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Purpose: To examine the effect of dexmedetomidine (DEX) on inflammatory response in spinal cord damage, and involvement of IKK/NF-κB signaling pathway in the process.Methods: Sixty healthy male Wistar rats were selected and randomly divided into sham, control, IKK inhibition, and DEX groups. Rat hind limb motor function in each group at 1, 24 and 48 h after surgery was determined using Basso Beattie Bresnahan (BBB) method, while Western blot assay was used to evaluate the protein expression levels of IL-1β, IKK and NF-κB in spinal cord tissue.Results: In DEX rat group, neuromotor function at 24 and 48 h, and protein expression level of IL-1β in spinal cord tissue significantly decreased, relative to IKK inhibition group (p < 0.05). There were higher protein expressions of IKK and NF-κB in IKK inhibition and DEX groups than in sham rats, but were lower than the corresponding values for model group (p < 0.05). However, these proteins were significantly downregulated in DEX group, relative to the IKK inhibition rats (p < 0.05).Conclusion: DEX mitigates inflammatory response in rats with acute spinal cord injury via IKK/NF-κB signaling pathway. This provides some ideas for research and development of other drugs for the treatment of acute spinal cord injury.

Data augmentation is a promising technique for unsupervised anomaly detection in industrial applications, where the availability of positive samples is often limited due to factors such as commercial competition and sample collection difficulties. In this paper, how to effectively select and apply data augmentation methods for unsupervised anomaly detection is studied. The impact of various data augmentation methods on different anomaly detection algorithms is systematically investigated through experiments. The experimental results show that the performance of different industrial image anomaly detection (termed as IAD) algorithms is not significantly affected by the specific data augmentation method employed and that combining multiple data augmentation methods does not necessarily yield further improvements in the accuracy of anomaly detection, although it can achieve excellent results on specific methods. These findings provide useful guidance on selecting appropriate data augmentation methods for different requirements in IAD.

Utilizing multi-modal neuroimaging data is proven to be effective in investigating human cognitive activ-ities and certain pathologies. However, it is not practical to obtain the full set of paired neuroimaging data centrally since the collection faces several constraints, e.g., high examination cost, long acquisition time, and image corruption. In addition, these data are dispersed into different medical institutions and thus cannot be aggregated for centralized training considering the privacy issues. There is a clear need to launch federated learning and facilitate the integration of dispersed data from different institutions. In this paper, we propose a new benchmark for federated domain translation on unsupervised brain image synthesis (FedMed-GAN) to bridge the gap between federated learning and medical GAN. FedMed-GAN mitigates the mode collapse without sacrificing the performance of generators, and is widely applied to different proportions of unpaired and paired data with variation adaptation properties. We treat the gradient penalties using the federated averaging algorithm and then leverage the differential privacy gra-dient descent to regularize the training dynamics. A comprehensive evaluation is provided for comparing FedMed-GAN and other centralized methods, demonstrating that the proposed algorithm outperforms the state-of-the-art. Our code is available at: https://github.com/M-3LAB/FedMed-GAN.(c) 2023 Elsevier B.V. All rights reserved.

Image anomaly detection (IAD) is an emerging and vital computer vision task in industrial manufacturing (IM). Recently many advanced algorithms have been published, but their performance deviates greatly. We realize that the lack of actual IM settings most probably hinders the development and usage of these methods in real-world applications. As far as we know, IAD methods are not evaluated systematically. As a result, this makes it difficult for researchers to analyze them because they are designed for different or special cases. To solve this problem, we first propose a uniform IM setting to assess how well these algorithms perform, which includes several aspects, i.e., various levels of supervision (unsupervised vs. semi-supervised), few-shot learning, continual learning, noisy labels, memory usage, and inference speed. Moreover, we skillfully build a comprehensive image anomaly detection benchmark (IM-IAD) that includes 16 algorithms on 7 mainstream datasets with uniform settings. Our extensive experiments (17,017 in total) provide in-depth insights for IAD algorithm redesign or selection under the IM setting. Next, the proposed benchmark IM-IAD gives challenges as well as directions for the future. To foster reproducibility and accessibility, the source code of IM-IAD is uploaded on the website, https://github.com/M-3LAB/IM-IAD.

