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When compared with other phylogroups (PGs) of the Pseudomonas syringae species complex, P. syringae pv. syringae (Pss) strains within PG2 have a reduced repertoire of type III effectors (T3Es) but produce several phytotoxins. Effectors within the cherry pathogen Pss 9644 were grouped based on their frequency in strains from Prunus as the conserved effector locus (CEL) common to most P. syringae pathogens; a core of effectors common to PG2; a set of PRUNUS effectors common to cherry pathogens; and a FLEXIBLE set of T3Es. Pss 9644 also contains gene clusters for biosynthesis of toxins syringomycin, syringopeptin and syringolin A. After confirmation of virulence gene expression, mutants with a sequential series of T3E and toxin deletions were pathogenicity tested on wood, leaves and fruits of sweet cherry (Prunus avium) and leaves of ornamental cherry (Prunus incisa). The toxins had a key role in disease development in fruits but were less important in leaves and wood. An effectorless mutant retained some pathogenicity to fruit but not wood or leaves. Striking redundancy was observed amongst effector groups. The CEL effectors have important roles during the early stages of leaf infection and possibly acted synergistically with toxins in all tissues. Deletion of separate groups of T3Es had more effect in P. incisa than in P. avium. Mixed inocula were used to complement the toxin mutations in trans and indicated that strain mixtures may be important in the field. Our results highlight the niche‐specific role of toxins in P. avium tissues and the complexity of effector redundancy in the pathogen Pss 9644. [ABSTRACT FROM AUTHOR]

Background: Tigecycline is regarded as a last‐resort antimicrobial agent against multidrug resistance (MDR). However, resistance‐nodulation‐division efflux pump resistance genes, such as tmexCD3‐toprJ3, that confer resistance to tigecycline have emerged. Objectives: This study aimed to characterise the tmexCD3‐toprJ3 gene cluster in Pseudomonas juntendi and Proteus terrae isolated from a pig farm. Methods: Samples were obtained from a Chinese piggery and included 92 pig faecal samples, 56 wastewater samples, 23 drinking water samples, 28 sow vagina samples and nine sow uterus swabs. The presence of tmexCD3‐toprJ3 was detected using a polymerase chain reaction assay, and the antimicrobial susceptibility profile of the tmexCD3‐toprJ3‐positive isolates was determined using the broth dilution method. Genomic locations were identified using whole‐genome sequencing and bioinformatics. Results: We identified two tmexCD3‐toprJ3‐positive isolates, and both isolates were highly resistant to antibiotics such as tigecycline. In addition, we identified several mobile elements (ISPa7, ISCfr1, ISVsa3) and insertion sequences (TnAs2, TnAs3) in tmexCD3‐toprJ3‐positive isolates that could increase the potential for the spread of MDR. Conclusions: To the best of our knowledge, this study is the first to report the detection of tmexCD3‐toprJ3 in P. juntendi and P. terrae isolated from a pig farm. [ABSTRACT FROM AUTHOR]

Background: Wildlife zoos provide the opportunity for children and adults to interact with animals, However, it's unknown that the risk of contact with animals, which carried zoonotic pathogens and antimicrobial resistant bacteria. Objectives: This study aimed to investigate the prevalence and antimicrobial susceptibility of extended‐spectrum β‐lactamases Escherichia coli (ESBLs‐EC) from a wildlife zoo in China. Methods: A total of 93 wildlife faecal samples were collected from a wildlife zoo. Agar dilution method was used to determine the resistant phenotype. Whole genomes sequencing and bioinformatic analysis were employed to evaluate the molecular typing and genetic relationships of ESBLs‐EC. Results: A total of 23 CTX‐M‐positive ESBLs‐EC were isolated from swan (n = 14), squirrel monkey (n = 5), black hat hanging monkey (n = 2), gibbon monkey (n = 1) and phoenicopteridae (n = 1) respectively. All ESBLs‐EC strains were resistant to cefotaxime, tetracycline, ciprofloxacin and trimethoprim‐sulfamethoxazole, but susceptible to colistin, tigecycline, meropenem and amikacin. By screening whole genome sequences, ESBLs‐EC strains main carried blaCTX‐M‐55 (34.8%, 8/23) and blaCTX‐M‐14 (26.0%, 6/23), following by blaCTX‐M‐27 (21.7%, 5/23), blaCTX‐M‐15 (13.0%, 3/23) and blaCTX‐M‐121 (4.3%, 1/23). ESBLs‐EC strains mainly belonged to phylogroup A (60.9%, 14/23), and ST48, ST746 and ST616 (3 strains respectively, 13.0%) were major ST types. Core genome‐based single nucleotide polymorphism (SNP) analysis suggested that strains from the swan, over the phylogenetic tree, have a closer genetic relationship with strains from other animals (black hat hanging monkey, gibbon monkey, phoenicopteridae and squirrel monkey). Conclusions: CTX‐M type ESBLs‐EC can transmit between animals in wildlife zoos, which may be a risk of spread to animal keepers, veterinarians and visitors when contact with animals. Our study provides that the importance of hygiene measures to minimise the risk of transmission of ESBLs‐EC to visitors in wildlife zoos. [ABSTRACT FROM AUTHOR]

