Study on the genotypes of Echinococcus granulosus in yaks and sheep from Langkazi County in Tibet Autonomous Region of China based on mitochondrial cox1 and nad1.

To determine the genotypes of the epidemic strains of Echinococcus granulosus in livestock in Tibet, samples of E. granulosus cysts were collected from 11 yaks and 62 sheep. Genomic DNA was extracted from these samples, and gene fragments of mitochondrial cytochrome c oxidase subunit I (cox1) and NADH dehydrogenase subunit I (nad1) were amplified by PCR and sequenced. DNASTAR and MAGA7.0 were employed for homology analysis and phylogenetic tree construction. Echinococcus granulosus cysts were detected in 56.2% (41/73) of the samples screened. Of these, 63.4% (26/41) were identified as E. granulosus G1 genotype (common sheep strain), 24.4% (10 /41) as G3 genotype (buffalo strain), and 12.2% (5/41) were G6 genotype (camel strain). The study concludes that yaks and sheep in Langkazi county, Tibet, carry three E. granulosus genotypes (G1, G3, and G6), with the G1 genotype the predominant genotype in the region. This study clarifies the distribution of E. granulosus genotypes, providing genetic data and insight for the surveillance and prevention of echinococcosis.

Relationship Between Genetic Polymorphism and Cognitive Impairment in Patients with Acute Ischemic Stroke (APOE).

Objective: To investigate the relationship between apolipoprotein E (ApoE) gene polymorphism and cognitive impairment (PSCI) in patients after acute ischemic stroke (AIS). Methods: A total of 150 AIS patients were treated in Chengde Central Hospital from December 2022 to December 2023 and were selected and divided into a disorder group (n=88) and a normal group (n=62) according to the presence or absence of PSCI. Clinical data of patients in the two groups were collected, ApoE genotype and allele distribution of patients in the disabled group and the normal group were detected, Montreal Cognitive Assessment and Mini-Mental State Examination scores of patients with different ApoE gene subtypes were compared, and the risk factors of PSCI after AIS were analyzed by unconditional Logistic regression. Results: The proportion of patients with acute lesions (≥3.0 cm) and the degree of carotid artery stenosis (moderate, severe, complete occlusion) in the disorder group was higher than that in the normal group, and the National Institutes of Health Stroke Scale score was higher than that in the control group, with statistical significance (P < .05). There were significant differences in the genotype and allelic distribution of ApoE between the two groups (P < .05). In both groups, the highest genotype frequency of ApoE was the ε3/3 homozygous type, which was 47.73% (in the disorder group) and 72.58% (in the normal group) respectively. In contrast, there were no significant differences in the genotype frequencies of ε2/2, ε2/3, ε2/4 and ε4/4 alleles in the two groups (P > .05). This means that in both groups of patients, the frequency of the ApoE ε3/3 genotype was the highest, while the genotype frequencies of ε2/2, ε2/3, ε2/4 and ε4/4 alleles were not significant between the two groups. difference. The distribution differences of these genotypes and alleles may be related to aspects such as disease risk and physiological function, providing valuable information for in-depth exploration of the role of ApoE in patients. The genotype frequency of ε3/3 in the disorder group was lower than that in the normal group. The frequency of the ε3/4 genotype was higher than that of the normal group, and the difference was statistically significant (P < .05). In both groups, the highest allele frequency was ε3 (68.75% in the disorder group and 83.06% in the normal group), and there was no difference in the frequency of ε2 allele between the two groups (P > .05). The frequency of the ε3 allele in the disorder group was lower than that in the normal group, and the frequency of the ε4 allele was higher than that in the normal group, the difference was statistically significant (P < .05). In the patients with cognitive impairment after AIS (disorder group), the MOCA and MMSE scores of patients with different ApoE subtypes (ε2, ε3, ε4) were compared, and the differences among the three groups were statistically significant (P < .05). The MOCA and MMSE scores in the ε4 group were lower than those in the ε2 and ε3 groups. The difference was statistically significant (P < .05). Logistic regression analysis showed that the degree of carotid artery stenosis, NIHSS score, and ApoEε4 gene were independent risk factors for PSCI in patients with AIS (P < .05). Conclusion: APOE gene polymorphism is associated with cognitive impairment in post-AIS patients, and carrying the ApoE Epsilon 4 gene may be associated with PSCI in post-AIS patients.

