One-step targeted maximum likelihood estimation for time-to-event outcomes

Researchers in observational survival analysis are interested in not only estimating survival curve nonparametrically but also having statistical inference for the parameter. We consider right-censored failure time data where we observe n independent and identically distributed observations of a vector random variable consisting of baseline covariates, a binary treatment at baseline, a survival time subject to right censoring, and the censoring indicator. We assume the baseline covariates are allowed to affect the treatment and censoring so that an estimator that ignores covariate information would be inconsistent. The goal is to use these data to estimate the counterfactual average survival curve of the population if all subjects are assigned the same treatment at baseline. Existing observational survival analysis methods do not result in monotone survival curve estimators, which is undesirable and may lose efficiency by not constraining the shape of the estimator using the prior knowledge of the estimand. In this paper, we present a one-step Targeted Maximum Likelihood Estimator (TMLE) for estimating the counterfactual average survival curve. We show that this new TMLE can be executed via recursion in small local updates. We demonstrate the finite sample performance of this one-step TMLE in simulations and an application to a monoclonal gammopathy data.     

A study on thermal damage during hyperthermia treatment based on DPL model for multilayer tissues using finite element Legendre wavelet Galerkin approach

Hyperthermia is a process that uses heat from the spatial heat source to kill cancerous cells without damaging the surrounding healthy tissues. Efficacy of hyperthermia technique is related to achieve temperature at the infected cells during the treatment process. A mathematical model on heat transfer in multilayer tissues in finite domain is proposed to predict the control temperature profile at hyperthermia position. The treatment technique uses dual-phase-lag model of heat transfer in multilayer tissues with modified Gaussian distribution heat source subjected to the most generalized boundary condition and interface at the adjacent layers. The complete dual-phase-lag model of bioheat transfer is solved using finite element Legendre wavelet Galerkin approach. The present solution has been verified with exact solution in a specific case and provides a good accuracy. The effect of the variability of different parameters such as lagging times, external heat source, metabolic heat source and the most generalized boundary condition on temperature profile in multilayer tissues is analyzed and also discussed the effective approach of hyperthermia treatment. Furthermore, we studied the modified thermal damage model with regeneration of healthy tissues as well. For viewpoint of thermal damage, the least thermal damage has been observed in boundary condition of second kind. The article concludes with a discussion of better opportunities for future clinical application of hyperthermia treatment.     

大田威廉斯香蕉叶片光合特性研究

用Li-6400型便携式光合作用测定系统研究大田威廉斯香蕉叶片光合日变化、光响应曲线和CO₂响应曲线,运用非直角双曲线模型并结合SPSS软件的非线性回归估算其光合作用参数。结果表明,香蕉叶片光合日进程呈单峰曲线,没有明显的午休现象,最大净光合速率出现在10:20左右;光饱和点与光补偿点分别为778.19和61.09μmol/m²·s,表观量子效率为0.0414;CO₂饱和点与补偿点分别为608.97和72.13μmol/mol,羧化效率为0.094。此外,对影响香蕉光合速率的主要环境因子分析表明,在土壤供水充分的条件下,限制光合速率的因子是光合有效辐射而非气孔导度。     

Optimizing selection for function-valued traits

We consider a function-valued trait z(t) whose pre-selection distribution is Gaussian, and a fitness function W that models optimizing selection, subject to certain natural assumptions. We show that the post-selection distribution of z(t) is also Gaussian, compute the selection differential, and derive an equation that expresses the selection gradient in terms of the parameters of W and of the pre-selection distribution. We make no assumptions on the nature of the “time” parameter t.      

Host genetic risk factors for community-acquired pneumonia

This study was conducted to establish the contribution of genetic host factors in the susceptibility to community acquired pneumonia (CAP) in the Russian population. Patients with CAP (n = 334), volunteers without a previous history of CAP, constantly exposed to infectious agents, control A group (n = 141) and a second control group B consisted of healthy persons (n = 314) were included in the study. All subjects were genotyped for 13 polymorphic variants in the genes of xenobiotics detoxification CYP1A1 (rs2606345, rs4646903, and rs1048943), GSTM1 (Ins/del), GSTT1 (Ins/del), ABCB1 rs1045642); immune and inflammation response IL-6 (rs1800795), TNF-a (rs1800629), MBL2 (rs7096206), CCR5 (rs333), NOS3 (rs1799983), angiotensin-converting enzyme ACE (rs4340), and occlusive vascular disease/hyperhomocysteinemia MTHFR (rs1801133). Seven polymorphic variants in genes CYP1A1, GSTM1, ABCB1, NOS3, IL6, CCR5 and ACE were associated with CAP. For two genes CYP1A1 and GSTM1 associations remained significant after correction for multiple comparisons. Multiple analysis by the number of all risk genotypes showed a highly significant association with CAP (P = 2.4 × 10^− 7, OR = 3.03, 95% CI 1.98–4.64) with the threshold for three risk genotypes. Using the ROC-analysis, the AUC value for multi-locus model was estimated as 68.38.     

