Analysis Software Package Research Articles

Ballistic Impact and Virtual Testing of Woven FRP Laminates

The aim of the work was to investigate the numerical simulations correlation with the experimental behaviour of steel ball high velocity impact onto a 2 × 2 twill woven carbon composite laminate. The experimental set up consisted of a pressurised gas-gun able to shot steel ball projectiles onto two different composite plate layup configurations of plates made of the same composite material fabric. Subsequently, the experiments were replicated using the LSDYNA explicit finite element analysis software package. Progressive failure numerical models of two different fidelity levels were constructed. The higher fidelity model was simulating each of the plys of the composite panels separately, tied together using cohesive zone modelling properties. The lower fidelity model consisted of a single layer plate with artificial integration points for each ply. The simulation results came out to be in satisfactory agreement with the experimental ones. While the delamination extent was moderately under predicted by the higher fidelity model, the general behaviour was complying with the experimental results. The lower fidelity model was consistent in representing the damage of the panel during the impact and better predicted the impactor residual velocities due to the better matching of the pane stiffness. Despite the competency of the higher fidelity model to capture the damage of the laminate in a more detailed level, the computational cost was 80% higher than the lower fidelity case, which rendered that model impractical against the lower fidelity one, to use in larger models representing more substantial or more complex structures.

LeXtender: a software package for advanced MOKE acquisition and analysis

Contemporary scanning laser Kerr magnetometers are very efficient measurement devices that achieve very good signal to noise ratios and spatial resolution for magnetization measurements. When going beyond simple hysteresis loop measurements, large amounts of data can be acquired quickly and, thus, control software and automated processing becomes necessary to go beyond these simple measurements. Here, we present an open source software that realizes first-order reversal curves and magnetic property mapping based on scanning laser Kerr magnetometry. The modular software is easily extensible and provides a convenient user interface to make these more complex measurements accessible to a broader user base.

Determination of bench, dump and road sliding wedge technological parameters

Mine surveying in mining operations is of particular importance, since all technological processes of the full life cycle of a mining enterprise and, ultimately, its competitiveness depend on the surveying quality, efficiency and reliability. Organizations independently determine the structure of mine surveying services, taking into account the methods applied and the scale of mining. To ensure safe open-pit mining of minerals, it is necessary to permanently assess and monitor the pit bench and wall rock mass condition. Misjudgement of rock physical and mechanical properties, non-observance of the minerals mining and transportation process cycle, changes in climatic conditions and other problems lead to loss of stability of rocks in all parts of an open pit, including in the areas of ore production and mining and transport equipment operation. The existing practice shows that the effectiveness of an open pit wall and bench stability calculation can be achieved using a technique that should take into account the slope deformation and failure mechanism, as well as the nature of the stress-strain state of the open pit rock mass. The studies presented in the paper are based on comparative analysis of the sliding wedge parameters for benches, dumps and roads at open pits using analytical and graphical software packages, and taking into account the static load produced by dump trucks. The study findings allow to establish that: determination of the bench slope stability and the sliding wedge width, performed by the analytical method, gives higher accuracy results than those obtained by the graphical method; the bench slope stability and the sliding wedge width depend not only on the rock physical and mechanical condition, but also on the bench height, the dump truck (plus its freight load) weight per 1 linear meter of the placement area, the distance from the slope edge and other factors; the rock mass is stable and not subject to landslide phenomena for as long as the sum of the holding forces is greater than or equal to the sum of the shearing forces; when using large-sized transport equipment of nonstandard weight in open-pit mining, it is necessary to calculate the safe width of the sliding wedges, taking into account the loads on them (per 1 linear meter), the values of which can be 1.5–2.0 times higher than those calculated for the circular-cylindrical sliding surface.

Spatiotemporal analysis of bubonic plague in Pernambuco, northeast of Brazil: Case study in the municipality of Exu.

