Combined Input Deep Learning Pipeline for Embryo Selection for In Vitro Fertilization Using Light Microscopic Images and Additional Features by Krittapat Onthuam, Norrawee Charnpinyo, Kornrapee Suthicharoenpanich, Supphaset Engphaiboon, Punnarai Siricharoen, Ronnapee Chaichaowarat, Chanakarn Suebthawinkul

“…For viability prediction, convolution-based transferred learning models were employed, multiple pretrained models were compared, and image preprocessing techniques and hyperparameter optimization via Optuna were utilized. …”
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Visual Simulation and Case Inversion of Gas Explosion in Underground Mine by Qiu Jinwei, Jiang Bingyou, Tang Mingyun, Zhou Liang, Ren Bo, Yang Yingdi

“…The research achievements in the paper not only embody the great engineering value of visual simulation technology in the field of safety engineering but also provide references for accident impact prediction, assessment, and emergency plan.…”
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The Temporal Pattern of Arterial Stiffness during Aging: A Large-Scale Cross-Sectional Study by Zhengli Tang, Yuanyuan Lu, Yiming Hao, Robert Morris, Di Kang, Fang Wang, Lin Fan, Weijian Wang, Yiqin Wang, Feng Cheng

“…The results will improve existing prediction models for future cardiovascular episodes induced by arterial hardening in different age groups.…”
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Decoding HIV-associated neurocognitive disorders: a new perspective from multimodal connectomics by Zhongkai Zhou, Wei Wang, Hui Li, Ying Shi, Lingling Zhao, Yibo Lu, Xingchen Wei, Hongjun Li

“…These technologies offer potential biomarkers for the early diagnosis, prognosis, and treatment monitoring of HAND, while also providing new avenues for personalized prediction of cognitive status. Here, we start with the pathogenesis and risk factors of HAND, providing a comprehensive review of the basic concepts of unimodal and multimodal macro connectomics and related graph theory methods, and we review the latest progress in HAND connectomics research. …”
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Molecular Characterization of Legionellosis Drug Target Candidate Enzyme Phosphoglucosamine Mutase from (strain Paris): An Approach by Anayet Hasan, Habibul Hasan Mazumder, Arif Khan, Mohammad Uzzal Hossain, Homaun Kabir Chowdhury

“…The purpose of this study was to predict the potential target of that specific drug. …”
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Machine Learning Models for Spring Discharge Forecasting by Francesco Granata, Michele Saroli, Giovanni de Marinis, Rudy Gargano

“…Considering that most of the world’s unfrozen freshwater reserves are stored in aquifers, the capability of prediction of spring discharges is a crucial issue. …”
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Assessment of a Neural-Network-Based Optimization Tool: A Low Specific-Speed Impeller Application by Matteo Checcucci, Federica Sazzini, Michele Marconcini, Andrea Arnone, Mario Coneri, Luigi De Franco, Matteo Toselli

“…Due to both manufacturing and geometrical constraints, two different optimized impellers with 3 and 5 blades have been developed, with the performance required in terms of efficiency and suction capability. The predicted performance of both configurations were compared with the measured head and efficiency characteristics.…”
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Enhanced Chemical Insights into Fullerene Structures via Modified Polynomials by Ali N. A. Koam, Ali Ahmad, Raed Qahiti, Muhammad Azeem, Waleed Hamali

“…Our qualitative analysis shows that these descriptors significantly improve the prediction of molecular behavior. For instance, the Randić index provided insights into the stability and reactivity of fullerene structures, while the Zagreb indices helped us understand their potential in electronic applications. …”
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Drug Target Investigation of <i>N</i>-<i>p</i>-Coumaroyl-<i>N</i>’-Caffeoylputrescine, a Naturally-Occurring Alkaloid Derived from <i>Saxifraga tangutica</i> by Chuang Liu, Jun Dang, Minchen Wu

“…An in vitro study on liver (HepG2) cells and breast (MCF-7) cancer cells revealed that PCC modulates HSP90AA1, subsequently affecting Mut-p53 expression, triggering a cascade effect that reduced adriamycin-induced drug resistance in cells. Furthermore, a prediction of the absorption, distribution, metabolism, excretion, and toxicity was also applied to evaluate the drug-like properties of PCC. …”
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Pelvic Ultrasound Findings in Women with Obstetric Fistula: A Cross-Sectional Study of Cases and Controls by Jeffrey P. Wilkinson, Angela M. Bengtson, Ennet Chipungu, Rachel J. Pope, Bonus Makanani, Margaret Moyo, Mwawi Mwale, Jennifer H. Tang

