Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs

Background: MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Results: Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable, performing well when using both experimentally validated and predicted miRNA-target gene interaction data for network construction. Finally, using RWRMTN, we identified 76 novel miRNAs associated with 23 disease phenotypes which were present in a recent database of known disease-miRNA associations. Conclusions: Summarizing, using random walks on mutual miRNA-target networks improves the prediction of novel disease-associated miRNAs because of the existence of "disease modules" in these networks

Towards Autoencoding Variational Inference for Aspect-based Opinion Summary

Aspect-based Opinion Summary (AOS), consisting of aspect discovery and sentiment classification steps, has recently been emerging as one of the most crucial data mining tasks in e-commerce systems. Along this direction, the LDA-based model is considered as a notably suitable approach, since this model offers both topic modeling and sentiment classification. However, unlike traditional topic modeling, in the context of aspect discovery it is often required some initial seed words, whose prior knowledge is not easy to be incorporated into LDA models. Moreover, LDA approaches rely on sampling methods, which need to load the whole corpus into memory, making them hardly scalable. In this research, we study an alternative approach for AOS problem, based on Autoencoding Variational Inference (AVI). Firstly, we introduce the Autoencoding Variational Inference for Aspect Discovery (AVIAD) model, which extends the previous work of Autoencoding Variational Inference for Topic Models (AVITM) to embed prior knowledge of seed words. This work includes enhancement of the previous AVI architecture and also modification of the loss function. Ultimately, we present the Autoencoding Variational Inference for Joint Sentiment/Topic (AVIJST) model. In this model, we substantially extend the AVI model to support the JST model, which performs topic modeling for corresponding sentiment. The experimental results show that our proposed models enjoy higher topic coherent, faster convergence time and better accuracy on sentiment classification, as compared to their LDA-based counterparts.Comment: 20 pages, 11 figure

Revisiting the Approaches for Exploring Students’ Drive in Japanese Studies

Japanese Studies undergraduate programs offer students an engaging curriculum that provides a deep understanding of the Japanese language and culture. A degree in Japanese Studies equips students with valuable skills that are relevant in various fields, making it a popular choice worldwide. College students’ motivation is a critical factor in academic success and has been extensively studied in education. The paper aims to review the existing theories related to study motivation, language acquisition, study abroad drives, and motivation, then to consider the approaches and details that we could prioritize for investigating the motivations and drives of students majoring and minoring in Japanese Studies in universities

Creating Fatigue Curve for Steel Machine Elements Using Fatigue Test Method with Gradually Increasing Stress Amplitude

In order to create a fatigue curve, the traditional fatigue test method is applied to specimens using a cyclic stress with constant amplitude. However, this method has disadvantages such as the experimental results could not be used because of specimens broken before reaching the expected stress amplitude, or the tests may be stopped before specimen broken because of limitation of time. To overcome this hurdle of the traditional method, a new experimental method using cyclic stress with gradually increasing amplitude was proposed to build the fatigue curve for steel machine elements

Study design for the 2016 baseline survey of a health system strengthening project in Quoc Oai District, Hanoi, Vietnam

Background: In order to provide essential scientific evidence on the population's health status and social health determinants as well as the current capacity of the health care system in Vietnam to health policy makers and managers, Vietnam Ministry of Health, Hanoi University of Public Health, Hanoi Medical University, and Ho Chi Minh University of Medicine and Pharmacy collaborated with Seoul National University (Korea) and conducted a health system survey in the Quoc Oai district (of Hanoi capital) that represented northern rural Vietnam. Methods: The study design was a cross-sectional study. The survey covered different topics (more than 200 questions) and was administered in three separate questionnaires: 1) Basic information of all household members; 2) Household characteristics; and 3) Individual characteristics. Socio-demographic characteristics among the households and individuals were collected from 2,400 households sampled by multi-stage cluster sampling method: more than 200 questions. Results: The household size of Quoc Oai was larger than the national average and there was no significant difference in gender composition. In addition, the proportions of pre-elderly, age 55-64, and elderly group (65 years old and over) were higher than the national population statistics. In this context, demographic transition has begun in Quoc Oai. Conclusion: This study design description provides the basic information about a baseline survey of a future prospective cohort (as a part of a collaborative project on strengthening the health system in Vietnam) to the prospective data user of this survey. © 2019 The Korean Academy of Medical Sciences. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Huy Nguyen” is provided in this record*

A Method for Authentication Services in Wireless Networks

With the widespread use of wireless network services and applications, security is a major concern. From wireless network security aspects, authentication for services is very important especially in Internet banking. In this paper, an authentication method for wireless networks using dynamic key theory is presented. The dynamic key theory is used to produce “one time keys” for authentication. These one time keys will improve the efficiency and security of wireless authentication. It can be applied for Internet banking and services in wireless networks

ENGLISH-MAJORED STUDENTS' MOST COMMON CAREER OPTIONS AND THE LEVELS OF READINESS FOR THE CAREERS

EFL students nowadays have a variety of career options. Most of them, however, still do not have a well-understanding or a strong readiness for their job targets. This study was conducted to find out the EFL students’ most career options, some language standards when selecting careers and to what extent students feel that they are ready for their future careers. To answer these questions, we use exploratory questionnaires to survey the participants. The findings demonstrate that teaching English is the most attractive career that EFL students want to attend after graduating, followed by the freelancer. However, a group of students still cannot locate their future careers. Additionally, juniors and seniors are considered to have better preparation for their career prospects than freshmen and sophomores.  Article visualizations

STIRLING ENGINE: FROM DESIGN TO APPLICATION INTO PRACTICE AND EDUCATION

Stirling motor is a type of outside ignition heat motor that can utilize various fuel sources from customary structures (coal, oil, kindling, rice husk, and so forth) to sustainable power sources (sun-oriented energy), climate, squander heat usage, and so forth). The article centers around introducing the fundamental highlights of the improvement history, activity qualities, and plan techniques for certain sorts of Stirling motors, in this way offering useful appropriateness as well as a college preparing for understudies. The understudy studying Thermal Engineering in our nation today.  

Trends in socioeconomic inequalities in full vaccination coverage among vietnamese children aged 12–23 months, 2000–2014: Evidence for mitigating disparities in vaccination

There has been no report on the situation of socioeconomic inequalities in the full vaccination coverage among Vietnamese children. This study aims to assess the trends and changes in the socioeconomic inequalities in the full vaccination coverage among Vietnamese children aged 12–23 months from 2000 to 2014. Data were drawn from Multiple Indicator Cluster Surveys (2000, 2006, 2011, and 2014). Concentration index (CCI) and concentration curve (CC) were applied to quantify the degree of the socioeconomic inequalities in full immunization coverage. The prevalence of children fully receiving recommended vaccines was significantly improved during 2000–2014, yet, was still not being covered. The total CCI of full vaccination coverage gradually decreased from 2000 to 2014 (CCI: from 0.241 to 0.009). The CC increasingly became close to the equality line through the survey period, indicating the increasingly narrow gap in child full immunization amongst the poor and the rich. Vietnam witnessed a sharp decrease in socioeconomic inequality in the full vaccination coverage for over a decade. The next policies towards children from vulnerable populations (ethnic minority groups, living in rural areas, and having a mother with low education) belonging to lower socioeconomic groups may mitigate socioeconomic inequalities in full vaccination coverage. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Huy Nguyen” is provided in this record*