DK-Port: construction and validation of port autonomous driving simulation environment based on large language models and reinforcement learning by LOU Yunjie, AI Mingfei, ZHUANG Shujie, YU Hai, WANG Xin, TENG Chu, WANG Jiangcheng, SHEN Tianyu, HAO Kunkun, CUI Wen

“…This paper incorporates survey-based expert input, employing zero-shot prompting and chain-of-thought reasoning techniques to enable large language models to assist in designing reward functions efficiently. Then, human-machine mixed-traffic scenarios are constructed using complex road data, and adversarial driver models are trained with the PPO reinforcement learning algorithm to identify safety vulnerabilities in autonomous driving systems. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…In the field of robotic arm trajectory imitation learning, Gaussian Mixture Models are widely used for their ability to capture the characteristics of complex trajectories. …”
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Application of reinforcement learning for integrating project risk analysis and risk response planning: A case study on construction projects by Sajad Soltan, Maryam Ashrafi

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AquaVar decision support system for water resource management: Lessons learned from the first five years of operation by Fanny Picourlat, Lian Guey Ler, Jérémy Targosz, Paguedame Game, Hézouwé Amaou Tallé, Morgan Abily, Félix Billaud

“…For a moderate flood, the real‐time functionality was able to simulate forecast discharges 26 h before the flood peak, with a maximum local error of 30%. …”
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Use of pattern recognition in photoacoustic imaging to identify neuronal ensembles in the prefrontal cortex of rats undergoing conditioned fear learning by Shane A. Perrine, Mohammad Beirami, James I. Matchynski, Rayyan Manwar, Srinivasu Kallakuri, Alana C. Conti, Kamran Avanaki

“…The current study uses pattern recognition analysis to extend our previous findings showing conditioned fear learning and novelty-exposure (i.e. sham conditioning) equally increase Fos-dependent neuronal ensemble signal intensity in the prefrontal cortex (PFC) of rats as quantified by photoacoustic imaging (e.g. functional/molecular photoacoustic tomography). …”
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Predicting Firefighter Injury and Entrapment in Urban Firefighting Operations: An Investigation Into the Effectiveness of Modified Fire Time Stages and Machine Learning by Mohammad Mahdi Barati Jozan, Hamed Khosravi, Aynaz Lotfata, Krzysztof J. Cios, Hamed Tabesh

“…Methods In this study, we compare the performance of eight machine learning algorithms in predicting the occurrence of firefighter injuries and entrapment during urban fire incidents. …”
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Lessons learned from whole exome sequencing in multiplex families affected by a complex genetic disorder, intracranial aneurysm. by Janice L Farlow, Hai Lin, Laura Sauerbeck, Dongbing Lai, Daniel L Koller, Elizabeth Pugh, Kurt Hetrick, Hua Ling, Rachel Kleinloog, Pieter van der Vlies, Patrick Deelen, Morris A Swertz, Bon H Verweij, Luca Regli, Gabriel J E Rinkel, Ynte M Ruigrok, Kimberly Doheny, Yunlong Liu, Joseph Broderick, Tatiana Foroud, FIA Study Investigators

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Applying the L3 assessment framework to identify knowledge gaps on the impact of classroom activities and listening on children’s learning and wellbeing by Kiri Mealings, Joerg M. Buchholz

“…The aims of this paper were to (i) understand what is known and what is not known about how the characterised activity impacts primary school children’s learning and wellbeing, and (ii) understand what is known and what is not known about how hearing, listening, comprehending, and communicating (Functioning Assessment) impacts primary school children’s learning and wellbeing. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…This study utilizes machine learning to analyze transcriptomic data from 515 RNA-seq profiles across 18 independent studies, covering eleven abiotic and three biotic stress types. …”
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Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data by Zhijie Liang, Ling Wang, Jianyu Su, Bo Sun, Daifa Wang, Juan Yang

“…Utilizing this dataset, a novel deep learning model named AC-LSTM is proposed, amalgamating Transformer and LSTM architectures to identify residual mathematical cognition during the English learning process. …”
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A Novel Method of Parameter Identification for Lithium-Ion Batteries Based on Elite Opposition-Based Learning Snake Optimization by Wuke Li, Ying Xiong, Shiqi Zhang, Xi Fan, Rui Wang, Patrick Wong

