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Abstract As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used fishery survey data from southern Zhejiang coastal waters from 2016 to 2020, employing a maximum entropy model (MaxEnt) to map the habitat distribution of C. nasus. Model performance was evaluated using two metrics: the area under the curve (AUC) of the receiver operating characteristic curve for the training and test sets and true skill statistics (TSS). This study aimed to predict the habitat distribution of C. nasus and explore how environmental variables influence habitat suitability. The results indicated that the models for each season had strong predictive performance, with AUC values above 0.8 and TSS values exceeding 0.6, indicating that they could accurately predict the presence of C. nasus. In the study area, C. nasus was primarily found in brackish or marine waters near bays and coastal islands. Among all environmental factors, salinity (S) and bottom temperature (BOT) had the highest correlations with habitat distribution, although these correlations varied across seasons. The findings of this study provide empirical evidence and a reference for the conservation and management of C. nasus and for the designation of its protected areas.

The radar climatology characteristics of convection in southeastern Gansu Province during the warm season （June to August）were investigated using Tianshui Doppler radar data that filtered by “Maximum Method” and tracking statistics by “TITAN”（Thunderstorm identification Tracking Analysis and Nowcasting） algorithm.The frequency of convective activity showed large value in high altitude mountains with the Great value center located in windward slope of Western Liupanshan Mountain and undulating region of western Qinling Mountains， and the peak time in August.The convective storm mainly propagated from northwest to southeast， meanwhile the propagation characteristics presented a difference in different months and it spreads fastest in June and slowest in August.The diurnal variation of convective activity showed a unimodal distribution of frequency with peak region at 16:00 -17:00 （Beijing Time）.It's also showed in the occurrence and development of convection in different terrain occurrence and development in different terrain conditions with the high frequency of thermal convection mainly at high altitude area in the afternoon and presentation in the mountain， river valley， basin and plain respectively at night.The diurnal variation of convective storms in different months was obviously different.The influence of solar heating and topographic forcing on convective storms in the afternoon of June was the most significant， while the response of convective storms in the night of July and August was higher to the complex topography of the plateau slope.The propagation direction of the well-organized storm in the afternoon was closely related to the extension and slope direction of the mountain， and was closely related to the prevailing winds at 500 hPa at night.More than 90% convective storms lasted less than 36 minutes， and only 1% lasted longer than 1 hour.

Small-sized fish are a vital food source for large predatory commercial fish and play a key role in marine food webs, bridging lower and higher trophic levels. They are indispensable in maintaining the energy flow and material cycling within aquatic ecosystems. This study utilized bottom-trawl survey data from 2017 to 2020 along the south inshore of Zhejiang, China, complemented by concurrent environmental data, to examine the influence of environmental factors on the resource density and seasonal distribution patterns of four dominant small-sized fish species. The research findings indicated that SSH (sea surface height) and Chl (chlorophyll-a concentration) emerged as the key environmental factors influencing resource densities, with all four species exhibiting similar preferences toward these variables. However, significant disparities were observed in their preferences for SST (sea surface temperature), SSS (sea surface salinity), and DO (dissolved oxygen). The various species’ resource density and distribution patterns underwent significant seasonal variations. Additionally, the seasons and regions with the highest resource densities consistently aligned, occurring predominantly in autumn within the northern waters of the study area. This research further elucidated the environmental predilections and seasonal spatial distribution traits of small-sized fish in the south inshore of Zhejiang, an important feeding ground for economic fish species in the East China Sea. This provides scientific backing for forecasting alterations in coastal fishery resources under environmental and climate change scenarios and supports ecosystem-based fisheries management strategies.

This paper addresses the collaborative localization problem for unmanned surface vehicle (USV) clusters with random measurement delays. We propose a Cubature Kalman Hybrid Consensus Filter (CKHCF) based on the cubature Kalman filter (CKF) for widely distributed USV clusters lacking global communication capabilities. In this approach, each USV exchanges two pairs of information with all its neighbors and recalculates the received localization data based on distance and relative angle measurements. The recalculated information is then fused with the locally filtered data and updated to obtain localization information based on global measurements. To mitigate the impact of random measurement delays, we employ one-step prediction to compensate for delayed measurements. We present the derivation of the CKHCF algorithm and prove its consistency and boundedness using mathematical induction. Finally, we validate the effectiveness of the proposed algorithm through simulation experiments.

