HDN-DDI: a novel framework for predicting drug-drug interactions using hierarchical molecular graphs and enhanced dual-view representation learning by Jinchen Sun, Haoran Zheng

“…Moreover, HDN-DDI exhibits substantial improvements in the cold-start setting with boosts of 4.96% in accuracy and 7.08% in F1 score on previously unseen drugs. …”
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The Effects of Laurencia caspica Algae Extract on Hemato-Immunological Parameters, Antioxidant Defense, and Resistance against Streptococcus agalactiae in Nile tilapia (Oreochromis... by Majid Khanzadeh, Babak Beikzadeh, Seyed Hossein Hoseinifar

“…Natural immune stimulants are among the most effective chemicals for boosting immunity and fish welfare. This study aims to investigate the effects of red macroalgae extract (Laurencia caspica) on hematological, immunological, antioxidant, biochemical, and disease resistance against S. agalactiae in Nile tilapia for 50 days. …”
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Elegant and Innovative Recoding Strategies for Advancing Vaccine Development by François Meurens, Fanny Renois, Uladzimir Karniychuk

“…Synonymous recoding, involving numerous codon alterations, boosts safety and vaccine stability. One challenge is balancing attenuation with yield; however, innovations like Zinc-finger antiviral protein (ZAP) knockout cell lines can enhance vaccine production. …”
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Determination of 5-fluorouracil anticancer drug solubility in supercritical CO 2 using semi-empirical and machine learning models by Gholamhossein Sodeifian, Ratna Surya Alwi, Reza Derakhsheshpour, Nedasadat Saadati Ardestani

“…Three models with different approaches were applied to correlate and model the experimental data set: (i) seven density-based models, (ii) PR equations of state (vdW2 mixing rule), and (iii) machine learning-based models, namely non-linear regressions, Random Forest, Gradient Boosting, Decision Tree, and Kernel Ridge. All tested models successfully correlate and model the solubility data within an acceptable accuracy. …”
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Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages by Sijin Lee, Hyun Ji Park, Jumi Hwang, Sung Woo Lee, Kap Su Han, Won Young Kim, Jinwoo Jeong, Hyunggoo Kang, Armi Kim, Chulung Lee, Su Jin Kim

“…Random forest and light gradient boosting machine (LightGBM) were applied to develop predictive models. …”
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Cognition and Implementation of Disaster Preparedness among Japanese Dialysis Facilities by Hidehiro Sugisawa, Toshio Shinoda, Yumiko Shimizu, Tamaki Kumagai

“…Our results suggest that boosting self-efficacy and support from surroundings among key persons of disaster preparedness in dialysis facilities may contribute to the advancement of the different domains of disaster preparedness.…”
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Quantifying Impacts of Local Traffic Policies on PM Concentrations Using Low Cost Sensors in Berlin by Sean Schmitz, Alexandre Caseiro, Andreas Kerschbaumer, Erika von Schneidemesser

“…We calibrate the Plantower sensors using Schmitz et al.’s (2021b) methodology and test three different models: multiple linear regression (MLR), gradient-boosting machines (GBM), and support vector machines (SVM). …”
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The Real-Time Prediction of Cracks and Wrinkles in Sheet Metal Forming According to Changes in Shape and Position of Drawbeads Based on a Digital Twin by Sarang Yi, Daeil Hyun, Seokmoo Hong

“…A digital twin was developed to predict the sheet metal forming process using Support Vector Machine, Random Forest, Gradient Boosting Machine, and Artificial Neural Networks. The machine learning models were trained using finite element analysis data corresponding to the position and bead force of drawbeads, enabling the real-time prediction of wrinkles and crack occurrences. …”
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Initial Stand Volume and Residual Live Trees Drive Deadwood Carbon Stocks in Fire and Harvest Disturbed Boreal Forests at North‐Central Alberta by Richard Osei, Charles A. Nock

“…Conversely, the size heterogeneity of remnant live trees significantly boosted deadwood C stocks in fire islands but not in harvest islands. …”
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Glucose Fluctuation Inhibits Nrf2 Signaling Pathway in Hippocampal Tissues and Exacerbates Cognitive Impairment in Streptozotocin-Induced Diabetic Rats by Haiyan Chi, Yujing Sun, Peng Lin, Junyu Zhou, Jinbiao Zhang, Yachao Yang, Yun Qiao, Deshan Liu

