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The rapid expansion of online commerce has significantly altered consumer behavior, particularly among digitally-savvy Generation Z individuals. This research analyzes the influence of product presentation videos on online impulsive buying behaviors in this demographic, using the Shopee video platform as a case study. The study aims to investigate how various external factors, including time pressure (TP), quantity pressure (QP), economic benefits (EB), social influence (SI), visual (VS), and sound (SO), affect online impulse buying by mediating emotions of arousal (AR) and pleasure (PL). This study employed a quantitative approach, and data was collected through a Likert scale questionnaire using a non-probability sampling technique. PLS-SEM statistical analysis was utilized to assess the research model, exploring the interplay of these stimuli in shaping impulsive buying behavior on the Shopee platform, among 438 Vietnamese Generation Z. The study's results indicate significant impacts of all factors on arousal, while time pressure, quantity pressure, and economic benefits did not significantly influence pleasure. Notably, arousal and pleasure emerged as mediators shaping impulsive buying decisions among Generation Z. These findings indicate that strategic use of external factors can effectively trigger emotions, leading to impulsive buying among digital natives. This also offers valuable insights for marketers looking to enhance e-commerce strategies on platforms such as Shopee video. Marketers can trigger customers' impulsive buying by creating a sense of urgency (e.g. flash sales, limited quantities), useful online reviewing, and personalizing discounts. Additionally, using visual and sound strategies in a positive online experience can further enhance this behavior and shape preferences. This study's findings contribute to a deeper understanding of consumer behavior theories in the digital era, highlighting the intricate roles of arousal and pleasure in online impulse buying.

The research investigates the effect of restaurant authenticity on perceived service quality, customer satisfaction, and electronic word of mouth (eWOM) in the context of ethnic restaurants. Additionally, it examines the mediating role of service quality and customer satisfaction, as well as their parallel mediating effect on the relationship between restaurant authenticity and diners’ eWOM intention. Data was collected from 279 diners who had experienced services at ethnic restaurants in Vietnam. The Partial Least Squares Structural Equation Modelling (PLS-SEM) approach was employed to investigate the relationships among the variables in the research model. The findings reveal that restaurant authenticity directly influences perceived service quality, customer satisfaction, and customers’ eWOM intention. Customer satisfaction fully mediates the relationship between service quality and eWOM, while it partially mediates the effect of restaurant authenticity on customer eWOM. However, the indirect impact of restaurant authenticity on customer eWOM through service quality was not significant. Ethnic restaurant managers should focus on enhancing the authenticity of their restaurants to generate positive outcomes such as increased customer satisfaction and eWOM intention. This study contributes to the existing literature on consumer behavior in the hospitality sector by conceptualizing the mediating role of service quality and customer satisfaction in the relationship between restaurant authenticity and eWOM intention. The research also extends the Stimuli Organism-Response model by considering restaurant authenticity as a stimulus that directly and indirectly influences service quality (stimulus), customer satisfaction (organism), and customer eWOM intention (response).

Environmental changes and human impact can alter biodiversity in negative manners that affect mankind’s sustainable development. Particularly, such effects on inland waters are even more concerning, as those ecosystems play essential roles in sustaining human life as well as relevant wildlife. Thus, in this study, we investigated such effects on microbial diversity in inland waters in Vietnam using bacterial communities in sediment as indicators. To do this, we collected sediment samples from various locations in three respective regions (Red river in the north, Ba river in the central area, and Mekong delta flood zone in the south) using standard methods, extracted their total DNA, sequenced their V3-V4 16S rRNA gene fragments using an Illumina Miseq platform and analyzed the sequences to infer the diversity of the bacterial communities in the samples. These communities were compared in terms of richness (alpha diversity) and composition (beta diversity), and the correlations between their diversity levels and environmental factors, as well as human activities, were analyzed by using standard statistical tools. Our results showed that the communities were different from each other solely by region, in richness and critically in composition, although there were some communities distinctively different from all the others. Among environmental factors, only water salinity (and conductivity) had negative correlations with alpha-diversity indices of the bacterial communities, and phosphate concentration and turbidity had positive correlations, while the other factors had almost no correlations, which partially explains the region-specific diversity. These results also suggest that climate change incidences, especially sea intrusion, can have significant effects on microbial diversity in inland waters. The impact of human activities did not appear severe, solely affecting bacterial community richness, but not significantly affecting bacterial community composition. However, apparently reduced bacterial diversity in several sites with intense human impacts and distinct environmental conditions should be noted and deserve further investigation.

In some settings, systems may not fail completely but instead undergo performance degradation, leading to reduced efficiency. A significant concern arises when a system transitions into a degraded state without immediate detection, with the degradation only becoming apparent after an unpredictable period. Undetected degradation can result in failures with significant consequences. For instance, a minor crack in an oil pipeline might go unnoticed, eventually leading to a major leak, environmental harm, and costly cleanup efforts. Similarly, in the nuclear industry, undetected degradation in reactor cooling systems could cause overheating and potentially catastrophic failure. This paper focuses on reliability modeling for systems experiencing degradation, accounting for time delays associated with undetected degraded states, self-repair mechanisms, and varying operating environments. The paper presents a reliability model for degraded, time-dependent systems, incorporating various aspects of degradation. It first discusses the model assumptions and formulation, followed by numerical results obtained from system modeling using the developed program. Various scenarios are illustrated, incorporating time delays and different parameter values. Through computational analysis of these complex systems, we observe that the probability of the system being in the undetected degraded state tends to stabilize shortly after the initial degradation begins. The model is valuable for predicting and establishing an upper bound on the probability of the undetected, degraded state and the system’s overall reliability. Finally, the paper outlines potential avenues for future research.

