Research on Practice Problems and Strategies for Professional Master's Degree Candidates for Agriculture

Taking the practice status of professional master’s degree candidates for agriculture in Anhui Agricultural University as an example,this paper analyzes the key factors affecting the practical training of graduate students in this major,and puts forward some strategies for improving the practice quality of professional master’s degree candidates.In terms of training professional master’s degree candidates,it is considered that agricultural colleges and universities should start with collaborative education,supervision and assessment mechanism,practice content and form,make full use of a large number of agricultural enterprise resources owned by colleges and universities and a good cooperation foundation in enterprises,so as to achieve the purpose of improving the practice quality of professional master’s degree candidates.

Current Situations of Internet Based Transformation and Upgrade of Hubei Comfort International Travel Service Co.,Ltd.

In the era of " Internet + ",the " Internet + tourism" comes into being,bringing unlimited development space and more possibilities to the traditional travel agency industry. Under the dual influence of development and impact,travel agencies start to take the road of transformation. Taking Hubei Comfort International Travel Service Co.,Ltd. as an example,this paper analyzed and evaluated the current situations of Internet based transformation and upgrade,and came up with some pertinent recommendations.

Evolution of cavity size and energy conversion due to droplet impact on a water surface

The deformation characteristics of the cavity due to droplet impact on a water surface are experimentally investigated.Dimensional analysis shows that the characteristic values of time,depth,and horizontal diameter can be taken as 10^(-3)times the ratio of surface tension to the product of viscosity coefficient and gravitational acceleration,the maximum depth,and the maximum horizontal diameter,respectively.The evolutions of the dimensionless cavity sizes for different values of Weber number(We)coincide for 220<We<686.A partial-sphere model of cavity is established based on experimental observations.Energy models are then derived,and the energy conversions are calculated to identify the relationship between these conversions and cavity deformation.It is found that the kinetic energy model established under the hypothesis proposed by Leng is no longer applicable when the dimensionless time t^(*)<3.5,owing to deviations from the geometric model.

不同年龄组低级别滤泡淋巴瘤的临床特征及预后分析

目的:分析低级别滤泡淋巴瘤(follicular lymphoma,FL)在各年龄段人群中的临床特征及预后。方法:收集2011年1月至2019年12月郑州大学第一附属医院初治的82例低级别FL患者的病例资料,男女比为1∶1.05,中位年龄52(19~84)岁。分类变量行Chi-square检验,采用Kaplan-Meier法、Logistic单因素分析及Cox回归模型多因素分析进行生存资料分析。结果:82例患者分为年龄<40岁、40~59岁和≥60岁3个组。随着年龄段的上升,患者多见红细胞沉降率(erythrocyte sedimentation rate,ESR)增快、外周血血小板与淋巴细胞比值(platelet to lymphocyte ratio,PLR)升高、Bcl-2表达呈阳性的患者比例升高、ECOG评分和FLIPI-2评分升高,且初治效果达到完全缓解(complete response,CR)的比例降低(P<0.05)。随访的73例患者2、5年总生存率(overall survival,OS)分别为97.2%和74.1%,无进展生存率(progression-free survival,PFS)分别为91.5%和88.8%。73例患者在年龄<40岁、40~59岁和≥60岁3个组中,5年OS分别为100%、73.8%和46.5%(P=0.014)。比较各组PFS差异无统计学意义(P=0.190)。根据化疗方案分析,利妥昔单抗联合化疗与单用化疗组,5年OS分别为85.7%和69.3%(P=0.004),5年PFS分别为96.8%和56.3%(P<0.001)。单用化疗组中3个年龄组3年OS分别为100%、75.0%和71.4%(P=0.048),利妥昔单抗联合化疗组中各年龄组的3年OS无显著性差异(P=0.050)。根据Ann Arbor分期分析,晚期组(Ⅲ+Ⅳ期)中3个年龄组的5年OS分别为100%、88.9%和47.7%(P=0.046),早期组(Ⅰ+Ⅱ期)各年龄组的5年OS无显著性差异(P=0.414)。结论:低级别FL患者预后随年龄段的上升变差,男性为预后不良因素,利妥昔单抗联合化疗可以改善预后,延长患者生存期。

Model of Tourism for Poverty Alleviation in Danjiangkou City

Tourism has become an important part of China's tertiary industry. Tourism for poverty alleviation has also become an important means of poverty alleviation. In China,most of the poverty-stricken areas still keep relatively intact natural and human landscapes which have high tourism development value. Through SWOT analysis,the model of tourism for poverty alleviation in Danjiangkou City was studied,to provide both theoretical and practical support for the local tourism for poverty alleviation.

