This paper studies federated learning (FL) in a classic wireless network, where learning clients share a common wireless link to a coordinating server to perform federated model training using their ...local data. In such wireless federated learning networks (WFLNs), optimizing the learning performance depends crucially on how clients are selected and how bandwidth is allocated among the selected clients in every learning round, as both radio and client energy resources are limited. While existing works have made some attempts to allocate the limited wireless resources to optimize FL, they focus on the problem in individual learning rounds, overlooking an inherent yet critical feature of federated learning. This paper brings a new long-term perspective to resource allocation in WFLNs, realizing that learning rounds are not only temporally interdependent but also have varying significance towards the final learning outcome. To this end, we first design data-driven experiments to show that different temporal client selection patterns lead to considerably different learning performance. With the obtained insights, we formulate a stochastic optimization problem for joint client selection and bandwidth allocation under long-term client energy constraints, and develop a new algorithm that utilizes only currently available wireless channel information but can achieve long-term performance guarantee. Experiments show that our algorithm results in the desired temporal client selection pattern, is adaptive to changing network environments and far outperforms benchmarks that ignore the long-term effect of FL.
Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as promising techniques in the Internet of Things era to provide massive low-power wireless devices with enhanced ...computation capability and sustainable energy supply. In this paper, we propose a unified MEC-WPT design by considering a wireless powered multiuser MEC system, where a multiantenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute computation tasks. With MEC, these users can execute their respective tasks locally by themselves or offload all or part of them to the AP based on a time-division multiple access protocol. Building on the proposed model, we develop an innovative framework to improve the MEC performance, by jointly optimizing the energy transmit beamforming at the AP, the central processing unit frequencies and the numbers of offloaded bits at the users, as well as the time allocation among users. Under this framework, we address a practical scenario where latency-limited computation is required. In this case, we develop an optimal resource allocation scheme that minimizes the AP's total energy consumption subject to the users' individual computation latency constraints. Leveraging the state-of-the-art optimization techniques, we derive the optimal solution in a semiclosed form. Numerical results demonstrate the merits of the proposed design over alternative benchmark schemes.
A vaccine to protect against COVID-19 is urgently needed. We aimed to assess the safety, tolerability, and immunogenicity of a recombinant adenovirus type-5 (Ad5) vectored COVID-19 vaccine expressing ...the spike glycoprotein of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain.
We did a dose-escalation, single-centre, open-label, non-randomised, phase 1 trial of an Ad5 vectored COVID-19 vaccine in Wuhan, China. Healthy adults aged between 18 and 60 years were sequentially enrolled and allocated to one of three dose groups (5 × 1010, 1 × 1011, and 1·5 × 1011 viral particles) to receive an intramuscular injection of vaccine. The primary outcome was adverse events in the 7 days post-vaccination. Safety was assessed over 28 days post-vaccination. Specific antibodies were measured with ELISA, and the neutralising antibody responses induced by vaccination were detected with SARS-CoV-2 virus neutralisation and pseudovirus neutralisation tests. T-cell responses were assessed by enzyme-linked immunospot and flow-cytometry assays. This study is registered with ClinicalTrials.gov, NCT04313127.
Between March 16 and March 27, 2020, we screened 195 individuals for eligibility. Of them, 108 participants (51% male, 49% female; mean age 36·3 years) were recruited and received the low dose (n=36), middle dose (n=36), or high dose (n=36) of the vaccine. All enrolled participants were included in the analysis. At least one adverse reaction within the first 7 days after the vaccination was reported in 30 (83%) participants in the low dose group, 30 (83%) participants in the middle dose group, and 27 (75%) participants in the high dose group. The most common injection site adverse reaction was pain, which was reported in 58 (54%) vaccine recipients, and the most commonly reported systematic adverse reactions were fever (50 46%), fatigue (47 44%), headache (42 39%), and muscle pain (18 17%. Most adverse reactions that were reported in all dose groups were mild or moderate in severity. No serious adverse event was noted within 28 days post-vaccination. ELISA antibodies and neutralising antibodies increased significantly at day 14, and peaked 28 days post-vaccination. Specific T-cell response peaked at day 14 post-vaccination.
The Ad5 vectored COVID-19 vaccine is tolerable and immunogenic at 28 days post-vaccination. Humoral responses against SARS-CoV-2 peaked at day 28 post-vaccination in healthy adults, and rapid specific T-cell responses were noted from day 14 post-vaccination. Our findings suggest that the Ad5 vectored COVID-19 vaccine warrants further investigation.
National Key R&D Program of China, National Science and Technology Major Project, and CanSino Biologics.
This is the first randomised controlled trial for assessment of the immunogenicity and safety of a candidate non-replicating adenovirus type-5 (Ad5)-vectored COVID-19 vaccine, aiming to determine an ...appropriate dose of the candidate vaccine for an efficacy study.
