Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HST-OFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-­interference-­plus-­noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the non-stationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HST-OFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs

Performance Investigation of High-Speed Train OFDM Systems under the Geometry-Based Channel Model

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HST-OFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-­interference-­plus-­noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the non-stationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HST-OFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs

Bacteria associated with soft coral from Mot island - Nha Trang bay and their antimicrobial activities

Microbial communities associated with invertebrates had been considered as a new source of bioactive compounds. The soft coral associated bacteria in Mot island, Nha Trang bay were isolated, extracted and assessed for antagonistic activity against human and coral pathogens, the strongly active strains were identified by 16S rRNA analysis. The soft coral associated bacterium SCN10 had abcd antibacterial pattern which was named for inhibition towards Bacillus subtilis (pattern a), Escherichia coli (pattern b), Salmonella typhimurium (pattern c) and Serratia marcescens (pattern d). It was the nearest strain to the well-known antibiotic producer Bacillus amyloliquefaciens with 99% sequence similarity. Whereas strain SCL19 had abde pattern which means inhibition of the growth of B. subtilis, E. coli, S. marcescens and Vibrio parahaemolyticus (pattern e). This strain SCL19 affiliated with Bacillus sp. strain A-3-23B with 99.8% identity. In addition to antimicrobial activity to the aforementioned tested bacteria, the isolate SCX15 also inhibited Vibrio alginolyticus (pattern f) and Candida albicans (pattern g), so this isolate possessed abcdefg antimicrobial pattern. The coral associated isolate SCX15 was identified as Bacillus velezensis with 99% sequence similarity. Among the 78 screened strains, 25 isolates possessed antibacterial activity against at least one of seven tested microorganisms and exhibited 12 different types of antimicrobial activities, suggesting that they can produce many different natural substances with antibacterial activity

Improving the Quality of Teaching Physical Education Courses at Universities

This manuscript explores the advantages and limitations of teaching physical education courses at universities and proposes strategies to enhance the quality of teaching. The advantages of improving the quality of physical education teaching include flexible selection of sports subjects, enhancing positive attitudes towards learning, continuous development and improvement of lecturers, testing and evaluation standards, and innovative teaching methods. The limitations identified are limited curriculum content, teaching plans dependent on weather conditions, limited lecturer team, and lack of motivation among some students. To enhance the quality of teaching physical education, the manuscript proposes enhancing the role and significance of physical education in universities and adjusting and improving the content of the physical education program through innovative teaching methods, such as introducing new elective subjects, adapting teaching content and methods to student needs, and promoting interdisciplinary collaboration between departments

Biomimetic Superhydrophobic Materials for Environmental Applications

Environmental pollution has been one of the people’s most significant concerns for decades. In today’s industrialized and modernized society, the problem of environmental pollution has become more and more serious, directly affecting the sustainable development of each country. The unique surface properties of materials and interfaces produced by biomimetic approaches can be leveraged to create practical solutions to challenging environmental issues. Among them, superhydrophobic materials get a lot of attention because of their exceptional capacities in various environmental applications such as oil-water separation, membrane-based water purification and desalination, biofouling prevention, high-performance vapor condensation, and atmospheric water capture. This chapter reviews and discusses the fundamental principles of superhydrophobicity, recent works in preparing superhydrophobic surfaces, their potential environmental applications, and the challenges confronted in their new applications

Genetic Diversity and Population Structure of Canarium tramdenum Dai and Yakovl. in Northern Vietnam

Canarium tramdenum occurs naturally in subtropical and tropical regions of Indochina and China. The wood is used for making high quality furniture and the fruit and leaves are used in traditional medicine. However, a lack of information on genetic diversity and population structure has handicapped the genetic conservation and domestication of this high-value species. This study evaluated genetic variation within and among four C. tramdenum populations. Sixty individuals were collected from four natural populations in Vietnam in the provinces of Ninhbinh, Bacgiang, Nghean, and Backan. Genetic diversity and genetic structure were determined using 20 ISSR markers. A total of 192 DNA fragments with sizes ranging from 110 bp to 3,000 bp were detected, of which 154 segments (80.2%) were polymorphic and 38 segments (19.8%) were monomorphic. The ISSR data indicated a moderate degree of genetic diversity for the species (h = 0.252). The four populations were separated into three genetic clusters with low levels of genetic distance between them. AMOVA result showed that most (78%) of the genetic variation was within the populations. The moderate to high genetic diversity of C. tramdenum and the low genetic differentiation among populations suggested that all existing natural populations in the particular regions needed to be preserved to protect the genetic diversity of this species