Research on the Training Mode of "Three-quality Talents" in Application-oriented Universities Based on OBE

Based on the concept of outcome-based education (OBE) and the existing OBE training mode, this paper puts forward the training mode of "three-quality talents" as a supplement. This mode effectively helps Chinese application-oriented colleges and universities to improve the training quality of application-oriented talents, is an effective way to train application-oriented undergraduate professionals, and has a certain promotion and application value.

Multi-Scale Fusion Model Based on Gated Recurrent Unit for Enhancing Prediction Accuracy of State-of-Charge in Battery Energy Storage Systems

Accurate prediction of the state-of-charge(SOC)of battery energy storage system(BESS)is critical for its safety and lifespan in electric vehicles.To overcome the imbalance of existing methods between multi-scale feature fusion and global feature extraction,this paper introduces a novel multi-scale fusion(MSF)model based on gated recurrent unit(GRU),which is specifically designed for complex multi-step SOC prediction in practical BESSs.Pearson correlation analysis is first employed to identify SOC-related parameters.These parameters are then input into a multi-layer GRU for point-wise feature extraction.Concurrently,the parameters undergo patching before entering a dual-stage multi-layer GRU,thus enabling the model to capture nuanced information across varying time intervals.Ultimately,by means of adaptive weight fusion and a fully connected network,multi-step SOC predictions are rendered.Following extensive validation over multiple days,it is illustrated that the proposed model achieves an absolute error of less than 1.5%in real-time SOC prediction.

Stochastic Approximation for Expensive One-Bit Feedback Systems

One-bit feedback systems generate binary data as their output and the system performance is usually measured by the success rate with a fixed parameter combination. Traditional methods need many executions for parameter optimization. Hence, it is impractical to utilize these methods in Expensive One-Bit Feedback Systems （EOBFSs）, where a single system execution is costly in terms of time or money. In this paper, we propose a novel algorithm, named Iterative Regression and Optimization （IRO）, for parameter optimization and its corresponding scheme based on the Maximum Likelihood Estimation （MLE） method and Particle Swarm Optimization （PSO） method, named MLEPSO-IRO, for parameter optimization in EOBFSs. The IRO algorithm is an iterative algorithm, with each iteration comprising two parts： regression and optimization. Considering the structure of IRO and the Bernoulli distribution property of the output of EOBFSs, MLE and a modified PSO are selected to implement the regression and optimization sections, respectively, in MLEPSO-IRO. We also provide a theoretical analysis for the convergence of MLEPSO-IRO and provide numerical experiments on hypothesized EOBFSs and one real EOBFS in comparison to traditional methods. The results indicate that MLEPSO-IRO can provide a much better result with only a small amount of system executions.

Facile Fabrication of Polymeric Ionic Liquid Grafted Porous Polymer Monolith for Mixed-Mode High Performance Liquid Chromatography

A novel polymeric ionic liquid grafted porous polymer monolith has been facilely fabricated for mixed-mode chromatography.The column is prepared from poly(glycidyl methacrylate-co-ethylene dimethacrylate)monolith through hydrolyzation of the epoxy moieties into hydroxyl groups,followed by“grafting from”polymerization of ionic liquid of 1-vinyl-3-butylimidazolium chloride.Successful modification is characterized by scanning electron microscope,infrared spectroscopy,elemental analysis and mercury intrusion porosimetry.The HPLC performance of developed column is evaluated by separating acidic vitamin B analytes,neutral steroids and basic aromatic amines in mixed-mode chromatography on a single column,respectively.The ionic liquid affords the monolith with both enhanced separation ability and improved column efficiency.

Cytomegalovirus antigen-specific T cell immune responses in patients with autoimmune diseases under different cytomegalovirus infection status

To the Editor:Patients with autoimmune diseases have increased risk of active cytomegalovirus(CMV)infection due to immune dysfunction or the application of glucocorticoid and immunosuppressants.[1]Cui et al[2]found that compared with human immunodeficiency virus(HIV)/acquired immune deficiency syndrome(27%),posttransplant patients(14.8%),and hematological malignancies(5.1%),patients with autoimmune disease had the highest incidence of CMV antigenemia(35.1%).Monitoring CMV antigen-specific T cell immunity is helpful for understanding the protective immunity against CMV infection and identifing the risk of CMV-related complications.Currently,the CMV antigen-specific T cell immune responses in patients with autoimmune diseases remains unknown.

