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This paper develops a numerical model to describe the bottom ash cooling process based on an actual power plant. By means of computational fluid dynamics, the influence of adjusting the operating parameters of the dry bottom ash removal system was investigated. The heat exchange enhancement effect and the resulting consequences were comprehensively considered. After comparing its results with the measured values, the model is considered valid. The numerical results indicate that: increasing air volume is an effective method to reduce ash discharge temperature but not desirable; the ash discharge temperature decreased from 452.47 K to 446.27 K, but the air outlet temperature also decreased by 6.05 K. Increasing the running speed of the conveyor belt is an ideal measure; the heat recovery coefficient improves by 7.53% as the speed increases from 0.046 m/s to 0.0766 m/s. In addition, a dry bottom ash removal system with a specific structure has rated ash handling capacity; its design should fully consider the amount of bottom ash discharge. Adjusting the operating mode may not significantly reduce the ash discharge temperature without other losses. The results provide a reference for designing and adjusting subsequent bottom ash sensible heat utilization equipment.

High temperatures associated with a fluctuating climate profoundly accelerate the occurrence of a myriad of plant diseases around the world. A comprehensive insight into how plants respond to pathogenic microorganisms under high-temperature stress is required for plant disease management, whereas the underlying mechanisms behind temperature-mediated plant immunity and pathogen pathogenicity are still unclear. Here, we evaluated the effect of high temperature on the development of grapevine canker disease and quantified the contribution of temperature variation to the gene transcription reprogramming of grapevine and its pathogenic agent Lasiodiplodia theobromae using a dual RNA-seq approach. The results showed that both grapevine and the pathogen displayed altered transcriptomes under different temperatures, and even the transcription of a plethora of genes from the two organisms responded in different directions and magnitudes. The transcription variability that arose due to temperature oscillation allowed us to identify a total of 26 grapevine gene modules and 17 fungal gene modules that were correlated with more than one gene module of the partner organism, which revealed an extensive web of plant–pathogen gene reprogramming during infection. More importantly, we identified a set of temperature-responsive genes that were transcriptionally orchestrated within the given gene modules. These genes are predicted to be involved in multiple cellular processes including protein folding, stress response regulation, and carbohydrate and peptide metabolisms in grapevine and porphyrin- and pteridine-containing compound metabolisms in L. theobromae, implying that in response to temperature oscillation, a complex web of signaling pathways in two organism cells is activated during infection. This study describes a co-transcription network of grapevine and L. theobromae in the context of considering temperature variation, which provides novel insights into deciphering the molecular mechanisms underlying temperature-modulated disease development.

Oasis vegetation contains a variety of ecological functions and can quickly indicate changes in the environment. According to the vegetation dynamics of natural oasis, this study constructed a natural oasis ecological vulnerability assessment model (NOEV) The model is based on Pressure-Sensitivity-Resilience framework, combined with redundancy analysis, minimum cumulative resistance model, and ecological risk sensitivity index to effectively assess the ecological vulnerability of natural oasis. The results showed that human activities, represented by the expansion of farmland and population growth, were the main factors affecting the vegetation dynamics of natural oasis in the last 30 years, and their contribution to the change of vegetation area is 42.08%. In the temporal dynamics, a serie of economic and environmental policies implemented by the government after the 21st century have promoted the recovery of vegetation. Vulnerability decreased on the whole oasis but increased in some local areas during 2005–2020. In the spatial dynamics, the transition zone of vulnerability from high to low occurred, it a distance of approximately 30 km from an artificial oasis located also in the area. We suggest that the governments should set up an ecological buffer zone in this area and implement different environmental protection policies inside and outside the buffer zone. Few vulnerability assessment models have been constructed for oasis ecosystems, and the NOEV model constructed in this study helps to formulate more direct and effective policy recommendations for the government's ecological protection and restoration work.

Abstract Background Steroid-resistant (SR) acute graft-versus-host disease (aGVHD) lacks standard second-line treatment. Mesenchymal stromal cells (MSCs) have potential efficacy in SR aGVHD. We aimed to assess the efficacy and safety of MSCs combined with basiliximab and calcineurin inhibitor as second-line therapy for SR aGVHD. Methods A randomized phase 3 trial involved 203 SR aGVHD patients at nine centers in China (September 2014–March 2019). Participants were randomized at a 1:1 ratio to receive second-line therapy with (n = 101) or without (n = 102) MSCs. The primary endpoint was the overall response (OR) at day 28. Secondary and safety endpoints included durable OR at day 56, failure-free survival, overall survival (OS), chronic GVHD (cGVHD), infection, hematological toxicity and relapse. Results Of 203 patients, 198 (97.5%; mean age, 30.1 years; 40.4% women) completed the study. The OR at day 28 was higher in the MSC group than the control group (82.8% [82 patients] vs. 70.7% [70]; odds ratio, 2.00; 95% confidence interval [CI], 1.01–3.94; P = 0.043). The durable OR at day 56 was also higher in the MSC group (78.8% [78 patients] vs. 64.6% [64]; odds ratio, 2.02; 95% CI, 1.08–3.83; P = 0.027). The median failure-free survival was longer in the MSC group compared with control (11.3 months vs. 6.0 months; hazard ratio (HR) 0.68; 95% CI, 0.48–0.95, P = 0.024). The 2-year cumulative incidence of cGVHD was 39.5% (95% CI, 29.3–49.4%) and 62.7% (51.4–72.1%) in the MSC and control groups (HR 0.55, 95% CI, 0.36–0.84; P = 0.005). Within 180 days after study treatments, the most common grade 3 and 4 adverse events were infections (65 [65.7%] in the MSC group vs. 78 [78.8%] in the control group) and hematological toxicity (37 [37.4%] vs. 53 [53.5%]). The 3-year cumulative incidence of tumor relapse was 10.1% (95% CI, 5.2–17.1) and 13.5% (7.5–21.2%) in the MSC and control groups, respectively (HR 0.75, 95% CI, 0.34–1.67, P = 0.610). Conclusions MSCs plus second-line treatments increase the efficacy of SR aGVHD, decrease drug toxicity of second-line drugs and cGVHD without increasing relapse, and are well-tolerated. MSCs could be recommended as a second-line treatment option for aGVHD patients. Trial registration clinicaltrials.gov identifier: NCT02241018. Registration date: September 16, 2014, https://clinicaltrials.gov/ct2/show/NCT02241018 .

