.
The hydroplane body development of design and topological optimization
Authors: Dolunts G V , Maslov L B , Zhmaylo M A 
Published: April 2021

Abstract
This work is devoted to the study of the stress-strain state of the hydroplane body and its topological optimization. During laboratory tests, physical and mechanical properties of materials were identified, which are necessary for use in further calculations to study the stress-strain state of the hydroplane body, followed by reducing its weight, using topological optimization of the structure. The end result is a developed method for manufacturing the hydroplane body using additive technologies.
Application of UHMWPE in energy-absorbing road safety systems
Authors: Gruzdev A S , Nadezhdin V S , Titov O V , Prohanov I S 
Published: April 2021

Abstract
The article considers the possibility of using a polymer material based on ultra-high molecular weight polyethylene (UHMWPE) in energy-absorbing structures of road safety systems. To determine the mechanical and energy absorbing characteristics of the material, bench tests carried out on the material and element of the designed structure in the form of a thin-walled cylinder. The possibility of using UHMWPE in the actual design of the road safety system checked by creating a validated digital twin of the impact attenuator. Based on the simulation results, polymer and metal structures compared.
Optimization of open-hole variable stiffness composite plates under tensile loading using curved continuous fibers
Authors: Malakhov A V 
Published: April 2021

Abstract
This paper describes optimization of variable stiffness composite plates (VSCPs) with open-holes under tensile loading. Curved continuous fibers are used to optimize distributions of fiber orientation and the fiber volume fraction during the optimization for the VSCPs. The modeling of VSCPs is performed by means of fiber trajectories, which are aligned in the direction of maximum principal stress. The progressive failure of the VSCPs is modeled by a material property degradation method, taking into account the variable distributions of material properties to predict the ultimate load. It is demonstrated that the ultimate load for the composite plates is increased using the change in a reinforcement structure and a transition from unidirectional to curvilinear reinforcement of fibers. Thus, application of VSCPs with curved fibers compared with unidirectional composites results in more effective use of composite materials in various fields of industry.
Design issues of energy-absorbing truck mounted attenuators
Authors: Mikheev P S , Karpov I A , Mukhametova A A 
Published: April 2021

Abstract
The work is devoted to the issues of finite element modeling of energy-absorbing truck mounted attenuators (TMA) used on the shadow vehicles in the zones of stationary and mobile road and construction works to protect workers from collisions with vehicles, as well as to reduce the severity of an accident for the driver who collided. Discusses various designs of TMAs, the main problems in design and defines the criteria for the development of structures based on mathematical modeling by the finite element method.
Simulation of wave propagation in a periodic layered elastomer using spectral element method
Authors: Khanazaryan A D , Golub M V , Doroshenko O V , Shpak A N , Fomenko S I 
Published: April 2021

Abstract
The problem of wave propagation in a periodic elastomer is investigated. Dispersion equation for a periodic layered composite made of elastomers is formulated and solved employing the spectral element method. The problem is formulated in a variational form taking into account that stiffness tensor has no symmetry when an elastomer is considered. The results are compared with the same calculations made using the transfer matrix method. The method can be naturally extended to dielectric elastomers and to the three-dimensional case.
The study of the motion of the truck vibration motors by the oscillating of a pendulum of variable length
Authors: Strygin Sergey V , Levin Vladimir D , Loschinin Nikolai V , Kiryushin Ilya N , Parshukov Sergey A , Metik Vladimir V 
Published: April 2021

Abstract
The article provides a solution to the problem, according to the condition of which there is a body - a cart, which must be brought into directional motion by means of a swinging elastic pendulum of variable length, pivotally mounted on it. A variant of creating the initial momentum of the trolley movement due to the movement of the pendulum, made in the form of a spring-loaded load with the possibility of movement along a straight guide when it rotates relative to the pendulum suspension point, is proposed and justified. The mode of movement of the cart-pendulum system is studied when the individual components of the system are gradually released from the connections to provide the initial impulse of the cart movement. The full-turn shape of the trajectory of a spring-loaded pendulum pivotally mounted on a cart is shown. We use numerical analysis methods (numerical integration of systems of nonlinear differential equations) with modeling by means of the Mathcad package.
Overview of possibilities of genometric information systems
Authors: Stepanyan I V , Lednev M Y 
Published: April 2021

