Detection and mapping of Antarctic lichen using drones, multispectral cameras, and supervised deep learning by Narmilan Amarasingam, Juan Sandino, Ashray Doshi, Diana King, Elka Blackman, Johan Barthelemy, Barbara Bollard, Sharon A. Robinson, Felipe Gonzalez

“…Two DL methods were evaluated to classify and map Usnea spp., Umbilicaria and Pseudephebe species (black lichen), moss and non-vegetation: method (1) standalone DL model fitting, namely fully convolutional network (FCN), U-Net, and Deeplabv3+, with semi-automatic labelling thresholding using VIs; and method (2) ensemble stacking by using eXtreme gradient boosting (XGBoost) as the input model, whose predictions are used as features for training a U-Net model. …”
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LGR6 modulates intervertebral disc degeneration through regulation of macrophage efferocytosis by Fudong Li, Yangyang Shi, Jun Chen, Jingchuan Sun, Jiangang Shi, Kaiqiang Sun, Bing Zheng

“…Principal component analysis (PCA), volcano plots, and hierarchical clustering were utilized to assess gene expression patterns. Weighted Gene Co-Expression Network Analysis (WGCNA) was employed to identify gene modules correlated with IVDD, and integrative analysis pinpointed key genes and pathways. …”
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Deep Learning–Based Prediction of Glaucoma Severity and Progression Using Imo/TEMPO Screening Program by Kei Sano, MD, PhD, Euido Nishijima, MD, PhD, Shunsuke Sumi, MD, PhD, Takahiko Noro, MD, PhD, Shumpei Ogawa, MD, PhD, Yuka Igari, MD, Aiko Iwase, MD, PhD, Tadashi Nakano, MD, PhD

“…Mean F1 score for total deviation (TD) and pattern deviation (PD) probability plot classification. …”
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A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma by Jia Liu, Lin Yao, Yong Yang, Jinchao Ma, Ruijian You, Ziyi Yu, Peng Du

“…We calculated RNA stemness scores (RNAss) for the samples to evaluate their stemness. SRlncRNAs and stemness-related mRNAs (SRmRNAs) in ccRCC were identified through weighted correlation network analysis (WGCNA), which employed sophisticated statistical methodologies to identify interconnected modules of related genes. …”
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Physical activity relates to carotid plaque vulnerability in older persons with subclinical carotid atherosclerosisResearch in context by Luoshiyuan Zuo, Maryam Kavousi, Julie A.E. Van Oortmerssen, Trudy Voortman, M Kamran Ikram, Daniel Bos

“…This study aimed to evaluate the association between physical activity and changes in carotid atherosclerotic plaque vulnerability, and the interaction between these two variables with the risk of first-ever stroke. …”
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Development and Validation of a Brain Aging Biomarker in Middle-Aged and Older Adults: Deep Learning Approach by Zihan Li, Jun Li, Jiahui Li, Mengying Wang, Andi Xu, Yushu Huang, Qi Yu, Lingzhi Zhang, Yingjun Li, Zilin Li, Xifeng Wu, Jiajun Bu, Wenyuan Li

“…We proposed a novel brain vision graph neural network (BVGN), incorporating neurobiologically informed feature extraction modules and global association mechanisms to provide a sensitive deep learning–based imaging biomarker. …”
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A 5-Year Follow-Up of Patient-Reported Outcome Measures Following External Beam Radiotherapy or Radical Prostatectomy in Localised Prostate Cancer by Rowan V. David, Peter L. Stapleton, Arman A. Kahokehr, Jason Lee, David I. Watson, John Leung, Michael E. O’Callaghan

“…<b>Results</b>: There were 1720 patients (EBRT n = 1441 vs. RP n = 279) with evaluable EPIC-26 PROMS. Patients in the EBRT group had a higher median age (74 vs. 66, <i>p</i> < 0.001) and National comprehensive Cancer Network (NCCN) high-risk disease (61% vs. 24%, <i>p</i> < 0.001). …”
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Transcriptome sequencing and Mendelian randomization analysis identified biomarkers related to neutrophil extracellular traps in diabetic retinopathy by Linlin Hao, Songhong Wang, Lian Zhang, Lian Zhang, Jie Huang, Yue Zhang, Xuejiao Qin

“…The qRT-PCR results revealed that the results of GBP2, PSAP and P2RY12 exhibited consistent expression patterns with the dataset.ConclusionThis study identified GBP2, P2RY12 and PSAP as NETs-associated biomarkers in the development of PDR, offering new insights for clinical diagnosis and potential treatment strategies for DR.…”
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Behavioral and neural effects of temporoparietal high-definition transcranial direct current stimulation in logopenic variant primary progressive aphasia: a preliminary study by Elias D. Granadillo, Elias D. Granadillo, Mason Fellmeth, Vahab Youssofzadeh, Joseph Heffernan, Priyanka P. Shah-Basak, Sara B. Pillay, Candida Ustine, Peter Kraegel, Shelby Schold, Kimberly D. Mueller, Kimberly D. Mueller, Chrysanthy Ikonomidou, Ozioma Okonkwo, Manoj Raghavan, Jeffrey R. Binder

