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Abstract Safeguarding water resources, aquatic habitats, and ecosystems is paramount for the well‐being of the populace, the future of the nation, and the sustainable development of China. With the relentless progression of ecological and environmental protection and the establishment of an ecological civilization, China's aquatic ecological environment protection has undergone five decades of exploration. The water environment protection paradigm has gradually transitioned from emphasizing pollutant emission concentration control and total pollutant emission control to prioritizing water environment quality improvement. Particularly in the past decade, regions nationwide have conducted proactive explorations and practices in source control, emission abatement, and quality enhancement. This paper systematically reviews the achievements in China's water environmental quality improvement and the characteristics of water environment management at various stages over the past half‐century. Considering the deployment of “three waters” coordination (water resources, water environment, and water ecology), green development, pollution, carbon reduction, and so forth, this paper analyzes the challenges confronted by China's aquatic ecological environment protection. Finally, future directions are prospected from six aspects: green development, climate change response, water resource allocation optimization, collaborative governance of multiple pollutants, aquatic ecological protection strengthening, and intelligent management improvement.

Hyssopus cuspidatus is a member of the Lamiaceae family, members of which are often used to treat cough and asthma by the Uigurs. However, the Hyssopus genus has a limited number of known chloroplast genomes, making it difficult to compare species within the genus and to classify species within and outside the genus accurately. The introduction of the chloroplast genome method would therefore help improve the classification of the Hyssopus genus. This report presents the complete chloroplast sequences of Hyssopus cuspidatus. The chloroplast genome of H. cuspidatus is 149,678 bp long and contains 129 genes, including 85 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. We identified 46 single sequence repeats (SSRs), most of which were mononucleotide adenine–thymine. The analysis of the repeat sequences, codon usage, and comparison of chloroplast genomes showed a high degree of conservation. The plastid genomes exhibited a typical quartile structure. Four hypervariable regions were identified: accD–psal, psbZ–trnG–GCC, trnH–GUG–psbA, and atpH–atpI. Phylogenetic analysis revealed that the Hyssopus genus was closely related to the adjacent genus Dracocephalum. Our research conducted a comprehensive analysis of the characteristics of the Hyssopus genus and provided a detailed comparison of the differences between species within and outside of this genus. Through IR comparison, phylogenetic analysis, and variation region analysis, we discovered a close relationship between the genera Hyssopus and Dracocephalum and propose a new perspective on the phylogenetic classification of H. cuspidatus. These findings will support the continued identification, classification, and evolutionary analysis of this genus.

Study region: Longchuan River Basin in the Hengduan mountain region, China. Study focus: With the decrease in annual precipitation, the sediment yield on the slope and sediment delivery ratio (SDR) in the river channel, both play a critical role in runoff and sediment load change. However, the response mechanism of SDR to climate change and human activities remains unclear. The RUSLE model was used to calculate the sediment yield on the slope, and the SDR is quantified by the ratio of sediment load in the channel to the sediment yield on the slope.New hydrological insights for the region: Under climate change, the reduced annual rainfall caused a significant decrease in annual runoff and sediment load in the Longchuan River Basin (LRB), since 2003. The RUSLE model was used to calculate the sediment yield on the slope in LRB, and the sediment delivery ratio (SDR) was calculated by the ratio of sediment load to sediment yield. We found a new approach relevant to the relationship of SDR with annual runoff and sediment yield, which can indicate the response mechanism of SDR to climate change. In anthropogenic activities, reservoir interception is the main reason for the sediment load reduction, instead of the land use and land cover change. With a large reservoir built in the LRB, the average SDR is reduced by 83.04 % and the average trap efficiency of the reservoir is 0.96, which was calculated by the Brune equation. This study provides a feasible method to evaluate the effect of different factors on the runoff and sediment load change in the basin.

