Isokinetic knee strength as a predictor of cardiorespiratory responses during loaded aerobic capacity test in elite athletes by Bekir Çar, Ahmet Kurtoğlu, Özdemir Atar, Musa Türkmen, Özgür Eken, Mehmet Soyler, Monira I. Aldhahi

“…Cardiorespiratory parameters—average breath volume (ABV), average breath frequency (ABF), auxiliary oxygen density (AOD), and heart rate (HR)—were recorded during the Bruce Protocol conducted under two conditions: unloaded and with a 10 kg loaded vest. …”
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Energy Dissipation and Failure Characteristics of Layered Composite Rocks under Impact Load by Wenjie Liu, Ke Yang, Wei Zhen, Xiaolou Chi, Rijie Xu, Xin Lv

“…The energy dissipation pattern of composite rock had an obvious strain rate effect. …”
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Neuroendocrine tumors of the digestive system: pathologic and molecular characteristics by V. V. Delektorskaya

“…The grade (G) is based on the proliferative activity of the tumor assessed by the mitotic rate or by Ki-67 immunohistochemistry. Several markers are useful in the identification of a primary organ of NETs in metastatic lesions are also discussed. …”
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Network meta-analysis of erlotinib, gefitinib, afatinib and icotinib in patients with advanced non-small-cell lung cancer harboring EGFR mutations. by Wenhua Liang, Xuan Wu, Wenfeng Fang, Yuanyuan Zhao, Yunpeng Yang, Zhihuang Hu, Cong Xue, Jing Zhang, Jianwei Zhang, Yuxiang Ma, Ting Zhou, Yue Yan, Xue Hou, Tao Qin, Xiaoxiao Dinglin, Ying Tian, Peiyu Huang, Yan Huang, Hongyun Zhao, Li Zhang

“…Pooled data on objective response rate (ORR), progression free survival (PFS), overall survival (OS) were calculated. …”
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Demographic and clinical characteristics of patients with benign bone tumors: Evidence of bimodal age distribution in a Hispanic population by Blake C. Martin, Mohammad Khalil, Juan Lopez-Alvarenga, Michael Sander

“…This indicates an incidence rate of 0.00018 per person-year. The average age was 38.8 years (SD 24.0), with females representing 58 % of the sample. …”
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Reduced Inter-Element Interference mmWave MIMO Antenna and Its Application in WBAN by Jawad Ahmad, Mohammad Hashmi

“…A specific absorption rate (SAR) analysis confirmed that the design complies with safety standards for both 1g and 10g tissue models. …”
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Early Recurrence of Hepatocellular Carcinoma in Patients without Microscopic Vascular Invasion: Clinicopathological Characteristics and Risk Factors by Ngo HTT, Nguyen DD, Dang MX, Doan TTP, Thai TT

“…Microscopic features of both tumor and non-tumor liver tissue were assessed using Hematoxylin-Eosin-stained slides.Results: The majority of patients were male (78.3%) and had cirrhosis (72.5%). The early recurrence rate was 31.9%, with most recurrences occurring between 6- and 18-month post-surgery. …”
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Factors associated with interstitial lung disease in patients with rheumatoid arthritis by Benyapa Suppa-Udom, Supparerk Disayabutr, Suwimon Wonglaksanapimon, Krittachat Butnian, Wanruchada Katchamart

“…Patients exhibited low disease activity [mean Disease Activity Score 28-erythrocyte sedimentation rate score (SD) 2.69 (0.90)] and mild functional impairment [median Health Assessment Questionnaire score (range) 0.25 (0–0.63)]. …”
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Comparative analysis of START and CAVI arterial stiffness scores in hypertensive patients by A. N. Sumin, A. V. Shcheglova, I. B. Bakholdin

“…Parameters were associated with age (r=0,412 for CAVI and r=0,355 for START; p<0,001), smoking duration (r=0,390 and r=0,361; p<0,001), glomerular filtration rate (r=-0,317 and r= -0,318; p<0,001), body mass index (r=-0,176 and r=-0,185; p=0,001). …”
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Multi-Step Natural Gas Load Forecasting Incorporating Data Complexity Analysis with Finite Features by Ning Tian, Bilin Shao, Huibin Zeng, Meng Ren, Wei Zhao, Xue Zhao, Shuqiang Wu