Abstract Association between alcohol intake and Coronavirus disease 2019 (COVID-19) risk has been explored in several observational studies, but the results are still controversial. These associations may be biased by reverse causation or confounded by other environmental exposures. To avoid potential biases, we used Mendelian randomization (MR) method to evaluate whether alcohol intake is the causal risk factor for COVID-19. Two-sample MR analyses were performed utilizing summary data from the UK Biobank with 38,984 COVID-19 patients and 1,644,784 control participants. Both inverse-variance weighted (IVW) and genetic risk score (GRS) methods were applied to estimate the relationship including COVID-19 vs. general population, hospitalized COVID-19 vs. not hospitalized COVID-19, hospitalized COVID-19 vs. general population, and severe COVID-19 vs. general population. Additionally, we conducted various sensitivity analyses to evaluate the impact of assumptions on the findings and ensure the robustness of the results. Using 80 single nucleotide polymorphisms as instrumental variables, we found that alcohol intake was not significantly associated with the occurrence of COVID-19 in both IVW and GRS methods (IVW: beta = 0.0372; 95% CI − 0.1817 to 0.2561; P = 0.74; GRS: beta = 0.0372, 95% CI − 0.1737 to 0.2481, P = 0.73). Furthermore, similar results were also observed in comparison hospitalized COVID-19 with not hospitalized COVID-19 (IVW: beta = − 0.3625; 95% CI − 1.4151 to 0.6900; P = 0.50; GRS: beta = − 0.3625, 95% CI − 1.3633 to 0.6383, P = 0.48), hospitalized COVID-19 with general population (IVW: beta = − 0.1203; 95% CI − 0.5997 to 0.3591; P = 0.62; GRS: beta = − 0.1203, 95% CI − 0.5352 to 0.2946, P = 0.57), and severe COVID-19 with general population (IVW: beta = 0.2963; 95% CI − 0.3682 to 0.9607; P = 0.38; GRS: beta = 0.2963, 95% CI − 0.3240 to 0.9166, P = 0.35). Besides, the heterogeneity and sensitivity tests suggested absence of bias due to pleiotropy. Our results highlight no evidence to support the causal role of alcohol consumption in COVID-19 risk. Further large-scale prospective studies are warranted to replicate our findings.

Despite the great prospects of alkali metal batteries, safety concerns associated with dendrite growth still limit their commercial applications. An attractive alternative is to use the room temperature liquid sodium–potassium alloy as the anode, which inherently prevents dendrite growth. Currently, Na–K alloy anodes allow only Na+ or K+ to be cycled, depending on the choice of electrolyte and ion selectivity of the cathode, which results in reduced energy density of the battery. Herein, the possibility of concurrent use of both Na+ and K+ ions in Na–K alloy anodes is explored, and the working mechanism by operando optical microscopy is investigated. It is found that the type of deposited metal is dictated by both salt and solvent in electrolyte. Impressively, Na–K co‐deposition is observed in KFSI‐DME electrolyte for the first time, which strongly influences the dendrite morphology and evolution. Furthermore, the current density also has a great impact on the deposition pattern, which allows dendrite‐free Na/K deposition on the liquid‐alloy anode. These findings enrich our understanding of the intricate electrochemical behaviors of Na–K binary electroactive alloy systems and offer guidance for the sufficient use of Na and K while avoiding dendrite formation in such liquid‐alloy batteries.

