Modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

Parametric Cure Model versus Proportional Hazards Model in Survival Analysis of Breast Cancer and Other Malignancies

As cancer therapy has progressed dramatically, its goal has shifted toward cure of the disease (curative therapy) rather than prolongation of time to death (life-prolonging therapy). Consequently, the proportion of cured patients (c) has become an important measure of the long-term survival benefit derived from therapy. In 1949, Boag addressed this issue by developing the parametric log-normal cure model, which provides estimates of c and m where m is the mean of log times to death from cancer among uncured patients. Unfortunately, traditional methods based on the proportional hazards model like the Cox regression and log-rank tests cannot provide an estimate of either c or m. Rather, these methods estimate only the differences in hazard between two or more groups. In order to evaluate the long-term validity and usefulness of the parametric cure model compared with the proportional hazards model, we reappraised randomized controlled trials and simulation studies of breast cancer and other malignancies. The results reveal that: 1) the traditional methods fail to distinguish between curative and life-prolonging therapies;2) in certain clinical settings, these methods may favor life-prolonging treatment over curative treatment, giving clinicians a false estimate of the best regimen;3) although the Boag model is less sensitive to differences in failure time when follow-up is limited, it gains power as more failures occur. In conclusion, unless the disease is always fatal, the primary measure of survival benefit should be c rather than m or hazard ratio. Thus, the Boag lognormal cure model provides more accurate and more useful insight into the long-term benefit of cancer treatment than the traditional alternatives.

Regression Analysis of Doubly Censored Data with a Cured Subgroup under a Class of Promotion Time Cure Models

In some situations,the failure time of interest is defined as the gap time between two related events and the observations on both event times can suffer either right or interval censoring.Such data are usually referred to as doubly censored data and frequently encountered in many clinical and observational studies.Additionally,there may also exist a cured subgroup in the whole population,which means that not every individual under study will experience the failure time of interest eventually.In this paper,we consider regression analysis of doubly censored data with a cured subgroup under a wide class of flexible transformation cure models.Specifically,we consider marginal likelihood estimation and develop a two-step approach by combining the multiple imputation and a new expectation-maximization(EM)algorithm for its implementation.The resulting estimators are shown to be consistent and asymptotically normal.The finite sample performance of the proposed method is investigated through simulation studies.The proposed method is also applied to a real dataset arising from an AIDS cohort study for illustration.

Semiparametric estimation for accelerated failure time mixture cure model allowing non-curable competing risk

The mixture cure model is the most popular model used to analyse the major event with a potential cure fraction.But in the real world there may exist a potential risk from other non-curable competing events.In this paper,we study the accelerated failure time model with mixture cure model via kernel-based nonparametric maximum likelihood estimation allowing non-curable competing risk.An EM algorithm is developed to calculate the estimates for both the regression parameters and the unknown error densities,in which a kernel-smoothed conditional profile likelihood is maximised in the M-step,and the resulting estimates are consistent.Its performance is demonstrated through comprehensive simulation studies.Finally,the proposed method is applied to the colorectal clinical trial data.

基于CURE算法和C4.5决策树的服装销售预测模型

针对服装销售中销售预测模型不能对复杂多变的市场以及分销商的需求作出及时响应的现状,提出一种基于CURE算法和C4.5决策树相结合的方法来建立服装销售预测模型,其中CURE算法从销售前景考虑把相似的项进行聚类,C4.5决策树则将这些聚类和选取的描述标准联系起来。通过对568项历史销售数据和326项新数据进行测试,分析模型的执行效率。最后,针对预测模型中出现的分类错误,提出了进一步改进的方法。

Comparative Analysis on Chemical Components and Sensory Quality of Aging Flue-Cured Tobacco from Four Main Tobacco Areas of China

Complicated changes are happening during the aging process of flue-cured tobacco （FCT） and understanding of the changing components is of great significance in improving the quality,shortening aging time,and enhancing production and economic efficiency in tobacco industry.The aging samples of FCT from four main producing areas of China,i.e.,Yunnan,Sichuan,Hubei,and Dongbei,were used to study the changing rule of the components such as alkali,acid,and carbohydrate as well as the aroma and their relationship with sensory quality;and based on the correlation among the components and the sensory quality index,multivariable models were established to predict the aging quality.The results showed that the sensory quality of FCT increased steadily during the aging time,and at the same time,the acidic components （total organic acids,volatile acids） increased gradually,while the alkaline substances （nicotine,volatile alkali）,carbohydrate （total sugars,reducing sugar） and pH values showed a downward trend.Correlation analysis found that the sensory quality and pH values were negatively correlated （P0.05）,while the sensory quality with total organic acids and aroma were positively correlated.The optimal model for predicting the quality of FCT was y=56.75-0.63x12＋50.09x2-13.27x22,（y：sensory quality;x1：pH;x2：total organic acids）.The average predicating error was 1.04% with maximum predicating error of 2.89% and the accuracy rate of above 97%.