BackgroundThe association between grip strength and depression in elderly individuals in low- and middle-income countries (LMICs) has rarely been studied. This study aims to explore the relevance of grip strength and depression in the elderly population using data from a national large-scale population.MethodsThis study was conducted using data from seniors over 60 years old in wave 1 of the Longitudinal Aging Study in India (LASI). Grip strength is the maximum of three measurements by the dynamometer. Depression symptoms were assessed using 10 items on the Center for Epidemiologic Studies Depression Scale (CESD-10) with a 10-point boundary. Multivariate linear regression analysis, non-linear analysis, subgroup analysis, interaction tests and sensitivity analysis were performed.ResultsThere were 27,343 participants in this study, including 19,861 participants with low grip strength and 7,482 participants with normal grip strength. The results revealed that grip strength and depression were negatively correlated in elderly individuals after adequate adjustment for confounding factors [odds ratio (OR) = 1.237, 95% confidence interval (CI) 1.172–1.305, p < 0.00001]. The results remained stable after adjusting for all confounding factors (OR = 1.090, 95% CI 1.030–1.155, p = 0.00307). Regression analysis showed that physical activity (PA), comorbidities and cognition may have an impact on the correlation between grip strength and depression symptoms. Smooth curve fit suggested that grip strength and depressive symptoms were linearly related. The interaction test results of gender in the relationship between grip strength and depression were significant (p for interaction < 0.05).ConclusionGrip strength and depression were negatively correlated in older Indians, and larger prospective studies are needed in the future to determine this association.

The existence of completely aligned and paired multi-modal neuroimaging data has proved its effectiveness in diagnosis of brain diseases. However, collecting the full set of well-aligned and paired data is expensive or even impractical, since the practical difficulties may include high cost, long time acquisition, image corruption, and privacy issues. A realistic solution is to explore either an unsupervised learning or a semi-supervised learning to synthesize the absent neuroimaging data. In this paper, we are the first one to comprehensively approach cross-modality neuroimage synthesis task from different perspectives, which include the level of the supervision (especially for weakly-supervised and unsupervised), loss function, evaluation metrics, the range of modality synthesis, datasets (aligned, private and public) and the synthesis-based downstream tasks. To begin with, we highlight several opening challenges for cross-modality neuroimage sysnthesis. Then we summarize the architecture of cross-modality synthesis under various of supervision level. In addition, we provide in-depth analysis of how cross-modality neuroimage synthesis can improve the performance of different downstream tasks. Finally, we re-evaluate the open challenges and point out the future directions for the remaining challenges. All resources are available at https://github.com/M-3LAB/awesome-multimodal-brain-image-systhesis

Visual sensory anomaly detection (AD) is an essential problem in computer vision, which is gaining momentum recently thanks to the development of AI for good. Compared with semantic anomaly detection which detects anomaly at the label level (semantic shift), visual sensory AD detects the abnormal part of the sample (covariate shift). However, no thorough review has been provided to summarize this area for the computer vision community. In this survey, we are the first one to provide a comprehensive review of visual sensory AD and category into three levels according to the form of anomalies. Furthermore, we classify each kind of anomaly according to the level of supervision. Finally, we summarize the challenges and provide open directions for this community. All resources are available at https://github.com/M-3LAB/awesome-visual-sensory-anomaly-detection.

