Haemophilus parasuis, the causative agent of Glässer's disease, has been reported widely, but seldom is known about its epidemiology in Sichuan province, China. The objective was to reveal the prevalence and distribution of H.parasuis in the area. Widely sampling and isolation was performed initially and following serotyping multiplex PCR (serotyping-mPCR) combined with agar gel diffusion (GD) was subjected to these strains. From January 2014 to May 2016, 254 H.parasuis field strains were isolated from 576 pigs with clinical symptoms, for the frequence of 44.10%. Statistically significant differences of infection incidence were found in three age groups and seasons. Serovars 5(25.98%) and 4(23.62%) were the most prevalent and non-typeable isolates accounted for 7.87%. In geographical distribution, serovars 5 and 4 were prepotent in both major two parts of Sichuan province. The results confirmed the compound approach was dependable and revealed the diversity and distribution of serovars in Sichuan province, which was promising to know relevant vaccinal candidates and further prevention. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2805v1 | CC BY 4.0 Open Access | rec: 15
BackgroundHuman papillomavirus (HPV) is one of the most common sexually transmitted viruses. Data about HPV infection in Guizhou is limited.Methods56,768 cervical samples were collected and genotyped for 15 main high risk and 6 main low risk HPV types.Results16.95% (9623/56768) of samples were HPV positive; 90.70% (8728/9623) of HPV positive women were infected by high risk HPV. High risk and high risk mix infection (1458; 70.85%) was the most common mix HPV infection type. The highest HPV detection rate was found in age group 41–45 years old (detection rate = 17.89%) (χ2 = 204.77; P < 0.001); the highest within-group HPV infection rates were found in the ≤20 (25.62%) and ≥ 61 (24.67%) years old age groups, the lowest within-group HPV infection rate was found in the 31–35 years old age group (15.02%). The highest mix infection proportions were found in the ≥61 (36.06%) and ≤ 20 (33.63%) years old age groups (χ2 = 111.21; P < 0.001), the lowest mix infection proportion was found in the 41–45 (17.42%) years old age group. The highest high risk infection proportions were found in the 26–30 (92.98%), ≥61 (92.68%), and 36–40 (92.16%) years old age groups (χ2 = 31.72; P < 0.001), the lowest high risk infection proportion was found in the ≤20 (84.96%) years old age group. HPV infection rates varied with seasons in Guizhou.ConclusionsCharacteristics of HPV distribution in Guizhou were identified. There were significant differences in HPV distribution among age groups, prevention strategies should be adjusted according to the characteristics.
The no-load radial magnetic field and no-load back electromotive force (EMF) of external rotor permanent magnet brushless DC motor (PMBLDCM) are calculated by applying the correction coefficient of magnetic conductance here, taking into account the stator slotting and static eccentricity effects. An external rotor PMBLDCM with 51-slot/46-pole, used as in-wheel motor, is taken as an example, the analytical calculation results of the no-load back EMF are validated by the finite-element method and experiment. The influences of static eccentricity ratio on the no-load radial magnetic field and no-load back EMF are investigated based on the analytical model. The investigation shows that static eccentricity does not change the harmonic contents of no-load radial magnetic field, so it does not change the harmonic contents of three-phase no-load back EMFs. However, static eccentricity changes the space order of no-load radial magnetic field, resulting in the different total harmonic distortions of three-phase no-load back EMFs; in other words, the asymmetric distortions of three-phase no-load back EMFs are generated. The asymmetric distortions of three-phase no-load back EMFs are intensified with the increase in static eccentricity ratio.
Our aim was to identify the relationships between self-esteem and social adaptation, and the chain mediating effect of peer trust and perceived social support in this relationship. The Rosenberg Self-Esteem Scale, Peer Trust Scale, Perceived Social Support Scale, and Scale on Social
Adaptability for Secondary School Students were integrated into a paper-and-pencil survey. Participants were 400 adolescents in southwestern China. Results demonstrated that the relationship between self-esteem and social adaptation was partially mediated by peer trust and perceived social
support. The results were explained using the ecological systems theory. Self-esteem is inside the core individual; peer trust is in the microsystem and/or mesosystem; perceived social support is in the mesosystem, exosystem, and/or macrosystem. Adolescent social adaptation could be promoted
by directly enhancing self-esteem, thus indirectly improving peer trust and perceived social support.
In this paper, to the best of our knowledge, we first present a deep learning based method for reconstructing the images of two adjacent objects passing through scattering media. We construct an imaging system for imaging of two adjacent objects located at different depths behind the scattering medium. In general, as the light field of two adjacent objects passes through the scattering medium, a speckle pattern is obtained. We employ the designed adversarial network, which is called as YGAN, for reconstructing the two images simultaneously from the speckle. It is shown that based on the trained YGAN, we can reconstruct images of the two adjacent objects with high quality. In addition, the influence of object image types, and the location depths of the two adjacent objects on the imaging fidelity will be studied. Results demonstrate the strong generalization ability and effectiveness of the YGAN. Even in the case where another scattering medium is inserted between the two objects, the YGAN can reconstruct the object images with high fidelity. The technique presented in this paper can be used for applications in areas of medical image analysis, such as medical image classification, segmentation, and studies of multi-object scattering imaging, three-dimensional imaging etc.
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