PREDICTION OF VERTICAL IMPACTION OF LOWER WISDOM TOOTH ACCORDING ORTHOPANTOMOGRAPHY OF LOWER JAW by A.M. Hohol, A.I. Pankevych, I.A. Kolisnyk, D.S. Machulenko, Ya.A. Hohol

“…To predict the nature of the impaction of the third lower molars, the authors provide indicators of the angle of the tooth, the structure of their roots, the degree of impact and age of the patient. …”
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Predicting OSA Using Radiographs of the Airway Anatomy by Du M, Gui Y, Guo Y, Liu J, Deng W, Huang J, Liu T, Zhang X, Pang F

“…The correlation between the Apnea-Hypopnea Index (AHI) and these upper airway anatomical factors was analyzed using both univariate and multivariate analyses to develop a predictive model for OSA.Results: The anatomical structure of the upper airway in patients with OSA is narrower compared to non-OSA individuals, and these patients exhibit a longer and thicker tongue. …”
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Breast cancer is a threatening scenario resulting from the development of endometriosis and benign breast disease overlap syndrome: literature review by T.A. Lunko, O.O. Lytvynenko, A.S. Lunko, S.V. Konovalenko, A.V. Khmel

“…According to the National Cancer Registry of Ukraine, mortality from breast cancer (BC) continues to be at the first places in the structure of oncological pathology among the female population. …”
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Development of a formative index for precarious employment in Denmark by Per Høgh Poulsen, Jesper Medom Vestergaard, Trine Nøhr Winding, Karin Biering, Johan Hviid Andersen, Rasmus Juul Møberg

“…Exploratory factor analysis was conducted to explore factor structure of the PE Index. To assess reliability and inter-item correlation of the individual dimensions, Cronbach's Alpha and Kendall's Tau were applied. …”
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Application of artificial muscle e-rubber for healthcare sensing: verification of measurement properties as a smart insole by Hidemasa Yoneda, Hidemasa Yoneda, Takashi Yamaga, Takeshi Fujiwara, Yoko Komori, Masatoshi Shimada, Yuki Kato, Shintaro Oyama, Shingo Shimoda, Michiro Yamamoto, Hitoshi Hirata

“…However, for the sensor embedded within the insole housing, the coefficient of variation increased to less than 8%, and the confidence interval was 1.5%, likely owing to the influence of gaps within the insole structure. Regarding the load estimation equation, a 5th-order polynomial approximation (R2 >0.999) demonstrated the best fit, indicating that it is sufficiently accurate for healthcare sensing applications. …”
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Identification of genetic determinants of antibiotic resistance in Helicobacter pylori isolates in Vietnam by high-throughput sequencing by Phuc Hoang Bui, Trang Ngoc Minh Cao, Thanh Truc Tran, Takashi Matsumoto, Junko Akada, Yoshio Yamaoka

“…In addition, a genome-wide association study (GWAS) and linear mixed model were used to identify genetic variants associated with antimicrobial resistance phenotypes while adjusting for covariates such as population structure. …”
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Quantifying hygroscopic deformation in lignocellulosic tissues: a digital volume correlation tool comparison by Kim Ulrich, Kim Ulrich, Fabian Scheckenbach, Tak Ming Wong, Tak Ming Wong, Tom Masselter, Silja Flenner, Anaclara Visconti, Anaclara Visconti, Anaclara Visconti, Martin Nopens, Andreas Krause, Sergej Kaschuro, Jakob Benedikt Mietner, Thomas Speck, Thomas Speck, Imke Greving, Berit Zeller-Plumhoff, Berit Zeller-Plumhoff, Linnea Hesse, Linnea Hesse

“…In addition, the abundance of structural features in the cell walls leads to an improved DVC accuracy. …”
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Socio‐ecological correlates of wildlife species identification across rural communities in northern Tanzania by Justin Raycraft, Reilly Becchina, Danielle Bettermann, Stephen Koester, Elana Kriegel, Kiana Lindsay, Edwin Maingo Ole, Emily Ramirez, Bryan Spizuco, Christian Kiffner

“…We showed photographs of 17 mammal species to participants and assessed species identification ability. Using a generalized linear mixed model within a Bayesian framework that accommodated the hierarchical data structure and non‐independence of the data, we tested specific hypotheses regarding the correlations of species identification accuracy with human demographic (ethnicity, education, age, wealth, gender), geographic (Human Footprint Index [HFI], distance to protected areas, district) and species‐specific (conservation status, activity patterns, body mass, diet) variables. …”
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The influence of socioeconomic factors on the knowledge of reptiles and mammals in the Lençóis Maranhenses National Park, Northeast Brazil by Pedro Victor Cardoso dos Santos, Felipe Silva Ferreira, Samuel Vieira Brito

“…Data were collected through semi-structured questionnaires and open-ended interviews, resulting in records of 36 species (plus 6 identified only at genus level) in 33 families and 10 orders, of which 53% were non-avian reptile and 47% mammals. …”
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An examination of the relationship between self-confidence and bullying among adolescent athletes and non-athletes by Satmyrza Mamikov, Ainur Abdullayeva

