bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the application of Fama and French three-factor and five-factor models in American industry
Authors: Li Kanlong , Duan Yanjun
Published: April 2021

By conducting ordinary least square estimations using the Fama and French Three-Factor and Five-Factor models on thirty U.S. based industry portfolios, the significant rate of all the variables is compared. Using the comparison, the impacts of the COVID-19 Pandemic on the markets and the Fama and French models are significant. As a result, the significance level of all the independent variables has increased during the COVID-19 Pandemic. The Five-Factor model fares a more substantial increase in efficiency during the Pandemic, and some variables, such as HML and CMA, see tremendous changes. The market becomes less sophisticated during the Pandemic, and the Fama and French Five-Factor model may be more suitable for estimation under certain market environments, contrary to many previous studies.
Research on the Design of Fire Alarm and Pre-treatment Robot System
Authors: Zhang Bingchen , Bai Long , Chen Xiaohong
Published: April 2021

With the development of society and economy, the application of fire warning robots based on sensors and artificial intelligence technology is a new research field. This paper proposes a design scheme for fire warning and pre-processing robots. The robot is based on visual tracking instead of human Uninterrupted patrol of space sites; comprehensive analysis of environmental data collected by sensors based on fuzzy theory algorithms, and issuing fire warning and alarm signals; analysis of infrared images of electrical equipment based on machine vision to monitor operating conditions; construction of fire site maps based on slam algorithm through laser radar. The fire early warning and pre-processing robot designed in this paper realizes the functions of autonomous inspection, fire early warning, fire detection, fire extinguishing, and obstacle removal. It makes full use of the golden extinguishing time to kill the fire and protect people’s lives and property.
Research on Quality and Safety Intelligent System under Ship Navigation
Authors: Lin Tao , Wang Huihui , Ma Mengyin , Zhang Haotian
Published: April 2021

This paper first analysed the importance of integrated ship control systems’ researches and developments, and find out why quality and safety plays an important role as the ship industry and the ship automation research develops. Then the paper introduced the ideas, theoretical basis, and the system structure of the whole system design, with the implementation steps of the quality and safety intelligent system followed. Finally, a simulation was executed on the system, and the data is persuasive.
Research on the Application of Big Data Technology in Information Statistics Research System
Authors: Hao Yuhong , Huang Ying , Feng Yu
Published: April 2021

With the continuous development of computing science and technology, the application of big data technology is very popular, especially in the field of scientific research. The content of mathematical information science fully reflects that mathematics is an important part of scientific research. This article adopts big data technology, which has certain educational significance for training scientific research staff to analyze sports technology of mathematics. The application of big data teaching has enabled scientific researchers to have a new understanding of mathematics, stimulated their interest in mathematics research, and gradually realized that mathematics information science is the basic skill of modern scientists, thus inspiring the continuous deepening of research mathematics Scientific research work.
Application Research and Implementation of Voice Control System Based on Android Speech Recognition
Authors: Meng Xiangrui , Song Yan
Published: April 2021

Based on the voice recognition technology of Android platform, combined with WiFi network communication technology and embedded control system, an audio voice control system is realized, which collects voice commands on the mobile phone APP for recognition and controls the operation of audio equipment through WiFi network and embedded control module. The voice recognition adopts the voice recognition SDK provided by IFLYTEK open platform, the WiFi network is provided by WiFi router, and the embedded control module adopts the STC15F204EA controller, which is matched with NL6621-M3WiFi module to receive processing instructions. After experimental test, the audio system can be effectively controlled by voice, which meets the requirements of modern audio equipment intelligence.
Simulation Analysis on Ride Comfort of Hybrid Heavy Truck Based on ADAMS
Authors: Wang Guangyu , Xie Chengwei
Published: April 2021

