Evaluation of iLead, a generic implementation leadership intervention: mixed-method preintervention–postintervention design by Anne Richter, Caroline Lornudd, Ulrica von Thiele Schwarz, Robert Lundmark, Rebecca Mosson, Ulrika Eskner Skoger, Tatja Hirvikoski, Henna Hasson

“…The contextualisation did not have a boosting effect on behaviour change. Hence, group 2 did not increase its active implementation leadership in comparison with group 1.Conclusions iLead introduces a new approach to how implementation leadership can be trained when knowledge of effective leadership for implementations is combined with findings on the importance of environmental factors for the transfer of training. …”
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Enhancing sustainable silk Textiles: Optimization of teak leaf extract dyeing and antibacterial efficacy by Nattadon Rungruangkitkrai, Rattanaphol Mongkholrattanasit, Peeraya Ounu, Nawarat Chartvivatpornchai, Jirachaya Boonyarit, Kamlai Laohaphatanaleart, Rungsima Chollakup

“…Nonetheless, future research should focus on optimizing extraction methods, boosting antimicrobial efficacy, and scaling the process for industrial applications.…”
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Extraction of Rubidium and Cesium Ions by Adsorption–Flotation Separation in Titanosilicate-Hexadecyltrimethylammonium Bromide System by Dezhen Fang, Haining Liu, Xiushen Ye, Yanping Wang, Wenjie Han

“…It holds significant theoretical and practical reference value for enhancing the separation processes of low-grade valuable components and boosting overall separation performance.…”
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Flood Index-Enhanced deep learning model for coastal inundation mapping in SAR imagery by Wantai Chen, Yinfei Zhou, Xiaofeng Li

“…After semi-automatic labeling and cropping, 4350 sample pairs were processed, with 2784/696/870 used for model training/validation/testing. …”
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Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

“…This study aims to predict the spatial distribution of nematode associations from 25 m to 2500 m water depth over an area of 350,000 km² and understand the major oceanographic processes influencing them. The study considered data from 245 nematode genera and 44 environmental parameters from 100 stations. …”
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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics by Jinghong Pei BD, Jing Yu BD, Ping Ge BD, Liman Bao BD, Haowen Pang MS, Huaiwen Zhang MS

“…Through stringent feature selection process, we identified 18 pivotal radiomic features for classification of cervical cancer and normal uterine tissue. …”
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Association of salivary Interleukin-6 levels in smokers with periodontitis by Alhussein M Ali, Ayser N Mohammed, Haider A Al-Waeli, Hadeer A Al-Ani

“…This shows that smoking cigarettes had a boosting effect on the levels of IL-6 in the saliva. …”
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An Improved Unmanned Aerial Vehicle Forest Fire Detection Model Based on YOLOv8 by Bensheng Yun, Xiaohan Xu, Jie Zeng, Zhenyu Lin, Jing He, Qiaoling Dai

“…Firstly, we incorporate SPDConv modules, enhancing the YOLOv8 architecture and boosting its efficacy in dealing with minor objects and images with low resolution. …”
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Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

“…This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.…”
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Moderating effect of gender and marital status in the association between religiosity and happiness among Bangladeshi university students by Md. Abdul Hannan Mondal, Md. Burhan Uddin Zubair, Pramath Chandra Sarker, Md. Nur-E-Alam Siddique, Md. Golam Hossain

“…Background: Boosting university students' happiness is essential for personal development, familial harmony, social equilibrium, and national progress. …”
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Innovative Approach Integrating Machine Learning Models for Coiled Tubing Fatigue Modeling by Khalil Moulay Brahim, Ahmed Hadjadj, Aissa Abidi Saad, Elfakeur Abidi Saad, Hichem Horra

“…The results from our machine learning analysis demonstrated that CatBoost and XGBoost are the most suitable models for fatigue life prediction. …”
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Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review by Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan

“…Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. …”
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Elucidating long non-coding RNA networks in tomato plants in response to Funneliformis mosseae colonization and cucumber mosaic virus infection by Narjes Maleki, Abozar Ghorbani, Mahsa Rostami, Solomon Maina

“…While this symbiosis boosts nutrient uptake and stress tolerance, viral infections can reduce yield and quality. …”
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Prognostic model for log odds of negative lymph node in locally advanced rectal cancer via interpretable machine learning by Ye Wang, Zhen Pan, Huajun Cai, Shoufeng Li, Ying Huang, Jinfu Zhuang, Xing Liu, Guoxian Guan

“…The extreme gradient boosting (XGB) model showed the best performance, with a mean AUC of 0.89 for OS and 0.83 for DFS in 10-fold cross-validation. …”
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Improving the accuracy of remotely sensed TSS and turbidity using quality enhanced water reflectance by a statistical resampling technique by Kunwar Abhishek Singh, Dongryeol Ryu, Meenakshi Arora, Manoj Kumar Tiwari, Bhabagrahi Sahoo

“…Our approach improved the estimation accuracy of the TSS by 33% and turbidity by 28% compared to the input processed using the built-in Sentinel-2 cloud and cloud shadow masks. …”
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Maize and soybean yield prediction using machine learning methods: a systematic literature review by Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon

“…The Random Forest (RF), Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), and Extreme Gradient Boosting (XG-Boost) were identified as the mostly used ML algorithms. …”
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Strategies for Soil Salinity Mapping Using Remote Sensing and Machine Learning in the Yellow River Delta by Junyong Zhang, Xianghe Ge, Xuehui Hou, Lijing Han, Zhuoran Zhang, Wenjie Feng, Zihan Zhou, Xiubin Luo

“…We employed four machine learning models—Support Vector Regression (SVR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Geographical Gaussian Process Regression (GGPR) for modeling, prediction, and accuracy comparison, with the objective of achieving high-precision salinity mapping under complex vegetation cover conditions. …”
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Machine Learning-Based Prediction of Ecosystem-Scale CO₂ Flux Measurements by Jeffrey Uyekawa, John Leland, Darby Bergl, Yujie Liu, Andrew D. Richardson, Benjamin Lucas

“…We found that Extreme Gradient Boosting (XGBoost) consistently produced the most accurate predictions (Root Mean Squared Error of 1.81 μmolm⁻²s⁻¹, R² of 0.86). …”
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Multivariate genome-wide association analysis of dyslexia and quantitative reading skill improves gene discovery by Hayley S. Mountford, Else Eising, Pierre Fontanillas, Adam Auton, 23andMe Research Team, Evan K. Irving-Pease, Catherine Doust, Timothy C. Bates, Nicholas G. Martin, Simon E. Fisher, Michelle Luciano

“…Gene-set analyses revealed significant enrichment of dyslexia-associated genes in four neuronal biological process pathways, and findings were further supported by enrichment of neuronally expressed genes in the developing embryonic brain. …”
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The Effect of Intravenous Glutamine Administration in Lowering AIF Expression in Renal Tubular Cells by Raihan Akbar Muhammad, Imam Susilo, Eko Budi Koendhori, Bambang Purwanto

“…Highlights • Glutamine, an amino acid, can help mitigate the side effects of cisplatin by boosting glutathione (GSH) levels, an antioxidant that counteracts oxidative stress…”
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