This work concerns the control of unknown nonlinear systems corrupted by disturbances. For such systems, we propose an anti-disturbance dual control approach with active learning of the disturbances. Our approach holds the dual property of handling the two tasks simultaneously and iteratively: (i) learn the disturbances affecting the system and (ii) drive the system output towards a reference trajectory. Particularly, we model nonlinear system dynamics using a specialized neural network (SNN). This SNN formulates the disturbances via the designed additive and multiplicative disturbance components. We consider both additive and multiplicative disturbances for precise description and recognition of disturbance profile. We achieve the disturbance recognition in the SNN via the design of a Bayesian-based active learning approach, which allows the disturbance learning to be decoupled from the control law derivation. Such a decoupling contributes to the control robustness in the existence of varying and abrupt disturbances. We derive the dual control law based on the active learning of the SNN, and validate our approach via one-time and Monte Carlo simulations. The results demonstrate a fast disturbance recognition by our method in real-time and the robustness of control of unknown systems with abrupt disturbances. We evaluate our approach on the speed control of high-speed train, and the results manifest efficient control of the train speed with disturbance resilience, without prior knowledge about the train dynamics and the disturbances imposed on the train. We openly released the code for this work for reproduction purpose.

In the present paper, the different heat transfer mechanisms in living biological tissue during pulse laser irradiation are studied with the fractional thermal wave bio-heat transfer (FTWBT) equation, the thermal wave bio-heat transfer (TWBT) equation and the Pennes bio-heat transfer (PBT) equation, respectively. The corresponding non-Fourier boundary condition is established and the analytical solutions based on the three models are obtained by employing the Fourier and Laplace transform methods. The heat wave propagation characteristics in biological tissues are revealed and discussed in detail. The results show that the FTWBT model has advantages over the others to describe the bio-heat transfer in laser therapy as long as the boundary condition is correct. The heat transfer predicted by the FTWBT model reveals the thermal diffusion feature as well as the thermal wave behavior, which is dependent on the fractional order parameter and biological tissue relaxation time.

Porcine reproductive and respiratory syndrome is an infectious disease that causes serious economic losses to the swine industry worldwide. To better understand the pathogenesis of the porcine reproductive and respiratory syndrome virus (PRRSV), three PRRSV strains with different molecular markers and virulence were used to infect MARC-145 cells. A total of 1804 proteins were identified, and 233 altered proteins and 72 signaling pathways involved in the proteomic profiling of virus-infected MARC-145 cells increased with the virulence of the PRRSV strain. The three types of viral strains shared a common pathway—the electron transport reaction in mitochondria—in the infected-MARC-145 cells. Moreover, the antisense pathway was the most variable of all significant signaling pathways for the highly virulent SX-1 strain, indicating that this unique pathway may be connected to the high virulence of the SX-1 strain. Our study is the first attempt to provide a proteome profile of MARC-145 cells infected with PRRSV strains with different virulence, and these findings will facilitate a deep understanding of the interactions between this virus and its host.

Circovirus infection is a growing problem in the field of veterinary and public health. It is associated with enteric diseases in both mammalian and avian hosts. In this study, we detected and isolated porcine circovirus strains in the tissue samples of minks that died from diarrhoea in Shandong Province, China. We sequenced the whole genome of two porcine strains of Circovirus, designated as MiSD-1 and MiSD-2， which had a 97.34% similarity on nucleotide sequence and were closely related to porcine circovirus type 2 (PCV2), but distantly related to mink circoviral species. Phylogenetically MiSD-1 and MiSD-2 are a part of the PCV2b genotype cluster, which is a highly prevalent genotype worldwide. The closer relationship of MiSD-1 and MiSD-2 to PCV2 from pigs than to other mink circoviral species may be evidence of cross-species transmission and considerable zoonotic potential.

The value of form factor k at different drafts is important in predicting full-scale total resistance and speed for different types of ships. In the ITTC community, most organizations predict form factor k using a low-speed model test. However, this method is problematic for ships with bulbous bows and transom. In this article, a Computational Fluid Dynamics (CFD)-based method is introduced to obtain k for different type of ships at different drafts, and a comparison is made between the CFD method and the model test. The results show that the CFD method produces reasonable k values. A grid generating method and turbulence model are briefly discussed in the context of obtaining a consistent k using CFD.

