Validation of an interferon-gamma enzyme-linked immunosorbent spot assay to evaluate cell-mediated immunity against severe acute respiratory syndrome coronavirus 2 by Yunhwa Kim, Eun-Jeong Jang, Ji-Young Hwang, Kyung-Min Lee, Sivilay Xayaheuang, Seok-Tae Choi, Hosun Park

“…Taken together, we demonstrated that the IFN-γ ELISpot assay is feasible for evaluating SARS-CoV-2-specific cell-mediated immune function through validation based on standard operating procedures.…”
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Data-driven modeling and regression analysis on ship resistance of in-service performance by Daehyuk Kim, Shin Hyung Rhee

“…The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We investigated the impact of using different feature extraction (spectro‐temporal measurements, linear and Mel‐frequency cepstral coefficients (MFCC), as well as highly comparative time‐series analysis) and classification methods (discriminant function analysis, neural networks, random forests (RF), and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. …”
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Toward generalizable prediction of antibody thermostability using machine learning on sequence and structure features by Ameya Harmalkar, Roshan Rao, Yuxuan Richard Xie, Jonas Honer, Wibke Deisting, Jonas Anlahr, Anja Hoenig, Julia Czwikla, Eva Sienz-Widmann, Doris Rau, Austin J. Rice, Timothy P. Riley, Danqing Li, Hannah B. Catterall, Christine E. Tinberg, Jeffrey J. Gray, Kathy Y. Wei

“…In this work, we show two machine learning approaches – one with pre-trained language models (PTLM) capturing functional effects of sequence variation, and second, a supervised convolutional neural network (CNN) trained with Rosetta energetic features – to better classify thermostable scFv variants from sequence. …”
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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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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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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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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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High expression of SOX10 is correlated with poor prognosis and immune infiltrates in skin cutaneous melanoma by Xu Sun, Yi-ming Cheng, Meng-wei Sun, Xu-dong Zhang, Xiao-yu Yu, Hai-bo Wang, Yi-fei Wang, Ning Li

“…Screening was performed by LASSO coefficients to select non-zero variables that satisfied the coefficients of lambda, and 8 genes were screened out. …”
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Multidimensional analysis of sedentary behaviour and participation in Spanish stroke survivors (Part&Sed-Stroke): a protocol for a longitudinal multicentre study by Pablo Bellosta-Lopez, Victor Domenech-Garcia, Maria Pilar López-Royo, Javier Gueita-Rodriguez, Jorge Alegre-Ayala, Julia Blasco-Abadía, Cristina de Diego-Alonso, Almudena Buesa, Patricia Roldán-Pérez, Rafael Giner-Nicolás, Natalie Ann Fini, Alicia Tornero Navarro, Ana Conte Lamenca, Andrea Yerro Astrain, Beatriz Martín Lamata, Carina Salgueiro, Claudia Marín Marín, Diana Ruiz Ramos, Elena Sanz Sanza, Enrique Villa Berges, Fernando Cuesta Ruiz, Inés Cortés Cabeza, Javier Harguindey, Juan Luis Abeledo Alcón, Laura Ares Barge, Leyre Leceaga Gaztambide, Lilian Le Roux, Lourdes Martín Gros, Lucía Díez Fuentes, María Carmen Grácia Sen, María Pilar Pardo Sanz, Paloma Rodríguez Escudero, Paz Cristina Sánchez Lecina, Rebeca Yebra Vilarchao, Sara Beltrán Roche, Verónica Montoya Murillo

“…Introduction Stroke survivors usually experience long-lasting functional, emotional and social consequences that might contribute to sedentary behaviour and participation restrictions, which are important targets to address during rehabilitation. …”
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Impact of short-term aircraft noise on cardiovascular disease risk in the area surrounding London Heathrow airport: the RISTANCO epidemiological study by Xiangpu Gong, Nicole Itzkowitz, Calvin Jephcote, Kathryn Adams, Glory O Atilola, John Gulliver, Marta Blangiardo, Anna Hansell