“…To address these challenges, this study proposes the Elite Opposition-Based Learning Snake Optimization (EOLSO) algorithm, which uses an elite opposition-based learning mechanism to enhance diversity and a non-monotonic temperature factor to balance exploration and exploitation. …”
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Machine learning driven multi-omics analysis of the genetic mechanisms behind the double-coat fleece formation in Hetian sheep by Yanwei Zhang, Wenrong Li, Xinming Xu, Mengwan Xie, Liping Tang, Peiyu Zheng, Nannan Song, Lijuan Yu, Jiang Di

“…PPI network analysis and machine learning identified IRF2BP2 and EGFR as key functional genes associated with coat fleece type.DiscussionThis study enhances understanding of the genetic mechanisms governing double-coated fleece formation in Hetian sheep. …”
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Development of GUI-Driven AI Deep Learning Platform for Predicting Warpage Behavior of Fan-Out Wafer-Level Packaging by Ching-Feng Yu, Jr-Wei Peng, Chih-Cheng Hsiao, Chin-Hung Wang, Wei-Chung Lo

“…This study presents an artificial intelligence (AI) prediction platform driven by deep learning technologies, designed specifically to address the challenges associated with predicting warpage behavior in fan-out wafer-level packaging (FOWLP). …”
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Optimization of heat and mass transfer in chemically radiative nanofluids using Cattaneo-Christov fluxes and advanced machine learning techniques by Shazia Habib, Saleem Nasir, Zeeshan Khan, Abdallah S. Berrouk, Waseem Khan, Saeed Islam

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Development of a machine learning-derived programmed cell death index for prognostic prediction and immune insights in colorectal cancer by Jinping Li, Yan Jiang, Shengbin Nong, Liudan Liang, Liangchao Chen, Qiming Gong

“…A nomogram integrating PCDI with clinical variables showed strong predictive accuracy for 1-, 3-, and 5 year survival rates. Functional analysis revealed significant metabolic differences between high- and low-PCDI groups. …”
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Boosting Reservoir Prediction Accuracy: A Hybrid Methodology Combining Traditional Reservoir Simulation and Modern Machine Learning Approaches by Mohammed Otmane, Syed Imtiaz, Adel M. Jaluta, Amer Aborig

“…The methodology involves data quality control, log interpretation, seismic interpretation, horizon and surface interpretation, fault interpretation, gridding, domain conversion, property and petrophysical modeling, well completion, fluid model definition, and rock physics functions. History matching and prediction are performed using simulation cases, and machine learning techniques such as data gathering, cleaning, dynamic time warping (DTW), long short-term memory (LSTM), and transfer learning are applied. …”
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Ventilation Strategy for Proper IAQ in Existing Nurseries Buildings - Lesson Learned from the Research during COVID-19 Pandemic by Katarzyna Ratajczak

“…Abstract During the COVID-19 pandemic, many recommendations were made in the field of limiting the transmission of the SARS-CoV-2 virus, from which we can learn a lesson for determining ventilation strategies in strategic types of buildings (those whose closure during a pandemic is harmful to the economy, e.g., nurseries). …”
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Exploring Nonlinear Threshold Effects and Interactions Between Built Environment and Urban Vitality at the Block Level Using Machine Learning by Cong Li, Yajuan Zhou, Manfei Wu, Jiayue Xu, Xin Fu

“…The results showed the following: (1) Xi’an’s urban vitality exhibited a distinct gradient, with the highest vitality concentrated in the Yanta District; (2) life service facility density was the most significant determinant of vitality (19.91%), followed by air quality (9.01%) and functional diversity (6.49%); and (3) significant interactions among built environment factors were observed. …”
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Reducing incidents of violence and aggression and self-harm on a secure mental health inpatient ward for women with learning disabilities by Megan Georgiou, Margaret Paradza, Farayi Zichawo

“…We have demonstrated the benefits of improved communication practices and meaningful engagement opportunities on quality of life and ward functionality. Both interventions could be easily replicated on other mental health and learning disability inpatient wards. …”
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Behavior Modeling and Bio-Hybrid Systems: Using Reinforcement Learning to Enhance Cyborg Cockroach in Bio-Inspired Swarm Robotics by Le Minh Triet, Nguyen Truong Thinh

“…By defining precise state-action spaces and reward functions, the RL model effectively learned to influence cockroach behavior via electrical stimulation of their antennae, guiding them to perform complex navigational tasks. …”
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