Input Files Research Articles

Detection of colinear blocks and synteny and evolutionary analyses based on utilization of MCScanX.

As different taxa evolve, gene order often changes slowly enough that chromosomal 'blocks' with conserved gene orders (synteny) are discernible. The MCScanX toolkit ( https://github.com/wyp1125/MCScanX ) was published in 2012 as freely available software for the detection of such 'colinear blocks' and subsequent synteny and evolutionary analyses based on genome-wide gene location and protein sequence information. Owing to its simplicity and high efficiency for colinear block detection, MCScanX provides a powerful tool for conducting diverse synteny and evolutionary analyses. Moreover, the detection of colinear blocks has been embraced as an integral step for pangenome graph construction. Here, new application trends of MCScanX are explored, striving to better connect this increasingly used tool to other tools and accelerate insight generation from exponentially growing sequence data. We provide a detailed protocol that covers how to install MCScanX on diverse platforms, tune parameters, prepare input files from data from the National Center for Biotechnology Information, run MCScanX and its visualization and evolutionary analysis tools, and connect MCScanX with external tools, including MCScanX-transposed, Circos and SynVisio. This protocol is easily implemented by users with minimal computational background and is adaptable to new data of interest to them. The data and utility programs for this protocol can be obtained from http://bdx-consulting.com/mcscanx-protocol .

UrsaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data.

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.

Elementary flow mapping across life cycle inventory data systems: A case study for data interoperability under the Global Life Cycle Assessment Data Access (GLAD) initiative

PurposeLimited availability of life cycle assessment (LCA) data poses a significant challenge to its mainstream adoption, rendering it a central issue within the LCA community. The Global LCA Data Access (GLAD) network aims to increase the accessibility and interoperability of LCA data and offers benefits for different use cases. GLAD is an intergovernmental collaboration involving different stakeholders organized into working groups. The GLAD Nomenclature Working Group (NWG) developed a procedure and a set of criteria to map elementary flows among major nomenclature systems and reviewed bidirectional mappings. This paper provides an overview of the methodological approach followed by the NWG to achieve the resulting mapping files.MethodsThe mapping procedure involves several steps of flow and compartment matches and bilateral review. The procedure is supported by an ad hoc software tool called the “GLAD Mapper Tool” developed with the NWG and which is made available for free by the European Commission. The input files for the procedure are the properly formatted source and target flow lists and a file containing the mapping criteria. The four nomenclature systems mapped are those used in ecoinvent, Environmental Footprint, IDEA, and the U.S. Federal LCA Commons. The procedure included representatives from each of these nomenclature systems to ensure a multilateral agreement on the approach to verifying and assessing the quality of the results. The iterative mapping process included different stages of bidirectional reviews to achieve a balance between mapping coverage (i.e., percentage of source flows covered by the target list) and accuracy.Results and discussionThe mapping procedure proved to be an efficient approach for LCA practitioners in mappings between different nomenclature systems. After a relatively low number of iterations, mapping coverages higher than 90% were achieved, which is driven by the availability of unique substances (flow names) and the granularity of environmental compartments. Overall, none of the four flow lists achieved full coverage and the use of approximated matches (proxy matches) for environmental compartments and/or substances was necessary when a perfect matches between flows were not possible.ConclusionsThe NWG’s mapping activities may serve as a starting point towards defining a central hub for mapping impact assessment methods and datasets, improving data accessibility and interoperability for the LCA community as a step towards defining a unified nomenclature system. The GLAD mapping approach is open and transparent. The approach fosters traceability in the mapping process and offers the potential for greater interoperability across the LCA community, underlining the commitment to openness and collaboration.

