Spatio-temporal Evolution of Land Surface Temperature and Its Response to LULC in the Urban Agglomeration of Central Yunnan by LIN Zhiqiang, PENG Shuangyun, SHI Shuangfu, HUANG Bangmei, MA Dongling, ZHU Ziyi, MA Xiaoliang, GONG Luping

“…The mesothermal area always occupied an absolutely dominant position (40%), but its area share decreased year by year. (2) From 1990 to 2020, the areas with UTFVI 0 showed an increasing trend year by year, and the areas with UTFVI > 0.02 showed a decreasing trend, and the ecological and thermal environments were gradually improved. (3) There were response differences in LST for different LULC types. …”
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Maximal and Explosive Muscle Strength During Hip Adduction Squeeze and Hip Abduction Press Test Using A Handheld Dynamometer: An Intra- and Inter-tester Reliability Study by Lasse Ishøi, Kristian Thorborg, Laura Krohn, Lars Louis Andersen, Asger Møller Nielsen, MIkkel Bek Clausen

“…Relative reliability for all tests was assessed using ICC~2,1~ two-way mixed model with absolute agreement, thereby taking bias between testers into account…”
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Pharmacokinetic Characterisation and Comparison of Bioavailability of Intranasal Fentanyl, Transmucosal, and Intravenous Administration through a Three-Way Crossover Study in 24 He... by S. Nardi-Hiebl, J. W. Ndieyira, Y. Al Enzi, W. Al Akkad, T. Koch, G. Geldner, C. Reyher, L. H. J. Eberhart

“…Cmax was 886 pg/ml (CV% = 59.38) for intravenous, 338 pg/ml (CV% = 45.61) for intranasal, and 310 pg/ml (CV% = 29.58) for oral transmucosal administration. tmax was shortest for intravenous administration (0.06 h, SD = 0.056), followed by intranasal (0.21 h, SD = 0.078) and oral transmucosal administration (1.20 h, SD = 0.763). Dose-adjusted absolute bioavailability was determined to be 74.70% for the intranasal formulation and 41.25% for the oral transmucosal product. …”
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EASTERN MYSTICISM AND TIMOTHY LEARY: HUMAN BEYOND THE CONVENTIONAL REALITY by T. V. Danylova

“…These non-dualistic traditions emphasize: we have to transcend our dual thinking in order to perceive true nature of our inner self and to achieve the state of the absolute unity with everything that exists. “Subject – object” duality is illusory. …”
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Problem of pain in the USA: evaluating the generalisability of high-impact chronic pain models over time using National Health Interview Survey (NHIS) data by Sean Mackey, Titilola Falasinnu, Md Belal Hossain, Mohammad Ehsanul Karim, Kenneth Arnold Weber

“…We used logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) and random forest techniques. …”
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Delirium at the intensive care unit and long-term survival: a retrospective study by Ignazio De Trizio, Maria Angeliki Komninou, Jutta Ernst, Reto Schüpbach, Jan Bartussek, Giovanna Brandi

“…The survival analysis was reported using Kaplan-Meier curves and absolute risk differences (ARD). A multivariable logistic regression model was fitted with long-term survival at four years after ICU-discharge as outcome of interest, including several clinical conditions and interventions associated with long-term survival for ICU patients. …”
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Comparative Study on the Reservoir Characteristics and Development Technologies of Two Typical Karst Weathering-Crust Carbonate Gas Reservoirs in China by Haijun Yan, Ailin Jia, Fankun Meng, Qinyu Xia, Wei Xu, Qingfu Feng, Wenjun Luo, Xinyu Li, Xun Zhu, Yicheng Liu

“…For these two gas reservoirs, although there are some similar aspects, such as the screen of enrichment areas, the application of irregular well pattern and reservoir stimulation techniques, the criteria of enrichment areas, the well types, and the means of reservoir stimulation are absolutely different. In addition, due to the differences of control reserves and production capacity for these two kinds of reservoirs, the mode of stable production is also different. …”
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An outline of typology of social relations in the countries of Byzantine civilization in the VII-XIV Centuries by Nerijus Babinskas

“…Gudavičius, there were two ways of historical development of humankind: the main one (extensive) and the exceptional one (intensive). The absolute majority of civilizations developed towards the pattern of the main way. …”
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Luminescence Nanothermometry Based on Pr3+ : LaF3 Single Core and Pr3+ : LaF3/LaF3 Core/Shell Nanoparticles by M. S. Pudovkin, D. A. Koryakovtseva, E. V. Lukinova, S. L. Korableva, R. Sh. Khusnutdinova, A. G. Kiiamov, A. S. Nizamutdinov, V. V. Semashko

“…The formation of the NP shell led to increasing of effective luminescence lifetime τeff of the 3P0 state of Pr3+ ions for the core nanoplates, core/shell nanoplates, core nanospheres, and core/shell nanospheres the values of τeff were 2.3, 3.6, 3.2, and 4.7 μsec, respectively (at 300 K). The values of absolute sensitivity Sa for fluorescence intensity ratio (FIR) thermometry was 0.01 K−1 at 300 K for all the samples. …”
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CompositIA: an open-source automated quantification tool for body composition scores from thoraco-abdominal CT scans by Raffaella Fiamma Cabini, Andrea Cozzi, Svenja Leu, Benedikt Thelen, Rolf Krause, Filippo Del Grande, Diego Ulisse Pizzagalli, Stefania Maria Rita Rizzo

