Open-source Software Package Research Articles

Elastic response of trabecular bone under compression calculated using the firm and floppy boundary lattice element method

Micro-Finite Element analysis (μFEA) has become widely used in biomechanical research as a reliable tool for the prediction of bone mechanical properties within its microstructure such as apparent elastic modulus and strength. However, this method requires substantial computational resources and processing time. Here, we propose a computationally efficient alternative to FEA that can provide an accurate estimation of bone trabecular mechanical properties in a fast and quantitative way. A lattice element method (LEM) framework based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) open-source software package is employed to calculate the elastic response of trabecular bone cores. A novel procedure to handle pore-material boundaries is presented, referred to as the Firm and Floppy Boundary LEM (FFB-LEM). Our FFB-LEM calculations are compared to voxel- and geometry-based FEA benchmarks incorporating bovine and human trabecular bone cores imaged by micro Computed Tomography (μCT). Using 14 computer cores, the apparent elastic modulus calculation of a trabecular bone core from a μCT-based input with FFB-LEM required about 15 min, including conversion of the μCT data into a LAMMPS input file. In contrast, the FEA calculations on the same system including the mesh generation, required approximately 30 and 50 min for voxel- and geometry-based FEA, respectively. There were no statistically significant differences between FFB-LEM and voxel- or geometry-based FEA apparent elastic moduli (+24.3% or +7.41%, and +0.630% or -5.29% differences for bovine and human samples, respectively).

Synthetic and practical reconstructions of SST and seawater pH using the novel multiproxy SMITE method.

Geochemical proxies of sea surface temperature (SST) and seawater pH (pHsw) in scleractinian coral skeletons are valuable tools for reconstructing tropical climate variability. However, most coral skeletal SST and pHsw proxies are univariate methods that are limited in their capacity to circumvent non-climate-related variability. Here we present a novel multivariate method for reconstructing SST and pHsw from the geochemistry of coral skeletons. Our Scleractinian Multivariate Isotope and Trace Element (SMITE) method optimizes reconstruction skill by leveraging the covariance across an array of coral elemental and isotopic data with SST and pHsw. First, using a synthetic proxy experiment, we find that SMITE SST reconstruction statistics (correlation, accuracy, and precision) are insensitive to noise and variable calibration period lengths relative to Sr/Ca. While SMITE pHsw reconstruction statistics remain relative to δ11B throughout the same synthetic experiment, the magnitude of the long-term trend in pHsw is progressively lost under conditions of moderate-to-high analytical uncertainty. Next, we apply the SMITE method to an array of seven coral-based geochemical variables (B/Ca, δ11B, Li/Ca, Mg/Ca, Sr/Ca, U/Ca & Li/Mg) measured from two Bermudan Porites astreoides corals. Despite a <3.5 year calibration period, SMITE SST and pHsw estimates exhibit significantly better accuracy, precision, and correlation with their respective climate targets than the best single- and dual-proxy estimators. Furthermore, SMITE model parameters are highly reproducible between the two coral cores, indicating great potential for fossil applications (when preservation is high). The results shown here indicate that the SMITE method can outperform the most common coral-based SST and pHsw reconstructions methods to date, particularly in datasets with a large variety of geochemical variables. We therefore provide a list of recommendations and procedures for users to begin implementing the SMITE method as well as an open-source software package to facilitate dissemination of the SMITE method.

Understanding the origins of reversible and hysteretic pathways of adsorption phase transitions in metal-organic frameworks

Phase behavior of nanoconfined fluids adsorbed in metal–organic frameworks is of paramount importance for the design of advanced materials for energy and gas storage, separations, electrochemical devices, sensors, and drug delivery, as well as for the pore structure characterization. Phase transformations in adsorbed fluids often involve long-lasting metastable states and hysteresis that has been well-documented in gas adsorption–desorption and nonwetting fluid intrusion-extrusion experiments. However, theoretical prediction of the observed nanophase behavior remains a challenging problem. The mesoscopic canonical, or mesocanonical, ensemble (MCE) is devised to study the nanophase behavior under conditions of controlled fluctuations to stabilize metastable and labile states. Here, we implement and apply the MCE Monte Carlo (MCEMC) simulation scheme to predict the origins of reversible and hysteric adsorption phase transitions in a series of practical MOF materials, including IRMOF-1, ZIF-412, UiO-66, Cu-BTC, IRMOF-74-V, VII, and IX. The MCEMC method, called the gauge cell method, allows to produce Van der Waals type isotherms with distinctive swings around the phase transition regions. The constructed isotherms determine the positions of phase equilibrium and spinodals, as well as the nucleation barriers separating metastable states. We demonstrate the unique capabilities of the MCEMC method in quantitative predictions of experimental observations compared with the conventional grand canonical and canonical ensemble simulations. The MCEMC method is implemented in the open-source RASPA and LAMMPS software packages and recommended for studies of adsorption behavior and pore structure characterization of MOFs and other nanoporous materials.

