BLACK HUMOUR: ORIGIN DESCRIPTION AND AN ATTEMPT OF IDENTIFICATION by Iryna A. Blynova.

“…Typical means at the syntactic level are overinterrogations and explanations based on repetitions with an evaluation of what was heard. This evaluation is expressed by declarative, exclamatory or interrogative sentences. …”
Get full text

Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction by Hua Cai, Liuqing Zhou, Yao Hu, Tao Zhou

Get full text

Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

“…The objective of this study was to assess the feasibility of using shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. Contrastive principal component analysis (PCA), cluster-based methods, and explainable artificial intelligence (AI) were evaluated for the detection of two anomalous sample classes using longitudinal metagenomic profiling of fluid milk compared to baseline (BL) samples collected under comparable circumstances. …”
Get full text

Geospatial parametric approach for identifying optimal sites for wind-solar hybrid energy systems by Nyange Augustine Mbufua, Pascalin Tiam Kapen, François Ngapgue, Armand Nzeukou Takougang

“…Within the present framework, the paper investigates and develops a geospatial-based parametric multi-criteria decision algorithm (GIS-MCDA), i.e., TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), and AHP (Analytic Hierarchy Process), which is applied to determine the most suitable locations for the installation of wind-solar hybrid renewable energy systems in a sub-area (Koung-Khi) of the West Region of Cameroon. …”
Get full text

A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery by Yanjuan Jia, Yuanyuan Ma, Zhenhao Li, Wenze Zhang, Rukun Lu, Wanxia Wang, Chaojun Wei, Chunyan Wei, Yonghong Li, Xiaoling Gao, Tao Qu

“…Immune checkpoint inhibitor (ICI) response between PS-related high- and low-risk groups was evaluated using TIDE algorithm scores. Potential therapeutic agents targeting signature genes were screened via Connectivity Map and HERB database analyses, followed by molecular docking validation. …”
Get full text

Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models by Benedictor Alexander Nguchu, Benedictor Alexander Nguchu, Yifei Han, Yanming Wang, Peter Shaw

“…We use machine learning (ML) algorithms, including Random Forest, Logistic Regression, and Support Vector Machine, to evaluate the diagnostic power of the brain features and network patterns in differentiating the PD subtypes and distinguishing PD from HC. …”
Get full text

Machine learning–guided single-cell multiomics uncovers GDF15-driven immunosuppressive niches in NSCLC: A translational framework for overcoming anti-PD-1 resistance by Xianfei Zhang, Zhengxin Yin, Xueyu Chen, Nengchong Zhang, Shengjia Yu, Congcong Zhu, Lianggang Zhu, Liulan Shao, Bin Li, Runsen Jin, Hecheng Li

“…We integrated multiomics profiling with machine learning to systematically identify determinants of ICB efficacy. Comparative evaluation of 22 survival algorithms across four NSCLC cohorts (n=156) led to the development of an Accelerated Oblique Random Survival Forest model, which outperformed conventional Cox regression and deep learning methods in predictive accuracy (training C-index=0.864; test C-index=0.748). …”
Get full text

Comparative analysis and selection of the geometry of the microphone array based on MEMS microphones for sound localisation by Andrii Riabko, Tetiana Vakaliuk, Oksana Zaika, Roman Kukharchuk, Yuriy Smorzhevsky

“…The tasks to be addressed include analyzing spatial-frequency characteristics of various microphone array geometries (Uniform Linear Array, Uniform Planar Array, Uniform Circular Array, and Uniform Concentric Array), comparing beamforming algorithms (delay-and-sum, differential, and superdirective), and evaluating their performance under isotropic noise fields and coherent noise sources. …”
Get full text

Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury by Tianyun Gao, Zhiqiang Nong, Yuzhen Luo, Manqiu Mo, Zhaoyan Chen, Zhenhua Yang, Ling Pan

“…The area under the receiver operating characteristic curve (ROC-AUC) was used to evaluate the differentiation accuracy and performance of the prediction model in the validation queue. …”
Get full text

An in silico evaluation of lorlatinib as a potential therapy for novel amino acid substitutions in the tyrosine kinase domain of the ALK protein associated with cancer by Richard Junior Zapata Dongo, Julio A. Poterico, Diletta Fontana, Luca Mologni, Carla Alvarez-Chacon, Juan Rojas-Armas, Jaeson Calla

“…Using the SIFT and Polyphen-2 algorithms, we identified 53 deleterious ALK mutations associated with different newly recognized cancer types. …”
Get full text