PurposeDesign/methodology/approachFindingsResearch ImplicationsPractical ImplicationsOriginalityThe factors that drive user value co-creation behavior are unique to China due to the country’s unique economic, political and cultural influences. However, few scholars have paid attention to the driving factors of user value co-creation behavior in the Chinese context. In this study, the authors deepen their understanding of the drivers of user value co-creation behavior by exploring the impact of relationship strength, a variable with Chinese characteristics, on value creation behavior.The article takes the relationship strength of online fitness users as the research object from the user’s perspective, uses literature and questionnaires to establish a model of the influence mechanism of online fitness users’ relationship strength on value co-creation behavior, use AMOS to test the model empirically based on the data of 471 senior Chinese online fitness users.The findings confirm that all dimensions of relationship strength, except duration, have a significant positive impact on value experience. Each dimension of relationship strength has a significant positive impact on demand satisfaction. Value experience and demand satisfaction have a significant direct positive impact on value co-creation behavior.This study introduced the variable relationship between strength, explore the user relationship strength with Chinese characteristics variables influence on value creating behavior, follow the “stimulus → psychological perception → value co-creation behavior” logic, build the user relationship strength of value creating action mechanism model, and carries on the empirical test, it broadens the research perspective of driving users to produce value co-creation behavior.The results of this study show that managers need to enhance the relationship strength of users in online fitness communities, especially to improve users’ perception of reciprocity, and to focus on users’ needs and experiences to achieve value co-creation.This study makes two main contributions. It examines the impact of online fitness user relationship strength on value co-creation behavior in the Chinese context, enriching the research on the drivers of value co-creation behavior. Additionally, this study reveals the influence mechanisms of online fitness user relationship strength on value co-creation behavior and provides theoretical guidance for online fitness company to drive users to generate value co-creation behavior. [ABSTRACT FROM AUTHOR]

Background: Risk of early-stage lung adenocarcinoma recurrence after surgical resection is significant, and the postrecurrence median survival is approximately 2 years. Currently, there are no commercially available biomarkers that predict recurrence. In this study, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. Methods: In 91 patients with early-stage (stage IA/IB) lung adenocarcinoma with extensive follow-up, we used 16s rRNA gene sequencing and host RNA sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. Results: Of 91 subjects, 23 had tumor recurrence over 5-year period. In tumor samples, lung adenocarcinoma recurrence was associated with enrichment in Dialister and Prevotella, whereas in unaffected lung samples, recurrence was associated with enrichment in Sphingomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with lung adenocarcinoma recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment in Stenotrophomonas geniculata and Chryseobacterium was positively correlated with upregulation of IL2, IL3, IL17, EGFR, and HIF1 signaling pathways among the host transcriptome. In tumor samples, enrichment in Veillonellaceae (Dialister), Ruminococcaceae, Haemophilus influenzae, and Neisseria was positively correlated with upregulation of IL1, IL6, IL17, IFN, and tryptophan metabolism pathways. Conclusions: Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC = 0.83). Impact: This study suggests that lung adenocarcinoma recurrence is associated with distinct pathophysiologic mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor. [ABSTRACT FROM AUTHOR]

Soil selenium (Se) speciation characteristics and their influence on the Se enrichment pattern and physiological characteristics of oilseed rape are poorly understood. We investigated dynamic changes in rhizosphere soil physicochemical properties, Se uptake and partitioning, biomass, and physiological indices in oilseed rape under five exogenous Se condition levels (0, 1.0, 2.5, 5.0, and 10.0 mg kg−1 Se in sodium selenite) using soil cultivation experiments. The rhizosphere pH and dissolved organic carbon in the soil solution were higher than those of the non-rhizosphere soil solution. The total Se, water-soluble Se, exchangeable Se, and organic Se contents in soils, as well as rapeseed root/leaf Se contents, significantly increased with increasing exogenous Se. Under 2.5 mg kg−1 Se, the biomass of rapeseed roots and leaves increased at the sixth week (82% and 58%) and eighth week (48% and 32%), respectively, reaching the highest level. Applications of 5.0 mg kg−1 Se at 6 and 8 weeks significantly increased the glutathione peroxidase activity (49%/82%), and decreased malondialdehyde content (23%/39%). Canonical correlation and ridge regression analyses showed that Se in the rapeseed roots/leaves significantly and positively correlated with water-soluble Se, exchangeable Se, and organic Se in rhizosphere soil. Overall, moderate-concentration Se soil application benefited oilseed rape growth (optimum = 2.5 mg kg−1 Se). Our findings reveal the response of oilseed rape to soil Se application based on plant growth and physiological traits, rhizospheric soil solution properties, and Se speciation transformation.

Real-time identification of the running state is one of the key technologies for a smart rail vehicle. However, it is a challenge to accurately real-time sense the complex running states of the rail vehicle on an Internet-of-Things (IoT) edge device. Traditional systems usually upload a large amount of real-time data from the vehicle to the cloud for identification, which is laborious and inefficient. In this paper, an intelligent identification method for rail vehicle running state is proposed based on Tiny Machine Learning (TinyML) technology, and an IoT system is developed with small size and low energy consumption. The system uses a Micro-Electro-Mechanical System (MEMS) sensor to collect acceleration data for machine learning training. A neural network model for recognizing the running state of rail vehicles is built and trained by defining a machine learning running state classification model. The trained recognition model is deployed to the IoT edge device at the vehicle side, and an offset time window method is utilized for real-time state sensing. In addition, the sensing results are uploaded to the IoT server for visualization. The experiments on the subway vehicle showed that the system could identify six complex running states in real-time with over 99% accuracy using only one IoT microcontroller. The model with three axes converges faster than the model with one. The model recognition accuracy remained above 98% and 95%, under different installation positions on the rail vehicle and the zero-drift phenomenon of the MEMS acceleration sensor, respectively. The presented method and system can also be extended to edge-aware applications of equipment such as automobiles and ships.

Since many factors affect the fatigue life of welded structures and the relationships between them are complex, finding effective ways to improve the fatigue reliability of welded structures has always been a challenge for the industry. A fatigue reliability assessment model and design method for welded structures based on the structural stress method is proposed. According to the limit state equation of the model, the design-life fatigue reliability and the service fatigue reliability assessment approaches are presented. Then, a first-order second-moment method is employed to reveal quantitative fatigue reliability for welded joints and structures. The relationships between the fatigue reliability and the influence variables are used to analyze and improve the welded structure design. Fatigue reliability of T-joint examples was assessed by accounting for weld leg sizes, plate thicknesses, penetration depths, and single-sided and double-sided forms. Furthermore, the assessment model was verified with a welded bogie frame. The fatigue reliability of the frame was improved based on the evaluation results. The model and method can be applied to other types of welded joints and welded structures.

