Porcine deltacoronavirus (PDCoV) can cause diarrhea and dehydration in newborn piglets. Here, we developed a double antibody sandwich quantitative enzyme-linked immunosorbent assay (DAS-ELISA) for detection of PDCoV by using a specific monoclonal antibody against the PDCoV N protein and an anti-PDCoV rabbit polyclonal antibody. Using DAS-ELISA, the detection limit of recombinant PDCoV N protein and virus titer were approximately 0.5 ng/mL and 10^3.0 TCID₅₀/mL, respectively. A total of 59 intestinal and 205 fecal samples were screened for the presence of PDCoV by using DAS-ELISA and reverse transcriptase real-time PCR (RT-qPCR). The coincidence rate of the DAS-ELISA and RT-qPCR was 89.8%. DAS-ELISA had a sensitivity of 80.8% and specificity of 95.6%. More importantly, the DAS-ELISA could detect the antigen of PDCoV inactivated virus, and the viral antigen concentrations remained unchanged in the inactivated virus. These results suggest that DAS-ELISA could be used for antigen detection of clinical samples and inactivated vaccines. It is a novel method for detecting PDCoV infections and evaluating the PDCoV vaccine.

Calf diarrhea is one of the common diseases involved in the process of calf feeding. In this study, a sample of calf diarrhea that tested positive for bovine coronavirus and bovine astrovirus was subjected to high-throughput sequencing. The reassembly revealed the complete genomes of bovine norovirus, bovine astrovirus, bovine kobuvirus, and the S gene of bovine coronavirus. Phylogenetic analysis showed that the ORF2 region of bovine astrovirus had the lowest similarity with other strains and gathered in the Mamastrovirus unclassified genogroup, suggesting a new serotype/genotype could appear. Compared with the most closely related strain, there are six amino acid mutation sites in the S gene of bovine coronavirus, most of which are located in the S1 subunit region. The bovine norovirus identified in our study was BNoV-GIII 2, based on the VP1 sequences. The bovine kobuvirus is distributed in the Aichi virus B genus; the P1 gene shows as highly variable, while the 3D gene is highly conserved. These findings enriched our knowledge of the viruses in the role of calf diarrhea, and help to develop an effective strategy for disease prevention and control.

The spherical distribution pairs of the plunger and the cylinder friction, has an important influence on the performance of spherical port plate axial piston pump. Based on the analysis of fluid viscosity change with pressure and temperature, considering friction differential pressure flow and shear flow, establishes the mathematics model of the friction pair of leakage. The simulation analysis using MATLAB software, the leakage flow rate is not proportional to pressure, but with the increase of pressure leakage flow was increased, and with the increase of pressure viscosity coefficient and temperature coefficient of viscosity, the leakage flow rate correction coefficient increases obviously, so in the choice of the hydraulic oil cylinder hole, should choose a relatively moving average leakage rate had no effect the piston ring slot.

COVID-19 is seriously threatening human health all over the world. A comprehensive understanding of the genetic mechanisms driving the rapid evolution of its pathogen (SARS-CoV-2) is the key to controlling this pandemic. In this study, by comparing the entire genome sequences of SARS-CoV-2 isolates from Asia, Europe and America, and analyzing their phylogenetic histories, we found a lineage derived from a recombination event that likely occurred before March 2020. More importantly, the recombinant offspring has become the dominant strain responsible for more than one-third of the global cases in the pandemic. These results indicated that the recombination might have played a key role in the pandemic of the virus.

Porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), and porcine rotavirus group A (PoRVA) are recognized as major enteric viral pathogens responsible for porcine viral diarrhea. These viruses exhibit similar clinical manifestations, including vomiting, diarrhea, and dehydration, which complicate differential diagnosis. Therefore, there is an urgent need for a highly sensitive and specific diagnostic method to differentiate these pathogens. In this study, we developed a TaqMan‐based one‐step quadruplex reverse transcription real‐time PCR (RT‐qPCR) assay for the simultaneous and differential detection of these four porcine diarrhea viruses. The standard curves demonstrated correlation coefficients ( R ² ) exceeded 0.990 across a dynamic range of 10 ^7.5 – 10 ^2.5 TCID ₅₀ /mL, and amplification efficiency ranged from 90% to 110%. The limit of detection (LOD) were 10 ^1.5 TCID ₅₀ /mL. Specificity analysis showed no cross‐reactivity with other related pathogens. The assay exhibited good repeatability, with coefficients of variation (CVs) ranging from 0.15% to 1.41% for intra‐assay and 0.09% to 2.09% for inter‐assay, respectively. Finally, this method was evaluated for its practicality in the field using 348 clinical fecal samples. The positive rates of PEDV, TGEV, PDCoV, and PoRVA were 43.68%, 0.57%, 26.44%, and 33.91%, respectively. Furthermore, the coinfection rates of PEDV/PDCoV, PEDV/PoRVA, PDCoV/PoRVA, and PEDV/PDCoV/PoRVA were14.37%, 13.51%, 2.01%, and 5.75%, respectively. Compared to singleplex RT‐qPCR assays, the quadruplex method demonstrated agreement rates ranging from 99.41% to 100% in detecting these four viral pathogens. In conclusion, the developed quadruplex RT‐qPCR assay offers a reliable, sensitive, and accurate tool for the identification of four causative agents of porcine viral diarrhea, making it suitable for clinical diagnosis, disease surveillance, and epidemiological studies.

Due to the multi-functional laying trolley has the problems such as complex and diverse fault reasons, low efficiency of fault diagnosis in tunnel construction, it is proposed to use AMESim software for fault simulation and intelligent algorithm for rapid fault diagnosis. Firstly, a hydraulic system simulation model was established based on Amesim, then the feature index of each fault was extracted from the system responses by injecting various typical faults into the model. Secondly, dynamic principal component analysis was applied to reduce the dimension of feature vectors, also to relieve correlation between features. The samples of the extracted fault feature parameters were trained in the improved SVM to obtain the classification model, finally the rapid fault diagnosis can be realized. The results show that the fault simulation technology provides a basis for state evaluation and fault prediction of hydraulic system, the intelligent analysis method can effectively improve the fault diagnosis efficiency, which gives guidance for rapid detection of hydraulic system in construction site. It provides technical support for the maintenance of trolley, and has good engineering application value.