Low-Code Application and Practical Implications of Common Machine Learning Models for Predicting Punching Shear Strength of Concrete Reinforced Slabs by Khuong Le Nguyen, Thanh Tu Do, Giang Huu Nguyen, Afaq Ahmad

“…The ML models and finite-element method (FEM) demonstrated superior performance compared with the literature and practical codes. Furthermore, the results emphasised the exceptional performance of the Gaussian process regression (GPR) with optimised hyperparameters, exhibiting the best performance in validation, training, and testing datasets with R2 values of 0.95, 0.99, and 0.98, respectively. …”
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Fine-Grained Fault Diagnosis Method of Rolling Bearing Combining Multisynchrosqueezing Transform and Sparse Feature Coding Based on Dictionary Learning by Guodong Sun, Yuan Gao, Kai Lin, Ye Hu

“…Finally, a linear support vector machine (LSVM) was trained with features of training samples, and the trained LSVM was employed to diagnosis the fault classification of test samples. …”
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Evaluating the Reasoning Capabilities of Large Language Models for Medical Coding and Hospital Readmission Risk Stratification: Zero-Shot Prompting Approach by Parvati Naliyatthaliyazchayil, Raajitha Muthyala, Judy Wawira Gichoya, Saptarshi Purkayastha

“…However, their reliability across critical tasks like diagnosis, medical coding, and risk prediction has received mixed reviews, especially in real-world settings without task-specific training. …”
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Exploring discrepancies in clinical coding between rural and urban hospitals in Aotearoa New Zealand in patients who underwent interhospital transfer by Anna Donaldson, Rory Miller, Garry Nixon, Gabrielle Davie

“…Anecdotally, clinical coding in NZ rural hospitals is often performed by clinicians or reception staff without formal coding training; in urban NZ hospitals this would usually be completed by formally trained clinical coders. …”
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A non-hypothesis-driven practical laboratory activity on functional metagenomics: “fishing” protein-coding DNA sequences from microbiomes by Melissa Morra, Denise Marradi, Luca Gandini, Vittorio Ivagnes, Giulia Ottolini, Alessandro Bovio, Grace Jabali, Lorenzo Maraschi, Ifeoluwa Ayomide Dada, Tonderai Vitalis Chawanda, Martina Gorla, Olga Tarasiuk, Chiara Mocchetti, Maria Felicia Soluri, Maria Felicia Soluri, Francesca Boccafoschi, Daniele Sblattero, Diego Cotella

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The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model by Yong Bai, Jing Gao, Yuwen Yan, Xu Zhao

“…The purpose of this study was to determine the value of Long chain non-coding RNA (LncRNA) RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 in the diagnosis of adult sepsis patients and to develop a Nomogram prediction model.MethodsWe screened adult sepsis microarray datasets GSE57065 and GSE95233 from the GEO database and performed differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), and machine learning methods to find the genes by random forest (Random Forest), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), respectively, with GSE95233 as the training set and GSE57065 as the validation set. …”
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Investigating the Prospects of ChatGPT in Training Medicinal Chemists and the Development of Novel Drugs by Michell O. Almeida, Artur C. G. Soares, Gustavo H. M. Sousa, Witor R. Ferraz, Gustavo Trossini

“…In the field of chemoinformatics and computational chemistry, ChatGPT can provide code examples and assist in code development, by evaluating and enhancing code readability and project documentation. …”
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Behavioural components and delivery features of early childhood obesity prevention interventions: intervention coding of studies in the TOPCHILD Collaboration systematic review by Brittany J. Johnson, Paul M. Chadwick, Samantha Pryde, Anna Lene Seidler, Kylie E. Hunter, Mason Aberoumand, Jonathan G. Williams, Hei In Lau, Sol Libesman, Jannik Aagerup, Angie Barba, Louise A. Baur, Samantha Morgillo, Lee Sanders, Sarah Taki, Kylie D. Hesketh, Karen Campbell, Alexandra Manson, Alison Hayes, Angela Webster, Charles Wood, Denise A. O’Connor, Karen Matvienko-Sikar, Kristy Robledo, Lisa Askie, Luke Wolfenden, Rachael Taylor, H. Shonna Yin, Vicki Brown, Alexander Fiks, Alison Ventura, Ata Ghaderi, Barry J. Taylor, Cathleen Stough, Christine Helle, Cristina Palacios, Eliana M. Perrin, Elizabeth Reifsnider, Finn Rasmussen, Ian M. Paul, Jennifer S. Savage, Jessica Thomson, Jinan Banna, Junilla Larsen, Kaumudi Joshipura, Ken K. Ong, Levie Karssen, Li Ming Wen, Márcia Vitolo, Margrethe Røed, Maria Bryant, Maribel Campos Rivera, Mary Jo Messito, Natalia Golova, Nina Cecilie Øverby, Rachel Gross, Rajalakshmi Lakshman, Rebecca Byrne, Russell L. Rothman, Sharleen O’Reilly, Stephanie Anzman-Frasca, Vera Verbestel, Claudio Maffeis, Kayla de la Haye, Sarah-Jeanne Salvy, Seema Mihrshahi, Janani Ramachandran, Paola Seffrin Baratto, Rebecca K. Golley, on behalf of the TOPCHILD Collaboration