Along with other countries in America, plague reached Brazil through the sea routes during the third pandemic. A brief ports phase was followed by an urban phase that took place in smaller inland cities and finally, it attained the rural area and established several foci where the ecological conditions were suitable for its continued existence. However, the geographic dispersion of plague in Brazil is still poorly studied. To better understand the disease dynamics, we accessed satellite-based data to trace the spatial occurrence and distribution of human plague cases in Pernambuco, Northeastern Brazil and using the municipality of Exu as study case area. Along with the satellite data, a historical survey using the Plague Control Program files was applied to characterize the spatial and temporal dispersion of cases in the period of 1945-1976. Kernel density estimation, spatial and temporal clusters with statistical significance and maximum entropy modeling were used for spatial data analysis, by means of the spatial analysis software packages. The use of geostatistical tools allowed evidencing the shift of the infection from the urban to the wild-sylvatic areas and the reemergence of cases after a period of quiescence, independent of the reintroduction from other plague areas.

Application Research of Computer Aided Architectural Design Based on BIM Technology

This paper summarizes the development and application experience of computer aided design software for control system. Discusses how to arrange interaction with users with extensive experience. This includes question and answer dialog boxes using macro tools and different types of menu driven systems. A set of software packages for modeling, identification, analysis, simulation and design are described. The problems related to architecture, portability, and maintainability and extensible are discussed. Experience in developing and using software packages in teaching and industrial environments.

Radiomics and Digital Image Texture Analysis in Oncology (Review).

One of the most promising areas of diagnosis and prognosis of diseases is radiomics, a science combining radiology, mathematical modeling, and deep machine learning. The main concept of radiomics is image biomarkers (IBMs), the parameters characterizing various pathological changes and calculated based on the analysis of digital image texture. IBMs are used for quantitative assessment of digital imaging results (CT, MRI, ultrasound, PET). The use of IBMs in the form of “virtual biopsy” is of particular relevance in oncology.The article provides the basic concepts of radiomics identifying the main stages of obtaining IBMs: data collection and preprocessing, tumor segmentation, data detection and extraction, modeling, statistical processing, and data validation. The authors have analyzed the possibilities of using IBMs in oncology, describing the currently known features and advantages of using radiomics and image texture analysis in the diagnosis and prognosis of cancer. The limitations and problems associated with the use of radiomics data are considered.Although the novel effective tool for performing virtual biopsy of human tissue is at the development stage, quite a few projects have already been implemented, and medical software packages for radiomics analysis of digital images have been created.

Argonaute-CLIP delineates versatile, functional RNAi networks in Aedes aegypti, a major vector of human viruses

Argonaute (AGO) proteins bind small RNAs to silence complementary RNA transcripts, and they are central to RNA interference (RNAi). RNAi is critical for regulation of gene expression and antiviral defense inAedes aegypti mosquitoes, which transmit Zika, chikungunya, dengue, and yellow fever viruses. In mosquitoes, AGO1 mediates miRNA interactions, while AGO2 mediates siRNA interactions. We applied AGO-crosslinking immunoprecipitation (AGO-CLIP) for both AGO1 and AGO2, and we developed a universal software package for CLIP analysis (CLIPflexR), identifying 230 small RNAs and 5,447 small RNA targets that comprise a comprehensive RNAi network map in mosquitoes. RNAi network maps predicted expression levels of small RNA targets in specific tissues. Additionally, this resource identified unexpected, context-dependent AGO2 target preferences, including endogenous viral elements and 3'UTRs.Finally, contrary to current thinking, mosquito AGO2 repressed imperfect targets. These findings expand our understanding of small RNA networks and have broad implications for the study of antiviral RNAi.

PCM-net: a refractive index database of chalcogenide phase change materials for tunable nanophotonic device modelling