Introduction: Pharmacists serve an important role in rural communities, and in some cases they may be the only health professional available. Their recruitment and retention is a major concern for rural communities and health services; however, a deeper understanding regarding the advantages and challenges of sustaining a rural pharmacy workforce is somewhat limited. The aim of this study was to develop a deeper understanding of pharmacists' perspectives about factors influencing pharmacist recruitment and retention to rural and remote communities. Methods: The exploratory study, carried out in rural Tasmania and rural Western Victoria, used a qualitative descriptive design. Structured interviews, lasting between 30-60 minutes, were conducted by a single researcher using the Pharmacist Community Apgar Questionnaire via face-to-face, telephone or videoconferencing technology. Data were analysed thematically using verbatim transcription, extraction of significant statements and identification of similarities in formulated meanings, grouping the similar meanings and significant statements that pertained to the phenomena of interest. Specifically, qualitative data were used to provide a deeper understanding of factors identified as key assets, capabilities, or those most challenging for pharmacist recruitment and retention. Results: The advantages and disadvantages rural communities face in recruiting and retaining pharmacists are presented. These insights are linked to the advantages of financial income, incentives and moving allowance. Further advantages include the degree of practice autonomy, breadth of tasks, the perception of the community, loyalty to the pharmacy and its pharmacists, along with community recognition. Challenges associated with the recruitment and retention of pharmacists centred on the need for spousal or partner employment opportunities, having greater proximity to schools, access to social or cultural opportunities, along with good transport connections. Further challenges included housing, the cost of schooling for children, having adequate locum or peer coverage and opportunities to host interns. Discussion: The study provides a deeper exploration of the meaning and experiences of factors that previous research has shown are considered advantageous or challenging to the recruitment and retention of pharmacists in rural areas. Through the voices of pharmacists living and working in a rural area, the findings further enlighten our understanding regarding how the multifaceted and complex nature of health workforce planning may be addressed. As such, greater pharmacist recruitment and retention is enabled through adequate financial compensation and incentives, along with additional tax incentives for business and health services. Further, innovation is required to enhance economic sustainability. Locum coverage and intern opportunities also require innovative approaches to address concerns among potential candidates. Lastly, efforts to enable and support social connections such as schooling and spousal employment, while building community connection and a sense of rural community belonging, remain essential to recruit and retain pharmacists. Conclusion: Rural pharmacist recruitment and retention is complex, requiring a multi-pronged approach to implement practical solutions. Given this complexity and the unique features of each rural community, solutions require whole-of-community ownership to create innovative solutions. Recognition of specific advantages and challenges can address key driving factors for pharmacist recruitment and retention in rural communities.

Cuprous oxide/copper/cupric oxide nanoparticles were synthesized through a hybrid process involving anodic dissolution and a controlled redox reaction between NaOH and glucose in the solution. The study demonstrates the structural manipulation of the material by varying the reaction components within the solution. Morphology, structural analyses using SEM (Scanning Electron Microscope), EDX (Energy-dispersive X-ray spectroscopy), TEM (Transmission Electron Microscope), FTIR (Fourier Transform Infrared Spectroscopy), XRD (X-ray diffraction), and XPS (X-ray photoelectron spectroscopy) unveiled the tunability of the material's structure based on the reaction components. Nitrogen adsorption analysis employing the Brunauer-Emmett-Teller (BET) equation confirmed the material's porosity, while Dynamic Light Scattering (DLS) measurements provided insights into the materials' hydrodynamic size and zeta potential. The results demonstrated that by increasing the glucose/NaOH ratio during the reaction, the different structures and morphologies of the distinct products were obtained from the clustering of small nanoparticles to cubic shape and flower-like structure. Antibacterial activity tests conducted on various bacterial strains showed a correlation between the morphology and structure of the material and its antibacterial properties. The highest substantial antibacterial efficacy against all tested bacterial strains at a dosage of 100 μg/L was obtained for the samples with clustering morphology, whereas the remaining materials showed no discernible antibacterial effect against one of the studied bacteria. The results also demonstrated that the sample with a clustering structure exhibited superior antibacterial properties when dispersed in water containing dimethylsulfoxide.

Abstract Background Socioeconomic status (SES) is associated with stroke occurrence and survival following stroke but its association with health-related quality of life (HRQoL) following stroke remains uncertain. We performed a systematic review and meta-analysis to examine the association between SES and HRQoL after stroke. Methods PubMed, SCOPUS, EMBASE, and Web of Science were searched to identify relevant cohort and case–control studies between January 2000 and May 2022. Two authors screened titles, abstracts and full text articles. One author extracted data from all included studies. Meta-analyses were performed for studies with comparable measurements of SES and HRQoL. Random effects models were used to estimate pooled summary standardised mean differences in HRQoL by SES. Results Out of 1,876 citations, 39 studies incorporated measurement of overall HRQoL following stroke and were included in the systematic review, with 17 studies included in the meta-analyses. Overall, reports including education, income, occupation and work status effects on HRQoL after stroke were inconsistent among all included 39 studies. In the global meta-analysis of 17 studies, HRQoL among survivors of stroke was lower in the low SES group than in the high SES group (standardised mean difference (SMD) -0.36, 95% CI -0.52, -0.20, p

AbstractThe US dollar is the most prevalent currency to settle internationally traded merchandise. A few existing studies demonstrate that the US dollar can significantly impact a country’s trade balance with a non-US partner. Nevertheless, the current literature indicates the remarkable deficiency of empirical results for the case of India despite the vital importance of the US dollar in its international trade. Recognizing the European Union (EU) as the largest trading partner of India over the 2000Q1–2022Q2 period, this study is the first to explore how the US dollar influences India’s trade balance with the EU by employing the Nonlinear Autoregressive Distributed Lag (NARDL) method. The results show that, no matter if the US dollar is employed, the depreciation of rupee cannot facilitate India’s trade balance, and the appreciation has a negative effect. Therefore, devaluation is an ineffectual policy for supporting India’s trade balance with the EU.

It is becoming increasingly common for software to operate in various environments. However, even if the software performs well in the test phase, uncertain operating environments may cause new software failures. Traditional proposed software reliability models under uncertain operating environments suffer from the problem of being well-suited to special cases due to the large number of assumptions involved. To improve these problems, this study proposes a new software reliability model that assumes an uncertain operating environment. The new software reliability model is a model that minimizes assumptions and minimizes the number of parameters that make up the model, so that the model can be applied to general situations better than the traditional proposed software reliability models. In addition, various criteria based on the difference between the predicted and estimated values have been used in the past to demonstrate the superiority of the software reliability models. Also, we propose a new multi-criteria decision method that can simultaneously consider multiple goodness-of-fit criteria. The multi-criteria decision method using ranking is useful for comprehensive evaluation because it does not rely on individual criteria alone by ranking and weighting multiple criteria for the model. Based on this, 21 existing models are compared with the proposed model using two datasets, and the proposed model is found to be superior for both datasets using 15 criteria and the multi-criteria decision method using ranking.