GDPS: an open-source python-based software package for multi-GNSS data preprocessing

GDPS: an open-source python-based software package for multi-GNSS data preprocessing

Finite Elements with Switch Detection for numerical optimal control of nonsmooth dynamical systems with set-valued heaviside step functions

This paper develops high-accuracy methods for the numerical solution of optimal control problems subject to nonsmooth differential equations with set-valued Heaviside step functions. An important subclass of these systems are Filippov systems. By writing the Heaviside step function as the solution map of a linear program and using its optimality conditions, the initial nonsmooth system is rewritten into an equivalent Dynamic Complementarity System (DCS). The Finite Elements with Switch Detection (FESD) method (Nurkanović et al., 2024) was originally developed for Filippov systems transformed via Stewart’s reformulation into DCS (Stewart, 1990). This paper extends it to the above mentioned class of nonsmooth systems. The key ideas are to start with a standard Runge–Kutta method for the DCS and to let the integration step sizes to be degrees of freedom. Then, additional conditions are introduced to allow implicit but accurate switch detection and to remove possible spurious degrees of freedom when no switches occur. The theoretical properties of the FESD method are studied. The motivation for these developments is to obtain a computationally tractable formulation of nonsmooth optimal control problems. Numerical simulations and optimal control examples are used to illustrate the favorable properties of the proposed approach. All methods introduced in this paper are implemented in the open-source software package nosnoc (Nurkanović and Diehl, 2022).

Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model

BackgroundMachine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Society of Thoracic Surgeons (STS)-defined aortic zones. The purpose of this study was to establish a trained, automatic machine learning aortic zone segmentation model to facilitate performance of an aortic zone volumetric comparison between patients with auTBAD based on the rate of aortic growth. MethodsPatients with auTBAD and serial imaging were identified. For each patient, imaging characteristics from two computed tomography (CT) scans were analyzed: (1) the baseline CT angiography (CTA) at the index admission and (2) either the most recent surveillance CTA or the most recent CTA before an aortic intervention. Patients were stratified into two comparative groups based on aortic growth: rapid growth (diameter increase of ≥5 mm/year) and no or slow growth (diameter increase of <5 mm/year). Deidentified images were imported into an open source software package for medical image analysis and images were annotated based on SVS/STS criteria for aortic zones. Our model was trained using four-fold cross-validation. The segmentation output was used to calculate aortic zone volumes from each imaging study. ResultsOf 59 patients identified for inclusion, rapid growth was observed in 33 patients (56%) and no or slow growth was observed in 26 patients (44%). There were no differences in baseline demographics, comorbidities, admission mean arterial pressure, number of discharge antihypertensives, or high-risk imaging characteristics between groups (P > .05 for all). Median duration between baseline and interval CT was 1.07 years (interquartile range [IQR], 0.38-2.57). Postdischarge aortic intervention was performed in 13 patients (22%) at a mean of 1.5 ± 1.2 years, with no difference between the groups (P > .05). Among all patients, the largest relative percent increases in zone volumes over time were found in zone 4 (13.9%; IQR, −6.82 to 35.1) and zone 5 (13.4%; IQR, −7.78 to 37.9). There were no differences in baseline zone volumes between groups (P > .05 for all). The average Dice coefficient, a performance measure of the model output, was 0.73. Performance was best in zone 5 (0.84) and zone 9 (0.91). ConclusionsWe describe an automatic deep learning segmentation model incorporating SVS-defined aortic zones. The open source, trained model demonstrates concordance to the manually segmented aortas with the strongest performance in zones 5 and 9, providing a framework for further clinical applications. In our limited sample, there were no differences in baseline aortic zone volumes between patients with rapid growth and patients with no or slow growth.