SWAT + input data preparation in a scripted workflow: SWATprepR

Input data collection, quality assurance and preparation are central but time_consuming steps in environmental modeling. Errors due to manual processing of model input data can result in an incorrect representation of an environmental system and may consequently lead to implausible model simulations. Correct input data preparation and thorough quality check at an early stage of the model setup procedure are essential to build confidence in model simulation results. Typically, in environmental model applications, many steps in the input data preparation phase have to be repeated with the inflow of new, additional or corrected data. In this study, we selected the widely used SWAT + ecohydrological model as an illustrative example to investigate challenges related to input data preparation. To assist in these tasks, we developed an R package named SWATprepR, which provides functions for typical and repeating SWAT + model input data preparation tasks. The package supports the preparation of weather input files, atmospheric deposition, soil parameters, crop rotations, and observed (control or calibration) data, to name a few, presently with focus on European applications. The SWATprepR functions are integrated in R script workflows and can help SWAT + modelers to avoid repetitive tasks, secure reproducibility and transparently document the data processing steps. Application of the package is illustrated with a test case of a SWAT + model for a small catchment in central Poland.

HYDRODYNAMIC ASSESSMENT ALONG THE COAST OF TANJUNG SEDELI, MALAYSIA

Tidal influence plays a significant role in coastal hydrodynamics as the impact may lead to coastal erosion. Tanjung Sedeli located on the southern coast of Malaysia is exposed to low tidal issues which disrupts the navigation of local fishermen due to the shallow river mouth in the area. This study presents the hydrodynamic processes along the shoreline of Tanjung Sedeli. BLUEKENUE was used as the pre-processor to create a bathymetry file and perform mesh generation to set up the initial model boundary which functions as input files for numerical study. TELEMAC2D further processes the hydrodynamic data (tides and currents), calibrated, and validated with the measured field data collected between 24th September to 6th October 2020 covering both spring and neap tide conditions. The nature of tides in the area was mainly mixed tides, predominantly semidiurnal tides. Modelled hydrodynamic values show good conformity with field measurements with an error of 1.4% for water level values, 10.6% and 20o for current speed and direction respectively. Water flows north into the estuary during spring tide with maximum velocity is 0.756m/s surrounding the river mouth and Pulau Tagal. Low velocity values were recorded at the left bank of the river (0.028 m/s) and Pulau Tagal (0.085 m/s) during spring tide. This study provides information on current hydrodynamic condition of the study area.

Method of exact solutions code verification of a superelastic constitutive model in a commercial finite element solver

The superelastic constitutive model implemented in the commercial finite element code ABAQUS is verified using the method of exact solutions (MES). An analytical solution for uniaxial strain is first developed under monotonic loading. Numerical simulations are then performed, and simulation predictions are compared to the exact analytical solutions. Results reveal the superelasticity model agrees with the analytical solution to within one ten-thousandth of a percent (0.0001%) or less for stress and strain quantities of interest when using displacement-driven boundary conditions. Full derivation of the analytical solution is provided in an Appendix, and simulation input files and post-processing scripts are provided as supplemental material.

PRD: An integrated database solution for medicinal and aromatic plant research in pharmaceuticals and toxicology

Research in medicinal and aromatic science laboratories often involves isolation, identification, and characterization of bioactive compounds from natural sources, particularly those with potential applications in medicine and healthcare. A wide range of analytical techniques, including chromatography, spectroscopy, in vitro – in vivo bioassays, and also toxicity tests to investigate the chemical and biological properties with the safeties of these compounds, and to understand how they interact with biological systems at the molecular level.However, many different species, and different test results creates a great challenge to keep track of results even within one research laboratory.In this study, we introduce a practical offline database and software program for recording medicinal and aromatic science experimental results in laboratories. The program uses a familiar input file, (Microsoft Excel), so users do not need to learn a new software. By implementing a standardized data recording system and evidence file for each plant, even if the same plant has different synonyms, different parts, and originates from different regions, all data can be collected and accessed through a single platform. This system allows for the integration of experimental results, including chromatograms, spectra, images, etc., and facilitates data management and analysis.The presented database provides a significant advantage by allowing immediate access to pertinent information regarding laboratory experimental results during collaborative efforts with diverse research groups and departments. It’s always-on data archiving features will prevent any experiment replications and also eliminates the potential loss of time during the data evaluation process.

Compromise in Docking Power of Liganded Crystal Structures of Mpro SARS-CoV-2 Surpasses 90% Success Rate.