In the context of global energy instability caused by the transformation of global demand for energy and energy resources, one of the most important areas in the automotive industry is the development of electric vehicles. Serial production of high-tech electric vehicles with a long range contributes to the stabilization of the energy market and the sustainable development of the whole fuel-energy sector. To evaluate the possibility of optimizing the electric vehicles energy consumption, various regenerative braking strategies are discussed in the article based on the Nissan Leaf electric vehicle, which simulation model includes submodules of the traction electric motor, hybrid braking system, traction rechargeable battery and tires. In order to test the adequacy of the simulation model to reproduce the relationship between the operating parameters of electric vehicles various systems and evaluate their ability to regenerate energy during braking the simulation results were compared with the actual experimental data published by the Lab Avt research laboratory (USA). The relative error of the mathematical modeling results of the braking energy regeneration processes is 4.5 %, which indicates the adequacy of the electric vehicle simulation model and the possibility of its using as a base for research and comparison of the energy efficiency of various regenerative braking strategies. As the results of experiments have shown, the usage of the proposed control strategy of the regenerative braking maximum force allows increasing 2.14 times the energy recharging traffic to the battery as compared with the basic control strategy of fixed coefficient braking forces distribution with an increase in braking distance by 10 m. An alternative control strategy of regenerative braking optimal efficiency as compared to the basic control strategy provides a reduction in braking distance by 13.2 % at increasing by 84.4 % the amount of energy generated by the electric motor for recharging the batteries. The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.

Seaports have a very important role in connecting freight by sea. Goods transported through seaports in the world are increasing day by day to meet human needs. This increases the pressure to apply more technologies for better port management. The world's seaports in the 4th generation, the generation in which seaports enhance connectivity to form a large network, have shown high efficiency when applying technology to port management. This optimizes port operations and connects port information into a network that improves productivity and reduces loading and unloading times. Today, the Internet of Things is the foundation for technologies to manage and optimize operations in various fields. It is considered by scientists to be a highly influential technology in the “4.0” era. The Internet of Things (IoT) technology directly affects the activities and processes of loading and unloading goods at seaports. Modern IoT-based port management technologies such as Radio Frequency Identification (RFID) and Dedicated Short Range Communications (DSRC) are contributing to the increased speed and safe movement of goods through seaports. The application of IoT in port management has become an inevitable trend and will be presented in this article. In the next generation, seaports tend to develop into smart ports based on rapidly developing technology platforms such as IoT, blockchain, and cloud computing. Smart port development also poses many issues to be resolved, including environmental issues. In this paper, the authors present some solutions to develop smart ports in an environmentally friendly manner.

Objective: To investigate the anti-inflammatory and analgesic effects of Solanum procumbens on complete Freund's adjuvant-induced arthritis rat models. Methods: We isolated and identified five compounds in the ethanol-soluble Solanum procumbens extract (SP) with anti-inflammatory effects, including ursolic acid, β-sitosterol, hexadecanoic acid, cis-vaccenic acid, and vanillic acid. Additionally, we investigated the anti-inflammatory effects of SP on rheumatoid arthritis symptoms, including paw volumes, local temperatures, withdrawal latency, and mechanical withdrawal threshold at the hind paw and white blood cell (WBC) number from complete Freund's adjuvant-induced arthritis rat models. Results: We have successfully established a complete Freund's adjuvant-induced arthritis rat model at a low dose (1 mg/mL). SP extract significantly reduced paw volumes (P

Shipping is facing huge pressure problems in this 21st century such as climate change and environmental pollution and the depletion of energy resources. Seaports are an important component of the shipping industry architecture. Although there is no common solution, seaports around the globe face the same challenge. Challenges raised include difficulties in integrating new technology into automation, traffic congestion, harmonizing residential communities around the port, quantifying and reducing CO2 emissions as well as planning for the energy transition. In addition, improving the adaptability of the port infrastructure in the context of increased pressure from market demand, labor shortage, and escalating prices should be considered. In that context, a smart port was born as a necessity. However, the understanding of smart ports is very limited. This review examines the recently published smart port literature to clarify the common concepts of smart ports and their development progress on the way to building a sustainable seaport ecosystem. Although smart port metrics and key port performance metrics are organized around four key performance areas including operations, environment, energy, and safety. However, a comprehensive review of all four key areas is very broad and difficult to cover in a review article. Therefore, this work focuses on analyzing and discussing the approaches and applications of the technology in smart port energy management systems. Our research has shown that different smart port founding perspectives play a decisive role in technology approaches to building a port energy management system including optimizing algorithms for energy consumption, balancing demand and energy production, and comprehensively integrating renewable energy. New findings in this study contribute to the elucidation of smart port concepts based on improving energy use and management efficiency with innovative technologies in the context of sustainable development of the shipping industry.

The global shipping industry has been contributing more than four-fifths of the volume of goods transported internationally. However, shipping is facing pressure from strict policies on combating climate change from the International Maritime Organization (IMO). Seaports are an essential component of shipping and are also having to change their development strategies to be more sustainable and smarter. The concept of a green port was born as an inevitable part of the green economic development path. Green port system development policies and strategies have been discussed and studied in recent literature reviews, and have revealed the limited reach of developing countries. This work focuses on evaluating successful green port policies and concepts in developed countries to highlight the distinctive features of green ports. Moreover, the experiences from the effective green port models of developed countries can be valuable lessons for developing countries like Vietnam. More interestingly, the core features of green ports, when piloted at several international ports in Vietnam, promote port efficiency and environmental friendliness. On the way to implementing the national green port strategy, Vietnam has been establishing legal and infrastructure corridors to realize the strategy of sustainable marine economic development by 2045.

In this study, we successfully synthesised bi-metallic ZIF(Zn-M) of 2-methyl imidazole with a second metal (cobalt or nickel) binding to the ZIF network. All ZIF samples were synthesised at room temperature and characterised by using XRD, FT-IR, SEM, DRS, and nitrogen adsorption and desorption isotherms. The materials have high crystallinity with a large surface area. The materials’ photocatalytic ability was examined via the degradation of indigo carmine under a sun-light simulator. The second metal enhanced the photon harvesting ability of ZIF(Zn) because the materials can absorb photons in both UV and visible regions. Of the two catalysts, ZIF(Zn-Co) exhibited high photocatalytic ability when it removed 100% of indigo carmine from an aqueous solution. The catalyst adsorbed 45% of indigo carmine after 2 h and entirely degraded the remaining dye dring 1.5 h of solar irradiation. While Co2+ increased the catalyst’s surface area, Ni2+ reduced it, leading to lower photocatalytic efficiency.

