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Urban flooding is one of the main challenges affecting sustainable urban development worldwide, threatening the safety and well-being of communities and citizens. The aim of this study is to assess the development and trends in urban flood resilience at the city scale, as well as to improve the resilience of cities to these risks over time. The study constructs a model for assessing urban flood resilience that incorporates economic, social, ecological, and managerial aspects and assesses them through a range of indicators identified in the literature. The comprehensive evaluation model of Network Analysis Method–Entropy Weight Method–The Distance between Excellent and Inferior Solutions (ANP-EWM-TOPSIS) was used to empirically investigate the flood resilience characteristics of Nanjing from 2010 to 2021. There are two main findings of the study: firstly, the flood resilience of Nanjing gradually improves over time, as the economic flood resilience steadily increases, while the social, ecological, and management flood resilience decreases; and secondly, during the study period, barriers caused by economic and regulatory factors in Nanjing decreased by 33.75% and 23.72%, respectively, while barriers caused by social and ecological factors increased by 32.69% and 24.68%, respectively. The novelty of this study is the introduction of a “barrier degree” model, which identifies and highlights barriers and obstacles to improving urban flood resilience and provides new insights into improving urban flood resilience at the city scale.

In recent years, large-scale flood events have occurred more frequently, and the concept of resilience has become a prevalent approach to managing flood risk in many regions. This has led to an increased interest in how to effectively measure a city’s flood resilience levels. This study proposes a novel modeling approach to quantify urban flood resilience by developing D-number theory and analytical hierarchy process (AHP) models, which are applied to three cities in China using the VIse Kriterijumski Optimizacioni Racun (VIKOR) method. The findings reveal that Hefei City has the most effective level of flood resilience, Hangzhou City was ranked second, while Zhengzhou City has the least effective level of flood resilience. This study provides a new scientific basis on how to quantify flood resilience at the city scale and provides a useful reference for these three specific cities. The methods and approaches developed in this study have the potential to be applied to other cities and in the related aspects of disaster prevention, recovery, and reconstruction.

Spinetoram is an important semi-synthetic insecticide extensively applied in agriculture. It is neurotoxic to insects, primarily by acting on acetylcholine receptors (nAChRs). However, few studies have examined the neurotoxicity of spinetoram in human beings. In this study, various concentrations (5, 10, 15, and 20 μM) of spinetoram were employed to expose SH-SY5Y cells in order to study the neurotoxic effects of spinetoram. The results showed that spinetoram exposure markedly inhibited cell viability and induced oxidative stress. It also induced mitochondrial membrane potential collapse (ΔΨm), and then caused a massive opening of the mitochondrial permeability transition pore (mPTP), a decrease in ATP synthesis, and Ca2+ overloading. Furthermore, spinetoram exposure induced cellular autophagy, as evidenced by the formation of autophagosomes, the conversion of LC3-I into LC3-II, down-regulation of p62, and up-regulation of beclin-1. In addition, we observed that p-mTOR expression decreased, while p-AMPK expression increased when exposed to spinetoram, indicating spinetoram triggered AMPK/mTOR-mediated autophagy. Complementarily, the effect of spinetoram on neurobehavior was studied using the zebrafish model. After being exposed to different concentrations (5, 10, and 20 μg/mL) of spinetoram, zebrafish showed neurobehavioral irregularities, such as reduced frequency of tail swings and spontaneous movements. Similarly, autophagy was also observed in zebrafish. In conclusion, spinetoram exposure produced potential neurotoxicity through autophagy mediated by mitochondrial damage. The experimental data and results of the neurotoxicity study of spinetoram provided above are intended to serve as reference for its safety assessment.

Humanitarian supply chains play a major role in enabling disaster-affected areas to recover in a timely manner and enable economic and social activities to be restored. However, the sudden onset and increasing frequency of natural disasters such as flash floods require humanitarian supply chains to be resilient during the relief process. In this study, the evaluation indicators were identified from the literature and the Delphi method, and the weights of the evaluation indicators were calculated using the ANP method; the ANP method was combined with the Pythagorean fuzzy VIKOR (PFs-VIKOR) to propose the ANP-PFs-VIKOR method model. The model was used to examine the example of the 2021 megaflood event in Zhengzhou City to evaluate the performance of the humanitarian supply chain in four cities. The findings suggest that the indicator with the strongest impact on the effectiveness of humanitarian supply chains is coordination among participating organizations. Dengfeng City was found to have the best performing humanitarian supply chain. The findings of this research provide some helpful indication of the importance of the various emergency measures which can help to inform policy recommendations for the Zhengzhou municipal government.

