Journal of Computational Science最新文献

{"title":"The impact of sequential versus parallel clearing mechanisms in agent-based simulations of artificial limit order book exchanges","authors":"Matej Steinbacher ,&nbsp;Mitja Steinbacher ,&nbsp;Matjaž Steinbacher","doi":"10.1016/j.jocs.2026.102793","DOIUrl":"10.1016/j.jocs.2026.102793","url":null,"abstract":"<div><div>This study examines the impact of different computing implementations of clearing mechanisms on multi-asset price dynamics within an artificial stock market framework. We show that sequential processing of order books introduces a systematic and significant bias by affecting the allocation of traders’ capital within a single time step. This occurs because applying budget constraints sequentially grants assets processed earlier preferential access to funds, distorting individual asset demand and consequently their price trajectories. The findings highlight that while the overall price level is primarily driven by macro factors like the money-to-stock ratio, the market’s microstructural clearing mechanism plays a critical role in the allocation of value among individual assets. This underscores the necessity for careful consideration and validation of clearing mechanisms in artificial markets to accurately model complex financial behaviors.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"95 ","pages":"Article 102793"},"PeriodicalIF":3.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"GAT based attention-reweighted PPI networks uncover shared hub genes in Crohn’s disease and ulcerative colitis","authors":"Pratibha Joshi ,&nbsp;Rinki Basoya ,&nbsp;Rana Pratap Singh ,&nbsp;Ravi Verma ,&nbsp;Buddha Singh","doi":"10.1016/j.jocs.2026.102791","DOIUrl":"10.1016/j.jocs.2026.102791","url":null,"abstract":"<div><div>Inflammatory bowel disease (IBD), comprising Crohn’s disease (CD) and ulcerative colitis (UC), exhibits molecular heterogeneity that complicates diagnosis. This study proposes an integrated deep learning and bioinformatics framework to uncover molecular pathways and identify potential therapeutic targets. The dataset includes 156 CD patients, 167 UC patients and 267 healthy controls. The Graph Attention Network (GAT) is applied to protein–protein interaction (PPI) networks for embedding the node features and reweighting edges based on learned attention scores. The <strong>Louvain algorithm</strong> on the embedded PPI network identifies the top 10 communities. Functional enrichment analysis of the genes within these communities reveals significantly enriched in immune responses, stress responses and pathogen-associated pathways. From these communities, 32 hub genes are identified as being implicated in IBD pathogenesis. The <strong>machine learning classifiers</strong> logistic regression, support vector machine, random forest, gradient boosting and a stacking classifier are applied to 32 genes to distinguish between CD and UC. Based on classification performance and statistical significance, 10 highly significant genes <strong>TLR5, TLR2, IL1B, IL4R, TLR4, IL18, STAT3, STAT1, IL18RAP</strong> and <strong>IFNGR1</strong> are selected. Furthermore, the KEGG pathway analysis of the 32 genes shows that five of these genes (<strong>STAT1</strong>, <strong>STAT3</strong>, <strong>IL4R</strong>, <strong>IL18</strong> and <strong>TLR2)</strong> are directly involved in IBD-related pathways. Experimental validation of five key genes using qRT-PCR in HCT116 cells confirms significant upregulation of these genes. Modularity and NMI scores demonstrate that the GAT-based framework achieves superior community detection performance compared to baseline methods. This approach gives a scalable and robust strategy for advancing biomarker discovery and personalized therapy in complex diseases like IBD.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"95 ","pages":"Article 102791"},"PeriodicalIF":3.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Dead gate elimination in hybrid quantum–classical programs","authors":"Yanbin Chen,&nbsp;Christian B. Mendl,&nbsp;Helmut Seidl","doi":"10.1016/j.jocs.2026.102789","DOIUrl":"10.1016/j.jocs.2026.102789","url":null,"abstract":"<div><div>Hybrid quantum algorithms combine the strengths of quantum and classical computing. Many such algorithms, including the variational quantum eigensolver (VQE), embed parameterized quantum circuits as subroutines inside a classical host program. In current toolchains these circuits are executed in full, even when only a subset of measurement outcomes actually contributes to subsequent classical computations. In this manuscript, we propose a circuit optimization technique that uses information from the host program to identify and remove dead gates, i.e. quantum operations whose effects propagate only into measurement outcomes that are never semantically consumed. We formalize equivalence of circuits relative to the valid measurement outcomes, characterize dead gates, and give a polynomial-time elimination algorithm. We prove that removing dead gates does not change the probability distribution of the contributory measurement outcomes and therefore preserves the semantics of the overall hybrid program. We also discuss the challenges in host-side analysis. We implement our optimization and evaluate it on instances of VQE, quantum phase estimation (QPE), a QAOA-based MaxCut solver, and a Trotterised Hamiltonian-simulation algorithm, as well as on randomly generated hybrid programs. Across all benchmarks, our method removes a non-trivial fraction of gates even on circuits that have already been pre-optimized by state-of-the-art transpilers; in some cases it can eliminate entire quantum blocks when all measurement outcomes are dead. This article is an extended journal version of our conference paper Chen et al. (2025) <span><span>[1]</span></span>.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"95 ","pages":"Article 102789"},"PeriodicalIF":3.