Microbiome analysis reveals the differences in gut fungal community between Dutch Warmblood and Mongolian horses.

Similar to gut bacterial community, gut fungal community are also an important part of the gut microbiota and play crucial roles in host immune regulation and metabolism. However, most studies have focused on the gut bacterial community, and research on the gut fungal community has been limited. Dutch Warmblood (DWH) and Mongolian horses (MGH) are important equine breeds, but little research has been done on their gut fungal community. Here, we assessed differences in gut fungal community between two horse species. Results showed that a total of 2159 OTUs were found in the Dutch Warmblood and Mongolian horses, of which 308 were common. Between-group analyzes of microbial diversity showed no differences in the alpha and beta diversity of gut fungal community between the two horse species. Microbiological taxonomic surveys showed that the dominant fungal phyla (Neocallimastigomycota and Ascomycota) and genera (unclassified_Neocallimastigaceae and Anaeromyces) were the same without being affected by species. Although the types of dominant fungal phyla did not change, the abundances of some fungal genera changed significantly. Results of Metastats analysis showed that there were a total of 206 fungal genera that were significantly different between the two horses, among which 78 genera showed an increase and 127 genera significantly decreased in Dutch Warmblood horses compared with Mongolian horses. In conclusion, this study investigated the composition and structure of the gut fungal community of Dutch Warmblood and Mongolian horses and found significant differences in gut fungal community between both breeds. Notably, this is the first exploration of the differences in the gut fungal community of both breeds, which may help to understand the distribution characteristics of the gut fungal community of different breeds of horses and reveal the differences in the traits of different horses.

Lactobacillus reuteri derived from horse alleviates Escherichia coli-induced diarrhea by modulating gut microbiota.

Diarrhea is a prevalent health issue in farm animals and poses a significant challenge to the progress of animal husbandry. Recent evidence suggested that probiotics can alleviate diarrhea by maintaining gut microbial balance and enhancing the integrity of the intestinal barrier. However, there is a scarcity of studies investigating the efficacy of equine Lactobacillus reuteri in relieving E. coli-induced diarrhea. Hence, this study aimed to examine the potential of equine-derived Lactobacillus reuteri in alleviating E. coli diarrhea from the perspective of gut microbiota. Results demonstrated that supplementation of Lactobacillus reuteri had the potential to alleviate diarrhea induced by E. coli infection and restore the decline of tight junction genes, such as Claudin-1 and ZO-1. Additionally, Lactobacillus reuteri supplementation can restore the expression of inflammatory factors (IL-6, IL-10, TNF-α, and IFN-γ) and reduce colon inflammatory damage. Diversity analysis, based on amplicon sequencing, revealed a significant reduction in the diversity of gut microbiota during E. coli-induced diarrhea. Moreover, there were notable statistical differences in the composition and structure of gut microbiota among the different treatment groups. E. coli could induce gut microbial dysbiosis by decreasing the abundance of beneficial bacteria, including Lactobacillus, Bifidobacterium, Ligilactobacillus, Enterorhabdus, and Lachnospiraceae_UCG_001, in comparison to the control group. Conversely, supplementation with Lactobacillus reuteri could restore the abundance of beneficial bacteria and increase the diversity of the gut microbiota, thereby reshaping gut microbiota. Additionally, we also observed that supplementation with Lactobacillus reuteri alone improved the gut microbial composition and structure. In summary, the findings suggest that Lactobacillus reuteri can alleviate E. coli-induced diarrhea by preserving the integrity of the intestinal barrier and modulating the composition of the gut microbiota. These results not only contribute to understanding of the mechanism underlying the beneficial effects of Lactobacillus reuteri in relieving diarrhea, but also provide valuable insights for the development of probiotic products aimed at alleviating diarrheal diseases.

Low-dose thiram exposure elicits dysregulation of the gut microbial ecology in broiler chickens.

