Age-Related Differences in Bimanual Isometric Force Tracking by Elisa Galofaro, Nicola Vale, Giulia Ballardini, Nicola Smania, Maura Casadio

“…Notably, the percentage of total force exerted by the left hand was negatively correlated with the disparity between the left and right coefficients of variation. This study confirms previous findings on the effect of aging on bimanual force control and provides evidence suggesting that the contribution of each hand may depend on the variability in force exertion.…”
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A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Türkiye by Ulubey Çeken, Fadime Sertçelik, Abdullah İçen

“…Additionally, a heteroscedastic model was created for aleatory variability as a function of <i>M_W</i>. The closest distance to the surface projection of the fault plane (<i>R_JB</i>) is between 0 and 350 km. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”

Long-term evolution of the calibration constant on a mobile water vapour Raman lidar by P. Chazette, J. Totems, F. Laly

“…We note that the use of ground-based measurements does not introduce any more uncertainty in the lidar calibration coefficient than vertical profiles obtained by radiosondes or airborne means. …”
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Assessment of heavy metal exposure risk to aquatic birds in the key wetland habitats of the Yellow River (China), using an integrated model by Jian Ding, Ni Wang, Yaqiao Lian, Qian Li, Xinran Li, Fei Yu

“…Heavy metal pollution poses a growing threat to wetland ecosystems, impacting their structure and function. Chenqiao Wetland and Qinglong Lake (Henan, China), key bird habitats in the middle and lower reaches of the Yellow River, were analyzed for heavy metal contamination. …”
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Effects of bedroom environment on average heart rate during sleep in temperate regions: Winter conditions in healthy males in their twenties with average BMI by Noriaki Oota, Yasuki Yamauchi, Gota Iwase, Masaru Abuku, Yasuhiro Hiraguri

“…Additionally, it has been suggested that as the average heart rate decreases, SDNN increases, indicating favorable autonomic function. This study aimed to identify the environmental factors that most significantly affect the day-to-day variability of average heart rate during sleep (SHR) in winter. …”
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Predictive factors of patient length of stay with multiloculated pleural effusion after medical thoracoscopy: single-center retrospective cohort study by Wiwien Heru Wiyono, Mohamad Fahmi Alatas, Andika Chandra Putra, Erlina Burhan, Amirah Nisrina, Elvan Wiyarta, Gita Fajri Gustya, Muhammad Ilham Dhiya Rakasiwi, Adlina Briliani

“…This study aimed to identify factors influencing the length of stay (LoS) after rigid medical thoracoscopy for loculated PE and assess clinical outcomes, including improvements in lung function. Method This was a retrospective cohort study conducted at St. …”
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Protocol refinement and inter- and intra-rater reliability assessment of ultrasound-based measurements of hamstring architecture, and echo intensity, and intra-rater reliability of... by Maria Belinda Cristina C. Fidel, Jan Tyrone Cabrera, Christine Grace V. Ogerio, Johann Querijero, Helen A. Banwell, Consuelo B. Gonzalez-Suarez

“…Inter-rater reliability ranged from moderate to excellent across all variables. Shear wave elastography showed moderate to excellent intra-rater reliability, with higher consistency during contraction than rest. …”
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A Predictive Model of the Photosynthetic Rate of Chili Peppers Using Support Vector Regression and Environmental Multi-Factor Analysis by Bin Li, Bo Qiao, Qianyu Zhao, Dan Yang, Rongcheng Zhu, Zhexuan Wang, Yujie Yang

“…Light intensity, CO₂ concentration, and temperature are three primary environmental factors with high temporal variability, nonlinearity, and strong coupling, which directly influence the photosynthetic rate of plants. …”
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Allometric equations for estimating biomass and carbon stocks of on-farm bamboo species in the agricultural landscapes of Kenya by John N. Kigomo, Justus Mukovi, Nancy Bor, Betty Leshaye, Titus Cheruiyot, Margaret Kuria

“…We developed species-specific and pooled (multiple species) allometric equations by regressing DBH, height and wood density variables against AGB using five non-linear functions. …”
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Fuzzy volume fraction model representation of blood-based sisko tri-hybrid nanofluid flow via a stretching cylinder by N. Deepa, P. Kavya, N. Thamaraikannan, S. Madhanraj, P. Asaigeethan, K. Loganathan