基于MFCC和GMM的昆虫声音自动识别

昆虫的运动、 取食、 鸣叫都会发出声音, 这些声音存在种内相似性和种间差异性, 因此可用来识别昆虫的种类。基于昆虫声音的昆虫种类自动检测技术对协助农业和林业从业人员方便地识别昆虫种类非常有意义。本研究采用了语音识别领域里的声音参数化技术来实现昆虫的声音自动鉴别。声音样本经预处理后, 提取梅尔倒谱系数（Mel frequency cepstrum coefficient, MFCC）作为特征, 并用这些样本提取的MFCC特征集训练混合高斯模型（Gaussian mixture model, GMM）。最后用训练所得到的GMM对未知类别的昆虫声音样本进行分类。该方法在包含58种昆虫声音的样本库中进行了评估, 取得了较高的识别正确率（平均精度为98.95%）和较理想的时间性能。该测试结果证明了基于MFCC和GMM的语音参数化技术可以用来有效地识别昆虫种类。     

具有竞争指针的短时记忆神经网络模型

在我们以前提出的短时记忆神经网络模型基础上［３］,我们在新模型中引入突触竞争机制,提出了一个新的短时记忆神经网络模型。模型仍由两个神经网络所组成;其一为与长时记忆共有的信息内容表达网络,另一个为指针神经元环路。由于表达区神经元与指针神经元间的突触权重的竞争,使得模型可以表现出由干扰引起的短时记忆的遗忘。相应于自由回忆序列位置效应和汉字组块两个心理学实验,对模型做了计算机仿真。仿真结果显示模型的行为与两个心理实验定量地符合得很好。由此表明现在的模型更合适于作为短时记忆的模型。     

濒危植物大果木莲种群格局及濒危原因分析

采用径级结构代替年龄结构以及方差均值比率法对木兰科(Magnoliaceae)木莲属(Manglietia Bl.)濒危植物大果木莲(Manglietia grandis Hu et Cheng)种群的年龄结构和种群格局进行了研究,并编制了大果木莲种群的特定时间生命表和存活曲线;结合生殖生物学特征以及遗传多样性研究结果,分析了导致大果木莲濒危的主要原因.根据株高和胸径可分别将大果木莲种群的年龄结构分为5级、高度结构分为6级;在大果木莲的5个年龄结构分级中,成年个体较多,幼年个体较少;其高度结构完整,个体高度主要在20 m以下.种群的方差均值比率为0.838 3,其空间分布格局属于随机分布.根据特定时间生命表可将大果木莲种群的发育分为3个阶段:幼树阶段(年龄级为Ⅱ～Ⅲ级)、成树阶段(年龄级为Ⅲ～Ⅳ级)、老树阶段(年龄级为Ⅳ～Ⅴ级),其中成树阶段个体死亡率最低.大果木莲种群存活曲线接近Deevey Ⅰ型,属于衰退型种群.种群自我更新能力差、种子生产力低下、有性生殖困难、生境片断化导致的基因流受限以及人为干扰是大果木莲濒危的主要原因.针对大果木莲濒危现状和致危原因,提出了相应的保护对策和建议.     

珍稀濒危植物南方铁杉种群动态研究

以种群生命表及生存分析理论为基础,编制南方铁杉种群静态生命表,绘制存活曲线、死亡率曲线、亏损度曲线、死亡密度函数曲线、积累死亡函数曲线和危险率函数曲线,分析种群生命过程。结果表明,南方铁杉有一个死亡最低峰,存活曲线趋于Deevey-Ⅱ型。并应用谱分析方法研究南方铁杉种群动态,结果表明,在南方铁杉种群自然更新过程中并没有表现出明显的周期性。     

入侵植物喜旱莲子草和本地种接骨草光合生理特征对增温响应的差异

利用红外加热器模拟增温,比较入侵植物喜旱莲子草和本地种接骨草的光合特性对增温响应的差异,以预测气候变暖背景下入侵植物的入侵潜力,并为筛选替代控制植物提供依据。结果表明:增温导致喜旱莲子草和接骨草的叶绿素a/b值分别比对照显著提高6.21%和降低5.55%。无论增温与否,接骨草的叶绿素b含量显著高于喜旱莲子草,而叶绿素a/b值则相反。增温导致喜旱莲子草净光合速率显著提高9.23%,由于气孔导度增大引起蒸腾速率大幅度增加,使得其水分利用效率比对照显著降低10.64%。增温仅导致接骨草的气孔导度显著增加10.95%,而对其他气体交换特征无显著影响。对照条件下,尽管接骨草的气孔导度和胞间CO_2浓度分别显著低于喜旱莲子草7.03%和4.57%,但是前者的净光合速率和水分利用效率分别显著高于后者10.30%和11.92%。增温条件下,两种植物的净光合速率和气孔导度无显著差异,由于接骨草的蒸腾速率显著低于喜旱莲子草18.02%,故其水分利用效率显著高于后者26.45%。增温、物种及其两者的交互作用对光补偿点、光饱和点、最大净光合速率、暗呼吸速率和初始量子效率等光响应参数影响均不显著。总之,对照条件下,接骨草凭借较高的叶绿素b含量、净光合速率和水分利用效率,比喜旱莲子草具有更强的光合能力。但增温后,接骨草的光合优势被削弱。研究从光合生理角度证明接骨草有望作为喜旱莲子草的替代控制植物,但是未来气候变化背景下喜旱莲子草的入侵潜力可能增强。