Summary: Research on the initial phage–host interaction has been conducted on a limited repertoire of phages and their cognate receptors, such as phage λ and the Escherichia coli LamB (EcLamB) protein. Apart from phage λ, little is known about other phages that target EcLamB. Here, we developed a simple method for isolating novel environmental phages in a predictable way, i.e. isolating phages that target a particular receptor(s) of a bacterium, in this case, the EcLamB protein. A plasmid (pMUT13) encoding the EcLamB porin was transferred into three different enterobacterial genera. By enrichment with these engineered bacteria, a number of phages (ZZ phages) that targeted EcLamB were easily isolated from the environment. Interestingly, although EcLamB‐dependent in their recombinant heterologous hosts, these newly isolated ZZ phages also targeted OmpC as an alternative receptor when infecting E. coli. Moreover, the phage host range was readily extended within three different bacterial genera with heterologously expressed EcLamB. Unlike phage λ, which is a member of the Siphoviridae family, these newly isolated EcLamB‐dependent phages were more commonly members of the Myoviridae family, based on transmission electron microscopy and genomic sequences. Modifications of this convenient and efficient phage enrichment method could be useful for the discovery of novel phages. [ABSTRACT FROM AUTHOR]

The preparation of flame-retardant encapsulated electrospun core-shell fibrous membrane (ECSFM) is the key to ensure both high performance and safety of battery separator. However, there are lacks of simulation analysis on the thermal deformation behaviour of core-shell fibers, and stable, controllable, and batch preparation method of ECSFM, which makes it difficult to efficiently prepare ECSFM with higher safety. Here, the thermal deformation process of core-shell fiber was simulated to analyze the core and shell ratio with the best flame retardancy and thermal shutdown performance. The results showed that a high ratio of shell layer would make it difficult for the flame retardant in core layer to spill out in time, causing insufficient flame retardancy, while the low ratio would lead to the insufficient thermal shutdown performance of the ECSFM. The ECSFM was prepared by coaxial electrospinning with the optimal proportion of shell and core layer, in which the shell layer was polyvinylidene fluoride (PVDF) and the core layer was triphenyl phosphate (TPP), and the optimized one (TPP@PVDF) had shutdown temperature (177 °C), a membrane rupture temperature (227 °C), and a short self-extinguishing time (1.82 s), while the unoptimized one could not thermal shutdown and had longer self-extinguishing time (2.13 s). Moreover, the batch preparation of TPP@PVDF was realized by sheath focusing multi-nozzle coaxial electrospinning, the output increased by 20.33 times compared with single coaxial electrospinning, and the comprehensive performance was better than commercial battery separator. This work provides a convenient method for the rapid fabrication of safe and high-performance battery separators. [Display omitted] • Core-shell nanofibrous membrane with both flame retardancy and thermal shutdown properties. • Simulation analysis on the thermal deformation behaviour of core-shell fibers. • Sheath focusing multi-nozzle coaxial electrospinning core-shell fibers. • Stable, controllable, and batch preparation method of core-shell fibers. [ABSTRACT FROM AUTHOR]