The effects of probiotics administration on the milk production,milk components and fecal bacteria microbiota of dairy cows

Probiotics administration can improve host health.This study aims to determine the effects of probiotics(Lactobacillus casei Zhang and Lactobacillus plantarum P-8) administration on milk production,milk functional components,milk composition,and fecal microbiota of dairy cows.Variations in the fecal bacteria microbiota between treatments were assessed based on 16 S rRNA profiles determined by Pac Bio single molecule real-time sequencing technology.The probiotics supplementation significantly increased the milk production and the contents of milk immunoglobulin G(IgG),lactoferrin(LTF),lysozyme(LYS)and lactoperoxidase(LP),while the somatic cell counts(SCC) significantly decreased(P < 0.01).However,no significant difference was found in the milk fat,protein and lactose contents(P > 0.05).Although the probiotics supplementation did not change the fecal bacteria richness and diversity,significantly more rumen fermentative bacteria(Bacteroides,Roseburia,Ruminococcus,Clostridium,Coprococcus and Dorea) and beneficial bacteria(Faecalibacterium prausnitzii) were found in the probiotics treatment group.Meanwhile,some opportunistic pathogens e.g.Bacillus cereus,Cronobacter sakazakii and Alkaliphilus oremlandii,were suppressed.Additionally,we found some correlations between the milk production,milk components and fecal bacteria.To sum up,our study demonstrated the beneficial effects of probiotics application in improving the quality and quantity of cow milk production.

Effect of dietary interventions on the intestinal microbiota of Mongolian hosts

The gut microbiota of Mongolian hosts has distinctive characteristics due to their meat- and dairyoriented daily diets and unique genotype.The aim of the present study was to investigate the effect of switching from the typical high protein and fat Mongolian diets to carbohydrate-rich meals composed principally of wheat,rice and naked oats on the host gut microbiota within 3 weeks.Our study took the advantage of the long sequence reads produced by the Pac Bio single molecule real-time sequencing technology to enable the profiling of subjects' gut microbiota communities along the diet intervention to the species precision.We found that the bacterial richness and diversity decreased apparently along the diet intervention.During the diet intervention,the gut microbiota composition displayed no significant difference at phylum level(with major phyla of Firmicutes,Bacteroidetes,Tenericutes and Proteobacteria).The relative abundances of some genera such as Bacteroidetes,Faecalibacterium,Roseburia,Alistipes,Streptococcus,and Oscillospira were significantly altered after the diet switching started.Notably,significant changes were also observed in the proportions of the species Bacteroides dorei,Bacteroides fragilis,Bacteroides thetaiotaomicron,Ruminococcus albus,Ruminococcus faecis,Roseburia faecis and Eubacterium ventriosum.These results have demonstrated that diet and host gut microbiota is closely linked.

Mycobacterium tuberculosis latency-associated antigen Rv1733c SLP improves the accuracy of differential diagnosis of active tuberculosis and latent tuberculosis infection