Accurately estimating nutrient loads is crucial for effective management and monitoring of aquatic ecosystems. This study evaluated the uncertainty in different sampling frequencies and calculation methods for estimating total nitrogen (TN) and total phosphorus (TP) loads in the Yiluo River watershed, a tributary of the Yellow River in China. Using daily TN and TP concentration data from 2019 to 2020, we conducted a bootstrapping analysis to evaluate the accuracy of nine different load estimation methods at different sampling frequencies. Our results showed that Method 3 (M_3, constant concentration interpolation) and Method 7 (M_7, flow-weighted concentration method), when used with a biweekly sampling frequency, had the lowest Standard Deviation of the Percentage errors (STD) (7.70% and 8.60% for TN, 12.0% and 18.8% for TP, respectively) and Mean Relative Error (MRE) values (0.078% and −1.60% for TN, 0.305% and 2.33% for TP, respectively) on an annual scale. For monthly TN and TP load estimates, M_7 can control the MRE within ±20% at a biweekly sampling frequency. Furthermore, the uncertainty in TN and TP load estimates was generally larger during the summer months (June–September), emphasizing the important role of storm events in nutrient export. Extreme events (

Transcriptomics and metabolomics offer distinct advantages in investigating the differentially expressed genes and cellular entities that have the greatest influence on end-phenotype, making them crucial techniques for studying plant quality and environmental responses. While numerous relevant articles have been published, a comprehensive summary is currently lacking. This review aimed to understand the global and longitudinal research trends of transcriptomics and metabolomics in plant quality and environmental response (TMPQE). Utilizing bibliometric methods, we presented a comprehensive science mapping of the social structure, conceptual framework, and intellectual foundation of TMPQE. We uncovered that TMPQE research has been categorized into three distinct stages since 2020. A citation analysis of the 29 most cited articles, coupled with a content analysis of recent works (2020–2023), highlight five potential research streams in plant quality and environmental responses: (1) biosynthetic pathways, (2) abiotic stress, (3) biotic stress, (4) development and ripening, and (5) methodologies and tools. Current trends and future directions are shaped by technological advancements, species diversity, evolving research themes, and an environmental ecology focus. Overall, this review provides a novel and comprehensive perspective to understand the longitudinal trend on TMPQE.

Abstract Background Rhizosphere and plant microbiota are assumed to play an essential role in deciding the well-being of hosts, but effects of parasites on their host microbiota have been rarely studied. Also, the characteristics of the rhizosphere and root microbiota of parasites and hosts under parasitism is relatively unknown. In this study, we used Cistanche deserticola and Haloxylon ammodendron from cultivated populations as our model parasites and host plants, respectively. We collected samples from BULK soil (BULK), rhizosphere soil of H. ammodendron not parasitized (NCD) and parasitized (RHA) to study how the parasite influenced the rhizosphere microbiota of the host. We also collected samples from the rhizosphere soil and roots of C. deserticola (RCD and ECD) and Haloxylon ammodendron (RHA and EHA) to explore the difference between the microbiota of the parasite and its host under parasitism. Results The parasite reduced the compositional and co-occurrence network complexities of bacterial and fungal microbiota of RHA. Additionally, the parasite increased the proportion of stochastic processes mainly belonging to dispersal limitation in the bacterial microbiota of RHA. Based on the PCoA ordinations and permutational multivariate analysis of variance, the dissimilarity between microbiota of C. deserticola and H. ammodendron were rarely evident (bacteria, R 2 = 0.29971; fungi, R 2 = 0.15631). Interestingly, four hub nodes of H. ammodendron in endosphere fungal microbiota were identified, while one hub node of C. deserticola in endosphere fungal microbiota was identified. It indicated that H. ammodendron played a predominant role in the co-occurrence network of endosphere fungal microbiota. Source model of plant microbiome suggested the potential source percentage from the parasite to the host (bacteria: 52.1%; fungi: 16.7%) was lower than host-to-parasite (bacteria: 76.5%; fungi: 34.3%), illustrating that microbial communication was bidirectional, mainly from the host to the parasite. Conclusions Collectively, our results suggested that the parasite C. deserticola shaped the diversity, composition, co-occurrence network, and community assembly mechanisms of the rhizosphere microbiota of H. ammodendron. Additionally, the microbiota of C. deserticola and H. ammodendron were highly similar and shared. Our findings on parasite and host microbiota provided a novel line of evidence supporting the influence of parasites on the microbiota of their hosts.