The United States Natural Resources Conservation Service (NRCS) Runoff Curve Number (CN) is the most widely used rainfall-runoff modeling method. The hydrologic soil group (HSG), land use/cover, hydrologic surface condition and antecedent moisture condition jointly determine the CN value. This study aims to update the previous global CN map using the recently available geospatial remote sensing data. Based on the conventional United States Department of Agriculture (USDA) and National Engineering Handbook Section 4 (NEH-4) standard lookup tables, the newly derived CN map utilizes the latest Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and the Harmonized World Soil Database (HWSD) soil data to investigate the current flood potential of the global land surface. The results show that the new CN map outperforms the previous one in detecting China’s flood event locations with an improvement in the ratio of the averaged CN value for flood events to the averaged CN value for the whole land area of China. The new CN map reveals the effects of land surface change on hydrological conditions in the 2000s. Based on the Soil Moisture Active and Passive (SMAP) data and the gauge-combined Global Satellite Mapping of Precipitation (GSMaP) product, global surface runoff (April 2015-March 2016, 0.1°×0.1°) is estimated with the new CN map. The currently derived global CN dataset can be used in multi-scale hydrological applications, such as rainfall-runoff modeling and flood hazard risk assessment across continents. [ABSTRACT FROM PUBLISHER]

Microspheres in fly ash are critically important for determining the properties and performance of fly ash dosed concrete, but facile and cost-effective analysis and quality control of fly ash microspheres remain difficult on construction sites. This paper describes a deep learning method to segment and analyze fly ash spherical particles using a simple optical microscope and a path aggregation network. The proposed method accurately detects microspheres and predicts their particle size distribution and volume fraction, outperforming traditional methods for particle analysis. The predicted results are directly linked to key properties that determine the quality of fly ash. This research establishes an automated and efficient method for rapid job-site fly ash spherical particle analysis, so that inexpensive and handy construction material quality control and assurance can be achieved for infrastructure construction. [Display omitted] • A simple microscope is presented to capture fly ash microspheres with all objects in focus. • A PANet model is trained and implemented for detecting fly ash microspheres. • The method accurately detects microspheres and predicts their particle size distribution. • Predicted results of the method are linked to properties determining fly ash quality. [ABSTRACT FROM AUTHOR]

The goal of this study is to quantitatively intercompare the standard products of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) and its successor, the Global Precipitation Measurement (GPM) mission Integrated Multisatellite Retrievals for GPM (IMERG), with a dense gauge network over the midlatitude Ganjiang River basin in southeast China. In general, direct comparisons of the TMPA 3B42V7, 3B42RT, and GPM Day-1 IMERG estimates with gauge observations over an extended period of the rainy season (from May through September 2014) at 0.25° and daily resolutions show that all three products demonstrate similarly acceptable (~0.63) and high (0.87) correlation at grid and basin scales, respectively, although 3B42RT shows much higher overestimation. Both of the post-real-time corrections effectively reduce the bias of Day-1 IMERG and 3B42V7 to single digits of underestimation from 20+% overestimation of 3B42RT. The Taylor diagram shows that Day-1 IMERG and 3B42V7 are comparable at grid and basin scales. Hydrologic assessment with the Coupled Routing and Excess Storage (CREST) hydrologic model indicates that the Day-1 IMERG product performs comparably to gauge reference data. In many cases, the IMERG product outperforms TMPA standard products, suggesting a promising prospect of hydrologic utility and a desirable hydrologic continuity from TRMM-era product heritages to GPM-era IMERG products. Overall, this early study highlights that the Day-1 IMERG product can adequately substitute TMPA products both statistically and hydrologically, even with its limited data availability to date, in this well-gauged midlatitude basin. As more IMERG data are released, more studies to explore the potential of GPM-era IMERG in water, weather, and climate research are urgently needed. [ABSTRACT FROM AUTHOR]