Spectrum and extension of the inverse-Compton emission of the Crab Nebula from a combined Fermi-LAT and H.E.S.S. analysis

The Crab Nebula is a unique laboratory for studying the acceleration of electrons and positrons through their non-thermal radiation. Observations of very-high-energy γ rays from the Crab Nebula have provided important constraints for modelling its broadband emission. We present the first fully self-consistent analysis of the Crab Nebula’s γ-ray emission between 1 GeV and ∼100 TeV, that is, over five orders of magnitude in energy. Using the open-source software package GAMMAPY, we combined 11.4 yr of data from the Fermi Large Area Telescope and 80 h of High Energy Stereoscopic System (H.E.S.S.) data at the event level and provide a measurement of the spatial extension of the nebula and its energy spectrum. We find evidence for a shrinking of the nebula with increasing γ-ray energy. Furthermore, we fitted several phenomenological models to the measured data, finding that none of them can fully describe the spatial extension and the spectral energy distribution at the same time. Especially the extension measured at TeV energies appears too large when compared to the X-ray emission. Our measurements probe the structure of the magnetic field between the pulsar wind termination shock and the dust torus, and we conclude that the magnetic field strength decreases with increasing distance from the pulsar. We complement our study with a careful assessment of systematic uncertainties.

Кластеризация научных публикаций по морскому автономному надводному судовождению для выявления кластеров ключевых слов

An approach to structuring scientific publications is proposed using the example of scientific works on marine autonomous surface navigation, which allows for data mining with clustering and visualization of the main keywords and phrases related to the designated topic. The resource of the Russian scientific electronic library was used as a source for obtaining data eLIBRARY.RU. Information has been collected on 534 relevant scientific publications for the period from 2013 to the beginning of 2024, containing the title of the work, the year of publication, the list of authors and their affiliation, keywords and phrases, etc. A database for intellectual analysis has been formed, containing 1304 keywords or phrases indicated by the authors of scientific publications related to the selected topic. Data mining was performed using an open source software package for visualization and analysis of related data Gephi. The processing results are presented in the form of undirected graphs. The undirected graphs obtained are presented, and the characteristics of certain graphs for various kernel parameters are indicated. Clusters of keywords or phrases and connections between them have been identified, demonstrating current trends in the development of the chosen scientific field. With the advent of new scientific publications on marine autonomous surface navigation, the graphs will change, fixing new connections between the authors of scientific publications, key words and phrases. Such an approach to data processing may be useful for students, graduate students and researchers to identify a pool of keywords and phrases that need to be paid attention to when studying this topic.

Revisiting the Landscape Mosaic model.

The landscape mosaic model quantifies and maps the spatial juxtaposition of different land uses. It provides a landscape perspective of anthropic threats posed by agriculture and urban development, and the spatial-temporal shifting of the landscape mosaic indicates landscapes where anthropic intensity has changed. We use the U.S. Geological Survey provided National Land Cover Database (NLCD) for the years 2001 and 2021 to derive the landscape mosaic at five analysis scales. To improve earlier implementations of the model, we introduce the heatmap, a flexible scheme providing more thematic reporting opportunities and allowing for better quantitative summary reporting across analysis scales as well as for temporal trends. The results are exemplified at regional scale for the Atlanta metropolitan area. We use the improved model to investigate the land cover context over time and at different analysis scales and show how custom color tables detail different thematic features of the landscape mosaic, including the degree and change of anthropic intensity. We conclude with a discussion of potential applications in ecology, landscape planning, and restoration to illustrate the benefits of the revised landscape mosaic model. All assessment tools are now available in open-source software packages.

DC3DPAFEM: An efficient and accurate 3-D direct current resistivity anisotropic forward modeling software for complex geological settings