This randomised, double-blind, placebo-controlled, phase 2 trial of the Ad5-vectored COVID-19 vaccine was done in a single centre in Wuhan, China. Healthy adults aged 18 years or older, who were HIV-negative and previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-free, were eligible to participate and were randomly assigned to receive the vaccine at a dose of 1 × 1011 viral particles per mL or 5 × 1010 viral particles per mL, or placebo. Investigators allocated participants at a ratio of 2:1:1 to receive a single injection intramuscularly in the arm. The randomisation list (block size 4) was generated by an independent statistician. Participants, investigators, and staff undertaking laboratory analyses were masked to group allocation. The primary endpoints for immunogenicity were the geometric mean titres (GMTs) of specific ELISA antibody responses to the receptor binding domain (RBD) and neutralising antibody responses at day 28. The primary endpoint for safety evaluation was the incidence of adverse reactions within 14 days. All recruited participants who received at least one dose were included in the primary and safety analyses. This study is registered with ClinicalTrials.gov, NCT04341389.
603 volunteers were recruited and screened for eligibility between April 11 and 16, 2020. 508 eligible participants (50% male; mean age 39·7 years, SD 12·5) consented to participate in the trial and were randomly assigned to receive the vaccine (1 × 1011 viral particles n=253; 5 × 1010 viral particles n=129) or placebo (n=126). In the 1 × 1011 and 5 × 1010 viral particles dose groups, the RBD-specific ELISA antibodies peaked at 656·5 (95% CI 575·2–749·2) and 571·0 (467·6–697·3), with seroconversion rates at 96% (95% CI 93–98) and 97% (92–99), respectively, at day 28. Both doses of the vaccine induced significant neutralising antibody responses to live SARS-CoV-2, with GMTs of 19·5 (95% CI 16·8–22·7) and 18·3 (14·4–23·3) in participants receiving 1 × 1011 and 5 × 1010 viral particles, respectively. Specific interferon γ enzyme-linked immunospot assay responses post vaccination were observed in 227 (90%, 95% CI 85–93) of 253 and 113 (88%, 81–92) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Solicited adverse reactions were reported by 183 (72%) of 253 and 96 (74%) of 129 participants in the 1 × 1011 and 5 × 1010 viral particles dose groups, respectively. Severe adverse reactions were reported by 24 (9%) participants in the 1 × 1011 viral particles dose group and one (1%) participant in the 5 × 1010 viral particles dose group. No serious adverse reactions were documented.
The Ad5-vectored COVID-19 vaccine at 5 × 1010 viral particles is safe, and induced significant immune responses in the majority of recipients after a single immunisation.
National Key R&D Programme of China, National Science and Technology Major Project, and CanSino Biologics.
The effects of neutron skin on the multiplicity (Nch) and eccentricity (ϵ2) in relativistic 4496Ru+4496Ru and 4096Zr+4096Zr collisions at sNN=200 GeV are investigated with the Trento model. It is ...found that the Ru+Ru/Zr+Zr ratios of the Nch distributions and ϵ2 in mid-central collisions are exquisitely sensitive to the neutron skin type (skin vs. halo). The state-of-the-art calculations by energy density functional theory (DFT) favor the halo-type neutron skin and can soon be confronted by experimental data. It is demonstrated that the halo-type density can serve as a good surrogate for the DFT density, and thus can be efficiently employed to probe nuclear deformities by using elliptic flow data in central collisions. We provide hereby a proof-of-principle venue to simultaneously determine the neutron skin type, thickness, and nuclear deformity.