The adverse effects of high temperatures on fruit quality and yield have been reported in many studies of grapevines. MiRNAs play crucial roles in plant growth and development and also fulfill functions in regulating the high-temperature response. In this research, miRNA-based SSR (simple sequence repeat) polymorphisms were analyzed according to the grape genome sequence and then combined with polymerase chain reaction (PCR) amplification and Sanger sequencing methods to analyze the miRNA-SSR diversity of different heat-resistant grape varieties. A statistical analysis of SSR sequences showed that 391 and 12 SSRs were specific to pri-miRNA and pre-miRNA, respectively. In pri-miRNA containing SSR, hexa-nucleotide repeats were the most abundant (52.69%), followed by tetra-nucleotide (13.04%) and minimum penta-nucleotide (4.09%), which were also observed in pre-miRNA sequences. On the other hand, differences in heat resistance among grape varieties were observed. Based on the results of leaf Fv/Fm images, values and phenotypic changes under high-temperature stress, 20 heat-resistant (e.g., Niagara Rosada and Grand Noir) and 20 heat-sensitive (e.g., Shine Muscat and Jumeigui) grape varieties were identified. Further, PCR-Sanger sequencing was used to screen SSR differences in four thermos-tolerant and four thermos-sensitive grape varieties, and finally, eight SSR differential primers were found to be able to distinguish these varieties. Of these, four pairs of primers were selected for validation in 40 grape germplasm resources (20 thermo-tolerance and 20 thermo-sensitivity). The VMIRSSR167c3 highlights that the ratio of SSR (CT) repeat values greater than 17 in heat-resistant varieties was 90%. In conclusion, the VMIRSSR167c3 marker can accurately distinguish between heat-resistant and heat-sensitive grape varieties. The results provide a novel molecular marker for the genetic improvement of grape germplasm resources and will be beneficial to the breeding of heat-resistant varieties in the future.

As one of the most frequently occurring natural hazards, flooding can seriously threaten global security and the sustainable development of our communities. Therefore, enhancing the resilience of cities and improving their ability to adapt to flooding have become issues of great significance. This study developed a new comprehensive evaluation model of flood resilience that includes an evaluation index system from the basis of four key dimensions of social resilience, economic resilience, ecological environment resilience and infrastructure resilience. Firstly, interpretative structural modelling (ISM) was applied to analyze the structural issues affecting urban flood resilience. Secondly, the analytic network process (ANP) was then used to calculate the importance of these indicators. Finally, taking three cities (Zhengzhou, Xi’an, and Jinan) in the Yellow River Basin of China as examples, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was used to evaluate their current levels of flood resilience using the findings from the earlier stages. The results show that the levels of rainfall and vulnerability of groups were the fundamental factors affecting urban flood resilience. Indicators such as average annual rainfall, fixed-asset investments, and emergency rescue capabilities were also found to have a greater impact on urban flood resilience. In the study area, Xi’an was found to have a higher level of resilience due to having strong ecological environmental resilience. These findings are expected to provide a useful reference for policymakers and stakeholders involved in the management of flooding events.

The widespread and excessive use of ivermectin (IVM) will not only cause serious environmental pollution, but will also affect metabolism of humans and other mammals that are exposed. IVM has the characteristics of being widely distributed and slowly metabolized, which will cause potential toxicity to the body. We focused on the metabolic pathway and mechanism of toxicity of IVM on RAW264.7 cells. Colony formation and LDH detection assay showed that IVM significantly inhibited the proliferation of and induced cytotoxicity in RAW264.7 cells. Intracellular biochemical analysis using Western blotting assay showed that LC3-B and Beclin-1 were upregulated and p62 was down-regulated. The combination of confocal fluorescence, calcein-AM/CoCl2, and fluorescence probe results showed that IVM could induce the opening of the mitochondrial membrane permeability transition pore, reduce mitochondrial content, and increase lysosome content. In addition, we focused on induction of IVM in the autophagy signal pathway. The Western blotting results showed that IVM increased expression of p-AMPK and decreased p-mTOR and p-S6K expression in protein levels, indicating that IVM activated the AMPK/mTOR signaling pathway. Therefore, IVM may inhibit cell proliferation by inducing cell cycle arrest and autophagy.

In recent years, the acceleration of urbanization processes coupled with more frequent extreme weather including more severe flood events, have led to an increase in the complexity of managing community flood resilience. This research presents an empirical study to explore the factors influencing community flood resilience in six communities located in the Hubei Province of China. The study presents the development of a flood resilience evaluation index system, comprising the use of the decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling method (ISM) methods. The results show that the three most important factors affecting the flood resilience capacity of the community are (i) the investment in disaster prevention, (ii) disaster relief capacity and (iii) flood control and drainage capacity. The differences between the six communities were analyzed across four dimensions to reveal the strengths and weaknesses of the communities across these dimensions and in terms of their overall resilience. By analyzing the causal hierarchical relationship that affects community flood resilience, this study helps to enhance community resilience to flood disasters and reduce disaster risk. These findings are conducive to enhancing the sustainable development of urban communities and are expected to provide scientific guidance for community risk management and strategic decision-making.