[Display omitted] • A 28-day concrete strength prediction model based on deep learning is proposed. • The explainable features based on the a priori knowledge of concrete engineers is introduced in model. • Contour maps depicting the interplay between varying explainable features are presented. Recently, a number of machine-learning models have been proposed for the prediction of 28-day compressive strength of concrete using constituent material information as inputs. These models required a series of unexplainable features to be pre-proportioned and predetermined via experiments. Therefore, the a priori knowledge and experience of concrete engineers in terms of concrete formulation and proportioning are unfortunately neglected and wasted in this prediction logic, which might lead to serious predictive errors in concrete design and construction. In this study, a deep-learning based "factors-to-strength" approach that considers multiple explainable features and therefore takes advantage of existing job-site proportioning information is presented for concrete strength prediction. A deep convolutional neural network is proposed and trained using a data set consisting of 380 groups of concrete mixes. The accuracy and reliability of the model are validated by comparing with three models – SVM, ANN, and AdaBoost – using a data set prepared experimentally. The results show that the proposed model achieves high coefficients of determination (0.973 for the training set and 0.967 for the test set), demonstrating its excellent accuracy and generalization ability. This new model also reveals the interplay between varying explainable features in determining the compressive strength of concrete, hence facilitating an interactive experience for engineers to maneuver familiar and understandable factors for concrete strength design. [ABSTRACT FROM AUTHOR]

Summary: Many strains of Pseudomonas colonise plant surfaces, including the cherry canker pathogens, Pseudomonas syringae pathovars syringae and morsprunorum. We have examined the genomic diversity of P. syringae in the cherry phyllosphere and focused on the role of prophages in transfer of genes encoding Type 3 secreted effector (T3SE) proteins contributing to the evolution of virulence.Phylogenomic analysis was carried out on epiphytic pseudomonads in the UK orchards. Significant differences in epiphytic populations occurred between regions. Nonpathogenic strains were found to contain reservoirs of T3SE genes. Members of P. syringae phylogroups 4 and 10 were identified for the first time from Prunus.Using bioinformatics, we explored the presence of the gene encoding T3SE HopAR1 within related prophage sequences in diverse P. syringae strains including cherry epiphytes and pathogens. Results indicated that horizontal gene transfer (HGT) of this effector between phylogroups may have involved phage. Prophages containing hopAR1 were demonstrated to excise, circularise and transfer the gene on the leaf surface.The phyllosphere provides a dynamic environment for prophage‐mediated gene exchange and the potential for the emergence of new more virulent pathotypes. Our results suggest that genome‐based epidemiological surveillance of environmental populations will allow the timely application of control measures to prevent damaging diseases. [ABSTRACT FROM AUTHOR]

Objectives: Intimal hyperplasia is a serious clinical problem associated with the failure of therapeutic methods in multiple atherosclerosis-related coronary heart diseases, which are initiated and aggravated by the polarization of infiltrating macrophages. The present study aimed to determine the effect and underlying mechanism by which tumor necrosis factor receptor-associated factor 5 (TRAF5) regulates macrophage polarization during intimal hyperplasia. Methods: TRAF5 expression was detected in mouse carotid arteries subjected to wire injury. Bone marrow-derived macrophages, mouse peritoneal macrophages and human myeloid leukemia mononuclear cells were also used to test the expression of TRAF5 in vitro. Bone marrow-derived macrophages upon to LPS or IL-4 stimulation were performed to examine the effect of TRAF5 on macrophage polarization. TRAF5-knockout mice were used to evaluate the effect of TRAF5 on intimal hyperplasia. Results: TRAF5 expression gradually decreased during neointima formation in carotid arteries in a time-dependent manner. In addition, the results showed that TRAF5 expression was reduced in classically polarized macrophages (M1) subjected to LPS stimulation but was increased in alternatively polarized macrophages (M2) in response to IL-4 administration, and these changes were demonstrated in three different types of macrophages. An in vitro loss-of-function study with TRAF5 knockdown plasmids or TRAF5-knockout mice revealed high expression of markers associated with M1 macrophages and reduced expression of genes related to M2 macrophages. Subsequently, we incubated vascular smooth muscle cells with conditioned medium of polarized macrophages in which TRAF5 expression had been downregulated or ablated, which promoted the proliferation, migration and dedifferentiation of VSMCs. Mechanistically, TRAF5 knockdown inhibited the activation of anti-inflammatory M2 macrophages by directly inhibiting PPARγ expression. More importantly, TRAF5-deficient mice showed significantly aggressive intimal hyperplasia. Conclusions: Collectively, this evidence reveals an important role of TRAF5 in the development of intimal hyperplasia through the regulation of macrophage polarization, which provides a promising target for arterial restenosis-related disease management. [ABSTRACT FROM AUTHOR]