Porcine circovirus type 2 (PCV2), the essential causative agent of postweaning multisystemic wasting syndrome (PMWS), can be divided into distinct genotypes. Thirty-two PCV2 isolates obtained made from pigs in Shandong Province between 2005 and 2013. Complete genome sequences were obtained in three replicates for each virus isolate, and the sequences were submitted to the NCBI database. The ORF1-encoded amino acid sequences had 98.4 %-100 % identity among the 32 isolates, and there were no significant differences among the three potential glycosylation positions: aa 23-25 (NPS), aa 256-258 (NQT) and aa 286-288 (NAT). The amino acid sequences of ORF2 had 88 %-100 % identity among the 32 isolates and the potential glycosylation position in the cap protein, aa 143-145 (NYS), had no variation. Phylogenetic analysis revealed that the PCV2b/1C genetic lineage was prevalent in swine populations in Shandong Province. It also suggested that selection pressure has made the PCV2 isolates more genetically distant from current vaccine strains.

Submerged breakwater is a kind of commonly used maritime sheltering structures, so it is necessary to accurately grasp the hydrodynamic characteristics before and after the submerged breakwater. Based on the longshore current experiment in harbor, taking the trapezoid submerged breakwater as the research object, this paper analyzes the influence of submerged breakwater on the mean longshore current by changing the position of submerged breakwater and observes the effect of submerged breakwater on the instability of longshore currents for frequency fluctuation. The results show that the closer the submerged breakwater, cross-shore longshore current velocity has the more obvious tendency to toward the shore. Meanwhile, it will make the upstream direction of longshore current velocity increase and will make the distribution of longshore current velocity in the direction of the whole coast is more uniform. Furthermore, some frequency fluctuation of longshore current instability may strong and new high frequency components of the instability of longshore currents may occur for the increase of the submerged breakwater.

PRRS is one of the most important diseases in swine industry. Current PRRS inactivated vaccine provides only a limited protection and cannot induce sufficient cell-mediated immune responses. In this study, we first found that the mRNA and protein levels of Th1-type cytokines (IFN-γ, IL-12) and Th2-type cytokines (IL-6, IL-10) were significantly increased through TRIF/MyD88-NF-κB signaling pathway when porcine peripheral blood monocyte-derived dendritic cells (MoDCs) were treated with poly (I: C) of TLR3 ligand and imiquimod of TLR7 ligand, along with inactivated PRRSV antigen. Meanwhile, the ability of catching PRRSV antigen was also significantly enhanced. In mice experiment, it was found that the PRRSV-specific T lymphocyte proliferation, the percentages of CD4+, CD8+ T lymphocytes and PRRSV-specific CD3+ T cells producing IFN-γ and IL-4, the levels of Th1- and Th2-type cytokines and the titers of neutralization antibody were significantly enhanced in poly (I: C), imiquimod along with inactivated PRRSV group. Taken together, results of our experiments described for the first time that synergy of TLR3 and 7 ligands could significantly enhance the function of DCs to present inactivated PRRSV antigen through TRIF/MyD88-NF-κB signaling pathway and be used as adjuvant candidate for the development of novel PRRS inactivated vaccine.

To improve the efficacy of porcine reproductive and respiratory syndrome virus (PRRSV) subunit vaccine, the immunological enhancement effects of four natural adjuvants were compared, including Astragalus extract, Astragalus/Bacillus production, propolis, and Freund's adjuvant. The results showed that titers of IgG and neutralizing antibody against highly pathogenic PRRSV (HP-PRRSV) glycoprotein 5 (GP5) from the groups of Astragalus/Bacillus adjuvant and Freund's adjuvant co-administered with a recombinant HP-PRRSV GP5 subunit were the highest among all the experimental groups. In cellular immunity, as shown in T lymphocyte proliferation level, Astragalus/Bacillus adjuvant and Freund's adjuvant exhibited the most potent immunological enhancement effects. Exceptionally, pigs inoculated with Freund's adjuvant developed severely delayed humoral immune responses within 28 days post inoculation. The adjuvants of Astragalus extract and propolis also exhibited immunological enhancement effects on humoral immune and cell-mediated immune responses, but which were obviously lower than Astragalus/Bacillus adjuvant and Freund's adjuvant. Following challenge with HP-PRRSV, pigs inoculated with Astragalus/Bacillus adjuvant and Freund's adjuvant co-administered with GP5 subunit showed lower viremia, slighter clinical signs, and less pathological lung lesions compared with the groups inoculated using Astragalus extract and propolis. In conclusion, from immune responses and immunological protection against HP-PRRSV, the Astragalus/Bacillus adjuvant demonstrated the most potent immunological enhancement effect on HP-PRRSV GP5 subunit. Astragalus/Bacillus adjuvant showed promise as a candidate immune adjuvant, to more efficiently prevent and control PRRS.