The concentrations of trace elements in agricultural soils directly affect the ecological security and quality of agricultural products. A comprehensive study aimed at quantitatively analyze the effects of anthropogenic and natural environmental factors on the spatial distribution of heavy metals (HMs) and selenium (Se) in agricultural soils in a typical grain producing area of China. Factors considered in this study were parent rock, soil physicochemical properties, topography, precipitation, mine activity, and vegetation. Results showed that the median values of Zn, Cd, Cr, and Cu of 111 topsoil samples exceeded the background values of Guangxi province but were lower than the relevant national soil quality standards, and 85% of soil samples were classified as having rich Se levels (0.40 −3.0 mg kg−1). The potential ecological risk index of soil heavy metals as a whole was low, with Cd in 9% of the samples posing moderate ecological risk. The concentrations of heavy metals and Se were relatively high in soils from shale rock. Soil properties, mainly Fe2O3 and Mn played a dominant role on soil HMs and Se concentrations. Based on GeoDetector, we found that the interaction effects of two factors on the spatial differentiation of soil HMs and Se were greater than their sum effect. Among the factors, Mn enhanced the explanatory power of the model the most when interacting with other factors for soil Zn; the greatest interactive effect was between distance from mining area and Mn for Cd (q = 0.70); Fe2O3 significantly promoted the spatial differentiation of soil Cr, Cu and Se when interacting with other factors (q > 0.50). These findings contribute to a better understanding of the factors that drive the distribution of HMs and Se in agricultural soils.

To better understand the responses of vegetable yields in a greenhouse system to organic fertilizer through a quantitative evaluation based on peer-reviewed journal articles and in consideration of environmental managerial factors. We conducted a meta-analysis of 453 paired observations from 68 peer-reviewed journal articles to assess the response of vegetable yields in greenhouse vegetable systems in China to organic fertilization. Compared with the control (no organic fertilizer), organic fertilization significantly increased the yields of vegetables by 44.11% on average. The response of vegetable yields to organic fertilizer tended to increase with the increasing experimental duration. Organic fertilizer application had the greatest potential for leafy vegetables (+76.44%), in loamy soils (+53.94%), at moderate organic fertilizer carbon input levels (+54.13%), and in soils with moderate initial soil total nitrogen levels (+50.89%). Aggregated boosted tree analysis indicated that organic fertilizer carbon inputs, vegetable type and experimental duration were the predominant factors that manipulated the response of vegetable yields to organic fertilizer application. The rational application of farmyard manure would be a promising strategy for increasing vegetable yields in greenhouse vegetable systems in China. Factoring in vegetable type, carbon and nitrogen inputs of organic fertilizer, and soil texture would benefit vegetable yields with the application of organic fertilizer.

The addition of fertilizers is indispensable in agricultural production, and currently, there is a wide variety of new types of fertilizers available. For example, commonly used are stabilized fertilizers with inhibitors and coated slow-release fertilizers, among others. However, the long-term effects of these fertilizers, when applied continuously are still uncertain. This study will provide scientific and theoretical support for the development and promotion of these fertilizers. A 16-year paddy field with brown soil treated with different urease and nitrification inhibitors, sulfur-coated urea (SCU), and resin-coated urea (PCU) was studied. The study showed that long-term use of conventional urea nitrogen fertilizer resulted in a significant reduction in soil total phosphorus (TP). Long-term application of NBPT and conventional urea significantly increased soil organic matter (SOM). Moreover, except for HQ and NBPT+DMPP, the prolonged application of new urea fertilizers also significantly enhanced soil total potassium (TK). Application of SCU fertilizer in brown soil type paddy fields resulted in a significant decrease in soil pH over time. However, changes in pH had no effect on the abundance of ammonia-oxidizing bacteria (AOB), as AOB was mainly affected by soil-available N. DMPP, HQ+DCD, NBPT+DMPP, SCU, and PCU significantly reduced the 16S rRNA gene copy number of soil bacteria, with the greatest effect of coated urea fertilizer (SCU and PCU). Long-term application of stable urea fertilizer with HQ significantly reduced the bacterial community in paddy soil. Conversely, HQ+DCD-stabilizede urea fertilizer significantly increased the population structure and abundance of Basidiomycota fungi while decreasing the population structure and abundance of Rozellomycota fungi. DMPP-stabilized urea fertilizer notably increased the population structure and abundance of Ascomycota fungi while decreasing the population structure and abundance of Rozellomycota and Chytridiomycota fungi. Furthermore, HQ-stabilized urea fertilizer significantly reduced the population structure and abundance of Chytridiomycota fungi.

To improve understanding of the characteristics of extreme summer rainfall and its water vapor transport in the eastern part of southwestern China (ESWC), this study analyzed data on daily precipitation from 118 meteorological stations in the ESWC from 1979 to 2020, as well as daily reanalysis data from ERA5 and daily reanalysis data from NCEP/NCAR. The study employed polynomial fitting, correlation, regression, clustering, and mixed single-particle Lagrangian trajectory (HYSPLITv5.0) modeling methods to simulate extreme summer precipitation and its water vapor transport characteristics in the ESWC and its possible formation mechanism. The results show that: (1) The contribution rate of extreme precipitation in the ESWC from 1979 to 2020 varied significantly on the interannual time scale. When the number of extreme precipitation days is high (low), the contribution rate of extreme precipitation is also high (low), while the contribution rate of general precipitation (the percentage of the sum of general precipitation to the total summer precipitation of that year) is often low (high). (2) When extreme precipitation occurs in the ESWC, compared with general precipitation, the high-level potential vortices are stronger, and the cold air from higher latitude is more likely to move southward. Meanwhile, the amount of water vapor input to the region is significantly larger than that of general precipitation. (3) There are four channels of water vapor sources in the ESWC during the period of extreme precipitation: the Bay of Bengal, the Arabian Sea, the western Pacific, and the northwest. The contribution of water vapor from the Bay of Bengal is the highest. The number of extreme summer precipitation days in the ESWC is significantly negatively correlated with the water vapor budget of the eastern boundary and positively correlated with Indian Ocean Basin-Wide (IOBW) index in the previous winter. (4) When the winter SST is high in the IOBW mode, it can cause the western Pacific subtropical high and the South Asian high to be stronger and shifted southward in summer, resulting in an increase in the number of extreme precipitation days in the ESWC.

Droughts are natural disasters that have significant implications for agricultural production and human livelihood. Under climate change, the drought process is accelerating, such as the intensification of flash droughts. The efficient and quick monitoring of droughts has increasingly become a crucial measure in responding to extreme drought events. We utilized multi-imagery data from the geostationary meteorological satellite FY-4A within one day; implemented the daily Maximum Value Composite (MVC) method to minimize interference from the clouds, atmosphere, and anomalies; and developed a method for calculating the daily-scale Temperature Vegetation Drought Index (TVDI), which is a dryness index. Three representative drought events (Yunnan Province, Guangdong Province, and the Huanghuai region) from 2021 to 2022 were selected for validation, respectively. We evaluated the spatial and temporal effects of the TVDI with the Soil Relative Humidity Index (SRHI) and the Meteorological Drought Composite Index (MCI). The results show that the TVDI has stronger negative correlations with the MCI and SRHI in moderate and severe drought events. Meanwhile, the TVDI and SRHI exhibited similar trends. The trends of drought areas identified by the TVDI, SRHI, and MCI were consistent, while the drought area identified by the TVDI was slightly higher than the SRHI. Yunnan Province has the most concentrated distribution, which is mostly between 16.93 and 25.22%. The spatial distribution of the TVDI by FY-4A and MODIS is generally consistent, and the differences in severe drought areas may be attributed to disparities in the NDVI. Furthermore, the TVDI based on FY-4A provides a higher number of valid pixels (437 more pixels in the Huanghuai region) than that based on MODIS, yielding better overall drought detection. The spatial distribution of the TVDI between FY-4A and Landsat-8 is also consistent. FY-4A has the advantage of acquiring a complete image on a daily basis, and lower computational cost in regional drought monitoring. The results indicate the effectiveness of the FY-4A TVDI in achieving daily-scale drought monitoring, with a larger number of valid pixels and better spatial consistency with station indices. This study provides a new solution for drought monitoring using a geostationary meteorological satellite from different spatial–temporal perspectives to facilitate comprehensive drought monitoring.

