Personality predicts internalizing symptoms and quality of life in police cadets: a comparison of artificial intelligence and parametric approaches by Macià Buades-Rotger, Ana Martínez Catena, Guillermo Recio, Mireia Cano Gallent, Jordi Niñerola i Maymí, Anna Figueras Masip, David Gallardo-Pujol

“…Here, in two large cohorts of police cadets (n = 1069, 30% women and n = 1377, 35% women) we investigated whether broad personality traits could predict internalizing symptoms (somatization, depression, and anxiety) as well as mental health-related quality of life (MHRQoL). Moreover, we compared seven popular artificial intelligence and linear regression models (Elastic Net, General Linear Model, Lasso Regression, Neural Networks, Random Forests, and Support Vector Regression) in predicting MHRQoL as a function of all other variables. …”
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A Review of Short-Term, Long-Term, and Memory Consolidation Mechanisms in the Hippocampus and Cerebral Cortex by Zuomin Yang, Anis Salwa Binti Mohd Khairuddin, Joon Huang Chuah, Wei Ru Wong, Hafiz Muhammad Fahad Noman, Tri Wahyu Oktaviana Putri, Xin Xu, Md Minhazul Haq

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Tribological Behaviour Analysis of Elastomer-Plastomer Couples in Dry Friction Conditions by Geanina Marcela PODARU, Carmelia Mariana DRAGOMIR-BĂLĂNICĂ, Igor ARSENE

“…This layer stands as a lubricant, offering a prolonged life for the parts in contact. Taking into account that the relationship between materials and working conditions cannot be framed into a mathematical equation, artificial neural networks (ANN) are a valid alternative. …”
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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

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Recent advances in deep learning for protein-protein interaction: a review by Jiafu Cui, Siqi Yang, Litai Yi, Qilemuge Xi, Dezhi Yang, Yongchun Zuo

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Prosumer Cost Efficiency and Ensuring Grid Stability Through a Hierarchical PPO Framework in Decentralized Community Energy Management by Ajay Singh, Bijaya Ketan Panigrahi

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Learning Dendritic-Neuron-Based Motion Detection for RGB Images: A Biomimetic Approach by Tianqi Chen, Yuki Todo, Zhiyu Qiu, Yuxiao Hua, Delai Qiu, Xugang Wang, Zheng Tang

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Models, systems, networks in economics, engineering, nature and society by D.V. Mirosh

A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions by Zhenyu Zhou, Lulu Wang, Gongjie Liu, Yuchen Li, Zhiyuan Guan, Zixuan Zhang, Pengfei Li, Yifei Pei, Jianhui Zhao, Jiameng Sun, Yahong Wang, Yiduo Shao, Xiaobing Yan

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Classification of iPSC-derived cultures using convolutional neural networks to identify single differentiated neurons for isolation or measurement by Purva Patel, Lina K. Mohammed Ali, Uma Kaushik, Mallory Wright, Kaylee Green, Jason E. Waligorski, Colin L. Kremitzki, Graham W. Bachman, Serena N. Elia, William J. Buchser

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Forecasting financial time series using a low complexity recurrent neural network and evolutionary learning approach by Ajit Kumar Rout, P.K. Dash, Rajashree Dash, Ranjeeta Bisoi

“…The paper presents a low complexity recurrent Functional Link Artificial Neural Network for predicting the financial time series data like the stock market indices over a time frame varying from 1 day ahead to 1 month ahead. …”
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Reconstructing Equatorial Electron Flux Measurements From Low‐Earth‐Orbit: A Conjunction Based Framework by D. L. Stumbaugh, J. Bortnik, S. G. Claudepierre

“…Abstract We present an artificial neural network model that reconstructs >30 keV electron flux measurements near the geomagnetic equator from low‐Earth‐orbit (LEO) observations, exploiting the global coherent nature of the high‐energy trapped electrons that constitute the radiation belts. …”
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Common and distinct neural underpinnings of the association between childhood maltreatment and depression and aggressive behavior by Yuan Li, Ting Zhang, Xin Hou, Xiaoyi Chen, Yu Mao

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CFD investigation and ANN prediction of heat transfer coefficient for fully developed turbulent air flow around double V-baffle turbulators by Abdulaziz Alasiri, H.E. Fawaz

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Predicting the compressive strength of polymer-infused bricks: A machine learning approach with SHAP interpretability by Sathvik Sharath Chandra, Rakesh Kumar, Archudha Arjunasamy, Sakshi Galagali, Adithya Tantri, Sujay Raghavendra Naganna

“…The primary innovation lies in leveraging advanced machine learning techniques, namely, artificial neural networks (ANN), support vector machines (SVM), Random Forest and AdaBoost to predict the compressive strength of these Polymer-infused bricks. …”
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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

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Reconfigurable neuromorphic functions in antiferroelectric transistors through coupled polarization switching and charge trapping dynamics by Jing Gao, Yu-Chieh Chien, Jiali Huo, Lingqi Li, Haofei Zheng, Heng Xiang, Kah-Wee Ang

“…Additionally, we further demonstrate synaptic and neuronal functions for implementing unsupervised learning rules and spiking behavior in spiking neural networks. …”
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Embedded Legendre expansion layer of physics-informed neural network with restarting strategy in solving partial differential equation in fluid dynamics by Danang A. Pratama, Maharani A. Bakar, Ruwaidiah Idris, Norizan Mohamed

“…On the other hand, single-layer Functional Link Artificial Neural Network (FLANN) has been a topic of interest in the field of artificial intelligence due to its unique architecture and computational efficiency. …”
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Estudio y simulación de las deformaciones corticales asociadas a la variación del campo gravitacional, usando redes neuronales artificiales by Figueredo Báez Yaqueline, Díaz Ramiro

“…These deformations can be used for the calculation of the gravity anomaly and magnetic anomaly through the method of Talwani. The neural computation assimilates the biological neurons as process elements that are assumed as the gravity information and the magnetic information in the inverse problem, being processed in a Neural Network Artificial with architecture Hopfield and in a Neural Network Artificial with structure cluster.…”
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A Novel Diagnostic Framework with an Optimized Ensemble of Vision Transformers and Convolutional Neural Networks for Enhanced Alzheimer’s Disease Detection in Medical Imaging by Joy Chakra Bortty, Gouri Shankar Chakraborty, Inshad Rahman Noman, Salil Batra, Joy Das, Kanchon Kumar Bishnu, Md Tanvir Rahman Tarafder, Araf Islam

“…<b>Background/Objectives:</b> Alzheimer’s disease (AD) is a progressive, neurodegenerative disorder, which causes memory loss and loss of cognitive functioning, along with behavioral changes. Early detection is important to delay disease progression, timely intervention and to increase patients’ and caregivers’ quality of life (QoL). …”
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