Quantitative comparison between single-photon emission computed tomography and positron emission tomography imaging of lung ventilation with 99mTc-technegas and 68Ga-gallgas in pat... by Enrique Gustavo Cuna, Juan Pablo Gambini, Liliana Servente, Eduardo Savio, Henry William Engler, Gabriel Adrián González, Omar Alonso

“…The aim of this study was quantitative comparison between 68Ga-Gallgas positron emission tomography (PET) and 99mTc-Technegas single photon emission computed tomography (SPECT) for lung ventilation function assessment in patients with moderate-to-severe obstructive pulmonary disease and to identify image-derived texture features correlating to the physiologic parameters. …”
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Strong Amplitude Modulation of Hard-band X-Ray Quasiperiodic Oscillation with Soft-band Flux in RE J1034+396 by Ruisong Xia, Hao Liu, Yongquan Xue

“…They are highly correlated, with an average cross-correlation function (CCF) peak coefficient of 0.61 and a lag of approximately 3 ks. …”
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Impact of Body Image Perception on Behavioral Outcomes in Chinese Adolescent and Young Adult Survivors of Sarcoma by Yihui Wei, Chung Tin Ma, Michael Can Heng Li, Keary Rui Zhou, Herbert Ho Fung Loong, Kwok Chuen Wong, Chi Kong Li, Yin Ting Cheung

“…The significant risk factors associated with body image dissatisfaction were being female (standardized coefficient estimate [Est] = 0.21, SE = 0.10; p = 0.047), surgery treatment (Est = 0.19, SE = 0.09; p = 0.046), and worse family functioning (Est = 0.27, SE = 0.10, p = 0.013). …”
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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

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

“…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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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

“…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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Revisiting the Group Classification of the General Nonlinear Heat Equation <i>u_t</i> = (<i>K</i>(<i>u</i>)<i>u_x</i>)<i>_x</i> by Winter Sinkala

“…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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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

“…However, evaluator variability and the subjective nature of assessments highlight the need for further optimization of AI tools. …”
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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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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

“…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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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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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

“…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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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

“…Using TikTok’s search functionality, we identified and reviewed public posts that contained relevant hashtags. …”
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Association between TSH Values and GFR Levels in Euthyroid Cases with Metabolic Syndrome by H. Keskin, K. Cadirci, K. Gungor, T. Karaaslan, T. Usta, A. Ozkeskin, A. Musayeva, F. Yesildal, F. Isman, H. Y. Zengin

“…Partial correlation coefficients were calculated to investigate the relationship between the eGFR values and several other numerical variables while controlling for age and BMI in addition to the adjusted gender effect. …”
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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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Research on the Combined Load-Bearing Mechanism of Deeply Buried Pressure Pipelines Under High Internal Water Pressure by LIU Yijie, ZHANG Xuhui, HUANG Bensheng, YANG Fengjie, YUAN Mingdao, XU Yunqian

“…To enhance the surrounding rock’s contribution, reinforcement measures such as grouting may be necessary.ConclusionsAiming at the calculation problem of load transfer and distribution in deep-buried pressure pipelines under high internal water pressure conditions, a power series solution method based on complex variable functions was proposed. By solving the potential functions for the steel liner and surrounding rock as well as the contact stress between the bearing bodies, the stress, deformation at any position of the bearing structure and surrounding rock sharing rate can be accurately determined. …”
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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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Detecting and reducing heterogeneity of error in acoustic classification by Oliver C. Metcalf, Jos Barlow, Yves Bas, Erika Berenguer, Christian Devenish, Filipe França, Stuart Marsden, Charlotte Smith, Alexander C. Lees

“…We recommend assessing—and if necessary correcting for—heterogeneity of precision error when using automated classification on acoustic data to quantify species presence as a function of an environmental, spatial or temporal predictor variable.…”
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