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  1. 1901

    Influence of Migratory Strategy, Group Size, and Environmental Conditions on the Movements of Caribou in Eastern Alaska by Kyle Joly

    Published 2025-05-01
    “…Migration is a diverse behavior exhibited by a wide array of organisms. Variability in the type of movements is rooted in their purpose, environmental factors, demographics, and individual physiological condition. …”
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    Article
  2. 1902

    Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

    Published 2024-11-01
    “…The proposed SHGWJA was tested very successfully in seven “real-world” engineering optimization problems taken from various fields, such as civil engineering, aeronautical engineering, mechanical engineering (included in the CEC 2020 test suite on real-world constrained optimization problems) and robotics; these problems include up to 14 optimization variables and 721 nonlinear constraints. Two representative mathematical optimization problems (i.e., Rosenbrock and Rastrigin functions) including up to 1000 variables were also solved. …”
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  3. 1903

    Effect of Pre-Trip Information in a Traffic Network with Stochastic Travel Conditions: Role of Risk Attitude by Yun Yu, Shiteng Zheng, Yuankai Li, Huaqing Liu, Jianan Cao

    Published 2025-05-01
    “…User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi></mrow></semantics></math></inline-formula>. …”
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  4. 1904

    Three-dimensional ultrasound for carotid vessel wall volume measurement by Ying-An Chen, Pei-Ya Chen, Shinn-Kuang Lin

    Published 2022-01-01
    “…Gray-scale 3D images from the distal common carotid artery (CCA) to internal carotid artery on both sides were acquired using a single-sweep 3D transducer and analyzed offline by using the vascular plaque quantification function of the Philips QLAB software. Then, the 3D IMT(QLAB intima–media thickness [QIMT]), total plaque volume (TPV), and VWV were measured by a neurologist and a technician, and the interobserver variability was assessed. …”
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  5. 1905

    Establishment of an evaluation system for conversion to laparotomy in laparoscopic cholecystectomy and exploration of surgical grading management by ZHANG Nannan, GUO Jinxing, WU Gang, YI Hui, ZHOU Yuanhang, LIAO Zhiwei, HUANG Qi, DONG Jian

    Published 2025-01-01
    “…Then, the risk factors were analyzed by multiple Logistic regression, and the pre-coefficient of each variable of the risk factors was assigned according to the established conversion to laparotomy possibility function. …”
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  6. 1906

    Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u<sub>t</sub></i> = (<i>K</i>(<i>u</i>)<i>u<sub>x</sub></i>)<i><sub>x</sub></i> by Winter Sinkala

    Published 2025-03-01
    “…In this paper, we revisit the group classification of the general nonlinear heat (or diffusion) equation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>u</mi><mi>t</mi></msub><mo>=</mo><msub><mfenced separators="" open="(" close=")"><mi>K</mi><mrow><mo>(</mo><mi>u</mi><mo>)</mo></mrow><mspace width="0.166667em"></mspace><msub><mi>u</mi><mi>x</mi></msub></mfenced><mi>x</mi></msub><mo>,</mo></mrow></semantics></math></inline-formula> where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> is a non-constant function of the dependent variable. We present the group classification framework, derive the determining equations for the coefficients of the infinitesimal generators of the admitted symmetry groups, and systematically solve for admissible forms of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>K</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula>. …”
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  7. 1907

    Evaluation of ChatGPT-4 as an Online Outpatient Assistant in Puerperal Mastitis Management: Content Analysis of an Observational Study by Fatih Dolu, Oğuzhan Fatih Ay, Aydın Hakan Kupeli, Enes Karademir, Muhammed Huseyin Büyükavcı

    Published 2025-07-01
    “…However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. …”
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    Article
  8. 1908

    Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow by Wenchao Cai, Yuan Gao, Xiping Zhang, Qin Si, Jiaoxin Jia, Bingzhen Li

    Published 2025-05-01
    “…By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. …”
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  9. 1909

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

    Published 2025-01-01
    “…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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  10. 1910

    A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Türkiye by Ulubey Çeken, Fadime Sertçelik, Abdullah İçen