“…The triangular membership function (TMF) is utilized to analyze the variability of uncertainty, while the α− cut is responsible for controlling the TFNs. …”
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Analysis of factors influencing the increase of extracellular water ratio in tumor patients without edema signs by Heling Zhu, Panpan Gan, Hao Jiang, Liangliang Bao, Chengjiang Liu, Jiawen Yu, Jiawen Yu

“…PA was the most influential factor among all independent variables affecting ECW/TBW (B = −1.006, p &lt; 0.001). …”
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Correlation of magnetic resonance imaging parameters with montreal cognitive assessment-Indonesian (MOCA-INA) score in dementia patients at Prof. Dr. IGNG Ngoerah General Hospital,... by Made Widhi Asih, Elysanti Dwi Martadiani, I Wayan Gede Artawan Eka Putra, Felicia Nike, Putri Ayu Ratnasari, Nugra Arenz Raturandang, Jessieca Liusen, Anak Agung Parama Swari Khrisna, Luh Dindi Ayu Surya Kanti, Adsel Kartadinata

“…Correlation between variables was evaluated based on the correlation coefficient, which indicates the direction and strength of the correlation. …”
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Sensitivity Analysis of Soil Hydraulic Parameters for Improved Flow Predictions in an Atlantic Forest Watershed Using the MOHID-Land Platform by Dhiego da Silva Sales, Jader Lugon Junior, David de Andrade Costa, Renata Silva Barreto Sales, Ramiro Joaquim Neves, Antonio José da Silva Neto

“…The hydraulic soil parameters of VGM are dependent on soil type and are typically estimated from experimental data; however, they are often obtained using pedotransfer functions, which carry significant uncertainty. As a result, calibration is frequently required to account for both the natural spatial variability of soil and uncertainties estimation. …”
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Enhancing Urban Heat Island Analysis Through Multisensor Data Fusion and GRU-Based Deep Learning Approaches for Climate Modeling by Ning Tang, Muhammad Farhan, Pir Mohammad, M. Abdullah-Al-Wadud, Saddam Hussain, Umair Hamza, Rana Muhammad Zulqarnain, Nazih Yacer Rebouh

“…The adopted approach emphasizes vegetation&#x0027;s crucial function in reducing UHI&#x0027;s effects and offers valuable insights for urban planning and measures to mitigate climate change.…”
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A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation by Dong Miao, Ying Zhao, Xue Ren, Meng Dou, Yu Yao, Yiran Xu, Yingchao Cui, Ailian Liu

“…To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommodating the complex anatomy and significant variations, optimizing surgical approaches, reducing postoperative complications, and preserving liver function.This research presents a novel approach to automating liver segmentation by identifying seven key anatomical landmarks using portal venous phase images from contrast-enhanced magnetic resonance imaging (CE-MRI). …”
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Assessment of Matrix Metalloproteinases a Prognostic Indicator in Advanced Fibrotic Lung Disease: A Systematic Review by Mehvish Aqil, Saif Ur Rahman, Muhammad Zeeshan Aslam, Mostafa Ahmed Abdellah Ahmed, Ammar Ahmed, Sidra Javaid, Ehsan Ul Haq

“…The MMP-7 was consistently elevated in 73.3% (n=11) of the studies and correlated with disease severity, lung function decline, and progression. In 46.7% (7) of studies, MMP-9 was associated with imaging severity and functional impairments, and in 26.7% (4) of studies, MMP-7 was found as the strongest biomarker, and the correlation coefficient calculated was from (r = 0.65 to 0.80), for MMP-9 it was (r = 0.4 to 0.6) and for MMP-1 (r = 0.3 to 0.45). …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…Principal Component analysis further highlighted five clusters of health-related variables, identifying age-related metabolic indicators (AGE, HbA1c, BMI), kidney function markers (creatinine (Cr), Urea), cardiovascular lipid profiles (Cholesterol, LDL), lipid transport (VLDL), and protective cardiovascular indicator (HDL). …”
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Quantitative analysis of ocular deviation under eye occlusion: a descriptive study using the ORTe EYENAC eye-tracking system by Shunya Tatara, Yuna Magara, Touko Sasaki, Fumiatsu Maeda, Noriaki Murata, Kazuhiro Itagaki, Tomoya Handa, Haruo Toda

“…Data were fitted to a logistic function to estimate ocular deviations, deviation speed, and stabilization time. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…The predicted data were evaluated by computing the correlation coefficients and area under the curve (AUC). Results: As a numerical variables analysis, albumin and hemoglobin predictions were relatively accurate (R=0.71, 0.74). …”
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