Deep Learning-Based Ground-Penetrating Radar Inversion for Tree Roots in Heterogeneous Soil by Xibei Li, Xi Cheng, Yunjie Zhao, Binbin Xiang, Taihong Zhang

“…Additionally, a GPR simulation data set and a measured data set are built in this study, which were used to train inversion models and validate the effectiveness of GPR inversion methods.The introduced GPR inversion model is a pyramid convolutional network with vision transformer and edge inversion auxiliary task (PyViTENet), which combines pyramidal convolution and vision transformer to improve the diversity and accuracy of data feature extraction. …”
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Multi-omics analysis reveals immunosuppression in oesophageal squamous cell carcinoma induced by creatine accumulation and HK3 deficiency by Yingzhen Gao, Siyu He, Xiaoyan Meng, Kun Zheng, Heyang Cui, Yikun Cheng, Xinyuan Shen, Yuanfang Zhai, Binbin Zou, Fang Wang, Hongyi Li, Pengzhou Kong, Yanqiang Wang, Xuefei Feng, Bin Yang, Ruifang Sun, Yongsheng Meng, Enwei Xu, Yanlin Guo, Ning Ding, Weimin Zhang, Xiaolong Cheng, Lunzhi Dai, Yongping Cui, Ling Zhang

“…This study aimed to provide novel insights into the molecular landscape of ESCC and identify clinically actionable targets associated with immunosuppression driven by metabolic changes. Methods We performed metabolomic and proteomic analyses combined with previous genomic and transcriptomic data, identified multi-omics-linked molecular features, and constructed metabolic-immune interaction-based ESCC classifiers in a discovery cohort and an independent validation cohort. …”
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Evaluation of Morphometric Factors on the Distribution of Debris: A Case Study on the Attica Ripples on the South of Paveh- Kermanshah Province, Iran by Mohammad Ahmadi

“…Even the distribution of scree surfaces has spread through the waterways due to displacement caused by rainfall, flood and snow avalanches. 4-Conclusion Geomorphologic and statistical analyses were performed to analyze how morphometric features may contribute to degradation. …”
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Detection of acute dengue virus infection, with and without concurrent malaria infection, in a cohort of febrile children in Kenya, 2014-2019, by clinicians or machine learning alg... by David M Vu, Amy R Krystosik, Bryson A Ndenga, Francis M Mutuku, Kelsey Ripp, Elizabeth Liu, Carren M Bosire, Claire Heath, Philip Chebii, Priscilla Watiri Maina, Zainab Jembe, Said Lipi Malumbo, Jael Sagina Amugongo, Charles Ronga, Victoria Okuta, Noah Mutai, Nzaro G Makenzi, Kennedy A Litunda, Dunstan Mukoko, Charles H King, A Desiree LaBeaud

“…DENV testing was performed afterwards. We randomly sampled 70% of the dataset to develop DENV and malaria prediction models using boosted logistic regression, decision trees and random forests, support vector machines, naïve Bayes, and neural networks with 10-fold cross validation, tuned to maximize accuracy. 30% of the dataset was reserved to validate the models. 485 subjects (7.8%) had DENV, and 3,145 subjects (50.7%) had malaria. 220 (3.5%) subjects had co-infection with both DENV and malaria. …”
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Renal tubulointerstitial lesions: a prognostic marker in idiopathic membranous nephropathy by Yonghua Liu, Xiuhua Ma, Min Yu, Xiaoling Zhou

“…After a median follow-up of 45 months, IMN patients in the TIL+ group had a lower disease remission rate and worse renal prognosis as demonstrated by Kaplan-Meier survival curves and Cox regression modeling. Logistic regression modeling identified hypertension, globular/segmental glomerulosclerosis, and intimal thickening of small renal arteries as independent risk factors for TIL in patients with idiopathic membranous nephropathy.Conclusion TIL is frequently associated with idiopathic membranous nephropathy, with more severe clinical manifestations and pathologic features, and idiopathic membranous nephropathy patients with TIL have a lower disease remission rate and worse overall renal prognosis. …”
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Mitochondrial subtypes in renal ischemia reperfusion injury guide delayed graft function and Long-Term graft prediction by Danni Hu, Zheng Wang

“…Differential expression analysis identified differentially expressed MGs (DE-MGs), and consensus clustering analysis performed cluster analysis of IRI samples. Comprehensive bioinformatics methods and machine learning were applied to establish predictive models for DGF and long-term graft survival based on DE-MGs. …”
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The Effect of Three-Dimensional Stabilization Thread Design on Biomechanical Fixation and Osseointegration in Type IV Bone by Nicholas J. Iglesias, Vasudev Vivekanand Nayak, Arthur Castellano, Lukasz Witek, Bruno Martins de Souza, Edmara T. P. Bergamo, Ricky Almada, Blaire V. Slavin, Estevam A. Bonfante, Paulo G. Coelho

“…In a low-density (Type IV) bone model, the TP 3DS implant demonstrated improved performance compared to the conventional TP, as evidenced by an increase in baseline lateral loading capacity and increased BIC during the early stages of osseointegration. …”
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Insulin resistance quantified by estimated glucose disposal rate predicts cardiovascular disease incidence: a nationwide prospective cohort study by Shiyi Tao, Lintong Yu, Jun Li, Ji Wu, Xuanchun Huang, Zicong Xie, Tiantian Xue, Yonghao Li, Lilan Su

“…The Boruta algorithm was performed for feature selection. Multivariate Cox proportional hazards regression models and restricted cubic spline (RCS) analysis were conducted to examine the associations between eGDR and CVD, and the results were expressed with hazard ratio (HR) and 95% confidence interval (CI) values. …”
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MULTIMODAL APPROACH TO THE STUDY OF SPECIALIZED TEXTS IN TECHNICAL DISCOURSE by Yuliia V. Polycheva, Volodymyr I. Vetokhin

