Asymptotic Theory of Rerandomization in Treatment-Control Experiments

Although complete randomization ensures covariate balance on average, the chance for observing significant differences between treatment and control covariate distributions increases with many covariates. Rerandomization discards randomizations that do not satisfy a predetermined covariate balance criterion, generally resulting in better covariate balance and more precise estimates of causal effects. Previous theory has derived finite sample theory for rerandomization under the assumptions of equal treatment group sizes, Gaussian covariate and outcome distributions, or additive causal effects, but not for the general sampling distribution of the difference-in-means estimator for the average causal effect. To supplement existing results, we develop asymptotic theory for rerandomization without these assumptions, which reveals a non-Gaussian asymptotic distribution for this estimator, specifically a linear combination of a Gaussian random variable and a truncated Gaussian random variable. This distribution follows because rerandomization affects only the projection of potential outcomes onto the covariate space but does not affect the corresponding orthogonal residuals. We also demonstrate that, compared to complete randomization, rerandomization reduces the asymptotic sampling variances and quantile ranges of the difference-in-means estimator. Moreover, our work allows the construction of accurate large-sample confidence intervals for the average causal effect, thereby revealing further advantages of rerandomization over complete randomization

Character of frustration on magnetic correlation in doped Hubbard model

The magnetic correlation in the Hubbard model on a two-dimensional anisotropic triangular lattice is studied by using the determinant quantum Monte Carlo method. Around half filling, it is found that the increasing frustration $t'/t$ could change the wave vector of maximum spin correlation along ($\pi,\pi$)$\rightarrow$($\pi,\frac{5\pi}{6}$)$\rightarrow$($\frac{5\pi}{6},\frac{5\pi}{6}$)$\rightarrow$ ($\frac{2\pi}{3},\frac{2\pi}{3}$), indicating the frustration's remarkable effect on the magnetism. In the studied filling region =1.0-1.3, the doping behaves like some kinds of {\it{frustration}}, which destroys the $(\pi,\pi)$ AFM correlation quickly and push the magnetic order to a wide range of the $(\frac{2\pi}{3},\frac{2\pi}{3})$ $120^{\circ}$ order when the $t'/t$ is large enough. Our non-perturbative calculations reveal a rich magnetic phase diagram over both the frustration and electron doping.Comment: 6 pages, 7 figure

Isolation and Characteristics of a Bacterial Strain for Deodorization of Dimethyl Sulfide

AbstractThe removal characteristics of dimethyl sulfide (DMS) with a peat packed tower were studied. The peat itself did not remove DMS. The peat inoculated with activated sludge as a source of microorganisms showed an efficient removal of DMS. Dominant microorganisms for degradation of DMS in the peat packed tower were some chemolithotrophic and non-acidophilic sulfur-oxidizing microorganisms originating from sludge. A dominant DMS-oxidizing strain Au7 was isolated and identified as chemolithotrophic Thiobacilli. Product of DMS oxidation by strain Au7 was sulfate. The optimum pH of DMS removal by strain Au7 was 7-5.45

UAV first view landmark localization with active reinforcement learning

We present an active reinforcement learning framework for unmanned aerial vehicle (UAV) first view landmark localization. We formulate the problem of landmark localization as that of a Markov decision process and introduce an active landmark-localization network (ALLNet) to address it. The aim of the ALLNet is to locate a bounding box that surrounds the landmark in a first view image sequence. To this end, it is trained in a reinforcement learning fashion. Specifically, it employs support vector machine (SVM) scores on the bounding box patches as rewards and learns the bounding box transformations as actions. Furthermore, each SVM score indicates whether or not the landmark is detected by the bounding box such that it enables the ALLNet to have the capability of judging whether the landmark leaves or re-enters a first view image. Therefore, the operation of the ALLNet is not only dominated by the reinforcement learning process but also supplemented by an active learning motivated manner. Once the landmark is considered to leave the first view image, the ALLNet stops operating until the SVM detects its re-entry to the view. The active reinforcement learning model enables training a robust ALLNet for landmark localization. The experimental results validate the effectiveness of the proposed model for UAV first view landmark localization

Band Structure Engineering of Interfacial Semiconductors Based on Atomically Thin Lead Iodide Crystals

To explore new constituents in two-dimensional materials and to combine their best in van der Waals heterostructures, are in great demand as being unique platform to discover new physical phenomena and to design novel functionalities in interface-based devices. Herein, PbI2 crystals as thin as few-layers are first synthesized, particularly through a facile low-temperature solution approach with the crystals of large size, regular shape, different thicknesses and high-yields. As a prototypical demonstration of flexible band engineering of PbI2-based interfacial semiconductors, these PbI2 crystals are subsequently assembled with several transition metal dichalcogenide monolayers. The photoluminescence of MoS2 is strongly enhanced in MoS2/PbI2 stacks, while a dramatic photoluminescence quenching of WS2 and WSe2 is revealed in WS2/PbI2 and WSe2/PbI2 stacks. This is attributed to the effective heterojunction formation between PbI2 and these monolayers, but type I band alignment in MoS2/PbI2 stacks where fast-transferred charge carriers accumulate in MoS2 with high emission efficiency, and type II in WS2/PbI2 and WSe2/PbI2 stacks with separated electrons and holes suitable for light harvesting. Our results demonstrate that MoS2, WS2, WSe2 monolayers with very similar electronic structures themselves, show completely distinct light-matter interactions when interfacing with PbI2, providing unprecedent capabilities to engineer the device performance of two-dimensional heterostructures.Comment: 36 pages, 5 figure