Thiram, a typical fungicide pesticide, is widely used in agricultural production. The presence of thiram residues is not only due to over-utilization, but is also primarily attributed to long-term accumulation. However, there is a paucity of information regarding the impact of prolonged utilization of thiram at low doses on the gut microbiota, particularly with respect to gut fungi. Our objective is to explore the effect of thiram on broilers from the perspective of gut microbiota, which includes both bacteria and fungi. We developed a long-term low-dose thiram model to simulate thiram residue and employed 16 S rRNA and ITS gene sequencing to investigate the diversity and profile of gut microbiota between group CC (normal diet) and TC (normal diet supplemented with 5 mg/kg thiram). The results revealed that low doses of thiram had a detrimental effect on broiler's growth performance, resulting in an approximate reduction of 669.33 g in their final body weight at day 45. Our findings indicated that low-dose thiram had a negative impact on the gut bacterial composition, leading to a notable reduction in the abundance of Merdibacter, Paenibacillus, Macrococcus, Fournierella, and Anaeroplasma (p < 0.05) compared to the CC group. Conversely, the relative level of Myroides was significantly increased (p < 0.05) in response to thiram exposure. In gut fungi, thiram significantly enhanced the diversity and richness of gut fungal populations (p < 0.05), as evidenced by the notable increase in alpha indices, i.e. ACE (CC: 346.49 ± 117.27 vs TC: 787.27 ± 379.14, p < 0.05), Chao 1 (CC: 317.63 ± 69.13 vs TC: 504.85 ± 104.50, p < 0.05), Shannon (CC: 1.28 ± 1.19 vs TC: 5.39 ± 2.66, p < 0.05), Simpson (CC: 0.21 ± 0.21 vs TC: 0.78 ± 0.34, p < 0.05). Furthermore, the abundance of Ascomycota, Kickxellomycota, and Glomeromycota were significantly increased (p < 0.05) by exposure to thiram, conversely, the level of Basidiomycota was decreased (p < 0.05) in the TC group compared to the CC group. Overall, this study demonstrated that low doses of thiram induced significant changes in the composition and abundance of gut microbiota in broilers, with more pronounced changes observed in the gut fungal community as compared to the gut bacterial community. Importantly, our findings further emphasize the potential risks associated with low dose thiram exposure and have revealed a novel discovery indicating that significant alterations in gut fungi may serve as the crucial factor contributing to the detrimental effects exerted by thiram residues.

MCMNET: Multi-Scale Context Modeling Network for Temporal Action Detection.

Temporal action detection is a very important and challenging task in the field of video understanding, especially for datasets with significant differences in action duration. The temporal relationships between the action instances contained in these datasets are very complex. For such videos, it is necessary to capture information with a richer temporal distribution as much as possible. In this paper, we propose a dual-stream model that can model contextual information at multiple temporal scales. First, the input video is divided into two resolution streams, followed by a Multi-Resolution Context Aggregation module to capture multi-scale temporal information. Additionally, an Information Enhancement module is added after the high-resolution input stream to model both long-range and short-range contexts. Finally, the outputs of the two modules are merged to obtain features with rich temporal information for action localization and classification. We conducted experiments on three datasets to evaluate the proposed approach. On ActivityNet-v1.3, an average mAP (mean Average Precision) of 32.83% was obtained. On Charades, the best performance was obtained, with an average mAP of 27.3%. On TSU (Toyota Smarthome Untrimmed), an average mAP of 33.1% was achieved.

Influence of Family-centered Health Intervention on Perioperative Mental Health of Patients Receiving Coronary Interventional Therapy.

Introduction: Cardiovascular ailments threaten human health. In China, the primary cardiovascular diseases include stroke and coronary heart disease, resulting in rising morbidity and mortality rates. Coronary heart disease accounts for 10%-20% of all deaths from cardiovascular diseases. These diseases increasingly affect younger individuals, with the disparity in incidence between urban and rural areas gradually diminishing. Experts predict that cardiovascular diseases will continue to increase through the end of this century and into the next in China. Therefore, it is imperative to implement preventive measures to treat coronary heart disease. This paper explores how family-centered health intervention affects anxiety levels, depression symptoms, and sleep quality among perioperative patients receiving coronary interventional therapy. Methods: The participants for this study received coronary intervention therapy in the researchers' hospital from August 2020 to April 2021. Study participants comprised control and observation groups based on a random number table. Both groups received routine care. However, the observation group received family-centered health interventions. Researchers observed the differences in anxiety and depression scores, self-care ability, sleep quality, and incidence of complications between the two groups before and after the intervention. Results: Following the intervention, the sleep quality of the observation group was better than that of the control group, and the difference was statistically significant. There was no difference in activities of daily living (ADL) scores between the two groups before the intervention. Moreover, there was no significant difference in ADL scores on the first, second, and third postoperative days. The incidence of postoperative arrhythmia and coronary artery restenosis between the two groups showed a statistically significant difference. Conclusions: Family-centered health intervention benefited perioperative patients receiving coronary intervention therapy. It improved patients' mood and sleep quality and demonstrated positive application value.