“…The principles of the multimodal approach and a model for conducting a multimodal analysis of a text are considered. …”
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Optimization of DD-110 Neutron Generator Output for Boron Neutron Capture Therapy Using Monte Carlo Simulation by Hossam Donya, Muhammed Umer

“…The entire system’s performance was modeled and simulated using the MCNPX code, focusing on parameters both in-air and in-phantom to evaluate its efficacy. …”
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Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods by Fernanda Cristina Barbosa Lana, Carolina Coimbra Marinho, Bruno Barbosa Miranda de Paiva, Lucas Rocha Valle, Guilherme Fonseca do Nascimento, Leonardo Chaves Dutra da Rocha, Marcelo Carneiro, Joanna d‘Arc Lyra Batista, Fernando Anschau, Pedro Gibson Paraiso, Frederico Bartolazzi, Christiane Corrêa Rodrigues Cimini, Alexandre Vargas Schwarzbold, Danyelle Romana Alves Rios, Marcos André Gonçalves, Milena Soriano Marcolino

“…Integrating the drift’s knowledge into models to improve effectiveness is a challenge, requiring continuous updates and monitoring of performance in real-world applications. …”
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Urban Recreational Space Heat-Emotion Distribution and Matching Pattern Based on Machine Learning: A Case Study of Guangzhou City by Wang Fuyuan, Zhang Zhiyu, Xie Yuanjing, Yang Xinyi, Sun Miao

“…In contrast, peripheral urban zones primarily feature government residences, premium ecological recreational spaces, and hot spring resources. …”
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Integrating multi-omics data reveals the antitumor role and clinical benefits of gamma-delta T cells in triple-negative breast cancer by Guixin Wang, Shuo Wang, Wenbin Song, Chenglu Lu, Zhaohui Chen, Long He, Xiaoning Wang, Yizeng Wang, Cangchang Shi, Zhaoyi Liu, Yue Yu, Xin Wang, Yao Tian, Yingxi Li

“…Immunohistochemistry was performed to validate the prognostic value of γδT cells in breast cancer patients. …”
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Smartphone-Based Pupillometry Using Machine Learning for the Diagnosis of Sports-Related Concussion by Anthony J. Maxin, Bridget M. Whelan, Michael R. Levitt, Lynn B. McGrath, Kimberly G. Harmon

“…In the machine learning pupillometry analysis that used the synthetic minority oversampling technique to account for the significant class imbalance in our dataset, the best-performing model was a random forest algorithm with the combination of latency, maximum diameter, minimum diameter, mean constriction velocity, and maximum constriction velocity PLR parameters as feature inputs. …”
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Retinal fundus imaging as biomarker for ADHD using machine learning for screening and visual attention stratification by Hangnyoung Choi, JaeSeong Hong, Hyun Goo Kang, Min-Hyeon Park, Sungji Ha, Junghan Lee, Sangchul Yoon, Daeseong Kim, Yu Rang Park, Keun-Ah Cheon

“…ADHD screening models achieved 95.5%-96.9% AUROC. For EF function stratification, the visual and auditory subdomains showed strong (AUROC > 85%) and poor performances, respectively. …”
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Strength analysis of sectional flat wagon supporting structures when transported by a railway ferry by Alyona Lovska, Juraj Gerlici, Ján Dižo, Vasyl Ravlyuk, Andrij Rybin

“…A derived mathematical model expresses the lateral loading of the flat wagon under the conditions of a railway ferry roll. …”
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‘Words are Flowing Out Like Endless Rain Into a Paper Cup’: ChatGPT & Law School Assessments by Stuart Hargreaves

“…It performed worst on exams that featured problem-style or “issue spotting” questions asking students to apply an invented factual scenario to local legislation or jurisprudence. …”
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Cold-blooded vertebrates evolved regulatory B cells to participate in inflammatory diseases by Jie Wang, Wen-Jing Dong, Tian-Tian Tian, Chang-Song Wu, Xiang-Yang Zhang, Ya-Zhen Hu, Yi-Ru Pan, Xue-Qing Han, Jun Li, Carolina Tafalla, Yong-An Zhang, Xu-Jie Zhang

“…Methods Flow cytometry, RNA-seq, qPCR, morphological analysis, immunoblotting, immunofluorescence, recombinant IL-35 stimulation, cell co-culture in Transwell system were performed to reveal the phenotypic features, differentiation mechanism and suppressive functions of teleost CD25L+ Breg. …”
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Challenges in AI-driven multi-omics data analysis for Oncology: Addressing dimensionality, sparsity, transparency and ethical considerations by Maryem Ouhmouk, Shakuntala Baichoo, Mounia Abik

“…We also discuss how well these methods consider explainability, interpretability, and ethical aspects in developing solutions that treat private medical and sensitive information.From the 32 studies, we can divide deep learning-based multi-omics integration methods into two types: non-generative and generative models. Non-generative approaches, such as feedforward neural networks (FFNs), graph convolutional networks (GCNs), and autoencoders, are designed to extract features and perform classification directly. …”
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Multi-Class Urinary Sediment Particles Detection Based on YOLOv7 With Attention Modules by Tatsuki Komori, Hiroki Nishikawa, Keita Sasaki, Ittetsu Taniguchi, Takao Onoye

“…In experiments, we perform the proposed models on urinary sediment dataset and the results demonstrate that our proposed models outperform original YOLOv7 and a state-of-the-art urinary sediment detector in terms of recall score by 12.4% and 4.3% as well as mAP score by 7.4% and 1.6%. …”
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