Randomization-Based Confidence Intervals for Cluster Randomized Trials

In a cluster randomized trial (CRT), groups of people are randomly assigned to different interventions. Existing parametric and semiparametric methods for CRTs rely on distributional assumptions or a large number of clusters to maintain nominal confidence interval (CI) coverage. Randomization-based inference is an alternative approach that is distribution-free and does not require a large number of clusters to be valid. Although it is well-known that a CI can be obtained by inverting a randomization test, this requires randomization testing a non-zero null hypothesis, which is challenging with non-continuous and survival outcomes. In this paper, we propose a general method for randomization-based CIs using individual-level data from a CRT. This fast and flexible approach accommodates various outcome types, can account for design features such as matching or stratification, and employs a computationally efficient algorithm. We evaluate this method\u27s performance through simulations and apply it to the Botswana Combination Prevention Project, a large HIV prevention trial with an interval-censored time-to-event outcome

Differential temporal beta‐diversity patterns of native and non‐native arthropod species in a fragmented native forest landscape

An important factor that hinders the management of non‐native species is a general lack of information regarding the biogeography of non‐natives, and, in particular, their rates of turnover. Here, we address this research gap by analysing differences in temporal beta‐diversity (using both pairwise and multiple‐time dissimilarity metrics) between native and non‐native species, using a novel time‐series dataset of arthropods sampled in native forest fragments in the Azores. We use a null model approach to determine whether temporal beta‐diversity was due to deterministic processes or stochastic colonisation and extinction events, and linear modelling selection to assess the factors driving variation in temporal beta‐diversity between plots. In accordance with our predictions, we found that the temporal beta‐diversity was much greater for non‐native species than for native species, and the null model analyses indicated that the turnover of non‐native species was due to stochastic events. No predictor variables were found to explain the turnover of native or non‐native species. We attribute the greater turnover of non‐native species to source‐sink processes and the close proximity of anthropogenic habitats to the fragmented native forest plots sampled in our study. Thus, our findings point to ways in which the study of turnover can be adapted for future applications in habitat island systems. The implications of this for biodiversity conservation and management are significant. The high rate of stochastic turnover of non‐native species indicates that attempts to simply reduce the populations of non‐native species in situ within native habitats may not be successful. A more efficient management strategy would be to interrupt source‐sink dynamics by improving the harsh boundaries between native and adjacent anthropogenic habitats.Portuguese FCT‐NETBIOME – ISLANDBIODIV grant 0003/2011.info:eu-repo/semantics/publishedVersio

Convergence of the Crank-Nicolson-Galerkin finite element method for a class of nonlocal parabolic systems with moving boundaries

The aim of this paper is to establish the convergence and error bounds to the fully discrete solution for a class of nonlinear systems of reaction-diffusion nonlocal type with moving boundaries, using a linearized Crank-Nicolson-Galerkin finite element method with polynomial approximations of any degree. A coordinate transformation which fixes the boundaries is used. Some numerical tests to compare our Matlab code with some existing moving finite elements methods are investigated

Spin-polarized quantum transport through a T-shape quantum dot-array: a model of spin splitter

We in this paper study theoretically the spin-polarized quantum transport through a T-shape quantum dot-array by means of transfer-matrix method along with the Green^{,}s function technique. Multi-magnetic fields are used to produce the spin-polarized transmission probabilities and therefore the spin currents, which are shown to be tunable in a wide range by adjusting the energy, and the direction-angle of magnetic fields as well. Particularly the opposite- spin- polarization currents separately flowing out to two electrodes can be generated and thus the system acts as a spin splitter.Comment: 8 pages, 8 figure

Evaluation of genome-wide chromatin library of Stat5 binding sites in human breast cancer

BACKGROUND: There is considerable interest in identifying target genes and chromatin binding sites for transcription factors in a genome-wide manner. Such information may become useful in diagnosis and treatment of disease, drug target identification, and for prognostication. In cancer diagnosis, patterns of transcription factor binding to specific regulatory chromatin elements are expected to complement and enhance current diagnostic predictions of tumor behavior based on protein and mRNA analyses. Signal transducer and activator of transcription-5 (Stat5) is a cytokine-activated transcription factor implicated in growth and progression of many malignancies, including hematopoietic, prostate, and breast cancer. We have explored immunoaffinity purification of Stat5-bound chromatin from breast cancer cells to identify Stat5 target sites in an unbiased, genome-wide manner. RESULTS: In this report, we evaluate the efficacy of a Stat5-bound chromatin library to identify valid Stat5 chromatin binding sites within the oncogenome of T-47D human breast cancer cells. A general problem with cloning of immunocaptured, transcription factor-bound chromatin fragments is contamination with non-specific chromatin. However, using an optimized strategy, five out of ten randomly selected clones could be experimentally verified to bind Stat5 both in vitro and in vivo as tested by electrophoretic mobility shift assay and chromatin immunoprecipitation, respectively. While there was no binding to fragments lacking a Stat5 consensus binding sequence, presence of a Stat5 binding sequence did not assure binding. CONCLUSION: A chromatin library coupled with experimental validation may productively identify novel in vivo Stat5 chromatin binding sites in cancer, including abnormal regulatory sites in tumor-specific neochromatin