Abstract Introduction Transport-related physical activity (TRPA) has been identified as a way to increase physical activity due to its discretionary and habitual nature. Factors thought to influence TRPA span multiple disciplines and are rarely systematically considered in unison. This systematic review aimed to identify cross-sectional and longitudinal factors associated with adult TRPA across multiple research disciplines. Methods Using four electronic databases, a systematic search of English, peer-reviewed literature from 2010 – 2020 was performed. Studies quantitatively examining factors associated with the outcome of adult TRPA were eligible. Results Seventy-three studies (n = 66 cross-sectional; n = 7 longitudinal) were included, cumulatively reporting data from 1,278,632 observations. Thirty-six factors were examined for potential association with TRPA and presented in a social-ecological framework: individual (n = 15), social (n = 3), and environmental (n = 18). Seven factors were found to be consistently associated with higher adult TRPA: lower socio-economic status, higher self-efficacy, higher social normalization, lower distance of travel, higher destination concentration, more streetlighting, and higher public transportation frequency with a greater number of terminals near route start and endpoints. Conclusions This is the first comprehensive compilation of the correlates and determinants of adult TRPA. Seven individual, social, and environmental factors demonstrated consistent associations with TRPA. Models formed using these factors may facilitate more effective promotion of TRPA. There is a lack of longitudinal studies as well as studies assessing cognitive/attitudinal and social factors, highlighting gaps for further research. Those developing policies and strategies targeting TRPA need to consider a range of factors at the individual, social, and environmental level to maximise the likelihood of effectiveness.

Abstract Aim To evaluate the safety and early outcomes of autologous bone marrow mononuclear cell (BMMNC) infusion for liver cirrhosis due to biliary atresia (BA) after Kasai operation. Methods An open-label clinical trial was performed from January 2017 to December 2019. Nineteen children with liver cirrhosis due to BA after Kasai operation were included. Bone marrow was harvested through anterior iliac crest puncture under general anesthesia. Mononuclear cells (MNCs) were isolated by Ficoll gradient centrifugation and then infused into the hepatic artery. The same procedure was repeated 6 months later. Serum bilirubin, albumin, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, and prothrombin time were monitored at baseline, 3 months, 6 months, and 12 months after the first transplantation. Esophagoscopies and liver biopsies were performed in patients whose parents provided consent. Mixed-effect analysis was used to evaluate the changes in Pediatric End-Stage Liver Disease (PELD) scores. Results The average MNC and CD34+ cell counts per kg body weight were 50.1 ± 58.5 × 106/kg and 3.5 ± 2.8 × 106 for the first transplantation and 57.1 ± 42.0 × 106/kg and 3.7 ± 2.7 × 106 for the second transplantation. No severe adverse events associated with the cell therapy were observed in the patients. One patient died 5 months after the first infusion at a provincial hospital due to the rupture of esophageal varices, while 18 patients survived. Liver function was maintained or improved after infusion, as assessed by biochemical tests. The severity of the disease reduced markedly, with a significant reduction in PELD scores. Conclusion Autologous BMMNC administration for liver cirrhosis due to BA is safe and may maintain or improve liver function. Trial registration ClinicalTrials.gov identifier: NCT03468699. Name of the registry: Vinmec Research Institute of Stem Cell and Gene Technology. https://clinicaltrials.gov/ct2/show/NCT03468699?cond=biliary+atresia&cntry=VN&draw=2&rank=2 . Registered on March 16, 2018. The trial results will also be published according to the CONSORT statement at conferences and reported in peer-reviewed journals.

This paper presents some recent views on the aspects of vitamin D levels in relation to the COVID-19 infections and analyzes the relationship between the prevalence rates of vitamin D deficiency and COVID-19 death rates per million of various countries in Europe and Asia using the data from the PubMed database. The paper also discusses a new mathematical model of time-delay interactions between the body's immune healthy cells, infected cells, and virus particles with the effect of vitamin D levels. The model can be used to monitor the timely progression of healthy immune cells with the effects of the levels of vitamin D and probiotics supplement. It also can help to predict when the infected cells and virus particles free state can ever be reached as time progresses. The consideration of the time delay in the modeling due to effects of the infected cells or virus particles and the growth of healthy cells is also an important factor that can significantly change the outcomes of the body's immune cells as well as the infections.

Big Data technology is emerging as a mass technology that can be applied to many industries in life. Decisions in a wide range of fields may benefit greatly from the information provided by Big Data and Analytics research. One of the areas that have benefited the most from this technology is transportation, which is known as an important field in the development of each nation and possesses a huge treasure of data that traditional technologies cannot handle. Indeed, many countries have applied Big Data-based intelligent transportation systems because it is a traffic system that interacts with vehicles and people on the road, thereby reducing traffic congestion and traffic accidents year by year in many countries. The article presents the applications of Big Data technology in smart traffic systems, thereby providing the perspective of a smart city with a smart traffic system as a critical factor. This paper's analysis indicated that smart cities could be born and further developed through the linkage of Big Data technology and smart traffic systems with smart traffic systems as the core. In addition, the results also showed that the obstacle that needs to be studied at this time is the policy and legal framework for Big Data technology. Therefore, a system managed by the state or shared between the state and the private sector should be studied in the future, aiming to harmonize interests and develop the system extensively.

Devaluation of domestic currency is traditionally believed to foster a country’s trade balance. Innumerable papers have attempted to scrutinize the exchange rate-trade balance nexus in many countries across the globe, yet their conclusions diverge as they utilize different data, time frames, and methods. Most of them share the same weakness: disregarding the role of vehicle currency. Even though the literature about China is relatively large, no study has scrutinized the asymmetric impacts of vehicle currency and real effective exchange rate on China’s total trade balance with the entire EU. This research gap is especially notable in the circumstances that the EU has surpassed the USA to become China’s largest trading partner, and USD is the vehicle currency heavily employed in China-EU trade. This article aims to fill the aforesaid gap by applying the nonlinear ARDL method to investigate how USD as a vehicle currency, alongside real effective exchange rate, asymmetrically influences China’s trade balance with the whole EU. The empirical results indicate both long-run and short-run asymmetries in all models, and China’s trade balance reacts differently to the two kinds of exchange rates. The findings are robust in the EU-28 and EU-27 cases, and some useful implications are provided for policy-makers.