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (−) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine.

ABSTRACT Paeonia lactiflora is a commercial crop with horticultural and medicinal value. Although interactions between plants and microbes are increasingly evident and considered to be drivers of ecosystem service, the regulatory relationship between microbial communities and the growth and root metabolites of P. lactiflora is less well known. Here, soil metabolomics indicated that carbohydrates and organic acids were enriched in the rhizosphere (RS) with higher diversity. Moreover, the variation of root-associated microbiotas between the bulk soil (BS) and the RS of P. lactiflora was investigated via 16S rRNA and internally transcribed spacer (ITS) amplicon sequencing. The RS displayed a low-diversity community dominated by copiotrophs, whereas the BS showed an oligotroph-dominated, high-diversity community. Hierarchical partitioning showed that cation exchange capacity (CEC) was the main factor affecting microbial community diversity. The null model and the dispersion niche continuum index (DNCI) suggested that stochastic processes (dispersal limitation) dominated the community assembly of both the RS and BS. The bacterial-fungal interkingdom networks illustrated that the RS possessed more complex and stable co-occurrence patterns. Meanwhile, positive link numbers and positive cohesion results revealed more cooperative relationships among microbes in the RS. Additionally, random forest model prediction and two partial least-squares path model (PLS-PM) analyses showed that the P. lactiflora root secondary metabolites were comprehensively impacted by soil water content (SWC), mean annual precipitation (MAP), pH (abiotic), and Alternaria (biotic). Collectively, this study provides a theoretical basis for screening the microbiome associated with the active components of P. lactiflora. IMPORTANCE Determining the taxonomic and functional components of the rhizosphere microbiome, as well as how they differ from those of the bulk soil microbiome, is critical for manipulating them to improve plant growth performance and increase agricultural yields. Soil metabolic profiles can help enhance the understanding of rhizosphere exudates. Here, we explored the regulatory relationship across environmental variables (root-associated microbial communities and soil metabolism) in the accumulation of secondary metabolites of P. lactiflora. Overall, this work improves our knowledge of how the rhizosphere affects soil and microbial communities. These observations improve the understanding of plant-microbiome interactions and introduce new horizons for synthetic community investigations as well as the creation of microbiome technologies for agricultural sustainability.

Sources and implications of black carbon (BC) and mineral dust (MD) on two glaciers on the central Tibetan Plateau were estimated based on in situ measurements and modeling. The results indicated that BC and MD accounted for ~11 ± 1% and 4 ± 0% of the albedo reduction relative to clean snow, while the radiative forcing varied between 11 and 196 and 1–89 W m−2, respectively. Assessment of BC and MD contributions to the glacier melt can reach up 88 to 434 and 35 to 187 mm w.e., respectively, contributing ~9–23 and 4–10% of the total glacier melt. A footprint analysis indicated that BC and MD deposited on the glaciers originated mainly from the Middle East, Central Asia, North China and South Asia during the study period. Moreover, a potentially large fraction of BC may have originated from local and regional fossil fuel combustion. This study suggests that BC and MD will enhance glacier melt and provides a scientific basis for regional mitigation efforts.

