Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. …”
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Identification of m6 A-regulated ferroptosis biomarkers for prognosis in laryngeal cancer by Xin Wang, Wen Zhang, Kun Liang, Yujuan Wang, Jin Zhang, Jinping Wang, An Li, Yonggang Yun, Hiu Liu, Yanan Sun

“…The TCGA-HNSC dataset consisted of 110 primary tumor oropharynx samples and 12 control oropharynx samples, while the GSE65858 dataset contained forty-eight primary tumor oropharynx samples. …”
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Trace Copilot: Automatically Locating Cryptographic Operations in Side-Channel Traces by Firmware Binary Instrumenting by Shipei Qu, Yuxuan Wang, Jintong Yu, Chi Zhang, Dawu Gu

“…In contrast, obtaining the (partial) binary firmware is more prevalent in practical attacks on embedded devices. While binary code theoretically encapsulates necessary information for side-channel attacks on software-implemented cryptographic algorithms, there is no systematic study on leveraging this information to facilitate side-channel analysis. …”
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Metabolic, Microvascular, and Structural Predictors of Long-Term Functional Changes Evaluated by Multifocal Electroretinogram in Type 1 Diabetes by Mariacristina Parravano, Serena Fragiotta, Eliana Costanzo, Fabiana Picconi, Paola Giorno, Daniele De Geronimo, Daniela Giannini, Monica Varano, Vincenzo Parisi, Lucia Ziccardi

“…The main factor influencing R1 IT was HbA1c, while R1 RAD was affected by Hpi and CC FD%. R1 + R2 IT was influenced by Hpi, LDi (<i>p</i> > 0.001, all), and modifications in the perfusion density in the SCP (<i>p</i> < 0.001) and DCP (<i>p</i> = 0.03) at the parafovea. …”
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Thermal performance enhancement in a solar air heater fitted with flapped V-baffles: Numerical study by Chinnapat Turakarn, Pitak Promthaisong, Teerapat Chompookham

“…The finite volume method using the SIMPLE algorithm was used to resolve the problem. The goal was to enhance the thermal performance (in terms of the thermal enhancement factor, TEF) by increasing the heat transfer together with reducing the pressure loss, compared with a conventional V-baffles (CVB). …”
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Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification by Shi Chen, Jiwei Qin, Shuning Dong, Yixi Liu, Pingping Sun, Dongze Yao, Xiaoyan Song, Congcong Li

“…Land use change dynamics were quantified via a transfer matrix, while changes in the ESV were evaluated using the ecosystem sensitivity index and ecological contribution rate. …”
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Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles by Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai

“…Our analyses revealed that the Random Forest algorithm exhibited the highest predictive accuracy, with AUC values of 0.809 for kidney stones, 0.99 for ureter stones, and 0.775 for multiple location stones. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Among them, 173 individuals had NSCLC with 228 BMs, while 87 patients were diagnosed with SCLC with 142 BMs. …”
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Preclinical markers of carotid atherosclerosis and cardiovascular risk assessed by the ESH/ESC scale (2003, 2007, 2009) by S. Sh. Urazalina, A. N. Rogoza, T. V. Balakhonova, R. P. Myasnikov, T. E. Kolmakova, Yu. A. Karpov, V. V. Kukharchuk, S. A. Boytsov

“…In the “low-risk” and “intermediate-risk” groups, most patients had normal blood pressure levels (72,8 % and 83,5 %, respectively), while most patients in the “high-risk” group had arterial hypertension (56,7 %). …”
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The value of triglyceride–glucose index–related indices in evaluating migraine: perspectives from multi–centre cross–sectional studies and machine learning models by Zixuan Yan, Lincheng Duan, Hong Yin, Muchen Wang, Jingwen Li, Chenghua Li, Xiao Wang, Dingjun Cai, Fanrong Liang, Wenchuan Qi

“…TyG–BMI indicated a strong positive association beyond the threshold of 206, while TyG–WHtR demonstrated a significant positive link below the cutoff of 7.4. …”
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DeepD&Cchl: an AI tool for automated 3D single-cell chloroplast detection, counting, and cell type clustering by Qun Su, Le Liu, Zhengsheng Hu, Tao Wang, Huaying Wang, Huaying Wang, Qiuqi Guo, Xinyi Liao, Yan Sha, Feng Li, Zhao Dong, Zhao Dong, Shaokai Yang, Shaokai Yang, Ningjing Liu, Qiong Zhao, Qiong Zhao, Qiong Zhao

“…It utilizes You-Only-Look-Once (YOLO), a real-time detection algorithm, for accurate and efficient performance. …”
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Soil moisture dominates gross primary productivity variation during severe droughts in Central Asia by Tao Yu, Guli Jiapaer, Anming Bao, Ye Yuan, Jiayu Bao, Tim Van de Voorde

“…RF predictions also indicated that during severe drought, SM had a significant effect on GPP, while Srad, Tem, and VPD had a slight effect on GPP.…”
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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…A Long Short-Term Memory (LSTM) neural network algorithm is employed, recognized for its strong predictive capability in time series data. …”
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Human-in-the-Loop Optimization of the Stiffness and Alignment of a Prosthetic Foot to Reduce the Metabolic Cost of Walking by Thijs Tankink, Han Houdijk, Johnnidel Tabucol, Marco Leopaldi, Juha M. Hijmans, Raffaella Carloni

“…This study aims to explore the potential of human-in-the-loop optimization to individually optimize prosthetic foot stiffness and alignment to decrease the metabolic cost of walking of transtibial amputees. 10 transtibial amputees underwent an optimization protocol while walking on a treadmill with an experimental prosthetic foot with tuneable stiffness and alignment. …”
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Comparison of Radiomics and conventional SUVr methods for Alzheimer’s disease classification using AV45 PET imaging by Haiyan Gao, Arui Tan, Junhao Wu, Zhen Cao, Ziyang Zhu, Wei Zhang

“…Feature importance was ranked using a random forest algorithm, and three models were constructed: an SUVr model, a radiomics model, and a combined model. …”
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A biphasic locomotor response to acute unsignaled high temperature exposure in Drosophila. by Daniela Ostrowski, Autoosa Salari, Melissa Zars, Troy Zars

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A One- or Two-Stage Revision of Fungal Prosthetic Joint Infection: A Review of Current Knowledge, Pitfalls and Recommendations by Hazem Alkhawashki, Joseph Benevenia, Lorenzo Drago, Yazan Kadkoy

“…Fungal prosthetic joint infection (fPJI) is one of the orthopaedic pathologies where there is no clear evidence, guidelines or algorithm to guide the surgeon in its management. This is in addition to the difficulty with which these infections are diagnosed, isolated and treated. …”
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Exploring the Shared Genetic Characteristics of Peri-Implantitis and Osteoporosis: A Transcriptomic Analysis Perspective by Churen Zhang, Feixiang Wang, Jianguo Ke, Cuihong Lin, Xiaohua Zeng, Qiuyan Yang, Qiaoling Cai

“…Finally, the CIBERSORT core algorithm was used to calculate immune cell infiltration levels. …”
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Proximal LiDAR Sensing for Monitoring of Vegetative Growth in Rice at Different Growing Stages by Md Rejaul Karim, Md Nasim Reza, Shahriar Ahmed, Kyu-Ho Lee, Joonjea Sung, Sun-Ok Chung

“…LiDAR offers high-resolution, non-destructive 3D canopy characterization, yet applications in rice cultivation across different growth stages remain underexplored, while LiDAR has shown success in other crops such as vineyards. …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The k-fold cross-validation technique is utilized in every algorithm to mitigate the overfitting problem during the training of models. …”
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