Root-zone restriction induces physiological stress on roots, thus limiting the vegetative and enhancing reproductive development, which promotes fruit quality and growth. Numerous bacterial-related growth-promoting, stress-mitigating, and disease-prevention activities have been described, but none in root-restricted cultivation. The study aimed to understand the activities of grapevine bacterial communities and plant-bacterial relationships to improve fruit quality. We used High-throughput sequencing, edaphic soil factors, and network analysis to explore the impact of restricted cultivation on the diversity, composition and network structure of bacterial communities of rhizosphere soil, roots, leaves, flowers and berries. The bacterial richness, diversity, and networking were indeed regulated by root-zone restriction at all phenological stages, with a peak at the veraison stage, yielding superior fruit quality compared to control plants. Moreover, it also handled the nutrient availability in treated plants, such as available nitrogen (AN) was 3.5, 5.7 and 0.9 folds scarcer at full bloom, veraison and maturity stages, respectively, compared to control plants. Biochemical indicators of the berry have proved that high-quality berry is yielded in association with the bacteria. Cyanobacteria were most abundant in the phyllosphere, Proteobacteria in the rhizosphere, and Firmicutes and Bacteroidetes in the endosphere. These bacterial phyla were most correlated and influenced by different soil factors in control and treated plants. Our findings are a comprehensive approach to the implications of root-zone restriction on the bacterial microbiota, which will assist in directing a more focused procedure to uncover the precise mechanism, which is still undiscovered.

Root restriction is a physical and ecological cultivation mode which restricts plant roots into a limited container to regulate vegetative and reproduction growth by reshaping root architecture. However, little is known about related molecular mechanisms. To uncover the root-related regulatory network of endogenous RNAs under root restriction cultivation (referred to RR), transcriptome-wide analyses of mRNAs, long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) involved in root development were performed. During root development, RR treatment had a positive effect on root weight, typically, young roots were significantly higher than conventional cultivation (referred to NR) treatment, suggesting that root architecture reconstruction under RR was attributed to the vigorous induction into lateral roots. Furthermore, a total of 26,588 mRNAs, 1971 lncRNAs, and 2615 circRNAs were identified in root of annual “Muscat Hamburg” grapevine by the transcriptomic analyses. The expression profile of mRNAs, lncRNAs and circRNA were further confirmed by the quantitative real-time PCR (RT-qPCR). Gene ontology enrichment analysis showed that a majority of the differentially expressed mRNAs, lncRNAs and circRNAs were enriched into the categories of cellular process, metabolic process, cell part, binding, and catalytic activity. In addition, the regulatory network of endogenous RNAs was then constructed by the prediction of lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA network, implying that these RNAs play significant regulatory roles for root architecture shaping in response to root restriction. Our results, for the first time, the regulatory network of competitive endogenous RNAs (ceRNAs) functions of lncRNA and circRNA was integrated, and a basis for studying the potential functions of non-coding RNAs (ncRNAs) during root development of grapevine was provided.

Cities around the world are having to become more resilient to the effects of climate change and ongoing development pressures and consequently are seeking to improve urban water resource management. In order to analyze the key factors affecting a city’s water resilience, this research establishes an urban water resilience evaluation model. The DEMATEL method is used to calculate the intensity of the interaction among the water resilience indicators and to establish their causal relationships. Then, an ANP structured diagram is established and the weighting of the water resilience evaluation index for the city of Wuhan is obtained using the Super Decisions software. The key water resilience factors for Wuhan are shown to have significant mutual influences, with the main factors found to be the utilization of rainwater resources, the utilization of reclaimed water, and the total annual runoff control of the city. This method provides a sound basis for the evaluation of urban water resilience with scope to extend this to other cities. The results provide useful guidance for policy makers and other key stakeholders in supporting more sustainable urban development.