• Passive microwave signal can determine flood time span. • Observed surface water fraction presents a strong correlation with passive microwave signal. • Daily surface water fraction can be estimated using the proposed integrated method. • Spatial and temporal restrictions of remote sensing observations can be removed. Monitoring changes in flood extent is critical for flood control and mitigation purposes in areas where flooding affects many people and dense infrastructure and properties. Remote sensing can be an effective technique to detect changes in surface water extent and its dynamics. Compared to optical remote sensing, microwave information is suitable for working in any weather condition without severe cloud interference. Usually passive microwave data has a high temporal but a rather coarse spatial resolution, whereas for active microwave data this is reversed and only with ideal satellite constellation observations it can reach high sampling rates. To overcome these spatial and temporal restrictions, we proposed an integrated methodology to combine the passive and active microwave remote sensing and thus provide flood information more frequently at a high resolution. In this paper, a demonstration of the methodology is presented for a flood event occurring in Wuhan, Hubei Province of China in July 2016. The major inundation occurred along the Jushui River, part of the Middle Yangtze River basin. Using the brightness temperature data from a special data set (MEaSUREs), a daily passive microwave signal at the resolution of 3.125 km is used as an indicator to monitor flood occurrence and obtain the flood duration over time. Synthetic Aperture Radar (SAR) imagery (12-day revisit, 10-m spatial resolution) from Sentinel-1 was processed to estimate high resolution flood extents within the time span of the flood based on a threshold-based method together with the High Above Nearest Drainage (HAND) index post-processor. Surface water fraction data generated from SAR images presents a strong correlation with the passive microwave signal (R2 = 0.84) when using a quadratic polynomial fit. The average bias between surface water fraction computed by the passive microwave signals and SAR observations for water pixels within the Jushui River basin for the validation dates is 0.34%, indicating that this relationship can be applied to interpolate surface water fraction for each pixel along the river and other permanent water bodies for days when SAR observations are not available. This integrated method takes advantage of both passive and active microwave remote sensing and enriches temporally sparse flood data. Given the global coverage of the datasets used in this study, it can be utilized to estimate flood status for other flood-prone areas and thus contribute towards societal flood preparedness and response. [ABSTRACT FROM AUTHOR]

Aqueous ammonium‐ion batteries (AIBs) are considered a promising alternative for large‐scale energy storage due to their cost‐effectiveness and high safety. Prussian blue analogues (PBAs) are widely regarded as potential cathode materials for AIBs because of their high working potential and stable 3D framework. However, the low capacity of PBAs (≈60 mAh g−1 in the existing reported works) hinders their further development. Herein, the ion insertion is first proposed to double the capacity of PBAs by unlocking the inert‐site. Using NH4+‐rich copper hexacyanoferrate as a representative, trace amounts of induced ion in the electrolyte can change the electronic states of atoms at the inert site to achieve much higher capacity. What's more, the construction of NH4+‐rich high‐entropy Prussian blue (N‐HEPBA) further facilitates structural stability. N‐HEPBA unlocked by corresponding induced ions can exhibit an impressive specific capacity (129 mAh g−1 at 0.1 A g−1), which is the highest and approximately twice that of reported PBAs for aqueous AIBs. Meanwhile, it delivers excellent cycling stability with nearly 100% capacity retention achieved over 1000 cycles at 2 A g−1. This innovative unlocking method can provide an effective way to obtain high‐capacity PBAs in AIBs, thus promoting the development of large‐scale energy storage. [ABSTRACT FROM AUTHOR]