In traditional heavy truck design process, a large number of real vehicle tests are required to evaluate the ride comfort of the heavy truck. This not only increases the R&D costs but also prolongs the R&D cycle, which brings great inconvenience. This paper establishes a three-dimensional digital model in Adams/car based on the relevant parameters of a hybrid heavy truck. The ride comfort with different speeds was tested on B-level random roads and A-level impulsive roads, and the maximum body vibration acceleration of the heavy truck when driving on A-level impulse roads, weighted root mean square value of acceleration of driving seat vibration when driving on a B-level random road are obtained with different speeds. These values reflect the impact on human comfort and health when driving, provide a theoretical basis for the subsequent optimization design and greatly save manpower and material resources.
An Empirical Analysis of the Service Efficiency of Basic Public Education Based on the BCC-DEA Model of Neural Network Computing Principles
Authors: Han Tianyue , Han Xiaowei
Published: April 2021

Aiming at the problem that the performance ranking analysis method in the traditional BCC-DEA model will produce infeasible solutions under the assumption of variable returns to scale, this paper proposes to apply the neural network calculation principle to the DEA performance ranking analysis, thereby establishing a BCC based on the neural network calculation principle -DEA model, and then use this model to analyze the efficiency of basic public education service investment in Jilin Province during the “Twelfth Five-Year Plan” period, and studied the details of the nine-year compulsory education service. The implementation measures and implementation rules examine the relationship between the government’s interactions between educational resources and economic benefits. The layer is facing empirical research in Jilin Province as a whole. The study found that the overall high speed of basic public education services in Jilin Province is insufficient, and the education system, management level, and pure technical efficiency of resource allocation are the main factors affecting overall efficiency. Various investments made by the government during the 12th Five-Year Plan period, the efficiency changes in the whole period: the overall comprehensive efficiency changes in Jilin Province decreased during the five years, and the direct influencing factors were insufficient progress in education and through a variety of training, and a variety of multimedia education and new technology application. To this end, the paper puts forward the following suggestions: explore the public policy of sufficiency education, improve the performance of resource allocation; build a public policy of responsive education, improve the financial security mechanism; esTablelish a public policy of binding education, improve the system management; promote learning education Public policy to improve the development of capabilities.
Adiabatic shear bands formation in polycrystalline aluminium
Authors: Mania I , Paul H , Chulist R , Petrzak P
Published: April 2021

The microstructure and texture evolutions during dynamic (or high strain rate) deformation of commercially pure AA1050 alloy have been studied to elucidate the mechanisms of shear band (SB) formation and its propagation across the flattened grains arranged in layers with special attention to texture evolution. The hat-shaped samples were compressed using drop hammer at a strain rate of 5.3 × 102 s−1. Detailed microstructure and texture characterizations were carried out using SEM equipped with EBSD facility. The shear displacement moves the upper part of the hat-shaped sample towards the bottom one leading to a strain localization in the form of SB. It was found that the strain localization occurs via deflection of flattened grains within narrow areas leading to kink-type bands that are considered to be the precursors of SB. The strain-induced crystal lattice rotation led to the formation of new texture components, different from those identified inside the undeformed matrix. It also facilitates slip propagation across the grain boundaries. The mechanism of macro-SB formation is essentially crystallographic in nature since in all grains of the sheared zone, the crystal lattice rotated in such a way that one of the {111} slip planes became nearly parallel to the shear plane and the <011> direction became parallel to the direction of maximum shear.
Observation of Inhomogeneous Deformation in a Cold-Rolled Ti-added Ultra-Low Carbon Steel using High-Precision Markers Drawn by Focused Ion Beam
Authors: Morikawa T , Kurosaka R , Tanaka M , Ichie T , Murakami K
Published: April 2021

The development of deformation inhomogeneities in ultra-low carbon steel due to cold rolling has been investigated by observation of the longitudinal plane at chosen sites of a rolled sheet using SEM and SEM-EBSD techniques. Particular attention has been paid to the development of strain distribution in the crystals. The microstructures and the orientation distribution in the longitudinal plane of a sheet rolled to a 60% reduction in thickness were observed, and some grains with preferred orientation such as α-fiber and γ-fiber were selected. In order to examine the local strain distribution of these grains due to cold rolling, high-precision dot markers, 0.3μm in diameter, were drawn using a focused ion beam. Then, before being subjected to additional rolling, the sheet was fitted into a frame made of the same steel under a plane strain condition. Using the marker method, the local displacement of the grains due to cold rolling has been directly measured.
A phase-field investigation of recrystallization boundary migration into heterogeneous deformation energy fields: Effects of dislocation boundary sharpness
Authors: Li R , Yadav V , Moelans N , Zhang Y , Juul Jensen D
Published: April 2021

