Knowledge, attitudes and practices relating to influenza A(H7N9) risk among live poultry traders in Guangzhou City, China

published_or_final_versio

GenDet: Meta Learning to Generate Detectors From Few Shots

Object detection has made enormous progress and has been widely used in many applications. However, it performs poorly when only limited training data is available for novel classes that the model has never seen before. Most existing approaches solve few-shot detection tasks implicitly without directly modeling the detectors for novel classes. In this article, we propose GenDet, a new meta-learning-based framework that can effectively generate object detectors for novel classes from few shots and, thus, conducts few-shot detection tasks explicitly. The detector generator is trained by numerous few-shot detection tasks sampled from base classes each with sufficient samples, and thus, it is expected to generalize well on novel classes. An adaptive pooling module is further introduced to suppress distracting samples and aggregate the detectors generated from multiple shots. Moreover, we propose to train a reference detector for each base class in the conventional way, with which to guide the training of the detector generator. The reference detectors and the detector generator can be trained simultaneously. Finally, the generated detectors of different classes are encouraged to be orthogonal to each other for better generalization. The proposed approach is extensively evaluated on the ImageNet, VOC, and COCO data sets under various few-shot detection settings, and it achieves new state-of-the-art results

Fine-scale evaluation of giant panda habitats and countermeasures against the future impacts of climate change and human disturbance (2015-2050): A case study in Ya'an, China

© 2018 by the authors. The accelerating impact of climate change on giant panda (Ailuropoda melanoleuca) habitats have become an international research topic. Recently, many studies have also focused on medium-sized mountain ranges or entire giant panda habitats to predict how habitats will change as the climate warms, but few say in detail what to do or where to focus efforts. To fill this gap, this paper presents a new method to take comprehensive, fine-scale evaluations incorporating climate change, human disturbance, and current conservation networks and translate them into practical countermeasures in order to help decision-makers set priority regions for conservation. This study looked at the core area of the Sichuan Giant Panda Sanctuaries United Nations Educational, Scientific and Cultural Organisation (UNESCO)World Natural Heritage site, namely Ya'an Prefecture, as a case study. The research employs the Maximum Entropy (MaxEnt) modeling algorithm to analyze how climate change will affect the habitats by 2050 under two scenarios: only considering the influence of climate change, and thinking about the coupled influence of climate change and human disturbance together. The results showed the following: (1) only considering climate change, the overall habitat that can be used by giant pandas in this region will increase, which differs from most of the previous results showing a decrease; (2) the new suitable habitat will shift westward, northward and eastward in this region; (3) conversely, the suitable habitat will be significantly reduced (about 58.56%) and fragmentized when taking into account human disturbance factors; (4) at present, the three small nature reserves are far from each other and cannot cover the present habitat well nor protect the potentially suitable habitats. Based on the comprehensive analysis of habitat shifts and our two field investigations, we suggest two regions that can be expanded into the conservation network to contain more potentially suitable habitats in the future. Furthermore, we used a geographical information system to incorporate high-resolution remote-sensing images from the GF-1 satellite, land-cover maps, and a digital elevation model (DEM) to verify the possibility of our two suggested regions

Integrative analyses of transcriptome sequencing identify novel functional lncRNAs in esophageal squamous cell carcinoma.

Long non-coding RNAs (lncRNAs) have a critical role in cancer initiation and progression, and thus may mediate oncogenic or tumor suppressing effects, as well as be a new class of cancer therapeutic targets. We performed high-throughput sequencing of RNA (RNA-seq) to investigate the expression level of lncRNAs and protein-coding genes in 30 esophageal samples, comprised of 15 esophageal squamous cell carcinoma (ESCC) samples and their 15 paired non-tumor tissues. We further developed an integrative bioinformatics method, denoted URW-LPE, to identify key functional lncRNAs that regulate expression of downstream protein-coding genes in ESCC. A number of known onco-lncRNA and many putative novel ones were effectively identified by URW-LPE. Importantly, we identified lncRNA625 as a novel regulator of ESCC cell proliferation, invasion and migration. ESCC patients with high lncRNA625 expression had significantly shorter survival time than those with low expression. LncRNA625 also showed specific prognostic value for patients with metastatic ESCC. Finally, we identified E1A-binding protein p300 (EP300) as a downstream executor of lncRNA625-induced transcriptional responses. These findings establish a catalog of novel cancer-associated functional lncRNAs, which will promote our understanding of lncRNA-mediated regulation in this malignancy

Search for Light Weakly-Interacting-Massive-Particle Dark Matter by Annual Modulation Analysis with a Point-Contact Germanium Detector at the China Jinping Underground Laboratory

