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Tick-borne Apicomplexan parasites pose a significant threat to both public health and animal husbandry. Identifying potential pathogenic parasites and gathering their epidemiological data are essential for prospectively preventing and controlling infections. In the present study, genomic DNA of ticks collected from two goat flocks (Goatflock1 and Goatflock2) and one dog group (Doggroup) were extracted and the 18S rRNA gene of Babesia/Theileria/Colpodella spp. was amplified by PCR and sequenced. Phylogenetic analysis was conducted based on the obtained sequences. The differences in pathogen positive rates between ticks of different groups were statistically analyzed using the Chi-square or continuity-adjusted Chi-square test. As a result, two pathogenic Theileria (T.) luwenshuni genotypes, one novel pathogenic Colpodella sp. HLJ genotype, and two potential novel Colpodella spp. (referred to as Colpodella sp. struthionis and Colpodella sp. yiyuansis in this study) were identified in the Haemaphysalis (H.) longicornis ticks. Ticks of Goatflock2 had a significantly higher positive rate of Colpodella spp. than those from Goatflock1 (χ2=92.10; P = 8.2 × 10−22) and Doggroup (χ2=42.34; P = 7.7 × 10−11), and a significantly higher positive rate of T. luwenshuni than Doggroup (χ2=5.38; P = 0.02). However, the positive rates of T. luwenshuni between Goatflock1 and Goatflock2 were not significantly different (χ2=2.02; P = 0.16), and so as the positive rates of both pathogens between Goatflock1 and Doggroup groups (P > 0.05). For either Colpodella spp. or T. luwenshuni, no significant difference was found in prevalence between male and female ticks. These findings underscore the potential importance of Colpodella spp. in domestic animal-attached ticks, as our study revealed two novel Colpodella spp. and identified Colpodella spp. in H. longicornis for the first time. The study also sheds light on goats' potential roles in the transmission of Colpodella spp. to ticks and provides crucial epidemiological data of pathogenic Theileria and Colpodella. These data may help physicians, veterinarians, and public health officers prepare suitable detection and treatment methods and develop prevention and control strategies.

ObjectivesThe purpose of this paper is to solve the vibration equations of a ring-stiffened conical shell using the analytical method, and to investigate the vibration characteristics of a ring-stiffened conical shell theoretically.MethodsFirst, the ring-stiffened conical shell is processed in segments, and its displacement along the radial, circumferential and normal directions is written in the form of power series solutions respectively. The recurrence relations of the coefficients ahead of the power series are then derived in detail. At the same time, a beam model is used to simulate the influence of the number of ring-stiffeners on the vibration characteristics of the conical shell, and the boundary conditions, displacement, internal force matrices and ring-stiffeners of the conical shell segments are assembled and solved, thereby obtaining the vibration response of the shell under harmonic external excitation. Moreover, a comparison of the calculation results with those obtained by the ANSYS finite element analysis is carried out to verify the validity of the proposed method. Finally, the theoretical method is applied to analyze the vibration characteristics of the ring-stiffened conical shell theoretically. ResultsThe results show that installing ring-stiffeners on the conical shell can significantly suppress the vibration of the conical shell, which is manifested by the decrease in response amplitude, the increase in natural frequency, and the decrease in the number of resonance peaks within the same frequency band. Increasing the thickness of the shell can reduce the vibration response amplitude and increase the natural frequency of the ring-stiffened conical shell. In addition, increasing the half cone angle, axis length and the number of ring ribs can also reduce the vibration response amplitude of the ring-stiffened conical shell.ConclusionsThe results of this study prove that the method used herein has a certain significance for the theoretical analysis of the vibration characteristics of ring-stiffened conical shells.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

Reassortment is a key driving force of the evolution and host adaptation of the influenza virus. A(H1N1)pdm2009 (pdm09), a novel H1N1 influenza viral subtype, caused a pandemic in 2009. The strain was established in pig herds and cocirculated with the highly pathogenic H5N1 avian influenza virus. The coexistence of pdm09 with H5N1 raises concerns that reassortment may cause the development of novel viral strains with unpredictable virulence. Given that the viral polymerase subunit PB2 is a determinant of host range and pathogenicity, and that the substantial amino acid differences in PB2 between pdm09 and H5N1, including positions 590/591 and 271, which are shown to play key roles in enhanced polymerase activity in mammalian host cells, we generated a reassortant virus containing PB2 derived from a pdm09 (A/Liaoning/1/2009, LN/09) to investigate if pdm09-derived PB2 can function in a heterologous avian virus isolate as an adaptive strategy, with H5N1 (A/duck/Hubei/hangmei01/2006, HM/06) as the backbone. We assessed the biological characteristics, including pathogenicity, replication, and polymerase activity, of the reassortant. Compared with HM/06 and LN/09, H5N1 hybrid virus containing PB2 from LN/09 exhibited significantly increased pathogenicity in mice and proliferation activity in mammalian cell lines, as well as markedly enhanced polymerase activity. Our results indicate that the coexistence of H5N1 and pdm09 may pose a great threat to public health through reassortment. Moreover, our results highlight the importance of monitoring the emergence of H5N1 reassortants containing pdm09-derived PB2.

Access network intrusion detection (ANID) is an indispensable role in guaranteeing information security, in which data-classification is a key operating procedure. In this paper, we propose an algorithm of the developed density peak clustering with support vector data description (SVDD), and it can break through the bottleneck of processing high-dimensional data with non-uniform density in the ANID system. The cutoff distance (dc) depending on experience in density peak clustering is then optimized by our defined coefficient called adjusted silhouette coefficient (ASIL). This can overcome the unfitness of traditional SIL due to multi-noise samples and clustering instability. In order to generate an accurate classifier, an improved particle swarm optimization algorithm is also developed to the parameters of SVDD. Finally, the proposed algorithm is evaluated through UCI standard data sets and KDD 99 data sets, and these results show higher accuracy and robustness compared with the conventional methods.