“…Additional studies to clarify the role of ultrasound in OF patients and prediction of future fertility are warranted.…”
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Elucidating the process mechanism in Mg-to-Al friction stir lap welding enhanced by ultrasonic vibration by Ming Zhai, Lei Shi, ChuanSong Wu

“…An equation related to the temperature and strain rate was derived to calculate the grain size at different locations of the weld nugget zone, and the effect of grain size distribution on the threshold thermal stress was included, so that the prediction accuracy of flow stress was further improved. …”
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Crude Oil Source Identification of Asphalt via ATR-FTIR Approach Combined with Multivariate Statistical Analysis by Ruibo Ren, Wenmiao Fan, Pinhui Zhao, Hao Zhou, Weikun Meng, Ping Ji

“…The types of crude oil for producing asphalt have a decisive influence on various performance measures (including aging resistance and durability) of asphalt. To discriminate and predict the crude oil source of different asphalt samples, a discrimination model was established using 12 greatly different infrared (IR) characteristic absorption peaks (CAPs) as predictive variables. …”
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GC–MS analysis and in silico approaches to Stichopus hermanii as anti-inflammatory through PKC-β inhibition by Kurnia Fatwati, Asmawati Amin, Lenni Indriani, Rusdina Bte Ladju, Fuad Husain Akbar, Nurlindah Hamrun

“…The pharmacokinetic properties were predicted via pkCSM (http://biosig.unimelb.edu.au/pkcsm/). …”
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Structural, elastic, electronic, magnetic and thermal properties of X3FeO4 (X = mg, ca and Sr) materials by Mohammed El Amine Monir, Abdelkarim Bendoukha Reguig, M. A. Ghebouli, K. Bouferrache, Faisal Katib Alanazi, M. Fatmi, H. Bouandas

“…Abstract This prediction evaluates the different physical characteristics of magnetic materials X3FeO4 (X = Mg, Ca and Sr) by using density functional theory (DFT). …”
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Accurate recognition of micromorphology images of epoxy coatings for deep-sea environments based on a deep learning super-resolution method by JiaQi Pan, Furou Liu, Jia Feng, Fandi Meng, Yufan Chen, Jianning Chi, Zelan Li, Jie Li, Li Liu

“…This method effectively highlights the details and improves the recognition accuracy of the edge texture with the aim of providing a good basis for subsequent recognition and even lifetime prediction studies.…”
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Quantifying impacts of two ENSO patterns on South China sea summer monsoon onset by Lianyi Zhang, Junshu Lin, Zesheng Chen, Yanping Shi, Yan Du

“…These results help improve the SCSSM onset prediction by involving diverse ENSO impacts.…”
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The Modulation of Meteorological Parameters on Surface PM2.5 and O3 Concentrations in Guangzhou, China by Qiaoli Bu, Yingying Hong, Haobo Tan, Li Liu, Chunlin Wang, Jianjun Zhu, Pakwai Chan, Chen Chen

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Low-frequency spectral graph convolution networks with one-hop connections information for personalized tag recommendation by Zhengshun Fei, Haotian Zhou, Jinglong Wang, Gui Chen, Xinjian Xiang

“…Lastly, we analyze the impact of different internal components, pooling methods, parameter choices, and prediction approaches of LSGCNT on recommendation performance. …”
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Familial Hemiplegic Migraine with Severe Attacks: A New Report with ATP1A2 Mutation by E. Martínez, R. Moreno, L. López-Mesonero, I. Vidriales, M. Ruiz, A. L. Guerrero, J. J. Tellería

“…We identified a variant in heterozygous state in ATP1A2 gene (p.Thr364Met), pathogenic according to different prediction algorithms (SIFT, PolyPhen2, MutationTaster, and Condel). …”
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Machine learning-assisted design of Ti–V–Nb–Mo refractory high-entropy alloys with higher ductility and specific yield strength by Yan Li, Junjie Gong, Shilong Liang, Wei Wu, Yongxin Wang, Zheng Chen

“…The predicted results are in general agreement with the trends of the experimental data. …”
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