87 research outputs found

    Analysis of Fungal System Decomposition Ability under Ka-Volterra Model

    Get PDF
    Differential equations are used to describe the decomposition ability of fungi and systems with multiple species under the influence of various factors. These factors include characteristics of the fungus itself, such as mycelium elongation, water tolerance, interactions between fungal populations, and the effects of the external environment. With reference to the classical population model and the Karvolterra differential equation model, the research made a further extension on these two models to describe the change of the population size along with the time and the decomposition ability of different species of fungi by adding a series of influencing factors to the equation. The effect of the interaction between various fungi on the decomposition rate was considered. Finally, we describe the trend of the overall decomposing ability of the system under the external environment. In summary, our model starts from initial models that describe populations of different species and the wood decomposition capacity of fungi under the influence of various factors, and simulates the wood decomposition capacity of a realistic polyfungal system on a given land

    Emm type distribution of group A Streptococcus in China during 1990 and 2020: a systematic review and implications for vaccine coverage

    Get PDF
    BackgroundThe recent increase of group A Streptococcus (GAS) infections in Europe has aroused global concern. We aim to provide molecular biological data for GAS prevention and control in China by analyzing the temporal shift of emm type.MethodsWe collected studies reporting GAS emm types in China from 1990 to 2020 by PRISMA statement and established a summary database including emm types and literature quality assessment. Based on the database we analyzed the geographic distribution of emm types from 1990 to 2020 and assessed the coverage of the known GAS 30-valent vaccine. Outbreak-associated emm types that had been reported over the past 30 years were also included.Results47 high quality studies were included for a systematic analysis of emm type distribution. This generated a database including totally 12,347 GAS isolates and 85 emm types. Shift of dominant emm type was witnessed during the past 30 years in China. In mainland China, dominant types changed from emm3, emm1, emm4, emm12 in 1990s to emm12 and emm1 in 2000s and 2010s. Hong Kong and Taiwan were dominated by emm12, emm4 and emm1, of which emm4 reduced but emm12 increased in 2010s significantly. From 1990 to 2020, newly found emm types were increasingly reported in various regions of China. The reported 30-valent M protein vaccine covered 26 M types prevalent in China, including all dominant types

    Pix2HDR -- A pixel-wise acquisition and deep learning-based synthesis approach for high-speed HDR videos

    Full text link
    Accurately capturing dynamic scenes with wide-ranging motion and light intensity is crucial for many vision applications. However, acquiring high-speed high dynamic range (HDR) video is challenging because the camera's frame rate restricts its dynamic range. Existing methods sacrifice speed to acquire multi-exposure frames. Yet, misaligned motion in these frames can still pose complications for HDR fusion algorithms, resulting in artifacts. Instead of frame-based exposures, we sample the videos using individual pixels at varying exposures and phase offsets. Implemented on a pixel-wise programmable image sensor, our sampling pattern simultaneously captures fast motion at a high dynamic range. We then transform pixel-wise outputs into an HDR video using end-to-end learned weights from deep neural networks, achieving high spatiotemporal resolution with minimized motion blurring. We demonstrate aliasing-free HDR video acquisition at 1000 FPS, resolving fast motion under low-light conditions and against bright backgrounds - both challenging conditions for conventional cameras. By combining the versatility of pixel-wise sampling patterns with the strength of deep neural networks at decoding complex scenes, our method greatly enhances the vision system's adaptability and performance in dynamic conditions.Comment: 14 pages, 14 figure

    ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints

    Full text link
    Recent studies have demonstrated that visual recognition models lack robustness to distribution shift. However, current work mainly considers model robustness to 2D image transformations, leaving viewpoint changes in the 3D world less explored. In general, viewpoint changes are prevalent in various real-world applications (e.g., autonomous driving), making it imperative to evaluate viewpoint robustness. In this paper, we propose a novel method called ViewFool to find adversarial viewpoints that mislead visual recognition models. By encoding real-world objects as neural radiance fields (NeRF), ViewFool characterizes a distribution of diverse adversarial viewpoints under an entropic regularizer, which helps to handle the fluctuations of the real camera pose and mitigate the reality gap between the real objects and their neural representations. Experiments validate that the common image classifiers are extremely vulnerable to the generated adversarial viewpoints, which also exhibit high cross-model transferability. Based on ViewFool, we introduce ImageNet-V, a new out-of-distribution dataset for benchmarking viewpoint robustness of image classifiers. Evaluation results on 40 classifiers with diverse architectures, objective functions, and data augmentations reveal a significant drop in model performance when tested on ImageNet-V, which provides a possibility to leverage ViewFool as an effective data augmentation strategy to improve viewpoint robustness.Comment: NeurIPS 202