Dissolved ozone (O3(aq)) and residual ozone in groundwater under differently controlled parameters are two important outcomes in a lab-scale system of ferrous treatment with ozone, but they have not been well investigated yet. In this study, several preliminary parameters of ozone generation, types of diffusers, hydraulic retention time, and the pH in an ozone system of laboratory treatment were examined and evaluated statistically. The results showed that a venturi injector coupled with a bubble diffuser increased O3(aq) concentration to 9.05±0.28 mg/L corresponding to its diffusive coefficient of 0.195 min-1, 2.6 times higher than the bubble diffuser only. The O3(aq) decay constant in the presence of ferrous was 4.88 times higher than that in its absence. The mole stoichiometry of (D[O3(aq)]/D[Fe2+]) in synthetic water during ozonation was 1.21, corresponding to its mass ratio of 1.04 mg O3(aq)/mg Fe2+. The highest efficacy of ozone on ferrous removal was achieved at pH4.0, followed by that at pH6.0; the residual iron concentration at pH6.0 was 0.230±0.149 mg/L, falling below the WHO standard for drinking water. The residual ozone at pH 4.0 and 6.0 was not statistically different and may take 186 and 300 hrs. to achieve EPA and FDA regulations, respectively. The obtained results may provide a system and information of ozone conditions applied in the treatment of iron to meet the maximum standards of iron and ozone in water.

Software is widely used in various fields. There is no place where it is not used from the smallest part to the entire part. In particular, the tendency to rely on software is accelerating as the fields of artificial intelligence and big data become more widespread. Therefore, it is extremely important to evaluate the reliability of software because of the extensive damage that could occur if the software fails. Previously, software reliability models were developed based on mathematical and statistical grounds; however, immediate response was difficult. Therefore, in this study, a software reliability model was developed that depends on data using deep learning, and it was analyzed by replacing the activation function previously used in deep learning with the proposed software reliability model. Since the sigmoid function has a similar shape to the software reliability model, we utilized this to propose a deep learning software reliability model that replaces the activation function, the sigmoid function, with the software reliability function. Two datasets were compared and analyzed using 10 criteria, and the superiority of the proposed deep-learning software reliability model was proved. In addition, the results were compared by changing the parameters utilized in the proposed deep-learning software reliability model by −10%, −5%, 5%, and 10%, and it was found that the larger the parameters, the smaller the change.

The coronavirus disease (COVID-19) outbreak has prompted various industries to embark on digital transformation efforts, with software playing a critical role. Ensuring the reliability of software is of the utmost importance given its widespread use across multiple industries. For example, software has extensive applications in areas such as transportation, aviation, and military systems, where reliability problems can result in personal injuries and significant financial losses. Numerous studies have focused on software reliability. In particular, the software reliability growth model has served as a prominent tool for measuring software reliability. Previous studies have often assumed that the testing environment is representative of the operating environment and that software failures occur independently. However, the testing and operating environments can differ, and software failures can sometimes occur dependently. In this study, we propose a new model that assumes uncertain operating environments and dependent failures. In other words, the model proposed in this study takes into account a wider range of environments. The numerical examples in this study demonstrate that the goodness of fit of the new model is significantly better than that of the existing SRGM. Additionally, we show the utilization of the sequential probability ratio test (SPRT) based on the new model to assess the reliability of the dataset.

Abstract Background Recruiting and retaining medical, nursing, and allied health professionals in rural and remote areas is a worldwide challenge, compromising continuity of care and population health outcomes in these locations. Specifically, pharmacists play an essential and accessible frontline healthcare role, and are often the first point of contact for health concerns. Despite several incentives, there remains a maldistribution and undersupply of pharmacists in rural and remote areas across many parts of the world. Although current systematic reviews have focussed on factors affecting pharmacists’ retention generally, literature specifically focused on rural pharmacist workforce in a global context remains limited. The aim of this systematic review is to identify factors associated with recruitment and retention of the pharmacist workforce in rural and remote settings. Better understanding of these contributors will inform more effective interventional strategies to resolve pharmacist workforce shortages. Methods A systematic search of primary studies was conducted in online databases, including Medline, Embase, CINAHL, Scopus, Web of Science and PsycINFO, and by hand-searching of reference lists. Eligible studies were identified based on predefined inclusion/exclusion criteria and methodological quality criteria, utilising the Critical Appraisal Skills Programme (CASP) and Good Reporting of A Mixed Methods Study (GRAMMS) checklists. Results The final review included 13 studies, with quantitative, qualitative, or mixed methods research design. Study-specific factors associated with recruitment and retention of pharmacists in rural practice were identified and grouped into five main themes: geographic and family-related, economic and resources, scope of practice or skills development, the practice environment, and community and practice support factors. Conclusions The results provide critical insights into the complexities of rural recruitment and retention of pharmacists and confirms the need for flexible yet multifaceted responses to overcoming rural pharmacist workforce challenges. Overall, the results provide an opportunity for rural communities and health services to better identify key strengths and challenges unique to the rural and remote pharmacist workforce that may be augmented to guide more focussed recruitment and retention endeavours.

In recent years, lithium-ion batteries (LIB) have been used widely in portable electronic devices because of their advantages of durability, stability, high-capacity, low-cost, light-weight and small-scale. It makes LIB also deployed in various complex systems, in which efficient prediction of battery data, especially state-of-health (SoH), becomes crucial to ensure that the systems work stably without risks of power interruptions. With the recent improvement of Artificial Intelligence (AI) technologies, many works have been reported using deep learning (DL) models to investigate this problem, since such models can potentially increase their performance with more training data. This is also our direction in this research, which introduces a novel data-driven approach so-called Autoregression Nested Sequence (ARNS). On one hand, we come up with a nested sequence model to efficiently aggregate channel-wise and cycle-wise information, both of which are closely related to the operations of LIB. On the other hand, we incorporate relaxation effects into the model operations to handle peak prediction. To the best of our knowledge, ARNS is the first sophisticated deep learning model that combines all those features into a whole predictive system. The experimental results obtained using the NASA and CALCE datasets confirm significant improvement of ARNS, especially when dealing with peak periods in different SoH of multiple cycles.