The migration of recrystallization boundaries into spatially varying deformation energy fields are simulated based on a two-dimensional phase-field model. The energy fields are chosen as idealized versions of deformation microstructures subdivided by two sets of intersecting geometrically necessary dislocation boundaries (GNBs), and effects of the sharpness of the GNBs are investigated. The simulations show that the shape of the recrystallizing grain as well as the recrystallization kinetics are considerably affected by the wall characteristics of the GNBs. Recrystallization occurs faster in the deformed matrix with “sharper” walls. The simulation results highlight the importance of the deformation microstructure characteristics on the recrystallization kinetics, and as the deformation microstructures depend on the initial grain orientations, the results also indicate tight relations between initial, deformation and recrystallization textures.
Texture evolutions in aluminum and Al-3%Mg alloy subjected to shear deformation and subsequent annealing
Authors: Takayama Yoshimasa , Xu Yihe , Yoshida Tsuyoshi , Tanaka Hiroki , Onuki Yusuke , Sato Shigeo
Published: April 2021

Shear deformation is imposed on materials by several advanced techniques for microstructural and textural control. Shear texture evolved during deformation tends to remain after subsequent annealing. Texture evolutions with shear deformation and subsequent annealing in aluminum and Al-3mass%Mg alloy rolled sheets have been investigated by neutron diffraction technique. N-shaped specimen was prepared from the alloy sheet to impose shear strain in compression. The central objective part of the N-shaped specimen was sheared with slight rotation about the normal axis so as to develop preferred orientations of {111} parallel to the original shear plane and <110> parallel to the original shear direction before deformation. In-situ neutron diffraction analysis during step heating revealed that the preferred orientations formed by shear deformation remain and evolve as recrystallization texture during subsequent annealing in both materials. Evolutions of shear and recrystallization textures were compared after shear deformations with strains of 0.5 and 0.7 in two samples sheared parallel to rolling and transverse directions.
Secondary recrystallization in grain-oriented silicon steel
Authors: Ushigami Y
Published: April 2021

Grain-oriented silicon steel is a soft magnetic material widely used for transformer cores. Magnetic properties are closely related to the sharpness of Goss texture, which is evolved by secondary recrystallization. An overview of our results will be presented; secondary recrystallization behaviour has been investigated by in situ observation utilizing synchrotron x-ray topography. The results support the selective growth mechanism. Migration of Goss grains is controlled by inhibitor and sharper Goss grains, which have higher frequency of CSL-boundaries to the matrix, start to grow preferentially while the other grains are stagnated by inhibitor. Secondary recrystallization behaviour can be explained based on this CSL-model. At the initial stage, inhibitor gradient through the thickness promotes Goss selective growth from the subsurface layer and at the later stage, inhibitor drop rate dominates the Goss selective growth. Inhibitor and CSL-boundaries synergistically affect Goss selective growth and Goss grain evolves to a coarse grain.
Grain growth in soft magnetic ferritic stainless steels under compressive stresses at high temperatures
Authors: Suzuki S. , Onuki Y. , Uchida M. , Sato S. , Naruse T. , Watanabe M. , Sato T. , Ebata T.
Published: April 2021