The growing demand for multifunctional nanophotonic devices has led to the exploration, and utilization, of a plethora of exotic electro-optical materials. Recently, chalcogenide glass based phase change materials (PCMs) have shown utility as a tuning material for a range of nanophotonic devices. Owing to their low loss, ultrafast switching speeds and wide waveband operation, PCMs are integrated in an increasing number of next-generation tunable components, including integrated photonic switches, metasurface optics and tunable spectral filters. Nonetheless, modelling of PCM-based devices is challenging—both in terms of accurate representation of experimentally derived material properties in different phase states, and standardization of results across the research community. Further, as each device requires optimization of specific performance metrics dependent on their respective application, any inaccuracies will lead to erroneous outcomes. In this work, we introduce PCM-net (http://nekocloud.com/pnet/): an online database of the complex refractive indices of a variety of chalcogenide glass PCMs (such as GeSbTe), as an accessible and indexed repository for data sharing across the PCM community. Refractive indices (n) and extinction coefficients (k) between amorphous and crystalline states are directly extracted from experimentally derived data in numerous academic research articles, and collated into the material resource database. Due to the inaccuracies associated with our data collection methods, this data is supplemented with additional computationally generated data, obtained through WVASE® —a commercial ellipsometry analysis software package. To demonstrate the utility of PCM-net, we provide a NASA application-driven device optimization example using the optical properties of PCMs collected with our database. We anticipate the database providing great use to the PCM community and coordinated research efforts enabled by PCM-net will promote the shared repository for the selection of appropriate PCMs for tunable nanophotonic device design for a range of applications.

Implementation and validation of true material constitutive model for accurate modeling of thick-walled cylinder swage autofrettage

The fatigue life prediction and associated fail-safe design of autofrettaged tubes require accurate stress modeling of each specific high-strength thick-walled cylinder during and after the autofrettage process, which depends largely on the elastoplastic behavior of the original steel tubes. However, the complex material behavior is dominated by the Bauschinger effect. Modeling swage autofrettage of such steel tubes remains problematic. This is a crucial issue that has not been resolved by any available modeling software. Therefore, the modeling and design of the autofrettage process for current and future materials depends upon extending the capability of current software.This research aims to develop a user-programmable function (UPF), USERMAT, to realize a user-defined material model that features true material constitutive behavior with the corresponding algorithms for accurate stress analysis of high strength thick-walled cylinders during the autofrettage process. The material constitutive model to be implemented can be formulated with high accuracy via an available material characterization, which can adapt to both nonlinear and linear strain hardening during the initial tensile loading, while the elastic modulus can be reduced during reversed-loading. It also incorporates the Bauschinger effect as a function of the prior tensile plastic strain during the nonlinear compressive reversed-loading phase and fits the experimental data of the true material model. Swage autofrettaged thick-walled cylinder case studies were reported. The results for residual radial and hoop stress and for elastic strain components were compared with independent, available neutron diffraction measurements, and they are in good agreement. Developing and integrating such a UPF into a standard finite element analysis software package is potentially the most significant unsolved fundamental modeling issue relating to re-yielding, fracture and fatigue of modern autofrettaged cylinders and pressure vessels. It can not only provide a fundamental understanding of the deformation mechanism and stress development within the high strength steel tubes during the autofrettage process, but also provide guidance for the design and optimization of the autofrettage manufacturing processes and of material selection for high intensity pressure vessels, a potential market of billions of dollars.

Soil–Structure Interaction and Structural Design of Raft-Foundation and Reinforced Concrete Superstructure

Raft foundations can be analyzed using the conventional, Winkler, and continuum methods. In the conventional method, it is assumed that the raft is rigid and settles uniformly. In the Winkler method, commonly employed in structural analysis software packages, soil is represented by a series of springs. On the other hand, in computer-aided continuum analysis, soil below the raft is modeled using solid elements available in finite element–based software. In the present study, analyses of the raft as a single unit and the raft together with the superstructure as a combined unit are carried out separately for a wide range of soil strength parameters employing the Winkler and continuum methods. The results of the analyses and subsequent designs were compared for different models. The variations in the quantity of reinforcement required for the raft and superstructure, corresponding to changes in soil stiffness values in different modeling methods, are investigated. Useful recommendations are presented to increase the effectiveness of Winkler model for structural design. The need for modeling the raft and superstructure as a combined unit is also highlighted.