Identification of ZNF652 as a Diagnostic and Therapeutic Target in Osteoarthritis Using Machine Learning by Chen Y, Liang R, Zheng X, Fang D, Lu WW, Chen Y

“…The accuracy of these DEGs in diagnosing OA was evaluated using the Receiver Operating Characteristic (ROC) Curve. …”
Get full text

Identification of ferroptosis-related gene signatures in temporal lobe epilepsy with hippocampal sclerosis by Fan Gao, Jinzi Li

“…We used weighed gene co-expression network analysis (WGCNA) algorithm, single-factor logistic regression analysis, and LASSO algorithm to screen characteristic FR-DEGs. …”
Get full text

Optimized breast cancer diagnosis using self-adaptive quantum metaheuristic feature selection by Alok Kumar Shukla, Shubhra Dwivedi, Deepak Singh, Sunil Kumar Singh, Diwakar Tripathi, Ram Kishan Dewangan

“…Comparative results based on optimal computing time and performance are also offered to empirically analyze the traditional algorithms. Therefore, this paper aims to evaluate the most recent quantum-inspired metaheuristic algorithms in WBCD and WDBC databases, emphasizing their advantages and disadvantages.…”
Get full text

Integrated intelligent neuro-evolutionary computing approach to study SEIRC model representing campylobacteriosis transmission dynamics by Muhammad Shoaib, Saba Kainat, Areej Abdullah Alabduljabbar, Kottakkaran Sooppy Nisar, Muhammad Asif Zahoor Raja

“…The objective of the presented study is to develop a neuro-evaluation-based algorithm for the mathematical solution of the SEIRC model that describes the dynamics of campylobacteriosis transmission (CBT) using the artificial neural network along with log-sigmoid as an activation function (ANN-LS) and the properties of both genetic algorithms and sequential quadratic programming (GASQP). …”
Get full text

Seakeeping of Hydrofoil-Equipped Unmanned Surface VehicleBased on LQR and ZOA by Xinhua SHUI, Fuhai DUAN

“…To evaluate the seakeeping of a hydrofoil-equipped unmanned surface vessel(USV), a linear quadratic regulator(LQR) was adopted, and its parameters were optimized using the zebra optimization algorithm(ZOA), with the amplitudes of roll, pitch, and heave motions as key metrics. …”
Get full text

Oxidative stress-related genes in uveal melanoma: the role of CALM1 in modulating oxidative stress and apoptosis and its prognostic significance by Yue Wu, Xiaoyan Cai, Menghan Hu, Runyan Cao, Yong Wang

“…Experimental validation encompassed H2O2-induced oxidative stress assays and CALM1 overexpression analysis in UVM cells to evaluate its protective effects.ResultsA total of 2,576 differentially expressed genes (DEGs) were identified, with 185 overlapping OSGs enriched in pathways such as HIF-1, FoxO, PI3K-Akt, and apoptosis. …”
Get full text

Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models by Izabela Cristina de Oliveira, Ricardo Gava, Dthenifer Cordeiro Santana, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Mayara Favero Cotrim, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro

“…The objectives of this work are (i) to classify soybean cultivars under different irrigation managements using hyperspectral data, looking for the best machine-learning algorithm for the classification and the input that improves the performance of the models. …”
Get full text

Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…The CatBoost (CATB) algorithm was optimized via 5-fold cross-validation and random grid search using 24 routine blood parameters. …”
Get full text

CT-Derived Features as Predictors of Clot Burden and Resolution by Quentin Auster, Omar Almetwali, Tong Yu, Alyssa Kelder, Seyed Mehdi Nouraie, Tamerlan Mustafaev, Belinda Rivera-Lebron, Michael G. Risbano, Jiantao Pu

“…These patients were referred for invasive cardiopulmonary exercise testing (CPET) at the University of Pittsburgh Medical Center from 2018 to 2022, for whom we have ground truth classification of chronic PE, as well as CT-derived features related to body composition, cardiopulmonary vasculature, and PE clot burden using artificial intelligence (AI) algorithms. We applied Lasso regularization to select parameters, followed by (1) Ordinary Least Squares (OLS) regressions to analyze the relationship between clot burden and the selected parameters and (2) logistic regressions to differentiate between chronic and resolved patients. …”
Get full text

Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation by Jin Han, Liang Yang

“…Using TF-IDF-weighted cosine similarity evaluation, our model achieved a τ of 0.528, ρ of 0.518, and an MAE of 1.343. …”
Get full text