Seasonal Characteristics of Black Carbon Aerosol and its Potential Source Regions in Baoji, China

Continuous measurements of black carbon (BC) aerosol were made at a midsized urban site in Baoji, China, in 2015. The daily average mass concentrations varied from 0.6 to 11.5 mu g m(-3), with an annual mean value of 2.9 +/- 1.7 mu g m(-3). The monthly variation indicated that the largest loading of BC occurred in January and the smallest in June. The mass concentrations exhibited strong seasonality, with the highest occurring in winter and the lowest in summer. The large BC loadings in winter were attributed to the increased use of fuel for domestic heating and to stagnant meteorological conditions, whereas the low levels in summer were related to the increase in precipitation. BC values exhibited similar bimodal diurnal patterns during the four seasons, with peaks occurring in the morning and evening rush hours and an afternoon trough, which was associated with local anthropogenic activities and meteorological conditions. A potential source contribution function model indicated that the effects of regional transport mostly occurred in spring and winter. The most likely regional sources of BC in Baoji were southern Shaanxi province, northwestern Hubei province, and northern Chongqing during spring, whereas the northeastern Sichuan Basin was the most important source region during winter

Regenerated woody plants influence soil microbial communities in a subtropical forest

10 páginas.- 4 figuras.- 3 tablas.- referencias.- upplementary data to this article can be found online at https://doi. org/10.1016/j.apsoil.2023.104890Forests are critical for supporting multiple ecosystem services such as climate change mitigation. Microbial diversity in soil provides important functions to maintain and regenerate forest ecosystems, and yet a critical knowledge gap remains in identifying the linkage between attributes of regenerated woody plant (RWP) communities and the diversity patterns of soil microbial communities in subtropical plantations. Here, we investigated the changes in soil microbial communities and plant traits in a nine hectare Chinese fir (Cunninghamia lanceolata; CF) plantation to assess how non-planted RWP communities regulate soil bacterial and fungal diversity, and further explore the potential mechanisms that structure their interaction. Our study revealed that soil bacterial richness was positively associated with RWP richness, whereas soil fungal richness was negatively associated with RWP basal area. Meanwhile, RWP richness was positively correlated with ectomycorrhizal (ECM) fungal richness but negatively correlated with the richness of both pathogenic and saprotrophic fungi, suggesting that the RWP-fungal richness relationship was trophic guild-specific. Soil microbial community beta diversity (i.e., dissimilarity in community composition) was strongly coupled with both RWP beta diversity and the heterogeneity of RWP basal area. Our study highlights the importance of community-level RWP plant attributes for the regulation of microbial biodiversity in plantation systems, which should be considered in forest management programs in the future.This work was funded by the National Key Research and Development Program of China (2021YFD2201301 and 2022YFF1303003), the National Natural Science Foundation of China (U22A20612), and the Key Project of Jiangxi Province Natural Science Foundation of China (20224ACB205003).Peer reviewe

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

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure < 100 mmHg (n = 1127), estimated glomerular filtration rate < 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Liquid-like Poly(ionic liquid) as Electrolyte for Thermally Stable Lithium-Ion Battery

A liquid-like poly­(ionic liquid) (PIL) with a very low glass transition temperature of −51 °C and a thermal decomposition temperature of 202.7 °C was synthesized. A PIL-based electrolyte by mixing this poly­(ionic liquid) with additives of 10 wt % propylene carbonate and 0.1 M LiClO4 is proved to be an excellent electrolyte for lithium-ion battery. The obtained PIL-based electrolyte exhibits a high ionic conductivity of 8.3 × 10–5 S cm–1 at 25 °C and 2.0 × 10–4 S cm–1 at 60 °C and a wide electrochemical potential window up to 5.61 V at 25 °C and 4.14 V at 60 °C. The Li/LiFePO4 batteries equipped with this PIL-based electrolyte achieve high capacity, outstanding cycling stability and rate capability at 25 °C, and even improved performance at high temperature like 60 °C. Such excellent performances of batteries are attributed to the formation of stable solid-electrolyte interface film at the lithium-electrolyte interface and the stability of electrolyte during cycling

Understanding oxygen electrochemistry in aprotic Liî¸O2 batteries

In the past decade, the aprotic lithiumâoxygen (Liî¸O2) battery has generated a great deal of interest because theoretically it can store more energy than today's lithium-ion batteries. Although considerable research efforts have been devoted to the R&D of this potentially disruptive technology, many scientific and engineering obstacles still remain to be addressed before a practical device could be realized. In this review, we summarize recent advances in the fundamental understanding of the O2 electrochemistry in Liî¸O2 batteries, including the O2 reduction to Li2O2 on discharge and the reverse Li2O2 oxidation on recharge and factors that exert strong influences on the redox of O2/Li2O2. In addition, challenges and perspectives are also provided for the future study of Liî¸O2 batteries. Keywords: Lithiumâoxygen battery, Oxygen electrochemistry, Mechanis

Knowledge-Aware Multispace Embedding Learning for Personalized Recommendation

Recommender systems help users filter items they may be interested in from massive multimedia content to alleviate information overload. Collaborative filtering-based models perform recommendation relying on users’ historical interactions, which meets great difficulty in modeling users’ interests with extremely sparse interactions. Fortunately, the rich semantics hidden in items may be promising in helping to describing users’ interests. In this work, we explore the semantic correlations between items on modeling users’ interests and propose knowledge-aware multispace embedding learning (KMEL) for personalized recommendation. KMEL attempts to model users’ interests across semantic structures to leverage valuable knowledge. High-order semantic collaborative signals are extracted in multiple independent semantic spaces and aggregated to describe users’ interests in each specific semantic. The semantic embeddings are adaptively integrated with a target-aware attention mechanism to learn cross-space multisemantic embeddings for users and items, which are fed to the subsequent pairwise interaction layer for personalized recommendation. Experiments on real-world datasets demonstrate the effectiveness of the proposed KMEL model

Study on the Water Quality and Protection Measures of Dongting Lake

From nitrogen and phosphorus, chemical oxygen demand, phytoplankton, and eutrophication, this article analyzes the current situation of water quality in the Dongting Lake area, and discusses the factors influencing the water quality of Dongting Lake. Based on the actual production, geographic characteristics and outstanding problem of grim water pollution situation in the Dongting Lake area, some specific proposed measures are put forward in order to provide the basis and reference for the future pollution control in the Dongting Lake area, such as strengthening the industrial pollution control, developing ecological agriculture, and enhancing ecological restoration and water quality early warning