Cure Reaction Kinetics of Low Pressure Sheet Molding Compound System Thickened by Crystalline Polymer

Several kinetic models for unsaturated polyester cure reaction and some existing parameter estimation techniques of these models were introduced. Correlated kinetic parameters and kinetic equations of the autocatalytic empirical kinetic model of LPSMC system were determined by using isothermal DSC to scan the system which was thickened by crystalline polymer （PEG-MAH）. Through using a serial curing degree of the system to validate the model, the experimental results were basically identical with the predictions of the autocatalytic empirical kinetic model. This model could provide a theoretical reference to the determination of molding techniques of low pressure SMC.

Transformation Models for Survival Data Analysis with Applications

When the event of interest never occurs for a proportion of subjects during the study period, survival models with a cure fraction are more appropriate in analyzing this type of data. Considering the non-linear relationship between response variable and covariates, we propose a class of generalized transformation models motivated by Zeng et al. [1] transformed proportional time cure model, in which fractional polynomials are used instead of the simple linear combination of the covariates. Statistical properties of the proposed models are investigated, including identifiability of the parameters, asymptotic consistency, and asymptotic normality of the estimated regression coefficients. A simulation study is carried out to examine the performance of the power selection procedure. The generalized transformation cure rate models are applied to the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study (NHANES1) for the purpose of examining the relationship between survival time of patients and several risk factors.

烤后烟叶不同部位高光谱特征分析及判别模型构建

利用高光谱(400~1700 nm)成像技术扫描得到3个部位(上B、中C、下X)烤后烟叶的高光谱图像,并提取其高光谱数据。采用相关性分析、主成分分析及方差分析研究了3个部位烟叶的高光谱特征,并构建5种识别烟叶部位的判别模型(SVM、KNN、RF、LightGBM和XGBoost)。结果表明,3个部位烟叶的光谱反射率为C>X>B(400~750 nm),B>C>X(750~1400 nm),C>B≈X(1400~1700 nm)。3个部位烟叶的高光谱数据存在较强相关性,总体上可见光以及近红外波段在各自区域内相关性较强,而两者之间相关性较弱。共提取得到7个特征值大于1的主成分,方差累计贡献率接近1.00。3个部位烟叶的光谱反射率在450~550 nm和750~1400 nm区域相互之间存在明显差异,中部叶在550~850 nm和1400~1700nm分别与上、下部叶具有明显差异,上部叶在400~450 nm分别与中、下部叶差异明显,下部叶在680 nm附近分别与上、中部叶差异显著。SVM判别不同部位烟叶的表现最好,准确率、精确率、召回率和F1分数均达95%以上,LightGBM表现居中,各项指标在90%~95%,RF、KNN和XGBoost相对较差,各项指标在90%以下。

基于随机骨料模型的EPS颗粒混凝土蒸养损伤及微观分析

为研究掺入废弃塑料对缓解混凝土蒸汽引起的热损伤机理,开展了不同聚苯乙烯泡沫塑料(EPS)颗粒掺量混凝土的抗压强度试验,建立了考虑界面过渡区效应的随机骨料模型,模拟了蒸养环境下混凝土内部的热应力分布,并通过压汞试验和扫描电子显微镜照片揭示了EPS颗粒掺入对蒸养试件孔结构特征和微观演化规律的影响。结果表明,随EPS颗粒掺量的增加,蒸养试件强度略有升高,EPS颗粒掺入有利于蒸养混凝土后期强度的发展;蒸养引起的热应力得到显著缓解,微裂缝和贯通裂缝数量降低,有效抑制蒸养引起的热损伤;掺入EPS颗粒细化了蒸养混凝土孔结构,缩小了EPS颗粒⁃水泥基体界面的裂隙宽度。

山东烤烟感官质量与化学成分关系及质量预测模型建立

为明确山东烤烟化学成分与感官质量之间的关系,探明影响山东烟叶质量提升的关键化学成分指标,对山东省6个地区代表性烟叶样品开展感官质量评价和常规成分、有机酸、生物碱、单双糖、多酚等5类23种化学指标测定,结合简单相关、方差分析、主成分分析和回归分析等统计方法进行数据分析。筛选出总糖、氯、绿原酸、降烟碱、柠檬酸/烟碱、油酸6个影响山东烟叶品质的关键化学指标,基于6个指标构建山东烟叶感官质量预测模型,验证样本预测值与真实值绝对差值0.43~3.88分,相对误差-5.66%~6.32%,平均误差3.18%。基于关键化学成分构建的感官质量预测模型可为山东烟叶质量的客观评价提供一定的技术支撑。