Abstract
The actuality of the research is due to the development of methods of matrix genetics and the genometric approach that emerged from it. The article presents the results of combining these developments in a single software package in the form of a genometric information system. The developed information system is implemented in C ++ 14 using the Qt library. The software package implements the parameterization of the following variables: scale parameter, offset relative to the beginning of the sequence, overlap step. The following systems of sub-alphabets are implemented: nucleotide, dinucleotide. Visualization types are implemented: structural, frequency, integral. Visualization spaces are implemented: one-, two-and three-dimensional. In the implementations of the algorithms, methods of parallel computations were applied. The introduction of a new parameter-the overlap step - is presented, which allows obtaining clearer graphic displays. An overview of modern bio-information systems and the main directions of their development is given. Genometric bio-informatics tools play a fundamental role in understanding the modulation mechanisms of biological signals and in proposing new hypotheses.
Effect of recording device parameters on the operation of the sugar beet recognition algorithm in the early stages of growth
Authors: Mirzaev M A , Dyshakov A I 
Published: April 2021

Abstract
This experiment makes it possible to estimate the influence of the distance from the recording device lens to the ground on the recognition algorithm by comparing the area of the recognized part of the plant. The experiments are based on the fact that the main error of the algorithm is to reduce the area of the recognized part of the plant with a significant deterioration of parameters. The study carried out a number of experiments including a gradual change of height from the minimum structurally possible value to the maximum at which there is a significant loss of quality under different lighting conditions ensuring normal operation of the vision algorithm.
Design of mechanisms of a robotic system for rehabilitation of the lower limbs
Authors: Voloshkin A A , Virabyan L G , Mamaev V A , Kholoshevskaya L R 
Published: April 2021

AbstractThe article describes the main stages of developing a robotic system for the rehabilitation of the lower limbs based on the “tripteron” robot. The structure of a robotic system has been designed, consisting of a 3-PRRR parallel mechanism, which provides the angles of rotation of all joints of the patient’s leg required for rehabilitation and a passive orthosis for supporting the limb. At the first stage, the positions of the active mechanism links are determined. The output link of only one kinematic chain, making a translational movement in the vertical direction, will experience a maximum load. A design diagram of this kinematic chain was built, and the reactions of the supports were determined at the second stage. At the third stage, kinematic dependences were obtained, and an engine was selected that would provide the required torque at the required speeds.
Design and strength estimation of composite multi-cavity pressure vessels
Authors: Sklemina O Yu , Tatus’ N A , Polilov A N 
Published: April 2021

Abstract
The article discusses a layer-by-layer method for calculating of composite products, and the “thread analogy” is provided for pressure vessels calculating. Stress fields at the multi-cavity cylindrical and spherical pressure vessels are calculated using FEM. Gas injection system is designed.
The effect of the heat treatment to Co-N-C derived from ZIF-67 on the electrochemical performance of lithium-sulfur battery
Authors: Cui Xiao , Zhang Zheng-Fu , Wang Jin-Song , Wan Run-dong , Guo Yu-Zhong , Dao Juan-Ye , Bao Chong-Jun 
Published: April 2021

Abstract
The composite of porous carbon obtained from MOFs loading sulfur has been regard as promising candidate for lithium-sulfur batteries cathode material due to the large specific surface area, high porosity, diversity of types, and designable structures large specific surface area, high porosity, diversity of types, and designable structures. However, the production processes of MOFs materials play a pivotal role on the lithium-sulfur batteries performance. Herein, the effect of key process parameters such as heat treatment temperature, heat treatment time, and heat treatment atmosphere on the electrochemical performance of lithium-sulfur batteries were systematically studied. The results show that at a heating rate of 5 ℃·min−1, heat preservation at 900 ℃ for 3 h, and treatment with CO2 airflow for 1 h, the composite material has the best electrochemical performance. The first discharge specific capacity of the lithium-sulfur battery reached 1060.32 mAh·g−1, and after 50 cycles it reached 614.29 mAh·g−1. This heat treatment research method based on MOFs-derived materials can be used as a reference for related research in other energy storage and conversion fields.
Deploying the Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the first superfacility platform in China
Authors: Wang Chunpeng , Yu Feng , Liu Yiyang , Li Xiaoyun , Chen Jige , Thiyagalingam Jeyan , Sepe Alessandro 
Published: April 2021

Abstract
With recent technological advances, large-scale experimental facilities generate huge datasets, into the petabyte range, every year, thereby creating the Big Data deluge effect. Data management, including the collection, management, and curation of these large datasets, is a significantly intensive precursor step in relation to the data analysis that underpins scientific investigations. The rise of artificial intelligence (AI), machine learning (ML), and robotic automation has changed the landscape for experimental facilities, producing a paradigm shift in how different datasets are leveraged for improved intelligence, operation, and data analysis. Therefore, such facilities, known as superfacilities, which fully enable user science while addressing the challenges of the Big Data deluge, are critical for the scientific community. In this work, we discuss the process of setting up the Big Data Science Center within the Shanghai Synchrotron Radiation Facility (SSRF), China’s first superfacility. We provide details of our initiatives for enabling user science at SSRF, with particular consideration given to recent developments in AI, ML, and robotic automation.
DamageProfiler: fast damage pattern calculation for ancient DNA
Authors: Neukamm Judith , Peltzer Alexander , Nieselt Kay 
Published: April 2021