Herein, we present the capacity of three different molecular docking programs (AutoDock, AutoDock Vina, and PLANTS) to identify and reproduce the binding modes of ligands present in 247 covalent and 169 noncovalent complex crystal structures of the severe acute respiratory syndrome coronavirus 2 main protease (Mpro). The compromise in docking power is evaluated with respect to their ability to generate poses similar to the crystal structure binding mode (heavy atoms' root-mean-square deviation < 2 Å) and their ability to recognize the native binding mode with an included compensation for the scoring function error. Noncovalently bound inhibitors are best modeled by AutoDock Vina (90.6% success rate in the active site), while the most relevant results for covalently bound inhibitors are produced by PLANTS (93.0%). AutoDock shows acceptable performance for both types of ligands, 81.1 and 76.4% for noncovalent and covalent complexes, respectively. All three programs manifest worse performance when reproducing surface-bound ligands. Comparison with other works illustrates the importance of crystal structure processing (12% of noncovalent and 26% of covalent ligands had to be manually corrected), proper sampling protocol settings, and inclusion of root-mean-square deviation (RMSD)/scoring function error compensations in crystal structure pose identification. Results are analyzed with respect to a clustering scheme of the noncovalently bound ligands and the chemical reaction type of the covalent ligand bound to the Cys145 residue. A comparison of screening power based on the docking scores of noncovalent ligands from the crystal structures with a "Directory of Useful Decoys, Enhanced" set of known decoys (6562 compounds) and ZINC15 in vivo subset (60,394 compounds) is provided. Ligand and protein input files are provided for future benchmarking purposes.

ERCS24: An updated version of the ERCS08 program for calculations of the cross sections for atomic electron removal based on the ECPSSR theory and its variants

ERCS24: An updated version of the ERCS08 program for calculations of the cross sections for atomic electron removal based on the ECPSSR theory and its variants

ERSN-OpenMC-Py: A python-based open-source software for OpenMC Monte Carlo code

The graphical user interface is a key element in facilitating the use of complex simulation software. This project describes the development of a graphical user interface called “ERSN-OpenMC-Py” for an existing neutron simulation code, OpenMC. The main goal is to make simulation more accessible to a wider audience by providing a user-friendly and intuitive user interface. The process of developing the graphical user interface is described in detail, including the different stages of development such as user interface design, user interface implementation, and user interface integration with the OpenMC simulation code. The development tools used, such as Python3 and PyQt5, are also explained. The user interface allows the user to control the simulation parameters and interact with the simulation results. Key features of the user interface include visualization of simulation results, modification of simulation parameters, saving and loading simulation configurations, as well as managing output files. The end result is a functional user interface that allows users to easily visualize simulation results and control simulation parameters in an intuitive manner. This user interface also provides a better user experience for non-programming experts who wish to use the simulation code for their own projects. Program summaryProgram Title: ERSN-OpenMC-Py, version 1.0CPC Library link to program files:https://doi.org/10.17632/83xrdht7mz.1Developer's repository link:https://github.com/mohamedlahdour/ERSN-OpenMC-PyLicensing provisions: GPLv2Programming language: Python 3External routines/libraries: NumPy, Matplotlib, PyQt5Nature of problem: The program is designed to be utilized in the everyday workflow for tasks such as preparing input files for the OpenMC code and analyzing the resulting calculations.Solution method: The graphical user interface of the OpenMC is created using PyQt5. Figures are plotted by means of matplotlib library.

