SoftwareXPub Date : 2025-09-17DOI: 10.1016/j.softx.2025.102367
Han Li, Yujie Xu, Tianzhen Hong
{"title":"EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling","authors":"Han Li, Yujie Xu, Tianzhen Hong","doi":"10.1016/j.softx.2025.102367","DOIUrl":"10.1016/j.softx.2025.102367","url":null,"abstract":"<div><div>Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"32 ","pages":"Article 102367"},"PeriodicalIF":2.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FQSHA: An open-source Python software for fault-based seismic hazard assessment","authors":"Nasrin Tavakolizadeh , Hamzeh Mohammadigheymasi , Nuno Pombo","doi":"10.1016/j.softx.2025.102339","DOIUrl":"10.1016/j.softx.2025.102339","url":null,"abstract":"<div><div>The PyQt framework facilitates the development of desktop applications, offering an effective environment for implementing scientific algorithms while leveraging the flexibility of Python. In this paper, we introduce FQSHA, a PyQt5-based application designed to streamline the workflow of fault-based Seismic Activity Rate (SAR) calculation and seismic hazard assessment. The primary aim is to provide a unified and user-friendly interface that makes these processes more accessible. FQSHA enables users to perform hazard calculations and map the results from scratch using minimal input data and requiring only basic knowledge of hazard computation engines. The SAR calculation core (FaultQuake) is seamlessly integrated with the hazard assessment engine (OpenQuake), offering additional flexibility to customize input parameters for hazard analysis. This integration supports an end-to-end workflow within a single software utilizing a user-friendly GUI. We present the architecture of FQSHA and demonstrate its capabilities through a hands-on example, which is publicly available on GitHub.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"32 ","pages":"Article 102339"},"PeriodicalIF":2.4,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145098113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-09-15DOI: 10.1016/j.softx.2025.102324
Haixiao Li , Azadeh Kermansaravi , Robert Dimitrovski , Aleksandra Lekić
{"title":"ACDC-OpFlow: A unified, cross-language framework for AC/DC optimal power flow solutions","authors":"Haixiao Li , Azadeh Kermansaravi , Robert Dimitrovski , Aleksandra Lekić","doi":"10.1016/j.softx.2025.102324","DOIUrl":"10.1016/j.softx.2025.102324","url":null,"abstract":"<div><div>Hybrid AC/voltage source converter-based multi-terminal DC (VSC-MTDC) power grids play a crucial role in enabling long-distance power transmission and flexible interconnection between AC grids. To fully leverage the functional advantages of such systems, it is essential that they operate in or close to optimal power flow (OPF) conditions. To address this, <em>ACDC-OpFlow</em> is developed as an open-source and cross-language framework for solving AC/DC OPF problems. Its core innovation lies in a unified modeling structure that supports MATLAB, Python, Julia, and C++, with Gurobi used as a consistent solver backend. This framework is beginner-friendly and allows users to work in their preferred programming languages. Both text-based and graph-topology results are provided to help users understand the system-wide power flow distribution and operational status. This work presents the design concept of <em>ACDC-OpFlow</em>, showcases representative example results, and discusses the performance differences observed in multiple programming language implementations.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"32 ","pages":"Article 102324"},"PeriodicalIF":2.4,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145061689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-09-01Epub Date: 2025-08-22DOI: 10.1016/j.softx.2025.102318
Fattaneh Pourakpour, Ákos Szölgyén, Ramin Nateghi, David A Gutman, David Manthey, Lee Ad Cooper
{"title":"HistomicsTK: A Python toolkit for pathology image analysis algorithms.","authors":"Fattaneh Pourakpour, Ákos Szölgyén, Ramin Nateghi, David A Gutman, David Manthey, Lee Ad Cooper","doi":"10.1016/j.softx.2025.102318","DOIUrl":"10.1016/j.softx.2025.102318","url":null,"abstract":"<p><p>Growth in the digital imaging of glass tissue slides has produced petabytes of data, however, this data remains underutilized in biomedical research due in part to a lack of open-source software. HistomicsTK is an open-source Python package that provides preprocessing, segmentation, and feature extraction capabilities for building histology image processing pipelines. HistomicsTK can function as a standalone Python package or serve containerized pipelines through a web-based interface using the Digital Slide Archive platform. This paper provides an overview of HistomicsTK with illustrative use cases and describes how this project engages the community in software development and maintenance.</p>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145233344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-09-01Epub Date: 2025-08-07DOI: 10.1016/j.softx.2025.102288
Xintong Lu, Lee Kennedy-Shaffer, Veronika Shabanova
{"title":"SWCRTsimulator: A simulation-based platform for power estimation in stepped wedge cluster randomized trials with interval-censored outcomes.","authors":"Xintong Lu, Lee Kennedy-Shaffer, Veronika Shabanova","doi":"10.1016/j.softx.2025.102288","DOIUrl":"10.1016/j.softx.2025.102288","url":null,"abstract":"<p><p>Stepped wedge cluster randomized trials (SWCRTs) have become increasingly popular across various disciplines, particularly in public health and clinical research, as they allow evaluations of interventions rolled out sequentially across clusters. SWCRTsimulator is a user-friendly, web-based RShiny application designed to facilitate sample size and statistical power estimation for an interval-censored time-to-event outcome in a SWCRT. Leveraging Monte Carlo simulations, the platform accommodates various study design features, including heterogeneity in intervention effect across different clusters, to provide a more accurate and reliable statistical approach to sample size and power estimates as compared to the approximate methods based on study design features when a closed-form solution is not feasible. SWCRTsimulator provides customizable visualizations for simulation results. We also illustrate the practical application of this platform using the <i>Sankofa 2</i> trial, an active multi-clinic SWCRT of a pediatric HIV disclosure intervention in Ghana, underscoring the importance of accounting for real-world complexities in the design and analysis of such trials.</p>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12483528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145207606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-08-13DOI: 10.1016/j.softx.2025.102284