“…Validation meetings confirmed coding with trialists. Narrative syntheses were performed. …”
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New Method for Isomorphism Identification of Planetary Gear Trains based on Traversing Loop by Jiawen Ding, Wei Sun

“…Then，the loop code，the loop sequence and loop degree of planetary gear trains are obtained based on the principle of improved Hamming number and the new loop matrix. …”
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Deep Learning Models to Predict Diagnostic and Billing Codes Following Visits to a Family Medicine Practice: Development and Validation Study by Akshay Rajaram, Michael Judd, David Barber

“…Visits between July 1, 2015, and June 30, 2020, containing a physician-authored note and an invoice in the electronic medical record were eligible for inclusion. We trained 2 deep learning models and compared their predictions to codes submitted for reimbursement. …”
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A Criticality and depletion analysis of the European Lead-Cooled Training Reactor (ELECTRA) by Ana Luiza Pereira Oliveira, Clarysson Alberto Mello da Silva

“…In this article, a criticality and depletion analysis of the European Lead-Cooled Training Reactor (ELECTRA), a low-power, compact, fast lead-cooled reactor, was performed. …”
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UFM: Unified feature matching pre-training with multi-modal image assistants. by Yide Di, Yun Liao, Hao Zhou, Kaijun Zhu, Qing Duan, Junhui Liu, Mingyu Lu

“…Image feature matching, a foundational task in computer vision, remains challenging for multimodal image applications, often necessitating intricate training on specific datasets. In this paper, we introduce a Unified Feature Matching pre-trained model (UFM) designed to address feature matching challenges across a wide spectrum of modal images. …”
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Effect of hope therapy training on life expectancy and general health in cancer patients by Masoumeh Movahedi, Yazdan Movahedi, Ali Farhadi

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Modeling of air braking process of 20 000 ton heavy haul train by WANG Qingyuan, ZHAO Zining, LIU Qiangqiang, WANG Kaiyun, RAO Yu, SUN Pengfei

“…In view of the limited accuracy of the traction calculation method specified in the code for train traction calculation in solving the air braking process of 20 000 ton heavy haul combined trains, based on the existing air braking calculation model of traction gauge, an air braking process solution method suitable for long marshaling heavy haul combined trains was put forward. …”
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Training-Free VLM-Based Pseudo Label Generation for Video Anomaly Detection by Moshira Abdalla, Sajid Javed

“…To address this, we propose a novel training-free pseudo-label generation module (TFPLG) for Weakly Supervised Video Anomaly Detection (WSVAD), which leverages the vision-language alignment of the pre-trained CLIP model to generate pseudo-labels without requiring any training. …”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…Conclusion This research presents a novel approach that not only enhances the accuracy of binding affinity predictions but also facilitates the identification of binding sites, showcasing the potential of pre-trained models in computational drug design. Data and code are available at https://github.com/MIALAB-RUC/SableBind .…”
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Balancing physical development and health in adolescents through controlled High-Intensity Training by Stanislav Lazarev, Iryna Kryventsova, Vasyl Lutskyi

“…The EG participated in high-intensity training sessions twice a week, with each session lasting 20 minutes. …”
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Optimization Method of High-Speed Train Composite Material Workshop Planning and Scheduling by Yanliang Jie, Lei Hao, Shujun Yan, Xueli Zhang

“…In this paper, a layered coding strategy is adopted. The first layer of coding represents the batch processing sequence. …”
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REALIZATION OF TRAINING PROGRAMME ON THE BASIS OF LINGUISTIC DATABASE FOR AUTOMATIC TEXTS PROCESSING SYSTEM by M. A. Makarych

“…The main advantage of the processor is using special semantic codes in the alphabetical dictionary. The semantic codes have been developed in accordance with a lexical-semantic classification. …”
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Evaluating the representational power of pre-trained DNA language models for regulatory genomics by Ziqi Tang, Nirali Somia, Yiyang Yu, Peter K. Koo

“…Discussion This work highlights a major gap with current gLMs, raising potential issues in conventional pre-training strategies for the non-coding genome.…”
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