An updated fluorescence emission model of CO+ for cometary science

ABSTRACT A new CO$^+$ fluorescence emission model for analysing cometary spectra is presented herein. Accurate line lists are produced using the PGOPHER software for all transitions between the three electronic states (X $^2\Sigma$, A $^2\Pi$, B $^2\Sigma$) with vibrational states up to $v_\textrm {max} = 9, 8, 6$, respectively, and maximum rotational states with rotational quantum numbers $N\le 20$. As a result of improved molecular constants and theoretical transition rates, an expansion of the utilized solar spectrum into the infrared, and the substantial expansion of the included rovibronic states, the model provides an update of the fluorescence efficiencies of the CO$^+$ cation. The dependencies on heliocentric velocity and distance are explicitly included. We report, for the first time, quantification of the fluorescence efficiencies for the ground state rovibrational transitions of CO$^+$ and predict the positions and relative intensities of CO$^+$ lines in windows accessible to both ground- and space-based observatories. The computed fluorescence efficiencies show excellent agreement with UV/optical observations of both C/2016 R2 (PanSTARRS) and 29P/Schwassmann-Wachmann 1. The updated fluorescence efficiencies allow for revised N$_2$/CO abundances for comets 1P/Halley, C/1987 P1 (Bradfield), and C/2016 R2 (PanSTARRS), which can change by up to 30 per cent when accounting for recent improvements to CO$^+$ and N$_2^+$ fluorescence efficiencies. The model code, input files, and fluorescence efficiencies are publicly available and distributed on permanent archives for future uses in cometary analyses.

Male Pedigree Toolbox: A Versatile Software for Y-STR Data Analyses.

Y-chromosomal short tandem repeats (Y-STRs) are widely used in forensic, genealogical, and population genetics. With the recent increase in the number of rapidly mutating (RM) Y-STRs, an unprecedented level of male differentiation can be achieved, widening and improving the applications of Y-STRs in various fields, including forensics. The growing complexity of Y-STR data increases the need for automated data analyses, but dedicated software tools are scarce. To address this, we present the Male Pedigree Toolbox (MPT), a software tool for the automated analysis of Y-STR data in the context of patrilineal genealogical relationships. The MPT can estimate mutation rates and male relative differentiation rates from input Y-STR pedigree data. It can aid in determining ancestral haplotypes within a pedigree and visualize the genetic variation within pedigrees in all branches of family trees. Additionally, it can provide probabilistic classifications using machine learning, helping to establish or prove the structure of the pedigree and the level of relatedness between males, even for closely related individuals with highly similar haplotypes. The tool is flexible and easy to use and can be adjusted to any set of Y-STR markers by modifying the intuitive input file formats. We introduce the MPT software tool v1.0 and make it publicly available with the goal of encouraging and supporting forensic, genealogical, and other geneticists in utilizing the full potential of Y-STRs for both research purposes and practical applications, including criminal casework.

UKRmol-scripts: A Perl-based system for the automated operation of the photoionization and electron/positron scattering suite UKRmol+

UKRmol-scripts is a set of Perl scripts to automatically run the UKRmol+ codes, a complex software suite based on the R-matrix method to model fixed-nuclei photoionization and electron- and positron-scattering for polyatomic molecules. Starting with several basic parameters, the scripts operatively produce all necessary input files and run all codes for electronic structure and scattering calculations as well as gather the more frequently required outputs. The scripts provide a simple way to run such calculations for many molecular geometries concurrently and collect the resulting data for easier post-processing and visualization. We describe the structure of the scripts and the input parameters as well as provide examples for photoionization and electron and positron collisions with molecules. The codes are freely available from Zenodo. Program summaryProgram Title: UKRmol-scriptsCPC Library link to program files:https://doi.org/10.17632/cpvc2473pt.1Developer's repository link:https://gitlab.com/Uk-amor/UKRMol/UKRmol-scriptsLicensing provisions: GPLv3Programming language: PerlNature of problem: Performing ab initio photoionization and low energy electron- and positron-scattering on polyatomic molecules requires selecting and setting a significant number of input parameters in order to model the physics in a numerically accurate way. These scripts streamline setting up and analyzing calculations based on the R-matrix method [1] using the UKRmol+ suite [2].Solution method: The scripts provide automatic generation of input files and execution of programs from the UKRmol+ suite [2] using a number of parameters that describe both physical models and machine-dependent settings, and also outputs of the previous programs in the suite which are automatically read and analyzed. The resulting output files are then post-processed to collect target and scattering data for further analysis and simple plotting.Additional comments including restrictions and unusual features: The scripts should be used with releases 3.2 of UKRmol-in and UKRmol-out [3] although they are compatible with earlier versions.