Biological invasion is one of the major threats to global biodiversity attracting a primary focus of scientific attention. During the past decades, due to the diversity and peculiarity of species, coupled with the vulnerable ecosystem, karst areas have received more and more attention. Numerous investigations and studies have confirmed that the karst areas in Southwest China are suffering from biological invasions under the intensified human activities and the climate change they caused. Despite some fundamental research on invasive species that has been conducted to understand the species and distribution in the karst areas, the mechanism of biological invasions and the response of karst ecosystem are still lack sufficient knowledge. In this paper, we summarized the habitat characteristics and invasion status of karst areas to biological invasions. This paper comprehensively analyzed the research results on biological invasions in karst areas to understand the status and development trends of biological invasions in the karst of China, so as to promote the relevant research on biological invasions in the karst areas. We found that the biological invasions in the karst areas were increasing with years. We also revealed the possible mechanism including competition, mutualism, allelopathy and phenotypic plasticity of biological invasion in karst by summarizing the relevant research results of in the karst areas. Moreover, the response of karst to biological invasion was described from the aspects of ecosystem, community, species and genetic levels, etc. By comparing the characteristics of invasive species that have been found in karst area, we analyzed the common characteristics including strong fecundity and rapid growth rate, strong environmental adaptability, strong phenotypic plasticity and high genetic diversity of the existing invasive species, we simulated and predicted the habitat of invasive species. Overall, we found three areas with high habitat suitability covering Chinese southwest Karst ecosystem, which include the southern Yunnan-Guizhou Plateau, foothill area on the Min-Yue-Gui and foothill area of southern Yunnan. It is also worth noting that the Sichuan Basin has a higher invasive risk compared to its surrounding Karst ecosystem, mainly because of the high habitat suitability of some invasive species. Therefore, we suggest that a general survey of alien invasive species in the karst areas of Southwest China should be carried out as soon as possible, focusing on the survey of the suitable areas of alien species for early warning. In addition, to establish a database of invasive alien species in the karst areas of southwest China, strengthen the monitoring of alien species, and evaluate the impact of invasive species in key areas on the biodiversity and ecosystem in the karst areas of Southwest China, so as to maintain the stability of cave biodiversity and the fragile ecosystem.

In algae and land plants, transport of fatty acids (FAs) from their site of synthesis in the plastid stroma to the endoplasmic reticulum (ER) for assembly into acyl lipids is crucial for cellular lipid homeostasis, including the biosynthesis of triacylglycerol (TAG) for energy storage. In the unicellular green alga Chlamydomonas reinhardtii, understanding and engineering of these processes is of particular interest for microalga-based biofuel and biomaterial production. Whereas in the model plant Arabidopsis thaliana, FAX (fatty acid export) proteins have been associated with a function in plastid FA-export and hence TAG synthesis in the ER, the knowledge on the function and subcellular localization of this protein family in Chlamydomonas is still scarce. Among the four FAX proteins encoded in the Chlamydomonas genome, we found Cr-FAX1 and Cr-FAX5 to be involved in TAG production by functioning in chloroplast and ER membranes, respectively. By in situ immunolocalization, we show that Cr-FAX1 inserts into the chloroplast envelope, while Cr-FAX5 is located in ER membranes. Severe reduction of Cr-FAX1 or Cr-FAX5 proteins by an artificial microRNA approach results in a strong decrease of the TAG content in the mutant strains. Further, overexpression of chloroplast Cr-FAX1, but not of ER-intrinsic Cr-FAX5, doubled the content of TAG in Chlamydomonas cells. We therefore propose that Cr-FAX1 in chloroplast envelopes and Cr-FAX5 in ER membranes represent a basic set of FAX proteins to ensure shuttling of FAs from chloroplasts to the ER and are crucial for oil production in Chlamydomonas.

This study investigated the bioaccumulation and transfer of heavy metals including Cd, Cr, Cu, Mn, Ni, Pb and Zn in soil-crop system in Lhasa, and assessed the health risks of the edible part of the crops. The results showed that the average values of Cd, Cr, Cu, Mn, Ni, Pb and Zn were 0.15, 44.55, 24.68, 532.40, 22.47, 38.18 and 73.99 mg kg−1 in natural soil, and 0.16, 46.93, 38.45, 559.13, 23.23, 40.03 and 83.29 mg kg−1 in cultivated soil, respectively. Highland barley and wheat had the strongest ability to accumulate Zn in grain, the BCF values were 0.24 and 0.27, respectively, significant differences in the distribution of metal contents in crop root, stem, leaf and grain were observed. Root presented larger accumulation capacity in most metals, Zn and Cu was easily transferred in the plant organs, most metals in this study presented difficult to migrate from root to grain. The transfer peak of most metals in soil-crop system appeared from stem to leaf. The concentrations of Cr and Mn in crop grains could be predicted according to the multiple linear regression models. THQ and HI values of heavy metals in edible parts of both highland barley and wheat were below the safety threshold of 1, indicating no detrimental effects posed to adults health. This study helps to understand the accumulation and transfer of heavy metals in soil-crop system in plateau region.

Lindera megaphylla, a broad-leaved evergreen that is used as a landscape ornamental plant and medicinal plant, is an ecologically important and dominant tree species. However, little is known about the molecular mechanisms of its growth, development, and metabolism. The selection of suitable reference genes is critical for molecular biological analyses. To date, no research on reference genes as a foundation for gene expression analysis has been undertaken in L. megaphylla. In this study, 14 candidate genes were selected from the transcriptome database of L. megaphylla for RT-qPCR assay under different conditions. Results showed that helicase-15 and UBC28 were most stable in different tissues of seedlings and adult trees. For different leaf developmental stages, the best combination of reference genes was ACT7 and UBC36. UBC36 and TCTP were the best under cold treatment, while PAB2 and CYP20-2 were the best under heat treatment. Finally, a RT-qPCR assay of LmNAC83 and LmERF60 genes were used to further verify the reliability of selected reference genes above. This work is the first to select and evaluate the stability of reference genes for the normalization of gene expression analysis in L. megaphylla and will provide an important foundation for future genetic studies of this species.