基于改进CURE聚类算法的网络用户异常行为识别方法

由于传统异常行为识别方法无法对随时变化的异常行为实现精准识别,因此对CURE聚类算法作出改进,针对网络用户异常行为提出了一种新的识别方法。通过改进CURE聚类算法将用户的上网行为分为正常行为簇和异常行为簇,标记正常行为簇,并利用超矩形建模方式识别数据,分析正常行为簇在每个维度上的正常值域,判断其是否包含在所建立的超矩形内。如果在判定用户行为为正常,反之判断其为异常行为。仿真实验选取了学生上网行为数据,分四个时间段注入异常行为数据,结果表明,所提方法识别结果与设定情况一致,没有出现误识别或不识别现象,改进CURE聚类算法的网络用户异常行为识别精度较高,而且具有超高的效率。

一类考虑先天免疫和非线性治愈率的时滞传染病模型Hopf分岔

考虑到传染病流行过程中先天免疫对个体的重要性,研究了一类具有先天免疫和非线性治愈率的时滞SEIS传染病模型。以感染者恢复所需要的时间周期时滞为分岔参数,通过讨论模型特征方程根的分布情况,推导出模型局部渐近稳定和产生Hopf分岔的时滞临界点。进而利用中心流形方法,计算出确定Hopf分岔性质的显式公式。研究表明,当感染者恢复所需要的时间周期时滞低于临界点时,疾病的传播可以得到有效控制。

基于Markov链的上海市枫林社区骨质疏松全人群防治工作的成本效果分析

背景随着社区卫生服务综合改革的逐步深化,社区对全人群的单病种防治工作也在不断优化,但目前仍缺乏合适的方法来评价社区防治的成效。目的通过分析2016—2022年度上海市徐汇区枫林街道社区卫生服务中心现有骨质疏松全人群防治措施的成本效果,探究社区单病种全人群防治的初步成效及可能存在的问题。方法本研究以4293例枫林社区2016—2022年度接受骨质疏松防治的社区居民为研究对象进行成本-效果分析。根据骨密度值将研究对象划分为三种状态:健康、低骨量、骨质疏松,以此构建Markov模型,分析不同状态转移的影响因素,并依据Markov模型预测值结合质量调整生命年(QALY)计算QALY增量,统计2016—2022年防治工作投入的所有成本,以成本/QALY增量比来评价防治效果,通过文献检索确定的健康效用值和期望寿命计算求得QALY。结果枫林社区骨质疏松防治总成本为33814102.15元。第一次诊断时社区骨质疏松防治人群的总QALY为77098.2889,人均均值为17.959,标准差为9.34;第二次诊断时防治人群的总QALY为79616.9361,人均均值为18.546,标准差为9.342,两次诊断QALY的差值为2518.6472。增量成本效果比(ICER)为2132.9070元/QALY,ICER值小于1倍(66965.10元)人均GDP,表明干预方案完全具有成本效果。结论本研究结合Markov模型及QALY对枫林社区持续接受骨质疏松随访管理的人群的防治效果进行了初步评价,结果显示枫林社区的骨质疏松防治干预方案是值得投入的,为后续骨质疏松的精准防治决策提供了一定的依据。

基于轻量化MobileViT深度学习模型的烤烟自动分组方法

针对烟叶自动识别分组过程中特征提取困难、分组准确率低、模型参数量大、部署困难等问题,本文结合轻量化网络MobileNetV2与ViT模型的优点提出了一种轻量化MobileViT模型的烤烟自动分组方法。首先对所采集的烟叶图像进行前景和背景的预处理,解决提取烟叶特征困难的问题;然后将预处理后的图像建立成完整的烟叶图像数据集;最后针对建立的数据集使用基于轻量化MobileViT模型进行分组。使用该模型对云南省多地收购的5871张混合烤烟叶片进行分组试验,结果表明MobileViT对正组烟叶、副组烟叶和正副混合组烟叶分组准确率分别达到了79.44%、83.83%、79.22%,与MobileNetV2相比分别提升了9.5%、17.66%、17.56%;与ViT模型相比分别提升了13.8%、30.83%、34.12%。与当前应用较多的MobileNetV3、Effcient、Resnet50三种模型相比,MobileViT模型在混合组上分组准确率较轻量化MobileNetV3网络提升了11.86%;较CNN为代表的Effcient、Resnet50模型分别提升了9.6%、6.55%,模型大小降低了24.62%、79.1%。轻量化MobileViT模型同时结合了轻量化网络MobileNetV2与ViT模型的优点,在降低模型大小的同时具有较高的分组准确率,更容易部署在工业设备中,符合实际工业应用需求。

广义治愈率模型的贝叶斯推断

广义治愈率模型是将治愈率模型推广到含有潜在变量.潜变量的引入增加了模型的复杂度.本文给出其一个分层表示,通过引入Polya-Gamma变量和广义生存时间,将比例治愈率模型置于分层框架内.分层形式提供了计算上的便利.我们在贝叶斯框架内进行了结果展示.