Dissimilar metals of copper (T2) and aluminium (1035) were brazed by vacuum brazing technology. Microstructure and phase constitution for the Cu/Al vacuum brazing were studied by means of metallography, electron probe microanalyser and X-ray diffraction. Experiment results indicated that an obvious transition layer of copper based solution was formed near the interface of copper and braze metal. The brazing seam zone mainly consists of various solid solutions between many elements and a few intermetallic compounds which are hard and brittle. This is favourable to the enhancing of service performance of the Cu/Al brazed joint. Process parameters of vacuum brazing are: brazing temperature T=425°C, vacuum level=10−3 Pa, holding time t=15 min.

The microstructure of Fe3Al/18-8 diffusion bonding joint after heat treatment was analysed by metalloscopy, scanning electron microscopy and X-ray diffraction. The experimental results indicated that the size of grains near the Fe3Al/18-8 diffusion interface was decreased significantly and the microstructure near the interface became homogeneous. The precipitations also became tiny with regular shape and were distributed evenly at the interface region. The microhardness of the Fe3A1/18-8 diffusion bonding joint was decreased and no brittle phase with high microhardness existed near the interface after heat treatment. The suitable parameters of heat treatment were: heating temperature T=800°C, holding time t=30 min, furnace cooling to 700°C then air cooling.

The effects of technological parameters on the interface morphology and shear strength of Fe3Al/18-8 diffusion bonded joints have been researched by means of a JXA-80 scanning electron microscope (SEM) and a digital tensile press test machine. Microstructural characteristics and fracture morphology near the Fe3Al/18-8 diffusion interface, obtained under conditions of various technological parameters, have been analysed using the SEM. The test results indicate that a diffusion bonded joint with higher shear strength (στ = 226 MPa) may be obtained with a heating temperature T = 1020 – 1040°C, holding time t = 45 – 60 min and pressure P = 12 – 15 MPa.

Phase structure characteristics near the interface of Fe3Al/Q235 carbon steel diffusion bonding are researched by means of X-ray diffraction and TEM. The test results indicated that an obvious diffusion transition zone was formed near the Fe3Al/Q235 carbon steel interface under the conditions: heating temperature 1050 - 1100°C, holding time 60 min and pressure 9.8 MPa. The diffusion transition zone consisted of Fe3Al and α-Fe (Al) solid solution. The microhardness near the diffusion transition zone was 480 - 540 HV(25 g). There was no brittleness phase of high hardness in the diffusion transition zone. This is favourable for increasing the toughness of a Fe3Al/Q235 diffusion joint. There was a crystal orientation relationship of (110) α-Fe(Al)//(011)Fe3Al and [001]α-Fe(Al)//[100]Fe3Al between the Fe3Al phase and the α-Fe (Al) solid solution in the diffusion transition zone.

A new species,Clathrocorys gracilis nov. spec. of Tripocyrtidae (Radiolarians: Nassellaria) from surface water in northern South China Sea, is described in this paper. The new species has four radial beams arising from the cephalic base centre, each foot with cup-shaped structure and ramified bar in the proximal section (near cephalic base), and each wing with a large mesh in the middle, a medium mesh and a small mesh on each side respectively.

A serologic investigation of porcine reproductive and respiratory syndrome virus (PRRSV) in hybrid wild boar herds was conducted during 2008–2009. PRRSV isolates with novel genetic markers were recovered. Experimental infection of pigs indicated that hybrid wild boars are involved in the epidemiology of PRRSV.

