Performance of Various Artificial Intelligence Models for Predicting Temperature in an Industrial Building—A Case Study by Johan Roussel, Zoubeir Lafhaj, Pascal Yim, Thomas Danel, Laure Ducoulombier

“…The article also highlights the practical implications of these findings for Industry 4.0. By integrating high-performing predictive models into equipment control systems, it is possible to reduce energy costs, improve thermal comfort, and ensure efficient process stability. …”
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Engineering Safety-Oriented Blasting-Induced Seismic Wave Signal Processing: An EMD Endpoint Suppression Method Based on Multi-Scale Feature by Miao Sun, Jing Wu, Yani Lu, Fangda Yu, Hang Zhou

“…Three evaluation metrics were utilized: error standard deviation, correlation coefficient, and computation time. …”
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Analysis of Ionospheric Disturbances in China During the December 2023 Geomagnetic Storm Using Multi-Instrument Data by Jun Tang, Sheng Wang, Jintao Wang, Mingxian Hu, Chaoqian Xu

“…The results provide scientific implications for improving GNSS positioning stability in mid- and low-latitude regions.…”
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The Effects Of Differing Density Of Swim-Training Sessions On Shoulder Range Of Motion and Isometric Force Production In National and University Level Swimmers by Matias Yoma, Lee Herrington, Tanya Mackenzie

“…The results were evaluated by the level of significance (p-value), effect size, and whether changes exceeded the measurement error. # Results University-level swimmers had lower baseline ER torque (p= 0.006; d= 2.55) and IR torque (p= 0.011; d= 2.42) than national-level swimmers. …”
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The neural signature of high myopia: structural and functional brain alterations and their cognitive-emotional associations by Xuan Li, Kuan Zhao, Kuan Zhao, Kuan Zhao, Boling Deng, Boling Deng, Boling Deng, Zhengzheng Wu, Zhengzheng Wu, Zhengzheng Wu, Ling Wei, Ling Wei, Ling Wei

“…Beyond refractive error, myopia is increasingly recognized as a systemic condition with neurological implications, associated with visual dysfunction and structural retinal–choroidal alterations. …”
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Practical and Accurate Evaluation of Numerical Aperture and Beam Quality Factor in Photonic Crystal Fibers by Mechanical Learning by Mengda Wei, Meisong Liao, Liang Chen, Yinpeng Liu, Wen Hu, Lidong Wang, Dongyu He, Tianxing Wang, Shizi Yu, Weiqing Gao

“…Moreover, when the noise factor remains below 0.32, the model's prediction error shows minimal fluctuation, highlighting its robustness. …”
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Integrating RS data with fuzzy decision systems for innovative crop water needs assessment by Faezeh Sadat Hashemi, Mohammad Javad Valadan Zoej, Fahimeh Youssefi, Huxiong Li, Sanaz Shafian, Mahdi Farnaghi, Saied Pirasteh

“…This approach has significant implications for improving irrigation management practices, reducing water waste, and increasing crop yields, which can contribute to global food security. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Additionally, the integration of SHAP analysis for feature importance ranking provides an interpretable machine learning approach to concrete mix design, which enhances decision-making for engineers and researchers. The practical implications of this research extend to sustainable machine learning-based concrete design, where AI-driven optimization can help reduce the reliance on conventional trial-and-error methods. …”
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Unleashing the potential of geostationary satellite observations in air quality forecasting through artificial intelligence techniques by C. Zhang, X. Niu, H. Wu, Z. Ding, K. L. Chan, J. Kim, T. Wagner, C. Liu, C. Liu, C. Liu

“…Our findings demonstrate the significant potential of geostationary satellite observations in artificial-intelligence-based air quality forecasting, with implications for early warning of air pollution events and human health exposure.…”
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Bezlotoxumab prevents extraintestinal organ damage induced by Clostridioides difficile infection by Steven J. Mileto, Melanie L. Hutton, Sarah L. Walton, Antariksh Das, Lisa J. Ioannidis, Don Ketagoda, Kylie M. Quinn, Kate M. Denton, Diana S. Hansen, Dena Lyras

“…As the thymus has such a crucial role in T cell production and immune system development, these findings may have important implications in relapse of C. difficile disease and impaired immunity during C. difficile infection. …”
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Chronotherapeutic intervention targeting emotion regulation brain circuitry, symptoms, and suicide risk in adolescents and young adults with bipolar disorder: a pilot randomised tr... by Jihoon A Kim, Anjali Sankar, Rebecca Marks, Erin Carrubba, Bernadette Lecza, Susan Quatrano, Linda Spencer, R. Todd Constable, Brian Pittman, Eli R Lebowitz, Wendy K Silverman, Holly A Swartz, Hilary P Blumberg

“…No intervention-related adverse events were observed.Conclusions Regularising DRs may enhance emotion regulation brain circuitry functioning, emotion regulation, and reduce suicide risk in BDAYA.Clinical implications Chronotherapeutic interventions regularising DRs, such as SRT, should be studied further as potential treatment strategies for BDAYA.Trial registration number NCT03183388.…”
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Enhancing water balance simulations in SWAT for paddy-dominated catchments through refined soil moisture dynamics by Meng Xiang, Di Wu, Qianan Yu, Haitao Wu, Tianchi Cai, Yuanlai Cui