Multivariate logistic regression analysis of clinical characteristics and risk factors of cognitive impairment after cerebral ischemic stroke: implications for clinical treatment.

Background: Stroke ranks first among disease fatalities, and those who do survive stroke are prone to cognitive impairment. The aim of this study was to explore the clinical characteristics of post stroke cognitive impairment (PSCI) and the risk factors of PSCI using multivariate logistic regression. Methods: January 2018 to January 2021, the clinical data of 120 patients treated for cerebral ischemic stroke (CIS) at Chengde Central Hospital were retrospectively analyzed. In this study, patients were divided into 2 groups: a control group and a cognitive impairment group. The clinical characteristics of cognitive impairment following CIS were determined using multivariate logistic regression analysis to examine the risk factors and identify clinical implications. Results: This study included the assessment of overall cognitive function and daily living activities of 120 participants, 68 of whom experienced cognitive impairment, representing an incidence of 57%, while 43% patients represented no cognitive impairment after CIS. After the careful analysis of the data, there were remarkable differences in age, sex, education level, stroke history, infarction area, and infarction location (P<0.05). There was no remarkable difference in the history of hypertension, diabetes, atrial fibrillation, carotid intima thickness, smoking, or drinking (P>0.05). The degree of white matter degeneration, brain atrophy, and dominant hemisphere involvement was higher in the cognitive impairment group (P<0.05). The results of multivariate logistic regression analysis indicated that sex, age, education level, stroke history, infarction size, and infarction location were the main risk factors for cognitive impairment after CIS (P<0.05). Conclusions: Patients with cognitive impairment after CIS have imaging features of white matter degeneration, brain atrophy, and involvement of dominant hemispheres. The results of multivariate logistic regression analysis indicated that sex, age, education level, stroke history, infarct size, and infarct location were main risk factors of cognitive impairment after CIS.

Multi-Modality Adaptive Feature Fusion Graph Convolutional Network for Skeleton-Based Action Recognition.

Graph convolutional networks are widely used in skeleton-based action recognition because of their good fitting ability to non-Euclidean data. While conventional multi-scale temporal convolution uses several fixed-size convolution kernels or dilation rates at each layer of the network, we argue that different layers and datasets require different receptive fields. We use multi-scale adaptive convolution kernels and dilation rates to optimize traditional multi-scale temporal convolution with a simple and effective self attention mechanism, allowing different network layers to adaptively select convolution kernels of different sizes and dilation rates instead of being fixed and unchanged. Besides, the effective receptive field of the simple residual connection is not large, and there is a great deal of redundancy in the deep residual network, which will lead to the loss of context when aggregating spatio-temporal information. This article introduces a feature fusion mechanism that replaces the residual connection between initial features and temporal module outputs, effectively solving the problems of context aggregation and initial feature fusion. We propose a multi-modality adaptive feature fusion framework (MMAFF) to simultaneously increase the receptive field in both spatial and temporal dimensions. Concretely, we input the features extracted by the spatial module into the adaptive temporal fusion module to simultaneously extract multi-scale skeleton features in both spatial and temporal parts. In addition, based on the current multi-stream approach, we use the limb stream to uniformly process correlated data from multiple modalities. Extensive experiments show that our model obtains competitive results with state-of-the-art methods on the NTU-RGB+D 60 and NTU-RGB+D 120 datasets.

Synthesis and Sonodynamic Antibacterial Activity Evaluation of Three Novel Fluoroquinolone Compounds.