Abstract

Motivation
In ancient DNA research, the authentication of ancient samples based on specific features remains a crucial step in data analysis. Because of this central importance, researchers lacking deeper programming knowledge should be able to run a basic damage authentication analysis. Such software should be user-friendly and easy to integrate into an analysis pipeline.

Results
DamageProfiler is a Java-based, stand-alone software to determine damage patterns in ancient DNA. The results are provided in various file formats and plots for further processing. DamageProfiler has an intuitive graphical as well as command line interface that allows the tool to be easily embedded into an analysis pipeline.

Availability and implementation
All of the source code is freely available on GitHub (https://github.com/Integrative-Transcriptomics/DamageProfiler).

Supplementary information
Supplementary data are available at Bioinformatics online.
Determining optical mapping errors by simulations
Authors: Vašinek Michal , Běhálek Marek , Gajdoš Petr , Fillerová Regina , Kriegová Eva 
Published: April 2021

Abstract

Motivation
Optical mapping is a complementary technology to traditional DNA sequencing technologies, such as next-generation sequencing (NGS). It provides genome-wide, high-resolution restriction maps from single, stained molecules of DNA. It can be used to detect large and small structural variants, copy number variations and complex rearrangements. Optical mapping is affected by different kinds of errors in comparison with traditional DNA sequencing technologies. It is important to understand the source of these errors and how they affect the obtained data. This article proposes a novel approach to modeling errors in the data obtained from the Bionano Genomics Inc. Saphyr system with Direct Label and Stain (DLS) chemistry. Some studies have already addressed this issue for older instruments with nicking enzymes, but we are unaware of a study that addresses this new system.

Results
The main result is a framework for studying errors in the data obtained from the Saphyr instrument with DLS chemistry. The framework’s main component is a simulation that computes how major sources of errors for this instrument (a false site, a missing site and resolution errors) affect the distribution of fragment lengths in optical maps. The simulation is parametrized by variables describing these errors and we are using a differential evolution algorithm to evaluate parameters that best fit the data from the instrument. Results of the experiments manifest that this approach can be used to study errors in the optical mapping data analysis.

Availability and implementation
Source codes supporting the presented results are available at: https://github.com/mvasinek/olgen-om-error-prediction. The data underlying this article are available on the Bionano Genomics Inc. website, at: https://bionanogenomics.com/library/datasets/.

Supplementary information
Supplementary data are available at Bioinformatics online.
RVAgene: generative modeling of gene expression time series data
Authors: Mitra Raktim , MacLean Adam L 
Published: April 2021

Abstract

Motivation
Methods to model dynamic changes in gene expression at a genome-wide level are not currently sufficient for large (temporally rich or single-cell) datasets. Variational autoencoders offer means to characterize large datasets and have been used effectively to characterize features of single-cell datasets. Here, we extend these methods for use with gene expression time series data.

Results
We present RVAgene: a recurrent variational autoencoder to model gene expression dynamics. RVAgene learns to accurately and efficiently reconstruct temporal gene profiles. It also learns a low dimensional representation of the data via a recurrent encoder network that can be used for biological feature discovery, and from which we can generate new gene expression data by sampling the latent space. We test RVAgene on simulated and real biological datasets, including embryonic stem cell differentiation and kidney injury response dynamics. In all cases, RVAgene accurately reconstructed complex gene expression temporal profiles. Via cross validation, we show that a low-error latent space representation can be learnt using only a fraction of the data. Through clustering and gene ontology term enrichment analysis on the latent space, we demonstrate the potential of RVAgene for unsupervised discovery. In particular, RVAgene identifies new programs of shared gene regulation of Lox family genes in response to kidney injury.

Availability and implementation
All datasets analyzed in this manuscript are publicly available and have been published previously. RVAgene is available in Python, at GitHub: https://github.com/maclean-lab/RVAgene; Zenodo archive: http://doi.org/10.5281/zenodo.4271097.