“…MultiResUNet was used to identify CT slices intersecting the L1 and L3 vertebrae, and its performance was evaluated using the mean absolute error (MAE). Two U-nets were used to segment the axial slices, with performance evaluated through the volumetric Dice similarity coefficient (vDSC). …”
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Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis by Tito Bassani, Andrea Cina, Fabio Galbusera, Andrea Cazzato, Maria Elena Pellegrino, Domenico Albano, Luca Maria Sconfienza

“…Mean ± standard deviation absolute errors were 7 ± 7° (LL), 9 ± 7° (SS), 9 ± 8° (PI), and 1.1 ± 0.8 cm (SVA). …”
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Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

“…Utilizing five machine learning models, namely linear regression (LR), least absolute shrinkage and selection operator (LASSO), extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR), we constructed inversion models. …”
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Development and validation of a novel risk-predicted model for early sepsis-associated acute kidney injury in critically ill patients: a retrospective cohort study by Bo Li, Kun Zhang, Cong-Cong Zhao, Zi-Han Nan, Yan-Ling Yin, Li-Xia Liu, Zhen-Jie Hu

“…Data for patients with sepsis included in the development cohort were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The least absolute shrinkage and selection operator regression method was used to screen the risk factors, and the final screened risk factors were constructed into four machine learning models to determine an optimal model. …”
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Study on the Calibration Transfer of Soil Nutrient Concentration from the Hyperspectral Camera to the Normal Spectrometer by Xue-Ying Li, Guo-xing Ren, Ping-Ping Fan, Yan Liu, Zhong-Liang Sun, Guang-Li Hou, Mei-Rong Lv

“…The transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using a normal spectrometer. The absolute coefficients Rt2 and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer. …”
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Association of liver biopsy pathology on outcome of patients undergoing heart transplantation by Lauren S. Eichenwald, MD, Raffi Karagozian, MD, Adam J. Eichenwald, PhD, John Morrissey, MD MBA, Saurav Kini, MD, Ariella Stein, MSCIS-HI, Amanda R. Vest, MBBS MPH

“…Conclusion: There was no significant difference in the survival rates between HT candidates with and without advanced fibrosis on the waitlist and post-HT, challenging the notion that advanced fibrosis should be an absolute contraindication for HT. However, our findings are limited by the small sample size, retrospective design, and focus on patients already deemed suitable for transplantation. …”
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Dual-modal radiomics ultrasound model to diagnose cervical lymph node metastases of differentiated thyroid carcinoma: a two-center study by Jiajia Tang, Yan Tian, Jiaojiao Ma, Xuehua Xi, Liangkai Wang, Zhe Sun, Xinyi Liu, Xuejiao Yu, Bo Zhang

“…We extracted radiomic characteristics from grayscale ultrasound and CDFI images, then applied lasso (least absolute shrinkage and selection operator) regression analysis to analyze radiomics features and calculate the rad-score. …”
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Development of a machine learning model related to explore the association between heavy metal exposure and alveolar bone loss among US adults utilizing SHAP: a study based on NHAN... by Jiayi Chen

“…Feature selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression with 10-fold cross-validation. …”
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A Novel Rubber Composite Sleeper-Deformation-Prediction Model Based on Response Surface Method (RSM) and Machine Learning (ML) Techniques by Abdulmumin Ahmed Shuaibu, Zhiping Zeng, Ibrahim Hayatu Hassan, Wang Weidong, Hassan Suleiman Otuoze, Suleiman Abdulhakeem, Bushrah Baba Abdulrahman

“…Model performance was evaluated using the correlation coefficient (R2), mean square error (MSE), root means square error (RMSE), and mean absolute error (MAE). The analysis revealed that the sleeper’s body temperature closely follows the changing trend of the ambient environment. …”
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Insights into the contribution of multiple factors on Ixodes ricinus abundance across Europe spanning 20 years using different machine learning algorithms by Samantha Lansdell, Abin Zorto, Misaki Seto, Edessa Negera, Saeed Sharif, Sally Cutler

“…To assess which ML model was most suited to prediction of I. ricinus abundance, four performance metric values were calculated per model: Normalised Root Mean Square Error (NRMSE), Scatter Index (SI), Mean Absolute Percentage Error (MAPE) and R2, all of which describe the statistical relationship between predicted and actual I. ricinus abundance values. …”
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Preoperative prediction of multiple biological characteristics in colorectal cancer using MRI and machine learning by Qiao-yi Huang, Hui-da Zheng, Bin Xiong, Qi-ming Huang, Kai Ye, Shu Lin, Jian-hua Xu

“…We employed Spearman's rank correlation coefficient, greedy recursive deletion strategy, minimum redundancy, maximum relevance, least absolute shrinkage, and selection operator regression were utilized to screen for radiological features. …”
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