OBJECTIVE: Three ciprofloxacin derivatives (CPDs) were synthesized. Also, their sonodynamic antibacterial activities and possible mechanism under ultrasound (US) irradiation were preliminarily investigated. METHODS: Staphylococcus aureus and Escherichia coli were selected as the research objects. The sonodynamic antibacterial effects of three CPDs and their structure-effective relationship were explored by the inhibition rate. The reactive oxygen species (ROS) produced under US irradiation were detected by oxidative extraction spectrophotometry and used to analyze the sonodynamic antibacterial mechanism of three CPDs. RESULTS: Research indicated that three CPDs, named compound 1 (C1), compound 2 (C2) and compound 3 (C3), separately all had strong sonodynamic antibacterial activities. In addition, C3 had the strongest effect relative to the other CPDs. The study also found that CPDs' concentration, US irradiation time, US solution temperature and US medium could disturb their sonodynamic antimicrobial effects. Moreover, 1O2 and ·OH were the main types of ROS produced by C1 and C3; the ROS produced by C2 included 1O2, among other types. CONCLUSION: Results showed that all three CPDs could be activated to produce ROS after US irradiation. Among them, C3 displayed the highest ROS production and the utmost activity, which may be related to the introduction of the electron-giving group at the C-3 position of the quinoline backbone.

Incorporating Multivariate Auxiliary Information for Traffic Prediction on Highways.

Traffic flow prediction is one of the most important tasks of the Intelligent Transportation Systems (ITSs) for traffic management, and it is also a challenging task affected by many complex factors, such as weather and time. Many cities adopt efficient traffic prediction methods to control traffic congestion. However, most of the existing methods of traffic prediction focus on urban road scenarios, neglecting the complexity of multivariate auxiliary information in highways. Moreover, these methods have difficulty explaining the prediction results based only on the historical traffic flow sequence. To tackle these problems, we propose a novel traffic prediction model, namely Multi-variate and Multi-horizon prediction based on Long Short-Term Memory (MMLSTM). MMLSTM can effectively incorporate auxiliary information, such as weather and time, based on a strategy of multi-horizon time spans to improve the prediction performance. Specifically, we first exploit a multi-horizon bidirectional LSTM model for fusing the multivariate auxiliary information in different time spans. Then, we combine an attention mechanism and multi-layer perceptron to conduct the traffic prediction. Furthermore, we can use the information of multivariate (weather and time) to provide interpretability to manage the model. Comprehensive experiments are conducted on Hangst and Metr-la datasets, and MMLSTM achieves better performance than baselines on traffic prediction tasks.

The influence of several nutritional supplements on the rational use of cabozantinib.

To promote the rational use of cabozantinib (CBZ), this paper studied the influence of several nutritional supplements on the interaction between CBZ and bovine serum albumin (BSA), an appropriate alternative model for human serum albumin (HSA) that is one of the important transporter proteins in plasma, by fluorescence spectroscopy and UV-vis spectroscopy. The results showed that CBZ could quench the fluorescence of BSA via a dynamic-static quenching process, and the six nutritional supplements did not change the quenching mode of BSA by CBZ. However, all of them could reduce the binding constant of the CBZ-BSA system at 293 K and increase the polarity around tryptophan residues. Among them, nicotinamide and vitamin B12 (VB12 ) had a greater effect on the binding constants of the CBZ-BSA system. In the meantime, the thermodynamic parameters of the CBZ-BSA system were examined, indicating that the interaction of CBZ with BSA was spontaneous and dominated by hydrophobic forces. Further research discovered that the combining of CBZ with BSA was primarily located within Site I of BSA, and the binding distance r was 2.48 nm. Consequently, while taking CBZ, patients should use VB12 and nicotinamide carefully, which may interfere with the transport of drugs.

Genetic Characterization and Phylogenetic Analysis of Fasciola Species Isolated From Yaks on Qinghai-Tibet Plateau, China.

The present study determined the complete mitochondrial DNA (mt DNA) sequence of Fasciola intermediate (isolated from yaks) based on gene content and genome organization. According to our findings, the genome of Fasciola intermediate was 13,960 bp in length, containing 2 ribosomal RNA (rRNA) genes, 12 protein-coding genes (PCGs), and 22 transfer RNA (tRNA) genes. The A+T content of genomes was 63.19%, with A (15.17%), C (9.31%), G (27.51%), and T as the nucleotide composition (48.02%). Meanwhile, the results showed negative AT-skew (-0.52) and positive GC-skew (0.494). The AT bias significantly affected both the codon usage pattern and amino acid composition of proteins. There were 2715 codons in all 12 protein-coding genes, excluding termination codons. Leu (16.72%) was the most often used amino acid, followed by Val (12.74%), Phe (10.90%), Ser (10.09%), and Gly (8.39%). A phylogenetic tree was built using Maximum-Likelihood (ML) through MEGA 11.0 software. The entire mt DNA sequence of Fasciola intermediate gave more genetic markers for investigating Trematoda population genetics, systematics, and phylogeography. Hence, for the first time, our study confirmed that yaks on the Qinghai-Tibet plateau have the infestation of Fasciola intermediate parasite.