“…Methodology: a quantitative cross-sectional study was conducted with 300 adolescents, categorized as athletes and non-athletes. participants completed a structured questionnaire on bullying and self-confidence. analyses included logistic regression, Chi-square tests, One-way ANOVA, MANOVA, and multiple linear regression for moderation effects. …”
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Analyzing Uncertainty and Hesitation in Refereeing Decision using Neutrosophic Vague N-Soft Sets: A Case Study of Officiating Ability Evaluation for National-Level Volleyball Refer... by Haikui Zhou, Xiang Zhong

“…Our framework integrated expert linguistic evaluations across multiple criteria into a structured NVNSS decision matrix. Then, we propose a risk-aware degree of support to quantify each referee’s performance under uncertainty, followed by a discrete rating assignment. …”
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The statistical relationship between sweet consumption and academic achievement among Palestinian university students: a cross-sectional study by Inad Nawajah

“…Data on academic performance (self-reported GPA), sweet consumption frequency, and potential confounders (demographics, BMI, parental education, income, breakfast consumption, physical activity, and mental health via the Strengths and Difficulties Questionnaire) were collected using structured questionnaires. Multiple linear regression models were used to assess associations. …”
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Optical neuromorphic computing via temporal up-sampling and trainable encoding on a telecom device platform by Manuylovich Egor, Stoliarov Dmitrii, Saad David, Turitsyn Sergei K.

“…Our up-sampling approach utilizes a trainable encoding mask, where each input symbol is replaced with a structured sequence of masked symbols, effectively increasing the representational capacity of the feature space. …”
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A New Technique to Solve Game Matrix with Neutrosophic Payoffs by Jitendra Singh, Ritika Chopra, Ratnesh R. Saxena, Pankaj Kumar Garg

“…This article develops a more structured technique to solve neutrosophic game matrix with payoffs as Single Valued Trapezoidal Neutrosophic (SVTrN) numbers. …”
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The impact of fall armyworm on subsistence farmers in the Limpopo Province of South Africa by Tlou D. Raphela, M. Mafadza

“…Lastly, the study assessed the impact of the fall armyworms on the food security of the farmers and their families. The study used a structured questionnaire to collect the data and applied several Generalized Linear Models (GLMs) and one ordinal Regression to analyse the data for this study with a sample size of 82. …”
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Low-Rank Kernel-Based Semisupervised Discriminant Analysis by Baokai Zu, Kewen Xia, Shuidong Dai, Nelofar Aslam

“…Semisupervised Discriminant Analysis (SDA) aims at dimensionality reduction with both limited labeled data and copious unlabeled data, but it may fail to discover the intrinsic geometry structure when the data manifold is highly nonlinear. …”
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Spatial patterns and key driving factors of wheat harvest index under irrigation and rainfed conditions in arid regions by Yongyu Chen, Yongyu Chen, Hengbati Wutanbieke, Dongdong Zhong, Dongdong Zhong, Jian Chen, Jian Chen, Zhen Huo, Zhen Huo, Hegan Dong, Hegan Dong

“…By integrating multidimensional factors such as geographical and climatic conditions, agronomic management practices, and soil nutrient status, methods including correlation analysis, random forest models, structural equation modeling, and linear regression analysis were employed to systematically investigate the spatial distribution characteristics and driving mechanisms of wheat HI under different irrigation regimes in arid regions.ResultsThe results revealed that: (1) Wheat HI in arid regions exhibited significant spatial heterogeneity (0.43–0.67), with an overall distribution pattern of "central high, peripheral low" and "northern high, southern low." (2) The importance rankings of influencing factors differed between irrigation regimes. …”
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Assessing the quality of gynaecological care in China: protocol for a nationwide survey using mixed-methods by Jing Ma, Yuanli Liu, Hua Yang, Guangyu Hu, Lan Zhu, Fengxia Xue, Pengming Sun, Chenyang Pei, Xiangyu Gu, Zixuan Fan

“…The study collects data on organisational structure, care processes and outcomes. Analysis of quantitative data will include risk adjustment of key quality indicators, comprehensive evaluation of care quality and exploration of influencing factors using linear regression. …”
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Whole-Genome Resequencing to Identify Selection Signatures Associated with High Fertility in Lüliang Black Goat by Xu Wang, Zhenqi Zhou, Xinrui Chai, Jie Li, Wannian Wang, Zhixu Pang, Lifen Cheng, Caihong Cheng, Liying Qiao, Yangyang Pan, Kaijie Yang, Wenzhong Liu, Jianhua Liu

“…Based on whole-genome resequencing data, this study comprehensively assessed the population structure and genetic diversity of LBG and explored the related genes that affect reproductive performance. …”
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How Public School Districts’ Characteristics Relate to Their Students’ Postsecondary Intentions by Cassie L. Barnhardt, Nicole Tennessen, Jeff Ching-Fan Lai, Sameer Ali, Brian An, Man Phan, Erin Bovid, Bridget A. Wright

“…To explore this topic, we utilize census, population-level data associated with all Iowa public school districts for a period of three academic years using a series of linear regression models. Findings emphasize the importance of the disciplinary climate in the overall climate of the district as an important factor that contributes to structuring students’ future intentions, with added nuance related to the total enrollment or size of the district.…”
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