Although new ecotourism indeed developed from the last years of the twentieth century, it has been receiving considerable attention from the whole society, because of its superiority compared to other types of tourism in terms of responsibility for people, nature, and environment. Ecotourism is becoming popular as visitors begin to pay more attention to minimizing their impact on the beautiful lands they come across. Vietnam has become an ideal place to provide many eco-tourism experiences for tourists interested in the environment. Tram Chim is one of the National Parks in Vietnam that has excellent potential to develop this type of ecotourism as it is considered a “small part“ of the ancient wetland ecosystem. Tram Chim National Park - Ramsar area is of international importance, ranking 2,000th in the world and 4th in Vietnam. Tram Chim National Park attracts many tourists because of its beautiful natural landscape and rare red-crowned crane and many other plants and animals in the Red Book. This article outlines the potentials, current status, strengths, weaknesses, opportunities, and challenges in ecological tourism development. On that basis, propose some orientations and solutions to promote ecotourism development in Tram Chim National Park in the next time.

The promising eatable coatings, which were obtained by the combination of chitosan and essential oils (EO), attracted many researchers. This article summarizes recent studies on fruit and vegetable preservation using chitosan and EOs. CS-essential oils (clove, thyme, cinnamon, cymbopogon martinii, lemon oil, olive oil, cardamom oil, heracleum persicum oil) brings remarkable benefits such as: against many harmful microorganism (many strains of gram-positive and gram-negative bacteria: L. monocytogenes, S. aureus, S. Typhi, E. coli and the fungus Colletotrichum gloeosporioides). They also prevented weight loss, and maintained stable quality in color, firmness, and nutrient content, of many fruits and vegetables such as pomegranate arils, mango, cherry fruits, avocados, bell pepper, lettuce, and carrot under storage conditions.

Introduction: An adequate healthcare workforce remains essential for the health of rural communities. Strategies to address rural health workforce challenges have often centred on the medical and nursing workforce; however, addressing the rural pharmacist workforce also remains critical as they are often the first point of contact for health advice. Initiatives have increased pharmacist supply; however, key issues such as poor attraction, recruitment, and retention to rural areas remain. The aim of this study was to support the recruitment and retention of pharmacists in rural areas of Australia through the development of the Pharmacy Community Apgar Questionnaire (PharmCAQ). Methods: A modified Delphi technique was employed to develop the PharmCAQ. A panel of experts were purposively selected. Eight representatives were from organisations with rural experience relevant to the study including the Society of Hospital Pharmacists of Australia, the Pharmaceutical Society of Australia, the Pharmacy Guild of Australia, the Pharmacy Board of Australia, and a representative of a government health agency, who also leads a hospital pharmacy. Three additional participants included local and international academics with health policy and rural health workforce expertise. All participants participated in three separate focus groups of 45-60 minutes duration, where the review and refinement of factors that drive recruitment and retention of pharmacist were discussed. Face and content validity was achieved through the representatives, while internal consistency was achieved when the tool was piloted among 10 rural pharmacists in rural Victoria. Results: Fifty key factors that impact the recruitment and retention of pharmacists were identified, developed and succinctly described. All factors were grouped into five classifications: (1) geographic, (2) economic and resources, (3) practice and scope of practice, (4) practice environment and (5) community practice support. After final consensus, the factors and their definitions formed the final questionnaire. Lastly, the reliability of PharmCAQ was determined, with a Cronbach's alpha coefficient of 0.852. Conclusion: While the development and use of the Apgar questionnaire for the recruitment and retention of health professionals is not a novel idea, seeking to specifically focus on pharmacists is unique. However, 10 factors were similar to factors associated with rural recruitment and retention of both physicians and nurses; they encompassed geographic, community support, and economic and resource factors. Regardless of similarities or differences between health professions in terms of recruitment and retention, as a mechanism for addressing the worsening health professional shortage currently experienced in rural areas, the PharmCAQ was developed to support the recruitment and retention of the pharmacist workforce in rural areas.

Nowadays, employee behavior that has emerged as one of the most crucial factors that determine the success of organizations in general, and in tourism industry in particular. Previous researchers indicated that it is necessary to shed light on the mechanism influence of determinant factors on organizational citizenship behavior in the tourism industry. So that the main purpose of this study is to examine the mechanism of employees’ perceptions of green performance of hotels influence their organizational citizenship behavior (OCB) with the serial mediating effects of psychology (perceived pride) and emotion (affective commitment) of employees working in the hotel. A conceptual research model is developed and then empirically examined using PLS - SEM. The study data was collected from 209 employees working in hotel at Moc Chau national tourism area (Vietnam) via a questionnaire survey. The results show a positive correlation between employees’ perception of green performance of their hotel and their OCB. Interestingly, employees’ perceived pride and affective commitment act as serial mediators in the relationship correlation between employees’ perception of green performance of their hotel and their OCB. This study offers new insight for researchers and managers in the hospitality industry in term of ―go green‖ tendency.

Purpose – In recent years, agricultural activities in the Mekong Delta have frequently faced the potential risks of drought, saline intrusion and unusually heavy rainfall because of climate change, leading to a decline in crop yield. Therefore, this study aimed to establish rice planting seasons in An Giang, an upper-located province in the Mekong Delta. Design/methodology/approach – The impacts of seasonal variation on the key rice seasons were simulated using the Food and Agriculture Organization-crop model for the OM6976 rice variety grown in the study area. For the simulation, the model combined crop, soil, weather and crop management data. Findings – The results show that seasonal variation because of changes in weather factors leads to alternation in crop yields across the study area. Specifically, the spring and summer rice planting seasons are advanced by one to two weeks compared with the baseline, and crop yield increased by 5.9% and 4.2%, respectively. Additionally, planting for the autumn–winter rice season on 3 August increased crop yield by up to 8.1%. Originality/value – In general, rice planting seasons that account for weather factor changes effectively reduce production costs and optimise production.

