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Background: Due to its hollow stem, ensiling triticale presents a challenge as it may cause an overabundance of oxygen during the fermentation process. This study investigated the effects of Bacillus coagulans (BC) and Lactobacillus plantarum (LP) on the fermentation characteristics, microbial community, and aerobic stability of ensiled triticale. Fresh triticale was wilted at a dry matter content of 350 g/kg. The experiment was arranged in a 2 × 2 factorial design, with both BC and commercial LP added at 0 or 1 × 106 cfu/g of fresh weight (FW) of chopped triticale. Results: After 60 days of ensiling, the pH, water-soluble carbohydrates (WSC), neutral detergent fiber (NDF), and ammonia nitrogen (NH3-N) of inoculated groups were lower than those of the control group (P < 0.05), especially in the LP + BC treatment (P < 0.05). The lactic acid (LA) concentration, lactic acid/acetic acid (LA/AA), and aerobic stability were also higher (P < 0.05) in the LP + BC treatment than in other treatments. The bacterial diversity was reduced, and the richness was increased by the application of LP and BC individually (P < 0.05). Compared with the control silage, LP-treated silage had higher Lactobacillus (P < 0.05), while BC-treated silage had higher Bacillus and Pediococcus (P < 0.05). The LP + BC-treated silage had higher Lactobacillus, Bacillus, Enterococcus, and Serratia (P < 0.05). Bacillus was negatively correlated with NDF (P < 0.05) and AA (P < 0.05). Lactobacillus was positively correlated with LA (P < 0.05) and LA/AA but negatively with pH and NH3-N (P < 0.05). Conclusions: The combination of BC and LP may lead to improved ensiled triticale fermentation quality and aerobic stability by inducing alterations in the composition of bacterial communities, which is crucial for the efficient utilization of triticale resources. [ABSTRACT FROM AUTHOR]

As a key component of Transforming growth factor-β (TGF-β) pathway, Smad2 has many crucial roles in a variety of cellular processes, but it cannot bind DNA without complex formation with Smad4. In the present study, the molecular mechanism in the progress of myogenesis underlying transcriptional regulation of SMAD2 and SMAD4 had been clarified. The result showed the inhibition between SMAD2 and SMAD4, which promotes and inhibits bovine myoblast differentiation, respectively. Further, the characterization of promoter region of SMAD2 and SMAD4 was analyzed, and identified C/EBPβ directly bound to the core region of both SMAD2 and SMAD4 genes promoter and stimulated the transcriptional activity. However, C/EBPβ has lower expression in myoblasts which plays vital function in the transcriptional networks controlling adipogenesis, while the overexpression of C/EBPβ gene in myoblasts significantly increased SMAD2 and SMAD4 gene expression, induced the formation of lipid droplet in bovine myoblasts, and promoted the expression of adipogenesis-specific genes. Collectively, our results showed that C/EBPβ may play an important role in the trans-differentiation and dynamic equilibrium of myoblasts into adipocyte cells via promoting an increase in SMAD2 and SMAD4 gene levels. These results will provide an important basis for further understanding of the TGFβ pathway and C/EBPβ gene during myogenic differentiation. [ABSTRACT FROM AUTHOR]

This paper discusses the mining of key nodes from the flow of knowledge in science and technology journals to technology patents at the community level. The knowledge flow network is established with spatial dimensions based on technological patent citations, scientific journals, and cooperation among researchers. The extensity centrality-Newman and commonly used degree indices are applied to isolate the nodes which occupy important positions among communities in the knowledge flow network. Suggestions are proffered accordingly to make full use of the key nodes' roles as "bridges" to promote knowledge flow from science and technology journals to technology patents. [ABSTRACT FROM AUTHOR]

Promoting knowledge diffusion and reducing the delay between scientific research and technology patents is important to achieve success in the highly competitive global environment. This paper studies the time delay between scientific research and technology patents, and focuses on the key components of time in the promotion of knowledge transformation. Based on United States Patent and Trademark Office patent data, we apply periodical citation distribution models to the patent process. The results show that our transfer function model is better than others, and is suitable for calculating the delay between basic scientific research activities and technology patents. [ABSTRACT FROM AUTHOR]

Drawing upon the periodical publication delay model and the Weibull distribution model, we develop an improved model and conduct an exploratory analysis to characterize patent grant delay, and learn the crux of the problem. In order to test the effect of the new model, we perform an experiment based on a database of four technological fields from the United States Patent and Trademark Office. The results show that the new model can improve the fitting effect, and is suitable for calculating the time delay between patent application and grant. In addition, we apply the improved model in two different technological fields to study the changing rules in the last two decades by comparing the results, and obtain some valuable information. For a theoretical contribution, we deduce the examination probability under steady-state conditions, extend the periodical publication delay model from a negative exponential distribution to a Weibull distribution, and overcome the shortcomings of the original model. [ABSTRACT FROM AUTHOR]

Community structure is one of the important properties of social networks in general and in particular the citation networks in the field of scientometrics. A majority of existing methods are not proper for detecting communities in a directed network, and thus hinders their applications in the citation networks. In this paper, we provide a novel method which not only overcomes the above mentioned disability, but also has a relative low algorithm time complexity which facilitates the application in large scale networks. We use the concept of Shannon entropy to measure a network's information and then consider the process of detecting communities as a process of information loss. Based on this idea, we develop an optimal model to depict the process of detecting communities and further introduce the principle of dynamic programming to solve the model. A simulation test is also designed to examine the model's accuracy in discovering the community structure and identifying the optimal community number. Finally, we apply our method in a citation network from the journal Scientometrics and then provide several insights on promising research topics through the detected communities by our method. [ABSTRACT FROM AUTHOR]

This paper focuses on methods to study the distribution of an author's collaborative relationships among different communities in co-authorship networks. Based on the index of extensity centrality, we propose a new index and name it extensity centrality-Newman (Cext-N). Drawing upon a data set of three top journals (MISQ, ISR, JMIS) between 2010 and 2012 in Information Systems, we verify and describe the application and value of our approach. Due to the fact that the starting points among Cext-N and classical indices are quite different and a single index is not advocated in scientific evaluation, we can select the indices in actual application by considering their starting points to ensure the value of each index is taken into account. [ABSTRACT FROM AUTHOR]