In recent years, there have been many new global companies investing and operating in Vietnam as a form of sharing economy (Uber, Grab, Foody, Agoda, Facebook, Google) These kinds of economy models are popular in the world but very new in Vietnam. Sharing economy enterprises bring both benefit and challenges for Vietnam. Before time, there is no policy and law to govern the activities of these companies. So they make the challenges for the authority of Vietnam to manage. This paper will analyze the nature, characters, and impact of the sharing economy in Vietnam. It also mentions the problems and recommends some solutions to manage activities of sharing - economy company

Little is known about how individual virus lineages replicating during acute Human Immunodeficiency Virus or Simian Immunodeficiency Virus (HIV/SIV) infection persist into chronic infection. In this study, we use molecularly barcoded SIV (SIVmac239M) to track distinct viral lineages for 12 weeks after intravenous and intrarectal challenge in macaques. Two Mafa-A1*063+ cynomolgus macaques (Macaca fascicularis) were challenged intravenously (IV), and two Mamu-A1*001+ rhesus macaques (Macaca mulatta) were challenged intrarectally (IR) with 200,000 Infectious Units (IU) of SIVmac239M. We deep sequenced the molecular barcode from all animals over 12 weeks to characterize the diversity and persistence of virus lineages, as well as the sequences of T cell epitopes during acute SIV infection. During the first three weeks post-infection, we found ~175-950 times more unique virus lineages circulating in the animals challenged intravenously than those challenged intrarectally, suggesting that challenge route is the primary driver restricting the transmission of individual viral lineages. Additionally, the emergence of escape variants can occur on multiple virus templates simultaneously, but elimination of some templates is likely a consequence of additional host factors. These data imply that virus lineages present during acute infection can be eliminated from the virus population even after initial T cell selection.

Background: South Africa’s public healthcare sector is overburdened, especially its under-resourced primary healthcare delivery system. This burden could be relieved by alleviating the population’s ill-health, focusing on the social determinants of health. These include living conditions and levels of social cohesion. In an attempt to address the aforementioned ‘challenge landscape’, this article considers socio-economic empowerment of those marginalised members of society living at the base of the pyramid (BOP) to improve factors contributing to poor health. We propose that Innovation Platforms (IPs) offer opportunities to achieve this by drawing diverse stakeholders together, which should include marginalised individuals, to pool resources and knowledge and collaborate around a specific set of challenges. Method: A Grounded Theory approach is utilised to develop the framework comprising concept definition from a systemized literature review. It is evaluated through various progressive stages through three phases of evaluation: 1) the initial framework was subjected to scrutiny in a theoretical case study, 2) a first-pass semi-structured interview and later four more semi-structured interviews with subject matter experts, and 3) an instrumental case study to refine the framework and to understand its application in a particular situation (this included four stakeholder interviews and a workshop and feedback session with the project champion). Results: This article contributes to the extant literature by addressing the lack of guidance on stakeholder engagement practices critical to the proper functioning of IPs in the context of overcoming the complex challenges associated with social determinants of health. The final output of the study is a refined management tool for stakeholder engagement in IPs. The tool provides practical recommendations to support policy makers, researchers and practitioners in 1) establishing IPs, 2) identifying areas for improvement and 3) identifying reasons for an IP’s failure and lessons to learn.

The global trend towards increased demand for organic food, greener environments, and the integration of biological control agents into pest management strategies has greatly enhanced the need for biological pesticides (biopesticides). Biopesticides are generally environmentally friendly and are made from micro-organisms or other natural substances. Despite their great potential, relatively few have been registered and commercialised in Nigeria compared to other African countries such as South Africa and Kenya. Biological active agents are so diverse such that ap-plying the same safety standards or environmental conditions to all of them is almost impossible. A review of risk assessment processes and comparative assessments of Nigeria's biopesticide regulations with other developing African countries and developed regions was conducted. Prolonged field testing, lack of bridged risk assessments and technical checklists have been identified as key factors hampering the timely development and commercialisation of biopesti-cides in Nigeria. Recommendations on necessary changes to the existing Nigeria biopesticide regulations have been made. Risk assessment matrices for microbial and biochemical biopesti-cides and a scientific/technical checklist have also been developed. Harmonisation and data ex-change among other countries in the region will also enhance the advancement of scientific and technical knowledge for sustainable regulation and cross-border trade.