“…Regarding the expressions in murine hippocampal tissues, GF depressed Nrf2, HO-1, NQO-1, Bcl-2, and BDNF but boosted Caspase-3 and Bax. Conclusions. GF aggravates cognitive impairment by inhibiting the Nrf2 signaling pathway and inducing oxidative stress and apoptosis in the hippocampal tissues.…”
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LAND SUITABILITY ASSESSMENT FOR SOYBEAN (GLYCINE MAX) IN BARDAGHAT MUNICIPALITY USING GIS TECHNIQUES by Birendra Tiwar, Amrit Dumre, Mahesh Jaishi

“…The central aim of this research is to assess land suitability for soybean cultivation within the study area, with the overarching objective of boosting crop productivity and refining land use planning strategies. …”
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Spectral enhancement of PlanetScope using Sentinel-2 images to estimate soybean yield and seed composition by Supria Sarkar, Vasit Sagan, Sourav Bhadra, Felix B. Fritschi

“…Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. …”
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A Systematic Review of Opportunities and Limitations of Innovative Practices in Sustainable Agriculture by Anita Boros, Eszter Szólik, Goshu Desalegn, Dávid Tőzsér

“…To eliminate these barriers, consistent policy regulations are required, targeting specific agricultural problems, alongside a complex, education-based support system, further boosting initiatives related to the green transition in agriculture.…”
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The Short-Term Wind Power Forecasting by Utilizing Machine Learning and Hybrid Deep Learning Frameworks by Sunku V.S., Namboodiri V., Mukkamala R.

“…In pursuit of these objectives, the CNN GRU model was rigorously tested and compared against three additional models: CNN with bidirectional long short-term memory (BiLSTM), extreme gradient boosting (XGBoost), and random forest (RF). Key performance metrics—namely, mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and the coefficient of determination (R²)—were employed to assess the efficacy of each model. …”
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A Study of the Different Strains of the Genus <i>Azospirillum</i> spp. on Increasing Productivity and Stress Resilience in Plants by Wenli Sun, Mohamad Hesam Shahrajabian, Na Wang

“…The most important modes of action of bacterial plant biostimulants on different plants are increasing disease resistance; activation of genes; production of chelating agents and organic acids; boosting quality through metabolome modulation; affecting the biosynthesis of phytochemicals; coordinating the activity of antioxidants and antioxidant enzymes; synthesis and accumulation of anthocyanins, vitamin C, and polyphenols; enhancing abiotic stress through cytokinin and abscisic acid (ABA) production; upregulation of stress-related genes; and the production of exopolysaccharides, secondary metabolites, and ACC deaminase. …”
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Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania by Ngong'Ho Bujiku Sende, Snehanshu Saha, Leon Ruganzu, Saibal Kar

“…A variety of supervised machine-learning algorithms such as RBF Kernel in SVM, Linear Kernel in SVM, Polynomial Kernel in SVM, Random Forest, Logistic regression classifier, Decision tree, Gradient Boosting, K-Nearest Neighbours Classifier, Na&#x00EF;ve Bayes Classifier, Artificial Neuron Network and Ensemble Learning Model were implemented to predict multidimensional poverty status for each dataset. …”
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Exploring the Mediation Effect of Brand Trust on the Link Between Tourism Destination Image, Social Influence and Brand Loyalty by Abu Elnasr E. Sobaih, Hassane Gharbi, Riadh Brini, Nadir Aliane

“…The findings demonstrate the importance of the tourism destination as well as social influence in boosting tourism trust and increasing destination loyalty among tourists. …”
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Estimation of the Visibility in Seoul, South Korea, Based on Particulate Matter and Weather Data, Using Machine-learning Algorithm by Bu-Yo Kim, Joo Wan Cha, Ki-Ho Chang, Chulkyu Lee

“…Through learning and validation of each ML algorithm, the extreme gradient boosting (XGB) algorithm was found to be most suitable for visibility estimations (bias = 0 km, root mean square error (RMSE) = 0.08 km, and r = 1 for training data set). …”
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A BIBLIOMETRIC ANALYSIS OF ENGINEERING EDUCATION IN THE METAVERSE by Veselina Nedeva, Snejana Dineva, Svetoslav Atanasov

“…This paper aim to enhance our understanding of how digital and immersive technologies are reshaping educational practices and boosting student engagement, motivation, and outcomes. …”
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A Data Mining Approach Identified Salivary Biomarkers That Discriminate between Two Obesity Measures by Ping Shi, J. Max Goodson

“…For a random cohort of over 700 subjects from 8137 Kuwait children (10.00 ± 0.67 years), four data mining methods were applied to identify important variables associated with obesity, including logistic regression by lasso regularization (Lasso), multivariate adaptive regression spline (MARS), random forests (RF), and boosting classification trees (BT). Each algorithm generated a variable importance rank list, based on an internal cross-validation procedure. …”
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