Radar Quantitative Precipitation Estimation（QPE） can provide continuous， high-resolution and wide-coverage precipitation products which have become critical means of meteorological monitoring.Although the current methods in different regions have made considerable progress， the effect of QPE in complex terrain areas still needs to be strengthened.Aiming at the QPE in the complex terrain area of ​​the northeast slope of the Qinghai-Xizang Plateau， this paper establishes a real-time-dynamic-correction algorithm used geographic terrain factors based on a quasi-stable moving-window based on existing estimation algorithms： Fixed empirical Z-I relationship， cloud classification empirical Z-I relationship， and echo classification statistics Z-I relationship.The estimation performance evaluation was conducted using the precipitation events in Linxia during the flood season from 2017 to 2018.The results demonstrate that the estimated precipitation value without the correction algorithm is often smaller than the actual observation value， and the corrected average precipitation value is more consistent with the actual observation value.For small rainfall events， the cumulative distribution function （CDF） obtained by different estimation algorithms deviates greatly from the actual observation.As the precipitation level gradually increases， the CDF of estimated precipitation gradually approaches the actual observation.It is more stable in the estimation performance of the correction algorithm based on the statistics Z-I relationship of the echo classification.The error of precipitation estimation by different algorithms is quite different and the uncorrected algorithm mainly underestimates to all precipitation events.The overall estimation deviation of the correction algorithm both based on Z-I relationship of echo classification statistics and Z-I relationship of fixed experience is relatively small.The uncorrected algorithm has the advantage to estimate the main precipitation area of convective-precipitation-weather events， but it has a poor ability to estimate the precipitation intensity， and the estimated effect is a boost after the correction.In particular， the correction algorithm based on cloud classification experience Z-I relationship has better estimation ability for convective precipitation weather events， especially the estimation ability of short-duration heavy rainfall is significantly better than other algorithms.The uncorrected algorithm has weaker precipitation estimates for stable precipitation weather events， and the corrected estimates get closer to observations.

Combined with visible light remote sensing technology and InSAR technology, this study employed the fundamental principles of the frequency ratio model, information content model, and analytic hierarchy process to assess the susceptibility of the study area. Nine susceptibility assessment factors such as elevation, slope, aspect, water system, vegetation coverage, geological structure, stratum lithology, rainfall, and human activities were selected, and the factor correlation degree was calculated by using the relative area density value of the landslide. The frequency ratio model and information content model were selected to carry out landslide susceptibility zoning, and the accuracy of the two models was verified by the ROC curve and density method. The results indicate that the information content model performed relatively well. Therefore, the information model, combined with the analytic hierarchy process and fuzzy superposition method using the landslide point density map, was chosen to evaluate landslide susceptibility. The study area was divided into five levels of landslide hazard, ranging from low to high, using the natural discontinuity point method. The results show that the area of each hazard zoning is 197.48, 455.72, 408.21, 152.66, and 16.22 km2 from low to high, and the proportion of landslides in the corresponding area is 0.17%, 1.60%, 3.88%, 8.41%, and 16.65%, respectively. It can be seen that with the increase in the hazard level, the proportion of landslides also increases significantly, which verifies the accuracy of the hazard results. Additionally, four representative landslides in the study area were selected for analysis to understand their characteristics and underlying mechanisms. The results revealed that these landslides were notably influenced by the density of the Jinsha River and the surrounding roads. The susceptibility assessment outcomes for geological disasters align well with the current situation of landslide occurrences in the Tuoding river section, demonstrating high accuracy. This study provides a scientific foundation for effective prevention and control measures against local landslide disasters.

Mesenchymal stem cells and the derived extracellular microvesicles are potential promising therapy for many disease conditions, including wound healing. Since current therapeutic approaches do not satisfactorily attenuate or ameliorate formation of hypertrophic scars, it is necessary to develop novel drugs to achieve better outcomes. In this study, we investigated the effects and the underlying mechanisms of human umbilical mesenchymal stem cells (HUMSCs)-derived microvesicles (HUMSCs-MVs) on hypertrophic scar formation using a rabbit ear model and a human foreskin fibroblasts (HFF) culture model. The results showed that HUMSCs-MVs reduced formation of hypertrophic scar tissues in the rabbit model based on appearance observation, and hematoxylin and eosin (H&E), Masson, and immunohistochemical stainings. HUMSCs-MVs inhibited invasion of HFF cells and decreased the levels of the α-SMA, N-WASP, and cortacin proteins. HUMSCs-MVs also inhibited cell proliferation of HFF cells. The MMP-1, MMP-3, and TIMP-3 mRNA levels were significantly increased, and the TIMP-4 mRNA level and the NF-kB p65/β-catenin protein levels were significantly decreased in HFF cells after HUMSCs-MVs treatment. The p-SMAD2/3 levels and the ratios of p-SMAD2/3/SMAD2/3 were significantly decreased in both the wound healing tissues and HFF cells after HUMSCs-MVs treatment. CD34 levels were significantly decreased in both wound healing scar tissues and HFF cells after HUMSCs-MVs treatment. The VEGF-A level was also significantly decreased in HFF cells after HUMSCs-MVs treatment. The magnitudes of changes in these markers by HUMSCs-MVs were mostly higher than those by dexamethasone. These results suggested that HUMSCs-MVs attenuated formation of hypertrophic scar during wound healing through inhibiting proliferation and invasion of fibrotic cells, inflammation and oxidative stress, Smad2/3 activation, and angiogenesis. HUMSCs-MVs is a potential promising drug to attenuate formation of hypertrophic scar during wound healing.