Porcine reproductive and respiratory syndrome (PRRS) has become one of the most economically important diseases to the global pork industry. The etiological agent is the PRRS virus (PRRSV). In the spring of 2006, a highly pathogenic porcine reproductive and respiratory syndrome virus (HP-PRRSV) appeared in China and caused heavy economic losses. Here we report the complete genomic sequence of a novel PRRSV variant with 174 amino acid deletions in the nonstructural protein 2 ( nsp2 ) gene.

Porcine reproductive and respiratory syndrome virus (PRRSV) has become one of the most economically important diseases to the global pork industry. Current vaccination strategies only provide a limited protective efficacy. In this study, a DNA vaccine, pVAX1(©)-α-γ-GP35, co-expressing GP3 and GP5 of PRRSV with interferon α/γ was constructed, and its immediate and long-lasting protection against highly pathogenic PRRSV (HP-PRRSV) challenge were examined in pigs. For immediate protection, the results showed that pVAX1(©)-α-γ-GP35 could provide partially protective efficacy, which was similar to the pVAX1(©)-α-γ (expressing interferon α/γ). For long-lasting protection, pigs inoculated with pVAX1(©)-α-γ-GP35 developed significantly higher PRRSV-specific antibody response, T cell proliferation, IFN-γ, and IL-4, than those vaccinated with pVAX1(©)-GP35 (expressing GP3 and GP5 of PRRSV). Following homologous challenge with HP-PRRSV strain SD-JN, pigs inoculated with pVAX1(©)-α-γ-GP35 showed almost no clinical signs, no lung lesions, and significantly lower viremia, as compared to those in pVAX1(©)-GP35 group. It indicated that pVAX1(©)-α-γ-GP35 could induce enhanced immune responses and provide both immediate and long-lasting protection against HP-PRRSV challenge in pigs. The DNA vaccine pVAX1(©)-α-γ-GP35 might be an attractive candidate vaccine for the prevention and control of HP-PRRSV infections.

Studying on river shoal evolution is a fundamental work in the science of water conservancy, water conservancy projects and waterways planning, designing, engineering feasiblility. First of all, the neural network model for predicting the evolution of shoal in a river is established, through training the neural network to determine the number of hidden layer’s neural, thus, a more ration neural network structure is detemaned; In the second step, by using genetic algorithm a fittest initial weight value is selectled from the solution group of initial weight values to avoid the blindness in the selection of initial weight value; if the traditional BP algorithm is used in the training, there are still some hidden dangers. Finally, conjugate gradient algorithm is used to improve performance of network. Simulation results show that the method is feasible and effective.

Focusing on the popular feature parameters applied in speaker recognition, this paper produces the scheme of the effective parameter optimization. In particular, optimized mel-frequency cepstrum coefficients obtained by adjusting the parameters of the filterbank using unidimensional search reveal their improved ability to represent the vital identification information embedded in the utterances of the different speakers. To evaluate the performance of the optimized parameters, the recognition experiments addressing the speech data of Chinese digit words have been conducted and the average recognition accuracy increases by 0.94% consistently.

This paper produces two types of the features of speaker recognition, mean of column elements (MC) and squared 2-norm of column elements (SNC). Both of them are derived from the curvelets representing the geometrical structure of squared modulus of Gabor representation of one-dimensional speech. The performance evaluation experiments have been conducted and the results indicate that with the score of 87.23%, the feature of mean of column elements bears a little better identification effect than that of squared 2-norm of column elements. The recognition accuracy of Mel-frequency cepstral coefficients (MFCC) reaches 86.52% based on the same speech database

As the generalization of the classical Fourier transform, fractional Fourier transform(FRFT) is introduced into the field of speaker recognition in this paper. The individual feature sets derived from fractional Fourier transform achieve the excellent recognition success rate which goes up to the extent a little higher than the counterparts of the classical MFCC parameters when applied in the GMM classifiers. In addition, the computation efficiency of the feature extraction process arrives at the acceptable level which completely matches the one of MFCC parameter acquirement.