This study investigated the effects of root-restriction cultivation on the root architecture, endogenous strigolactone (SL) content, and SL-related genes expression in grapevine (Vitis vinifera L.). In addition, we clarified the effects of synthetic SL analog GR24 application on grapevine roots to explore the role of SLs in their development. The results showed that the root architecture changed significantly under root-restriction cultivation. At 40 days after transplantation (DAT), the contents of two types of SLs in roots under root restriction were both significantly lower than that in roots of the control. SL content was significantly positively correlated with the expression levels of VvCCD8 and VvD27, indicating that they play vital roles in SLs synthesis. After GR24 treatment for 20 days, the root length was significantly shorter than in the control. A low concentration (0.1 μM) of GR24 significantly reduced the root diameter and increased the fine-root density, while a high concentration (10 μM) of GR24 significantly reduced the lateral root (LR) length and increased the LR density. Concomitantly, GR24 (0.1 μM) reduced endogenous SL content. After GR24 treatment for 5 days, the total content of two tested SLs was highly positively correlated with the expression levels of VvDAD2, whereas it was highly negatively correlated with VvSMAXL4 at 20 days after GR24 treatment. This study helps to clarify the internal mechanism of root-restriction cultivation affecting the changes in grapevine root architecture, as well as further explore the important role of SLs in the growth of grapevine roots in response to root-restriction treatment.

Frequent natural hazards such as flooding and the devastating consequences of severe events make the humanitarian supply chain particularly important in alleviating the suffering of those communities impacted by such events. However, the ambiguity of information and the different goals of stakeholders demand that the humanitarian supply chain must be resilient. This research adopts the use of literature review and expert opinions to identify the indicators that affect the resilience of the humanitarian supply chain using the flood event in Hechuan District, China in 2020 as an example. Based on the combination of fuzzy Decision-making Trial and Evaluation Laboratory and Analytic Network Process (fuzzy-DEMATEL-ANP), the interrelationships between the indicators and the weights of each indicator are calculated. The research results indicate that decision-makers in the humanitarian supply chain should vigorously coordinate the cooperation among stakeholders, ensure the effective transmission of information, and formulate forward-looking strategic plans. At the same time, these key decision makers should also be aware of the need to adjust their strategies at different stages of the flooding event in order to achieve a flexible humanitarian supply chain that responds to the varying demands over the course of a flooding event. The results of this study will help professionals involved in humanitarian supply chains to develop strategies and plans to become more resilient thus helping to reduce losses from natural hazards such as floods.

Flooding has become the natural disaster that causes the greatest losses, with urban flooding restricting the healthy development of cities. The ability to assess a city’s resilience to flooding is very important and would contribute to improving resilience and also help to inform planning and development. The aim of this study was to determine the key urban flood resilience indicators for three different Chinese cities (Wuhan, Nanjing, and Hefei) and to prioritize these for each city. A combined interpretive structure and network analysis method (ISM-ANP) model was used to evaluate and analyze the selected evaluation indicators. A four-level urban flood resilience evaluation network model was constructed to determine the interdependence between indicators and to calculate the priorities of the flood resilience indicators for the three cities. Overall, rescue capacity was found to be extremely important and was defined as the most important index. For Wuhan, indicators related to the distribution of waters were found to be more important, while for Nanjing, spatial planning and spatial structure of land use were found to be key priorities. In Hefei, the level of investment in infrastructure and the level of public resources occupy a more important position. The framework presented in this study contributes to the understanding of urban flood resilience and has the potential to be extended to other natural hazards.

Due to population growth and human activities, water shortages have become an increasingly serious concern in recent years. The agri-food industry is the largest water-consuming industry among all industries, and various efforts have been made to reduce the loss of water in the agricultural supply chain. Improving the resilience of water resource management is a key measure to reduce the risks in the agricultural supply chain. This study aims to identify the factors affecting the resilience of water management in the agricultural supply chain and to help manage the risks related to water resources use. A total of 14 factors are selected from five dimensions of society, economy, environment, institution, and crop characteristics, and an index institution is constructed. This was used to determine the level and importance of each factor. Data were collected through a questionnaire survey involving 28 experts from the agricultural industry in Northwest China, as well as a thorough literature analysis and interactions with experts. Using a combination of an interpretative structural model (ISM) and an analytical network process (ANP), a hierarchical structure model was developed, composed of direct factors, indirect factors, and basic factors. The results show that the selection of agricultural products, the establishment of a water audit control institution, the recycling of wastewater, and the investment in water-saving technologies are the main factors affecting the resilience of water resources management in the agricultural supply chain. These findings provide useful guidance for practitioners involved in the management of water resources in agricultural supply chains. These results are expected to contribute to the sustainable management and strategic deployment of water by agricultural supply chain stakeholders.

The compositions and contents of metabolites in the pulp tissue play critical roles in the fruit quality for table grape. In this study, the effects of root restriction (RR) on the primary and secondary metabolites of pulp tissue at five developmental stages were studied at the metabolomics level, using “Red Alexandria” grape berry (Vitis vinifera L.) as materials. The main results were as follows: 283 metabolites were annotated by using ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS); 28 and 16 primary metabolites contents were increased and decreased, and 11 and 19 secondary metabolites contents were increased and decreased, respectively, along the berry development; RR significantly decreased 12 metabolites (four amino acids and derivatives, three organic acids, four flavonoids and one other compound) contents, and improved 40 metabolites (22 amino acids and derivatives, six nucleotides, four carbohydrates, four cofactors, three cinnamic acids and one other compound) accumulation at the different developmental stages. Altogether, our study would be helpful to increase our understanding of grape berry’s responses to RR stress.

Pseudomonas syringae pv. actinidiae (Psa) is a phytopathogen that causes canker in kiwifruit. Few conventional control methods are effective against this bacterium. Therefore, alternative approaches, such as phage therapy are warranted. In this study, a lytic bacteriophage (PN09) of Psa was isolated from surface water collected from a river in Hangzhou, China in 2019. Morphologically, PN09 was classified into the Myoviridae family, and could lyse all 29 Psa biovar 3 strains. The optimal temperature and pH ranges for PN09 activity were determined as 25 to 35 ∘C and 6.0 to 9.0, respectively. The complete genome of PN09 was found to be composed of a linear 99,229 bp double-stranded DNA genome with a GC content of 48.16%. The PN09 endolysin (LysPN09) was expressed in vitro and characterized. LysPN09 was predicted to belong to the Muraidase superfamily domain and showed lytic activity against the outer-membrane-permeabilized Psa strains. The lytic activity of LysPN09 was optimal over temperature and pH ranges of 25 to 40 ∘C and 6.0 to 8.0, respectively. When recombinant endolysin LysPN09 was combined with EDTA, Psa strains were effectively damaged. All these characteristics demonstrate that the phage PN09 and its endolysin, LysPN09, are potential candidates for biocontrol of Psa in the kiwifruit industry.

While various measures of mitigation and adaptation to climate change have been taken in recent years, many have gradually reached a consensus that building community resilience is of great significance when responding to climate change, especially urban flooding. There has been a dearth of research on community resilience to urban floods, especially among transient communities, and therefore there is a need to conduct further empirical studies to improve our understanding, and to identify appropriate interventions. Thus, this work combines two existing resilience assessment frameworks to address these issues in three different types of transient community, namely an urban village, commercial housing, and apartments, all located in Wuhan, China. An analytic hierarchy process–back propagation neural network (AHP-BP) model was developed to estimate the community resilience within these three transient communities. The effects of changes in the prioritization of key resilience indicators under different environmental, economic, and social factors was analyzed across the three communities. The results demonstrate that the ranking of the indicators reflects the connection between disaster resilience and the evaluation units of diverse transient communities. These aspects show the differences in the disaster resilience of different types of transient communities. The proposed method can help decision makers in identifying the areas that are lagging behind, and those that need to be prioritized when allocating limited and/or stretched resources.

Pseudomonas syringae pv. actinidiae (Psa) is the causative agent of the bacterial canker of kiwifruit (Actinidia spp.). Phage therapy has been suggested as a viable alternative approach to controlling this disease, but its efficacy is limited by the emergence of phage-resistant mutants. Carvacrol is an essential oil that may be useful for the control of Psa. Combination therapies can be used to overcome resistance development. Here, the combination of phages (single phage suspensions of phages PN05 and PN09, and a cocktail of both phages) and carvacrol was investigated in controlling Psa planktonic and biofilm forms in vitro. The phage therapy alone (with phages PN05 and PN09), and the carvacrol alone (minimum inhibitory concentration 2.0 mg/mL), inhibited Psa growth, but the combined effect of both therapies was more effective. The phages alone effectively inhibited Psa growth for 24 h, but Psa regrowth was observed after this time. The carvacrol (2.0 mg/mL) alone prevented the biofilm formation for 48 h, but did not destroy the pre-formed biofilms. The combined treatment, phages and carvacrol (2.0 mg/mL), showed a higher efficacy, preventing Psa regrowth for more than 40 h. In conclusion, the combined treatment with phages and carvacrol may be a promising, environment-friendly and cost-effective approach to controlling Psa in the kiwifruit industry.

Root restriction cultivation (RRC) can influence plant root architecture, but its root phenotypic changes and molecular mechanisms are still unknown. In this study, phenotype observations of grapevine root under RRC and control cultivation (nRC) at 12 time points were conducted, and the root phenotype showed an increase of adventitious and lateral root numbers and root tip degeneration after RRC cultivation from 70 days after planting (DAP). The 70 and 125 DAP sampling of two different cultivations, named nR70, RR70, nR125, and RR125, were selected for small RNA sequencing. A total of 153 known miRNAs and 119 predicted novel miRNAs were obtained. Furthermore, BLAST was used to predict the novel miRNAs with miRBase databases using the default parameters; 96 of the 119 predicted novel miRNAs were similar to other species, and the remaining 23 grapevine-specific novel miRNAs were obtained. There were 26, 33, 26, and 32 miRNAs that were differentially expressed in different comparison groups (RR70 vs. nR70, RR125 vs. nR125, nR125 vs. nR70 and RR125 vs. RR70). Target genes prediction of differentially expressed miRNAs was annotated on a variety of biological processes, and 24 participated in root development. Moreover, multiple miRNAs were found to jointly regulate lateral root development under root restriction conditions. The miRNA expression pattern comparison between RRC and nRC may provide a framework for the future analysis of miRNAs associated with root development in grapevine.

Floral bud dormancy release of fruit tree species is greatly influenced by climate change. The lack of chilling accumulation often results in the occurrence of abnormal flower and low yields of sweet cherries (Prunus avium L.) in warm regions. To investigate the regulation of dormancy in sweet cherries, six DAM genes with homology to peach DAM, designated PavDAM1-6, have been identified and characterized. Phylogenetic analysis indicate that these genes are similar to DAMs in peach, apple and pear. The expression patterns of the PavDAMs in the low-chill cultivar ‘Royal Lee’ were different from that in the high-chill cultivar ‘Hongdeng’. ‘Royal Lee’ exhibits lower transcriptional level of PavDAM1 compared to ‘Hongdeng’, especially at the stage of chilling accumulation, and transcriptional levels of PavDAM4/5 were high in both cultivars during the endodormancy. Ectopic expression of PavDAM1 and PavDAM5 in Arabidopsis resulted in plants with abnormal flower and seed development, especially the PavDAM5. Higher transcriptional levels of SOC1 were observed in transgenic PavDAM1/5 lines, and ectopic expression of PavSOC1 had the similar floral phenotype. Further, protein interaction analysis demonstrated that PavDAM1/5 could interact with PavSOC1 in vivo and in vitro, which will help clarify the molecular mechanism of the flower development in sweet cherry or other fruit trees.

Retinoic acid-inducible gene I (RIG-I), a cytosolic pattern recognition receptor (PRR), can sense various RNA viruses, including the avian influenza virus (AIV) and infectious bursal disease virus (IBDV), and trigger the innate immune response. Previous studies have shown that mammalian RIG-I (human and mice) and waterfowl RIG-I (ducks and geese) are essential for type I interferon (IFN) synthesis during AIV infection. Like ducks, pigeons are also susceptible to infection but are ineffective propagators and disseminators of AIVs, i.e., “dead end” hosts for AIVs and even highly pathogenic avian influenza (HPAI). Consequently, we sought to identify pigeon RIG-I and investigate its roles in the detection of A/Chicken/Shandong/ZB/2007 (H9N2) (ZB07), Gansu/Tianshui (IBDV TS) and Beijing/CJ/1980 (IBDV CJ-801) strains in chicken DF-1 fibroblasts or human 293T cells. Pigeon mRNA encoding the putative pigeon RIG-I analogs was identified. The exogenous expression of enhanced green fluorescence protein (EGFP)-tagged pigeon RIG-I and caspase activation and recruitment domains (CARDs), strongly induced antiviral gene (IFN-β, Mx, and PKR) mRNA synthesis, decreased viral gene (M gene and VP2) mRNA expression, and reduced the viral titers of ZB07 and IBDV TS/CJ-801 virus strains in chicken DF-1 cells, but not in 293T cells. We also compared the antiviral abilities of RIG-I proteins from waterfowl (duck and goose) and pigeon. Our data indicated that waterfowl RIG-I are more effective in the induction of antiviral genes and the repression of ZB07 and IBDV TS/CJ-801 strain replication than pigeon RIG-I. Furthermore, chicken melanoma differentiation associated gene 5(MDA5)/ mitochondrial antiviral signaling (MAVS) silencing combined with RIG-I transfection suggested that pigeon RIG-I can restore the antiviral response in MDA5-silenced DF-1 cells but not in MAVS-silenced DF-1 cells. In conclusion, these results demonstrated that pigeon RIG-I and CARDs have a strong antiviral ability against AIV H9N2 and IBDV in chicken DF-1 cells but not in human 293T cells.

Root restriction cultivation leads to early maturation and quality improvement, especially in the anthocyanin content in grapevine. However, the molecular mechanisms that underlie these changes have not been thoroughly elucidated. In this study, four small RNA libraries were constructed, which included the green soft stage (GS) and ripe stage (RS) of ‘Muscat’ (Vitis vinifera L.) grape berries that were grown under root restriction (RR) and in traditional cultivation (no root restriction, CK). A total of 162 known miRNAs and 14 putative novel miRNAs were detected from the four small RNA libraries by high-throughput sequencing. An analysis of differentially expressed miRNAs (DEMs) revealed that 13 miRNAs exhibited significant differences in expression between RR and CK at the GS and RS stages, respectively. For different developmental stages of fruit, 23 and 34 miRNAs showed expression differences between the GS and RS stages in RR and CK, respectively. The expression patterns of the eight DEMs and their targets were verified by qRT-PCR, and the expression profiles of target genes were confirmed to be complementary to the corresponding miRNAs in RR and CK. The function of Vvi-miR828, which showed the down regulated expression in the RS stage under root restriction, was identified by gene transformation in Arabidopsis. The anthocyanin content significantly decreased in transgenic lines, which indicates the regulatory capacity of Vvi-miR828 in fruit coloration. The miRNA expression pattern comparison between RR and CK might provide a means of unraveling the miRNA-mediated molecular process regulating grape berry development under root restricted cultivation.

This research aimed to comparatively evaluate the influences of root restriction (RR) cultivation and traditional cultivation (RC) on grape berry skin metabolomics using a non-targeted metabolomics method. Two-hundred-and-ninety-one metabolites were annotated and the kinetics analyses showed that berry skin metabolome is stage- and cultivation-dependent. Our results showed that RR influences significantly the metabolomes of berry skin tissues, particularly on secondary metabolism, and that this effect is more obvious at pre-veraison stage, which was evidenced by the early and fast metabolic shift from primary to secondary metabolism. Altogether, this study provided an insight into metabolic adaptation of berry skin to RR stress and expanded general understanding of berry development.

We present an in-depth analysis of aroma profiles and sensory attributes, employing solid-phase microextraction gas chromatography/mass spectrometry (SPME-GC-MS) to identify the key compounds driving consumer preference in 19 unfamiliar cultivars. In combination with popular cultivars, we identified a total of 100 compounds in all table grapes, of which 26 key volatiles were correlated with consumer liking. Based on this relationship, five aroma combinations (AC) were formulated, wherein 33 compounds contributed to aroma intensity, and thus, were viewed as active volatiles. The fruity, floral, and sweet aromas were further divided into secondary aromatic series, of which the apple, citrus, orange, rose, geranium, violet, and honey aromas constituted the predominant series in unfamiliar cultivars. Xiangyue and Heikuixiang emerged as the preferred table grapes according to our analysis. By comparison, the popular cultivars showed relatively fewer volatiles, but their contents were much greater than the large number of volatiles identified in the unfamiliar cultivars.

A number of polysaccharides have been reported to show immunomodulatory and antiviral activities against various animal viruses. AEX is a polysaccharide extracted from the green algae, Coccomyxa gloeobotrydiformis. The aim of this study was to examine the function of AEX in regulating the immune response in chickens and its capacity to inhibit the infectious bursal disease virus (IBDV), to gain an understanding of its immunomodulatory and antiviral ability. Here, preliminary immunological tests in vitro showed that the polysaccharide AEX can activate the chicken peripheral blood molecular cells’ (PBMCs) response by inducing the production of cytokines and NO, promote extracellular antigen presentation but negatively regulate intracellular antigen presentation in chicken splenic lymphocytes, and promote the proliferation of splenic lymphocytes and DT40 cells. An antiviral analysis showed that AEX repressed IBDV replication by the deactivation of viral particles or by interfering with adsorption in vitro and reduced the IBDV viral titer in the chicken bursa of Fabricius. Finally, in this study, when AEX was used as an adjuvant for the IBDV vaccine, specific anti-IBDV antibody (IgY, IgM, and IgA) titers were significantly decreased. These results indicate that the polysaccharide AEX may be a potential alternative approach for anti-IBDV therapy and an immunomodulator for the poultry industry. However, more experimentation is needed to find suitable conditions for it to be used as an adjuvant for the IBDV vaccine.