In this study, a picosecond (ps) laser was employed to produce micro-textures on ductile iron in linearly processing leading to significantly higher processing efficiency. The fabrication efficiency was increased about 1331 times as compared to the more common spot-by-spot texturing method. The ps laser induced graphene (LIG) structures were simultaneously fabricated in dimples, which further enhanced the surface tribological properties. The surface micro-textures were produced by forming micro-dimples on the substrate via the laser ablation process. The dimple diameter and area density were regulated by varying the key laser processing parameters, and were experimentally correlated to the tribological properties of the ductile iron substrate. To understand deeper into the wear reduction mechanism of the micro-dimples, simulation models based on the Reynold equation were established, which analyze the flow field pressure distribution and demonstrate the hydrodynamic lubrication effect of the micro-textures. The ball-on disk friction test showed that the area density of the micro-textures had a significant influence on the friction and wear properties. The micro-texture with the area density of 20% and the average dimple diameter of 36 μm showed the highest volume wear rate reduction of 70% and the friction coefficient reduction of 20% respectively. The results indicated that the simultaneous laser in-situ generation of graphene micro-textures is an effective way of enhancing tribological properties on the ductile iron surface. It enhances the hardness of textured surfaces, thermal diffusion, debris capture ability, and fluid dynamic lubrication effect.

In the analysis of rock slope stability and rock mass hydraulics, the dominant partitioning of discontinuities of rock masses is a very important concept, and it is still a key for establishing the three-dimensional (3-D) network model of random discontinuities. The traditional graphical analysis method is inadequate and greatly influenced by subjective experience. A new method using density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed for the dominant partitioning of discontinuities of rock mass. In the proposed method, we do not need to determine the centers of every cluster before clustering, and the acnodes or outliers can be eliminated effectively after clustering. Firstly, the spatial coordinate transformation of the discontinuity occurrence is carried out and the objective function is established by using the sine value of the angle of the unit normal vector as the similarity measure standard. The DBSCAN algorithm is used to establish the optimal clustering centers by searching the global optimal solution of the objective function, and the fuzzy C-means clustering algorithm is optimized and the mathematical model of the advantage grouping of rock discontinuities is established. The new method and the fuzzy C-means method are compared and verified by using the artificially randomly generated discontinuity occurrence data. The proposed method is a better method than the fuzzy C-means method in general cases, and it can provide more accurate results by eliminating the acnodes or outliers. Finally, the proposed method is applied to discontinuity orientation partition data at Maji dam site, Nujiang River, and there is good agreement with the in situ measurement.

In this study, the K-means algorithm based on particle swarm optimization (K-PSO) and game theory are introduced to establish the quality evaluation model of a rock mass. Five evaluation factors were considered, i.e., uniaxial saturated compressive strength of rock, discontinuity spacing, acoustic velocity, rock quality designation (RQD), and integrity coefficient. The rock mass of an elevation adit at the abutment of Maji hydropower station was taken as a case study. The subjective weight of the evaluation factor was determined by the weighted least squares method, and the objective weight of the evaluation factor was determined by the entropy method. The combined weights of each influencing factor were determined by game theory to be 0.142, 0.179, 0.035, 0.116, and 0.108. The rock mass quality evaluation in the study area was analyzed by K-PSO algorithm. The results indicate that the K-PSO clustering results are almost the same as the evaluation results of the traditional basic quality (BQ) classification method and the widely used extension evaluation method and are consistent with the preliminary judgment of the expert field. The results are consistent with the field observation law. It is considered that the K-PSO clustering theory can reflect the engineering geological characteristics of the rock mass of the hydropower project in the rock mass quality evaluation.