“…To identify areas with high variability in aircraft noise exposure (due to changes in flight paths because of wind direction and airport operations), we used coefficients of variation (CoV). …”
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TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluat... by S. Schmitt, S. Schmitt, S. Schmitt, F. J. Fischer, J. G. C. Ball, N. Barbier, M. Boisseaux, D. Bonal, B. Burban, X. Chen, G. Derroire, G. Derroire, G. Derroire, J. W. Lichstein, D. Nemetschek, N. Restrepo-Coupe, S. Saleska, G. Sellan, P. Verley, G. Vincent, C. Ziegler, J. Chave, I. Maréchaux

“…The simulated canopy height distribution showed a high correlation coefficient (CC) with observed aerial and satellite data (CC <span class="inline-formula">&gt;</span> 0.92), while the species and functional composition were well represented (CC <span class="inline-formula">&gt;</span> 0.75). …”
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Characterizing Performance on a Suite of English-Language NeuroUX Mobile Cognitive Tests in a US Adult Sample: Ecological Momentary Cognitive Testing Study by Emily W Paolillo, Jessica Bomyea, Colin A Depp, Ashley M Henneghan, Anunay Raj, Raeanne C Moore

“…The tests tapped the domains of executive function, processing speed, reaction time, recognition memory, and working memory. …”
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Skin hyperspectral imaging and machine learning to accurately predict the muscular poly-unsaturated fatty acids contents in fish by Yi-Ming Cao, Yan Zhang, Qi Wang, Ran Zhao, Mingxi Hou, Shuang-Ting Yu, Kai-Kuo Wang, Ying-Jie Chen, Xiao-Qing Sun, Shijing Liu, Jiong-Tang Li

“…With the skin spectra of fish, five ML methods, including the extreme learning machine (ELM), random forest (RF), radial basis function (RBF), back propagation (BP), and least squares support vector machine (LS-SVM) methods, were used to predict the PUFAs and EPA + DHA contents. …”
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Correlation of Immune Parameters in Breast Cancer Patients Undergoing General Anesthesia: post-hoc Analysis of the TeMP Study by Kristina K. Kadantseva, Valery V. Subbotin, Mikhail Y. Yadgarov, Elizaveta M. Korolenok, Levan B. Berikashvili, Roman A. Akchulpanov, Nikolay S. Karnaukhov, Ksenia S. Korchagina, Polina I. Kukina, Oksana A. Svitich, Artem N. Kuzovlev, Anna S. Barmina, Valery V. Likhvantsev

“…Spearman correlation coefficients and heat maps were used for analysis.Results. …”
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Feasibility of in vivo small animal imaging using a clinical total-body PET/CT system by Julia G. Mannheim, Wenhong Lan, Maurizio Conti, Franziska Siedler, Marcel A. Krueger, Kristina Herfert, Christian la Fougère, Fabian P. Schmidt

“…SUVmax values exhibited greater variability, with significant differences observed in muscle and brain regions. …”
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Randomized single-dose crossover comparative bioavailability study of two novel oral cannabidiol (CBD) formulations in healthy volunteers under fed conditions, compared to a standa... by Mehmet Nevzat Pisak, Edibe Bereket, Aydin Erenmemisoglu

“…The time to peak concentration (tmax) was shortest for the liquid (median ~ 1.0 h), followed by the capsule (2.0 h), and longest for the reference (6.0 h). Inter-individual variability in C_max and AUC was substantially lower for both novel formulations (coefficients of variation ~ 27–44%) than for the reference (> 90%). …”
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不同种群元宝枫种仁含油率及脂肪酸组成分析与评价Analysis and evaluation of oil content in seed kernel and fatty acid composition of Acer truncatum from different populations... by 韩旻昊1，2，燕丽萍1，王因花1，任飞1，梁燕1，仲伟国1，孙超1，吴德军1 HAN Minhao1,2, YAN Liping1, WANG Yinhua1, REN Fei1, LIANG Yan1, ZHONG Weiguo1, SUN Chao1, WU Dejun1

“…The average coefficients of variation of oil content in seed kernel and various main fatty acid from Haiyang, Shandong(12.59%), Tai′an, Shandong(11.22%) and Jinan, Shandong(10.36%) were higher. …”
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