Precipitation-hardened ferritic stainless steels are used for soft magnetic actuators of engines, as these steels exhibit high strength and soft magnetic properties. These ferritic stainless steels are hardened by nanoscale precipitates formed during an aging process after solution treatment. Furthermore, texture control of these steels is required in order to improve the soft magnetic properties. Therefore, texture control of ferritic stainless steels with <100> fiber texture by deformation at high temperatures is attempted in this study, as it has been demonstrated that the texture of ferritic Fe-Si alloys is significantly changed by deformation conditions, including temperature and strain rate. The results demonstrate that grains with the <100> fiber texture in the present stainless steels are preferentially evolved by compressive deformation under specific strain rates at high temperatures.
Improving Ductility in Dual-Phase Steel by Cold Rolling and Intercritical Annealing
Authors: Singh Alok Kumar , Bhattacharya Basudev , Biswas Somjeet
Published: April 2021

Dual-phase steels offer huge potential to provide a cost-effective solution in the automobile industry to fulfill the demand for high strength with formability. The desirable strength is achieved by increasing geometrically necessary boundaries and ferrite grain refinement but not by increasing martensite fraction. The major challenge is to improve the ductility and formability, without compromising its strength. In this work, cold rolling reductions to ∼84% was given to hot rolled annealed steel, followed by intercritical annealing and water quenching. Tensile tests, Optical microscopy, Electron Back Scattered Diffraction and X-Ray characterizations were carried out. The improvement in strength and ductility were correlated with microstructure and texture.
η-fiber microstructure and texture evolutions in ultra-thin silicon steel
Authors: Zhang N , Meng L , Zhang B , He C X , Ma G , Han Y , Chen X
Published: April 2021

0.08mm ultra-thin silicon steel is prepared with 0.30mm commercial grain-oriented silicon steel as raw material, and the evolutions of η-fiber microstructure and texture are investigated with emphasis. During rolling deformation, initial Goss orientation shows crystal rotation to {111 }<112> orientation. With the increase of rolling reduction, the retention of Goss orientation is reduced and more observed near the sheet surface. For initial deviated Goss oriented grains, {111}<112> and η-fiber oriented areas are also observed in 0.08mm rolled sheet, while the accuracy and concentration of these two components are decreased. During annealing, η-fiber nucleation superiority in γ-fiber deformed regions is significant, and thus contributes to strong η-fiber recrystallization texture. When the rolled sheets are heated at 800 °C for 15 min, strong η-fiber recrystallization texture and uniform microstructure is beneficial for the magnetic properties of ultrathin silicon steel sheets.
Influence of substructure inhomogeneity on the anisotropy of physical properties of textured materials
Authors: Krymskaya O A , Isaenkova M G , Perlovich Y A , Fesenko V A
Published: April 2021

Calculation of the physical properties anisotropy is based on single crystal properties and information about material texture, i.e. orientation distribution function (ODF). At the same time, the grains of different orientations are known to have different substructure parameters including the lattice distortion and microstrains. Determination of these parameters is possible with the X-ray method of Generalized Pole Figures (GPF), which consists of registration of the whole X-ray reflection profile under the pole figure recording. As a result, one can obtain the FWHMs of X-ray line profiles and microstrains distributed on the stereographic projection. Despite the observable equilibrium of tensile and compressive microstrains of differently oriented grains within the studied material volume, they can affect the product properties anisotropy. In this study the calculation method for elastic properties and thermal expansion coefficients taking into account substructure inhomogeneity is offered on the basis of elastic energy minimization. Its efficiency is demonstrated for the samples of zirconium alloys.
Depth Profile of Residual Stresses to Analyze Textures in Extruded A6XXX
Authors: Oda Shogo , Tanaka Shun-Ichiro
Published: April 2021

The extruded profiles of A6XXX alloys have a textured surface structure, different from those having the inner cube and Goss orientations. This structure possibly contributes to the decrease in bending strength. Although the mechanism of degradation has been discussed for precipitates, it is necessary to reconsider it from the viewpoint of residual stress distribution. In this study, we first determine the optimal method to evaluate the residual stress in a textured structure. The cosa method with 3-axis oscillation successfully yielded highly precise residual stress values even in extruded aluminum alloys. Although the inner layers of A6063 and A6005C had the cube and Goss orientation, the surface layer at a depth of ∼400 μm had a (112) orientation in A6063 and that at ∼200 μm had a (110) orientation in A6005C. The residual stress increased further from the surface, and changes in the preferred orientation corresponded well with those of residual stress, especially in A6005C. It is suggested that the residual stress increases as the tensile strength increases.
Process parameter influence on deformation and recrystallization textures in Al alloys
Authors: Sidor Jurij J , Xie Qingge , Chakravarty Purnima , Pal Gyula
Published: April 2021