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"New way to control hidden memory chaotic attractors of fractional order systems beyond equilibrium points","authors":"Bichitra Kumar Lenka,&nbsp;Ranjit Kumar Upadhyay","doi":"10.1016/j.jocs.2026.102806","DOIUrl":"10.1016/j.jocs.2026.102806","url":null,"abstract":"<div><div>Going beyond controlling the dynamics of hidden chaotic attractors in integer order systems remains a long-standing problem, and it is not known how to control dynamics to a precise target control goal, when it comes to non-equilibrium fractional order systems. We introduce a modified state feedback control method that uses an extra feed-forward control part that allows measuring disturbance of the control goal when intended to flow through the system along with the state feedback part. We have shown that our proposed control strategy works because the control matrix associated with the state feedback part satisfied a reasonable matrix inequality that has been proposed under Lipschitz constraints. A new fractional-order system and fractional-order Wei systems are considered, including numerical simulations to demonstrate the effectiveness of the proposed control method.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"95 ","pages":"Article 102806"},"PeriodicalIF":3.7,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146191336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Exploring scalarization methods and approximation algorithms for the Multi-Objective Set Covering Problem","authors":"Lakmali Weerasena,&nbsp;Chathuri Aththanayake","doi":"10.1016/j.jocs.2026.102785","DOIUrl":"10.1016/j.jocs.2026.102785","url":null,"abstract":"<div><div>This study focuses on the Multi-Objective Set Covering Problem (MOSCP), a prominent challenge in Multi-Objective Combinatorial Optimization. Given the NP-completeness of the Set Covering Problem (SCP), both Single Objective SCP (SOSCP) and MOSCP evolve into NP-hard combinatorial optimization problems. Our investigation reveals a gap in the literature, as norm-based scalarizations have been identified as effective in approximating multi-objective minimization problems, yet limited research exists on <span><math><mi>ϵ</mi></math></span>-approximation algorithms for the MOSCP. Our contribution unfolds on two fronts: (1) We explore the impact of using a common set of weight vectors for two scalarization methods weighted-sum and weighted max-ordering in solving the MOSCP under various conditions. We integrate four distinct weight computing methods and precisely solve both weighted-sum scalarization and weighted max-ordering scalarization of the MOSCP. (2) We utilize the cost-effectiveness vector proposed in previous literature to extract additional theoretical properties describing the approximation quality. Furthermore, we introduce a new cost-effectiveness vector and discuss its validity in relation to the properties identified in prior studies, resulting in the derivation of new theoretical properties. The study indicates that introduced weight generation methods demonstrate commendable performance with an equivalent number of weight vectors on the MOSCP. Furthermore, employing weighted max-ordering scalarization is proposed as a suitable choice for generating a robust initial pool for two-phase algorithms.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102785"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Development and implementation of a tool for the analysis and circuit representation of steady-state alternating current circuits","authors":"Celal Atalar ,&nbsp;Selda Bayrak ,&nbsp;Huseyin Pehlivan","doi":"10.1016/j.jocs.2025.102774","DOIUrl":"10.1016/j.jocs.2025.102774","url":null,"abstract":"<div><div>Electrical circuits are a phenomenon that has important implications and application areas in science and engineering. They hold many underlying concepts and principles that provide guidance in the design and construction of mathematical models of various control systems. In this study, we present the development process of a software tool for the analysis of steady-state alternating current circuits. AC circuits can contain elements like resistors, inductors, and capacitors, as well as sinusoidal independent voltage and current sources. The developed tool is an improved version of the ECDAT tool that can analyze direct current circuits and is therefore called IECDAT (Improved ECDAT). The analysis process takes a text-based description of an AC circuit that is specified using a formal language and calculates the current and voltage values of all elements of the related circuit in steady state. The tool also supplies some intermediate steps of the calculation, performed based on the graph analysis method along with a schematic representation of the AC circuit, in the form of a portable document. Additionally, an automatic circuit generation module is incorporated into the tool, which randomly creates AC circuits based on the user’s input parameters. The module can be described as a question bank that can generate questions at any difficulty level. The IECDAT system utilizes the rational number system to produce highly accurate results. The usability and effectiveness of the tool are evaluated through various methods and findings, and it is generally found to be successful.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102774"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"A local–global Graph Transformer model for fluid dynamics simulations","authors":"Jiamin Jiang ,&nbsp;Jingrun Chen ,&nbsp;Zhouwang Yang","doi":"10.1016/j.jocs.2025.102773","DOIUrl":"10.1016/j.jocs.2025.102773","url":null,"abstract":"<div><div>Computational fluid dynamics is indispensable across numerous engineering disciplines, yet classical numerical methods often face efficiency bottlenecks that limit their suitability for real-time predictions and extensive parametric studies. Graph Neural Networks (GNNs) have shown promise as powerful deep learning alternatives that can naturally process unstructured data and capture nonlinear interactions within complex geometries. Nonetheless, GNNs struggle to effectively propagate global information due to their local aggregation mechanisms, significantly hindering their performance on PDE problems exhibiting long-range dependencies.