A photon counting reconstructive spectrometer combining metasurfaces and superconducting nanowire single-photon detectors

Faint light spectroscopy has many important applications such as fluorescence spectroscopy, lidar and astronomical observations. However, long measurement time limit its application on real-time measurement. In this work, a photon counting reconstructive spectrometer combining metasurfaces and superconducting nanowire single photon detectors (SNSPDs) was proposed. A prototype device was fabricated on a silicon on isolator (SOI) substrate, and its performance was characterized. Experiment results show that this device support spectral reconstruction of mono-color lights with a resolution of 2 nm in the wavelength region of 1500 nm ~ 1600 nm. The detection efficiency of this device is 1.4% ~ 3.2% in this wavelength region. The measurement time required by this photon counting reconstructive spectrometer was also investigated experimentally, showing its potential to be applied in the scenarios requiring real-time measurement

Slower-decaying tropical cyclones produce heavier precipitation over China

The post-landfall decay of tropical cyclones (TC) is often closely linked to the magnitude of damage to the environment, properties, and the loss of human lives. Despite growing interest in how climate change affects TC decay, data uncertainties still prevent a consensus on changes in TC decay rates and related precipitation. Here, after strict data-quality control, we show that the rate of decay of TCs after making landfall in China has significantly slowed down by 45% from 1967 to 2018. We find that, except the warmer sea surface temperature, the eastward shift of TC landfall locations also contributes to the slowdown of TC decay over China. That is TCs making landfall in eastern mainland China (EC) decay slower than that in southern mainland China (SC), and the eastward shift of TCs landfall locations causes more TCs landfalling in EC with slower decay rate. TCs making landfall in EC last longer at sea, carry more moisture upon landfall, and have more favorable dynamic and thermodynamic conditions sustaining them after landfall. Observational evidence shows that the decay of TC-induced precipitation amount and intensity within 48 h of landfall is positively related to the decay rate of landfalling TCs. The significant increase in TC-induced precipitation over the long term, due to the slower decay of landfalling TCs, increases flood risks in China’s coastal areas. Our results highlight evidence of a slowdown in TC decay rates at the regional scale. These findings provide scientific support for the need for better flood management and adaptation strategies in coastal areas under the threat of greater TC-induced precipitation

Stomatal response to decreased relative humidity constrains the acceleration of terrestrial evapotranspiration

Terrestrial evapotranspiration (ET) is thermodynamically expected to increase with increasing atmospheric temperature; however, the actual constraints on the intensification of ET remain uncertain due to a lack of direct observations. Based on the FLUXNET2015 Dataset, we found that relative humidity (RH) is a more important driver of ET than temperature. While actual ET decrease at reduced RH, potential ET increases, consistently with the complementary relationship (CR) framework stating that the fraction of energy not used for actual ET is dissipated as increased sensible heat flux that in turn increases potential ET. In this study, we proposed an improved CR formulation requiring no parameter calibration and assessed its reliability in estimating ET both at site-level with the FLUXNET2015 Dataset and at basin-level. Using the ERA-Interim meteorological dataset for 1979-2017 to calculate ET, we found that the global terrestrial ET showed an increasing trend until 1998, while the trend started to decline afterwards. Such decline was largely associated with a reduced RH, inducing water stress conditions that triggered stomatal closure to conserve water. For the first time, this study quantified the global-scale implications of changes in RH on terrestrial ET, indicating that the temperature-driven acceleration of the terrestrial water cycle will be likely constrained by terrestrial vegetation feedbacks.Peer reviewe

Health Consequences Among COVID-19 Convalescent Patients 30 Months Post-Infection in China