Sequential Recommendation Based on Multivariate Hawkes Process Embedding With Attention.

Recommender systems are important approaches for dealing with the information overload problem in the big data era, and various kinds of auxiliary information, including time and sequential information, can help improve the performance of retrieval and recommendation tasks. However, it is still a challenging problem how to fully exploit such information to achieve high-quality recommendation results and improve users' experience. In this work, we present a novel sequential recommendation model, called multivariate Hawkes process embedding with attention (MHPE-a), which combines a temporal point process with the attention mechanism to predict the items that the target user may interact with according to her/his historical records. Specifically, the proposed approach MHPE-a can model users' sequential patterns in their temporal interaction sequences accurately with a multivariate Hawkes process. Then, we perform an accurate sequential recommendation to satisfy target users' real-time requirements based on their preferences obtained with MHPE-a from their historical records. Especially, an attention mechanism is used to leverage users' long/short-term preferences adaptively to achieve an accurate sequential recommendation. Extensive experiments are conducted on two real-world datasets (lastfm and gowalla), and the results show that MHPE-a achieves better performance than state-of-the-art baselines.

Establishment of a Multiplex RT-PCR Method for the Detection of Five Known Genotypes of Porcine Astroviruses.

Porcine astroviruses (PAstVs) are prevalent in pigs worldwide, and five genotypes have been reported to circulate in China. However, little is known about the coinfection status of PAstVs. For differential and simultaneous diagnoses of these five genotypes of PAstVs, a multiplex RT-PCR method was established on the basis of the ORF2 gene of type 1 PAstV, and the ORF1ab genes of type two to five PAstVs. This quintuple PCR system was developed through optimization of multiplex PCR and detection sensitivity and specificity. The results showed that this multiplex RT-PCR method could specifically detect all the five PAstV genotypes without cross-reaction to any other major viruses circulating in Chinese pig farms. The detection limit of this method was as low as 10 pg of standard plasmids of each PAstV genotype. In addition, a total of 275 fecal samples collected from different districts of Guangxi, China, between April 2019 and November 2020, were tested by this newly established multiplex RT-PCR. Moreover, the sensitivity and specificity of monoplex and multiplex RT-PCR methods were compared by detecting the same set of clinical positive samples. The results revealed that PAstV1 (31/275), PAstV2 (49/275), PAstV3 (36/275), PAstV4 (41/275), and PAstV5 (22/275) were all detected, and dual (PAstV1+PAstV2, PAstV1+PAstV3, PAstV2+PAstV3, PAstV2+PAstV4, PAstV3+PAstV4, and PAstV4+PAstV5) or triple genotypes (PAstV1+PAstV2+PAstV3 and PAstV2+PAstV3+PAstV4) of coinfections were also unveiled in this study. The detection result of multiplex PCR was consistent with that of monoplex PCR. Compared with monoplex PCR, this multiplex PCR method showed obvious advantages such as time and cost efficiency and high sensitivity and specificity. This multiplex RT-PCR method offered a valuable tool for the rapid and accurate detection of PAstV genotypes circulating in pig herds and will facilitate the surveillance of PAstV coinfection status.

Epidemiological Survey of Mycoplasma bovis in Yaks on the Qinghai Tibetan Plateau, China.

Mycoplasma bovis (M. bovis) is one of the most important pneumonia pathogens in yaks. It may result in more economic losses due to the cold and anoxia condition at Qinghai Tibetan plateau. However, to date, limited information on M. bovis infection in yaks is available in China. For this purpose, the seroprevalence of M. bovis was investigated in yaks living in the mentioned area through commercial ELISA kits. A total of 959 yaks were incorporated into this study. The prevalence of the disease in yaks was 48.70%. The serological results revealed a relatively high prevalence of M. bovis infection in yaks. The present study may greatly contribute to the prevention of this disease. More importance should be given to the potential threat caused by M. bovis in the special plateau.