In detection-based multi-object tracking (MOT), one challenging problem is to design a robust affinity model for data association. Moreover, since these approaches entirely rely on detection responses to locate targets, a strategy should be taken to deal with a detector's defect. In this paper, we propose a robust online MOT tracking method that can handle these two issues effectively. We first present a novel affinity model by jointly learning more powerful feature representation and distance metric within a deep architecture. Specifically, we design a convolutional neural network to extract appearance cue tailored toward person Re-ID and a long short-term memory network to extract motion cue to encode dynamics of targets. Both the cues are then combined with a triplet loss function, which performs end-to-end deep metric learning to encode dependences across both cues automatically and thus generates fused features in embedding space to distinguish targets. To overcome the detector's limitation, a trajectory estimation strategy is presented. We design a recurrent neural network-based Bayesian filtering module, which takes a hidden state of the above-mentioned LSTM network as an input and performs recursive prediction and update for explicitly estimating targets state. In this way, we can reconstruct trajectories by filling the gaps where no detections are present or adjusting the exact locations of trajectory where detections are imprecise. The experiments on the challenging MOT 2015 and 2016 datasets show very competitive results when comparing our method with the recent state-of-the-art batch and online tracking approaches. We achieve top one in terms of multiple objects tracking accuracy and multiple objects tracking precision among online methods on the MOT2016 dataset.

The cracks in concrete are a fast transport path for chlorides and influence the service life of concrete structures in chloride environments. This study aimed to reveal the effect of crack geometry on chloride diffusion in cracked concrete. The chloride diffusion process in cracked concrete was simulated with the finite difference method by solving Fick’s law. The results showed that the apparent chloride diffusivity was lower in more tortuous cracks, and the cracks with more narrow points also showed lower apparent chloride diffusivity. For tortuous cracks, a higher crack width meant relatively more straight cracks, and consequently, higher apparent chloride diffusivity, while a lower crack width resulted in more tortuous cracks and lower apparent chloride diffusivity. The crack depth showed a more significant influence on the chloride penetration depth in cracked concrete than crack geometry did. Compared with rectangular and V-shaped cracks, the chloride diffusion process in cracked concrete with a tortuous crack was slower at the early immersion age. At the same crack depth, the crack geometry showed a marginal influence on the chloride penetration depth in cracked concrete during long-term immersion.

Permeability of concrete is regarded as a basic indicator of its durability. This paper proposed a simple model to predict the permeability of engineered cementitious composites (ECC), which are fiber reinforced cementitious composites with extremely high ductility and toughness. The permeability of cement paste in ECC was firstly determined based on the general effective media theory. The needed microstructure information of cement paste was obtained from a simulated microstructure. Porosity of the interfacial transition zone (ITZ) was obtained with an ITZ porosity model, and then used to calculate the permeability of ITZ. The permeability of the matrix was determined according to the general self-consistent scheme, and the influence of fiber was simplified with its volume fraction. The calculated permeability of ECC was verified with results from water permeability tests and the accuracy of the model was acceptable for cement-based materials.

At present, research on the influence of friction heat on the wear resistance of laser cladding layers is still lacking, and there is even less research on the temperature of laser cladding layers under different loads by a finite element program generator (FEPG). After a symmetrical laser cladding path, the wear performance of the moving jaw will change. The study of the temperature change of the moving jaw material in friction provides a theoretical basis for the surface modification of the moving jaw. The model of the column ring is built in a finite element program generator (FEPG). When the inner part of the column is WDB620 (material inside the cylinder) and the outer part is ceramic powder (moving jaw surface material), the relationship between the temperature and time of the contact surface is analyzed under the load between 100 and 600 N. At the same time, the stable temperature, wear amount, effective hardening layer thickness, strain thickness, and iron oxide content corresponding to different loads in a finite element program generator (FEPG) were analyzed. The results showed that when the load is 300 N, the temperature error between the finite element program generator (FEPG) and the movable jaw material is the largest, and the relative error is 4.3%. When the load increases, the stable temperature of the moving jaw plate increases after the symmetrical laser cladding path, and the wear amount first decreases and then increases. The minimum wear amount appears at a load of 400 N and a temperature of 340 °C; the strain thickness of the sample material increases gradually, and the effective hardening layer thickness increases. However, when the load reaches 400 N, the thickness of the effective hardening layer changes little; the content of Fe decreases gradually, and the content of FeO and Fe2O3 increases. The increase of the moving jaw increases in turn the temperature of the laser cladding layer of the test jaw material, which intensifies the oxidation reaction of the ceramic powder of the laser cladding layer.

