Hepatitis A virus – a general overview

Hepatitis A virus infection occurs globally and is causing a public health concern, primarily in developing countries due to its persistent circulation in the environment. The improved sanitary condition and increase in awareness of personal hygiene have led to the marked reduction of HAV prevalence in industrialized countries during childhood and to a shift of the infection towards adulthood. HAV is an environmentally stable, positive single stranded RNA virus that is primarily transmitted by the fecal-oral route, person to person contact or ingestion of contaminated food and drink. One of the main causes leading to HAV infection is epidemiologically linked to the consumption of raw or undercooked shellfish particularly oysters and clams. Due to their filter-feeding style, these shellfishes readily concentrate viruses from the surrounding water containing municipal sewage, and as a consequence pose a health threat to consumers. Therefore, development of detection techniques possessing the requisite sensitivity and specificity for the practical routine monitoring purposes is of great importance necessary for the protection of shellfish-consuming public. Nucleic acid based method such as reverse transcription PCR has emerged as the popular method of choice in view of its rapidity, accuracy and sensitivity in contrary of the time-consuming conventional cell culture and hybridization techniques. However, detection of hepatitis A virus is firstly hampered by the non-cytophatic effect of wild type HAV strain, secondly, the low concentration of viral genome present in the environmental sample which requires effective isolation and concentration of virions and lastly the labor-extensive purification and thorough removal of the abundance of the PCR inhibitors which will unfavorably reduce the efficiency of PCR detection

Editorial Introduction: Urban-Rural Regeneration and Cultural Sustainability

In the current rapid urbanization view of most countries in the world, it is important to pay attention to legislation and policy development, the improvement of adequate infrastructure and basic services, urban planning and design. This will create an inclusive, tough, prosperous economic environment and maximize the benefits of agglomeration. Sustainable urban rural development remains one of the most pressing global challenges of the twenty-first century. Central and local governments and their partners should pay greater attention to one another and work together to build on a more harmonious, fair, inclusive and environmentally sustainable planned environment at the urban-rural scale. According to the UN-HABITAT Global Activity Report 2015, the world has experienced rapid urbanization. In 2008, the urban population exceeded the rural population. By 2050, it is expected that two thirds of the world's population will live in urban areas. With more than half of humanity living in cities, it is estimated that urban areas account for 70% of the world's gross domestic product and therefore have led to economic growth and prosperity (UN-HABITAT, 2015)

Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories

Human action recognition (HAR) is at the core of human-computer interaction and video scene understanding. However, achieving effective HAR in an unconstrained environment is still a challenging task. To that end, trajectory-based video representations are currently widely used. Despite the promising levels of effectiveness achieved by these approaches, problems regarding computational complexity and the presence of redundant trajectories still need to be addressed in a satisfactory way. In this paper, we propose a method for trajectory rejection, reducing the number of redundant trajectories without degrading the effectiveness of HAR. Furthermore, to realize efficient optical flow estimation prior to trajectory extraction, we integrate a method for dynamic frame skipping. Experiments with four publicly available human action datasets show that the proposed approach outperforms state-of-the-art HAR approaches in terms of effectiveness, while simultaneously mitigating the computational complexity

On the Estimation of the Mission Performance Index of Unmanned Surface Vehicles Based on the Mission Coverage Area

For mission planning and replanning of multiple unmanned surface vehicles (USVs), it is important to estimate each USV’s mission performance in terms of sea surveillance (e.g., illegal ship control). In this study, a mission performance index (MPI) is proposed based on the mission coverage area for estimating the USVs’ mission performance of illegal ship control. The penalty value is considered in the MPI calculation procedure owing to the track-off of the USV. In addition, the USV simulation is conducted under illegal ship control, and the MPI is calculated based on changing the mission coverage area. The results show that the MPI increases with the path width of the mission coverage area