The Effects of Overstration on the Stratified Log Rank Test for Survival Analysis

Survival analysis concerns the characterization or comparison of one or more distributions of the time to a well defined event. The log-rank test is the most common method used to compare the survival distributions of two samples. When data within the two groups are stratified according to some risk factors, then a stratified log-rank test is employed. Stratified analysis is a procedure used to compare outcomes in different groups while at the same time correcting for the effects of confounders. It is one way to ensure that important prognostic factors are equally distributed among different treatments. The ordinary log-rank test is known to be conservative when treatments have been assigned by a stratified design. The stratified log-rank test is valid even when the sizes of strata differ. Schoenfeld and Tsiatis modified the log-rank test with a variance adjustment reflecting the dependence of survival on strata size. Their method is shown to be more efficient than the ordinary stratified log rank test when the number of strata is large, and it remains valid when the censoring distributions differ across treatment groups. In this thesis, we investigate these three log-rank tests for survival analysis. The effect of the stratum sizes on each type of analysis is evaluated using simulated data. Our results show that the modified log rank test is beneficial for stratified survival analysis in most cases especially when there are large numbers of strata and the strata sizes get small. The statistical power of the modified log-rank test is relatively stable even with very small strata sizes and high strata effects. The public health relevance of this thesis is that the modified log-rank test we investigated and implemented using the R programming language provides an alternative and more efficient way to accommodate higher amounts of stratification in analyzing survival data. More efficient statistical methods indirectly have public health impact as such methods lead to analyses which better identify treatments, interventions or factors that influence health outcomes. Such analyses are commonly used in clinical trials and other studies which influence public healt

Big Changes in How Students are Tested

For the past decade, school accountability has relied on tests for which the essential format has remained unchanged. Educators are familiar with the yearly testing routine: schools are given curriculum frameworks, teachers use the frameworks to guide instruction, students take one big test at year’s end which relies heavily upon multiple-choice bubble items, and then school leaders wait anxiously to find out whether enough of their students scored at or above proficiency to meet state standards. All this will change with the adoption of Common Core standards. Testing and accountability aren’t going away. Instead, they are developing and expanding in ways that aim to address many of the present shortcomings of state testing routines. Most importantly, these new tests will be computer-based. As such, they will potentially shorten testing time, increase tests’ precision, and provide immediate feedback to students and teachers

Research on Teaching Method of Packaging Design Course Based on Chinese Style

The teaching of Packaging Design started late in China, but develops fast. After experiencing the changes of economy, politics and culture, it has entered a new era of self-publicity. The Chinese style has come out quietly with a strong momentum. The contents of packaging design in the new era pay more attention to the spiritual level, and become a bridge between the society and people, forming an aesthetics concept with the spirit of the Chinese people. Based on the application of Chinese style in the course of Packaging Design, this paper discusses the characteristics of Packaging Design with Chinese style and the problems of traditional Packaging Design, and puts forward how to better apply Chinese elements in Packaging Design

Non-covalent interactions in electrochemical reactions and implications in clean energy applications

Understanding and controlling non-covalent interactions associated with solvent molecules and redox-inactive ions provide new opportunities to enhance the reaction entropy changes and reaction kinetics of metal redox centers, which can increase the thermodynamic efficiency of energy conversion and storage devices. Here, we report systematic changes in the redox entropy of one-electron transfer reactions including [Fe(CN)6]3-/4-, [Fe(H2O)6]3+/2+and [Ag(H2O)4]+/0induced by the addition of redox inactive ions, where approximately twenty different known structure making/breaking ions were employed. The measured reaction entropy changes of these redox couples were found to increase linearly with higher concentration and greater structural entropy (having greater structure breaking tendency) for inactive ions with opposite charge to the redox centers. The trend could be attributed to the altered solvation shells of oxidized and reduced redox active species due to non-covalent interactions among redox centers, inactive ions and water molecules, which was supported by Raman spectroscopy. Not only were these non-covalent interactions shown to increase reaction entropy, but they were also found to systematically alter the redox kinetics, where increasing redox reaction energy changes associated with the presence of water structure breaking cations were correlated linearly with the greater exchange current density of [Fe(CN)6]3-/4-.United States. Department of Energy. Office of Basic Energy Science (Award Number DE-SC0001299/DE-FG02-09ER46577)Hong Kong (China). Innovation and Technology Commission (Project No. ITS/ 020/16FP)United States. Department of Energy (Contract No. DE-AC02-5CH11231

