Empowering Particle Jamming Soft Gripper with Tactility via Stretchable Optoelectronic Sensing Skin by Liyan Mo, Wenhao Xie, Jingting Qu, Jiutian Xia, Yunquan Li, Yuanfang Zhang, Tao Ren, Yang Yang, Juan Yi, Changchun Wu, Yonghua Chen

“…It can precisely distinguish between different grasping postures using a light gradient boosting machine (LightGBM) learning model. Furthermore, it can effectively detect the slippage of grasped objects, facilitating accurate closed‐loop control for secure manipulation.…”
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Smart Driving Hardware Augmentation by Flexible Piezoresistive Sensor Matrices with Grafted‐on Anticreep Composites by Kaifeng Chen, Hua Yang, Ang Wang, Linsen Tang, Xin Zha, Ndeutala Selma Iita, Hong Zhang, Zhuoxuan Li, Xinyu Wang, Wei Yang, Shaoxing Qu, Zongrong Wang

“…The recognition of sitting postures is achieved by two 12 × 12 matrices facilitated by machine learning, which prompts the potential for the augmentation of smart driving.…”
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The Accuracy of the NSQIP Universal Surgical Risk Calculator Compared to Operation-Specific Calculators by Mark E. Cohen, PhD, Yaoming Liu, PhD, Bruce L. Hall, MD, PhD, MBA, FACS, Clifford Y. Ko, MD, MS, MSHS, FACS

“…For the N-RC, a cohort of 5,020,713 NSQIP patient records were randomly divided into 80% for machine learning algorithm training and 20% for validation. …”
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Effectiveness of mental health interventions for older adults in South Asia: A scoping review. by Hoimonty Mazumder, Farah Faizah, Easter Protiva Gain, Irfath Sharmin Eva, Kaniz Ferdouse Mou, Nobonita Saha, Farzana Rahman, Jyoti Das, A M Khairul Islam, Fazilatun Nesa, M Mahbub Hossain

“…Across studies, mental health interventions can be broadly categorized into the following types- 1) traditional Yoga, Tai chi, or other meditative movements; 2) behavioral, occupational, or learning-based interventions; 3) tech-based interventions; 4) music therapy; and 5) new healthcare model. …”
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Tongue-LiteSAM: A Lightweight Model for Tongue Image Segmentation With Zero-Shot by Daiqing Tan, Hao Zang, Xinyue Zhang, Han Gao, Ji Wang, Zaijian Wang, Xing Zhai, Huixia Li, Yan Tang, Aiqing Han

“…Objective: Tongue image segmentation is a crucial step in the intelligent recognition of tongue diagnosis in Traditional Chinese Medicine (TCM). Existing deep learning-based tongue image segmentation models face issues such as poor versatility and insufficient expressiveness in zero-shot tasks. …”
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Early Detection of Verticillium Wilt in Cotton by Using Hyperspectral Imaging Combined with Recurrence Plots by Fei Tan, Xiuwen Gao, Hao Cang, Nianyi Wu, Ruoyu Di, Jingkun Yan, Chengkai Li, Pan Gao, Xin Lv

“…This study proposes an early detection method for cotton wilt disease using hyperspectral imaging and recurrence plots (RP) combined with machine learning techniques. First, spectral curves were collected and analyzed under three conditions of cotton plants: healthy, asymptomatic, and symptomatic. …”
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses by Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang

“…Here we show that the deep learning models can non-invasively predict the likelihood of malignant and aggressive pathology of a renal mass based on preoperative multi-phase CT images.…”
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Using computer modeling to find new LRRK2 inhibitors for parkinson’s disease by María C. García, Sebastián A. Cuesta, José R. Mora, Jose L. Paz, Yovani Marrero-Ponce, Frank Alexis, Edgar A. Márquez

“…This study aims to create a detailed dataset to build strong predictive models with various machine learning algorithms. An ensemble modeling approach was employed to screen the DrugBank database, aiming to repurpose approved medications as potential treatments for Parkinson’s disease (PD). …”
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Estimating rare disease prevalence and costs in the USA: a cohort study approach using the Healthcare Cost Institute claims data by Keith A Crandall, Christine M Cutillo, Ainslie Tisdale, Mahdi Baghbanzadeh, Reva L Stidd, Manpreet S Khural, Laurie J Hartman, Jeff Greenberg, Kevin B Zhang, Ali Rahnavard

“…Building capabilities to use machine learning to accelerate the diagnosis of RDs would vastly improve with changes to healthcare data, such as standardising data input, linking databases, addressing privacy issues and assigning ICD-10 codes for all RDs, resulting in more robust data for RD analytics.…”
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Sex-specific association between maternal childhood adversities and offspring’s weight gain in a Brazilian cohort by Vinicius Oliveira Santana, Aline Camargo Ramos, Hugo Cogo-Moreira, Célia Maria Araújo, Barbara Shibuya Alves, Lucas Ribeiro, Aline Lodi, Ana Carolina Coelho Milani, Ivaldo Silva, Cristiane S. Duarte, Jonathan Posner, Andrea Parolin Jackowski

