TimeSQL: Improving Multivariate Time Series Forecasting with Multi-Scale Patching and Smooth Quadratic Loss

Time series is a special type of sequence data, a sequence of real-valued random variables collected at even intervals of time. The real-world multivariate time series comes with noises and contains complicated local and global temporal dynamics, making it difficult to forecast the future time series given the historical observations. This work proposes a simple and effective framework, coined as TimeSQL, which leverages multi-scale patching and smooth quadratic loss (SQL) to tackle the above challenges. The multi-scale patching transforms the time series into two-dimensional patches with different length scales, facilitating the perception of both locality and long-term correlations in time series. SQL is derived from the rational quadratic kernel and can dynamically adjust the gradients to avoid overfitting to the noises and outliers. Theoretical analysis demonstrates that, under mild conditions, the effect of the noises on the model with SQL is always smaller than that with MSE. Based on the two modules, TimeSQL achieves new state-of-the-art performance on the eight real-world benchmark datasets. Further ablation studies indicate that the key modules in TimeSQL could also enhance the results of other models for multivariate time series forecasting, standing as plug-and-play techniques

Mesenteric CD103+DCs Initiate Switched Coxsackievirus B3 VP1-Specific IgA Response to Intranasal Chitosan-DNA Vaccine Through Secreting BAFF/IL-6 and Promoting Th17/Tfh Differentiation

Intranasal chitosan-formulated DNA vaccination promotes IgA secretion in the intestine. However, the mechanism whereby chitosan-DNA skews IgA class switch recombination (CSR) of B cells in the Gut-associated lymph tissue (GALT) is not fully resolved. In this study, we investigated the effects of nasally administered chitosan-DNA (pcDNA3.1-VP1 plasmid encoding VP1 capsid protein of Coxsackievirus B3) on IgA production, DC activation and Tfh/Th17 response in the intestine. Compared to DNA immunization, intranasal chitosan-DNA vaccination induced antigen-specific IgA production in feces, a pronounced switching of antigen-specific IgA+ plasmablast B cells in the mesenteric lymph nodes (MLNs) and an enhanced expression of post-recombination Iα-CH transcripts/IgA germline transcript (αGT) as well as activation-induced cytidine deaminase (AID) in MLN B cells. MLN Tfh frequency was markedly enhanced by chitosan-DNA, and was associated with VP1-specific IgA titer. 24 h after immunization, intranasal chitosan-DNA induced a recruitment of CD103+DCs into the MLN that paralleled a selective loss of CD103+DCs in the lamina propria (LP). In vivo activated MLN-derived CD103+DCs produced high levels of IL-6 and BAFF in response to chitosan-DNA, which up-regulated transmembrane activator and CAML interactor (TACI) expression on MLN B cells. Upon co-culture with IgM+B in the presence of chitosan-DNA, MLN CD103+DCs induced IgA production in a T-dependent manner; and this IgA-promoting effect of CD103+DC was blocked by targeting TACI and, to a lower extent, by blocking IL-6. MLN CD103+DCs displayed an enhanced capacity to induce an enhanced CD4+Th17 response in vivo and in vitro, and IL-17A deficient mice had a pronounced reduction of specific intestinal IgA following immunization. Taken together, mesenteric CD103+DCs are indispensable for the adjuvant activity of chitosan in enhancing DNA vaccine-specific IgA switching in gut through activating BAFF-TACI and IL-6-IL-6R signaling, and through inducing Th17/Tfh differentiation in the MLN

Effects of Lactobacillus plantarum on the Fermentation Profile and Microbiological Composition of Wheat Fermented Silage Under the Freezing and Thawing Low Temperatures

The corruption and/or poor quality of silages caused by low temperature and freeze-thaw conditions makes it imperative to identify effective starters and low temperature silage fermentation technology that can assist the animal feed industry and improve livestock productivity. The effect of L. plantarum QZ227 on the wheat silage quality was evaluated under conditions at constant low temperatures followed by repeated freezing and thawing at low temperatures. QZ227 became the predominant strain in 10 days and underwent a more intensive lactic acid bacteria fermentation than CK. QZ227 accumulated more lactic acid, but lower pH and ammonia nitrogen in the fermentation. During the repeated freezing and thawing process, the accumulated lactic acid in the silage fermented by QZ227 remained relatively stable. Relative to CK, QZ227 reduced the abundance of fungal pathogens in silage at a constant 5°C, including Aspergillus, Sporidiobolaceae, Hypocreaceae, Pleosporales, Cutaneotrichosporon, Alternaria, and Cystobasidiomycetes. Under varying low temperature conditions from days 40 to days 60, QZ227 reduced the pathogenic abundance of fungi such as Pichia, Aspergillus, Agaricales, and Plectosphaerella. QZ227 also reduced the pathogenic abundance of Mucoromycota after the silage had been exposed to oxygen. In conclusion, QZ227 can be used as a silage additive in the fermentation process at both constant and variable low temperatures to ensure fast and vigorous fermentation because it promotes the rapid accumulation of lactic acid, and reduces pH values and aerobic corruption compared to the CK

Large field-of-view pine wilt disease tree detection based on improved YOLO v4 model with UAV images