Research on the emission reduction effects of carbon trading mechanism on power industry: plant-level evidence from China

Purpose Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design. Design/methodology/approach This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO2 and PM2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016. Findings Results suggest that the carbon trading mechanism induces 2.7% of CO2 emission reduction and 6.7% of PM2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers. Originality/value This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors

DMI Report 21-17 Including a dynamic Greenland Ice Sheet in the EC-Earth global climate model

Recent observations have indicated rapidly increasing mass loss from the Greenland Ice Sheet. To explore the interactions and feedbacks of the ice sheets in the climate system, it is important to develop coupled climate-ice sheet models. The integration of an ice sheet model in a global model is challenging, and, currently, relatively few climate models include a two-way coupling to a dynamical ice sheet model. In this work package, we have continued developing the coupled ice sheet-climate model system comprising the global climate model EC-Earth and the Parallel Ice Sheet Model (PISM) for Greenland. The new model system, EC-Earth3-GrIS, is upgraded to include the recent model versions, EC-Earth3 and PISM version 1.2. In addition, a new module has been developed to handle the exchange of information between the ice sheet model and EC-Earth using the OASIS3- MCT software interface. The new module reads output from the ice sheet model and exchanges the fields with the relevant EC-Earth components. The ice sheet mask and topography are provided to the atmosphere and land surface components. The heat and freshwater fluxes from basal melt and ice discharge are provided to the ocean module via the runoff-mapper that routes surface runoff into the ocean. The new module also prepares the forcing fields for the ice sheet model, i.e., subsurface temperature and surface mass balance. These fields are calculated in EC- Earth3 using a land ice surface parameterization, developed explicitly for the Greenland ice sheet. The parameterization contains a responsive snow and ice albedo scheme and includes land ice characteristics in the calculation of heat and energy transfer at the surface. Experiments with and without the land ice surface parameterization have been carried out for preindustrial and present-day conditions to assess the influence of the surface parameterization on the calculated surface mass balance. The results show that the ice sheet responds stronger and more realistically to forcing changes when the new surface parameterization is used. Besides the model development, the results from experiments with the first model version, EC- Earth-PISM, have been analyzed. These results stress that a decent surface scheme with a responsive snow albedo scheme is necessary for investigating mass balance changes of the Greenland Ice Sheet. Overall, our results indicate that the feedbacks induced by the interactive ice sheet have a significant influence on Arctic climate change under warming conditions. In warm scenarios where the CO2 level is raised to four times the preindustrial level, the coupled model has a colder Arctic surface, a fresher ocean, and more sea-ice in winter

DETC2008-49170 DYNAMIC MODEL OF PROCESS PLANNING FOR TOP-DOWN COLLABORATIVE ASSEMBLY DESIGN

ABSTRACT The design process of top-down collaborative assembly design is high parallel. There are complex task relationships not only in a task group but also among different task groups, which we call them as inside and outside relationships. A dynamic model of process planning based on hierarchical object-oriented Petri-net (HOOPN) is constructed for top-down collaborative assembly design. The dynamic model represents the outside and inside task relationships including parallel, sequential and coupling relationships. Based on the dynamic model, the dynamic supervising, analysis and decision-making for the states of the design process are implemented. The fuzzy overall evaluation model (FOEM) is utilized for risk evaluation of the design process. The task execution is influenced by local and global risk level from FOEM. Finally, the whole process planning is adjusted and controlled dynamically by the special risk decision-making mechanism