The Optimization of Bayesian Extreme Value: Empirical Evidence for the Agricultural Commodities in the US

Bayesian extreme value analysis was used to forecast the optimal point in agricultural commodity futures prices in the United States for cocoa, coffee, corn, soybeans and wheat. Data were collected daily between 2000 and 2020. The estimation of extreme value can be empirically interpreted as representing crises or unusual time series trends, while the extreme optimal point is useful for investors and agriculturists to make decisions and better understand agricultural commodities future prices warning levels. Results from the Non-stationary Extreme Value Analysis (NEVA) software package using Bayesian inference and the Newton-optimal methods provided optimal interval values. These indicated extreme maximum points of future prices to inform investors and agriculturists to sell the contract and product before the commodity prices dropped to the next local minimum values. Thus, agriculturists can use this information as an advanced warming of alarming points of agricultural commodity prices to predict the efficient quantity of their agricultural product to sell, with better ways to manage this risk.

Satisfaction and Revisiting Behaviour of Tourists in India

Despite the fact that the tourists choose and visit the destination after considering the available information, there are certain aspects of the destination which result in the satisfaction of tourists and their revisit behaviour towards a destination. The present paper aims to create a conceptual framework that incorporates the principles of service efficiency system and an efficiency to measure revisiting and recommendation behaviour at various tourist spots in the Union territory of Jammu and Kashmir in India. It used a formal questionnaire to interview 431 visitors to Jammu and Kashmir, India. Primary data was collected and subjected to a statistical software package for analysis. The dimension reduction (factor analysis) technique on the collected data decreased the 25 proposed variables into five new variable constructs. The finding showed that all new variables were relevant for influencing the overall satisfaction level, be them Indians or foreigners. Moreover, the results signified that the total satisfaction leads to the likelihood that families and friends will visit the union territory of Jammu and Kashmir. The data review research can contribute to successful tourism industry policies and strategy preparation.

Research on Reactive Power Compensation Configuration of Wind Farm Integration

The large-scale wind power integration into power system brings great impact on the grid voltage stability. In order to reduce the influences of grid-connected wind power on the power system and improve the safety of wind power integration, it is necessary to conduct research on reactive power compensation configuration of wind farm integration. Firstly, based on the actual situation of wind power project, the principle of reactive power compensation configuration is studied. Secondly, a theoretical calculation method of reactive power compensation configuration is proposed. On this basis, combined with the practical 300MW wind farm project, the reactive power compensation configuration example is analyzed. Finally, through the modeling and simulation by power system analysis software package (PSASP), the accuracy and effectiveness of the calculation method proposed by this paper are verified. This paper put forward a reactive power compensation configuration method which is applicable to all wind farms connected to the power system. This provides important support for voltage stability in the wind power integration project.

Finite element simulations of stresses in bone implants made by three-dimensional printing

The article is devoted to the analysis of the strength properties of a compact bone tissue in order to produce subsequently the equivalent in strength individual implant. An example of a fragment of a skeleton bone shows the fundamental possibility of solving the problem using a 3d modelling finite element analysis software package.

The prebiotic molecular inventory of Serpens SMM1

Aims. Methyl isocyanate (CH3NCO) and glycolonitrile (HOCH2CN) are isomers and prebiotic molecules that are involved in the formation of peptide structures and the nucleobase adenine, respectively. These two species are investigated to study the interstellar chemistry of cyanides (CN) and isocyanates (NCO) and to gain insight into the reservoir of interstellar prebiotic molecules. Methods. ALMA observations of the intermediate-mass Class 0 protostar Serpens SMM1-a and ALMA-PILS data of the low-mass Class 0 protostar IRAS 16293B are used. Spectra are analysed with the CASSIS line analysis software package in order to identify and characterise molecules. Results. CH3NCO, HOCH2CN, and various other molecules are detected towards SMM1-a. HOCH2CN is identified in the PILS data towards IRAS 16293B in a spectrum extracted at a half-beam offset position from the peak continuum. CH3NCO and HOCH2CN are equally abundant in SMM1-a at [X]/[CH3OH] of 5.3 × 10−4 and 6.2 × 10−4, respectively. A comparison between SMM1-a and IRAS 16293B shows that HOCH2CN and HNCO are more abundant in the former source, but CH3NCO abundances do not differ significantly. Data from other sources are used to show that the [CH3NCO]/[HNCO] ratio is similar in all these sources within ~10%. Conclusions. The new detections of CH3NCO and HOCH2CN are additional evidence for a large interstellar reservoir of prebiotic molecules that can contribute to the formation of biomolecules on planets. The equal abundances of these molecules in SMM1-a indicate that their formation is driven by kinetic processes instead of thermodynamic equilibrium, which would drive the chemistry to one product. HOCH2CN is found to be much more abundant in SMM1-a than in IRAS 16293B. From the observational data, it is difficult to indicate a formation pathway for HOCH2CN, but the thermal Strecker-like reaction of CN− with H2CO is a possibility. The similar [CH3NCO]/[HNCO] ratios found in the available sample of studied interstellar sources indicate that these two species are either chemically related or their formation is affected by physical conditions in the same way. Both species likely form early during star formation, presumably via ice mantle reactions taking place in the dark cloud or when ice mantles are being heated in the hot core. The relatively high abundances of HOCH2CN and HNCO in SMM1-a may be explained by a prolonged stage of relatively warm ice mantles, where thermal and energetic processing of HCN in the ice results in the efficient formation of both species.