</div><div>To overcome these challenges, we present a local–global Graph Transformer (LGGT) model that integrates message passing with global attention via a linear transformer. The LGGT architecture effectively preserves local details while capturing long-range dependencies without incurring quadratic computational complexity. We further propose a two-stage training strategy to mitigate temporal error accumulation during inference. Experiments on challenging fluid dynamics scenarios demonstrate that our LGGT neural solver delivers improved predictive accuracy, long-term stability, and generalization to unseen model configurations compared to baseline methods.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102773"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"Temporal carbon neutral Chinese knowledge graph completion method based on latent semantic mining","authors":"Xiping Zhu,&nbsp;Lijuan Xiao,&nbsp;Ang Gao,&nbsp;Lu Guo,&nbsp;Huan Yang","doi":"10.1016/j.jocs.2025.102744","DOIUrl":"10.1016/j.jocs.2025.102744","url":null,"abstract":"<div><div>In order to promote the digital transformation in the field of carbon neutrality, the article constructed a carbon neutral data set CANdata15k with a sample size of 16,050 to realize the completion of temporal knowledge graphs. The latent semantics of the data are not fully taken into account by the current temporal knowledge graph completion approach. In order to mine the entire latent semantics, we suggest a temporal carbon-neutral knowledge graph completion model (Tc-MLS). Replace entities and relationships in the pre-trained language model with text descriptions to acquire probable text semantics. And through the knowledge fusion model proposed in Tc-MLS to obtain the latent semantics between entities. The latent semantics between entities and relations are then obtained by embedding related topology and similarity soft logic. Finally, the comparison with other SOTA algorithm results shows that the MRR value of Tc-MLS on the CANdata15k dataset has increased by 56.91% on average, and the MRR values obtained on the two public datasets YAGO11k and Wikidata12k have increased by an average of 9.96% and 7.72%, respectively. Prove the effectiveness of the Tc-MLS model.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102744"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"A novel deep transfer learning model with a bidirectional quasi-recurrent neural network for underwater object classification from aquarium images","authors":"Tabeer Jan,&nbsp;Lavanya Madhuri Bollipo","doi":"10.1016/j.jocs.2025.102775","DOIUrl":"10.1016/j.jocs.2025.102775","url":null,"abstract":"<div><div>The significance of underwater research and the utilization of deep-sea resources highlights the importance of autonomous underwater operations in mitigating risks associated with hazardous high-pressure deep-sea environments. For underwater autonomous operation, intellectual computer vision (CV) techniques have proven highly beneficial. Moreover, underwater object classification plays a vital part in numerous applications such as maintenance and repair of marine scientific equipment and sub-aquatic structures. Numerous CV-based solutions have been presented, but the optimal solution for underwater object classification and species classification needs further research. The emergence of deep learning (DL) has enabled investigators to address various challenges, including the security of sub-aquatic ecological systems, emergency services, reducing the likelihood of underwater disasters, and underwater object classification. The proposed work aims on the development of underwater object classification using Bidirectional Quasi-Recurrent Neural Networks and Deep Learning Model (UOCBQRNN-DLM). The presented UOCBQRNN-DLM technique enables the accurate detection and classification of underwater objects by employing image preprocessing that involves dual stages: noise removal utilizing a Wiener filter (WF) and contrast enhancement utilizing CLAHE. For the object classification process, the UOCBQRNN-DLM method employs a bidirectional quasi-recurrent neural network (BQRNN) technique with a backbone of Xception for underwater feature extraction. BQRNN is particularly effective for bounding box generation utilizing the Sigmoid function and object classifier using the Softmax function. Finally, the process of hyperparameter tuning is used by the antlion optimization algorithm (AOA). The simulated performance of the proposed UOCBQRNN-DLM method was evaluated under diverse conditions, and experimental results demonstrate that the proposed approach outperforms existing models.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102775"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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":"RBF partition of unity method for solving nonlinear multi-term fractional parabolic PDEs on irregular domains: A numerical study and error analysis","authors":"Banafsheh Raeisi,&nbsp;Mojtaba Fardi,&nbsp;Mohammadreza Ahmadi Darani","doi":"10.1016/j.jocs.2026.102783","DOIUrl":"10.1016/j.jocs.2026.102783","url":null,"abstract":"<div><div>This paper introduces an innovative radial basis function partition of unity method for the numerical simulation of multi-term time-fractional parabolic partial differential equations. The proposed method simplifies algorithms and reduces computational costs by utilizing local approximations rather than global ones, thereby eliminating the need for differential operators on weight functions. It combines localized spatial discretization with a time-stepping strategy with a variable-step, which improves the rate of temporal convergence. The method uses the scalability of polyharmonic spline kernels to manage instability. The effectiveness of the proposed method is demonstrated through various numerical experiments.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"94 ","pages":"Article 102783"},"PeriodicalIF":3.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146022546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}