DendroX: multi-level multi-cluster selection in dendrograms

BackgroundCluster heatmaps are widely used in biology and other fields to uncover clustering patterns in data matrices. Most cluster heatmap packages provide utility functions to divide the dendrograms at a certain level to obtain clusters, but it is often difficult to locate the appropriate cut in the dendrogram to obtain the clusters seen in the heatmap or computed by a statistical method. Multiple cuts are required if the clusters locate at different levels in the dendrogram.ResultsWe developed DendroX, a web app that provides interactive visualization of a dendrogram where users can divide the dendrogram at any level and in any number of clusters and pass the labels of the identified clusters for functional analysis. Helper functions are provided to extract linkage matrices from cluster heatmap objects in R or Python to serve as input to the app. A graphic user interface was also developed to help prepare input files for DendroX from data matrices stored in delimited text files. The app is scalable and has been tested on dendrograms with tens of thousands of leaf nodes. As a case study, we clustered the gene expression signatures of 297 bioactive chemical compounds in the LINCS L1000 dataset and visualized them in DendroX. Seventeen biologically meaningful clusters were identified based on the structure of the dendrogram and the expression patterns in the heatmap. We found that one of the clusters consisting of mostly naturally occurring compounds is not previously reported and has its members sharing broad anticancer, anti-inflammatory and antioxidant activities.ConclusionsDendroX solves the problem of matching visually and computationally determined clusters in a cluster heatmap and helps users navigate among different parts of a dendrogram. The identification of a cluster of naturally occurring compounds with shared bioactivities implicates a convergence of biological effects through divergent mechanisms.

Text Summarization Using NLP

Abstract: This Project represents the work associated with Text Summarization. In this paper, we present a framework for summarizing the massive facts. The proposed framework depends on highlight extraction from internet, using each morphological element and semantic data. Presently, in which large facts is available on the internet, it's far maximum important to offer the improved approaches to extract the statistics quickly and most successfully. It may be very hard for human beings to manually extract the precis of a large document of text. There are lots of text substances to be had on the internet. So, there's a hassle of looking for related files from the quantity of documents to be had and absorbing associated statistics from it. In essence to determine out the previous issues, the automated textual content summarization could be very a whole lot essential. Text Summarization is the method of figuring out the most vital and significant information in a input report or set of related input files and compressing all the inputs into a shorter version preserving its normal goals.

GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system

Abstract. A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelized Large-Eddy Simulation (PALM) model system. PALM is a community-driven large-eddy simulation model for atmospheric and environmental research. Throughout PALM's 20-year development, research interests have been increasing in its application to realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, geospatial data availability and quality are highly variable and inconsistent. Currently, the geospatial static input generation tools in the PALM community heavily rely on users for data acquisition and pre-processing. New PALM users face large obstacles, including significant time commitments, to gain the knowledge needed to be able to pre-process geospatial data for PALM. Expertise beyond atmospheric and environmental research is frequently needed to understand the data sets required by PALM. Here, we present GEO4PALM, which is a free and open-source tool. GEO4PALM helps users generate PALM static input files with a simple, homogenised, and standardised process. GEO4PALM is compatible with geospatial data obtained from any source, provided that the data sets comply with standard geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available, with several data sets having the finest resolution of 1 m. In addition, GEO4PALM provides a graphical user interface (GUI) for PALM domain configuration and visualisation. Two application examples demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany, and Ōtautahi / Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting. The wide applicability of GEO4PALM makes PALM more accessible to a wider user base in the scientific community.

The shortest path method (SPM) webserver for computational enzyme design.

SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme structure and dynamics. The server is built on top of the DynaComm.py code and enables the calculation and visualization of the SPM pathways. SPMweb is easy-to-use as it only requires three input files: the three-dimensional structure of the protein of interest, and the two matrices (distance and correlation) previously computed from a Molecular Dynamics simulation. We provide in this publication information on how to generate the files for SPM construction even for non-expert users and discuss the most relevant parameters that can be modified. The tool is extremely fast (it takes less than one minute per job), thus allowing the rapid identification of distal positions connected to the active site pocket of the enzyme. SPM applications expand from computational enzyme design, especially if combined with other tools to identify the preferred substitution at the identified position, but also to rationalizing allosteric regulation, and even cryptic pocket identification for drug discovery. The simple user interface and setup make the SPM tool accessible to the whole scientific community. SPMweb is freely available for academia at http://spmosuna.com/.