An evaluation of the feature set of the vector difference (VD) based on fractional cosine and sine transform focusing on the high-order fractional domains for text-independent speaker recognition is elucidated in this paper. The experiments have been done following the principles varying the number of the vector dimension and the power of the output parameters of fractional cosine and sine transform separately. The recognition results show that when the order of primary fractional domain is fixed to be 1 and the one of secondary fractional domain is 0.98, the correct recognition rate of the VD feature matches the one of the previous MFCC feature

In the literature of speaker recognition, the short-term features obviously dominates in the description of the individualized information for the candidates whose conventional assumption is the nonstationarity in the block. This paper discards the popular ideas and produces such features as segment center decimation(SCD), differential segment center decimation (DSCD), maximum element(MAE) and minimum element(MIE) to examine the geometrical composition of the spectrum in the time-frequency plane of the one-dimensional speech signal. A great number of the experiments based on these features have shown that the feature sets of segment center decimation and differential segment center decimation possess the favorable recognition performance respectively, especially when the process of the reasonable dimension reduction is imposed

This paper presents the fusion features resulting from contourlet transform on the geometry structure in the time-frequency representation for the one-dimensional speech. In the experiments, after extracting the separate features including main diagonal of the inner lowpass subband (MDL), main anti-diagonal of the inner lowpass subband (MADL), main diagonal of bandpass subband (MDB) and ordinal binary tree difference of main diagonal of bandpass subband(BTDB), the combination features such as MDL-MDB, MDL-MADL-MDB and MDL-MADL-BTDB achieve the remarkable performance with the recognition veracity up to 86.88% enough to match the classical MFCC parameters though the high dimension of the fusion features is still a disadvantage

In this paper, the novel features derived from fractional cosine and sine transform of speaker recognition task are presented, which are abbreviated to be DMEGB and Delta DMEGB. A lot of the experiments based on the multiple parameters are employed to investigate their recognition performance. The single application of above mentioned features doesn't show the excellent results, but the reasonable combination of them which is able to describe the speaker individual characteristics more exactly will lead to the favorable effects which are even better than the conventional MFCC feature.

Porcine circovirus (PCV), belonging to Circoviridae family, is a small, non-enveloped, icosahedral virus containing a circular single-stranded DNA genome (Tischer and others 1982). PCV is divided into two genotypes, PCV type 1 (PCV1) and PCV type 2 (PCV2). PCV1 is a contaminant of PK-15 cells that is non-pathogenic and exists in pigs (Tischer and others 1986, Puvanendiran and others 2011). PCV2 is associated with postweaning multisystemic wasting syndrome (PMWS), which has caused severe losses in the global swine industry in recent decades. Many PK-15 cell lines are contaminated with PCV1, which confers difficulty in using PK-15 cell line to isolate PCV2 for further research. Accordingly, this study aimed to establish a multiplex real-time PCR assay to differentiate and rapidly detect PCV1 and PCV2 in laboratory and clinical samples. PCV2 strain SD2 (GenBank Accession Number DQ478947) was originally isolated from a pig that clinically manifested PMWS (Zhou and others 2009). In the present study, PCV1 was cultured in our laboratory using PK-15 cells. PCV1 and PCV2 viral DNA were extracted by the proteinase K method according to the instructions(Sambrook and others 2001). Primer P15ʹ-GAACCGCGGGCTGGCTGA ACTTTTGAAAGT-3ʹ and …

PORCINE reproductive and respiratory syndrome (prrs) is an economically important disease of pigs, defined by severe respiratory disorders in piglets and reproductive failure in gestating sows and gilts. prrs has been reported in most pig-producing countries in the world, with only a few countries

We report here the genome sequence of a recombinant porcine circovirus type 2 strain SD-3, isolated from a commercial swine farm with an outbreak of postweaning multisystemic wasting syndrome (PMWS) in pigs in Shandong Province of China. The complete circular genome of this isolate is 1,767 nucleotides in length. This recombinant isolate has the ORF1 regions from PCV2a viruses and ORF2 regions from PCV2b. The findings will help us to understand the molecular evolution of porcine circovirus type 2 and the relationship between porcine circovirus type 2 and disease.