The intercropping patterns of protected cultivations have been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry intercropping cultivated by clean tillage. We introduced 10 forages into wolfberry cultivation through land productivity and an interspecific competitiveness analysis, and we screened out the appropriate intercropping modes to provide a scientific basis for wolfberry green cultivation and pasture production. The results showed that the wolfberry–forage intercropping land equivalent ratio (LER) of greenhouse and field tests increased from 29% to 59% and from 62% to 170%, respectively, when compared with the monoculture weighted mean, showing significant yield advantages (p < 0.05), particularly in wolfberry–mangold, wolfberry–ryegrass, wolfberry–alfalfa, and wolfberry–clover. The aggressivity of interspecific competitiveness analysis showed that the forage introduction did not affect the dominant competitive position of wolfberry. In addition, wolfberry–forage intercropping could promote the monetary advantage index (MAI). Wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa performed well, with MAI values of 827.63, 994.18, and 1918.57 for fruit and 2106.54, 1706.27, and 3103.13 for biomass, respectively. Finally, wolfberry–mangold, wolfberry–ryegrass, and wolfberry–alfalfa were screened out, which can form a new mode of wolfberry and forage production.

The tangent modulus method of undisturbed soil is a new method in settlement calculation, which is mainly applied to hard soil with a strong structure, such as silty clay, completely weathered rock, and granite residual soil with an SPT blow count greater than 8. The tangent modulus is mainly obtained from a field plate load test, which can consider the influence of the soil stress level and reflect the nonlinear characteristics of the foundation settlement. In a multi-layer soil foundation, since the deep plate loading test is difficult, a method was proposed to determine the tangent modulus of deep soil. It is assumed that the ratio of the initial tangent modulus to the deformation modulus is equal to the ratio of the unloading–reloading modulus Eurref to the secant modulus E50ref obtained by triaxial unloading–reloading test. Since there are corresponding empirical formulae for SPT counts and the deformation modulus of different types of soils in many regions, the initial tangent modulus can be derived by the above method. In two cases of a composite foundation, the compression modulus and tangent modulus were used to calculate the settlement of the foundation, which is then compared with the measured results. The results show that the proposed method for determining the tangent modulus of deep soil is feasible in theory, and the calculating accuracy of the tangent modulus is significantly higher than that of the traditional compression modulus.

Community public service facilities have a primary supportive role in the health of the elderly. Under the background of global aging, it has become vital to evaluate the elderly-adaptability of their layouts. Based on the supply and demand interaction perspective, this study used the questionnaire-AHP-2SFCA method for this purpose. Firstly, taking the six main districts of Hangzhou as an example, we analyzed the spatial distribution characteristics of the elderly population, and a weight index table of the health importance of public service facilities was constructed using a questionnaire survey and the AHP method. Secondly, the improved 2SFCA was used to analyze the accessibility of public service facilities in Hangzhou, and combined with the weight index table, the elderly-adaptability of public service facilities in the community life circle was comprehensively evaluated. Finally, the demands of the elderly and the supply of public service facilities in the same region were superimposed to study the differential pattern of supply and demand. The results showed the following: (1) The communities with the largest elderly population are mainly concentrated in Shangcheng District, Xiacheng District, the north of Gongshu District, the west of Jianggan District, and the north of Binjiang District. (2) Green space facilities in parks are most important to the health of the elderly, with a weight of 0.46. (3) The overall evaluation results of the community life circle in the study area were good, and the proportion of areas above the medium level was more than 50%. This showed that the concepts of “neighborhood center” and “big community elderly care” in Hangzhou have achieved initial positive results. (4) Based on the interaction between supply and demand, the research area can be divided into four patterns: supply and demand balance, supply shortage, demand gap, and low supply and demand. The results of this study will help to improve the layout and aging-friendly status of community life circle facilities in Hangzhou, and provide information for other aging cities.

In order to improve the calculation efficiency and reduce the uncertainty in the reliability evaluation process of flat car underframe, a new method based on an improved genetic simulated annealing algorithm-back propagation neural network (GSA-BP) and probability box is proposed. Firstly, a certain type of flat car underframe is taken as the research object, genetic evolution algorithm (GA) and simulated annealing algorithm (SA) are utilized to optimize the weights and thresholds of the GSA-BP neural network and obtain the best initial parameter values. Applying the values, the BP neural network is trained, and the improved GSA-BP neural network is established which is verified by test functions. Secondly, the central plate sub-model of the flat car underframe is obtained by sub-model technology and the correctness of its boundary conditions is tested. On this basis, the static strength analysis of the sub-model is carried out. Finally, the improved GSA-BP neural network and probability box are utilized to evaluate the reliability of the sub-model of flat car underframe, and the Monte Carlo method is utilized to verify it. The results show that the proposed method not only improves the accuracy of reliability evaluation but also shortens the calculation time from 10 hours to 6 hours. The calculation efficiency is increased by 40%, which further verifies its superiority and feasibility in structural reliability evaluation. [ABSTRACT FROM AUTHOR]

It is an inherently challenging scientific endeavor to understand and predict multi-scale, high-dimensional and nonlinear seismological phenomena. The increasing amount of observational big data breaks the linkage between data collection and interpretation, and increases the obscurity and uncertainty in data analysis. However, there is also artificial intelligent computer technology, i.e. machine learning in the era of big data. The excellent capability of machine learning for implicit relation extraction and complex task processing has enabled it to be applied to a variety of fields. In this article, we introduce some of the commonly used machine learning algorithms in seismology as well as their applications, and discuss the future directions of integrating artificial intelligence with seismic data interpretation.

Aiming at the problem that gear modification is difficult to determine under the influence of multiple factors， the gear modification is optimized based on the polynomial response surface proxy model and particle swarm optimization algorithm. Firstly， considering the influence of the shaft and the bearing， the parametric modeling of the gear transmission device is carried out， and the transmission linear error， the maximum contact stress of the tooth surface and the unit normal load of the gear model are simulated and analyzed to determine gear modification mode for composite modification. Secondly， according to the model parameters and analysis results， the range of each shape modification parameter is determined， the orthogonal test design on the practice parameter is performed， and the test data is fitted to establish a polynomial response surface model. Finally， the particle swarm optimization algorithm is used to optimize the response surface model to obtain the optimal amount of gear modification. The results show that the fitted polynomial response surface proxy model has good accuracy and can accurately simulate the relationship between the gear modification parameters and the maximum contact stress. The optimal modification amount obtained by the particle swarm algorithm is used for gear modification， the maximum contact stress of the gear meshing process is reduced， the transmission error is reduced， and the eccentric load phenomenon is effectively improved.

