Artificial intelligence and machine learning to enhance critical mineral deposit discovery by Rhys S. Davies, McLean Trott, Jaakko Georgi, Alexander Farrar

“…Broader adoption of statistical methods, integrated spatial models, and innovative data preparation techniques can address the inconsistencies in exploration datasets. …”
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Transferring CLIP for visual grounding in remote sensing images by Linlin Liang, Yizhuo Quan, Chengbo Wang, Yuanfei Chang, Yanyou Qiao

“…This effectively enhances the feature representation of target objects, thereby mitigating issues such as scale variations and cluttered backgrounds in remote sensing imagery. …”
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Enrollment Motivations, Career Perceptions, and Preferences of Pharmacy Students under a Changing Educational Landscape: An Exploratory Survey at a Single Institution in South Kore... by Youran Noh, Kyung-Bok Son

“…This study investigates students’ enrollment motivations, career perceptions, and career preferences at a single institution that admits cohorts under both the two-plus-four-year and six-year integrated systems. Methods A web-based survey was conducted among all enrolled students at a college of pharmacy in South Korea. …”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Methods: Following PRISMA, 64 studies were reviewed that outlined the latest feature extraction and classification developments using deep learning models such as CNNs and RNNs. …”
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The Impact of Green Taxation on Sustainable Economic Development in the European Union by Valentin Marian Antohi, Costinela Fortea, Monica Laura Zlati, Marius Sorin Dinca

“…The study analyses the impact of green taxation on sustainable economic development in the European Union, using econometric multiple linear regression methods applied to a dataset for the 27 Member States covering the period 2010-2022. …”
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A New Sensorized Approach Based on a DeepLabCut Model and IR Thermography for Characterizing the Thermal Profile in Knees During Exercise by Davide Crisafulli, Marta Spataro, Cristiano De Marchis, Giacomo Risitano, Dario Milone

“…DeepLabCut was used to automate the selection of the region of interest (ROI) for temperature assessments, improving data accuracy compared to traditional time-consuming semi-automatic methods. This integrative approach enables precise and marker-free measurements, offering clinically relevant data that can aid in the diagnosis of knee pathologies, evaluation of the rehabilitation progress, and assessment of treatment effectiveness. …”
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BLE Signal Processing and Machine Learning for Indoor Behavior Classification by Yi-Shiun Lee, Yong-Yi Fanjiang, Chi-Huang Hung, Yung-Shiang Huang

“…Smart home technology enhances the quality of life, particularly with respect to in-home care and health monitoring. While video-based methods provide accurate behavior analysis, privacy concerns drive interest in non-visual alternatives. …”
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A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF by Zenzen, Roumaissa, Ayadi, Ayoub, Benaissa, Brahim, Belaidi, Idir, Sukic, Enes, Khatir, Tawfiq

“…In recent years, substantial investments in structural construction underscore the paramount importance of ensuring structural integrity for safety and dependability. Structural Health Monitoring (SHM) has emerged as a pivotal tool for assessing structural health, with an emphasis on damage detection, localisation, and quantification, particularly through vibration-based methods that exploit variations in modal properties as precursors to structural damage. …”
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In situ and dynamic screening of extracellular vesicles as predictive biomarkers in immune-checkpoint inhibitor therapies by Yihe Wang, Yue Sun, Mengqi Liu, Chao Wang, Miao Huang, Jiaoyan Qiu, Ningkai Yang, Yu Zhang, Hong Liu, Lin Han

“…But it is challenging to determine the level of circulating EVs due to their variations in spatial and temporal distribution. To address this, we developed an in situ EV detection platform integrating multiplex EV capture with microfluidic-generated immune-tumor spheroids. …”
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Towards national risk-targeted seismic hazard maps for mainland China by Meng Zhang, Hua Pan, Yaohu Zhang

“…Initially, well-founded hazard curves were plotted based on the probabilistic model of the fifth-generation ground motion zoning map. The study examined methods for integrating regional variations in hazard to achieve a uniform target risk across the region. …”
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Melatonin effects on animal behavior: circadian rhythm, stress response, and modulation of behavioral patterns by Yubin Song, Minjung Yoon

“…The review also examines the seasonal variations of melatonin and its impact on aggression and reproductive activities related to photoperiods, as well as its effects on learning and memory to suggest improvements in animal training methods and practices. …”
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Finite-element analysis on the parameters influencing the brittle crack arrest in steel plates by Jeongung Park, Gyubaek An

“…The analysis incorporates yield stress variations influenced by temperature gradients, strain rates, and thermal effects, considering Young's modulus and strain rate dependency. …”
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A Learning Emotion Recognition Model Based on Feature Fusion of Photoplethysmography and Video Signal by Xiaoliang Zhu, Zili He, Chuanyong Wang, Zhicheng Dai, Liang Zhao

“…Therefore, on the one hand, it is necessary to improve the performance of the two recognition methods mentioned above; on the other hand, using the complementary advantages of the two methods through multimodal fusion needs to be considered. …”
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NPP estimation by fusing geodetector and deep spatio-temporal networks by Xiaohui He, Chenqiao Yuan, Panle Li, Xijie Cheng, Mengjia Qiao, Xiaoyu He, Nan Yang, Guangsheng Zhou, Jiandong Shang

“…In recent years, deep learning has demonstrated significant potential in net primary productivity (NPP) estimation but the existing methods fall short in fully exploiting the spatio-temporal dependencies inherent in remote sensing data for modeling NPP. …”
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Understanding the determinants of user choice in ride-hailing motorcycle services: evidence from Indonesia by Remba Yanuar Efranto, Muhammad Rajab Rahmatan Hidayah

“…It provides empirical evidence for integrating user-centric attributes into service design to enhance adoption and retention.…”
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Depression and Anxiety among Tuberculosis Patients: A Systematic Review and Meta-analysis by Vikas Panibatla, Sharath Burugina Nagaraja, Deepa Mohan, Sreenath Menon Parambanattu Kizhakkethil, M. D. Sangeetha

“…Understanding the magnitude of these mental health issues is crucial for improving TB programs and achieving successful treatment outcomes. Materials and Methods: We conducted a systematic review and meta-analysis, to assess the prevalence of depressive and anxiety symptoms among TB patients. …”
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Study on the Typological Chronology of Cantonese Palatial-Type (Diantang Shi) Timber Structures in Guangdong Province, China: An Interdisciplinary Approach of Building Archaeology by Yunan Ren

“…Through the interdisciplinary methodology of building archaeology, archaeological theory of material cultural evolution as well as archaeological methods of dating analysis are integrated, achieving more precision in architectural examination both geographically and historically. …”
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A recursive framework of vehicle trajectory planning at mixed‐traffic signalized intersections by Menglin Yang, Hao Yu, Pan Liu

“…Besides, the recomputing of CAV trajectories will only be conducted when the variation in predictions rises to a certain threshold, balancing efficiency and computing consumption, inspired and modified based on MPC methods. …”
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Performance Analysis of Resampling Techniques for Overcoming Data Imbalance in Multiclass Classification by Anggit Larasati, Sugiyarto Surono, Aris Thobirin, Deshinta Arrova Dewi

“…The main objective of this research is to identify the performance of deep learning models in classifying kidney disease. By integrating the Convolutional Neural Network model, the performance of the classification process can be analyzed effectively and efficiently. …”
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Improving thermal state preparation of Sachdev–Ye–Kitaev model with reinforcement learning on quantum hardware by Akash Kundu

“…This paper addresses this challenge by integrating reinforcement learning (RL) with convolutional neural networks, employing an iterative approach to optimize the quantum circuit and its parameters. …”
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