Nowadays, there is a growing trend that direct current (DC) field surveys are shifting towards challenging areas characterized by mountainous topography and electrical anisotropy. Given these complex geological settings, there is an urgent need for 3-D DC forward modeling software capable of effectively addressing large-scale problems and delivering accurate modeling results to interpret field data. However, most open-source software packages face certain limitations, such as the high numerical cost to handle complex surface topography, the lack of consideration for anisotropic conductivity, the absence of mesh refinement techniques to guarantee accuracy in forward modeling, and the lack of parallel computing techniques to solve large-scale problems. In this study, we develop an efficient and highly accurate 3-D DC anisotropic forward modeling software, namely DC3DPAFEM, using the adaptive finite element algorithm based on the unstructured tetrahedral mesh. Firstly, we construct a strong compatible boundary value problem (BVP) for 3-D anisotropic DC problems by adopting a specialized secondary potential approach to handle the surface topography efficiently. Then, we develop a goal-oriented adaptive mesh refinement (AMR) technique to ensure accurate forward modeling results, even with a coarse initial mesh. To ensure time and memory efficiency, we employ a robust conjugate gradient (CG) algorithm preconditioned by the algebraic multigrid (AMG) solver to solve the large-scale linear system of equations resulting from complex geological structures. We aim to investigate the performance of the AMG scheme in anisotropic DC cases. Furthermore, we incorporate the domain decomposition technique into the iterative solution scheme for further efficiency gains. This technique significantly improves computing efficiency for large-scale problems in parallel clusters. Finally, we conduct comprehensive performance tests for DC3DPAFEM using a two-layer anisotropic model and a 3-D complex model with undulating terrain. The results of both examples validate the accuracy of DC3DPAFEM, as they closely align with the analytical solutions and the solutions obtained from the existing 3-D DC forward modeling code. Compared to traditional direct solver MUMPS and ILU-preconditioned iterative solvers, DC3DPAFEM exhibits highly scalable performance for large-scale problems, offering significant advantages in terms of memory and time consumption. Overall, DC3DPAFEM demonstrates substantial advances in efficiency, accuracy, and practicality through a series of numerical examples. This open-source code provides an efficient and available tool for developing a 3-D DC inversion method that can deal with large-scale problems involving intricate topography and anisotropic media.

MISTER-T: An open-source software package for quantum optimal control of multi-electron systems on arbitrary geometries

We present an open-source software package, MISTER-T (Manipulating an Interacting System of Total Electrons in Real-Time), for the quantum optimal control of interacting electrons within a time-dependent Kohn-Sham formalism. In contrast to other implementations restricted to simple models on rectangular domains, our method enables quantum optimal control calculations for multi-electron systems (in the effective mass formulation) on nonuniform meshes with arbitrary two-dimensional cross-sectional geometries. Our approach is enabled by forward and backward propagator integration methods to evolve the Kohn-Sham equations with a pseudoskeleton decomposition algorithm for enhanced computational efficiency. We provide several examples of the versatility and efficiency of the MISTER-T code in handling complex geometries and quantum control mechanisms. The capabilities of the MISTER-T code provide insight into the implications of varying propagation times and local control mechanisms to understand a variety of strategies for manipulating electron dynamics in these complex systems. Program summaryProgram Title: MISTER-TCPC Library link to program files:https://doi.org/10.17632/psymy4ddnw.1Licensing provisions: GNU General Public License 3Programming language: MATLABSupplementary material: animated movies of total electron densities under the influence of optimal control fields for (1) an asymmetric double-well potential for long propagation times, (2) an asymmetric double-well potential for short propagation times, and (3) a triple-well potential with a position-dependent effective mass.Nature of problem: The MISTER-T code solves quantum optimal control problems for interacting electrons within a time-dependent Kohn-Sham formalism. It can handle two-dimensional systems with arbitrary cross-sectional geometries within the effective mass formulation. The user-friendly code uses forward and backward propagator integration methods to evolve the Kohn-Sham equations with a pseudoskeleton decomposition algorithm for enhanced computational efficiency.Solution method: iterative solution of the quantum optimal control equations using finite element methods, effective mass formulation, pseudoskeleton decomposition, sparse matrix linear algebra, and nonuniform fast Fourier transforms.

Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3

Abstract. Systematic, routine, and comprehensive evaluation of Earth system models (ESMs) facilitates benchmarking improvement across model generations and identifying the strengths and weaknesses of different model configurations. By gauging the consistency between models and observations, this endeavor is becoming increasingly necessary to objectively synthesize the thousands of simulations contributed to the Coupled Model Intercomparison Project (CMIP) to date. The Program for Climate Model Diagnosis and Intercomparison (PCMDI) Metrics Package (PMP) is an open-source Python software package that provides quick-look objective comparisons of ESMs with one another and with observations. The comparisons include metrics of large- to global-scale climatologies, tropical inter-annual and intra-seasonal variability modes such as the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO), extratropical modes of variability, regional monsoons, cloud radiative feedbacks, and high-frequency characteristics of simulated precipitation, including its extremes. The PMP comparison results are produced using all model simulations contributed to CMIP6 and earlier CMIP phases. An important objective of the PMP is to document the performance of ESMs participating in the recent phases of CMIP, together with providing version-controlled information for all datasets, software packages, and analysis codes being used in the evaluation process. Among other purposes, this also enables modeling groups to assess performance changes during the ESM development cycle in the context of the error distribution of the multi-model ensemble. Quantitative model evaluation provided by the PMP can assist modelers in their development priorities. In this paper, we provide an overview of the PMP, including its latest capabilities, and discuss its future direction.