Tropical cyclones (TCs) in the South China Sea (SCS) cause serious disasters and loss every year to the coastal and inland areas of southern China. The types of TCs are usually difficult to forecast, and studies on the understanding of the TCs affecting the SCS are lacking. In this study, the authors use the TC data during 1965–2017 from two best-track datasets to analyse the climatic characteristics in terms of the frequency, the track activity, and the influencing indexes of the TCs affecting the SCS and investigate the possible causes. The results show that, during 1965–2017, there were 535 TCs affecting the SCS, mainly occurring from June to November of each year, with the annual average frequency exhibiting a significant downward trend. Meanwhile, the frequency of the track activity in most areas of the SCS also demonstrate a remarkable decreasing trend but an increase in the Gulf of Tonkin and the Taiwan Strait. The large-scale environmental anomalous westerlies and the decrease of humidity in the mid- and low-level over the northern part of the SCS are likely the main causes for the decrease in frequency and the track activity. In addition, the analysis using the cyclone activity index shows that the influence of the before mentioned TCs in southern China gradually decreases, while the influence of TCs in the SCS show a decreasing trend during past decades.

Abstract Background Lycium barbarum and L. ruthenicum have been used as traditional medicinal plants in China and other Asian counties for centuries. However, the molecular mechanisms underlying fruit development and ripening, as well as the associated production of medicinal and nutritional components, have been little explored in these two species. Results A competitive transcriptome analysis was performed to identify the regulators and pathways involved in the fruit ripening of red wolfberry (L. barbarum) and black wolfberry (L. ruthenicum) using an Illumina sequencing platform. In total, 155,606 genes and 194,385 genes were detected in red wolfberry (RF) and black wolfberry (BF), respectively. Of them, 20,335, 24,469, and 21,056 genes were differentially expressed at three different developmental stages in BF and RF. Functional categorization of the differentially expressed genes revealed that phenylpropanoid biosynthesis, flavonoid biosynthesis, anthocyanin biosynthesis, and sugar metabolism were the most differentially regulated processes during fruit development and ripening in the RF and BF. Furthermore, we also identified 38 MYB transcription factor-encoding genes that were differentially expressed during black wolfberry fruit development. Overexpression of LrMYB1 resulted in the activation of structural genes for flavonoid biosynthesis and led to an increase in flavonoid content, suggesting that the candidate genes identified in this RNA-seq analysis are credible and might offer important utility. Conclusion This study provides novel insights into the molecular mechanism of Lycium fruit development and ripening and will be of value to novel gene discovery and functional genomic studies.

This study presents a detailed analysis of the asymmetric relationships between the warm/cold phase of the El Niño–Southern Oscillation and the typical flood/drought years in summer over Chongqing. Furthermore, its underpinning mechanisms are also explored. The results show that: (1) El Niño and La Niña have an asymmetric influence on summer precipitation in the following year over Chongqing. Generally, the composite atmospheric circulation anomalies for El Niño years are consistent with the composite results for typical flood years in summer over Chongqing, which indicates a tight link between typical flood years in summer over Chongqing and El Niño events. However, the relationship between typical drought years in summer over Chongqing and La Niña events is not significant. (2) From winter to the following summer, the extent of positive SST anomalies in the equatorial eastern Pacific associated with typical flood years in summer over Chongqing shrinks, whereas in the tropical Indian Ocean, the extent slightly expands. This trend indicates that the impact of El Niño on typical flood years in summer over Chongqing is maintained through the ‘relay effect’ of SSTs in the tropical Indian Ocean, which is the result of a lagged response of positive SST anomalies in the tropical Indian Ocean to El Niño events in winter.

In this work, a fuzzy design optimization-based fatigue reliability analysis technique is addressed to obtain the optimal fatigue reliability of the structures with random parameters under the minimum fluctuation of fatigue life. The challenge of the problem lies in uncertainties involved from both structural parameters and loads, which renders the fatigue reliability becoming the primary problem to be considered in evaluating structural performance. In order to obtain the optimal fatigue reliability, the optimal mathematical models aiming at the mass and fatigue life of welding robots are constructed respectively, and the genetic particle swarm optimization algorithm and radial basis function neural network (GAPSO-RBFNN) based surrogate model is then presented. Moreover, fuzzy constraints are introduced into the optimization model, and the improved non-dominated sorting genetic algorithm (INSGA-III) optimization strategy is proposed to solve it, which can effectively reduce the workload by increasing the diversity of Pareto solutions during the iterative process. Finally, the optimized structure combined with numerical simulation method is adopted to analyze the fatigue reliability. After analysis steps are given in detail, a practical welding robot structure is presented to demonstrate the validity and reasonability of the developed methodology.

Selenium (Se) is an essential micronutrient for animals and humans, and it is present in many different forms with different levels of bioaccessibility in food. Based on the maldistribution of Se and overall low level of Se dietary intake in China, an integrated study was conducted in this thesis to provide references for the regulation of Se nutrition. An in vitro simulation test was used to monitor the concentration effects, the impacts of dietary supplement combinations on the bioaccessibility of Se were examined in rice, and a model animal experiment (in vivo) was used to evaluate the practicability of the Se nutrition regulation scheme. The main results were as follows: the bioaccessibility of Se was effectively increased by 30 mg·d−1 VE (VE), 300 mg·d−1 VC + 300 μg·d−1 VB9 (VC+VB9) and 30 mg·d−1 VE + 300 mg·d−1 VC + 300 μg·d−1 VB9 (3IN1) (P

Based on the hourly precipitation data of 34 meteorological stations in Chongqing in the summers (June to August) from 1996 to 2015, the spatial distribution and daily variation of precipitation amount (PA), precipitation intensity (PI), precipitation frequency (PF), and precipitation extremes in Chongqing are analyzed. The results show that, from the perspective of spatial distribution, the precipitation amount (PA) in Chongqing presents a distribution pattern of more around and less in the middle; the area with high precipitation intensity (PI) is mainly located in the northeast of Chongqing; the large value centers of precipitation frequency (PF) are located in the south and west of Chongqing and near Chengkou. On the spatial distribution of hourly precipitation, the precipitation in most areas of Chongqing is mainly concentrated at night [0200–0900 BT (1800–0100 UTC)], and the rain belt spreads from west to east with the passage of time. On the whole, interannual evolution characteristics of summer precipitation amount, precipitation intensity, and precipitation frequency in Chongqing are basically the same, showing a fluctuation characteristic without obvious trend, but there are some peaks and valleys. From the perspective of diurnal cycle, a larger peak of PA in Chongqing appears near 0300 BT (1900 UTC), another lower peak around 1200 BT (0400 UTC), a larger peak of PI around 0300 BT (1900 UTC), another smaller peak around 1500 BT (0700 UTC), and only one peak of PF around 0700 BT (2300 UTC). The extreme precipitation of different duration in summer in Chongqing is closely related to the topographic characteristics and weather system, the extreme centers of each diachronic precipitation are mainly located near Shapingba, Kaizhou, Youyang, and Shizhu, and the time evolution characteristics of the extreme precipitation are not obvious, but the trend of the extreme precipitation accumulated in 1 h, 3 h, 6 h, or 12 h is basically the same.