Recently macrophage polarization has emerged as playing an essential role in the oathogenesis of atherosclerosis, which is the most important underlying process in many types of cardiovascular diseases. Although Nek6 has been reported to be involved in various cellular processes, the effect of Nek6 on macrophage polarization remains unknown. Macrophages exposed to lipopolysaccharide (LPS) or IL‐4 were used to establish an in vitro model for the study of regulation of classically (M1) or alternatively (M2) activated macrophage. Bone marrow‐derived macrophages (BMDMs) transfected with short hairpin RNA‐targeting Nek6 were then in functional studies. We observed that Nek6 expression was decreased in both peritoneal macrophages (PMs) and BMDMs stimulated by LPS. This effect was seen at both mRNA and protein level. The opposite results were obtained after administration of IL‐4. Macrophage‐specific Nek6 knockdown significantly exacerbated pro‐inflammatory M1 polarized macrophage gene expression in response to LPS challenge, but the anti‐inflammatory response gene expression that is related to M2 macrophages was attenuated by Nek6 silencing followed by treatment with IL‐4. Mechanistic studies exhibited that Nek6 knockdown inhibited the phosphorylated STAT3 expression that mediated the effect on macrophage polarization regulated by AdshNek6. Moreover, decreased Nek6 expression was also observed in atherosclerotic plaques. Collectively, these evidences suggested that Nek6 acts as a crucial site in macrophage polarization, and that this operates in a STAT3‐dependent manner. [ABSTRACT FROM AUTHOR]

• Machine learning revealed the dominant factors in global terrestrial water storage variation. • Long-term changes in bivariate drought risk were quantified using a copula -based most likely realization method. • A large proportion of global socioeconomic assets was exposed to increasing drought risk. • Drought intensification was mainly caused by changes in the marginal distributions of duration and severity. The intensification of the hydrological cycle has altered the spatiotemporal redistribution of terrestrial water storage (TWS). The long-term evolutionary mechanism controlling global TWS droughts and their bivariate risks (i.e., drought and severity) remain uncertain. Using machine learning-based TWS reconstructions, we explored the drivers, changes, and impacts of TWS droughts during 1940–2022 at the global scale. We developed a machine learning framework to detect the dominant climate/vegetation factors governing TWS. During 1940–1970, precipitation and vapor pressure deficit were the primary factors influencing TWS; however, the leaf area index was the dominant factor during 1992–2022. We evaluated past changes in drought frequency, duration, severity, and intensity, and found a substantial intensification tendency in most land areas. Subsequently, we evaluated the bivariate risks by combing a copula-based modeling approach and the most likely realization method, revealing a fivefold intensification over most regions. Changes in the marginal distributions of duration and severity accounted for 40–60% of the overall changes in bivariate drought risk, while the contribution from their dependence varied globally. Approximately 80–90% of the global population and gross domestic product were exposed to increasing bivariate drought risk, indicating the need to improve the adaptivity of society and ecosystems to climate change. [ABSTRACT FROM AUTHOR]