不同养护制度下掺废弃塑料对混凝土的影响研究

为研究掺入废弃塑料对蒸汽养护混凝土的作用机制,开展了不同塑料颗粒掺量混凝土力学试验,建立了考虑界面过渡区效应的随机骨料模型,模拟塑料颗粒掺入对蒸养混凝土热损伤的影响,并通过压汞试验,揭示了塑料颗粒掺入对蒸养试件孔结构演化规律。结果表明,随塑料颗粒掺量的增加,蒸养试件强度高于标养混凝土强度;蒸养引起的内部应力因塑料颗粒的掺入得到显著缓解,微裂纹数量明显减少,有效抑制蒸养引起的热损伤;塑料颗粒细化了蒸养混凝土孔结构,多害孔占比降低,无害孔占比增加。

蒸养条件下机制砂混凝土的力学性能及干缩性能

为推动机制砂在预制混凝土构件中的应用,实现机制砂在建筑行业的更广阔应用,进而有效减缓天然砂资源短缺的问题,通过混凝土抗压强度、动弹性模量和干燥收缩试验等宏观性能测试和扫描电镜测试、压汞测试及显微硬度测试等微观测试方法,探讨养护条件和砂型对混凝土力学性能及干缩性能的影响规律及相应机理。试验结果表明:无论采用河砂还是机制砂,蒸养混凝土相较标养混凝土具有更高的早期力学性能和更低的干燥收缩,但高温导致水化产物分布不均,阻碍了后续的水化反应,使其后期力学性能出现不同程度的劣化。结合微观测试结果可知,孔径粗化、界面过渡区间隙增大和水化产物结构疏松是造成蒸养混凝土后期性能劣化的主要原因,但采用机制砂替代河砂能有效减弱蒸养热伤损效应产生的劣化影响。此外,蒸养机制砂混凝土相较蒸养河砂混凝土具有更高的力学性能和更优的微观结构,具体表现为:蒸养机制砂混凝土孔结构更加细化,界面过渡区间隙更小,同时基体显微硬度均值更高,整体密实度更高。但小于50 nm毛细孔增加将导致蒸养机制砂混凝土干缩变形增大。基于GL 2000收缩模型,通过引入考虑机制砂的影响因子,建立了蒸养机制砂混凝土干燥收缩预测模型,可较准确且有效地进行蒸养机制砂混凝土的干燥收缩预测。

不同光谱采集方式对手持式近红外建模效果的影响

对烟叶原烟采取滑动法和六点法2种方式进行扫描,同时对烟末样品采取滑动法,用二阶导数预处理,异常样本剔除、波长选择、剔一交互验证等后用偏最小二乘法分别建立烟碱模型,三者的相关系数分别为0.97、0.98、0.99,三者的校正标准误差(SEC)分别为0.20%、0.25%、0.09%。结果表明烟叶样品采用滑动法扫描优于六点法,检测的烟叶样品更具有代表性和其快速的结果能满足实际应用需求,在应用过程中节省大量的时间,明显提高工作效率。

Leaching kinetics of low-grade copper ore containing calcium-magnesium carbonate in ammonia-ammonium sulfate solution with persulfate

The leaching kinetics of copper from low-grade copper ore was investigated in ammonia-ammonium sulfate solution with sodium persulfate. The effect parameters of stirring speed, temperature, particle size, concentrations of ammonia, ammonium sulfate and sodium persulfate were determined. The results show that the leaching rate is nearly independent of agitation above 300 r/min and increases with the increase of temperature, concentrations of ammonia, ammonium sulfate and sodium persulfate. The EDS analysis and phase quantitative analysis of the residues indicate that bornite can be dissolved by persulfate oxidization. The leaching kinetics with activation energy of 22.91 kJ/mol was analyzed by using a new shrinking core model （SCM） in which both the interfacial transfer and diffusion across the product layer affect the leaching rate. A semi-empirical rate equation was obtained to describe the leaching process and the empirical reaction orders with respect to the concentrations of ammonia, ammonium sulfate and sodium persulfate are 0.5, 1.2 and 0.5, respectively.