Construction of circRNA-Based ceRNA Network to Reveal the Role of circRNAs in the Progression and Prognosis of Hepatocellular Carcinoma.

BackgroundCircular RNAs (circRNAs) are now under hot discussion as novel promising biomarkers for patients with hepatocellular carcinoma (HCC). The purpose of our study is to identify several competing endogenous RNA (ceRNA) networks related to the prognosis and progression of HCC and to further investigate the mechanism of their influence on tumor progression.MethodsFirst, we obtained gene expression data related to liver cancer from The Cancer Genome Atlas (TCGA) database (http://www.portal.gdc.cancer.gov/), including microRNA (miRNA) sequence, RNA sequence, and clinical information. A co-expression network was constructed through the Weighted Correlation Network Analysis (WGCNA) software package in R software. The differentially expressed messenger RNAs (DEmRNAs) in the key module were analyzed with the Database for Annotation Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/summary.jsp) to perform functional enrichment analysis including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The data of miRNA expression and clinical information downloaded from TCGA were utilized for survival analysis to detach the prognostic value of the DEmiRNAs of the key module.ResultsThe 201 differentially expressed miRNAs (DEmiRNAs) and 3,783 DEmRNAs were preliminarily identified through differential expression analysis. The co-expression networks of DEmiRNAs and DEmRNAs were constructed with WGCNA. Further analysis confirmed four miRNAs in the most significant module (blue module) were associated with the overall survival (OS) of patients with liver cancer, including hsa-miR-92b-3p, hsa-miR-122-3p, hsa-miR-139-5p, and hsa-miR-7850-5p. DAVID was used for functional enrichment analysis of 286 co-expressed mRNAs. The GO analysis results showed that the top enriched GO terms were oxidation–reduction process, extracellular exosome, and iron ion binding. In KEGG pathway analysis, the top three enriched terms included metabolic pathways, fatty acid degradation, and valine, leucine, and isoleucine degradation. In addition, we intersected the miRNA–mRNA interaction prediction results with the differentially expressed and prognostic mRNAs. We found that hsa-miR-92b-3p can be related to CPEB3 and ACADL. By overlapping the data of predicted circRNAs by circBank and differentially expressed circRNAs of GSE94508, we screened has_circ_0077210 as the upstream regulatory molecule of hsa-miR-92b-3p. Hsa_circ_0077210/hsa-miR-92b-3p/cytoplasmic polyadenylation element binding protein-3 (CPEB3) and acyl-Coenzyme A dehydrogenase, long chain (ACADL) were validated in HCC tissue.ConclusionOur research provides a mechanistic elucidation of the unknown ceRNA regulatory network in HCC. Hsa_circ_0077210 might serve a momentous therapeutic role to restrain the occurrence and development of HCC.

ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis

The advent of single-cell chromatin accessibility profiling has accelerated the ability to map gene regulatory landscapes but has outpaced the development of scalable software to rapidly extract biological meaning from these data. Here we present a software suite for single-cell analysis of regulatory chromatin in R (ArchR; https://www.archrproject.com/) that enables fast and comprehensive analysis of single-cell chromatin accessibility data. ArchR provides an intuitive, user-focused interface for complex single-cell analyses, including doublet removal, single-cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing (scRNA-seq). Enabling the analysis of over 1.2 million single cells within 8 h on a standard Unix laptop, ArchR is a comprehensive software suite for end-to-end analysis of single-cell chromatin accessibility that will accelerate the understanding of gene regulation at the resolution of individual cells.

Modeling driver behavior in the dilemma zone based on stochastic model predictive control.

Driver behavior is considered one of the most important factors in the genesis of dilemma zones and the safety of driver-vehicle-environment systems. An accurate driver behavior model can improve the traffic signal control efficiency and decrease traffic accidents in signalized intersections. This paper uses a mathematical modeling method to study driver behavior in a dilemma zone based on stochastic model predictive control (SMPC), along with considering the dynamic characteristics of human cognition and execution, aiming to provide a feasible solution for modeling driver behavior more accurately and potentially improving the understanding of driver-vehicle-environment systems in dilemma zones. This paper explores the modeling framework of driver behavior, including the perception module, decision-making module, and operation module. The perception module is proposed to stimulate the ability to perceive uncertainty and select attention in the dilemma zone. An SMPC-based driver control modeling method is proposed to stimulate decision-making behavior in the dilemma zone. The operation module is proposed to stimulate the execution ability of the driver. Finally, CarSim, the well-known vehicle dynamics analysis software package, is used to verify the proposed models of this paper. The simulation results show that the SMPC-based driver behavior model can effectively and accurately reflect the vehicle motion and dynamics under driving in the dilemma zone.

Automating Data Analysis Methods in Epidemiology

Technological advances in software development effectively handled technical details that made life easier for data analysts, but also allowed for nonexperts in statistics and computer science to analyze data. As a result, medical research suffers from statistical errors that could be otherwise prevented such as errors in choosing a hypothesis test and assumption checking of models. Our objective is to create an automated data analysis software package that can help practitioners run non-subjective, fast, accurate and easily interpretable analyses. We used machine learning to predict the normality of a distribution as an alternative to normality tests and graphical methods to avoid their downsides. We implemented methods for detecting outliers, imputing missing values, and choosing a threshold for cutting numerical variables to correct for non-linearity before running a linear regression. We showed that data analysis can be automated. Our normality prediction algorithm outperformed the Shapiro-Wilk test in small samples with Matthews correlation coefficient of 0.5 vs. 0.16. The biggest drawback was that we did not find alternatives for statistical tests to test linear regression assumptions which are problematic in large datasets. We also applied our work to a dataset about smoking in teenagers. Because of the opensource nature of our work, these algorithms can be used in future research and projects.

D-karyo-A New Prenatal Rapid Screening Test Detecting Submicroscopic CNVs and Mosaicism.

Chromosomal microarray analysis (CMA), recently introduced following conventional cytogenetic technology, can detect submicroscopic copy-number variations (CNVs) in cases previously diagnosed as “cytogenetically benign”. At present, rapid and accurate chromosomal analysis is required in prenatal diagnostics, but prenatal CMA is not widely used due to its high price and long turnaround time. We introduced a new prenatal screening method named digital karyotyping (D-karyo), which utilizes a preimplantation genetic test for the aneuploidy (PGT-A) platform. First, we conducted a preliminary experiment to compare the original PGT-A method to our modified method. Based on the preliminary results, we decided to implement the modified strategy without whole-genome amplification (WGA) and combined it with three analytical software packages. Next, we conducted a prospective study with 824 samples. According to the indication for invasive tests, the D-karyo positive rates were 2.5% and 5.0%, respectively, in the screening positive group with NT ≥ 3.5 mm and the group with fetal abnormalities by ultrasound. D-karyo is a breakthrough modality that can detect submicroscopic CNVs ≥ 1.0 Mb accurately in only 10.5 h for 24 samples at a low cost. Implementing D-karyo as a prenatal rapid screening test will reduce unnecessary CMA and achieve more accurate prenatal genetic testing than G-banding.