MLatom 3: A Platform for Machine Learning-Enhanced Computational Chemistry Simulations and Workflows.

Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framework for designing custom workflows. MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows. This open-source package provides plenty of choice to the users who can run simulations with the command-line options, input files, or with scripts using MLatom as a Python package, both on their computers and on the online XACS cloud computing service at XACScloud.com. Computational chemists can calculate energies and thermochemical properties, optimize geometries, run molecular and quantum dynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, and two-photon absorption spectra with ML, quantum mechanical, and combined models. The users can choose from an extensive library of methods containing pretrained ML models and quantum mechanical approximations such as AIQM1 approaching coupled-cluster accuracy. The developers can build their own models using various ML algorithms. The great flexibility of MLatom is largely due to the extensive use of the interfaces to many state-of-the-art software packages and libraries.

Phbuilder: A Tool for Efficiently Setting up Constant pH Molecular Dynamics Simulations in GROMACS.

Constant pH molecular dynamics (MD) is a powerful technique that allows the protonation state of residues to change dynamically, thereby enabling the study of pH dependence in a manner that has not been possible before. Recently, a constant pH implementation was incorporated into the GROMACS MD package. Although this implementation provides good accuracy and performance, manual modification and the preparation of simulation input files are required, which can be complicated, tedious, and prone to errors. To simplify and automate the setup process, we present phbuilder, a tool that automatically prepares constant pH MD simulations for GROMACS by modifying the input structure and topology as well as generating the necessary parameter files. phbuilder can prepare constant pH simulations from both initial structures and existing simulation systems, and it also provides functionality for performing titrations and single-site parametrizations of new titratable group types. The tool is freely available at www.gitlab.com/gromacs-constantph. We anticipate that phbuilder will make constant pH simulations easier to set up, thereby making them more accessible to the GROMACS user community.

H-wave – A Python package for the Hartree-Fock approximation and the random phase approximation

H-wave is an open-source software package for performing the Hartree–Fock approximation (HFA) and random phase approximation (RPA) for a wide range of Hamiltonians of interacting fermionic systems. In HFA calculations, H-wave examines the stability of several symmetry-broken phases, such as anti-ferromagnetic and charge-ordered phases, in the given Hamiltonians at zero and finite temperatures. Furthermore, H-wave calculates the dynamical susceptibilities using RPA to examine the instability toward the symmetry-broken phases. By preparing a simple input file for specifying the Hamiltonians, users can perform HFA and RPA for standard Hamiltonians in condensed matter physics, such as the Hubbard model and its extensions. Additionally, users can use a Wannier90-like format to specify fermionic Hamiltonians. A Wannier90 format is implemented in RESPACK to derive ab initio Hamiltonians for solids. HFA and RPA for the ab initio Hamiltonians can be easily performed using H-wave. In this paper, we first explain the basis of HFA and RPA, and the basic usage of H-wave, including download and installation. Thereafter, the input file formats implemented in H-wave, including the Wannier90-like format for specifying the interacting fermionic Hamiltonians, are discussed. Finally, we present several examples of H-wave such as zero-temperature HFA calculations for the extended Hubbard model on a square lattice, finite-temperature HFA calculations for the Hubbard model on a cubic lattice, and RPA in the extended Hubbard model on a square lattice. Program summaryProgram Title:H-waveCPC Library link to program files:https://doi.org/10.17632/9gr6pxhfjm.1Developer's repository link:https://github.com/issp-center-dev/H-waveCode Ocean capsule:https://codeocean.com/capsule/6875177Licensing provisions: GNU General Public License version 3Programming language: Python3External routines/libraries: NumPy, SciPy, Tomli, Requests.Nature of problem: Physical properties of strongly correlated electrons are examined such as ground state phase structure and response functions at zero and finite temperatures.Solution method: Calculations based on the unrestricted Hartree-Fock approximation and the random phase approximation are performed for the quantum lattice models such as the Hubbard model and its extensions.