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  1. 1661

    Factors affecting survival of adult female white‐tailed deer after coyote establishment in south Carolina by John C. Kilgo, Mark Vukovich, Michael J. Conroy, H. Scott Ray, Charles Ruth

    Published 2016-12-01
    “…Models assessing the effects of harvest and distance from a primary road also received support (ΔAICc < 2.0), but effects of these variables were weak. …”
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  2. 1662

    Development and Validation of a Nosocomial Infection Nomogram Model in the NICU: A Novel and Nurse-Led Way to Prediction in Preterm Infants by Shang Y, Chen L, Hu X, Zhang K, Cheng Q, Shui X, Deng Z

    Published 2025-01-01
    “…Yanyan Shang,&ast; Ling Chen,&ast; Xindie Hu, Keqian Zhang, Qian Cheng, Xiaoyu Shui, Zhiyue Deng Department of Neonatology, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhiyue Deng; Xiaoyu Shui, Department of Neonatology, Renmin Hospital of Wuhan University, Wuchang District, Jiefang Road, No. 99, Wuhan, Hubei, 430060, People’s Republic of China, Tel +86 18086403090, Email 2015302180361@whu.edu.cn; 15926276672@163.comPurpose: Nosocomial infections (NI) are a leading cause of mortality in preterm infants in the Neonatal Intensive Care Unit (NICU). …”
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  3. 1663
  4. 1664

    A Case-Control Study Exploring the Association Between Cosmetic Use and Acne Risk: Implications for Prevention and Clinical Practice by Choi K, Liu H, Zhu Y, Jiang Z, Lu S

    Published 2025-07-01
    “…Kitman Choi, Hsingmei Liu, Yingying Zhu, Zhuoyu Jiang, Sha Lu Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Sha Lu, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang Road West, Guangzhou, Guangdong, 510120, People’s Republic of China, Tel +86-020-81332199, Email lush7@mail.sysu.edu.cnBackground: Acne cosmetica refers to acne breakouts caused by cosmetics. …”
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  5. 1665

    Construction and Validation of a Nomogram-Based Predictive Model for Acute Kidney Injury Caused by Drug Resistance to Tuberculosis by Deng M, Han N, Jia M, Zheng Z, Tian Y, Wang H, Feng L

    Published 2025-07-01
    “…In this study, five variables (age, hypertension, diabetes, Scr, and ALB) were included to construct a nomogram for predicting AKI caused by drug resistance to TB. …”
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  6. 1666
  7. 1667
  8. 1668

    Causal Relationship Between Depression, Sleep Disorders, and Constipation: A Mendelian Randomization and Mediation Analysis by Wang JX, Wei KY, Lin W, Liu YJ

    Published 2025-07-01
    “…Additionally, the potential mediating effects of sleep disorders in the association between depression and constipation were evaluated.Methods: Genome-wide association study (GWAS) data were utilized to identify genetic variants associated with depression, sleep disorders, and constipation as instrumental variables (IVs). The inverse-variance weighted (IVW) method was applied as the primary analytical approach. …”
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  9. 1669

    The contribution of integrated and non-integrated pig farms to epidemiological dynamics of porcine reproductive and respiratory syndrome virus in Italy by M. Ustulin, D. Vio, C. Targhetta, C. Zanon, L. Ferino, G. Faustini, G. Franzo

    Published 2025-08-01
    “…Abstract Porcine reproductive and respiratory syndrome (PRRS) is a global challenge for swine production. Due to its high variability and limited cross-protection, immune-based control measures are only partially effective, emphasizing the critical role of biosecurity. …”
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  10. 1670

    Analysis of Prognostic Factors for Drilling Drainage Surgery in Patients with Hypertensive Intracerebral Hemorrhage and Development of a Predictive Nomogram by Gu J, Dai L, Hu W, Xie C, Ren X, Huang J

    Published 2025-04-01
    “…The established nomogram model based on these variables accurately predicts the risk of poor postoperative prognosis and can serve as an effective clinical reference tool.Keywords: hypertensive intracerebral hemorrhage, drilling drainage surgery, prognosis, influencing factors, nomogram…”
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  11. 1671
  12. 1672

    Utilizing Low-cost Mobile Monitoring to Estimate the PM2.5 Inhaled Dose in Urban Environment by Muhammad Miftahul Munir, Martin Adrian, Casmika Saputra, Puji Lestari

    Published 2022-04-01
    “…Statistical analysis shows that the on-road area (53 µg m−3) has higher PM2.5 concentration than residential area (41 µg m−3). …”
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  13. 1673
  14. 1674

    Developing a Small-Scale Experimental Method for Evaluating the Effectiveness of Soil Improvement Using Prefabricated Vertical Drains by Merley Misriani, Abdul Hakam, Joleha Joleha, Elianora Elianora, Eka Pebrilista Putri, Dodi Kifrah Hasian

    Published 2025-05-01
    “…Soil samples were collected from the Padang-Pekanbaru Toll Road construction site in West Sumatra, Indonesia. …”
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  15. 1675
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  17. 1677

    Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

    Published 2025-04-01
    “…Machine learning models achieve an average accuracy of 75–80%, providing strong performance, particularly in industries like road construction and healthcare. Regression models typically deliver 70–80% accuracy, being more suitable for simpler cost estimations where the relationships between variables are linear. …”
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  18. 1678
  19. 1679

    Construction and Verification of Risk Predictive Nomogram in Patients of Connective Tissue Disease with Severe Pneumonia by Zhang C, Zou Z

    Published 2025-06-01
    “…Area under the curve (AUC) of receiver operating characteristic (ROC) was used to evaluate the nomogram’s discrimination, and the calibration curve and Hosmer–Lemeshow test were used to reflect the nomogram’s calibration.Results: The study cohort was including 48 patients in the general pneumonia group and 32 patients in the severe pneumonia group. The model variables included Ln CD4/CD8, Ln CRP, Ln PCT and Ln IFN-γ. …”
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  20. 1680

    Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling by Nighat Perveen, Sabir B. Muzaffar, Areej Jaradat, Olivier A. Sparagano, Arve L. Willingham, Ala Tabor

    Published 2024-08-01
    “…Middle of the road scenario (ssp2-4.5) where CO2 levels remain similar to current levels, did not indicate a major change in the tick distributions. …”
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