The coordination network toolkit: a framework for detecting and analysing coordinated behaviour on social media

This paper introduces and evaluates the Coordination Network Toolkit, an open-source software package and methodological framework designed to detect and analyse coordinated behaviour on social media platforms. As the dynamics of online communication continue to evolve, coordination analysis has emerged as an important field of study with significant implications for understanding online influence, digital astroturfing, and online activism. Recognising the absence of a comprehensive, open-source tool for constructing coordination networks, our approach fills this gap, catering to multiple behaviors across diverse social media platforms. Our approach synthesises and significantly enhances various methods to provide a methodological framework for ‘multi-behaviour’ coordination detection, utilising weighted, directed multigraphs to capture intricate coordination dynamics. We evaluate our approach by revisiting a case study of the 2020 #ReopenAmerica Covid protest movement on Twitter. The paper concludes with a set of recommendations for future work, emphasising the need for a tailored statistical framework for coordination analysis and a deeper exploration into the motives behind online coordination.

Human exposure to formaldehyde and health risk assessment: a 46-year systematic literature review.

After confirming that formaldehyde (FA) is carcinogenic, many studies were conducted in different countries to investigate this finding. Therefore, according to the dispersion of related studies, a bibliometric review of the current literature was performed with the aim of better understanding the exposure to FA and the resulting health risk, for the first time, using the Scopus database and the two open-source software packages, Bibliometrix R package. After screening the documents in Excel, the data was analyzed based on three aspects including performance analysis, conceptual structure, and intellectual structure, and the results were presented in tables and diagrams. A total of 468 documents were analyzed over period 1977-2023, in which 1956 authors from 56 countries participated. The number of scientific publications has grown significantly from 1977 (n = 1) to 2022 (n = 19). Zhang Y., from the Yale School of Public Health (USA), was identified as the most impactful author in this field. The Science of the Total Environment journal was identified as the main source of articles related to exposure to formaldehyde by publishing 25 studies. The United States and China were the most active countries with the most international collaboration. The main topics investigated during these 46years included "formaldehyde" and "health risk assessment", which have taken new directions in recent years with the emergence of the keyword "asthma". The present study provides a comprehensive view of the growth and evolution of studies related to formaldehyde and the resulting health risks, which can provide a better understanding of existing research gaps and new and emerging issues.

Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data

Background Machine learning and AI promise to revolutionize the way we leverage medical imaging data for improving care but require large datasets to train computational models that can be implemented in clinical practice. However, processing large and complex medical imaging datasets remains an open challenge. Methods To address this issue, we developed Med-ImageTools, a new Python open-source software package to automate data curation and processing while allowing researchers to share their data processing configurations more easily, lowering the barrier for other researchers to reproduce published works. Use cases We have demonstrated the efficiency of Med-ImageTools across three different datasets, resulting in significantly reduced processing times. Conclusions The AutoPipeline feature will improve the accessibility of raw clinical datasets on public archives, such as the Cancer Imaging Archive (TCIA), the largest public repository of cancer imaging, allowing machine learning researchers to process analysis-ready formats without requiring deep domain knowledge.

Разработка модуля для управления моделированием системы двух сжимаемых жидких фаз с одной дисперсной фазой на базе платформы OpenFOAM