“…Concurrently, variational mode decomposition (VMD) provides frequency-domain decomposition capability, while the gated recurrent unit (GRU) captures long-term dependencies. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

“…This study evaluates multiple ML models, including logistic regression, random forest, and LightGBM, alongside DL architectures such as ALBERT and Gated Recurrent Units (GRUs), for both binary and multi-class classification of mental health conditions. …”
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MIR155HG promotes metastasis and cisplatin resistance of cervical cancer cells by regulating the miR-409-3p and ZEB1 axis by Yanxia Chen, Jing Wang, Youqiang Heng, Yu Guo, Ka Ding, Cailing Ma

“…Overexpression of MIR155HG (MIR155HG-OE) demonstrated higher proliferation and migration levels in HeLa cells, while MIR155HG inhibited the apoptosis rate of HeLa cells. Meanwhile, we found MIR155HG can reduce the effect of cisplatin sensitivity on HeLa cells. …”
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RNAi-mediated suppression of toll-like receptor NlToll1 enhances Nilaparvata lugens susceptibility to entomopathogenic fungal infection by Zhu-Long Shao, Chen-Ping Lan, Xiao-Ping Yu, Zheng-Liang Wang

“…Toll-like receptors (TLRs) are a family of crucial pattern recognition proteins that are responsible for the immunologic recognition of invading pathogen in insects. …”
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Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning by Mohammed Assiri, Mahmoud M. Selim

“…For the feature extraction process, the squeeze-and-excitation capsule network (SE-CapsNet) effectively captures spatial hierarchies and complex relationships within gesture patterns. In addition, an ensemble of classification processes, such as bidirectional gated recurrent unit (BiGRU), Variational Autoencoder (VAE), and bidirectional long short-term memory (BiLSTM) technique, is employed. …”
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Wind Speed Forecasting in the Greek Seas Using Hybrid Artificial Neural Networks by Lateef Adesola Afolabi, Takvor Soukissian, Diego Vicinanza, Pasquale Contestabile

“…Of all the ANNs examined, the hybrid model combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) networks demonstrated superior forecasting performance compared to the individual models, as evaluated by standard statistical metrics, while it also exhibited a very good performance at high wind speeds, i.e., greater than 15 m/s. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…Hybrid forecasting models were then constructed by integrating VMD with both statistical (autoregressive integrated moving average [ARIMA]) and deep learning (gated recurrent unit [GRU], long short-term memory [LSTM], and Transformer) architectures. …”
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An Overview of Deep Learning Applications in Groundwater Level Modeling: Bridging the Gap between Academic Research and Industry Applications by Ahmed Shakir Ali Ali, Farhad Jazaei, Peyman Babakhani, Muhammad Masood Ashiq, Alireza Bakhshaee, Brian Waldron

“…DL models utilize complex algorithms to identify patterns that may be difficult to observe with traditional physics-based models, specifically where the underlying physics is complex or poorly understood or where the available physical model is too simple. …”
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Multi-view mixture-of-experts for predicting molecular properties using SMILES, SELFIES, and graph-based representations by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Indra Priyadarsini, Seiji Takeda

“…Our analysis of routing activation patterns reveals that MoL-MoE dynamically adjusts its use of different molecular representations based on task-specific requirements. …”
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Mediodorsal thalamic nucleus mediates resistance to ethanol through Cav3.1 T-type Ca2+ regulation of neural activity by Charles-francois V Latchoumane, Joon-Hyuk Lee, Seong-Wook Kim, Jinhyun Kim, Hee-Sup Shin

“…Thalamocortical activity is known to orchestrate sensory gating and consciousness switching. The precise thalamic regions involved, or the firing patterns related to the unconsciousness, remain unclear. …”
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Hybrid GIS-Transformer Approach for Forecasting Sentinel-1 Displacement Time Series by Lama Moualla, Alessio Rucci, Giampiero Naletto, Nantheera Anantrasirichai, Vania Da Deppo

“…This study presents a deep learning-based approach for forecasting Sentinel-1 displacement time series, with particular attention to irregular temporal patterns—an aspect often overlooked in previous works. …”
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