As the famous naturally occurring flavonoid, rutin exists in many foods, beverages, and their processed functional products. To realize highly efficient analysis for it, a novel supramolecular hydrogel was developed as the electrode modification material for sensor. Here 12 amino acid-based ionic liquids ([C n mim][AA]) were synthesized and 6 of them could self-aggregate to form hydrogels. Especially, all the hydrogels possessed dual sensitivities to temperature and pH, as well as relatively excellent electrocatalytic performance. A three-layer electrochemical sensor [C n mim][AA]/MWCNTs/CS/GCE was prepared by decorating glass carbon electrode (GCE) with hydrogels, multiwalled carbon nanotubes (MWCNTs) and chitosan (CS) to detect rutin. After comprehensive characterization, computation and systematic investigation, the results indicated that Ipa was linearly related to the concentration of rutin in the range of 0.5–5 μM and 5–100 μM with a limit of detection (LOD) of 0.05 μM (S/N = 3). The selectivity, repeatability, stability and potential in electrochemical analysis of the developed supramolecular sensor were proved after analysis of black tartary buckwheat tea and related health-care pills. [Display omitted] • The new IL gelator-based self assembly hydrogels were obtained for the first time. • The supramolecular hydrogel was found dual sensitive to temperature and pH. • A new tri-layer electrochemical sensor was developed via simple economic route. • The composite sensor had excellent electrocatalytic performance for detection. • The developed sensor was selective, repeatable and stable for different samples. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fabrication strategy inspired by nature mutualism was used. • Optimization of essential oil in preparation of high-performance air filter. • CMA and PHMB work together to achieve functionalization and fiber refinement. • Biopolymer–based air filtration membrane was prepared by one-step electrospinning. • High–performance air filter with antibiosis and mosquito repellent was realized. Composite bio–based multifunctional air filtration is a great challenge and development trend for personal protection. This work was inspired by nature mutualism to produce bio–based and essential oil loaded nanofibrous membrane with multiple functions of high–performance, antibacterial, and mosquito–repellent. The cinnamaldehyde (CMA) and poly(hexamethylene biguanide) (PHMB) were introduced into the cellulose acetate (CA) polymer system to achieve functionalization, and then the CA/CMA/PHMB ultrafine bimodal nanofibrous membrane was prepared through one–step electrospinning. Compared to eugenol, the CMA contributed to the refinement of fiber and minimized the reduction of mechanical properties, thermal stability, and hydrophobicity. On the other hand, the PHMB enhanced jet splitting and synergistically improved antibacterial ability with CMA. The filtration efficiency for PM 0.3 , the pressure drop, and the quality factor were 99.78%, 59.5 Pa, and 0.1028 Pa−1, respectively. The bacteriostatic rates against Escherichia coli and Staphylococcus aureus , and the mosquito–repellent rate were 99.65%, 99.99%, and 92.7%, respectively. Lastly, the batch preparation of this solution was explored, which contributed to commercialization. This work provides a novel and simple approach to efficiently fabricate multifunctional high–performance air filter, which will promote the development of bio–based and sustainable air filter. [ABSTRACT FROM AUTHOR]

NASA's Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology. [ABSTRACT FROM AUTHOR]

• A dynamic three-stage blending scheme is developed to simultaneously correct precipitation occurrence and intensity. • A new daily 0.25° precipitation dataset over mainland China is produced by merging four multi-satellite/reanalysis products. • Different data merging methods are systematically evaluated in 238 catchments over China. • Our developed approach can facilitate hydrological modelling by substantially improving the KGE of simulated streamflow. Satellite-retrieved and atmospheric reanalysis precipitation can bridge the spatiotemporal gaps of in-situ gauging networks, but estimation biases can limit their reliable applications in hydrological monitoring and modelling. To correct precipitation occurrence and intensity simultaneously, this study develops a three-stage blending approach to integrate three multi-satellite precipitation datasets (IMERG Final, TMPA 3B42V7 and PERSIANN-CDR), the ERA5 atmospheric reanalysis product and a gauge dataset within a dynamic framework. Firstly, the systematic biases of the four members were individually corrected by combining the local intensity scaling and ratio bias correction methods. Then, the "state weights" used for determining wet/dry events were optimized by evaluating a score function of the four bias-corrected members. Thirdly, the "intensity weights" were optimized using the cuckoo search (CS) algorithm and the Bayesian Model Averaging (BMA) method, respectively. The three-stage blending approach produced dynamic weights varying both spatially and temporally, and the performance was thoroughly evaluated over mainland China. Results show that the three-stage dynamic scheme performs better than individual datasets and two-stage blending methods in terms of all eight statistical metrics, and the CS algorithm outperforms the BMA method in the third stage. By randomly sampling validation sites using K-fold experiments, the developed algorithm also demonstrates a superior performance in ungauged regions. After interpolating and normalizing blending parameters of all gauges to entire domain using ordinary kriging, a new blended precipitation dataset with a daily 0.25° scale was produced. Four hydrological models are forced by blended and primary precipitations in 238 catchments over China, further confirming that the developed approach can facilitate hydrological modelling demonstrated by improving the Kling-Gupta efficiency of simulated streamflow by 12–35%. [ABSTRACT FROM AUTHOR]