IntroductionPine wilt disease spreads rapidly, leading to the death of a large number of pine trees. Exploring the corresponding prevention and control measures for different stages of pine wilt disease is of great significance for its prevention and control.MethodsTo address the issue of rapid detection of pine wilt in a large field of view, we used a drone to collect multiple sets of diseased tree samples at different times of the year, which made the model trained by deep learning more generalizable. This research improved the YOLO v4(You Only Look Once version 4) network for detecting pine wilt disease, and the channel attention mechanism module was used to improve the learning ability of the neural network.ResultsThe ablation experiment found that adding the attention mechanism SENet module combined with the self-designed feature enhancement module based on the feature pyramid had the best improvement effect, and the mAP of the improved model was 79.91%.DiscussionComparing the improved YOLO v4 model with SSD, Faster RCNN, YOLO v3, and YOLO v5, it was found that the mAP of the improved YOLO v4 model was significantly higher than the other four models, which provided an efficient solution for intelligent diagnosis of pine wood nematode disease. The improved YOLO v4 model enables precise location and identification of pine wilt trees under changing light conditions. Deployment of the model on a UAV enables large-scale detection of pine wilt disease and helps to solve the challenges of rapid detection and prevention of pine wilt disease

Isolation, characterization, and genomic analysis of a lytic bacteriophage, PQ43W, with the potential of controlling bacterial wilt

Bacterial wilt (BW) is a devastating plant disease caused by the soil-borne bacterium Ralstonia solanacearum species complex (Rssc). Numerous efforts have been exerted to control BW, but effective, economical, and environmentally friendly approaches are still not available. Bacteriophages are a promising resource for the control of bacterial diseases, including BW. So, in this study, a crop BW pathogen of lytic bacteriophage was isolated and named PQ43W. Biological characterization revealed PQ43W had a short latent period of 15 min, 74 PFU/cell of brust sizes, and good stability at a wide range temperatures and pH but a weak resistance against UV radiation. Sequencing revealed phage PQ43W contained a circular double-stranded DNA genome of 47,156 bp with 65 predicted open reading frames (ORFs) and genome annotation showed good environmental security for the PQ43W that no tRNA, antibiotic resistance, or virulence genes contained. Taxonomic classification showed PQ43W belongs to a novel genus of subfamily Kantovirinae under Caudoviricetes. Subsequently, a dose of PQ43W for phage therapy in controlling crop BW was determined: 108 PFU*20 mL per plant with non-invasive irrigation root application twice by pot experiment. Finally, a field experiment of PQ43W showed a significantly better control effect in crop BW than the conventional bactericide Zhongshengmycin. Therefore, bacteriophage PQ43W is an effective bio-control resource for controlling BW diseases, especially for crop cultivation

Involvement of NMDA-AKT-mTOR Signaling in Rapid Antidepressant-Like Activity of Chaihu-jia-Longgu-Muli-tang on Olfactory Bulbectomized Mice

Background: Fast-onset antidepressants are urgently needed. Chaihu-jia-Longgu-Muli-tang (CLM), a classic Chinese herbal medicine, has been used for antidepressant treatment with long history. Olfactory bulbectomization (OB) model is validated for identification of rapid antidepressant efficacy. Here we used OB model for investigating the rapid onset activity of CLM in mice, and also tested the involvement of prefrontal Akt-mTOR and associated AMPA/NMDA receptors as well as hippocampal BDNF in the rapid antidepressant-like effect of CLM.Methods: The OB model was first characterized with depression-like behaviors and the time course changes of the behaviors. The fast onset of antidepressant effect of CLM was evaluated using sucrose preference test, tail suspension test and forced swim test in OB mice after a single administration. The expression of synaptic proteins of AMPA and NMDA subunits as well as Akt/mTOR signaling in the prefrontal cortex, and hippocampal BDNF was evaluated with the immunoblotting method.Results: A single dose of CLM significantly improved the deficiency in the sucrose preference and decreased the immobility time in the tail suspension test in OB mice. In the prefrontal cortex (PFC) in OB mice, there was lower expression level of the AMPA receptor subunit GluR1, rescued by a single dose of CLM. Additionally, the expression of NMDA subunit NR1 was up-regulated in OB mice, whereas mTOR and its upstream Akt signalings were both down-regulated. These deficiencies were reversed by a single dose of CLM. The CLM treatment also attenuated the expressions of NMDA receptor subunits NR2A and NR2B, which did not change in OB mice. In the hippocampus, expressions of GluR1 and brain derived neurotrophic factor (BDNF) were both up-regulated in OB mice, although CLM increased GluR1, but not BDNF.Conclusion: CLM elicited rapid antidepressant-like effects in the OB model mice, and CLM reversal of the abnormality in PFC expression of AMPA and NMDA receptors and associated Akt-mTOR signaling may underlie the effects

Agricultural Ecological Efficiency under the Carbon Emissions Trading System in China: A Spatial Difference-in-Difference Approach

The agriculture sector plays a significant role in the development of the national economy and providing raw materials to the industrial sector. Trying to get more agricultural productivity, most farmers ignored the adverse effects of agricultural chemicals or pesticides that have a negative impact on the environment. So, the importance of agricultural ecological efficiency needs to be understood. This study attempts to explore whether agriculture, as an important source of carbon dioxide production, can have an effective impact on the agricultural ecological efficiency of carbon trading pilot policies in the context of the global implementation of carbon trading. This study evaluated the agricultural ecological efficiency (AEE) and its spatial distribution characteristics of 31 provinces in China, the data period was from 2000 to 2018. By applying the spatial difference-in-difference (SDID) approach, the study investigates the effects of low-carbon policies on agricultural ecological efficiency in pilot areas. The results demonstrate that low-carbon trading pilot policies have a significant impact on agricultural ecological efficiency. At the same time, the effects of regional economic development, population growth, urbanization, and urban innovation on efficiency are also significant. The improvement of agricultural ecological efficiency requires not only the full implementation of low-carbon trading pilot policies but also the development of regional economy and high-quality agriculture. The findings provide further policy recommendations for high-quality agricultural development