CAME: Content- and Context-Aware Music Embedding for Recommendation.

Traditional recommendation methods suffer from limited performance, which can be addressed by incorporating abundant auxiliary/side information. This article focuses on a personalized music recommender system that incorporates rich content and context data in a unified and adaptive way to address the abovementioned problems. The content information includes music textual content, such as metadata, tags, and lyrics, and the context data incorporate users' behaviors, including music listening records, music playing sequences, and sessions. Specifically, a heterogeneous information network (HIN) is first presented to incorporate different kinds of content and context data. Then, a novel method called content- and context-aware music embedding (CAME) is proposed to obtain the low-dimension dense real-valued feature representations (embeddings) of music pieces from HIN. Especially, one music piece generally highlights different aspects when interacting with various neighbors, and it should have different representations separately. CAME seamlessly combines deep learning techniques, including convolutional neural networks and attention mechanisms, with the embedding model to capture the intrinsic features of music pieces as well as their dynamic relevance and interactions adaptively. Finally, we further infer users' general musical preferences as well as their contextual preferences for music and propose a content- and context-aware music recommendation method. Comprehensive experiments as well as quantitative and qualitative evaluations have been performed on real-world music data sets, and the results show that the proposed recommendation approach outperforms state-of-the-art baselines and is able to handle sparse data effectively.

Isolation, identification and biological characteristics of Mycoplasma bovis in yaks.

Mycoplasma bovis (M. bovis) is one of the important pathogens which may cause bovine respiratory disease syndrome (BRDS), and results in huge economic losses for yaks (Bos gaurus) breeding industry. However, there is limited information about M. bovis in yaks. In our study, 145 nasal mucus samples from yaks with pneumonia were collected to clarify. Bacteriological determination was carried out through biochemical identification and Polymerase Chain Reaction (PCR) detection. And ten strains of Mycoplasma bovis (M. bovis) were found from collected samples. Then, the growth curve of isolated strains was determined by the change of optical density (OD630), pH value and Color Change Cnit (CCU). K-B disk method was also used for antimicrobial susceptibility testing. Results of colony morphology and biochemical testing were consistent with the biological characters of M. bovis. The nucleotide sequences of uvrC specific gene and 16S rRNA gene among the 10 strains were highly homologous. The growth curve assay showed that the isolates cultured in PPLO medium were in lag phase for 24 h, entered stable period in 42 h, and entered decline phase after 78 h. The isolates were found resistant to macrolides, aminoglycosides and lincomycin at various degrees, but they were sensitive or moderately sensitive to doxycycline and kanamycin under antimicrobial susceptibility analysis. In conclusion, the results provided certain reference for the follow-up research and guiding for the treatment of M. bovis in yaks.

A Recommendation System to Facilitate Business Process Modeling.

This paper presents a system that utilizes process recommendation technology to help design new business processes from scratch in an efficient and accurate way. The proposed system consists of two phases: 1) offline mining and 2) online recommendation. At the first phase, it mines relations among activity nodes from existing processes in repository, and then stores the extracted relations as patterns in a database. At the second phase, it compares the new process under construction with the premined patterns, and recommends proper activity nodes of the most matching patterns to help build a new process. Specifically, there are three different online recommendation strategies in this system. Experiments on both real and synthetic datasets are conducted to compare the proposed approaches with the other state-of-the-art ones, and the results show that the proposed approaches outperform them in terms of accuracy and efficiency.

[DNA extraction from bones and teeth using AutoMate Express forensic DNA extraction system].

OBJECTIVE: To explore a new method in order to extract DNA from bones and teeth automatically. METHODS: Samples of 33 bones and 15 teeth were acquired by freeze-mill method and manual method, respectively. DNA materials were extracted and quantified from the triturated samples by AutoMate Express forensic DNA extraction system. RESULTS: DNA extraction from bones and teeth were completed in 3 hours using the AutoMate Express forensic DNA extraction system. There was no statistical difference between the two methods in the DNA concentration of bones. Both bones and teeth got the good STR typing by freeze-mill method, and the DNA concentration of teeth was higher than those by manual method. CONCLUSION: AutoMate Express forensic DNA extraction system is a new method to extract DNA from bones and teeth, which can be applied in forensic practice.