Field Observations during the Eleventh Microwave Water and Energy Balance Experiment (MicroWEX-11): from April 25, 2012, through December 6, 2012 by Tara Bongiovanni, Pang-Wei Liu, Karthik Nagarajan, Daniel Preston, Patrick Rush, Tim H.M. van Emmerik, Robert Terwilleger, Alejandro Monsivais-Huertero, Jasmeet Judge, Susan Steele-Dunne, Roger De Roo, Ruzbeh Akbar, Ella Baar, Max Wallace, Anthony England

“… This new report from UF/IFAS researchers provides another set of observation data that can be used to develop better models for accurate prediction of weather and near-term climate. It describes the observations conducted during the MicroWEX-11, a season-long experiment incorporating active and passive microwave observations for bare soil, elephant grass, and sweet corn using a variety of sensors to understand land–atmosphere interactions and their effect on observed microwave signatures. …”
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Physical experimental simulation of unconventional reservoir formation process for carboniferous in Hudson Oilfield, Tarim Basin by Rujun Wang, Yongliang Tang, Wei Zhou, Daiyu Zhou, Zangyuan Wu, Guangqiang Shao

“…And the application of advanced simulations, enhancing unconventional reservoir prediction accuracy by 25% compared to standard geological techniques. …”
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Detection of Corn Quality Based on Surface-Enhanced Raman Spectroscopy and Electronic Nose Technology by HuiHe Yang, XiaoYan Wei, Guifang Wu, PengCheng Qiu, JiaNing Di, XiangPeng Zhao, WenDong Zhong, He Ren

“…The results showed that the model’s coefficient of determination of the test set for predicting AFB1 reached 0.70, and the model’s coefficient of determination of the test set for predicting OTA reached 0.74. …”
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CRIP1 inhibits cutaneous melanoma progression through TFAM-mediated mitochondrial biogenesis by Jianqiang Wu, Lixia Chen, Peijun Wen

“…However, the biological function and underlying mechanisms of CRIP1 in melanoma progression are largely unknown. Bioinformatic prediction of CRIP1 expression in melanoma and its association with clinical parameters and prognosis of patients. …”
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Thermodynamic, diffusion and precipitation behaviors in Cu–Ni–Si–Co alloys: Modeling and experimental validation by Haoyue Ling, Ying Tang, Jing Zhong, Xiangpeng Meng, Min Zhang, Lijun Zhang

“…Aging precipitation is an important process that affects the mechanical and electrical properties of Cu alloys. Quantitative prediction of microstructure evolution during aging process is crucial for controlling their performance. …”
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Artificial Intelligence (AI) in the Banking Industry: A Review of Service Areas and Customer Service Journeys in Emerging Economies by Tajudeen Alaburo Abdulsalam, Rofiat Bolanle Tajudeen

“…The research highlights AI's growing use in process automation, customer experience, stock market trend prediction, credit risk management, online banking, marketing management, and auditing. …”
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Identification of the immune infiltration and biomarkers in ulcerative colitis based on liquid–liquid phase separation-related genes by Zhixing Hong, Shilin Fang, Haihang Nie, Jingkai Zhou, Yuntian Hong, Lan Liu, Qiu Zhao

“…Hub genes were screened that displayed high prediction accuracy of UC patients. Both the microarray and scRNA-seq datasets showed a strong correlation with immune cell infiltration and cytokines, especially GBP1, TRIM22, SRI. …”
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Biodiversity characteristics of large forest plots in Qinghai area of Qilian Mountain National Park by WANG Dinghui, SUONAN Cairang, YU Hongyan, DU Yangong

“…This indicated that the model had a high explanatory power and prediction accuracy for the Shannon-Wiener data. [Conclusion] The species diversity of the Qinghai spruce forest is relatively low and is significantly influenced by tree height, species richness, and the Simpson index. …”
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Numerical optimization by the PFEMCT-SIF method of the crack propagation of a linear elastic material by Mohammed Bentahar, Noureddine Mahmoudi, Youcef Moulai Arbi

“…Conclusions: The PFEMCT-SIF method effectively evaluates SIFs and predicts crack propagation paths. A 10-contour crack tip model balances accuracy and computational efficiency. …”
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Predictors of infliximab efficacy in patients with severe attack of ulcerative colitis by A. O. Golovenko, I. L. Khalif, O. V. Golovenko, V. V. Veselov

