Easy, fast and reproducible Stochastic Cellular Automata with chouca by Génin, Alexandre, Dupont, Guillaume, Valencia, Daniel, Zucconi, Mauro, Ávila-Thieme, M. Isidora, Navarrete, Sergio A., Wieters, Evie A.

“…By providing an easy and efficient entry point to SCAs, chouca lowers the bar to the use of this class of models for ecologists, managers and general practitioners, providing a leveled-off reproducible platform while opening novel methodological approaches.…”
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Discovering emergent connections in quantum physics research via dynamic word embeddings by Felix Frohnert, Xuemei Gu, Mario Krenn, Evert van Nieuwenburg

“…In this work, we introduce a novel approach based on dynamic word embeddings for concept combination prediction. …”
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Chromosomal genome assembly resolves drug resistance loci in the parasitic nematode Teladorsagia circumcincta. by Jennifer McIntyre, Alison Morrison, Kirsty Maitland, Duncan Berger, Daniel R G Price, Sam Dougan, Dionysis Grigoriadis, Alan Tracey, Nancy Holroyd, Katie Bull, Hannah Rose Vineer, Mike J Glover, Eric R Morgan, Alasdair J Nisbet, Tom N McNeilly, Yvonne Bartley, Neil Sargison, Dave Bartley, Matt Berriman, James A Cotton, Eileen Devaney, Roz Laing, Stephen R Doyle

“…Genome-wide analyses of drug resistance, combining evidence from three distinct experiments, identified selection around known candidate genes for benzimidazole, levamisole and ivermectin resistance, as well as novel regions associated with ivermectin and moxidectin resistance. …”
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Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment by Praveen Vijai, Bagavathi Sivakumar P

“…The proposed model addresses key challenges, including data imbalance, interpretability issues, and computational complexity. …”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…Machine learning (ML) models present a faster, cost-effective alternative for simulating outcomes and exploring various scenarios. This study adopts a novel approach by utilizing hybrid models, which offer greater accuracy than individual or ensemble ML models. …”
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Computer-aided cholelithiasis diagnosis using explainable convolutional neural network by Dheeraj Kumar, Mayuri A. Mehta, Ketan Kotecha, Ambarish Kulkarni

“…Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited because Convolutional Neural Network (CNN) models are black box in nature. Therefore, a novel approach for cholelithiasis classification using custom CNN with post-hoc model explanation is proposed. …”
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On supergravity and noncritical strings by Andrea Dei, Pietro Ferrero, Leonardo Rastelli

“…In particular, we find a novel class of solutions with RR flux, parametrized by a function of three variables that solves an elegant PDE. …”
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Intrusion Detection for Wireless Sensor Network Using Particle Swarm Optimization Based Explainable Ensemble Machine Learning Approach by Shaikh Afnan Birahim, Avijit Paul, Fahmida Rahman, Yamina Islam, Tonmoy Roy, Mohammad Asif Hasan, Fariha Haque, Muhammad E. H. Chowdhury

“…This paper proposes a novel Intrusion Detection System (IDS) leveraging Particle Swarm Optimization (PSO) and an ensemble machine learning approach combining Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN) models to enhance the accuracy and reliability of intrusion detection in WSNs. …”
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CR-DEQ-SAR: A Deep Equilibrium Sparse SAR Imaging Method for Compound Regularization by Guoru Zhou, Yixin Zuo, Zhe Zhang, Bingchen Zhang, Yirong Wu

“…The deep equilibrium model (DEQ) serves as a novel deep network framework that directly computes fixed points using analytical methods, theoretically allowing for infinite forward iterations while maintaining constant memory requirements. …”
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Structural bioinformatics for rational drug design by Soroush Mozaffari, Agnethe Moen, Che Yee Ng, Gerry A.F. Nicolaes, Kanin Wichapong

“…Finally, we summarize relevant data and highlight cases where various computational approaches were successfully applied to develop novel inhibitors, as presented during the ISTH 2024 Congress.…”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

“…In this paper, we propose SensorDBSCAN, a novel semi-supervised method for anomaly detection and diagnosis. …”
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MONITORING AND ANALYSIS OF STUDENTS' PERFORMANCE DURING SOFTWARE DEVELOPMENT by Oleksandr Sharyhin, Vasyl Fedorets, Oksana Klochko

“…The primary focus is on the development of novel performance metrics that effectively capture the level of control required from the Team Leader and the quality of work assessed by the QA Engineer. …”
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An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network by R. Karthik, Armaano Ajay, Anshika Jhalani, Kruthik Ballari, Suganthi K

“…This research proposes a novel feature fusion-based model that incorporates two parallel tracks for efficient feature extraction. …”
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Cross-Modal Augmented Transformer for Automated Medical Report Generation by Yuhao Tang, Ye Yuan, Fei Tao, Minghao Tang

“…In clinical practice, interpreting medical images and composing diagnostic reports typically involve significant manual workload. …”
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Humanising nanotoxicology: replacement of animal-derived products in the application of integrated approaches to testing and assessment of nanomaterial inhalation hazard by Roma Fraser, Keira Campbell, Pawel Pokorski, Eve MacKinnon, Katie McAllister, Karla B. Neves, Fiona Murphy

“…This has prompted the design of Novel Approach Methods (NAMs) to streamline risk assessment and predict human hazards without relying on animal testing. …”
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An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…The system incorporates an Autoregressive Moving Average-Generalized AutoRegressive Conditional Heteroskedasticity model that offers an interpretability advantage over machine-learning methods. …”
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Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

“…By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we utilise the powerful Barlow Twins architecture for feature-extraction while considering the structure of the target protein. …”
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Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction by Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis, Constantinos S. Pattichis

“…In the balanced dataset, GB had an AUC of 0.729, accuracy of 68.86%, sensitivity of 75.39%, and specificity of 58.59%. To enhance interpretability, a novel rule extraction method for GB model was implemented using relevant important predictors, such as triage acuity, comorbidity scores, and arrival methods. …”
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Designing smartphone-based cognitive assessments for schizophrenia: Perspectives from a multisite study by Aishwarya Raje, Abhijit R. Rozatkar, Urvakhsh Meherwan Mehta, Ritu Shrivastava, Ameya Bondre, Manaal Amir Ahmad, Anshika Malviya, Yogendra Sen, Deepak Tugnawat, Anant Bhan, Tamonud Modak, Nabagata Das, Srilakshmi Nagendra, Erlend Lane, Juan Castillo, John A. Naslund, John Torous, Soumya Choudhary

“…Thematic analysis reinforces the importance of feedback and data sharing, although this presents a challenge, given the novel nature of smartphone-based cognitive measures that have not yet been standardized or validated.…”
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Caution when using network partners for target identification in drug discovery by Dandan Tan, Yiheng Chen, Yann Ilboudo, Kevin Y.H. Liang, Guillaume Butler-Laporte, J. Brent Richards

“…Summary: Identifying novel, high-yield drug targets is challenging and often results in a high failure rate. …”
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