Machine learning-based proteomics profiling of ALS identifies downregulation of RPS29 that maintains protein homeostasis and STMN2 level by Wei Xu, Zhipeng Guo, Yian Guan, Shihui Lv, Xue Gao, Wenchen Luo, Tianlin Cheng, Zhicheng Shao, Bangbao Tao, Tao Wang, Zhixin Qiu

“…Compared to the transcriptome, proteomic profiling closely correlates with ALS pathology, which is interrogated to identify 110 proteomics-based biomarkers (Proteomics Markers for ALS 110, PMA110). Functional enrichment highlights dysregulation of ALS pathways, including protein translation and neuronal function. …”
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Time-domain brain: temporal mechanisms for brain functions using time-delay nets, holographic processes, radio communications, and emergent oscillatory sequences by Janet M. Baker, Peter Cariani

“…A temporal theory for realizing major brain functions (e.g., sensation, cognition, motivation, attention, memory, learning, and motor action) is proposed that uses temporal codes, time-domain neural networks, correlation-based binding processes and signal dynamics. …”
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Depth-Guided Monocular Object Pose Estimation for Warehouse Automation by Phan Xuan Tan, Dinh-Cuong Hoang, Anh-Nhat Nguyen, Eiji Kamioka, Ta Huu Anh Duong, Tuan-Minh Huynh, Duc-Manh Nguyen, Duc-Huy Ngo, Minh-Duc Cao, Thu-Uyen Nguyen, Van-Thiep Nguyen, Duc-Thanh Tran, Van-Hiep Duong, Anh-Truong Mai, Duc-Long Pham, Khanh-Toan Phan, Minh-Quang Do

“…However, RGBD-based methods require specialized depth sensors, which can be costly and may not function reliably in warehouse environments with reflective surfaces, varying lighting conditions, or sensor occlusions. …”
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Becoming smart “digital natives”: cultivating Chinese English majors’ new media literacy via Journalism English Reading and Listening by Zhang Danyang, Wu Yang

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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

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An Improved Northern Goshawk Optimization Algorithm for Mural Image Segmentation by Jianfeng Wang, Zuowen Bao, Hao Dong

“…To alleviate the aforementioned issues, this paper proposes a mural image segmentation algorithm based on OPBNGO by integrating the Northern Goshawk Optimization (NGO) algorithm with the off-center learning strategy, partitioned learning strategy, and Bernstein-weighted learning strategy. …”
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Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms by Nurcan Öztürk

“…In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function.…”
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Research on mine worker behavior detection in low-light underground coal mine environments by DONG Fangkai, ZHAO Meiqing, HUANG Weilong

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Ecosystem Service and Biodiversity Patterns Observed across Co-Developed Land Use Scenarios in the Piedmont: Lessons Learned for Scale and Framing by John E. Quinn, Craig Fergus, Emilia Hyland, Caroline Vickery, Iara L. Lacher, Thomas S. Akre

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Risk prediction for acute kidney disease and adverse outcomes in patients with chronic obstructive pulmonary disease: an interpretable machine learning approach by Siqi Jiang, Lingyu Xu, Xinyuan Wang, Chenyu Li, Chen Guan, Lin Che, Yanfei Wang, Xuefei Shen, Yan Xu

“…The key predictors for mortality included the use of dopamine and epinephrine drugs, cystatin c, renal function trajectory, albumin, and neutrophil percentage. …”
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Anatomically Guided Deep Learning System for Right Internal Jugular Line (RIJL) Segmentation and Tip Localization in Chest X-Ray by Siyuan Wei, Liza Shrestha, Gabriel Melendez-Corres, Matthew S. Brown

“…In this study, we propose a deep learning system that integrates an anatomical landmark segmentation, an RIJL segmentation network, and a postprocessing function to segment the RIJL course and detect the tip with accuracy and precision. …”
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Knockout of AMPA receptor binding protein Neuron-specific gene 2 (NSG2) enhances associative learning and cognitive flexibility by Amber J. Zimmerman, Antonio Serrano-Rodriguez, Melody Sun, Sandy J. Wilson, David N. Linsenbardt, Jonathan L. Brigman, Jason P. Weick