Abstract Idiopathic pulmonary fibrosis (IPF) is a severe disorder leading to progressive and irreversible loss of pulmonary function. In this study we investigated the anti-fibrotic effect of vitamin D using a mouse model of IPF. Lung fibrosis was induced with bleomycin in vitamin D-sufficient and vitamin D-deficient C57BL/6 mice. We found that treatment with active vitamin D analog paricalcitol prevented mouse body weight loss and alleviated lung fibrosis, whereas vitamin D deficiency severely aggravated lung injury. At the molecular level, paricalcitol treatment suppressed the induction of fibrotic inducer TGF-β and extracellular matrix proteins α-SMA, collagen type I and fibronectin in the lung, whereas vitamin D deficiency exacerbated the induction of these proteins. Interestingly, bleomycin treatment activated the local renin–angiotensin system (RAS) in the lung, manifested by the induction of renin, angiotensinogen, angiotensin II and angiotensin receptor type 1 (AT1R). Paricalcitol treatment suppressed the induction of these RAS components, whereas vitamin D deficiency enhanced the activation of the lung RAS. We also showed that treatment of bleomycin-induced vitamin D-deficient mice with AT1R antagonist losartan relieved weight loss, substantially ameliorated lung fibrosis and markedly blocked TGF-β induction in the lung. Moreover, we demonstrated that in lung fibroblast cultures, TGF-β and angiotensin II synergistically induced TGF-β, AT1R, α-SMA, collagen type I and fibronectin, whereas 1,25-dihydroxyvitamin D markedly suppressed the induction of these fibrotic markers. Collectively, these observations strongly suggest that vitamin D mitigates lung fibrosis by blocking the activation of the lung RAS in this mouse model of IPF.

Picosecond fiber laser was subjected on surface of ductile cast iron to induce graphene-like micro-texture array and enhance the tribological properties. The size of the dimples was regulated in the range of 5 μm–110 μm. The in-situ fabrication process was carried out on the workpiece surface in parallel manner and the scanning speed can be up to 3 m/s. The formation mechanism of graphene-like structure was analyzed. The tribological properties of the textured samples were investigated using a ball-on-disk tribometer. The results showed that the laser textured samples exhibit low coefficient of friction and the anti-wear properties were improved significantly. The textured sample showed no distinct wear pit, while the non-textured sample showed typical wear pit with depth up to 15 μm. Volume wear rate was reduced by 69.6 ± 6.9%. The graphene-like micro-texture array conducted by picosecond fiber laser scanning will not change the material isotropic, and the improved tribological properties are attributed to the combined effects of the increased surface hardness, improved heat dispersion property and entrapment of wear debris.

The traffic and user have significant impacts on the electric vehicle (EV) charging load but are not considered in the existing research. We propose a novel integrated simulation framework considering the traffic, the user, and power grid as well as the EV traveling, parking and charging based on cellular automaton (CA). The traffic is modeled by the traffic module of the proposed framework based on CA, while the power grid and user are modeled in the EV charging module. The traffic flow, user's charging preference, user's charging satisfaction, and the total supply capability (TSC) in the surveyed region are considered in the proposed framework. Two cases are carried out to show the interactions between the user and power grid. It is shown that the proposed framework can accurately simulate the interactions among traffic situation, user's behavior and TSC, which are significantly lacking in the existing research. The proposed framework is scalable in considering additional interrelated elements.

We proposed a slanted grating suitable for RGB bands which is polarization-independent and has a high diffraction efficiency of −1st order under normal incidence. We used Rigorous Coupled Wave Analysis (RCWA)and simulated annealing (SA) algorithm to optimize grating parameters and the simulation results showed that the -1st order diffraction efficiency of TE and TM polarizations in the RGB band under normal incidence both exceed 83%, which can be used for three-dimensional (3D) display. Then, by using rigorous modal theory, simplified modal method (SMM), and mode coupling theory, we analyzed the reason for the high-efficiency of −1st order diffracted light. Moreover, the numerical simulation of the simplified modal method is consistent with the rigorous coupled wave analysis of the small slanted angle grating. Therefore, the simplified modal method can be used for small slanted angle gratings as its physical analysis proved that small slanted angle gratings and rectangular gratings have equivalence to a certain extent. This work not only presents numerical solutions of slanted grating with high efficiencies over a wide range of RGB wavelength, but also enables us to have a deeper understanding of the diffraction of slanted gratings.