The purpose of the presented research is to refine the initial release of the graphical shell for the OpenFOAM package by designing and connecting an additional module focused on numerical experiments using the twoPhaseEulerFoam solver in the field of modeling problems in continuum mechanics. This module, unlike existing analogue applications, has the status of an open source software product, does not require the purchase of maintenance services, and has a Russian-language interface. In the presented software, to simplify further support and modification, the source code of the external part of the application is separated from the code that provides the operating logic. The key original approaches proposed by the author also include a subsystem for serializing design parameters, which allows you to convert the parameters of a design case into json and csv objects and perform the reverse process. This allows the user to switch between different parameter sets for one design case. In addition, it is worth emphasizing the presence in the created software module of a mechanism for checking the completeness of the design case before starting the numerical experiment. Some features of the solver and the principles of its use in preparing calculation cases are considered. The purpose of the study was determined and a list of required tasks was compiled. The selected technology stack is described, as well as development aids. A process diagram is provided to demonstrate how the application works, along with a description of each step. The results of the study were tested using the example of one of the fundamental problems of continuum mechanics and are presented in the form of an updated version of the graphical shell, publicly available on the GitHub resource. Based on the results of the study, the effectiveness of the selected technology stack for achieving development goals was confirmed, and the completed tasks were noted. The practical significance of the results is formulated, expressed in the potential saving of working time for engineers and researchers, minimizing modeling errors and simplifying the process of preparing a design case.

Hyper Illumination of Exoplanets: Analytical and Numerical Approaches

This work describes the illumination of exoplanets whose orbits are close enough to their host star that the finite angular size of their host star causes hyper illumination, in which more than 50% of the planet receives light. Such exoplanets include the hot Jupiters KELT-9 b (64.5% illuminated) and Kepler-91 b (69.6% illuminated). We describe the geometry of three primary illumination zones: the fully illuminated zone, penumbral zone, and unilluminated zone. The integrals required to determine the incident radiation as a function of position from the substellar point on the exoplanet are explained and derived, and the analytical solution is presented within the fully illuminated zone. We find that the illumination predicted by our model is greater at the substellar point than the typical plane-parallel ray model used would suggest. In addition, it is greater within the region of the penumbral zone extending into the antistellar side of the exoplanet. Finally, we compare our model to that used in starry, an open-source software package used to create albedo maps. It appears that starry may be overestimating the illumination of closely orbiting exoplanets because the foreshortening of the area element of the host star is not included in its calculation.

Sniping at web applications to discover input-handling vulnerabilities

Web applications play a crucial role in modern businesses, offering various services and often exposing sensitive data that can be enticing to attackers. As a result, there is a growing interest in finding innovative approaches for discovering vulnerabilities in web applications. In the evolving landscape of web security, the realm of fuzz testing has garnered substantial attention for its effectiveness in identifying vulnerabilities. However, existing literature has often underemphasized the nuances of web-centric fuzzing methodologies. This article presents a comprehensive exploration of fuzzing techniques specifically tailored to web applications, addressing the gap in the current research. Our work presents a holistic perspective on web-centric fuzzing, introduces a modular architecture that improves fuzzing effectiveness, demonstrates the reusability of certain fuzzing steps, and offers an open-source software package for the broader security community. By addressing these key contributions, we aim to facilitate advancements in web application security, empower researchers to explore new fuzzing techniques, and ultimately enhance the overall cybersecurity landscape.

SHORYUKEN: An open-source software package for calculating nonlocal exchange interactions in nanowires

We present the open-source software package, SHORYUKEN (Streamlined High-level Operations in Real-space to Yield, Understand, and Keep Exchange in Nanowires), for calculating nonlocal exchange interactions in nanowires with arbitrary geometries, sizes, doping densities, and compositions. In addition to enabling new calculations of nonlocal exchange, the SHORYUKEN software package is a significant enhancement of our previous HADOKEN code and includes new algorithmic improvements as well as an improved treatment of surface states for nanowires with intrinsic polarization. Our calculations show that the inclusion of nonlocal exchange can have significant effects on the eigenenergy spectrum, number of occupied states, and distribution of electrons within these nanosystems. The SHORYUKEN software package is the first open-source code for calculating nonlocal exchange to predict electron gas formation in nanowire systems with arbitrary cross-sectional geometries. Program summaryProgram Title: SHORYUKENCPC Library link to program files:https://doi.org/10.17632/f77p84pbcv.1Licensing provisions: GNU General Public License 3Programming language: MATLABNature of problem: The SHORYUKEN code calculates nonlocal exchange interactions of electrons in nanowires by solving modified nonlocal exchange and Poisson-like equations self-consistently on a finite element grid. The software package is capable of performing calculations for core-multishell nanowires with arbitrary cross-sectional shapes.Solution method: iterative solution of the Schrödinger-Poisson equations with nonlocal exchange using finite element methods and sparse matrix linear algebra

An easy to use tool for the analysis of subcellular mRNA transcript colocalisation in smFISH data

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of programming expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for computational image analysis expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation in the expression of Cd4 by T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei. These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis.