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Agricultural Jiaosu is rich in nutrients and plant-beneficial microbial communities, and thus has great potential in reducing fertilizer dosage and improving fertilizer use efficiency. This pot experiment was conducted to investigate the effects of agricultural Jiaosu on the growth and yield of rice. The experiment employed three agricultural Jiaosu treatments (i.e., soil solid agricultural Jiaosu, soil liquid agricultural Jiaosu, leaf liquid agricultural Jiaosu) in various combinations, along with one control treatment (chemical fertilizer). Results revealed that plant height of rive agricultural Jiaosu treatments were higher than that of the control treatment, with the ranks as follows: JT (soil solid agricultural Jiaosu + soil liquid agricultural Jiaosu), JY (soil solid agricultural Jiaosu + leaf liquid agricultural Jiaosu), JA (soil solid agricultural Jiaosu + soil liquid agricultural Jiaosu + leaf liquid agricultural Jiaosu) and F (conventional fertilizer) during harvest. The ratio of panicle biomass to total biomass and straw of three types of Jiaosu treatments was significantly higher than that in the chemical fertilizer treatment, indicating that agricultural Jiaosu treatment altered the dry matter distribution characteristics of rice. The yield per plant of JA treatment (49.35 ± 2.43 g) was 8.51% higher than chemical fertilizer treatment. Additionally, the correlation between soil nutrients and plant growth and yield analysis indicated that agricultural Jiaosu has higher nutrient use efficiency with lower input of N, P, and K. The study highlights the potential function of agricultural Jiaosu in promoting crop growth and yields while reducing the need for fertilization.

Large-scale distributed generation (DG) access to the distribution network brings many uncertainties to the distribution network, considering the impact of different types of distributed power supply on the optimization results as well as the uncertainty and correlation of wind energy, photovoltaic power generation, and load. A metaheuristic algorithm the Improved Beluga Whale Optimization Algorithm (IBWO) is used to optimize the capacity and location of DG. This algorithm incorporates the elite reverse learning strategy and cyclone foraging strategy while adjusting the balance factor to enhance the diversity of the algorithm population and further balance local search capability with global search capability. This study optimizes the configuration of distributed energy resources considering the uncertainty and correlation of wind power, photovoltaic power, and load. The optimization objective is to reduce active power loss, improve voltage stability, and minimize investment and operating costs. By conducting simulations on IEEE 33-bus and IEEE 118-bus test cases, the active power network losses are enhanced by 55.49% and 45.39% respectively, and the algorithm outperforms other methods regarding other data, demonstrating its superiority and effectiveness.

The duck oil microcapsule powder was prepared by spray drying with sodium starch octenyl succinate (wall materials), maltodextrin (wall materials) and duck oil (core materials) to broaden the application of duck oil in food industry. Then, the flavoring powder of duck soup was prepared with edible salt, granulated sugar, yeast extract and disodium flavored nucleotides. The optimum formula of the flavoring powder of duck soup was determined using single factor and response surface optimization test by taking the sensory score as the response value. The results showed that 205 g/L of duck oil microcapsule powder, 155 g/L of edible salt, 87.5 g/L of granulated sugar, 7.8 g/L of yeast extract and 7.5 g/L of disodium flavored nucleotides were the best in the sensory score of 84.9 and taste of the flavoring powder of duck soup. In addition, the volatile flavor compounds of the flavoring powder of duck soup were determined by headspace solid phase microextraction combined with GC-MS. A total of 49 kinds of volatile flavor compounds were identified, among which aldehydes and alcohols were the most abundant. The characteristic volatile flavor compounds of the flavoring powder of duck soup were determined as nonanal, octanal and 3-octenol, by calculating the odor activity value, and all of these compounds gave the flavoring powder of duck soup unique fresh aroma together. The study improved the utilization of duck oil in the oil system, and will provide some theoretical guidance and reference for the application of microcapsule powder.

Abstract The spike protein of SARS‐CoV‐2 hijacks the host angiotensin converting enzyme 2 (ACE2) to meditate its entry and is the primary target for vaccine development. Nevertheless, SARS‐CoV‐2 keeps evolving and the latest Omicron subvariants BQ.1 and XBB have gained exceptional immune evasion potential through mutations in their spike proteins, leading to sharply reduced efficacy of current spike‐focused vaccines and therapeutics. Compared with the fast‐evolving spike protein, targeting host ACE2 offers an alternative antiviral strategy that is more resistant to viral evolution and can even provide broad prevention against SARS‐CoV and HCoV‐NL63. Here, we use prime editor (PE) to precisely edit ACE2 at structurally selected sites. We demonstrated that residue changes at Q24/D30/K31 and/or K353 of ACE2 could completely ablate the binding of tested viruses while maintaining its physiological role in host angiotensin II conversion. PE‐mediated ACE2 editing at these sites suppressed the entry of pseudotyped SARS‐CoV‐2 major variants of concern and even SARS‐CoV or HCoV‐NL63. Moreover, it significantly inhibited the replication of the Delta variant live virus. Our work investigated the unexplored application potential of prime editing in high‐risk infectious disease control and demonstrated that such gene editing‐based host factor reshaping strategy can provide broad‐spectrum antiviral activity and a high barrier to viral escape or resistance.

Distributed generation equipment improves renewable energy utilization and economic benefits through an energy storage system (ESS). However, dominated by short-term data, the configuration of long-period ESS capacity is absent based on the dynamic change of load, which leads to a large deviation from the expected return. Considering the system characteristics of lack of data and less information, after introducing the grey theory, we propose a new long-term capacity configuration method for ESS and establish the long-term grey forecasting model (GFM) of user load, improving the basic forecasting model to improve the accuracy of the long-term forecasting model. Then, the scheduling model is established with the maximum economic and social benefits as the optimization objective. Based on the forecast data of the improved grey forecasting model (IGFM), the hierarchical solution method is used to solve the scheduling model. Finally, the parameters are configured based on the service life of the equipment and the expected rate of return. The simulation results show that higher accuracy is realized in the improved prediction model, and the improved algorithm gets higher convergence speed and precision. Apart from that, the nonlinear correlation trend of the EES return rate between the capacity and life cycle is revealed. Compared with the ESS configuration in a short period, this study provides more comprehensive and accurate data support for the capacity configuration of the ESS, reducing the error between the actual return and the expected return significantly.

In order to improve the ability to detect and identify topological errors and measurement errors, and further enhance the rapidity and reliability of substation state estimation, this paper proposes a three-phase linear state estimation method for substations based on zero impedance model. Firstly, for the shortcomings of the traditional regularized weighted residual method with many cycles and slow calculation speed, improvements are made to improve the rapidity of state estimation while suppressing the residual flooding phenomenon. Based on this, the zero-impedance model of the substation makes full use of the three-phase telemetry and telecommunication state data to establish the power measurement equation for zero-impedance initial power state estimation, and proposes a discrimination method to identify measurement errors and topological errors and to determine the state of the switching circuit breakers. Based on the secondary power state estimation, a voltage measurement equation is established based on the voltage measurement information to estimate the substation voltage state. The simulation results show that the method can accurately identify and locate the simultaneous measurement errors and topology errors, and can also identify individual measurement errors, thus improving the estimation accuracy of state estimation.

Prime editors can mediate all twelve types of base substitutions and small insertions or deletions in living cells but its efficiency remains low. Here the authors introduce same-sense mutations into pegRNAs to increase base-editing efficiency and the pegRNA secondary structure was altered to increase indel-editing efficiency.

Traditional shallow machine learning algorithms cannot effectively explore the relationship between the fault data of oil-immersed transformers, resulting in low fault diagnosis accuracy. This paper proposes a transformer fault diagnosis method based on Multi-class AdaBoost Algorithms in response to this problem. First, the AdaBoost algorithm is combined with Support Vector Machines (SVM), The SVM is enhanced through the AdaBoost algorithm, and the transformer fault data is deeply explored. Then the dynamic weight is introduced into the Particle Swarm Optimization (PSO); through the real-time update of the particle inertia weight, the search accuracy and optimization speed of the particle swarm optimization algorithm is improved, and the improved particle swarm optimization algorithm (IPSO) is used to optimize the parameters of the SVM. Finally, by analyzing the relationship between the dissolved gas in the transformer oil and the fault type, the uncoded ratio method forms a new gas group cooperation. The improved ratio method is constructed as the input feature vector. Simulations based on 117 sets of IECTC10 standard data and 419 sets of transformer fault data collected in China show that the diagnosis method proposed in this paper has strong search ability and fast convergence speed and has a significant improvement in diagnostic accuracy compared with traditional methods.

In this paper, a novel fuzzy fault tolerance algorithm is proposed for quarter vehicle active suspensions based on multi-objective constrained optimizations, which improves the riding comfort and driving safety. The objective function approach the optimal solutions via integrating multi-objective constraints as cost functions. By introducing the barrier function, the nonlinear active suspensions with multi-objective constraints are transformed into pure feedback systems without constraints. The problem is rather complicated yet challenging if the actuator faults are taken into account in quarter vehicle. The actuator faults are solved by the utilization of proportional actuation method. The unknown smooth dynamics based on physical truth are identified by exploiting the fuzzy logic knowledge. Meanwhile, the signals received in the suspensions do not violate the constraint boundary. Finally, the simulation results show that the algorithm is effective.

Hypoxia is one of the most important environmental stressors in aquatic ecosystems. To deal with the hypoxia environment, fishes exhibit a series of physiological and molecular responses to maintain homeostasis and organism functions. In the present study, hypoxia-induced changes in gene expression profiles and alternative splicing (AS) events in spotted sea bass (Lateolabrax maculatus), a promising marine-culture fish species in China, were thoroughly investigated by RNA-Seq analysis. A total of 1,242, 1,487 and 1,762 differentially expressed genes (DEGs) were identified at 3 h, 6 h and 12 h in gills after hypoxia stress. Functional enrichment analysis by KEGG and GSEA demonstrated that HIF signal network system was significantly activated and cell cycle process was remarkably suppressed in response to hypoxia. According to the temporal gene expression profiles, six clusters were generated and protein-protein interaction (PPI) networks were constructed for the two clusters that enriched with hypoxia-induced (cluster 2) or -suppressed genes (cluster 5), respectively. Results showed that HIF signaling related genes including vegfa, igf1, edn1, cox2b, cxcr4b, ctnnb1, and slc2a1a, were recognized as hubs in cluster 2, while mcm2, chek1, pole, mcm5, pola1, and rfc4, that tightly related to cell cycle, were down-regulated and considered as hubs in cluster 5. Furthermore, a total of 410 differential alternative splicing (DAS) genes were identified after hypoxia, which were closely associated with spliceosome. Of them, 63 DAS genes also showed differentially expressed levels after hypoxia, suggesting that their expression changes might be regulated by AS mechanism. This study revealed the key biological pathways and AS events affected by hypoxia, which would help us to better understand the molecular mechanisms of hypoxia response in spotted sea bass and other fish species.

Dissolved gas analysis (DGA) is a widely used method for diagnosing internal transformer defects. The traditional single intelligent diagnostic method cannot efficiently process large amounts of incomplete defect information with DGA, which affects the accuracy of fault diagnosis. To this end, this paper proposes a transformer fault diagnosis method based on the optimization of kernel parameters and weight parameters of a kernel extreme learning machine (KELM). First, based on Mercer’s theorem, we combine the radial basis kernel function with the polynomial kernel function to construct a new hybrid kernel function. Then, the gray wolf optimization (GWO) algorithm and the differential evolution (DE) algorithm are combined to improve the diversity of the gray wolf population, enhance the searchability of GWO, and prevent GWO from falling into a local optimum during the iterative process. Finally, the kernel parameters and weight parameters of the hybrid kernel function are optimized by using the modified grey wolf optimization (MGWO) algorithm. The International Electrotechnical Commission Technical Committee (IEC TC) 10 transformer fault data and constructed hybrid feature set is used as the input set of the model, the model is simulated and analyzed, and the transformer fault data collected at a site are used for training and verification. The simulation results on the two sets of data show that the method can accurately and effectively diagnose transformer faults, and has a higher fault diagnosis accuracy rate than traditional methods.

We explore physical layer security of simultaneous wireless information and power transfer (SWIPT) relay network in this paper. Modeling channel error between relay and eavesdroppers (Eves) as random channel state information (CSI) error, we present an algorithm to optimize secret rate of SWIPT in the constraints of relay forward power, receiver signal-to-interference-plus-noise ratio (SINR) and Eves SINR. A slack variable is introduced to decompose original non-convex problem into upper and lower sub-problems, meanwhile, Bernstein-type inequality is used to convert probability constraint of lower sub-problems to linear matrix inequality constraints. Simulation experiments show that the proposed algorithm obtains higher secret rate than that of zero-forcing algorithm and worst-case algorithm.

Heat shock proteins (HSPs) are a large class of highly conserved chaperons, which play important roles in response to elevated temperature and other environmental stressors. In the present study, 5 HSP90 genes and 17 HSP70 genes were systematically characterized in spotted seabass (Lateolabrax maculatus). The evolutionary footprint of HSP genes was revealed via the analysis of phylogeny, chromosome location, and gene copy numbers. In addition, the gene structure features and the putative distribution of heat shock elements (HSEs) and hypoxia response elements (HREs) in the promoter regions were analyzed. The protein-protein interaction (PPI) network analyses results indicated the potential transcriptional regulation between the heat shock factor 1 (HSF1) and HSPs and a wide range of interactions among HSPs. Furthermore, quantitative (q)PCR was performed to detect the expression profiles of HSP90 and HSP70 genes in gill, liver, and muscle tissues after heat stress, meanwhile, the expression patterns in gills under alkalinity and hypoxia stresses were determined by analyzing RNA-Seq datasets. Results showed that after heat stress, most of the examined HSP genes were significantly upregulated in a tissue-specific and time-dependent manners, and hsp90aa1.1, hsp90aa1.2, hsp70.1, and hsp70.2 were the most intense responsive genes in all three tissues. In response to alkalinity stress, 11 out of 13 significantly regulated HSP genes exhibited suppressed expression patterns. Alternatively, among the 12 hypoxia-responsive-expressed HSP genes, 7 genes showed induced expressions, while hsp90aa1.2, hsp70.1, and hsp70.2 had more significant upregulated changes after hypoxic challenge. Our findings provide the essential basis for further functional studies of HSP genes in response to abiotic stresses in spotted seabass.

Smolting is an important development stage of salmonid, and an energy trade-off occurs between osmotic regulation and growth during smolting in rainbow trout (Oncorhynchus mykiss). Growth hormone releasing hormone, somatostatin, growth hormone and insulin-like growth factor (GHRH-SST-GH-IGF) axis exhibit pleiotropic effects in regulating growth and osmotic adaptation. Due to salmonid specific genome duplication, increased paralogs are identified in the ghrh-sst-gh-igf axis, however, their physiology in modulating osmoregulation has yet to be investigated. In this study, seven sst genes (sst1a, sst1b, sst2, sst3a, sst3b, sst5, sst6) were identified in trout. We further investigated the ghrh-sst-gh-igf axis of diploid and triploid trout in response to seawater challenge. Kidney sst (sst1b, sst2, sst5) and sstr (sstr1b1, sstr5a, sstr5b) expressions were changed (more than 2-fold increase (except for sstr5a with 1.99-fold increase) or less than 0.5-fold decrease) due to osmoregulation, suggesting a pleiotropic physiology of SSTs in modulating growth and smoltification. Triploid trout showed significantly down-regulated brain sstr1b1 and igfbp2a1 (p < 0.05), while diploid trout showed up-regulated brain igfbp1a1 (~2.61-fold, p = 0.057) and igfbp2a subtypes (~1.38-fold, p < 0.05), suggesting triploid trout exhibited a better acclimation to the seawater environment. The triploid trout showed up-regulated kidney igfbp5a subtypes (~6.62 and 7.25-fold, p = 0.099 and 0.078) and significantly down-regulated igfbp5b2 (~0.37-fold, p < 0.05), showing a conserved physiology of teleost IGFBP5a in regulating osmoregulation. The IGFBP6 subtypes are involved in energy and nutritional regulation. Distinctive igfbp6 subtypes patterns (p < 0.05) potentially indicated trout triggered energy redistribution in brain and kidney during osmoregulatory regulation. In conclusion, we showed that the GHRH-SST-GH-IGF axis exhibited pleiotropic effects in regulating growth and osmoregulatory regulation during trout smolting, which might provide new insights into seawater aquaculture of salmonid species.

Temperature strongly modulates muscle development and growth in ectothermic teleosts; however, the underlying mechanisms remain largely unknown. In this study, primary cultures of skeletal muscle cells of Lateolabrax maculatus were conducted and reared at different temperatures (21, 25, and 28 °C) in both the proliferation and differentiation stages. CCK-8, EdU, wound scratch and nuclear fusion index assays revealed that the proliferation, myogenic differentiation, and migration processes of skeletal muscle cells were significantly accelerated as the temperature raises. Based on the GO, GSEA, and WGCNA, higher temperature (28 °C) induced genes involved in HSF1 activation, DNA replication, and ECM organization processes at the proliferation stage, as well as HSF1 activation, calcium activity regulation, myogenic differentiation, and myoblast fusion, and sarcomere assembly processes at the differentiation stage. In contrast, lower temperature (21 °C) increased the expression levels of genes associated with DNA damage, DNA repair and apoptosis processes at the proliferation stage, and cytokine signaling and neutrophil degranulation processes at the differentiation stage. Additionally, we screened several hub genes regulating myogenesis processes. Our results could facilitate the understanding of the regulatory mechanism of temperature on fish skeletal muscle growth and further contribute to utilizing rational management strategies and promoting organism growth and development.

Long noncoding RNAs (lncRNAs) play an important role in many life activities, but the expression pattern and function of lncRNAs in Japanese flounder skeletal muscle are unclear. In this study, 751 lncRNAs were selected from skeletal muscle in different development stages of the Japanese flounder [stage A: larval 7 days post hatching (dph); stage B: juvenile about 90 dph; stage C (female) and stage D (male): adult about 24 months] using coding potential analysis methods. In total, 232, 211, 194, 28, 29, and 14 differentially expressed lncRNAs and 9549, 8673, 9181, 1821, 1080, and 557 differentially expressed mRNAs were identified in comparisons of A versus B, A versus C, A versus D, B versus C, B versus D, and C versus D, respectively. We identified the cis- and trans-regulatory target genes of differentially expressed lncRNAs, and lncRNA–gene interaction networks were constructed using the Cytoscape program. In total, there were 200, 200, 200, 93, 47, and 11 cis-regulation relationships, and 29, 19, 24, 38, 8, and 47 trans-regulation relationships in the comparisons between A versus B, A versus C, A versus D, B versus C, B versus D, and C versus D, respectively. These results indicate that lncRNA may participate in the development of Japanese flounder skeletal muscle through cis- or trans-acting mechanisms, thus providing a scientific basis for further study of the biological function of lncRNA in Japanese flounder skeletal muscle. Based on these relationships, functional annotation of the related lncRNAs was performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Differentially expressed genes associated with muscle development were enriched in multiple pairs of comparisons (e.g., differentially expressed genes LOC109640370, LOC109634180, LOC109643555, rusc1, and LOC109626999 were enriched in the actin-binding term, and differentially expressed genes LOC109640370, was, LOC109644970, LOC109643555, and itga9 were enriched in the regulation of the actin cytoskeleton pathway in the KEGG pathway analysis in the comparison of stages C and D). We predicted lncRNA–mRNA, miRNA–mRNA, and lncRNA–miRNA regulatory relationships and constructed interactive networks using Cytoscape software. Co-expression networks show that most lncRNAs interact with one or two predicted miRNAs involved in muscle growth and development. These results provide a basis for further study of the function of lncRNAs on skeletal muscle in different developmental stages of Japanese flounder.

Summary: The advent of base editors (BEs) holds great potential for correcting pathogenic-related point mutations to treat relevant diseases. However, Cas9 nickase (nCas9)-derived BEs lead to DNA double-strand breaks, which can trigger unwanted DNA damage response (DDR). Here, we show that the original version of catalytically dead Cas12a (dCas12a)-conjugated BEs induce a basal level of DNA breaks and minimally activate DDR proteins, including H2AX, ATM, ATR, and p53. By fusing dCas12a with engineered human apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A), we further develop the BEACON (base editing induced by human APOBEC3A and Cas12a without DNA break) system to achieve enhanced deamination efficiency and editing specificity. Efficient C-to-T editing is achieved by BEACON in mammalian cells at levels comparable to AncBE4max, with only low levels of DDR and minimal RNA off-target mutations. Importantly, BEACON induces in vivo base editing in mouse embryos, and targeted C-to-T conversions are detected in F0 mice.

Rainbow trout (Oncorhynchus mykiss) serves as one of the most important commercial fish with an annual production of around 800,000 tonnes. However, infectious diseases, such as furunculosis caused by Aeromonas salmonicida infection, results in great economic loss in trout culture. The brain and kidney are two important organs associated with “sickness behaviors” and immunomodulation in response to disease. Therefore, we worked with 60 trout and investigated transcriptional responses and enrichment pathways between healthy and infected trout. We observed that furunculosis resulted in the activation of toll-like receptors with neuroinflammation and neural dysfunction in the brain, which might cause the “sickness behaviors” of infected trout including anorexia and lethargy. We also showed the salmonid-specific whole genome duplication contributed to duplicated colony stimulating factor 1 (csf-1) paralogs, which play an important role in modulating brain immunomodulation. Enrichment analyses of kidneys showed up-regulated immunomodulation and down-regulated neural functions, suggesting an immune-neural interaction between the brain and kidney. Moreover, the kidney endocrine network was activated in response to A. salmonicida infection, further convincing the communications between endocrine and immune systems in regulating internal homeostasis. Our study provided a foundation for pathophysiological responses of the brain and kidney in response to furunculosis and potentially offered a reference for generating disease-resistant trout strains.

Abstract Background Salinity is an important abiotic stress that influences the physiological and metabolic activity, reproduction, growth and development of marine fish. It has been suggested that half-smooth tongue sole (Cynoglossus semilaevis), a euryhaline fish species, uses a large amount of energy to maintain osmotic pressure balance when exposed to fluctuations in salinity. To delineate the molecular response of C. semilaevis to different levels of salinity, we performed RNA-seq analysis of the liver to identify the genes and molecular and biological processes involved in responding to salinity changes. Results The present study yielded 330.4 million clean reads, of which 83.9% were successfully mapped to the reference genome of C. semilaevis. One hundred twenty-eight differentially expressed genes (DEGs), including 43 up-regulated genes and 85 down-regulated genes, were identified. These DEGs were highly represented in metabolic pathways, steroid biosynthesis, terpenoid backbone biosynthesis, butanoate metabolism, glycerolipid metabolism and the 2-oxocarboxylic acid metabolism pathway. In addition, genes involved in metabolism, osmoregulation and ion transport, signal transduction, immune response and stress response, and cytoskeleton remodeling were affected during acclimation to low salinity. Genes acat2, fdps, hmgcr, hmgcs1, mvk, pmvk, ebp, lss, dhcr7, and dhcr24 were up-regulated and abat, ddc, acy1 were down-regulated in metabolic pathways. Genes aqp10 and slc6a6 were down-regulated in osmoregulation and ion transport. Genes abat, fdps, hmgcs1, mvk, pmvk and dhcr7 were first reported to be associated with salinity adaptation in teleosts. Conclusions Our results revealed that metabolic pathways, especially lipid metabolism were important for salinity adaptation. The candidate genes identified from this study provide a basis for further studies to investigate the molecular mechanism of salinity adaptation and transcriptional plasticity in marine fish.

Transcriptome complexity plays crucial roles in regulating the biological functions of eukaryotes. Except for functional genes, alternative splicing and fusion transcripts produce a vast expansion of transcriptome diversity. In this study, we applied PacBio single-molecule long-read sequencing technology to unveil the whole transcriptome landscape of Lateolabrax maculatus. We obtained 28,809 high-quality non-redundant transcripts, including 18,280 novel isoforms covering 8,961 annotated gene loci within the current reference genome and 3,172 novel isoforms. A total of 10,249 AS events were detected, and intron retention was the predominant AS event. In addition, 1,359 alternative polyadenylation events, 3,112 lncRNAs, 29,609 SSRs, 365 fusion transcripts, and 1,194 transcription factors were identified in this study. Furthermore, we performed RNA-Seq analysis combined with Iso-Seq results to investigate salinity regulation mechanism at the transcripts level. A total of 518 transcripts were differentially expressed, which were further divided into 8 functional groups. Notably, transcripts from the same genes exhibited similar or opposite expression patterns. Our study provides a comprehensive view of the transcriptome complexity in L. maculatus, which significantly improves current gene models. Moreover, the diversity of the expression patterns of transcripts may enhance the understanding of salinity regulatory mechanism in L. maculatus and other euryhaline teleosts.

Multi-resolution feature fusion DCF (Discriminative Correlation Filter) methods have significantly advanced the object tracking performance. However, careless choice and fusion of sample features make the algorithm susceptible to interference, leading to tracking failure. Some trackers embed the re-detection module to remedy tracking failures, yet distinguishing ability and stability of the sample features are scarcely considered when training the detector, resulting in low effectiveness detection. Firstly, this paper proposes a criterion of feature tracking reliability and conduct a novel feature adaptive fusion framework. The feature tracking reliability criterion is proposed to evaluate the robustness and distinguishing ability of the sample features. Secondly, a re-detection module is proposed to further avoid tracking failures and increase the accuracy of target re-detection. The re-detection module consists of multiple SVM detectors trained by different sample features. When the tracking fails, the SVM detector trained by the most reliable sample feature will be activated to recover the target and adjust the target position. Finally, comparison experiments on OTB2015 and UAV123 databases demonstrate the accuracy and robustness of the proposed method.

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market. However, the interaction between agri-food e-commerce (AEC) and the traditional agri-food wholesale industry (AWI) has not received enough attention in the existing literature. Based on the provincial panel data from 2013 to 2020 in China, this paper examines the effect of AEC on AWI, comprising three dimensions: digitalization (DIGITAL), agri-food e-commerce infrastructure and supporting services (AECI), and agri-food e-commerce economy (AECE). First, AWI and AEC are measured using an entropy-based combination of indicators. The results indicate that for China as a whole, AWI has remained practically unchanged, whereas AEC exhibits a significant rising trend. Second, the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI, whereas AECI negatively affects AWI. Third, threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity, which manifests as a first increase and then a drop in the inhibition degree. These results suggest that with the introduction of e-commerce for agricultural product circulation, digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress. Furthermore, the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

Abstract Background Proper flowering time is important for the growth and development of plants, and both too early and too late flowering impose strong negative influences on plant adaptation and seed yield. Thus, it is vitally important to study the mechanism underlying flowering time control in plants. In a previous study by the authors, genome-wide association analysis was used to screen the candidate gene SISTER OF FCA (SSF) that regulates FLOWERING LOCUS C (FLC), a central gene encoding a flowering suppressor in Arabidopsis thaliana. Results SSF physically interacts with Protein arginine methyltransferase 5 (PRMT5, SKB1). Subcellular co—localization analysis showed that SSF and SKB1 interact in the nucleus. Genetically, SSF and SKB1 exist in the same regulatory pathway that controls FLC expression. Furthermore, RNA-sequencing analysis showed that both SSF and SKB1 regulate certain common pathways. Conclusions This study shows that PRMT5 interacts with SSF, thus controlling FLC expression and facilitating flowering time control.