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Dependences of longleaf pine(Pinus palustris) natural reproduction on environments above ground

Journal of Forestry Research 2014年第3期25卷 565-570页

作者： Qiuju Guo Dexiang Wang Xunru Ai Lan Yao College of Forestry and Horticulture Hubei University for Nationalities College of Forestry Northwest A&F University

We studied relations between natural seedling reproduction and above ground environment in a longleaf pine ecosystem. Forty-eight 0.05 ha circular plots were sampled under single-tree selection, group-tree selection and control stands in three main longleaf pine areas in south Alabama, USA. We measured six above-ground environment factors, viz. canopy closure, stand density, basal area, average tree height, understory cover and PAR under canopy. We employed forward, back-ward and stepwise selection regression to produce one model. Three main variables：canopy closure, stand density and basal area, were left in the model; light, PAR and understory cover were not incorporated into the model at the 0.10 significance level. Basal area was a positive pa-rameter, while canopy closure and stand density were negative parame-ters. Canopy closure was the main parameter in the model. The model proved to be meaningful, and has potential to provide useful guidance for future work.

关键词： seedling reproduction number selection regression analysis model

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Diagnostic value of preoperative examination for evaluating margin status in breast cancer

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World Journal of Clinical Cases 2023年第20期11卷 4852-4864页

作者： Peng Liu Ye Zhao Dong-Dong Rong Kai-Fu Li Ya-Jun Wang Jing Zhao Hua Kang Department of General Surgery Center for Thyroid and Breast SurgeryXuanwu HospitalCapital Medical UniversityBeijing 100053China Department of General Surgery Beijing Fengtai HospitalBeijing 100071China Department of Radiology Xuanwu HospitalCapital Medical UniversityBeijing 100053China

BACKGROUND A positive resection margin is a major risk factor for local breast cancer recurrence after breast-conserving surgery(BCS).Preoperative imaging examinations are frequently employed to assess the surgical *** To investigate the role and value of preoperative imaging examinations[magnetic resonance imaging(MRI),molybdenum target,and ultrasound]in evaluating margins for *** A retrospective study was conducted on 323 breast cancer patients who met the criteria for BCS and consented to the procedure from January 2014 to July *** study gathered preoperative imaging data(MRI,ultrasound,and molybdenum target examination)and intraoperative and postoperative pathological *** on their BCS outcomes,patients were categorized into positive and negative margin ***,the patients were randomly split into a training set(226 patients,approximately 70%)and a validation set(97 patients,approximately 30%).The imaging and pathological information was analyzed and summarized using R ***-conditional logistic regression and LASSO regression were conducted in the validation set to identify factors that might influence the failure of BCS.A column chart was generated and applied to the validation set to examine the relationship between pathological margin range and *** study aims to identify the risk factors associated with failure in *** The multivariate non-conditional logistic regression analysis demonstrated that various factors raise the risk of positive margins following *** factors comprise non-mass enhancement(NME)on dynamic contrastenhanced MRI,multiple focal vascular signs around the lesion on MRI,tumor size exceeding 2 cm,type III timesignal intensity curve,indistinct margins on molybdenum target examination,unclear margins on ultrasound examination,and estrogen receptor(ER)positivity in *** regression was additionally employed in this study to identify four predictive

关键词： Breast cancer Breast-conserving surgery Imaging features Positive surgical margin regression analysis model

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Prediction of the final size for COVID-19 epidemic using machine learning:A case study of Egypt

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Infectious Disease modelling 2020年第1期5卷 622-634页

作者： Lamiaa A.Amar Ashraf A.Taha Marwa Y.Mohamed Networks and Distributed Systems Department Informatics Research InstituteCity of Scientific Research and Technological ApplicationsSRTA-CITYEgypt Multimedia and Computer Graphics Department Informatics Research InstituteCity of Scientific Research and Technological ApplicationsSRTA-CITYEgypt Department of Mathematics and Computer Science Faculty of ScienceAlexandria UniversityEgypt

COVID-19 is spreading within the sort of an enormous epidemic for the *** epidemic infects a lot of individuals in *** World Health Organization states that COVID-19 could be spread from one person to another at a very fast speed through contact and respiratory *** these days,Egypt and all countries worldwide should rise to an effective step to investigate this disease and eliminate the effects of this *** this paper displayed,the real database of COVID-19 for Egypt has been analysed from February 15,2020,to June 15,2020,and predicted with the number of patients that will be infected with COVID-19,and estimated the epidemic final *** regression analysis models have been applied for data analysis of COVID-19 of *** this study,we’ve been applied seven regression analysis-based models that are exponential polynomial,quadratic,thirddegree,fourth-degree,fifth-degree,sixth-degree,and logit growth respectively for the COVID-19 ***,the exponential,fourth-degree,fifth-degree,and sixth-degree polynomial regression models are excellent models specially fourth-degree model that will help the government preparing their procedures for one *** addition,we have applied the well-known logit growth regression model and we obtained the following epidemiological insights:Firstly,the epidemic peak could possibly reach at 22-June 2020 and final time of epidemic at 8-September ***,the final total size for cases 1.6676Et05 *** action from government of interevent over a relatively long interval is necessary to minimize the final epidemic size.

关键词： COVID-19 regression analysis model Epidemic model

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我国高等学历继续教育办学规模的历史与趋势研究

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成人教育学刊 2022年第8期

作者：袁松鹤张文辉

历史数据分析发现，我国高等学历继续教育办学规模有两个核心影响因素，即生源需求和教育政策，前者决定长期趋势，后者影响短期起伏。常规回归模型分析发现，到2035年，高等继续教育本专科招生规模仍然呈现稳步增长趋势；但结合生源消... 详细信息

历史数据分析发现，我国高等学历继续教育办学规模有两个核心影响因素，即生源需求和教育政策，前者决定长期趋势，后者影响短期起伏。常规回归模型分析发现，到2035年，高等继续教育本专科招生规模仍然呈现稳步增长趋势；但结合生源消耗模型分析发现，自2021年起算，专科6年左右(2026年)招生难度开始倍增，11年(2031年)吸收完真实生源存量，基本萎缩；本科2032年开始消耗存量生源，2044年基本萎缩。面对新形势，在机构层面，学历继续教育要将重心从专科向本科、研究生层次转移，面向在职成人，办出特色；非学历继续教育要发挥线上线下融合优势，优化证书体系、推进课程认证，扩大办学规模；在政策层面，要以高质量发展为目标，促进各类高等继续教育协调发展、错位发展；要通过立法和公共服务平台建设，建设终身学习体系。

关键词：高等继续教育办学规模回归分析模型消耗模型趋势 higher continuing education education scale regression analysis model consumption model trend

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