We present results on light weakly interacting massive particle (WIMP) searches with annual modulation (AM) analysis on data from a 1-kg mass $p$-type point-contact germanium detector of the CDEX-1B experiment at the China Jinping Underground Laboratory. Datasets with a total live time of 3.2 yr within a 4.2 yr span are analyzed with analysis threshold of 250 eVee. Limits on WIMP-nucleus (${\chi}$-$N$) spin-independent cross sections as function of WIMP mass ($m_{\chi}$) at 90\% confidence level (C.L.) are derived using the dark matter halo model. Within the context of the standard halo model, the 90\% C.L. allowed regions implied by the DAMA/LIBRA and CoGeNT AM-based analysis are excluded at $>$99.99\% and 98\% C.L., respectively. These results correspond to the best sensitivity at $m_{\chi}$$<$6$~{\rm GeV}/c^2$ among WIMP AM measurements to date.Comment: 5 pages, 4 figure

Limits on Light Weakly Interacting Massive Particles from the First 102.8 kg ×{\times} day Data of the CDEX-10 Experiment

We report the first results of a light weakly interacting massive particles (WIMPs) search from the CDEX-10 experiment with a 10 kg germanium detector array immersed in liquid nitrogen at the China Jinping Underground Laboratory with a physics data size of 102.8 kg day. At an analysis threshold of 160 eVee, improved limits of 8 $\times 10^{-42}$ and 3 $\times 10^{-36}$ cm$^{2}$ at a 90\% confidence level on spin-independent and spin-dependent WIMP-nucleon cross sections, respectively, at a WIMP mass ($m_{\chi}$) of 5 GeV/${c}^2$ are achieved. The lower reach of $m_{\chi}$ is extended to 2 GeV/${c}^2$.Comment: 5 pages, 4 figure

Constraints on Spin-Independent Nucleus Scattering with sub-GeV Weakly Interacting Massive Particle Dark Matter from the CDEX-1B Experiment at the China Jin-Ping Laboratory

We report results on the searches of weakly interacting massive particles (WIMPs) with sub-GeV masses ($m_{\chi}$) via WIMP-nucleus spin-independent scattering with Migdal effect incorporated. Analysis on time-integrated (TI) and annual modulation (AM) effects on CDEX-1B data are performed, with 737.1 kg$\cdot$day exposure and 160 eVee threshold for TI analysis, and 1107.5 kg$\cdot$day exposure and 250 eVee threshold for AM analysis. The sensitive windows in $m_{\chi}$ are expanded by an order of magnitude to lower DM masses with Migdal effect incorporated. New limits on $\sigma_{\chi N}^{\rm SI}$ at 90\% confidence level are derived as $2\times$10$^{-32}\sim7\times$10$^{-35}$ $\rm cm^2$ for TI analysis at $m_{\chi}\sim$ 50$-$180 MeV/$c^2$, and $3\times$10$^{-32}\sim9\times$10$^{-38}$ $\rm cm^2$ for AM analysis at $m_{\chi}\sim$75 MeV/$c^2-$3.0 GeV/$c^2$.Comment: 5 pages, 4 figure

Measurements of J/ψJ/\psi and ψ(2S)\psi(2S) decays into ΛΛˉπ0\Lambda \bar{\Lambda}\pi^0 and ΛΛˉη\Lambda \bar{\Lambda}\eta

Using 58 million $J/\psi$ and 14 million $\psi(2S)$ events collected by the BESII detector at the BEPC, branching fractions or upper limits for the decays $J/\psi$ and $\psi(2S) \to \Lambda \bar{\Lambda}\pi^0$ and $\Lambda \bar{\Lambda}\eta$ are measured. For the isospin violating decays, the upper limits are determined to be ${\cal B}(J/\psi \to \Lambda \bar{\Lambda}\pi^0)<6.4\times 10^{-5}$ and ${\cal B}(\psi(2S) \to \Lambda \bar{\Lambda}\pi^0)<4.9\times 10^{-5}$ at the 90% confidence level. The isospin conserving process $J/\psi \to \Lambda \bar{\Lambda}\eta$ is observed for the first time, and its branching fraction is measured to be ${\cal B}(J/\psi \to \Lambda \bar{\Lambda}\eta)=(2.62\pm 0.60\pm 0.44)\times 10^{-4}$, where the first error is statistical and the second one is systematic. No $\Lambda \bar{\Lambda}\eta$ signal is observed in $\psi(2S)$ decays, and ${\cal B}(\psi(2S) \to \Lambda \bar{\Lambda}\eta)<1.2\times 10^{-4}$ is set at the 90% confidence level. Branching fractions of $J/\psi$ decays into $\Sigma^+ \pi^- bar{\Lambda}$ and $\bar{\Sigma}^- \pi^+ \Lambda$ are also reported, and the sum of these branching fractions is determined to be ${\cal B}(J/\psi \to \Sigma^+\pi^- \bar{\Lambda} + c.c.)=(1.52\pm 0.08\pm 0.16)\times 10^{-3}$.Comment: 7 pages, 10 figures. Phys.Rev.D comments considere