The class IA phosphatidylinositol 3-kinase p110-β subunit is a positive regulator of autophagy

p110-β associates with the Vps34–Vps15–Beclin 1–Atg14L complex and facilitates generation of PtdIns(3)P to promote autophagy

Seizing the window of opportunity to mitigate the impact of climate change on the health of Chinese residents

The health threats posed by climate change in China are increasing rapidly. Each province faces different health risks. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate and even prevent the achievement of the Healthy and Beautiful China initiatives. The 2021 China Report of the Lancet Countdown on Health and Climate Change is the first annual update of China’s Report of the Lancet Countdown. It comprehensively assesses the impact of climate change on the health of Chinese households and the measures China has taken. Invited by the Lancet committee, Tsinghua University led the writing of the report and cooperated with 25 relevant institutions in and outside of China. The report includes 25 indicators within five major areas (climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement) and a policy brief. This 2021 China policy brief contains the most urgent and relevant indicators focusing on provincial data: The increasing health risks of climate change in China; mixed progress in responding to climate change. In 2020, the heatwave exposures per person in China increased by 4.51 d compared with the 1986–2005 average, resulting in an estimated 92% increase in heatwave-related deaths. The resulting economic cost of the estimated 14500 heatwave-related deaths in 2020 is US$176 million. Increased temperatures also caused a potential 31.5 billion h in lost work time in 2020, which is equivalent to 1.3% of the work hours of the total national workforce, with resulting economic losses estimated at 1.4% of China’s annual gross domestic product. For adaptation efforts, there has been steady progress in local adaptation planning and assessment in 2020, urban green space growth in 2020, and health emergency management in 2019. 12 of 30 provinces reported that they have completed, or were developing, provincial health adaptation plans. Urban green space, which is an important heat adaptation measure, has increased in 18 of 31 provinces in the past decade, and the capacity of China’s health emergency management increased in almost all provinces from 2018 to 2019. As a result of China’s persistent efforts to clean its energy structure and control air pollution, the premature deaths due to exposure to ambient particulate matter of 2.5 μm or less (PM2.5) and the resulting costs continue to decline. However, 98% of China’s cities still have annual average PM2.5 concentrations that are more than the WHO guideline standard of 10 μg/m3. It provides policymakers and the public with up-to-date information on China’s response to climate change and improvements in health outcomes and makes the following policy recommendations. (1) Promote systematic thinking in the related departments and strengthen multi-departmental cooperation. Sectors related to climate and development in China should incorporate health perspectives into their policymaking and actions, demonstrating WHO’s and President Xi Jinping’s so-called health-in-all-policies principle. (2) Include clear goals and timelines for climate-related health impact assessments and health adaptation plans at both the national and the regional levels in the National Climate Change Adaptation Strategy for 2035. (3) Strengthen China’s climate mitigation actions and ensure that health is included in China’s pathway to carbon neutrality. By promoting investments in zero-carbon technologies and reducing fossil fuel subsidies, the current rebounding trend in carbon emissions will be reversed and lead to a healthy, low-carbon future. (4) Increase awareness of the linkages between climate change and health at all levels. Health professionals, the academic community, and traditional and new media should raise the awareness of the public and policymakers on the important linkages between climate change and health.</p

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Characteristics of Breaking Wave Forces on Piles over a Permeable Seabed

Most offshore wind turbines are installed in shallow water and exposed to breaking waves. Previous numerical studies focusing on breaking wave forces generally ignored the seabed permeability. In this paper, a numerical model based on Volume-Averaged Reynolds Averaged Navier–Stokes equations (VARANS) is employed to reveal the process of a solitary wave interacting with a rigid pile over a permeable slope. Through applying the Forchheimer saturated drag equation, effects of seabed permeability on fluid motions are simulated. The reliability of the present model is verified by comparisons between experimentally obtained data and the numerical results. Further, 190 cases are simulated and the effects of different parameters on breaking wave forces on the pile are studied systematically. Results indicate that over a permeable seabed, the maximum breaking wave forces can occur not only when waves break just before the pile, but also when a “secondary wave wall” slams against the pile, after wave breaking. With the initial wave height increasing, breaking wave forces will increase, but the growth can decrease as the slope angle and permeability increase. For inclined piles around the wave breaking point, the maximum breaking wave force usually occurs with an inclination angle of α = −22.5° or 0°

Refractory high-entropy alloys fabricated by powder metallurgy: Progress, challenges and opportunities

Refractory high-entropy alloys, which involve the mixing of four or more refractory metal elements in an equiatomic or near-equiatomic ratio, hold significant potential for various applications in high-temperature materials fields. This is mainly due to their stable phase structure and excellent high-temperature properties. While considerable interest has been in these alloys, most of them have been developed using melting casting technology. However, powder metallurgy has emerged as a promising alternative for further advancement in this field. It has the potential to expand the application areas and enhance the properties of these alloys. This article introduces to various techniques for fabricating pre-alloyed refractory high-entropy powders and their densification. Additionally, it reviews the methods for regulating the microstructure and properties of powder metallurgy refractory high-entropy alloys

Distributed Economic Dispatch Scheme for Droop-Based Autonomous DC Microgrid

In this paper, a distributed economic dispatch scheme considering power limit is proposed to minimize the total active power generation cost in a droop-based autonomous direct current (DC) microgrid. The economical dispatch of the microgrid is realized through a fully distributed hierarchical control. In the tertiary level, an incremental cost consensus-based algorithm embedded into the economical regulator is utilized to search for the optimal solution. In the secondary level, the voltage regulator estimating the average voltage of the DC microgrid is used to generate the voltage correction item and eliminate the power and voltage oscillation caused by the deviation between different items. Then, the droop controller in the primary level receives the reference values from the upper level to ensure the output power converging to the optimum while recovering the average voltage of the system. Further, the dynamic model is established and the optimal communication network topology minimizing the impact of time delay on the voltage estimation is given in this paper. Finally, a low-voltage DC microgrid simulation platform containing different types of distributed generators is built, and the effectiveness of the proposed scheme and the performance of the optimal topology are verified

Predicting passengers in public transportation using smart card data

Transit prediction has long been a hot research problem, which is central to the public transport agencies and operators, as evidence to support scheduling and urban planning. There are several previous work aiming at transit prediction, but they are all from the macro perspective. In this paper, we study the prediction of individuals in the context of public transport. Existing research on the prediction of individual behaviour are mostly found in information retrieval and recommender systems, leaving it untouched in the area of public transport. We propose a NLP based back-propagation neural network for the prediction job in this paper. Specifically, we adopt the concept of “bag of words” to build user profile, and use the result of clustering as input of back-propagation neural network to generate predictions. To illustrate the effectiveness of our method, we conduct an extensive set of experiments on a dataset from public transport fare collecting system. Our detailed experimental evaluation demonstrates that our method gets good performance on predicting public transport individuals

Realistic Image Rendition Using a Variable Exponent Functional Model for Retinex

The goal of realistic image rendition is to recover the acquired image under imperfect illuminant conditions, where non–uniform illumination may degrade image quality with high contrast and low SNR. In this paper, the assumption regarding illumination is modified and a variable exponent functional model for Retinex is proposed to remove non–uniform illumination and reduce halo artifacts. The theoretical derivation is provided and experimental results are presented to illustrate the effectiveness of the proposed model