“…The investigated risk factors do not allow clear-cut prediction of relapse-free course of ulcerative colitis for one year of maintenance therapy by infliximab.…”
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A robust, deep learning-based analysis of time-domain signals for NMR spectroscopy by Kyungdoe Han, Eunhee Kim, Kyoung-Seok Ryu, Donghan Lee

“…As a proof of concept, we present the resulting spectra, along with peak lists predicted by supplying only FID input to the deep learning algorithm. …”
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Smart Filter Performance Monitoring System by Chenxing Pei, Weiqi Chen, Qisheng Ou, David Y. H. Pui

“…Moreover, filter monitoring data can establish a database for researchers to validate the filter models or train a machine learning model for filter performance prediction. Filter or air-cleaning device manufacturers can improve their products or recommend suitable products to their customers based on big data contributed by this filter monitoring system.…”
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Rehabilitation Following ACL Repair with Internal Brace Ligament Augmentation in Female Gymnast: A Resident’s Case Report by Colten Haack, Giorgio Zeppieri, Micheal W Moser

“…Patient reported outcomes including the International Knee Documentation Committee (IKDC), the Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) and the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) were assessed in conjunction with isokinetic strength and hop performance testing to determine return to sport readiness…”
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Comprehensive design of a 100-kilowatt solar power plant with bifacial technology in PVsyst for Arak, Iran by Mohammad Parhamfar, Alireza Zabihi

“…Furthermore, this paper explores incorporating climatic and environmental impacts into PVsyst software for accurate power plant performance prediction, providing a practical example for designing a 100-kilowatt plant.…”
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Antioxidants and Cognitive-Behavioral Therapy in Patients with Functional Dyspepsia by T. V. Sapozhnikova, S. A. Parfenov, T. E. Yesina, K. V. Sapozhnikov, A. N. Smirnov, A. A. Paulov, D. M. Rizakhanov, O. A. Rizakhanova

“…After comparing it with a threshold, the probability of a positive response to a combination of antioxidant and cognitive-behavioral therapy is estimated. The developed prediction algorithm is valid (sensitivity — 91 %, specificity — 73 %, accuracy — 84.8 %) and allows to optimize the definition of treatment tactics for a patient with functional dyspepsia.…”
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Mini meta-analysis of anticholinesterase actions of atorvastatin, simvastatin and rosuvastatin, and in silico identification of their protein targets in Mus musculus by Fouad Kasim Mohammad, Rawnaq Faris Al-Shalchi

“…The study aims at conducting a mini meta-analysis on in vivo and in vitro adverse anti-ChE effects of atorvastatin, simvastatin and rosuvastatin in mice, and using the SwissPrediction to identify in silico body target proteins. …”
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Immediate and short-term effects of neurodynamic techniques on hamstring flexibility: A systematic review with meta-analysis. by Sergio Núñez de Arenas-Arroyo, Vicente Martínez-Vizcaíno, Ana Torres-Costoso, Sara Reina-Gutiérrez, Bruno Bizzozero-Peroni, Iván Cavero-Redondo

“…Furthermore, to reflect the variation in genuine therapy effects in different scenarios, including future patients, we calculated a 95% prediction interval(prI).<h4>Results</h4>Thirteen trials were included, involving 624 participants. …”
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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

“…The CNN-LSTM model achieved superior performance with accuracies of 99.17% and 99.90% on the respective datasets. This paper uses prediction evaluation metrics such as accuracy, sensitivity, specificity, F-score, and the AUC curve. …”
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Response of the Magnetospheric Convection Electric Field (MCEF) to Geomagnetic Storms During the Solar Cycle 24 Maximum Phase by Bazié Nongobsom, Kaboré Salfo, Guibula Karim, Ouattara Frédéric

“…These results provide us with some information on the complete evolution of geomagnetic storms, with a view to better prediction.…”
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From data to diagnosis: leveraging deep learning in IoT-based healthcare by Miracle A. Atianashie, Chukwuma Chinaza Adaobi

“…This article explores the advanced architectures of deep learning and their application in healthcare IoT, emphasizing the enhancement of disease prediction models, medical image analysis, and real-time health monitoring systems. …”
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