On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis by Banamali Panigrahi, Saman Razavi, Lorne E. Doig, Blanchard Cordell, Hoshin V. Gupta, Karsten Liber

“…Unlike many methods for explainable artificial intelligence (XAI), this method (a) accounts for complex multi‐variate distributional properties of data, common in environmental systems, (b) offers a global assessment of the input‐output response surface formed by ML, rather than focusing solely on local regions around existing data points, and (c) is scalable and data‐size independent, ensuring computational efficiency with large data sets. We apply this method to a suite of ML models predicting various water quality variables in a pilot‐scale experimental pit lake. …”
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Cross-Sectional Evaluation of Hydroxyapatite-Coated Titanium Implants: Insights into Biocompatibility and Osseointegration by Tayyaba Rafiq, Iqra Amin, Atiq Ur Rehman, Amna Mehwish Ikram, Khurram Anwar, Arsalan Ahmed, Ayesha Ali Khawaja

“…Professionals used both patient evaluations and imaging data to evaluate the efficiency of osseointegration. The analysis of data occurred through SPSS version 20 using one way ANOVA with p-value<0.05, statistically significant. …”
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Observational partitioning of water and CO₂ fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial... by E. Zahn, E. Bou-Zeid

“…<p>Long-term time series of transpiration, evaporation, plant net photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. …”
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Artificial intelligence Defect Detection Robustness inReal-time Non-Destructive Testing of Metal Surfaces by Chaoyu Dong, Jovian Sanjaya Putra, Andrew A. Malcolm

“… Artificial intelligence (AI) is revolutionizing defect detection by employing advanced computational techniques to enhance accuracy and efficiency. Through machine learning methods and deep neural networks, it is possible for AI systems to learn from diverse datasets and accurately identify defects across various applications. …”
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Genome-wide association study of blood vitamin D metabolites and bone remodelling markers in pigs by Dipanwita Paul, Michael Oster, Siriluck Ponsuksili, Klaus Wimmers, Henry Reyer

“…Hence, mineral utilization efficiency might be indirectly improved which remains to be empirically demonstrated through further research.…”
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Minimally Invasive Surgery in Modern Medicine: A Review of Laparoscopic Techniques, Indications, and Postoperative Outcomes by Maksymilian Czarnota, Martyna Adamowicz, Aleksandra Górniak

“…Enhanced visualisation, single-incision access and staple-line optimisation improved technical efficiency, while restrictive fluid and ERAS pathways halved pulmonary complications and hastened recovery. …”
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Unveiling the corporate governance dynamics: exploring the nexus of board composition, audit committee attributes, foreign ownership, and firm performance in an emerging market by Mohd Arsh, Mohd Shamim Ansari, Gayas Ahmad, Marghoob Enam, Mosab I. Tabash, Mujeeb Saif Mohsen Al-Absy

“…This study investigates the collective impact of key corporate governance variables namely board composition, audit committee characteristics, and foreign ownership on firm performance in an emerging economy, India. …”
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Age-Related Differences in Bimanual Isometric Force Tracking by Elisa Galofaro, Nicola Vale, Giulia Ballardini, Nicola Smania, Maura Casadio

“…Notably, the percentage of total force exerted by the left hand was negatively correlated with the disparity between the left and right coefficients of variation. This study confirms previous findings on the effect of aging on bimanual force control and provides evidence suggesting that the contribution of each hand may depend on the variability in force exertion.…”
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Drying kinetics and thermodynamic analysis; enhancing quinoa (Chenopodium quinoa Willd.) quality profile via pre-treatments assisted germination and processing by Jabir Khan, Palwasha Gul, Qingyun Li, Kunlun Liu

“…Principal Component Analysis revealed significant correlations between analyses, explaining 80.37 % variability. The intensity of functional groups decreased in the infrared spectra, although the transmission of signals was greater in pretreated samples than in control. …”
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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…Future capsules will feature AI-driven lesion detection and therapeutic functions, higher-resolution imaging, wider fields of view, controllable movement bringing the concept of "swallowing the gastroenterologist" closer to reality. …”
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A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Türkiye by Ulubey Çeken, Fadime Sertçelik, Abdullah İçen