This review paper aimed at reviewing English language teaching articles on EFL teachers’ perceptions, practices and challenges towards communicative language teaching. In this review, two ELT articles, which have been conducted on teachers’ perceptions, practices and challenges towards communicative language teaching in EFL classes, were reviewed in detail. While reviewing the articles, the researcher adapted Rideley’s (2008) checklist to evaluate elements of article. Thus, articles were reviewed by focusing on the title, abstract, introduction, research questions, objectives, research design, participants, sample and sampling techniques, data collecting instruments, methods of data analyses, findings and references based on the checklist provided above. The review revealed that the articles had clear objectives, researchable questions, appropriate methods and inevitable conclusions. They tried to answer the questions which were raised in each article, and the objectives went along with the overall research findings. The review, on the other hand, revealed that the participants in the articles were not representative so as to conclude and generalize the overall population by taking only few participants which were selected even by using non probability sampling.

Deforestation and forest degradation mostly caused by human interventions affects the capacity of forest ecosystem to provide ecosystem services and livelihood benefits. Forest Land Restoration (FLR) is an emerging concept which focuses on the improvement of ecosystem as well as livelihood of the people at the landscape level. Nepal has successfully recovered degraded forest land mainly from the hilly region through forest restoration initiatives especially community based forestry. However, the Terai region is still experiencing deforestation and forest degradation. This study navigated the gaps related to forest restoration in the existing policies and practices and revealed that the persistence of deforestation and forest degradation in Terai is a result of a complex socio-economic structure, limitation of government to implement appropriate management modality, unplanned infrastructure, and urban development. We suggest that forest restoration should focus on ecological and social wellbeing pathways at the landscape level, to reverse the trend of deforestation and forest degradation in the Terai regions of Nepal. The study provides a critical insight to the policy makers and practitioners of Nepal and other countries (with similar context) who are engaged in forest/ecosystem restoration enterprise.

Avian infectious bronchitis virus (IBV) is the causative agent of infectious bronchitis, which causes considerable economic losses to the poultry industry worldwide. It is imperative to develop safe and efficient candidate vaccines to control IBV infection. In the current study, recombinant baculoviruses co-expressing S1 and N proteins, mono-expressing S1 or N proteins alone of IBV were constructed and prepared into subunit vaccines rHBM-S1-N, rHBM-S1 and rHBM-N. The levels of immune protection of these subunit vaccines were evaluated by inoculating specific pathogen-free (SPF) chickens at 14 days of age, boosting with the same dose 14 days later, and following challenge with a virulent GX-YL5 strain of IBV 14 days post-booster (dpb). The commercial vaccine strain H120 was used as a control. The IBV-specific antibody levels as well as the percentages of CD4+ and CD8+ T lymphocytes were detected within 28 days post-vaccination (dpv). The morbidity, mortality, and re-isolation of virus from the tracheas and kidneys of challenged birds were evaluated at 5 days post-challenge (dpc). The results showed that the IBV-specific antibody levels and the percentages of CD4+ and CD8+ T lymphocyte in rHBM-S1-N group were higher than those of rHBM-S1 and rHBM-N groups, especially the cellular immunity response. At 5 dpc, the mortality, morbidity and virus re-isolation rate of rHBM-S1-N were slightly higher than those of H120 group, but were lower than those of rHBM-S1 group and rHBM-N group. The present study demonstrated that the protection of recombinant baculovirus co-expressing S1 and N proteins was better than that of recombinant baculoviruses mono-expressing S1 or N protein alone. Thus, the recombinant baculovirus co-expressing S1 and N proteins could serve as a potential IBV vaccine and this demonstrates that the bivalent subunit vaccine including the S1 and N proteins might be a strategy for the development of an IBV subunit vaccine.

COVID-19 has become a part of everyone's day-to-day life, since the outbreak in 2019 the novel coronavirus disease (COVID-19) has caused more than 4.5 million deaths with over 200 million cases reported globally. Currently, the number of infections and deaths are gradually lowering in different countries however the underlying challenges still exist. COVID-19 threatens human life, social functioning and development. Although numerous studies have been carried out in the past to highlight the key challenges very limited studies have been conducted from an ordinary person's viewpoint. In the fight against COVID-19, humanity has been pushed to a level which cannot be accepted where establishing that balance is a priority. This study focuses on highlighting the common issues faced by the ordinary public in the current era. Five key areas were identified to be the most essential; education, technological adaptation, transportation, mental health and gender-based violence (GBV).