Background: Differential diagnosis of active tuberculosis (ATB) and latent tuberculosis infection (LTBI) has been a challenge for clinicians in high TB burden countries. The purpose of this study was to improve the accuracy of differential diagnosis of ATB and LTBI by using fluorescent immunospot (FluoroSpot) assay to detect specific Th1 cell immune responses. The novelmycobacterium tuberculosis (MTB) latency-associated antigens Rv1733c and synthetic long peptides derived from Rv1733c (Rv1733c SLP) were used based on virulence factors early secreting antigen target-6 (ESAT-6) and culture filtrate protein-10 (CFP-10).Methods: Fifty-seven ATB cases, including 20 pathogen-confirmed ATB and 37 clinically diagnosed ATB, and 36 LTBI cases, were enrolled between January and December 2017. FluoroSpot assay was used to detect the interferon γ (IFN-γ) and interleukin 2 (IL-2) secreted by the specific T cells after being stimulated with MTB virulence factors ESAT-6 and CFP-10, MTB latency-associated antigens Rv1733c and Rv1733c SLP. The receiver operating characteristic (ROC) curve was used to define the best cutoff value of latency-associated antigens in the use of differentiating ATB and LTBI. The sensitivity, specificity, predictive value, and likelihood ratio of ESAT-6 and CFP-10-FluoroSpot combined with latency-associated antigen in the differential diagnosis of ATB and LTBI were also calculated.Results: Following the stimulation with Rv1733c and Rv1733c SLP, the frequency of single IL-2-secreting T cells stimulated by Rv1733c SLP had the largest area under the ROC curve, which was 0.766. With a cutoff value of 1 (spot-forming cells [SFCs]/2.5 × 105 peripheral blood mononuclear cells) for frequency, the sensitivity and specificity of distinguishing ATB from LTBI were 72.2% and 73.7%, respectively. ESAT-6 and CFP-10-FluoroSpot detected the frequency and proportion of single IFN-γ-secreting T cells;the sensitivity and specificity of distinguishing ATB from LTBI were 82.5% and 66.7%, respectively. Combined with the frequency of single IL-2-secreting T cells stimulated by Rv1733c SLP on the basis of ESAT-6 and CFP-10-FluoroSpot, the sensitivity and specificity increased to 84.2% and 83.3%, respectively.Conclusion: Rv1733c SLP, combined with ESAT-6 and CFP-10, might be used as a candidate antigen for T cell-based tuberculosis diagnostic tests to differentiate ATB from LTBI.

New progress in spectroscopic probes for reactive oxygen species

Reactive oxygen species(ROS)play an important role in many critical physiological processes.However,overproduction and accumulation of ROS in vivo can damage some biomolecules and lead to a variety of diseases.Therefore,it is necessary to develop efficient methods for the detection of ROS.Spectroscopic probes have been extensively employed in this respect because of their high sensitivity and superior spatiotemporal sampling capability.In this review,representative spectroscopic probes for the common ROS developed in the recent 5 years are summarized,and discussed according to design strategies and recognition groups.

Optimization of the Occlusion Strategy in Visual Tracking

Interference and anti-interference are two opposite and important issues in visual tracking. Occlusion interference can disguise the features of a target and can also be used as an effective benchmark to determine whether a tracking algorithm is reliable. In this paper, we proposed an inner Particle Swarm Optimization （PSO） algorithm to locate the optimal occlusion strategy under different tracking conditions and to identify the most effective occlusion positions and direction of movement to allow a target to evade tracking. This algorithm improved the standard PSO process in three ways. First, it introduced a death process, which greatly reduced the time cost of optimization. Second, it used statistical data to determine the fitness value of the particles so that the fitness more accurately described the tracking. Third, the algorithm could avoid being trapped in local optima, as the fitness changes with time. Experimental results showed that this algorithm was able to identify a global optimal occlusion strategy that can disturb the tracking machine with 86.8% probability over more than 10 000 tracking processes. In addition, it reduced the time cost by approximately 80%, compared with conventional PSO algorithms.

LIDAR:learning from imperfect demonstrations with advantage rectification

In actor-critic reinforcement learning(RL)algorithms,function estimation errors are known to cause ineffective random exploration at the beginning of training,and lead to overestimated value estimates and suboptimal policies.In this paper,we address the problem by executing advantage rectification with imperfect demonstrations,thus reducing the function estimation errors.Pretraining with expert demonstrations has been widely adopted to accelerate the learning process of deep reinforcement learning when simulations are expensive to obtain.However,existing methods,such as behavior cloning,often assume the demonstrations contain other information or labels with regard to performances,such as optimal assumption,which is usually incorrect and useless in the real world.In this paper,we explicitly handle imperfect demonstrations within the actor-critic RL frameworks,and propose a new method called learning from imperfect demonstrations with advantage rectification(LIDAR).LIDAR utilizes a rectified loss function to merely learn from selective demonstrations,which is derived from a minimal assumption that the demonstrating policies have better performances than our current policy.LIDAR learns from contradictions caused by estimation errors,and in turn reduces estimation errors.We apply LIDAR to three popular actor-critic algorithms,DDPG,TD3 and SAC,and experiments show that our method can observably reduce the function estimation errors,effectively leverage demonstrations far from the optimal,and outperform state-of-the-art baselines consistently in all the scenarios.