Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov, Pavel V. Nesterov, Timur A. Aliev, Alexandra A. Timralieva, Alexander S. Novikov, Ekaterina V. Skorb

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A bespoke water T–maze apparatus and protocol: an optimized, reliable, and repeatable method for screening learning, memory, and executive functioning in laboratory mice by Jeremy Davidson Bailoo, Susan E. Bergeson, Igor Ponomarev, Joshua O. Willms, Brent R. Kisby, Gail A. Cornwall, Clinton C. MacDonald, J. Josh Lawrence, J. Josh Lawrence, Vadivel Ganapathy, Sathish Sivaprakasam, Praneetha Panthagani, Scott Trasti, Justin A. Varholick, Michael Findlater, Amrika Deonarine

“…Given the robust performance observed across spatial acquisition (learning and memory) as well as during reversal learning (executive function), we further reduced (by 43%) the overall distance and time that the animal must swim in order to find the escape platform in a bespoke standalone Water T-Maze (WTM). …”
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Virally mediated expression of a biologically active peptide to restrain the nuclear functions of ERK1/2 attenuates learning extinction but not acquisition by Bar Izkovich, Adonis Yiannakas, Sapir Ne’eman, Sailendrakumar Kolatt Chandran, Kobi Rosenblum, Efrat Edry

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Evaluating the Effect of Thermal Treatment on Phenolic Compounds in Functional Flours Using Vis–NIR–SWIR Spectroscopy: A Machine Learning Approach by Achilleas Panagiotis Zalidis, Nikolaos Tsakiridis, George Zalidis, Ioannis Mourtzinos, Konstantinos Gkatzionis

“…This study explores the thermal stability of phenolic compounds in various functional flours using visible, near and shortwave-infrared (Vis–NIR–SWIR) spectroscopy (350–2500 nm), integrated with machine learning (ML) algorithms. …”
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Machine Learning-Assisted High-Throughput Screening for Electrocatalytic Hydrogen Evolution Reaction by Guohao Yin, Haiyan Zhu, Shanlin Chen, Tingting Li, Chou Wu, Shaobo Jia, Jianxiao Shang, Zhequn Ren, Tianhao Ding, Yawei Li

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Uncovering biologically relevant Autism subtypes using advanced machine learning techniques by Christopher "Gabby" Vento, Joseph Cubells, Larry Young, Elissar Andari

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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

Subjects: “…Reinforcement learning…”
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Estimation of Cation Exchange Capacity for Low-Activity Clay Soil Fractions Using Experimental Data from South China by Jun Zhu, Zhong-Xiu Sun

Subjects: “…pedotransfer function…”
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Screening tools for subjective cognitive decline and mild cognitive impairment based on task-state prefrontal functional connectivity: a functional near-infrared spectroscopy study by Zhengping Pu, Hongna Huang, Man Li, Hongyan Li, Xiaoyan Shen, Lizhao Du, Qingfeng Wu, Xiaomei Fang, Xiang Meng, Qin Ni, Guorong Li, Donghong Cui

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Palmitoylation regulators drive the progression of clear cell renal cell carcinoma through Inhibition of cuproptosis: insights into the role of ZDHHC18 by Wei Xu, Xiao-chao Chen, Yang Wang, Jian-chun Chen, Zhi-jun Cao, Ru Huang, Chao Chen, Dao-rong Hou, Min-jun Jiang, Chen Xu

“…Abstract Background Protein palmitoylation is a reversible post-translational modification that increases protein hydrophobicity, which can affect protein localization, stability, and function. Although palmitoylation is frequently observed in various cancers, the specific mechanisms by which it influences clear cell renal cell carcinoma (ccRCC) are still not well understood. …”
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Machine learning-based smart irrigation controller for runoff minimization in turfgrass irrigation by Sambandh Dhal, Jorge Alvarado, Ulisses Braga-Neto, Benjamin Wherley

Subjects: “…Machine learning…”
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Earthquake induced liquefaction hazard analysis for Chittagong City using machine learning by Md. Mehedi Hasan, Md. Zillur Rahman, Abul Kashem Faruki Fahim

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Rate of brain aging associates with future executive function in Asian children and older adults by Susan F Cheng, Wan Lin Yue, Kwun Kei Ng, Xing Qian, Siwei Liu, Trevor WK Tan, Kim-Ngan Nguyen, Ruth LF Leong, Saima Hilal, Ching-Yu Cheng, Ai Peng Tan, Evelyn C Law, Peter D Gluckman, Christopher Li-Hsian Chen, Yap Seng Chong, Michael J Meaney, Michael WL Chee, BT Thomas Yeo, Juan Helen Zhou

“…Moreover, the longitudinal change in brain age gap reflects developing and aging processes in the brain, relating to future cognitive function.…”
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Characterizing Duodenal Immune Microenvironment in Functional Dyspepsia: An AutoML-Driven Diagnostic Framework by Zhang X, Fan X, Hu X, Qian Z, Li J, Wu W, Chen L, Wu S, Ma L, Yang C, Zhang T, Su X, Wei W

Subjects: “…Functional dyspepsia…”
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The efficacy of training on the four quadrant brain processes on cognitive functions of students with mathematical disorders by zohreh sadat moeini, farnaz Keshavarzi Arshadi, Masoud Gholam Ali Lavasani, SAEED hasanzadeh

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An exploration of distinguishing subjective cognitive decline and mild cognitive impairment based on resting-state prefrontal functional connectivity assessed by functional near-in... by Zhengping Pu, Zhengping Pu, Hongna Huang, Man Li, Hongyan Li, Xiaoyan Shen, Qingfeng Wu, Qin Ni, Yong Lin, Donghong Cui

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A Robust Multi-Modal Deep Learning-Based Fault Diagnosis Method for PV Systems by Shahabodin Afrasiabi, Sarah Allahmoradi, Mousa Afrasiabi, Xiaodong Liang, C. Y. Chung, Jamshid Aghaei

“…To enhance the proposed model’s robustness and accuracy, a probabilistic loss function based on the entropy theory is formulated. …”
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A novel method (RIM-Deep) for enhancing imaging depth and resolution stability of deep cleared tissue in inverted confocal microscopy by Yisi Liu, Pu Wang, Junjie Zou, Hongwei Zhou

“…To overcome these challenges, the RIM-Deep was developed to significantly improve deep imaging capabilities without compromising the normal function of the confocal microscope. This system facilitates deep immunofluorescence imaging of the prefrontal cortex in cleared macaque tissue, extending imaging depth from 2 mm to 5 mm. …”
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Folk High School as a Supportive Environment for Participants with High-Functioning Autism by Joel Hedegaard, Martin Hugo, Cecilia Bjursell

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