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Coordinated conformational changes in P450 decarboxylases enable hydrocarbons production from renewable feedstocks by Wesley Cardoso Generoso, Alana Helen Santana Alvarenga, Isabelle Taira Simões, Renan Yuji Miyamoto, Ricardo Rodrigues de Melo, Ederson Paulo Xavier Guilherme, Fernanda Mandelli, Clelton Aparecido Santos, Rafaela Prata, Camila Ramos dos Santos, Felippe Mariano Colombari, Mariana Abrahão Bueno Morais, Rodrigo Pimentel Fernandes, Gabriela Felix Persinoti, Mario Tyago Murakami, Leticia Maria Zanphorlin

“…Combining X-ray crystallography, molecular dynamics simulations, and machine learning, we have identified intricate molecular rearrangements within the active site that enable the Cβ atom of the substrate to approach the heme iron, thereby promoting oleate decarboxylation. …”
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Chemically Engineered GaN Thin Films for Light‐Stimulated Artificial Synapses by Xiaoqin Yang, Jiawen Lu, Luyu Zhao, Xiaorui Han, Zhongwei Bai, Peiwen Quan, Liangshuai Xie, Liang Li, Haoxuan Sun, Mark Hermann Rummeli, Bingcheng Luo, Hong Gu

“…The device demonstrates the ability to mimic various biological synaptic functions, including learning‐experience behavior, the transition from short‐term to long‐term memory, paired‐pulse facilitation, and visual recognition and memory. …”
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Phytochemical screening and neuro-pharmacological activity of Mimosa pudica flowers: Integrating in vitro, in silico and in vivo approaches by Fahmida Alam, Rashedul Alam, A.T.M. Yusuf, Joya Datta Ripa, Raktim Das Nithin, Sourav Barua, Mohammed Fazlul Kabir, Seong-Tshool Hong, Hea-Jong Chung

“…It also has effects on memory and learning, which could lead to significant gains in pharmaceutical development and medical progress.…”
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Improving explainability of post-separation suicide attempt prediction models for transitioning service members: insights from the Army Study to Assess Risk and Resilience in Servi... by Emily R. Edwards, Joseph C. Geraci, Sarah M. Gildea, Claire Houtsma, Jacob A. Holdcraft, Chris J. Kennedy, Andrew J. King, Alex Luedtke, Brian P. Marx, James A. Naifeh, Nancy A. Sampson, Murray B. Stein, Robert J. Ursano, Ronald C. Kessler

“…As universal prevention programs have been unable to resolve this problem, a previously reported machine learning model was developed using pre-separation predictors to target high-risk transitioning service members (TSMs) for more intensive interventions. …”
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Critical factors influencing live birth rates in fresh embryo transfer for IVF: insights from cluster ensemble algorithms by Zheng Yu, Xiaoyan Zheng, Jiaqi Sun, Pengfei Zhang, Ying Zhong, Xingyu Lv, Hongwen Yuan, Fanrong Liang, Dexian Wang, Jie Yang

“…By combining feature matrices from NMF, accelerated multiplicative updates for non-negative matrix factorization (AMU-NMF), and the generalized deep learning clustering (GDLC) algorithm. NMFE exhibits superior accuracy and reliability in analyzing the in vitro fertilization and embryo transfer (IVF-ET) dataset. …”
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Detection of Alzheimer Disease in Neuroimages Using Vision Transformers: Systematic Review and Meta-Analysis by Vivens Mubonanyikuzo, Hongjie Yan, Temitope Emmanuel Komolafe, Liang Zhou, Tao Wu, Nizhuan Wang

“…Vision transformers (ViTs) are emerging as promising deep learning models in medical imaging, with potential applications in the detection and diagnosis of AD. …”
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Advancing soil-structure interaction (SSI): a comprehensive review of current practices, challenges, and future directions by Imtiyaz Akbar Najar, Raudhah Ahmadi, Akeem Gbenga Amuda, Raghad Mourad, Neveen El Bendary, Idawati Ismail, Nabilah Abu Bakar, Shanshan Tang

“…Additionally, the review discusses recent innovations, including the application of machine learning and advanced computational tools, and their potential to enhance the accuracy and efficiency of SSI analysis. …”
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Pemeringkatan Pencarian pada Buku Pedoman Akademik Filkom UB Menuju Merdeka Belajar dan Free E-Book Pembelajaran Sebagai Prototype Local Smart Micro Search Engine Menggunakan Algor... by Imam Cholissodin, Akhmad Sa’rony, Rona Salsabila, Ilham Firmansyah, Guedho Augnifico Mahardika, Andreas Pardede, Zaien Bin Umar Alaydrus

“…Abstract The Brawijaya University FILKOM Academic Handbook is an important academic information need, as well as learning support books such as Free e-Books for students. …”
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Distributed representations enable robust multi-timescale symbolic computation in neuromorphic hardware by Madison Cotteret, Hugh Greatorex, Alpha Renner, Junren Chen, Emre Neftci, Huaqiang Wu, Giacomo Indiveri, Martin Ziegler, Elisabetta Chicca

“…To address this, we describe a single-shot weight learning scheme to embed robust multi-timescale dynamics into attractor-based RSNNs, by exploiting the properties of high-dimensional distributed representations. …”
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DPD-YOLO: dense pineapple fruit target detection algorithm in complex environments based on YOLOv8 combined with attention mechanism by Cong Lin, Wencheng Jiang, Weiye Zhao, Lilan Zou, Zhong Xue

“…With the development of deep learning technology and the widespread application of drones in the agricultural sector, the use of computer vision technology for target detection of pineapples has gradually been recognized as one of the key methods for estimating pineapple yield. …”
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