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  1. 20821

    Scalar Field Kantowski–Sachs Solutions in Teleparallel <i>F</i>(<i>T</i>) Gravity by Alexandre Landry

    Published 2025-01-01
    “…We find a general formula allowing us to compute all possible new teleparallel <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>F</mi><mo>(</mo><mi>T</mi><mo>)</mo></mrow></semantics></math></inline-formula> solutions applicable for any scalar field potential and ansatz. …”
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  2. 20822

    Phase angle in bioelectrical impedance analysis for assessing congestion in acute heart failure. by Sangho Sohn, Jinsung Jeon, Ji Eun Lee, Soo Hyung Park, Dong Oh Kang, Eun Jin Park, Dae-In Lee, Jah Yeon Choi, Seung Young Roh, Jin Oh Na, Cheol Ung Choi, Jin Won Kim, Seung Woon Rha, Chang Gyu Park, Sunki Lee, Eung Ju Kim

    Published 2025-01-01
    “…<h4>Methods</h4>PhA was measured in 50 patients with HF and 20 non-HF controls along with the edema index (EI), another BIA parameter suggestive of edema. Chest computed tomography-measured lung fluid content (LFC) was used to assess pulmonary congestion. …”
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  3. 20823

    The analysis of the notions of Russian school principals about digital transformation by A. A. Deryabin, I. E. Boytsov, A. A. Popov, P. D. Rabinovich, K. E. Zavedensky, I. S. Tsarkov

    Published 2021-12-01
    “…The authors analysed 7189 questionnaires using computer methods for processing the natural language. …”
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  4. 20824

    Baska Mask versus I-gel in Spontaneously Breathing Anaesthetised Patients: A Randomised Clinical Study by Bhagyavardhan Botta, Yogarajan Ramalingam, Grishma Robba, Tanya Elizabeth, Kala Balasubramanian, Selvamani Subramanian, Senthil Kumar Vannivedu Santhnam, Kavyasri Morampudi

    Published 2025-01-01
    “…These patients were randomly assigned to either the Baska group (Group B) or the I-gel group (Group I) using computer-generated random numbers. Both groups were compared with respect to airway pressure, sealing pressure, ease of insertion of the device, number of attempts to insert, haemodynamic changes during and after insertion, and any complications. …”
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  5. 20825

    Cardiovascular Disease Screening in Primary School Children by Alena Bagkaki, Fragiskos Parthenakis, Gregory Chlouverakis, Emmanouil Galanakis, Ioannis Germanakis

    Published 2024-12-01
    “…Further study is needed regarding performance of individual components, accuracy of interpretation (including computer assisted diagnosis) and cost-effectiveness, before large-scale application of CVD screening in unselected pediatric populations.…”
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  6. 20826

    Assessment Of Heavy Metals Concentration and Pollution Indices Of Surface Water In Enerhen River, Warri South LGA, Delta State, Nigeria by A. O. Egai, M. Paaru

    Published 2025-02-01
    “…Data obtained show that the result indicated the concentration of Zinc 0.065mg/l - 0.190mg/l, Pb (0.003mg/l -0.142mg/l), Cu (0.081mg/l - 0.213mg/l), Cd (0.02mg/l - 0.282mg/l, Cr (0.041mg/l - 0.171mg/l), Fe (0.162mg/l - 0.278mg/l) and Ni (0.104mg/l - 0.762mg/l)  comparison with WHO 2012 permissible limit the probed water sample falls within the allowable concentration of the standard except the  concentration of lead (Pb) in SW1, SW2, SW4 and SW5 which is a  concern because it exceeded the allowable limit, lead is considered toxic to human at higher concentrations . The computed indices for the maximum admissible concentration upper permissible values buttress as follows Zn 0.3MAC, Pb 0.01MAC, Cu 2MAC, Cd 0.01MAC, Cr 0.05MAC, Fe, 0.3MAC and Ni 0.02MAC. …”
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  7. 20827

    CT-based skeletal muscle loss predicts long term prognosis in patients with distal cholangiocarcinoma undergone pancreaticoduodenectomy by Guangzhen Qu, Shao-Cheng Lyu, Yong Zhang, Kun Gao, Chuanguo Zhou

    Published 2025-01-01
    “…The cross-sectional images of skeletal muscle area at the level of the third lumbar spine was obtained based on computed tomography (CT), and the SMI was calculated by skeletal muscle mass through height squared normalization. …”
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  8. 20828

    Connective tissue disease-associated interstitial lung disease – A multicenter observational study from India by Sham Santhanam, Pravin Patil, Mohit Goyal, C B Mithun, Parthajit Das, Kavitha Mohanasundaram, Neeraj Jain, Vijaya Prasanna, Keerthi Talari, Himanshu Pathak, Parshant Aggarwal, Deepika Ponnuru, Vikram Raj Jain, Sharath Kumar

    Published 2021-01-01
    “…In our cohort, 372 (60%) patients had not received a diagnosis of their rheumatic disease or the ILD before seeing their rheumatologist. High-resolution computed tomography of the chest was available for 551 (88.9%) of the patients, and 327 (59.3%) had a nonspecific interstitial pneumonitis (NSIP) pattern. …”
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  9. 20829

    Fibroblast growth factor receptor 3 mutation promotes HSPB6-mediated cuproptosis in hypochondroplasia by impairing chondrocyte autophagy by Jing Chen, Dan He, Chengrun Yuan, Na Li, Baohong Shi, Conway Niu, Jiangfei Yang, Liangkai Zheng, Lin Che, Ren Xu

    Published 2025-03-01
    “…Radiography and micro-computed tomography were employed to assess the bone-specific phenotype in Fgfr3 (V376D)mutant mice. …”
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  10. 20830