This study contributes to the literature by exploring challenges to implementing ISO 20000-1 in an emerging economy context, and suggests ways to overcome these challenges. A survey-based methodology was adopted. The data were analyzed using principal component analysis. The results indicated that senior management support was the most significant challenge for the successful implementation of IT Service Management (ITSM) systems. Other significant challenges were the justification of significant investment, premium customer support, co-operation and co-ordination among IT support teams, proper documentation, and effective process design The findings help managers introduce IT service management system (ISO 20000-1:2011) as well as improving IT service delivery system in IT support organizations for managing big data in an emerging economy. In the future, cross-firm and cross-country studies on challenges to ISO 20000 can be conducted. Also, interpretive structural model (ISM) can be formulated to examine the interrelationships among the identified challenges to ISO 20000.

Rift Valley Fever virus (RVFV) is a zoonotic arbovirus of the Phenuiviridae family. Infection causes abortions in pregnant animals, high mortality in neonate animals and mild to severe symptoms in both people and animals. There is currently an ongoing effort to produce safe and efficacious veterinary vaccines against RVFV in livestock to protect against both primary infection in animals and zoonotic infections in people. To test the efficacy of these vaccines it is essential to have a reliable challenge model in relevant target species, including ruminants. We evaluated two goats breeds (Nubian and LaMancha), three routes of inoculation (intranasal, mosquito-primed subcutaneous and subcutaneous) using an infectious dose of 10⁷ pfu/ml, a virus strain from the 2006-07 Kenyan/Sudan outbreak and compared the effect of using virus stocks produced in either mammalian or mosquito cells. Our results demonstrated that Nubian goats achieved the highest levels and longer duration of viremia. In the Nubian goats, all three routes of inoculation were equally efficient at producing clinical signs, consistent viremia (peak viremia: 1.2x10³ - 1.0x10⁵ pfu/ml serum), nasal and oral shedding of viral RNA (1.5x10¹ – 8x10⁶ genome copies/swab), a systemic infection of tissues, and robust antibody responses. The Nubian goat breed and a needle-free intranasal inoculation technique could both be utilized in future vaccine and challenge studies.

In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained 6 key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

The presented research faces the problem of early detection of sepsis for patients in the Intensive Care Unit. The PhysioNet/Computing in Cardiology Challenge 2019 facilitated the development of automated, open-source algorithms for the early detection of sepsis from clinical data. A labeled clinical records dataset for training and verification of the algorithms was provided by the challenge organizers. However, a relatively small number of records with sepsis, supported by Sepsis-3 clinical criteria, led to highly unbalanced dataset (only 2% records with sepsis label). A high number of unbalanced data records is a great challenge for machine learning model training and is not suitable for training classical classifiers. To address these issues, a number of various models were investigated. A solution including feature selection and data balancing techniques was proposed in this paper. In addition, several performance metrics were investigated. Results show, that for successful prediction, a particular model having few or more predictors based on the length of stay in the Intensive Care Unit should be applied.

Many agonists for the estrogen receptor are known to disrupt endocrine functioning. We have developed a computational model that predicts agonists for the estrogen receptor ligand-binding domain in an assay system. Our model was entered into the Tox21 Data Challenge 2014, a computational toxicology competition organized by the National Center for Advancing Translational Sciences. This competition aims to find high-performance predictive models for various adverse-outcome pathways, including the estrogen receptor. Our predictive model, which is based on the random forest method, delivered the best performance in its competition category. In the current study, the predictive performance of the random forest models was improved by strictly adjusting the hyperparameters to avoid overfitting. The random forest models were optimized from 4,000 descriptors simultaneously applied to 10,000 activity assay results for the estrogen receptor ligand-binding domain, which have been measured and compiled by Tox21. At this time, our model delivers the highest predictive power on estrogen receptor agonists in the world. Furthermore, analysis of the optimized model revealed some important features of the agonists, such as the number of hydroxyl groups in the molecules.