BackgroundComorbidity, along with aging, affects stroke-induced health-related quality of life (HRQoL). We examined the potential role of diet quality in modifying the association between comorbidity and HRQoL in patients with stroke.MethodsA cross-sectional study was conducted on 951 patients with stroke from December 2019 to December 2020 across Vietnam. Comorbidity was assessed using the Charlson Comorbidity Index (CCI) items and classified into two groups (none vs. one or more). Diet quality was evaluated using the Dietary Approaches to Stop Hypertension Quality (DASH-Q) questionnaire, and HRQoL was measured using the RAND-36, with a higher score indicating better diet quality or HRQoL, respectively. Besides, socio-demographics, health-related behaviors (e.g., physical activity, smoking, and drinking), disability (using WHODAS 2.0), and health literacy were also assessed. Linear regression analysis was utilized to explore the associations and interactions.ResultsThe proportion of patients with stroke aged ≥65 years and having comorbidity were 53.7 and 49.9%, respectively. The HRQoL scores were 44.4 ± 17.4. The diet quality was associated with higher HRQoL score (regression coefficient, B, 0.14; (95% confidence interval, 95% CI, 0.04, 0.23; p = 0.004), whereas comorbidity was associated with lower HRQoL score (B, −7.36; 95% CI, −9.50, −5.23; p < 0.001). In interaction analysis, compared to patients without comorbidity and having the lowest DASH-Q score, those with comorbidity and higher DASH-Q score had a higher HRQoL score (B, 0.21; 95% CI, 0.03, 0.39; p = 0.021).ConclusionThe findings showed that good diet quality could modify the adverse impact of comorbidity on HRQoL in patients with stroke. Diet quality should be considered as a strategic intervention to improve the HRQoL of patients with stroke, especially those with comorbidity, and to promote healthier aging.

The use of subway tunnel engineering technology has become more professional and refined with the growth of society and the advancement of science and technology. The initial construction process of a subway tunnel shield is the most critical part of the entire engineering system. Shield launching period construction is the most prone to accidents in the shield construction process, directly related to the smooth through the shield tunnel. The line 1 of Ho Chi Minh (HCM) Metro is the first subway line, the full length of 19.7 km, the underground road length of 2.6 km from km 0 + 615 to km 2 + 360, from Ben Thanh market, and then through the Sai Gon river and 14 station (including 3 underground stations and 11 elevated stations), reach Suoi Tien park and is located in Long Binh area station, underground building blocks including Ben Thanh market station to Opera House station interval, Opera House station, Opera House station to Ba Son station interval. This paper selects Shield launching period of Opera House station to Ba Son shaft interval as an example, analyze the key construction technology, construction control parameters and launching considerations of shield machine.

Background: Hypertension and oxidative stress are involved in the pathophysiological mechanism of stroke. We aimed to investigate the modification impact of the pro-oxidant–anti-oxidant balance (PAB) on the association between hypertension and stroke recurrence (SR). Methods: A cross-sectional design was conducted from December 2019 to December 2020 in 951 stroke patients in six hospitals across Vietnam. Hypertension was defined using antihypertensive medication or systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. PAB was estimated using weighting methods based on smoking, drinking, and overweight/obesity with pro-oxidant capacity, diet quality, fruit intake, vegetable intake, and physical activity with antioxidant capacity. The higher PAB scores indicated a beneficial balance shifting toward antioxidant dominance. SR was diagnosed by neurologists. Moreover, sociodemographic and health conditions were included as covariates. Multiple logistic regression analyses were used to explore the associations and interactions. Results: The hypertension and SR proportions were 72.8% and 17.5%, respectively. hypertension was associated with an increased SR likelihood (odds ratio (OR) = 1.93; p = 0.004), whereas a higher PAB score was associated with a lowered SR likelihood (OR = 0.87; p = 0.003). Moreover, hypertension interacting with every one-point increment of PAB was associated with a lowered SR likelihood (OR = 0.83; p = 0.022). Conclusions: The harmful impact of hypertension on SR could be alleviated by PAB. The interplay of health behaviors should be highlighted in the intervention strategies for stroke prevention.

A common limitation of the studies on the exchange rate-trade balance linkage is ignoring the USD’s role as a vehicle currency. Some recent papers have recognized this gap and proposed a hypothesis that the neglection of the USD’s role as a vehicle currency can restrict the significance of findings. This study aims to test that hypothesis in the trade between each of the 10 countries in ASEAN (Association of Southeast Asian Nations) with the whole EU-28. Specifically, this paper is the first to examine how the vehicle currency USD’s exchange rates, along with the real effect exchange rates, asymmetrically impact the trade balance of each ASEAN country with the EU-28 by employing the NARDL method to investigate whether the ignorance of the USD leads to fewer significant coefficients of exchange rates. The results indicate that the vehicle currency model (VCER) outperforms the real effective exchange rate (REER) model, which supports the hypothesis. In addition, the results are robust when controlling for the role of exchange rate volatility.

The ultimate goals of education and training are the development of learners' learning outcomes. The prospect of achieving high academic results should function as a driving force for students to be engaged in learning. Recognition of the factors affecting their learning satisfaction should facilitate their learning process, especially in online learning environments such as Massive Open Online Courses (MOOCs). The purpose of this study was to examine the interactions among students' characteristics, their perceived values of self-regulated learning (SRL) strategies, satisfaction and academic performances. A mixed-methods design was employed to investigate the issue under exploration. The 227 surveyed responses were collected from English majors who had experience in MOOCs and were studying at a private university in Can Tho city in the Mekong Delta, Vietnam. Data from the survey was analysed with the Statistical Package for the Social Sciences (SPSS) 25 for the correlations between their characteristics and the quantitative variables, while Partial Least Squares Structural Equation Modelling (PLS-SEM) was performed to examine the perceived effects of self-regulated learning (SRL) strategies on their satisfaction and academic outcomes. Qualitative data was collected through open-ended survey questions and analysed based on thematic analysis guidelines. The results revealed that SRL strategies such as strategic planning, time management, environment structuring, and help-seeking positively influenced both student satisfaction and academic performance. Notably, the study identified flexible learning time, self-paced learning, and the ability to choose study locations as significant factors enhancing student satisfaction. Conversely, limited social interaction, poor internet connectivity, and low motivation were found to be demotivating factors. Additionally, the study highlighted the importance of gender and prior online learning experience in shaping students' satisfaction and performance in MOOCs. While gender showed no significant correlation with SRL strategies, satisfaction, or academic performance, prior experience in online learning environments, such as the number of completed MOOC courses, was significantly correlated with better academic outcomes. However, a weak negative correlation between students' academic years and their satisfaction was observed, suggesting that more advanced students might face increased academic pressure and higher expectations, leading to lower satisfaction levels. The research underscores the critical role of SRL strategies in facilitating effective learning in MOOCs, especially in the context of English major students who often lack direct interaction with instructors and peers. Training students in SRL strategies can help them better manage their learning processes, overcome challenges, and achieve their academic goals. This study contributes to the understanding of how student characteristics and SRL strategies affect learning in online environments and suggests practical implications for enhancing MOOC experiences. Future research should investigate additional SRL strategies and include a larger, more diverse sample to provide a more comprehensive understanding of their impact on student satisfaction and academic performance in MOOCs. Furthermore, exploring the specific challenges faced by different academic disciplines in MOOCs could offer more tailored solutions to improve online learning experiences.