    Facial Anthropometry and Self-expressed Behaviours: A Systematic Review by Ankit Srivastava, Vilas Chimurkar, Nisha Mani Pandey, Anand Bihari

    Published 2025-01-01
    “…The findings of present review provide new insights for future research in the fields of behavioural medicine and computational face recognition.…”
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  11. 20831

    Safety and Feasibility of Transanal Endoscopic Surgery for Diffuse Cavernous Hemangioma of the Rectum by Ziwei Zeng, Xianrui Wu, Junji Chen, Shuangling Luo, Yujie Hou, Liang Kang

    Published 2019-01-01
    “…The level of hemoglobin at admission ranged from 59.0 to 148.0 g/l (mean 106.6 g/l), and the level of mean corpuscular volume (MCV) ranged from 75.1 fl to 93.5 fl (mean 83.7 fl). Colonoscopy, computed tomography (CT), and magnetic resonance imaging (MRI) were important in the diagnosis of DCHR because of their high positive rates and accurate features. …”
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  12. 20832

    Novel Pythagorean fuzzy score function to optimize fuzzy transportation models by Ritu, Tarun Kumar, Jahnvi, Kapil Kumar, Nitesh Dhiman, M.K. Sharma

    Published 2025-03-01
    “…Also, the proposed score function integrates these interval values to quantify and rank the alternatives more effectively.However, a notable trade-off is the increased computational complexity due to the use of interval values in the membership and non-membership functions, particularly in larger-scale transportation problems. …”
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  13. 20833

    Smartphone applications for physical activity and sedentary behaviour change in people with cardiovascular disease: A systematic review and meta-analysis. by Kacie Patterson, Rachel Davey, Richard Keegan, Nicole Freene

    Published 2021-01-01
    “…Cardiovascular disease secondary prevention physical activity or sedentary behaviour interventions were included where the primary element was a smartphone or tablet computer application (excluding SMS-only text-messaging). …”
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  14. 20834

    Bifurcation analysis of multistability and hysteresis in a model of HIV infection by I. V. Mironov, M. Yu. Khristichenk, Yu. M. Nechepurenko, D. S. Grebennikov, G. A. Bocharov

    Published 2023-12-01
    “…To this end, original computational methods of bifurcation analysis of mathematical models formulated with systems of ordinary differential equations and delay differential equations are used. …”
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  15. 20835

    Role of Chest X-Ray in Coronavirus Disease and Correlation of Radiological Features with Clinical Outcomes in Indian Patients by Satyanand Sathi, Richa Tiwari, Savita Verma, Anil Kumar Garg, Virendra Singh Saini, Manoj Kumar Singh, Amit Mittal, Devinder Vohra

    Published 2021-01-01
    “…Recent literature has reported that radiological features of coronavirus disease (COVID-19) patients are influenced by computed tomography. This study aimed to assess the characteristic chest X-ray features of COVID-19 and correlate them with clinical outcomes of patients. …”
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  16. 20836

    Distinguishing Compact Objects in Extreme-Mass-Ratio Inspirals by Gravitational Waves by Lujia Xu, Shucheng Yang, Wenbiao Han, Xingyu Zhong, Rundong Tang, Yuanhao Zhang

    Published 2025-01-01
    “…Assuming the “true” GW signals originate from an extended body inspiraling into a supermassive black hole, we compute the signal-to-noise ratio (SNR) and Bayes factors between a test-particle waveform template and our model, which includes the spin and quadrupole of the compact object. …”
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  17. 20837

    Biologic Cost per Effectively Treated Rheumatoid Arthritis Patient in a Large Managed Care Population: A Retrospective Cohort Study by Tao Gu, Neel Shah, Gaurav Deshpande, Derek H. Tang, Debra F. Eisenberg, David J. Harrison

    Published 2015-09-01
    “…**Objectives:** To implement a validated claims-based effectiveness algorithm in a US managed care claims database to compute the 1-year biologic cost per effectively treated patient among first-line biologics approved for moderate-to-severe RA (abatacept, adalimumab, certolizumab pegol, etanercept, golimumab, and infliximab). …”
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  18. 20838

    Effects of a periodic intermittent theta burst stimulation in Alzheimer’s disease by Yue Wu, Lu Wang, Kai Wang, Shanshan Zhou, Pan Wu, Yibing Yan, Ling Wei, Bensheng Qiu, Yanghua Tian, Zhi Geng, Xingqi Wu, Panpan Hu, Guixian Xiao, Gongjun Ji, Hesheng Liu

    Published 2024-02-01
    “…The longitudinal pipeline of the Computational Anatomy Toolbox for SPM was used to detect significant treatment-related changes over time.Results The iTBS group maintained MoCA scores relative to the control group (t=3.26, p=0.013) and reduced hippocampal atrophy, which was significantly correlated with global degeneration scale changes. …”
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  19. 20839

    Enhancing Semi-Supervised Learning With Concept Drift Detection and Self-Training: A Study on Classifier Diversity and Performance by Jose L. M. Perez, Roberto S. M. Barros, Silas G. T. C. Santos

    Published 2025-01-01
    “…Semi-supervised classifiers often consume a lot of memory and run-time, and the addition of a detection mechanism increases the computational cost. Furthermore, classification in semi-supervised environments can lead to problems related to labeling data to training: an error in this process can negatively impact model performance. …”
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  20. 20840

    Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models by Sollmann, Rahel

    Published 2024-01-01
    “…Ignoring temporal variation allows collapsing detection data across repeated sampling occasions, speeding up computations, which can be important when analyzing large datasets with complex models. …”
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