This study measures the communication ability of wineries in two extreme territories of Southern Italy, Mount Etna and the island of Pantelleria. The evaluation of four dimensions of web communication was carried out by the AGIL Scheme (i.e. adaptation, goal-attainment, integration, latent pattern maintenance). The study provides a generalizable model to be applied in other similar studies. Also, focus groups of experts were carried out. The method proved to be suitable to measure the communication effectiveness of wineries through websites. Extreme territories may add value to the wine, regardless of the brand. The heroic wines may become the symbol of these territories helping environmental safeguard and contrasting territory abandonment by rural communities. The findings highlight that effective communication of heroic viticulture may be used to reposition these wines and increase their competitive advantage in foreign markets. The study generates new ideas for reflection on new types of web communication.

Vaccination is one of the best approaches to control and eradicate foot-and-mouth disease (FMD). To achieve this goal, vaccines with inactivated FMD virus antigen in suitable adjuvants are being used in addition with other control measures. However, only a limited number of vaccine strains are commercially available which often have a restricted spectrum of activity against the different FMD virus strains in circulation. As a result, when new strains emerge, it is important to measure the efficacy of the current vaccine strains against these new variants. This is important for countries where FMD is endemic but also for countries that hold an FMD vaccine bank to be prepared for emergency vaccination. The emergence and spread of the O/ME-SA/Ind-2001 lineage of viruses posed a serious threat to countries which had OIE-endorsed FMD control plans and had not reported FMD for many years. In vitro vaccine matching results showed a poor match (r1-value <0.3) to the more widely used vaccine strain O Manisa and less protection in a challenge test. This paper describes the use of O3039 vaccine strain as an alternative either alone or in combination with the O Manisa vaccine strain with virulent challenge by a O/ME-SA/Ind-2001d sub-lineage virus from Algeria (O/ALG/3/2014). The experiment included challenge at 7 days post vaccination (to study protection and emergency use) and 21 days post vaccination (as would be done in standard potency studies). The results indicated that the O3039 vaccine strain alone as well as the combination with O Manisa is effective against this strain of the O/ME-SA/Ind/2001d lineage offering protection from clinical disease even after 7 days post vaccination and with reduction in viraemia and virus excretion.

This paper combines the Good Regulator Theorem with the Law of Requisite Variety and seven other requisites that are necessary and sufficient for a cybernetic regulator to be effective and ethical. The resulting Ethical Regulator Theorem provides a basis for systematically evaluating and improving the adequacy of existing or proposed designs for systems that make decisions that can have ethical consequences; regardless of whether the regulators are human, machines, cyberanthropic hybrids, organizations, corporations, or government institutions. The theorem is then used to define an ethical design process that has potentially far-reaching implications for society. A six-level framework is proposed for classifying cybernetic and superintelligent systems, which highlights the existence of a possibility-space bifurcation in our future time-line. The implementation of “super-ethical” systems is identified as an urgent imperative for humanity to avoid the danger that superintelligent machines might lead to a technological dystopia. Third-order cybernetics is defined as the cybernetics of ethical systems. Concrete actions, a grand challenge, and a vision of a super-ethical society are proposed to help steer the future of the human race and our wonderful planet towards a realistically achievable minimum viable cyberanthropic utopia.

Health information technology has been widely used in healthcare, which has contributed a huge amount of data. Health data has four characteristics: high volume; high velocity; high variety and high value. Thus, they can be leveraged to i) discover associations between genes, diseases and drugs to implement precision medicine; ii) predict diseases and identify their corresponding causal factors to prevent or control the diseases at an earlier time; iii) learn risk factors related to clinical outcomes (e.g., patients’ unplanned readmission), to improve care quality and reduce healthcare expenditure; and iv) discover care coordination patterns representing good practice in the implementation of collaborative patient-centered care. At the same time, there are major challenges existing in data-driven healthcare research, which include: i) inefficient health data exchanges across different sources; ii) learned knowledge is biased to specific institution; iii) inefficient strategies to evaluate plausibility of the learned patterns and v) incorrect interpretation and translation of the learned patterns. In this paper, we review various types of health data, discuss opportunities and challenges existing in the data-driven healthcare research, provide solutions to solve the challenges, and state the important role of the data-driven healthcare research in the establishment of smart healthcare system.