Learning from Octopuses: Cutting-Edge Developments and Future Directions by Jinjie Duan, Yuning Lei, Jie Fang, Qi Qi, Zhiming Zhan, Yuxiang Wu

Get full text

Application of Machine Learning Technologies for Managing Multifactor Threats in an Integrated Model of Cognitive Security Center at Defense Industry Enterprise by Pavel Panilov, Tatiana Tsibizova

Get full text

A Study on Distributed Multi-Sensor Fusion for Nonlinear Systems Under Non-Overlapping Fields of View by Liu Wang, Yang Zhou, Wenjia Li, Lijuan Shi, Jian Zhao, Haiyan Wang

Get full text

Exploring Mechanisms of Lang Qing Ata in Non-Alcoholic Steatohepatitis Based on Metabolomics, Network Pharmacological Analysis, and Experimental Validation by Li S, Zhu H, Zhai Q, Hou Y, Yang Y, Lan H, Jiang M, Xuan J

“…By integrating known databases and target prediction algorithms, which encompassed database-based target prediction, protein-protein interaction networks, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, we unveiled the potential key targets and signaling pathways that these bioactive components might engage with. …”
Get full text

Identification of m6 A-regulated ferroptosis biomarkers for prognosis in laryngeal cancer by Xin Wang, Wen Zhang, Kun Liang, Yujuan Wang, Jin Zhang, Jinping Wang, An Li, Yonggang Yun, Hiu Liu, Yanan Sun

“…Furthermore, drug sensitivity prediction found that 19 chemotherapy drugs were strongly correlated with a risk score. …”
Get full text

De novo KCNK4 variant caused epilepsy with febrile seizures plus, neurodevelopmental abnormalities, and hypertrichosis by Hong-Jun Yan, Wen-Hui Liu, Min-Xing Xu, Peng-Yu Wang, Yu-Jie Gu, Hua Li, Jing Guo, Sheng Luo

“…The identified variant was absent in normal populations, indicated to alter hydrogen bonds with surrounding residues by various protein modeling, predicted to be damaging for protein function by twenty algorithms, located in residues of high conservation across species, and classified as pathogenic by the ACMG guidelines. …”
Get full text

Machinability Assessment and Multi-Objective Optimization of Graphene Nanoplatelets-Reinforced Aluminum Matrix Composite in Dry CNC Turning by Nikolaos A. Fountas, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

“…The results indicated that the feed rate was the dominant parameter affecting both objectives, namely the main cutting force and surface roughness, while the NSGA-II algorithm was capable of delivering advantageous solutions for enhancing machinability with less than 10% error predictions when comparing simulated and actual machining results.…”
Get full text

Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. …”
Get full text

The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…This study utilized five years of daily meteorological data (from 1 January 2019 to 31 December 2023) to model atmospheric conditions and two years of daily air pollutant data (from 21 December 2021 to 20 December 2023) to simulate how pollutant levels would respond to annual temperature increases of 1 °C and 2 °C, employing a Support Vector Machine, a supervised machine learning algorithm. Predictive models were developed for both annual averages and seasonal variations. …”
Get full text

Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Methods and Results This study analyzed 8,119 HER2‐positive HR‐negative breast cancer patients from the SEER database, randomly allocated to training/validation/test cohorts (7:1:2 ratio). Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
Get full text

Transformation of Management Technologies in the Digital Economy by P. A. Levchaev, B. Khezazna

Get full text

Digital Eversion of a Hollow Structure: An Application in Virtual Colonography by Jun Zhao, Liji Cao, Tiange Zhuang, Ge Wang

“…Together with other techniques, digital eversion may help improve screening, diagnosis, surgical planning, and medical education. Two eversion algorithms are proposed and evaluated in numerical simulation to demonstrate the feasibility of the approach.…”
Get full text

Optimal Mobile Sensor Scheduling for a Guaranteed Coverage Ratio in Hybrid Wireless Sensor Networks by Zhixin Fu, Keyou You

Get full text

Monthly Rainfall Estimation Using Data-Mining Process by Özlem Terzi

Get full text

Short-Term Load Forecasting Based on EEMD-WOA-LSTM Combination Model by Lei Shao, Quanjie Guo, Chao Li, Ji Li, Huilong Yan

“…Compared with the prediction results of EEMD-ARMA model, RNN model, LSTM model, and WOA-LSTM model, the combined prediction model optimized by whale bionics has less prediction error and higher prediction accuracy.…”
Get full text

Genotypes Diversity and Virulence Factor screening of Trichomonas vaginalis Isolated from Pregnant Women in Mosul (North of Iraq) by Fouad S. I. Al-Rubaye, Firas M. B. Alkhashab

“…Samples underwent microscopic examination and nucleic acid detection of AP65-1 gene, the wet smear test showed that 16.18%  of the collected specimen were positive while the parasite appeared only in 8.9% of the samples stained with Giemsa dye, the molecular screening for AP65-1gene that encodes for the surface attachment protein showed high sensitivity level of 100 at 50 specificity level in compare with other routine methods, the algorithm was evaluated according to specificity, sensitivity, and predictive values. …”
Get full text

RuleKit2: Faster and simpler rule learning by Adam Gudyś, Cezary Maszczyk, Joanna Badura, Adam Grzelak, Marek Sikora, Łukasz Wróbel

“…Rules offer an invaluable combination of predictive and descriptive capabilities. Our package for rule-based data analysis, RuleKit, has proven its effectiveness in classification, regression, and survival problems. …”
Get full text

Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). …”
Get full text

Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Feature selection was performed using a novel approach derived from gene expression analysis, based on the DNetPRO algorithm. The prediction was done using a Support Vector Classifier (SVC) with a 10-fold cross-validation. …”
Get full text

A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…The proposed method yielded a maximum error of 163 mm, indicating a 23.5% reduction compared to the 213 mm obtained using the PL-VINS algorithm. …”
Get full text