“…Agricultural water management, especially irrigation regimes such as Alternate Wetting and Drying (AWD) in rice cultivation, holds significant implications for regional water balances. However, the Soil and Water Assessment Tool (SWAT) model, widely used for agricultural water management, has notable limitations in accurately simulating AWD irrigation practices due to improper description of soil moisture dynamics. …”
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The gas discharge visualization (GDV) order parameter model based on the principle of mastering both permanence and change by Yu Xin, Lei Zhang, Qiancheng Zhao, Yurong She, Zhensu She, Shuna Song

“…Further, the health implications of GDV signals were explored by analyzing subclass symptom profiles. …”
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Artificial neural networks for predicting first-lactation 305-day milk yield in crossbred cattle by SM Usman, A Kumar, A Sherasiya, IM Youssef, MM Abo Ghanima, J Chandrakar, R Tiwari, NP Singh, QS Sahib, T Dutt, AA Swelum

“…The study compares ANN and multiple linear regression models, showing that ANNs provide superior predictive accuracy and lower error margins. This has important implications for local dairy farming systems, particularly in data-limited environments, as it offers a practical tool for early identification of high- and low-producing cows. …”
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Electroencephalography estimates brain age in infants with high precision: Leveraging advanced machine learning in healthcare by Saeideh Davoudi, Gabriela Lopez Arango, Florence Deguire, Inga Sophie Knoth, Fanny Thebault-Dagher, Rebecca Reh, Laurel Trainor, Janet Werker, Sarah Lippé

“…The EEG-based BAG score offers a reliable non-invasive measure of brain maturation, with significant advantages and implications for developmental neuroscience and clinical practice.…”
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Prediction of PD-L1 tumor positive score in lung squamous cell carcinoma with H&E staining images and deep learning by Qiushi Wang, Xixiang Deng, Pan Huang, Qiang Ma, Lianhua Zhao, Yangyang Feng, Yiying Wang, Yuan Zhao, Yan Chen, Peng Zhong, Peng He, Mingrui Ma, Peng Feng, Hualiang Xiao

“…Therefore, the application of deep learning models to segment and quantitatively predict PD-L1 expression in digital sections of Hematoxylin and eosin (H&E) stained lung squamous cell carcinoma is of great significance.MethodsWe constructed a dataset comprising H&E-stained digital sections of lung squamous cell carcinoma and used a Transformer Unet (TransUnet) deep learning network with an encoder-decoder design to segment PD-L1 negative and positive regions and quantitatively predict the tumor cell positive score (TPS).ResultsThe results showed that the dice similarity coefficient (DSC) and intersection overunion (IoU) of deep learning for PD-L1 expression segmentation of H&E-stained digital slides of lung squamous cell carcinoma were 80 and 72%, respectively, which were better than the other seven cutting-edge segmentation models. The root mean square error (RMSE) of quantitative prediction TPS was 26.8, and the intra-group correlation coefficients with the gold standard was 0.92 (95% CI: 0.90–0.93), which was better than the consistency between the results of five pathologists and the gold standard.ConclusionThe deep learning model is capable of segmenting and quantitatively predicting PD-L1 expression in H&E-stained digital sections of lung squamous cell carcinoma, which has significant implications for the application and guidance of immune checkpoint inhibitor treatments. …”
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Perfil inflamatorio del humor acuoso tras tratamiento asistido por láser de femtosegundo en casos de catarata nuclear by Claudia Palacio-Pastrana, Andric C. Perez-Ortiz, Bani Antonio-Aguirre, Cristina Mendoza-Velásquez, Azyadeh Camacho-Ordóñez, Manuel Ceballos-Reyes, Atzin Robles-Contreras, Virgilio Lima-Gómez

“…Conclusion: FL-exposed cases have a significant increase in IL-6 and PgE2 during the first steps of the surgical approach. The clinical implications of these elevations on visual outcomes warrant future study. …”
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Mental fatigue of operating room nurses and its relationship with missed perioperative nursing care: a descriptive-analytical study by Vahid Rahmani, Valerie L. Marsh, Ebrahim Aliafsari Mamaghani, Ali Soleimani, Maedeh Alizadeh, Omid Zadi, Nasrin Aghazadeh

“…Abstract Introduction Mental fatigue is a psychological condition characterised by diminished alertness, impaired cognitive functioning, heightened error rates, and overall decreased performance. missed perioperative nursing care diminishes patient safety and increases the likelihood of adverse incidents. …”
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Assessment of predictors and mitigation strategy for therapeutic inertia in the management of hypertension: a quality improvement project by Ananyan Sampath, Shreya Deshpande, Rashmi Verma, Rajnish Joshi

“…When patient adherence was disregarded, TI increased to 49.7%. The total error rate in BP management ranged from 53.29% to 61.5%. …”
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Visual screening in orthogeriatric rehabilitation setting: a single centre pilot study by Chi Kit Yan, Siraj Farid, Jay Chillala, Robert Harper

“…Introduction: Visual impairment is a prevalent issue among the older population, with studies suggesting approximately one in five individuals over the age of 75 experience some form of visual loss in the UK.1 As the population ages, this figure is expected to rise, with significant implications for health, independence and quality of life. …”
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