“…Additionally, a heteroscedastic model was created for aleatory variability as a function of <i>M_W</i>. The closest distance to the surface projection of the fault plane (<i>R_JB</i>) is between 0 and 350 km. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…To efficiently analyze and optimize the structural performance of rudder structures, a parametric optimization model for the radial configuration of reinforcement ribs is constructed. …”
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images by Ruifen Cao, Qingbin Meng, Dayu Tan, Pijing Wei, Yun Ding, Chunhou Zheng

“…Moreover, the coarse predictions and refined predictions are combined by using a loss function that employs cross-entropy loss and generalized dice loss to efficiently tackle the challenge of class imbalance among nuclei in histology images. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Development and validation of a novel prediction model for osteoporosis: from serotonin to fat-soluble vitamins by Jinpeng Wang, Lianfeng Shan, Jing Hang, Hongyang Li, Yan Meng, Wenhai Cao, Chunjian Gu, Jinna Dai, Lin Tao

“…Stepwise discriminant analysis was performed to identify efficient predictors for osteoporosis. The prediction model was developed based on Bayes and Fisher’s discriminant functions, and validated via leave-one-out cross-validation. …”
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Speciation and mobilization of ultra-trace Hg(II) in groundwater by Kunfu PI, Yanxin WANG, Juewen LIU, Ya’nan YANG, Van Cappellen PHILIPPE

“…Applying tests to hydrogeochemically diverse groundwaters from the Grand River Watershed, Canada, the results indicate that the DNA-functionalized hydrogel is able to quickly detect dissolved Hg(II) but inapplicable to low Hg(II) concentrations (<1.60 μg/L), whereas the DNA-DGT sensor can capture variably ultra-trace Hg(II) species depending on the deployment time. …”
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Assessment of heavy metal exposure risk to aquatic birds in the key wetland habitats of the Yellow River (China), using an integrated model by Jian Ding, Ni Wang, Yaqiao Lian, Qian Li, Xinran Li, Fei Yu

“…Heavy metal pollution poses a growing threat to wetland ecosystems, impacting their structure and function. Chenqiao Wetland and Qinglong Lake (Henan, China), key bird habitats in the middle and lower reaches of the Yellow River, were analyzed for heavy metal contamination. …”
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Influence of Migratory Strategy, Group Size, and Environmental Conditions on the Movements of Caribou in Eastern Alaska by Kyle Joly

“…The ability of caribou (<i>Rangifer tarandus granti</i>) to efficiently move long distances and have a high degree of plasticity in their movements allows them to respond and be resilient to dynamic and dramatic differences in environmental conditions. …”
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A Fusion Strategy for High-Accuracy Multilayer Soil Moisture Downscaling and Mapping by Xu Zhang, Xin Liu, Xiang Zhang, Aminjon Gulakhmadov, Jiefeng Wu, Xihui Gu, Won-Ho Nam, Panda Rabindra Kumar, Veber Afonso Figueiredo Costa, Mahlatse Kganyago, Berhanu Keno Terfa, Wenying Du, Chao Wang, Peng Wang, Jing Yuan, Nengcheng Chen

“…Soil moisture (SM) is a critical factor influencing plant growth, agricultural yield, ecosystem functions, and water resource management. Existing SM products, such as SMAP, ERA5, and ESA-CCI, provide daily SM data. …”
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Fabrication of Wood-Derived Carbon Aerogel/Mg(OH)₂ Bio-Composite and Its High Performance for Adsorption and Separation of Cadmium Ions by Ran An, Jinyue Liu, Haomiao Ma, Yuqing Yan, Yuanru Guo, Qingjiang Pan, Shujun Li

“…The resulting wood-derived carbon aerogels (WCA) were functionalized with Mg(OH)₂ to boost their environmental remediation potential. …”
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