Accurately obtaining the spatial distribution of soil moisture and its variability are the basis for the land-atmosphere interaction study. We investigated the fidelity of four satellite-based soil moisture products (AMSR2, CCI, SMAP, and SMOS) using in situ observation during the period 2019–2020. The spatial distribution and variability of different soil moisture products in northern China were analyzed for different seasons and climate zones. The satellite products showed the best performance of summer soil moisture with the bias and uncertainty of the three products (CCI, SMAP, and SMOS) being less than 0.041 and 0.097, whereas soil moisture showed a large bias in winter. For all seasons, AMSR2 and CCI demonstrated a positive bias whereas SMAP and SMOS showed a negative bias. CCI product had little bias in spring, summer, and fall in northern China, while SMAP and SMOS had the smallest bias in winter. For different climate zones, CCI product performed better in describing the temporal variability of soil moisture in arid climate zones with the correlation coefficients > 0.50 for most areas, while AMSR2 product provided a similar spatial distribution. In the eastern monsoon region, the soil moisture from SMAP and SMOS was found to have a large bias, whereas the bias in CCI product was small. Four products failed to reproduce the observed soil moisture characteristics in the transitional zones affected by the summer monsoon, with a positive bias found in AMSR2 and CCI and the largest biases in SMAP and SMOS products. We also suggest several reasons for the bias and error in the satellite soil moisture products. These results have important implications for soil moisture studies over midlatitude regions.

Four kinds of antifungal compounds from an extract of Paenibacillus polymyxa A21 with molecular masses of 883.56, 897.59, 947.55, and 961.58 Da were characterized as the members of fusaricidin-type of antibiotics according to LC-MS analysis. Fusaricidins isolated from culture filtrate displayed high antagonistic activity against several plant fungal pathogens, especially Botrytis cinerea, the causal agent of gray mold. The fusaricidins biosynthetic gene cluster (BGC) from A21 was cloned by PCR and comparative cluster analysis revealed that gene fusTE, the 3′ boundary of the fusaricidin BGC in strain PKB1, was not present in fusaricidin BGC of A21, indicating that fusTE is not necessary for fusaricidin synthesis. Fusaricidin extract from A21 significantly reduced gray mold disease incidence and severity on tomato. The mRNA levels for three patho-genesis-related proteins (PRs) revealed that treatment of tomato leaves with fusaricidin extract induced the expression of PR genes to different levels, suggesting that one reason for the reduction of gray mold infection by fusaricidin is induction of PR proteins, which lead to increased resistance to pathogens. This is the first report of the application of fusaricidins to control tomato gray mold and the comparative cluster analysis provides important molecular basis for research on fusaricidin biosynthesis.

Abstract Streptomyces lydicus A02 is used by industry because it has a higher natamycin-producing capacity than the reference strain S. natalensis ATCC 27448. We sequenced the complete genome of A02 using next-generation sequencing platforms, and to achieve better sequence coverage and genome assembly, we utilized single-molecule real-time (SMRT) sequencing. The assembled genome comprises a 9,307,519-bp linear chromosome with a GC content of 70.67%, and contained 8,888 predicted genes. Comparative genomics and natamycin biosynthetic gene cluster (BGC) analysis showed that BGC are highly conserved among evolutionarily diverse strains, and they also shared closer genome evolution compared with other Streptomyces species. Forty gene clusters were predicted to involve in the secondary metabolism of A02, and it was richly displayed in two-component signal transduction systems (TCS) in the genome, indicating a complex regulatory systems and high diversity of metabolites. Disruption of the phoP gene of the phoR-phoP TCS and nsdA gene confirmed phosphate sensitivity and global negative regulation of natamycin production. The genome sequence and analyses presented in this study provide an important molecular basis for research on natamycin production in Streptomyces, which could facilitate rational genome modification to improve the industrial use of A02.

Smelter grade alumina (SGA) plays multiple roles in the Hall−Héroult process for primary aluminum production. Given its very porous nature, one major role of SGA is to adsorb toxic hydrogen fluoride (HF) in the dry scrubber. However, also because of its porous nature, SGA inevitably adsorbs ambient moisture. This paper discusses the influence of alumina properties, including pore size distribution and specific surface area, on the physical adsorption of water vapor on SGA, as well as the adsorption kinetics. The result shows that the adsorption enthalpy of moisture on SGA is in the range of 4−13 kJ/mol. The adsorption capacity increases significantly with the particle specific surface area and total pore volume. A higher adsorption temperature indicates a much faster adsorption rate but corresponds to a lower equilibrium adsorption capacity.