Supplementary information
Supplementary data are available at Bioinformatics online.
Advancing admixture graph estimation via maximum likelihood network orientation
Authors: Molloy Erin K , Durvasula Arun , Sankararaman Sriram 
Published: April 2021

Abstract

Motivation
Admixture, the interbreeding between previously distinct populations, is a pervasive force in evolution. The evolutionary history of populations in the presence of admixture can be modeled by augmenting phylogenetic trees with additional nodes that represent admixture events. While enabling a more faithful representation of evolutionary history, admixture graphs present formidable inferential challenges, and there is an increasing need for methods that are accurate, fully automated and computationally efficient. One key challenge arises from the size of the space of admixture graphs. Given that exhaustively evaluating all admixture graphs can be prohibitively expensive, heuristics have been developed to enable efficient search over this space. One heuristic, implemented in the popular method TreeMix, consists of adding edges to a starting tree while optimizing a suitable objective function.

Results
Here, we present a demographic model (with one admixed population incident to a leaf) where TreeMix and any other starting-tree-based maximum likelihood heuristic using its likelihood function is guaranteed to get stuck in a local optimum and return an incorrect network topology. To address this issue, we propose a new search strategy that we term maximum likelihood network orientation (MLNO). We augment TreeMix with an exhaustive search for an MLNO, referring to this approach as OrientAGraph. In evaluations including previously published admixture graphs, OrientAGraph outperformed TreeMix on 4/8 models (there are no differences in the other cases). Overall, OrientAGraph found graphs with higher likelihood scores and topological accuracy while remaining computationally efficient. Lastly, our study reveals several directions for improving maximum likelihood admixture graph estimation.

Availability and implementation
OrientAGraph is available on Github (https://github.com/sriramlab/OrientAGraph) under the GNU General Public License v3.0.

Supplementary information
Supplementary data are available at Bioinformatics online.
CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes
Authors: Li Victoria R , Zhang Zijun , Troyanskaya Olga G 
Published: April 2021

Abstract

Motivation
CRISPR/Cas9 is a revolutionary gene-editing technology that has been widely utilized in biology, biotechnology and medicine. CRISPR/Cas9 editing outcomes depend on local DNA sequences at the target site and are thus predictable. However, existing prediction methods are dependent on both feature and model engineering, which restricts their performance to existing knowledge about CRISPR/Cas9 editing.

Results
Herein, deep multi-task convolutional neural networks (CNNs) and neural architecture search (NAS) were used to automate both feature and model engineering and create an end-to-end deep-learning framework, CROTON (CRISPR Outcomes Through cONvolutional neural networks). The CROTON model architecture was tuned automatically with NAS on a synthetic large-scale construct-based dataset and then tested on an independent primary T cell genomic editing dataset. CROTON outperformed existing expert-designed models and non-NAS CNNs in predicting 1 base pair insertion and deletion probability as well as deletion and frameshift frequency. Interpretation of CROTON revealed local sequence determinants for diverse editing outcomes. Finally, CROTON was utilized to assess how single nucleotide variants (SNVs) affect the genome editing outcomes of four clinically relevant target genes: the viral receptors ACE2 and CCR5 and the immune checkpoint inhibitors CTLA4 and PDCD1. Large SNV-induced differences in CROTON predictions in these target genes suggest that SNVs should be taken into consideration when designing widely applicable gRNAs.

Availability and implementation
https://github.com/vli31/CROTON.

Supplementary information
Supplementary data are available at Bioinformatics online.
EnHiC: learning fine-resolution Hi-C contact maps using a generative adversarial framework
Authors: Hu Yangyang , Ma Wenxiu 
Published: April 2021

Abstract

Motivation
The high-throughput chromosome conformation capture (Hi-C) technique has enabled genome-wide mapping of chromatin interactions. However, high-resolution Hi-C data requires costly, deep sequencing; therefore, it has only been achieved for a limited number of cell types. Machine learning models based on neural networks have been developed as a remedy to this problem.

Results
In this work, we propose a novel method, EnHiC, for predicting high-resolution Hi-C matrices from low-resolution input data based on a generative adversarial network (GAN) framework. Inspired by non-negative matrix factorization, our model fully exploits the unique properties of Hi-C matrices and extracts rank-1 features from multi-scale low-resolution matrices to enhance the resolution. Using three human Hi-C datasets, we demonstrated that EnHiC accurately and reliably enhanced the resolution of Hi-C matrices and outperformed other GAN-based models. Moreover, EnHiC-predicted high-resolution matrices facilitated the accurate detection of topologically associated domains and fine-scale chromatin interactions.

Availability and implementation
EnHiC is publicly available at https://github.com/wmalab/EnHiC.

Supplementary information
Supplementary data are available at Bioinformatics online.