Jan Hölter , Tim Rickmeyer , Christiane Thielemann
{"title":"CellRex: Software platform for managing biological cell data","authors":"Jan Hölter , Tim Rickmeyer , Christiane Thielemann","doi":"10.1016/j.softx.2025.102284","DOIUrl":"10.1016/j.softx.2025.102284","url":null,"abstract":"<div><div>This work introduces the software platform CellRex, a research data management system for laboratories capable of storing, searching, and enriching data with biological metadata. CellRex addresses data management challenges by storing data in an ontology-based directory structure within the filesystem, with metadata saved as JSON files and in a document-oriented SQLite database. The framework, deployed as container services in a software-as-a-service model, features a web-based GUI and API for user interaction and machine-readable access, providing functionalities such as duplicate detection, experiment grouping, and templating. CellRex improves research efficiency and facilitates data reuse, providing a targeted solution for laboratories focused on cell analysis research.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102284"},"PeriodicalIF":2.4,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-08-12DOI: 10.1016/j.softx.2025.102275
Andrea Giulianelli , Samuele Burattini , Andrei Ciortea , Alessandro Ricci
{"title":"HWoDT Framework: A toolchain to build interoperable Digital Twin Ecosystems","authors":"Andrea Giulianelli , Samuele Burattini , Andrei Ciortea , Alessandro Ricci","doi":"10.1016/j.softx.2025.102275","DOIUrl":"10.1016/j.softx.2025.102275","url":null,"abstract":"<div><div>Digital Twins are increasingly being applied as a design paradigm to model complex Cyber-Physical Systems. These systems extend beyond the original Digital Twin concept, which focused on the virtualization of individual standalone physical assets in vertical application stacks. The interconnected nature of physical environments foresees in Digital Twin Ecosystems a novel abstraction to represent multiple connected Digital Twins of heterogeneous assets. In this paper, we present a toolchain to support the development of Digital Twin Ecosystems based on Web standards and principles, to provide a uniform interface and tackle the heterogeneous nature of Digital Twins.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102275"},"PeriodicalIF":2.4,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-08-11DOI: 10.1016/j.softx.2025.102303
Turan Goktug Altundogan , Mehmet Karakose
{"title":"QUBVIS: query based multi-modal summarization system using CLIP based transformer and vision language models","authors":"Turan Goktug Altundogan , Mehmet Karakose","doi":"10.1016/j.softx.2025.102303","DOIUrl":"10.1016/j.softx.2025.102303","url":null,"abstract":"<div><div>In this study, a new approach is proposed for user-interactive summarization of online videos. In the proposed approach, video-to-video summarization is performed with a very high success rate using a multimodal transformer architecture (QUBVIS) that also takes activity queries from the user as input, and the resulting summary video is subjected to captioning using a Vision Language Model with a GPT-2 decoder. The developed models are integrated with a Flask API and presented in a way that online video platforms can easily integrate into their systems. In addition, a simple web interface using this API is developed to provide API communication with the user. The performance evaluations of both models of the proposed method show our superiority over similar studies in the literature.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102303"},"PeriodicalIF":2.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-08-11DOI: 10.1016/j.softx.2025.102291
Jaiyun Lee , Gyusik Ham , Sooyoung Jang , Sungjoo Kang , Changbeom Choi
{"title":"pyjevsim: Streamlining simulation workflows using journaling in Python-based discrete event simulation environments","authors":"Jaiyun Lee , Gyusik Ham , Sooyoung Jang , Sungjoo Kang , Changbeom Choi","doi":"10.1016/j.softx.2025.102291","DOIUrl":"10.1016/j.softx.2025.102291","url":null,"abstract":"<div><div>Experts develop simulation software for domain-specific problems and utilize it to solve the problem. However, repeated simulations during development and experimentation often lead to excessive computational costs. To mitigate this, we propose <em>pyjevsim</em>, a Python-based discrete event simulation environment with integrated journaling. <em>pyjevsim</em> enables users to restore simulations, modify parameters or models, and resume execution. Additionally, <em>pyjevsim</em> follows the separation of concerns principle, allowing experts to focus on domain-specific logic without explicitly handling data marshaling. Examples illustrate that <em>pyjevsim</em> reduces execution time and computational overhead, improving productivity across various domains.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102291"},"PeriodicalIF":2.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SoftwareXPub Date : 2025-08-05DOI: 10.1016/j.softx.2025.102276
Majid Kundroo, Ghani Haider, Nguyen Khoa, Abdul Wahab Mamond, Taehong Kim
{"title":"FedEasy : Federated learning with ease","authors":"Majid Kundroo, Ghani Haider, Nguyen Khoa, Abdul Wahab Mamond, Taehong Kim","doi":"10.1016/j.softx.2025.102276","DOIUrl":"10.1016/j.softx.2025.102276","url":null,"abstract":"<div><div>Federated learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data while preserving privacy and adhering to regulations. However, existing FL frameworks often require extensive code modifications, creating challenges for researchers. In this paper, we introduce <em>FedEasy</em>, a user-friendly and scalable FL framework built on Flower and PyTorch. <em>FedEasy</em> adopts a configuration-based approach, enabling seamless customization of datasets, data distributions, and FL algorithms through a editable configuration file. It supports multi-node simulation, integrated results logging, and high scalability. <em>FedEasy</em> lowers the entry barrier for FL experimentation while addressing key limitations of existing frameworks.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102276"},"PeriodicalIF":2.4,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}