Conspectus Future electronics will take on more important roles in people’s lives. They need to allow more intimate contact with human beings to enable advanced health monitoring, disease detection, ...medical therapies, and human–machine interfacing. However, current electronics are rigid, nondegradable and cannot self-repair, while the human body is soft, dynamic, stretchable, biodegradable, and self-healing. Therefore, it is critical to develop a new class of electronic materials that incorporate skinlike properties, including stretchability for conformable integration, minimal discomfort and suppressed invasive reactions; self-healing for long-term durability under harsh mechanical conditions; and biodegradability for reducing environmental impact and obviating the need for secondary device removal for medical implants. These demands have fueled the development of a new generation of electronic materials, primarily composed of polymers and polymer composites with both high electrical performance and skinlike properties, and consequently led to a new paradigm of electronics, termed “skin-inspired electronics”. This Account covers recent important advances in skin-inspired electronics, from basic material developments to device components and proof-of-concept demonstrations for integrated bioelectronics applications. To date, stretchability has been the most prominent focus in this field. In contrast to strain-engineering approaches that extrinsically impart stretchability into inorganic electronics, intrinsically stretchable materials provide a direct route to achieve higher mechanical robustness, higher device density, and scalable fabrication. The key is the introduction of strain-dissipation mechanisms into the material design, which has been realized through molecular engineering (e.g., soft molecular segments, dynamic bonds) and physical engineering (e.g., nanoconfinement effect, geometric design). The material design concepts have led to the successful demonstrations of stretchable conductors, semiconductors, and dielectrics without sacrificing their electrical performance. Employing such materials, innovative device design coupled with fabrication method development has enabled stretchable sensors and displays as input/output components and large-scale transistor arrays for circuits and active matrixes. Strategies to incorporate self-healing into electronic materials are the second focus of this Account. To date, dynamic intermolecular interactions have been the most effective approach for imparting self-healing properties onto polymeric electronic materials, which have been utilized to fabricate self-healing sensors and actuators. Moreover, biodegradability has emerged as an important feature in skin-inspired electronics. The incorporation of degradable moieties along the polymer backbone allows for degradable conducting polymers and the use of bioderived materials has led to the demonstration of biodegradable functional devices, such as sensors and transistors. Finally, we highlight examples of skin-inspired electronics for three major applications: prosthetic e-skins, wearable electronics, and implantable electronics.
Under the approximate chiral symmetry restoration, quark interactions with topological gluon fields in quantum chromodynamics can induce a chirality imbalance and parity violation in local domains. ...An electric charge separation (CS) could be generated along the direction of a strong magnetic field (B), a phenomenon called the chiral magnetic effect (CME). CS measurements by azimuthal correlators are contaminated by major backgrounds from elliptic flow anisotropy (v_{2}). Isobaric _{44}^{96}Ru+_{44}^{96}Ru and _{40}^{96}Zr+_{40}^{96}Zr collisions have been proposed to identify the CME (expected to differ between the two systems) out of the backgrounds (to be almost the same). We show, by using the density functional theory calculations of the proton and neutron distributions, that these expectations may not hold as originally anticipated because the two systems may have sizable differences in eccentricity and v_{2}.
Ethylene/polar monomer coordination copolymerization offers an attractive way of making functionalized polyolefins. However, ethylene copolymerization with industrially relevant short chain length ...alkenoic acid remain a big challenge. Here we report the efficient direct copolymerization of ethylene with vinyl acetic acid by tetranuclear nickel complexes. The protic monomer can be extended to acrylic acid, allylacetic acid, ω-alkenoic acid, allyl alcohol, and homoallyl alcohol. Based on X-ray analysis of precatalysts, control experiments, solvent-assisted electrospray ionization-mass spectrometry detection of key catalytic intermediates, and density functional theory studies, we propose a possible mechanistic scenario that involves a distinctive vinyl acetic acid enchainment enabled by Ni···Ni synergistic effects. Inspired by the mechanistic insights, binuclear nickel catalysts are designed and proved much more efficient for the copolymerization of ethylene with vinyl acetic acid or acrylic acid, achieving the highest turnover frequencies so far for both ethylene and polar monomers simultaneously.
•Remotely sensed metrics are effective for monitoring vegetation responses to meteorological drought.•Drought resistance is associated with water balance and vegetation characteristics.•Drought ...impacts are determined by water stress levels and drought resistance among ecosystems.•Arid and semi-arid ecosystems are most susceptible to drought.•Future drought may threaten the survival of mesic ecosystems.
Improving our understanding of present and future impacts of drought on the vegetation in northern China is heightened by expectations that drought would increase its vulnerability and subsequently accelerate land degradation. The response of vegetation activity to drought and the underlying mechanisms are not well known. By using the third-generation Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI), we investigated the relationship between NDVI and SPEI, across different climate regimes and land cover types, and determined the dominant time-scales at which different biome types respond to drought during the period of 1981–2014. Our results showed that biome response is coupled with drought trends in most regions of northern China. The highest correlation between monthly NDVI and SPEI at different time scales (1–48 months) assessed the impact of drought on vegetation, and the time scales resulting in the highest correlation were an effective indicator of drought resistance, which was related to the interactive roles of mean water balance and divergent drought survival traits and strategies. Diverse responses of vegetation to drought were critically dependent on characteristic drought time-scales and different growing environments. This study highlighted the most susceptible ecosystem types to drought occurrence under current climate, including temperate steppes, temperate desert steppes, warm shrubs and dry forests. Given that drought will be more frequent and severe under future climate scenarios, it may threaten the survival of mesic ecosystems, such as temperate meadows, alpine grasslands, dwarf shrubs, and moist forests not normally considered at drought risk. We propose that future research should be focused on arid and semi-arid ecosystems, where the strongest impact of drought on vegetation is occurring and the need for an early warning drought system is increasingly urgent.
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.
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