Application of nitrification inhibitors (NIs) with nitrogen (N) fertilizer is one of the most efficient ways to improve nitrogen use efficiency (NUE). To fully understand the efficiency of NIs with N fertilizer on soil nitrification, yield and NUE of maize (Zea mays L.), an outdoor pot experiment with different NIs in three soils with different pH was conducted. Five treatments were established: no fertilizer (Control); ammonium sulfate (AS); ammonium sulfate + 3, 4-dimethyl-pyrazolate phosphate (DMPP) (AD); ammonium sulfate + nitrogen protectant (N-GD) (AN); ammonium sulfate + 3, 4-dimethyl-pyrazolate phosphate + nitrogen protectant (ADN). The results showed that NIs treatments (AD, AN and ADN) significantly reduced soil nitrification in the brown and red soil, especially in AD and ADN, which decreased apparent nitrification rate by 28% - 44% (P < 0.05). All NIs treatments significantly increased yield and NUE of maize in three soils, especially ADN in the cinnamon soil and AD in the red soil were more efficiency, which significantly increased maize yield and apparent nitrogen recovery by 5.07 and 6.81 times, 4.39 and 8.16 times, respectively. No significant difference on maize yield was found in the brown soil, but AN significantly increased apparent nitrogen recovery by 70%. Given that the effect of NIs on both soil nitrification and NUE of maize, DMPP+N-GD was more efficient in the cinnamon soil, while N-GD and DMPP was the most efficiency in the brown and red soil, respectively. In addition, soil pH and soil organic matter play important role in the efficiency of NIs.

From 19 July 2022 to 31 August 2022, a rare persistent drought and heat event occurred in the middle of the Yangtze River basin (MYRB). Normalized difference vegetation Index (NDVI) over 25% of the area decreased more than 0.05 compared with the climatology, causing extremely agricultural drought disaster and economic losses to China. Previous studies have shown that the occurrence of compound drought and heat events (CDHEs) in the MYRB was associated with intra-seasonal oscillations (ISOs) from different latitudes. Nevertheless, what was the role of ISOs at different latitudes in the formation of the CDHE? To address this question, this paper designed a numerical simulation experiment of partial lateral forcing to investigate the changes in meteorological elements by removing the signals of ISOs on different lateral boundaries. We found that the wave series formed in the upper troposphere at 200 hPa played a significant role in the occurrence of the CDHE in the northern part of the MYRB in this progress. It was found that the ISO component of the northern boundary caused the mean temperature to rise by 2.4 °C and aggravated the drought in 53.7% of the region. On the other hand, the anticyclone anomaly in the lower troposphere at 800 hPa had a continuous impact on the southern and eastern boundaries. It was found that the ISO component of these two boundaries can increase the average temperature by 1.93 °C in the MYRB and intensify the drought in 49.7% of the area. In the developing period of the CDHE, the South Asian high and the Western North Pacific subtropical high were coupled with each other and jointly controlled the MYRB, so that the significant positive geopotential height anomaly stayed above the MYRB for a long time, which was conducive to the development of local subsidence. The results of this paper will help to better understand the formation mechanism of CDHEs in the MYRB and assist meteorologists to prevent and forecast the occurrence of CDHEs in advance.

Maintaining the integrity and stability of oasis ecosystems is an important topic in the field of ecological research. Assessment of ecosystem services and their changes can provide important support for the sustainable development of oases. This study took the Dunhuang oasis in the hyper-arid area as the research object and used 1990, 2010, and 2020 Landsat series satellite images to complete the land use interpretation by random forest classification. Then we estimated the ecosystem services value (ESV) by using benefit transfer method, and predicted the trend of ecosystem service value changes under three scenarios using the Analytic Hierarchy Process method and the patch generation land use simulation model (AHP-PLUS model). The results showed that the vegetation areas of the Dunhuang Oasis first decreased and then increased during 1990–2020. The decrease was largely due to the expansion of built-up land and farmland, and the increase was mainly contributed by the implementation of ecological protection policies. The path of changes in the ESV of the Dunhuang Oasis during 1990–2020 was well consistent with that of vegetation areas, with a maximum of 9068.15×106 yuan (in 1990) and a minimum of 6271.46×106 yuan (in 2010). Spatial autocorrelation analysis showed that urbanization reduced ESV, and the implementation of ecological policies enhanced ESV. The ESV of the Dunhuang Oasis for the year 2030 under the ecological conservation scenario could reach 7631.07×106 yuan, which is 381.1×106 yuan higher that under the economic development scenario. The ecological conservation scenario is the optimal option to achieve sustainable development of the Dunhuang Oasis. We suggested that the government should continuously enhance the protection of forests and waterbodies, reasonably restrict production and domestic water consumption, and efficiently increase the proportion of ecological water consumption. In addition, this study improved the evaluation method of oasis ESV based on the proportion of Normalized Difference Vegetation Index (NDVI) of grasslands with different coverage, which is important for improving the environment in arid areas.

The essence of plant ecological stoichiometry is to study the relationships between species and their environment, including nutrient absorption, utilization and cycling processes as well as the nutrient limitation of plants. Plants can regulate nutrient elements and adapt to environmental changes. To understand the adaptation mechanism, it is important to take plants as a whole and quantify the correlation between the chemometrics of different organs. Ammopiptanthus mongolicus is within the second-class group of rare–endangered plants in China and is the only evergreen broad-leaved shrub in desert areas. We analyzed the ecological stoichiometric characteristics of leaves, stems, roots, flowers and seeds of A. mongolicus in five habitats, namely fixed sandy land, semi-fixed sandy land, stony–sandy land, alluvial gravel slope and saline–alkali land. We found that (1) the nutrient contents of N, P and K were in the order of seed > flower > leaf > root > stem. The enrichment of the N, P and K in the reproductive organs promoted the transition from vegetative growth to reproductive growth. Additionally, (2) the contents of C, N, P and K and their stoichiometric ratios in different organs varied among different habitat types. The storage capacity of C, N and P was higher in sandy soil (fixed and semi-fixed sandy land), whereas the content of K was higher in gravelly soil (stony–sandy land and alluvial gravel slope), and the C:N, C:P and N:P were significantly higher in gravelly soil than those in sandy soil. A. mongolicus had higher nutrient use efficiency in stony–sandy land and alluvial gravel slope. Furthermore, (3) the C:N and N:P ratios in each organ were relatively stable among different habitats, whereas the K:P ratio varied greatly. The N:P ratios of leaves were all greater than 16 in different habitats, indicating that the growth was mainly limited by P. Moreover, (4) except for the P element, the content of each element and its stoichiometric ratio were affected by the interaction between organs and habitat. Habitat had a greater impact on C content, whereas organs had a greater influence on N, P and K content and C:N, C:P, C:K and N:P.