Due to the increasing integration of photovoltaic (PV) solar power into power systems, the prediction of PV solar power output plays an important role in power system planning and management. This study combines an optimized data clustering method with a serially integrated AdaLSTM network to improve the accuracy and robustness of PV solar power prediction. During the data clustering process, the Euclidean distance-based clustering centroids are optimized by an improved particle swarm optimization (iPSO) algorithm. For each obtained data cluster, the AdaLSTM network is utilized for model training, in which multiple LSTMs are serially combined together through the AdaBoost algorithm. For PV power prediction tasks, the inputs of the testing set are classified into the nearest data cluster by the K-nearest neighbor (KNN) method, and then the corresponding AdaLSTM network of this cluster is used to perform the prediction. Case studies from two real PV stations are used for prediction performance evaluation. Results based on three prediction horizons (10, 30 and 60 min) demonstrate that the proposed model combining the optimized data clustering and AdaLSTM has higher prediction accuracy and robustness than other comparison models. The root mean square error (RMSE) of the proposed model is reduced, respectively, by 75.22%, 73.80%, 67.60%, 66.30%, and 64.85% compared with persistence, BPNN, CNN, LSTM, and AdaLSTM without clustering (Case A, 30 min prediction). Even compared with the model combining the K-means clustering and AdaLSTM, the RMSE can be reduced by 10.75%.

Based on the research background of improving personal thermal comfort and promoting building energy efficiency, personal comfort systems (PCSs) have recently received considerable attention. The thermoelectric conversion unit (TECU) has great potential in PCSs as it is compact in size, environmentally friendly and highly reliable. Aiming to improve heat exchange efficiency, this paper investigates the structural optimization of heat sink for the TECU used in PCSs. Firstly, the heat exchange mechanism of the thermoelectric module is analyzed. The structural design of the cold-side heat sink in the TECU is summarized as a multiobjective optimization problem in which four structural parameters (number of fin rows, fin thickness, fin height and thickness of base) of the heat sink are selected as the adjusting variables. Then, based on the establishment of the cold-side computational fluid dynamics simulation model, a multiobjective genetic algorithm is utilized for the optimization task. Sensitivity analysis demonstrates that the number of rows and the fin thickness have significant influence on the optimization objectives. Taking both the outlet airflow temperature and the velocity into consideration, five representative heat sinks involving two different materials are customized. A testing platform is built for performance comparison. Results show that the proposed optimization method can effectively improve the heat exchange efficiency of a TECU, which provides a reference for the TECU-based PCS design.

As one of the major production facilities in agriculture, a greenhouse has many spatial distributed factors influencing crop growth and energy consumption, such as temperature field, air flow pattern, CO 2 concentration distribution, etc. By introducing a hybrid computational fluid dynamics−evolutionary algorithm (CFD-EA) method, this paper constructs a micro-climate model of greenhouse with main environmental parameters optimized. Considering environmental factors’ spatial influences together with energy usage simultaneously, the optimal solutions of control variables for crop growth are calculated. A commercial greenhouse located in east China is chosen for the method validation. Field experiments using temperature/velocity sensor matrix are carried out for CFD accuracy investigation. On this basis, the proposed optimization method is employed to search for the optimal control variables and parameters corresponding to the environmental Pareto frontier. By the proposed multi-objective scheme, we believe the method can provide set point basis for the design and regulation of large/medium-sized greenhouse production with high spatial resolution.

This paper is concerned with the development of a high-resolution and control-friendly optimization framework in enclosed environments that helps improve thermal comfort, indoor air quality (IAQ), and energy costs of heating, ventilation and air conditioning (HVAC) system simultaneously. A computational fluid dynamics (CFD)-based optimization method which couples algorithms implemented in Matlab with CFD simulation is proposed. The key part of this method is a data interactive mechanism which efficiently passes parameters between CFD simulations and optimization functions. A two-person office room is modeled for the numerical optimization. The multi-objective evolutionary algorithm—non-dominated-and-crowding Sorting Genetic Algorithm II (NSGA-II)—is realized to explore the environment/energy Pareto front of the enclosed space. Performance analysis will demonstrate the effectiveness of the presented optimization method.

Numerous conflicting criteria exist in building design optimization, such as energy consumption, greenhouse gas emission and indoor thermal performance. Different simulation-based optimization strategies and various optimization algorithms have been developed. A few of them are analyzed and compared in solving building design problems. This paper presents an efficient optimization framework to facilitate optimization designs with the aid of commercial simulation software and MATLAB. The performances of three optimization strategies, including the proposed approach, GenOpt method and artificial neural network (ANN) method, are investigated using a case study of a simple building energy model. Results show that the proposed optimization framework has competitive performances compared with the GenOpt method. Further, in another practical case, four popular multi-objective algorithms, e.g., the non-dominated sorting genetic algorithm (NSGA-II), multi-objective particle swarm optimization (MOPSO), the multi-objective genetic algorithm (MOGA) and multi-objective differential evolution (MODE), are realized using the propose optimization framework and compared with three criteria. Results indicate that MODE achieves close-to-optimal solutions with the best diversity and execution time. An uncompetitive result is achieved by the MOPSO in this case study.