“…Preliminary data on efficacy was evaluated based on relative changes from baseline in language and cognitive scores. …”
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Efficient Sleep, Enhanced Attention: Exploring the Interplay With RBC-Inflammation Mechanisms in Hypoxic High-Altitude Areas by Shi CY, Xue XJ, Li ZF, Huang XY, Su R, Wang NN, Zhu JG, Li H, Ma HL, Liu M, Zhang DL

“…Participants underwent an attention network test with concurrent electroencephalography to assess attentional function. …”
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W-Band Transverse Slotted Frequency Scanning Antenna for 6G Wireless Communication and Space Applications by Hurrem Ozpinar, Sinan Aksimsek, Nurhan Türker Tokan

“…Additionally, it exhibits pattern-reconfigurable capabilities, enabling main lobe beam steering between 5° and 68° with low side lobe levels. …”
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Incorporating Attention Mechanism Into CNN-BiGRU Classifier for HAR by Ohoud Nafea, Wadood Abdul, Ghulam Muhammad

“…The proposed methodology uses convolutional neural networks (CNN) and recurrent neural networks (RNN) to extract the spatial and temporal features. …”
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Climate change–drylands–food security nexus in Africa: From the perspective of technical advances, challenges, and opportunities by Hirwa, Hubert, Li, Fadong, Qiao, Yunfeng, Measho, Simon, Muhirwa, Fabien, Tian, Chao, Leng, Peifang, Muhirwa, Fabien, Tian, Chao, Leng, Peifang, Ingabire, Romaine, Itangishaka, Auguste Cesar, Chen, Gang, Turyasingura, Benson

“…To bridge the gap from science to policy making in the CDF nexus, it is vital to enhance the impacts and feedbacks of ecohydrological processes on agrarian production, ecosystem service tradeoffs and their effects on livelihoods, and regional development and preservation by optimization of the ecological water security pattern. This state-of-the-art assessment uses acquired information and knowledge to conceptually evaluate the past, current, and future impacts and risks and facilitates decision making through the delivery of long-term sustainability and socio-ecological resilience.…”
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Performance Analyses of the Radio Orbital Angular Momentum Steering Technique Based on Ka-Band Antenna by Mingtuan Lin, Yue Gao, Peiguo Liu, Zhiqing Guo

“…The misalignment in the orbital angular momentum- (OAM-) based system would distort the radiation patterns of twisted beams carrying OAM, consequently making the OAM-based communication infeasible. …”
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Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence by Xiao-Xiao Wang, Yu-Yun Song, Rui Jin, Zi-Long Wang, Xiao-He Li, Qiang Yang, Xiao Teng, Fang-Fang Liu, Nan Wu, Yan-Di Xie, Hui-Ying Rao, Feng Liu

“…The aim of this study is to apply an artificial intelligence (AI) system based on second-harmonic generation (SHG)/two-photon-excited fluorescence (TPEF) technology to automatically assess the dynamic patterns of hepatic steatosis in MASLD mouse models. …”
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MindLift: AI-powered mental health assessment for students by Shanky Goyal, RishiRaj Dutta, Saurabh Dev, Kola Narasimha Raju, Mohammed Wasim Bhatt

“…The goal of this research is to create a real-time, multimodal system that can assess mental health through the use of behavioral pattern tracking, audio tone analysis, facial expression recognition, and text sentiment interpretation. …”
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LSTM and TCN application for airport surface distress detection by Ludek Cicmanec, Adam Kubica, Jiri Maslan

“…Using experimental measurements taken on a test road section, we tested the smartphone accelerometers to recognize and categorize selected distress patterns. In our work, we investigated the capacity of neural networks with a Long Short-Term Memory (LSTM) layer with normalized data weighted and not weighted, bidirectional LSTM, and Temporal Convolutional Networks (TCNs). …”
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LSTM vs. Prophet: Achieving Superior Accuracy in Dynamic Electricity Demand Forecasting by Saleh Albahli

“…The LSTM component captures nonlinear dependencies and long-term temporal patterns, while Prophet models seasonal trends and event-driven fluctuations. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…Several machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forests, and Neural Networks, were implemented and evaluated. Model performance was assessed using accuracy, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) metrics. …”
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Characterization of private mutations in the spike protein of SARS-CoV-2 correlates with viral prevalence by Shuo Wang, Ziyang Hao, Yuhan Ding, Heng Rong, Shuo Ning, Qiao Qiao, Xiaojuan Zhu, Tao Wu, Kangchen Zhao, Liguo Zhu, Jingxin Li, Yiyue Ge, Lunbiao Cui

“…Methods Genomic information from the SARS-CoV-2 network surveillance laboratories in Jiangsu Province in 2023 was collected. …”
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