“…Abstract The vast majority of gene mutations and/or gene knockouts result in either no observable changes, or significant deficits in molecular, cellular, or organismal function. However, in a small number of cases, mutant animal models display enhancements in specific behaviors such as learning and memory. …”
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Unraveling hereditary breast cancer susceptibility: a systems biology approach on GEO datasets with functional genomic insights and implications for traditional Chinese medicine by Elham Amjad, Babak Sokouti

“…All of these have been shown to affect the functioning of cancer cells. Based on enrichment analysis, some of these herbs may boost the immune system and stop tumor growth. …”
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Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning by Wenjian Guo, Fayuan Li, Lingyu Wang, Li'an Zhu, Yicong Ye, Zhen Wang, Bin Yang, Shifeng Zhang, Shuxin Bai

“…This work presents a novel active learning framework that integrates generative adversarial networks (GAN) with a directionally constrained expected absolute improvement (EAI) acquisition function to accelerate the discovery of ultra-high temperature ceramics (UHTCs) using small data. …”
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Association of urinary metal elements with sarcopenia and glucose metabolism abnormalities: Insights from NHANES data using machine learning approaches by Xinmin Jin, Lei Li, Xiaoyan Hu, Pengfei Bi, Song Zhang, Qian Wang, Zhongwei Xiao, Hua Yang, Tongtong Liu, Lifang Feng, Jinhuan Wang

“…Background: Sarcopenia, a condition marked by the decline of skeletal muscle mass and function, is prevalent in the elderly and closely linked to abnormal glucose metabolism, particularly type 2 diabetes. …”
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Fine-tuning optimization of poly lactic acid impact strength with variation of plasticizer using simple supervised machine learning methods by Jaka Fajar Fatriansyah, Elvi Kustiyah, Siti Norasmah Surip, Andreas Federico, Agrin Febrian Pradana, Aniek Sri Handayani, Mariatti Jaafar, Donanta Dhaneswara

“…The use of machine learning to fine-tune the properties of materials is a remarkable achievement in the 21st century. …”
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Hybrid deep learning optimization for smart agriculture: Dipper throated optimization and polar rose search applied to water quality prediction. by Amal H Alharbi, Faris H Rizk, Khaled Sh Gaber, Marwa M Eid, El-Sayed M El-Kenawy, Ehsan Khodadadi, Nima Khodadadi

“…We applied this hybrid strategy to a Radial Basis Function Network (RBFN), and validated its performance improvements through extensive experiments, including ANOVA and Wilcoxon tests for both feature selection and optimization phases. …”
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Geometric Detail-Preserved Point Cloud Upsampling via a Feature Enhanced Self-Supervised Network by Shengwei Qin, Yao Jin, Hailong Hu

“…These loss functions enable efficient network training, leading to superior upsampling results. …”
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Characteristics of left ventricular dysfunction in repaired tetralogy of Fallot: A multi-institutional deep learning analysis of regional strain and dyssynchrony by Brendan T. Crabb, Rahul S. Chandrupatla, Evan M. Masutani, Sophie Y. Wong, Sachin Govil, Silvia Montserrat, Susana Prat-González, Julián Vega-Adauy, Melany Atkins, Daniel Lorenzatti, Chiara Zocchi, Elena Panaioli, Nathalie Boddaert, Laith Alshawabkeh, Lewis Hahn, Sanjeet Hegde, Andrew D. McCulloch, Francesca Raimondi, Albert Hsiao

“…Background: Patients with repaired tetralogy of Fallot (rTOF) are commonly followed with cardiovascular magnetic resonance (CMR) imaging and frequently develop right ventricular (RV) dysfunction, which can be severe enough to impact left ventricular (LV) function in some patients. In this study, we sought to characterize patterns of LV dysfunction in this patient population using deep learning synthetic strain (DLSS), a fully automated deep learning algorithm capable of measuring regional LV strain and dyssynchrony. …”
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AI in dermatology: a comprehensive review into skin cancer detection by Kavita Behara, Ernest Bhero, John Terhile Agee

“…We analyzed and categorized the articles based on four key dimensions: advantages, difficulties, methodologies, and functionalities. Results AI-based models exhibit remarkable performance in skin cancer detection by leveraging advanced deep learning algorithms, image processing techniques, and feature extraction methods. …”
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