    Published 2025-03-01
    “…Additionally, a heteroscedastic model was created for aleatory variability as a function of <i>M<sub>W</sub></i>. The closest distance to the surface projection of the fault plane (<i>R<sub>JB</sub></i>) is between 0 and 350 km. …”
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  11. 1911

    The potential habitat of Phlomoides rotata in Tibet was based on an optimized MaxEnt model by Jun-Wei Wang, Jun-Wei Wang, Min Xu, Norbu Ngawang, Yonghao Chen, Ngawang Bonjor, Xiaoyan Jia, Zhefei Zeng, Zhefei Zeng, La Qiong, La Qiong

    Published 2025-06-01
    “…IntroductionPhlomoides rotata, an important Tibetan medicinal plant, has garnered significant attention due to its remarkable medicinal value and ecological functions. However, overharvesting and climate change have progressively reduced its distribution range, threatening its survival.MethodsThis study employed an optimized MaxEnt model, integrating field survey data and multiple environmental variables, to predict and analyze the potential suitable distribution of P. rotata in Tibet.ResultsThe model achieved high predictive accuracy, with Ture skill statistic (TSS) = 0.87 and Cohen’s Kappa Coefficient (Kappa) = 0.81. …”
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  12. 1912
  13. 1913

    Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

    Published 2025-02-01
    “…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. …”
    Article
  14. 1914

    Investigating the relationship between the monetary policy shock through the exchange rate channel on the management quality index in the banking system: by examining the productiv... by Farhad Sharifi Bagha, Jafar Haqiqat, Zahra Karimi Takanloo

    Published 2025-03-01
    “…During this time, the number of changes in the target variables by the variables themselves decreases and the changes in the variables caused by the shock of the exchange rate channel increase. …”
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  15. 1915

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

    Published 2025-06-01
    “…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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  16. 1916

    The Effectiveness of Using the Reggio Emilia Approach on the Experimental Science Lesson for Third-Grade Elementary Students by Batool Sabzeh, Farangis Ghalavand, Seyedamir Ghasemtabar

    Published 2024-03-01
    “…Results of the normality test for the research variables (level 1, 2, and 3 science learning) in third-grade students indicated that all variables, both pre-test and post-test, met the assumption of normality, with significance levels greater than 0.05. …”
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  17. 1917

    Crisis Communication About the Maui Wildfires on TikTok: Content Analysis of Engagement With Maui Wildfire–Related Posts Over 1 Year by Jim P Stimpson, Aditi Srivastava, Ketan Tamirisa, Joseph Keaweʻaimoku Kaholokula, Alexander N Ortega

    Published 2025-03-01
    “…Using TikTok’s search functionality, we identified and reviewed public posts that contained relevant hashtags. …”
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  18. 1918

    Engineering safe anti-CD19-CD28ζ CAR T cells with CD8a hinge domain in serum-free media for adoptive immunotherapy by Muthuganesh Muthuvel, Muthuganesh Muthuvel, Thamizhselvi Ganapathy, Trent Spencer, Sunil S. Raikar, Saravanabhavan Thangavel, Alok Srivastava, Alok Srivastava, Alok Srivastava, Sunil Martin

    Published 2025-05-01
    “…CARs are modular synthetic antigen receptors integrating the single-chain variable fragment (scFv) of an immunoglobulin molecule to the TCR signaling. …”
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  19. 1919

    Deep Learning Approaches for Morphological Classification of Intestinal Organoids by Giovanni Cicceri, Sebastiano Di Bella, Simone Di Franco, Giorgio Stassi, Matilde Todaro, Salvatore Vitabile

    Published 2025-01-01
    “…The use of deep learning (DL) in organoid image analysis becomes crucial to handle complexity, variability, and large amounts of data efficiently and accurately, overcoming the limitations of traditional image processing approaches. …”
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  20. 1920

    Application of machine learning algorithms for predicting the life-long physiological effects of zinc oxide Micro/Nano particles on Carum copticum by Maryam Mazaheri-Tirani, Soleyman Dayani, Majid Iranpour Mobarakeh

    Published 2024-10-01
    “…All ML algorithms showed varied efficiencies in predicting the nonlinear relationships among parameters, with higher efficiency in predicting the behavior of root and shoot dry mass, root fresh weight and number of flowers according to R2 index. …”
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