iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…Finally, a hybrid model combining an unsupervised SOM and followed by the supervised Random Forest model returned an accuracy of 83.47% for the training and 80.77% for the test, with Bathymetry, Chlorophyll, and Coarse Sand as key predictive variables. IMESc permits the customization of plots and saving the workflows into “savepoints” guarantying reproducibility. iMESc bridges the gap between the complexity of machine learning algorithms and the need for user-friendly interfaces in environmental research. …”
Get full text

Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…Then, the immune particle swarm algorithm, which incorporates the self-regulatory mechanism of the immune system, is used to optimize the system based on the predicted model. …”
Get full text

Universal multilayer network embedding reveals a causal link between GABA neurotransmitter and cancer by Léo Pio-Lopez, Michael Levin

“…Our model made new predictions about a link between GABA and cancer that we verified experimentally in the Xenopus laevis model. …”
Get full text

Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…The positive correlation between judge evaluations and sensor data indicates judges’ ability to evaluate overall gait quality. Three different algorithms were employed to predict the judges score from the IMU measurements: Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and K-Nearest Neighbors (KNN). …”
Get full text

Hybrid AI and semiconductor approaches for power quality improvement by Ravikumar Chinthaginjala, Asadi Srinivasulu, Anupam Agrawal, Tae Hoon Kim, Sivarama Prasad Tera, Shafiq Ahmad

“…The research concludes that although deep learning models offer superior accuracy and predictive power for complex power quality scenarios, practical deployment requires careful balancing of computational demands and addressing class distribution challenges.…”
Get full text

Near-Field Nulling Control Beamfocusing Optimization for Multi-User Interference Suppression by Yuanzhe Gong, Mohammadhossein Karimi, Tho Le-Ngoc

“…The model achieves a phase error of less than 0.021 radians and a magnitude error of 0.17 dB in the predicted feeding weights. The resulting near-field beam patterns using the LCMV-based vector and the DNN-predicted vector show good agreement.…”
Get full text

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis. by Jessica L Nielson, Shelly R Cooper, John K Yue, Marco D Sorani, Tomoo Inoue, Esther L Yuh, Pratik Mukherjee, Tanya C Petrossian, Jesse Paquette, Pek Y Lum, Gunnar E Carlsson, Mary J Vassar, Hester F Lingsma, Wayne A Gordon, Alex B Valadka, David O Okonkwo, Geoffrey T Manley, Adam R Ferguson, TRACK-TBI Investigators

“…<h4>Conclusions</h4>TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. …”
Get full text

Hybrid intelligence framework for optimizing shear capacity of lightweight FRP-reinforced concrete beams by Iman Faridmehr, Moncef L. Nehdi, Mohammad Ali Sahraei, Kiyanets Aleksandr Valerievich, Chiara Bedon

“…The hybrid intelligence models reached superior predictive accuracy over traditional codes, achieving R2 values of 0.89. …”
Get full text

Secondary Migration Trend Based on Basin Modeling: A Case Study of the Cambrian Petroleum System in the Tarim Basin by Yong Yue, Bin Li, Peng Wei, Xin Zhang, Kun Zhang, Yang Suju, Xu Qingqi

“…While previous studies have relied on geological and fluid geochemical characteristics to predict migration direction, these results are often limited by the number of samples. …”
Get full text

Comprehensive analysis of pyroptosis-related genes in psoriasis and targeted gene editing of CASP1 and CASP5 using lipid nanoparticles to alleviate skin inflammation by Gexiao Xu, Guanyi Ma, Jiachen Sun, Xiaoyan Yu, Jie Sun, Bing Gao

“…The generated risk score model demonstrated robust performance in external validation datasets, showing strong predictive power for psoriasis severity and immune infiltration. …”
Get full text

Modeling the variables that influence substance consumption of people who experience homelessness in Colombia by Leandro González Támara, Sandra Patricia Barragán Moreno