Due to the complex terrain, sparse precipitation observation sites, and uneven distribution of precipitation in the northeastern slope of the Qinghai–Tibet Plateau, it is necessary to establish a precipitation estimation method with strong applicability. In this study, the precipitation observation data from meteorological stations in the northeast slope of the Qinghai–Tibet Plateau and 11 geographical and topographic factors related to precipitation distribution were used to analyze the main factors affecting precipitation distribution. Based on the above, a multivariate linear regression precipitation estimation model was established. The results revealed that precipitation is negatively related to latitude and elevation, but positively related to longitude and slope for stations with an elevation below 1700 m. Meanwhile, precipitation shows positive correlations with both latitude and longitude, and negative correlations with elevation for stations with elevations above 1700 m. The established multivariate regression precipitation estimating model performs better at estimating the mean annual precipitation in autumn, summer, and spring, and is less accurate in winter. In contrast, the multivariate regression mode combined with the residual error correction method can effectively improve the precipitation forecast ability. The model is applicable to the unique natural geographical features of the northeast slope of the Qinghai–Tibet Plateau. The research results are of great significance for analyzing the temporal and spatial distribution pattern of precipitation in complex terrain areas.

Melatonin plays an important role in plant growth, development, and environmental stress. In this study, a systematic analysis of tomato tryptophan decarboxylase (SlTrpDC), which is the first enzyme of melatonin biosynthesis, was conducted by integrating structural features, phylogenetic relationships, an exon/intron feature, and a divergent expression profile. The results determined that the tomato genome encoded five members (SlTrpDC1-SlTrpDC5). The phylogenetic relationships indicated that gene expansion was proposed as the major mode of evolution of the TrpDC genes from the different plant algae species to the higher plants species. The analyses of the exon/intron configurations revealed that the intron loss events occurred during the structural evolution of the TrpDCs in plants. Additionally, the RNA-seq and qRT-PCR analysis revealed that the expression of the SlTrpDC3 was high in all of the tested tissues, while the SlTrpDC4 and SlTrpDC5 were not expressed. The expression patterns of the remaining two (SlTrpDC1 and SlTrpDC2) were tissue-specific, which indicated that these genes may play important roles within the different tissues. No expression difference was observed in the tomato plants in response to the biotic stresses. This study will expand the current knowledge of the roles of the TrpDC genes in tomato growth and development.

Acetylserotonin methyltransferase (ASMT) is the last enzyme of melatonin biosynthesis and may play a rate-limiting role in the melatonin production of plants. In this study, systematic analysis of the ASMT gene family in tomato (Solanum lycopersicum Mill) has been presented by the integration of the structural features, phylogenetic relationships, exon/intron configuration, and expression profile during growth and development, as well as biotic stresses. The results revealed that the tomato genome encoded a minimum of 14 members, containing three probable encoded pseudogenes. Chromosome mapping indicated that the family had probably expanded via tandem duplication events. Genome-wide RNA-seq and qRT-PCR based gene expression analysis revealed that almost half of the SlASMT genes were expressed in at least one of the experimental stages studied and also showed differential accumulation. Furthermore, the tandem duplicated SlASMT genes showed differential expression levels, which indicated probable functional divergence during the course of the evolution. Finally, this study also determined that some SlASMT genes were induced by multiple pathogens. The results suggested that these genes could be involved in tomato plant response to biotic stresses.

Hard carbons hold great promise as the anode materials for sodium-ion batteries (SIBs), but the limited capacities and sluggish Na+ transfer kinetics still hinder their practical applications. These issues can be addressed from the perspective of improving the wettability of hard carbons with electrolyte. Herein, we demonstrate that the wettability of hard carbons can be regulated by tuning their pore size, so as to optimize their electrochemical properties. A series of N-doped hollow mesoporous carbon nanotubes (HMCNTs) with the average pore sizes in the range of 2–8 nm are synthesized. Among them, the HMCNTs with an average pore size of 6.1 nm (HMCNTs-6.1) exhibits the most improved wettability and reaction kinetics, which delivers a high reversible capacity (415.5 mA h g−1 after 100 cycles at 0.1 A g−1), superior long-term cycle stability and rate capability. In addition, as visualized by in situ transmission electron microscopy, the HMCNTs-6.1 with relatively large mesopores is more favorable for the mass transport across the carbon shells than the HMCNTs with smaller pore sizes. This work provides new insight for understanding the relationship between pore size, electrolyte wettability and electrochemical performance of porous hard carbon, which can help to design the high-performance SIB anodes. [ABSTRACT FROM AUTHOR]