We measured black carbon (BC) with a seven-wavelength aethalometer (AE-31) at the Nam Co Lake (NCL), the hinterland of the Tibetan Plateau (TP) from May 2015 to April 2016. The daily average concentration of BC was 145 ± 85 ng m−3, increasing by 50% since 2006. The seasonal variation of BC shows higher concentrations in spring and summer and lower concentrations in autumn and winter, dominated by the adjacent sources and meteorological conditions. The diurnal variation of BC showed that its concentrations peaked at 9:00–16:00 (UTC + 8), significantly related to local human activities (e.g., animal-manure burning and nearby traffic due to the tourism industry). The concentration-weighted trajectory (CWT) analysis showed that the long-distance transport of BC from South Asia could also be a potential contributor to BC at the NCL, as well as the biomass burning by the surrounding residents. The analyses of the absorption coefficient and absorption Ångström exponent show the consistency of sourcing the BC at the NCL. We suggest here that urgent measures should be taken to protect the atmospheric environment at the NCL, considering the fast-increasing concentrations of BC as an indicator of fuel combustion.

Rapid change of alpine lakes in the Tibetan Plateau (TP) is a clear manifestation of regional-scale climate variability that can be investigated by quantifying the regional hydrological cycle. The degree-day model (DDM) coupled with the Soil and Water Assessment Tool (SWAT) model were used to quantify the water budget of the Nam Co Lake over the period of 2007 to 2013. Driven by local observed meteorological data, the coupled model was successfully validated with the observed lake levels (with R2 = 0.65, NSE = 0.61, and PBIAS = −2.26). Analysis of the water balance revealed that rapid enlargement of the Nam Co Lake was primarily associated with precipitation increase while glacier melt played its role as the potential secondary driver in lake expansion. However, temporal analysis of lake expansion displayed that supremacy of precipitation and glacier melt interchanged between the years. It was found that average annual relative contributions of the precipitation, including direct precipitation on the lake, and glacier melt to the lake were 57% (or 667 mm), and 43% (or 502 mm), respectively. Besides, it was observed that annual values of actual evapotranspiration (ET) from the lake, glaciated, and non-glaciated subbasins were 615 mm, 280 mm, and 234 mm respectively. The average annual glacier mass balance (GMB) of the Nam Co basin was −150.9 millimeter water equivalent (mm w.e.). The relatively high amount of glacier melt was a consequence of the substantial increase in annual temperature in the lake basin. This work is of importance for understanding the rapid water cycle in the TP under global warming. Moreover, this work will also be helpful in monitoring and sustaining the local ecosystem and infrastructure, which is under risk due to rapid lake expansion as a result of climate change in the TP.

Formamidinium (FA)-based quasi-2D perovskites show attractive potential for use in perovskite solar cells (PSCs) owing to their broad absorption range and high stability. However, the toxic solvents used in their fabrication process hinder their further commercialization. Using a green solvent system to prepare highquality perovskite films is a crucial step in solar cell manufacturing. Herein, we employed a green solvent triethyl phosphate (TEP) to prepare an FA-based quasi-2D perovskite precursor and studied antisolvent effects by comparing less toxic petroleum ether (PE) and dibutyl ether (DBE). We found that the sample treated with the lower polarity solvent PE produced better perovskite films with larger grain sizes and fewer defects. The advantages of using PE as an antisolvent during film growth and the characterization of their properties are discussed and elucidated. Finally, a champion PCE of 17.42% was obtained with a solar cell configuration of ITO/PTAA/perovskite/PCBM/BCP/Ag, which is the highest value among FAbased quasi-2D PSCs containing perovskite layers fabricated using an all-green solvent system. This work provides a promising way to use an all-green process to fabricate high-performance quasi-2D PSCs in an environment-friendly manner. [ABSTRACT FROM AUTHOR]