“…A two-stage quantitative methodology was applied: (1) descriptive analysis of the demographic and socioeconomic characteristics of the homeless population, and (2) predictive modeling using random forest algorithms to identify key variables associated with substance use. …”
Get full text

Multimodal fusion radiomic-immunologic scoring model: accurate identification of prostate cancer progression by Zhonglin Zhang, Huan Liu, Xiling Gu, Yang Qiu, Jiangqing Ma, Guangyong Ai, Xiaojing He

“…The RDIS model demonstrates good specificity in further predicting bone metastases and castration-resistant prostate cancer (CRPC). …”
Get full text

Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…These obstacles were mitigated through the integration of algorithmically derived pseudo-rugosity and slope metrics as innovative proxies for seafloor complexity, significantly improving predictive performance. …”
Get full text

Evaluation of eco-friendly soil slope stabilization techniques for forest roads by using an Artificial Neural Network (ANN) by Kıvanç Yüksel, Neşe Gülci, Abdullah Emin Akay, Sercan Gülci

“…In the solution process, an Artificial Neural Network (ANN) model, which is one of the machine learning algorithms, was used to predict sediment yield from forest road cut slopes. …”
Get full text

Novel candidate genes may be possible predisposing factors revealed by whole exome sequencing in familial esophageal squamous cell carcinoma by Narjes Forouzanfar, Ancha Baranova, Saman Milanizadeh, Alireza Heravi-Moussavi, Amir Jebelli, Mohammad Reza Abbaszadegan

“…A more advanced method to identify new molecular biomarkers predicting disease prognosis can be whole exome sequencing. …”
Get full text

Oxygen isotope values of charred tree bark as an indicator of forest fire severity by Elizabeth McDonald, Elizabeth A. Webb, Jeffery P. Dech

“…We also analyzed pre- and post-fire Sentinel-2 imagery of the burn area to compute various Normalized Burn Ratio (NBR)-based change detection algorithms, which are known to produce reliable predictions of CBI. …”
Get full text

An immunoinformatic investigation on Rift Valley fever virus protein reveals possible epitopes for vaccines by Tanjir Hosen, Saaimatul Huq, Mohammad Abdullah-Al-Shoeb, Shahidul Islam, Muhammad Abul Kalam Azad

“…Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T-cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively. …”
Get full text

Semantic Segmentation with Multispectral Satellite Images of Waterfowl Habitat by Mateo Gannod, Nicholas Masto, Collins Owusu, Cory Highway, Katherine Brown, Abigail Blake-Bradshaw, Jamie Feddersen, Heath Hagy, Douglas Talbert, Bradley Cohen

“…Therefore, conservation planners rely on accurate predictions of wetland habitats for waterfowl at regional scales. …”
Get full text

Critical structural and functional roles for the N-terminal insertion sequence in surfactant protein B analogs. by Frans J Walther, Alan J Waring, Jose M Hernandez-Juviel, Larry M Gordon, Zhengdong Wang, Chun-Ling Jung, Piotr Ruchala, Andrew P Clark, Wesley M Smith, Shantanu Sharma, Robert H Notter

“…Surface plasmon resonance (SPR), predictive aggregation algorithms, and molecular dynamics (MD) and docking simulations further suggested a preliminary model for dimeric Super Mini-B, in which monomers self-associate to form a dimer peptide with a "saposin-like" fold. …”
Get full text

Focusing on scRNA-seq-Derived T Cell-Associated Genes to Identify Prognostic Signature and Immune Microenvironment Status in Low-Grade Glioma by Jiayu Wen, Qiaoyi Huang, Jiuxiu Yao, Wei Wei, Zehui Li, Huiqin Zhang, Surui Chang, Hui Pei, Yu Cao, Hao Li

“…The ROC curve showed that the predictive ability of the prognostic model for 1, 3, and 5 years was 0.881, 0.817, and 0.749 in the TCGA cohort, respectively. …”
Get full text