Dynamic Relationship among Effective Supply Chain Practices, Income, Exchange Rate, Foreign Direct Investment, and Export Performance

This study has an effort to explore the dynamic relationship among income, exchange rate, foreign direct investment, effective supply chain practices and export performance. Based on quarterly data from Q2/2009 to Q4/2019, constituting 43 observations. To attain dynamic and unvarying relationship among these variables, applying Vector Autoregressive Model, results indicate that, in short run, each variable is highly influenced by changes of value and past value of its and the other variables at different degree. In addition, there does not exist a long run association among exchange rate, income, foreign direct investment and export in Vietnam in the research period

Bridging Cultures in Academia: The Role of Mindfulness in Enhancing Intercultural Communication and Social Capital among Scholars

Studies that comprehensively incorporate mindfulness therapies and the theory of intercultural communication into the investigation of social capital are lacking in the body of existing literature. This restricts our comprehension of how these important components interact and affect social relationships in academic communities as a whole. Therefore, the purpose of this study is to investigate how mindfulness practices affect cross-cultural communication and, in turn, build social capital in academic environments. A mixed method was adopted in the study. In the first stage, focused group interviews are employed in the first stage with seven groups of nine Australian alumni, for a total of 63 participants who have experience conducting research and teaching abroad or in multicultural settings. In the second stage, 149 alumni were surveyed, and Process Macro SPSS\u27s Hayes model was used to analyse the data. The results showed that those who practice mindfulness are more likely to approach cross-cultural encounters with a greater awareness of and respect for different points of view. According to the findings, mindfulness can be a potent instrument for boosting perception of the community, networking, trust and safety, scholarly participation, citizen power, life values and diverse perspectives among academics. Scholars who engage in mindfulness practices have the potential to cultivate closer ties within academic communities, which could result in joint research opportunities, information exchanges, and career assistance. This study might offer academics a fresh theoretical viewpoint that improves the conceptual frameworks for mindfulness practice for enhancing academic social capital via intercultural communication

Carotenoid producing Bacillus aquimaris found in chicken gastrointestinal tracts

Pigmented spore-forming bacterial strains were isolated from the gastrointestinal tracts of chickens for screening for heat-stable carotenoid-producing strains that could be applied as feed supplements. Of the seven heat-stable pigmented isolates screened, only two, yellow Sporosarcina saromensis CH1 and red-orange Bacillus aquimaris CH9, produced pigments with typical carotenoid absorbance peaks (400–500 nm). The CH9 carotenoids exhibited higher scavenging activity (73.2%) of DPPH free radicals than the CH1 carotenoids (35.9%) and carotenoids of the reference B. indicus HU36 strain (78.4%), in comparison to 100% activity of acid ascorbic at 18.75 M as the standard. The CH9 strain produced high levels of carotenoids (439 g [g DW]-1) and formed nearly 100% spores, whereas the CH1 strain produced low levels of carotenoids (92 g [g DW]-1) and only achieved 30% sporulation. Chromatographic and spectral profiles of the carotenoids found in CH9 indicated the presence of as many as 11 different carotenoid types closely related to 1-HO-demethylspheroidene and keto/hydroxyl derivatives of carotene. We successfully produced concentrated orange CH9 spore powder at a high concentration of 6.1 × 1011 CFU g-1; these spores were much more heat-stable (66% survival at 80°C for 20 min) than the reference B. indicus HU36 spores (9% survival at 50°C for 20 min). In conclusion, B. aquimaris CH9 is a promising probiotic carotenoid-producing strain, with heat-stable spores that should withstand the heat-treatment processing required for feed and food supplement production

Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks

Federated Learning (FL) has recently become an effective approach for cyberattack detection systems, especially in Internet-of-Things (IoT) networks. By distributing the learning process across IoT gateways, FL can improve learning efficiency, reduce communication overheads and enhance privacy for cyberattack detection systems. Challenges in implementation of FL in such systems include unavailability of labeled data and dissimilarity of data features in different IoT networks. In this paper, we propose a novel collaborative learning framework that leverages Transfer Learning (TL) to overcome these challenges. Particularly, we develop a novel collaborative learning approach that enables a target network with unlabeled data to effectively and quickly learn knowledge from a source network that possesses abundant labeled data. It is important that the state-of-the-art studies require the participated datasets of networks to have the same features, thus limiting the efficiency, flexibility as well as scalability of intrusion detection systems. However, our proposed framework can address these problems by exchanging the learning knowledge among various deep learning models, even when their datasets have different features. Extensive experiments on recent real-world cybersecurity datasets show that the proposed framework can improve more than 40% as compared to the state-of-the-art deep learning based approaches.Comment: 12 page