Open physical systems with balanced loss and gain, described by non-Hermitian parity-time Formula: see text reflection symmetric Hamiltonians, exhibit a transition which could engender modes that ...exponentially decay or grow with time, and thus spontaneously breaks the Formula: see text-symmetry. Such Formula: see text-symmetry-breaking transitions have attracted many interests because of their extraordinary behaviors and functionalities absent in closed systems. Here we report on the observation of Formula: see text-symmetry-breaking transitions by engineering time-periodic dissipation and coupling, which are realized through state-dependent atom loss in an optical dipole trap of ultracold
Li atoms. Comparing with a single transition appearing for static dissipation, the time-periodic counterpart undergoes Formula: see text-symmetry breaking and restoring transitions at vanishingly small dissipation strength in both single and multiphoton transition domains, revealing rich phase structures associated to a Floquet open system. The results enable ultracold atoms to be a versatile tool for studying Formula: see text-symmetric quantum systems.
•The total amount of SO2 emissions was selected as the study object.•Three direct factors driving the emissions were detected.•Total energy consumption increased the emissions most.•Treatment ...technology inhibited the emissions most.•Lowering energy use and updating energy structure would have great potential.
Air pollution is increasingly a focus of concern worldwide due to its adverse impacts on human health and profound influences on global ecosystem. Although the existing studies have paid much attention to the causes of pollutant emissions, they fail to distinguish between direct and indirect factors, yielding the mixed results. Direct causes denote energy-related factors, as air pollutants are mainly produced by energy utilization directly, while indirect elements refer to socio-economic factors, as these factors act on pollutant emissions through affecting energy-related aspects. This paper investigated the impacts of three dominant direct factors: total energy consumption (EC), energy structure (ES) and treatment technology (TT) on sulfur dioxide (SO2) emissions in China during 1995–2014 using the logarithmic mean Divisia Index method. Distinguished from the previous studies which took particular interest in SO2 emissions from the industrial sector, this study put the total amount of SO2 emissions as the target. The results show that increased EC was the main reason for SO2 enhancement, while increasingly advanced TT played a dominant role in inhibiting the emissions throughout the study period. In contrast, ES had an unusually slight effect on SO2 emissions due to its minor variation in the meantime. On regional scale, the differences in relative contribution rates (RCRs) of EC, ES and TT among the eastern, central and western regions all gradually decreased over time; EC in central region had the largest improved effect, ES in eastern region held the greatest reduction effect, and TT in western region got the biggest inhibitory effect. At provincial level, most provinces (60%) had relatively quick EC growth and slow ES adjustment (i.e., reducing the coal consumption rate); only Beijing, Tianjin, Shanghai and Sichuan had a relatively slow growth of EC and quick decrease in the percentage of coal consumption. Further, the projection of SO2 emissions in four scenarios from 2015 to 2020 based on a grey projection model indicated that controlling both EC and ES would be the most efficient approach to SO2 abatement followed by individually controlling EC and ES.
This paper presents optimal sizing algorithms of grid-connected photovoltaic-battery system for residential houses. The objective is to minimize the total annual cost of electricity. The proposed ...methodology is based on a genetic algorithm involving a time series simulation of the entire system and is validated using data collected through one year. Genetic algorithm jointly optimises the sizes of the photovoltaic and the battery systems by adjusting the battery charge and discharge cycles according to the availability of solar resource and a time-of-use tariff structure for electricity. Houses without pre-existing solar systems are considered. The results show that jointly optimizing the sizing of battery and photovoltaic systems can significantly reduce electricity imports and the cost of electricity for the household. However, the optimal capacity of such photovoltaic battery varies strongly with the electricity consumption profile of the household, and is also affected by electricity and battery prices. Besides individual PV generation and battery storage for each house, this paper also investigates group battery optimizations for communities with different consumption levels or with different energy demand diversity to see their effects on optimal sizing and peak demands for aggregated PV-battery system.
•We investigate the optimal sizing problem of PV and battery with purpose of maximization of economic benefit received by the use for grid-connected PV-battery system, i.e., the minimization of the annual energy related costs of the household while at the same time satisfying the load demand. The optimization is Genetic Algorithm (GA) based, formulated in terms of annual energy related cost, which includes the cost of electricity, the cost and technical capabilities of PV and battery systems, and the energy usage profiles of real users in the state of New South Wales, Australia. The optimization also takes into account variable electricity price through the day in a time-of-use (TOU) tariff structure split into peak, shoulder, and off peak periods.
Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and ...identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.
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•AI system that can diagnose COVID-19 pneumonia using CT scans•Prediction of progression to critical illness•Potential to improve performance of junior radiologists to the senior level•Can assist evaluation of drug treatment effects with CT quantification
Zhang et al. present an AI-based system, based on hundreds of thousands of human lung CT scan images, that can aid in distinguishing patients NCP versus other common pneumonia and can help to predict the prognosis of COVID-19 patients.