Narrow-ranged species face challenges from natural disasters and human activities, and to address why species distributes only in a limited region is of great significance. Here we investigated the genetic diversity, gene flow, and genetic differentiation in six wild and three cultivated populations of Thuja sutchuenensis, a species that survive only in the Daba mountain chain, using chloroplast simple sequence repeats (cpSSR) and nuclear restriction site-associated DNA sequencing (nRAD-seq). Wild T. sutchuenensis populations were from a common ancestral population at 203 ka, indicating they reached the Daba mountain chain before the start of population contraction at the Last Interglacial (LIG, ∼120–140 ka). T. sutchuenensis populations showed relatively high chloroplast but low nuclear genetic diversity. The genetic differentiation of nRAD-seq in any pairwise comparisons were low, while the cpSSR genetic differentiation values varied with pairwise comparisons of populations. High gene flow and low genetic differentiation resulted in a weak isolation-by-distance effect. The genetic diversity and differentiation of T. sutchuenensis explained its survival in the Daba mountain chain, while its narrow ecological niche from the relatively isolated and unique environment in the “refugia” limited its distribution.

Land-use/land-cover change (LUCC) is an important factor affecting carbon storage. It is of great practical significance to quantify the relationship between LUCC and carbon storage for regional ecological protection and sustainable socio-economic development. In this study, we proposed an integrated framework based on multiobjective programming (MOP), the patch-level land-use simulation (PLUS) model, and the integrated valuation of ecosystem service and trade-offs (InVEST) model. First, we used the InVEST model to explore the spatial and temporal evolution characteristics of carbon storage in Hangzhou from 2000 to 2020 using land-cover data. Second, we constructed four scenarios of natural development (ND), economic development (ED), ecological protection (EP), and balanced development (BD) using the Markov chain model and MOP, and then simulated the spatial distribution of land cover in 2030 with the PLUS model. Third, the InVEST model was used to predict carbon storage in 2030. Finally, we conducted a spatial correlation of Hangzhou’s carbon storage and delineated carbon storage zoning in Hangzhou. The results showed that: (1) The artificial surfaces grew significantly, while the cultivated land decreased significantly from 2000 to 2020. The overall trend was a decrease in carbon storage, and the changing areas of carbon storage were characterized by local aggregation and sporadic distribution. (2) The areas of artificial surfaces, water bodies, and shrubland will continue to increase up to 2030, while the areas of cultivated land and grassland will continue to decrease. The BD scenario can effectively achieve the multiple objectives of ecological protection and economic development. (3) The carbon storage will continue to decline up to 2030, and the EP scenario will have the highest carbon storage, which will effectively mitigate the carbon storage loss. (4) The spatial distribution of carbon storage in Hangzhou was inextricably linked to the land cover, which was characterized by a high–high concentration and a low–low concentration. The results of the study can provide decision support for the sustainable development of Hangzhou and other cities in the Yangtze River Delta region.

In order to improve the application effect of inhibitors, the combination of seaweed extracts (SE), urease inhibitors (UIs) and nitrification inhibitors (NIs) were added to urea fertilizers for providing a theoretical basis to develop the efficient stabilized nitrogen (N) fertilizer. The combinations were tested in outdoor pots with no N fertilizer (CK) and application of urea alone (U) as control, and SE, N-butyl phosphorothioate triamine (NBPT), 3,4-dimethylpyrazole phosphate (DMPP), 2-chloro-6-trimethylpyridine (CP), and combinations of SE with each of the three inhibitors were added to urea to make seven fertilizer prototypes. The results showed that the addition of inhibitors and SE could regulate the N transformation, enzyme activity and microbial biomass carbon (MBC) contents and significantly improve maize yield and N use efficiency (NUE) (p < 0.05). Compared with the addition of inhibitor alone, the addition of SE was beneficial to N uptake by plants at the early growth stage of maize, but reduced the inhibitors effect; DMPP + S significantly increased the maize total biomass and NUE (p < 0.05), and the grain yield, N uptake and NUE by 15.6%, 28.5% and 30.6%, respectively. Therefore, the addition of DMPP with SE to urea significantly improved yield when planting maize in loess areas.

ABSTRACT: The genotype VII Newcastle disease virus (NDV) vaccine has begun to replace the traditional genotype II NDV vaccine and is widely used in the commercial poultry of China. However, the effect of homologous and heterogeneous anti-NDV serum on the evolution of prevalent NDV is unknown. To understand the effect of genotype II and VII anti-NDV serum on the evolution of genotype VII NDV strains, ZJ1 (waterfowl origin) and CH/SD/2008/128 (ND128; chicken origin) were used for serial passage of 30 generations in DF-1 cells without anti-NDV serum or with genotype II and VII anti-NDV serum independently. The F and HN genes of the 2 viruses were amplified for the 10th, 20th, and 30th generations of each serial passage group and compared with their respective original viruses. We found that there was only one mutation at position 248 in the F gene of ZJ1 due to the serum pressure of genotype VII anti-NDV. Similarly, mutations at residue 527 of the F gene, and position 9 and 319 of the HN gene of ND128 were noted in both anti-NDV serum groups. The results show that the nonsynonymous (NS)-to-synonymous (S) ratio of the F gene of ZJ1 virus was 1.6, and for the HN gene, it was 2.5 in the anti-II serum group. In the anti-VII serum group, the NS/S ratio for the F gene was 2.1, and for the HN gene, it was 2.5. The NS/S ratio of the F gene of the ND128 virus was 0.8, and for the HN gene, it was 3 in the anti-II serum group. Furthermore, the NS/S ratio of the F gene was 0.8, and the HN gene was 2.3 in the anti-VII group. Taken together, our findings highlight that there was no significant difference in the variation of protective antigens in genotype VII NDV under the selection pressure of homologous and heterogeneous genotype NDV inactivated vaccines.

A novel method is proposed to augment the precision and efficiency of the fatigue reliability analysis. This method utilizes an Improved Northern Goshawk Optimization (INGO) algorithm to optimize the BP neural network (BPNN). The enhanced Circle Chaotic Map, adaptive inertia weight, Elite opposition-based learning strategy, and artificial rabbits optimization strategy are incorporated to enhance both the accuracy and speed of the optimization algorithm. Proposing a fatigue reliability calculation approach for the bogie frame based on the maximum material utilization rate. The approach computes fatigue reliability through the segmentation of all bogie frame welds, employing the maximum material utilization rate within each experimental design scheme. The INGO-BPNN is trained using 80 sample sets acquired through experimental design. The fatigue reliability of the bogie frame is assessed using the Monte Carlo method based on the surrogate model. Research findings indicate that the surrogate model achieves a predictive accuracy of 99.8%, while the fatigue reliability of the bogie frame stands at 99.36%. The proposed method improves the calculation efficiency while ensuring the prediction accuracy of the model. [ABSTRACT FROM AUTHOR]