Mesoscopic changes take place during the entire thermomechanical processing (TMP) of polycrystalline metallic materials. Controlling the TMP parameters is of key importance since both microstructure and texture evolution of a particular technological step severely influence the final properties of a given product. This study is focusing on the crystallographic aspect of microstructural formation in Al alloys. The effect of straining level on the crystallographic texture evolution and texture-dependent properties is discussed. This contribution clearly demonstrates that the plastic stain ratio can be modified via TMP route. Implementation of relatively small deformation could account for improvement of anisotropy of plastic yielding, necessary for advanced deep drawing qualities.
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

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

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

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

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

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

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

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

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

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

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

The 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

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

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

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

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

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

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

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

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

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.
scPNMF: sparse gene encoding of single cells to facilitate gene selection for targeted gene profiling
Authors: Song Dongyuan , Li Kexin , Hemminger Zachary , Wollman Roy , Li Jingyi Jessica
Published: April 2021

Motivation

Single-cell RNA sequencing (scRNA-seq) captures whole transcriptome information of individual cells. While scRNA-seq measures thousands of genes, researchers are often interested in only dozens to hundreds of genes for a closer study. Then, a question is how to select those informative genes from scRNA-seq data. Moreover, single-cell targeted gene profiling technologies are gaining popularity for their low costs, high sensitivity and extra (e.g. spatial) information; however, they typically can only measure up to a few hundred genes. Then another challenging question is how to select genes for targeted gene profiling based on existing scRNA-seq data.

Results

Here, we develop the single-cell Projective Non-negative Matrix Factorization (scPNMF) method to select informative genes from scRNA-seq data in an unsupervised way. Compared with existing gene selection methods, scPNMF has two advantages. First, its selected informative genes can better distinguish cell types. Second, it enables the alignment of new targeted gene profiling data with reference data in a low-dimensional space to facilitate the prediction of cell types in the new data. Technically, scPNMF modifies the PNMF algorithm for gene selection by changing the initialization and adding a basis selection step, which selects informative bases to distinguish cell types. We demonstrate that scPNMF outperforms the state-of-the-art gene selection methods on diverse scRNA-seq datasets. Moreover, we show that scPNMF can guide the design of targeted gene profiling experiments and the cell-type annotation on targeted gene profiling data.

Availability and implementation

The R package is open-access and available at https://github.com/JSB-UCLA/scPNMF. The data used in this work are available at Zenodo: https://doi.org/10.5281/zenodo.4797997.

Supplementary information

Supplementary data are available at Bioinformatics online.
Mapping the Pains of Neo-Colonialism: A Critical Elaboration of Southern Criminology
Authors: Ciocchini Pablo , Greener Joe
Published: April 2021

Recent appeals to decolonize criminology argue for a radical reorientation of the subject towards Global South relevant research agendas, theories and scholars. This paper begins by problematizing the current theoretical tendencies in Southern criminology’s view of coloniality and the vision for decolonization. First, Southern criminology has not directly engaged in investigating ‘empire’ in its current form; second, decolonization is viewed as primarily epistemological (transforming systems of knowledge production is seen as the central mode for decolonization); and, third, there is a tendency to reify Southern institutional responses to crime as preferable to Northern crime control. Launching from this critique, we argue that a successful Southern criminology should take seriously the continuing importance of structures of neo-colonialization: the Global system of accumulation founded on various matrixes of inequality, facilitating dispossession, appropriation and exploitation. We develop three criminological analyses of contemporary neo-colonization in Global South contexts: state-corporate ‘regimes of permission’, political economies of gender violence and racialization through criminalization regimes.