China has received increased international criticism in recent years in relation to its air pollution levels, both in terms of the transmission of pollutants across international borders and the ...attendant adverse health effects being witnessed. Whilst existing research has examined the factors influencing ambient air pollutant concentrations, previous studies have failed to adequately explore the determinants of such concentrations from either a source or diffusion perspective. This study addressed both source (specifically, anthropogenic emissions) and diffusion (namely, meteorological conditions) indicators, in order to detect their respective impacts on the spatial variations seen in the distribution of air pollution. Spatial panel data for 113 major cities in China was processed using a range of global regression models—the ordinary least square model, the spatial lag model, and the spatial error model—as well as a local, geographic weighted regression (GWR) model. Results from the study suggest that in 2014, average SO2 concentrations exceeded China's first-level target. The most polluted cities were found to be predominantly located in northern China, while less polluted cities were located in southern China. Global regression results indicated that precipitation exerts a significant effect on SO2 reduction (p<0.001) and that a regional increase of 1mm in precipitation can reduce SO2 concentrations by 0.026μg/m3. Both emission and temperature factors were found to aggravate SO2 concentrations, although no such significant correlation was found in relation to wind speed. GWR results suggest that the association between SO2 and its factors varied over space. Increased emissions were found to be able to produce more pollution in the northwest than in other parts of the country. Higher wind speeds and temperatures in northwestern areas were shown to reinforce SO2 pollution, while in southern regions, they had the opposite effect. Further, increased precipitation was found to exert a greater inhibitory effect on SO2 pollution in the country's northeast than that in other areas. Our findings could provide a detailed reference for formulating regionally specific emission reduction policies in China.
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•Both source and diffusion factors were used to detect their impacts on SO2 pollution.•Emissions and meteorological conditions were seen as the two types of drivers.•A regional increase of 1mm in precipitation could reduce SO2 by 0.026μg/m3 in China.•Increased emissions could produce more pollution in the northwest than in others.•Higher temperature inhibited SO2 in the southeast, but opposite in the northwest.
Cyberspace has become an indispensable factor for all areas of the modern world. The world is becoming more and more dependent on the internet for everyday living. The increasing dependency on the ...internet has also widened the risks of malicious threats. On account of growing cybersecurity risks, cybersecurity has become the most pivotal element in the cyber world to battle against all cyber threats, attacks, and frauds. The expanding cyberspace is highly exposed to the intensifying possibility of being attacked by interminable cyber threats. The objective of this survey is to bestow a brief review of different machine learning (ML) techniques to get to the bottom of all the developments made in detection methods for potential cybersecurity risks. These cybersecurity risk detection methods mainly comprise of fraud detection, intrusion detection, spam detection, and malware detection. In this review paper, we build upon the existing literature of applications of ML models in cybersecurity and provide a comprehensive review of ML techniques in cybersecurity. To the best of our knowledge, we have made the first attempt to give a comparison of the time complexity of commonly used ML models in cybersecurity. We have comprehensively compared each classifier’s performance based on frequently used datasets and sub-domains of cyber threats. This work also provides a brief introduction of machine learning models besides commonly used security datasets. Despite having all the primary precedence, cybersecurity has its constraints compromises, and challenges. This work also expounds on the enormous current challenges and limitations faced during the application of machine learning techniques in cybersecurity.
Temperature-dependent photoluminescence (PL) properties of inorganic perovskite CsPbBr
3
nanocrystal (NC) films were studied by using steady-state and time-resolved PL spectroscopy. The closely ...packed solid films were obtained by dropping NC solution on silicon substrates. It was found that the PL intensities of the NC films, which are dependent on the size of NCs, slightly decreased with increasing temperature to 300 K, while the PL intensities dropped rapidly with increasing temperature above 300 K and were nearly quenched at 360 K. Further the corresponding average PL lifetimes increased significantly with increasing temperature below about 320 K and then significantly became shorter. The PL quenching mechanisms were demonstrated through heating and cooling experiments. The experimental results indicated inorganic perovskite NCs exhibited a thermal PL quenching in the temperature range of 80-300 K and a thermal degradation at temperatures above 300 K. The linewidths, peak energies, and lifetimes of PL emissions for the NC films as a function of temperature were discussed in detail.
The photoluminescence stability of all-inorganic perovskite nanocrystals (CsPbBr
3
) with different size is studied.
Reasonable production capacity is related to the economic benefits of an open-pit coal mine. This study analyzes the relationship between the working face length, the annual advancing speed and the ...production capacity. It constructs a production capacity function relationship model. Take the Baorixile open-pit coal mine as an example. The remaining unmined parts are divided into four regions, and the range of production capacity in each region is analyzed by the established model and the determined respectively. On this basis, three mining district division plans are proposed. By analyzing and comparing the stripping ratio, mining life of the district, fault influence, difficulty of transition connection in the mining districts, the convenience of transportation system layout and other indexes of each plan, Plan 3 is determined to be the optimal plan. The production capacity planning results of each mining district in this plan are as follows: the production capacity of the 3rd mining district is 30-35 Mt/a; the production capacity of the 4th mining district in Region 1 is 20-31 Mt/a, and the production capacity in Region 2 is 24-33 Mt/a; the production capacity of the 5th mining district is 20-27 Mt/a.
Porous single crystal has the characteristics of long-range order, continuous lattice and large specific surface area, which could reduce energy losses and keep high activity and stability in ...electrochemical systems. Here, we grow porous single-crystalline and polycrystalline molybdenum nitrides microcubes from MoO3 single crystals. These porous microcubes show superior HER and OER performance. The overpotential of Mo2N porous single crystal microcubes is only 73.13 mV at a current density of 10 mA cm−2, which is 150.53 mV, 192.76 mV and 255.87 mV lower than that of MoN single crystal, Mo2N polycrystal and MoN polycrystal, respectively. The advantages of Mo2N porous single crystals in electrocatalytic properties are also reflected in OER.
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•A new way to synthesize porous single crystals of molybdenum nitrides.•Molybdenum nitrides have a good performance in HER.•Porous single crystal performs high activity and stability in HER and OER.
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