    Advancing the understanding of variations of Arctic sea ice optical and thermal behaviors through an international research and mobility project

    Get PDF
    In recent decades, significant changes of Arctic sea ice have taken place. These changes are expected to influence the surface energy balance of the ice-covered Arctic Ocean. To quantify this energy balance and to increase our understanding of mechanisms leading to observed changes in the Arctic sea ice, the project “Advancing Modelling and Observing solar Radiation of Arctic sea ice—understanding changes and processes (AMORA)” was initiated and conducted from 2009 to 2013. AMORA was funded and organized under a frame of Norway-China bilateral collaboration program with partners from Finland, Germany, and the USA. The primary goal of the project was achieved by developing an autonomous spectral radiation buoy, deploying it on drifting sea ice close to the North Pole, and receiving a high-resolution time series of spectral radiation over and under sea ice from spring (before melt onset) to autumn (after freeze-up) 2012. Beyond this, in-situ sea ice data were collected during several field campaigns and simulations of snow and sea ice thermodynamics were performed. More autonomous measurements are available through deployments of sea ice mass balance buoys. These new observational data along with numerical model studies are helping us to better understand the key thermodynamic processes of Arctic sea ice and changes in polar climate. A strong scientific, but also cultural exchange between Norway, China, and the partners from the USA and Europe initiated new collaborations in Arctic reseach

    Wielding the sword: President Xi’s new anti-corruption campaign

    Get PDF
    A state achieves legitimacy through multiple sources, one of which is the effectiveness of its governance. Generations of scholars since Hobbes have identified the maintenance of peace and order as core functions of a legitimate state. In the modern world, economic prosperity, social stability and effective control of corruption often provide adequate compensation for a deficit of democracy. Corruption closely correlates with legitimacy. While a perceived pervasive, endemic corruption undermines the legitimacy of a regime, a successful anti-corruption campaign can allow a regime to recover from a crisis of legitimacy (Gilley 2009; Seligson and Booth 2009). This is the rationale behind the periodical campaigns against corruption that have been conducted by the Chinese Communist Party (‘Party’ or ‘CCP’) (Manion 2004; Wedeman 2012). Political leaders in China have found it expedient to use anti-corruption campaigns to remove their political foes, to rein in the bureaucracy and to restore public confidence in their ability to rule. Through anti-corruption campaigns, emerging political leaders consolidate their political power, secure loyalty from political factions and regional political forces, and enhance their legitimacy in the eyes of the general public. In an authoritarian state that experiences a high level of corruption, an anti-corruption campaign is a delicate political battle that addresses two significant concerns. The first concern is to orchestrate the campaign so that it is regime-reinforcing instead of regime-undermining. To remain credible, the regime must demonstrate its willingness and capacity to punish corrupt officials at the highest levels.preprin

    Antenatal depression is associated with perceived stress, family relations, educational and professional status among women in South of China: a multicenter cross-sectional survey

    Get PDF
    BackgroundAntenatal depression is a commonly seen mental health concern for women. This study introduced a multicenter cross-sectional survey with a large sample to provide new insights into pregnant women’s depression, its socio-demographic and obstetric characteristics correlates, and its perceived stress among Chinese pregnant women.MethodsThis study conducted an observational survey according to the STROBE checklist. The multicenter cross-sectional survey was performed from August 2020 to January 2021 by distributing paper questionnaires among pregnant women from five tertiary hospitals in South China. The questionnaire included socio-demographic and obstetrics information, the Edinburgh Postnatal Depression Scale, and the 10-item Perceived Stress Scale. For the analyses, the Chi-square test and Multivariate logistic regression were utilized.ResultsAmong 2014 pregnant women in their second/third trimester, the prevalence of antenatal depression was 36.3%. 34.4% of pregnant women reported AD in their second trimester of pregnancy, and 36.9% suffered from AD in third trimester of pregnancy. A multivariate logistic regression model indicated that unemployed women, lower levels of education, poor marital relationships, poor parents-in-law relationships, concerns about contracting COVID-19, and higher perceived stress could aggravate antenatal depression among participants (p<0.05).ConclusionThere is a high proportion of antenatal depression among pregnant women in South China, so integrating depression screening into antenatal care services is worthwhile. Maternal and child health care providers need to evaluate pregnancy-related risk factors (perceived stress), socio-demographic factors (educational and professional status), and interpersonal risk factors (marital relations and relationship with Parents-in-law). In future research, the study also emphasized the importance of providing action and practical support to reduce the experience of antenatal depression among disadvantaged sub-groups of pregnant women
    corecore