The health consequences among COVID-19 convalescent patients 30 months post-infection were described and the potential risk factors were determined. In August 2022 we recruited 217 COVID-19 convalescent patients who had been diagnosed with COVID-19 in February 2020. These convalescent patients were residents of multiple districts in Wuhan, China. All convalescent patients completed a detailed questionnaire, laboratory testing, a 6-min walk test, a Borg dyspnea scale assessment, lung function testing, and had a chest CT. The potential risk factors for health consequences among COVID-19 convalescent patients 30 months post-infection were identified using a multivariate logistic regression model. The majority of convalescent patients were in good overall health and returned to work 30 months post-infection; however, 62.2% of the convalescent patients had long COVID symptoms. The most common symptoms were chest pain, fatigue, and dizziness or headaches. The convalescent patients with severe symptoms had a significantly higher proportion of depression disorder ( P = 0.044) and lower health-related quality of life ( P = 0.034) compared to the convalescent patients with mild symptoms. Compared to convalescent patients who were not vaccinated, convalescent patients who received three vaccines had significantly less fatigue, lower anxiety and depression scores, and had a better health-related quality of life (all P < 0.05). Older age was associated with a higher risk of long COVID (OR = 1.52, 95% CI = 1.16–2.02) and chest CT abnormalities (OR = 1.75, 95% CI = 1.33–2.36). Female gender was associated with a higher risk of anxiety (OR = 3.20, 95% CI = 1.24–9.16) and depression disorders (OR = 2.49, 95% CI = 1.11–5.92). Exercise was associated with a lower risk of anxiety (OR = 0.41, 95% CI = 0.18–0.93). Notably, vaccination protected convalescent patients from developing long COVID symptoms (OR = 0.18, 95% CI = 0.06–0.50), anxiety disorders (OR = 0.22, 95% CI = 0.07–0.71), and depression disorders (OR = 0.33, 95% CI = 0.12–0.92). The majority of COVID-19 convalescent patients were in good overall health 30 months post-infection and returned to work. More attention should be paid to convalescent patients who are older, female, physically inactive, and not vaccinated

PMSM System Controlled by SVM-DTC

Direct Torque Control (DTC), proposed after Vector Control (VC), has been widely used in speed regulation system due to its good dynamic performance. In order to solving the shortage of poor torque stationary properties of traditional DTC, this paper introduces direct torque control using space vector modulations (SVM-DTC) in Permanent Magnet Synchronous Motor (PMSM) system, which reduces torque ripple by using SVM and maintains fast dynamic response. Simulation model of SVM-DTC under MATLAB condition has been set up and compared with system controlled by traditional DTC. The results testify that the PMSM system based on SVM-DTC has high rate dynamic response, high stationary precision, and good robustness when load has a disturbance

PMSM System Controlled by SVM-DTC

Direct Torque Control (DTC), proposed after Vector Control (VC), has been widely used in speed regulation system due to its good dynamic performance. In order to solving the shortage of poor torque stationary properties of traditional DTC, this paper introduces direct torque control using space vector modulations (SVM-DTC) in Permanent Magnet Synchronous Motor (PMSM) system, which reduces torque ripple by using SVM and maintains fast dynamic response. Simulation model of SVM-DTC under MATLAB condition has been set up and compared with system controlled by traditional DTC. The results testify that the PMSM system based on SVM-DTC has high rate dynamic response, high stationary precision, and good robustness when load has a disturbance

MBF: a Real Matrix Bloom Filter Representation Method on Dynamic Set

Bloom Filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries, which uses an m-bit array to represent a data set. In order to support representing dynamic set, dynamic bloom filter (DBF) and split bloom filter (SBF) have been developed Both DBF and SBF can support concisely representation and approximate membership queries of dynamic set instead of static set. SBF declares that it uses an s Xm bit matrix that consists of s bloom filters to represent a dynamic set, so DBF dose. But in fact, both the two bloom filters are not matrix representation method at all. They are just a set of s bloom filters whose length is in, and they have got a departure from the original idea of bloom filter: the constant query time cost. This paper points out the fact, and then introduce a truly matrix representation method of bloom filter to represent a dynamic set. We call it the Matrix Bloom Filter (MBF). Then, we will analysis the algorithm of MBF and study the average time complexity and the false positive probability.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000251390000125&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Computer Science, Hardware &amp; ArchitectureComputer Science, Theory &amp; MethodsEngineering, Electrical &amp; ElectronicCPCI-S(ISTP)

An efficient privacy-preserving scheme with signature aggregation and key updating in smart grid

In comparison with traditional power grid system, smart power grid has the feature of distributed energy control with large amount of information transmission. Because the grid needs to collect users&#39; usage data, privacy becomes a critical issue. Therefore, providing an efficient privacypreserving demand response scheme is vital to smart grid. We propose an efficient privacypreserving demand response scheme achieves confidentiality and integrity. The model transmits both real usage data and the future demand data for analyzing, comparing, and adjusting the generation and usage of electricity. In addition, updating keys can ensure users&#39; data to be forward secrecy, and signature aggregation can reduce computation cost. The performance comparison with another scheme which also achieves key updating, shows that our scheme is more efficient in terms of computation and communication overhead; thus helping users save energy and maintain supply-demand balance.</p