Research has suggested that the type of feedback learners receive can impact on whether learners understand the feedback, the extent to which they engage with it, and whether they incorporate it in their revised drafts. However, to date, only a small number of studies have investigated learner engagement with corrective feedback provided by automated writing evaluation tools, and of those few have considered in greater depth the impact of the type of automated feedback on engagement. This multiple-case study examines two EFL learners' engagement with the two forms of corrective feedback provided by Criterion categorised as generic and specific and factors that can explain the nature of their engagement. Data were collected from learners' first and revised drafts of multiple essays on Criterion, screencasts of students' think-aloud procedures while revising essays, and stimulated recall interviews. Findings indicate the learners' higher uptake rate and more successful error corrections in response to generic versus specific feedback. However, their mental effort expenditure differed when cognitively engaging with the feedback, which could be explained in terms of individual learning goals, feedback quality, and the nature of tagged errors. These findings have relevant implications for utilising automated corrective feedback in L2 writing classes.

This qualitative study explored the possibility of implementing the happy school model (HSM) in the context of Vietnamese higher education, with a focus on the socio-cultural perspectives of nine tertiary English as a foreign language (EFL) teachers at different career stages. Through semi-structured interviews, thematic analysis, and theoretical underpinning by constructivist paradigm and humanistic education theory, the study illuminated multifaceted insights. Key themes emerged, including aligning the HSM with holistic student development, recognizing challenges and potential benefits, balancing traditional Confucian values, and adapting the model to Vietnam's unique socio-cultural and economic landscape. The findings provide valuable guidance for educational innovation in Vietnam, highlighting complexities of aligning a new educational paradigm with existing practices and cultural norms. While the study's focus on a specific cultural context and limited participant pool presents certain limitations, the insights offer rich contributions to the broader global dialogue on education and human development. Future research directions and practical implications are also discussed, making this study a valuable resource for educators, policymakers, and researchers interested in the intersection of universal educational principles and specific cultural contexts like Vietnam.

This study investigated how teachers perceived the benefits and difficulties of implementing a Lesson Study (LS) in the context of English language teaching at a university in Vietnam. The data were collected from six teachers through semi-structured interviews. To analyze the data, two addressing themes (teachers' perceived benefits and teachers' perceived difficulties) were focused on while implementing LS. The results generally showed that the teachers believed that LS brought them three benefits: encouraging teachers' exchange activities and helping them deepen knowledge of lesson content, understanding students' learning activities and working processes, and promoting teachers' motivation in pursuing their continuous professional development (CPD). Regarding teachers' perceived difficulties in LS implementation, they reported lacking confidence in actively implementing LS activities. Additionally, they had difficulties in time management and encountered problems reaching a consensus for joint work due to the influence of muti-faceted aspects. Accordingly, the study provides pedagogical implications for related stakeholders (teachers, students, and policymakers) regarding LS implementation issues contributing to the success of LS implementation in Vietnam and other similar contexts.

A comprehensive educational framework is provided by the Conceive-Design-Implement-Operate (CDIO) which is particularly relevant to engineering and applied sciences. This paper investigates the application of the CDIO approach in the field of chemistry pedagogy in Vietnam focusing on its adaptability to the current educational demands and its potential to enhance the competency of future teachers. The CDIO approach develops training curricula and outputstandards based on input from teachers,students, alumni and recruitment firms. This study uses the CDIO approach extensively with professional knowledge, social awareness and creative tendencies. The study involved a survey of 240 chemistry teachers and 242 students from various universities across Vietnam. Data were collected through online surveys using Google Forms and processed using SPSS software for statistical analysis. The research analyzed the alignment of practical teaching activities with CDIO standards and developed a framework for experimental practice competency. Findings indicated a robust implementation of the CDIO approach in chemistry pedagogy. In laboratory safety, experimental planning, execution and competence were high. The study shows that the CDIO strategy enhances professional competence and practical abilities in Vietnamese chemistry pedagogy students. It promotes collaboration and personal growth to meet changing educational needs. The CDIO approach could transform chemistry pedagogy in Vietnam suggesting science education reforms and capacity building.

In the 1980s of the twentieth century, universities in developed countries began to realize the growing gap between the capabilities of new graduate engineers and the actual requirements of engineering branches. The strong progress of technology requires engineers to have the intellectual abilities and necessary job-specific skills to master that progress. This paper focuses on Conceive, Design, Implement and Operate (CDIO) approach-based teaching for students majoring in electrical and electronic engineering technology at engineering universities in Vietnam to demonstrate the feasibility of the teaching model. The experimental method of synthesizing qualitative and quantitative results for 90 students in control and experimental classes was used. The experimental and control classes both had 45 students. SPSS software version 22 was used to gather data and evaluate the learning results of the two experimental and control groups. According to the findings of the T-test analysis of the independent variables for the two groups, the experimental class performed better in academics and had students in the experimental group who were more satisfied with their post-test scores. This result contributes to confirm that the use of the CDIO-based teaching model in Vietnam is effective for students majoring in electrical and electronic engineering technology.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global health concern. The development of vaccines with high immunogenicity and safety is crucial for controlling the global COVID-19 pandemic and preventing further illness and fatalities. Here, we report the development of a SARS-CoV-2 vaccine candidate, Nanocovax, based on recombinant protein production of the extracellular (soluble) portion of the spike (S) protein of SARS-CoV-2. The results showed that Nanocovax induced high levels of S protein-specific IgG and neutralizing antibodies in three animal models: BALB/c mouse, Syrian hamster, and a non-human primate (Macaca leonina). In addition, a viral challenge study using the hamster model showed that Nanocovax protected the upper respiratory tract from SARS-CoV-2 infection. Nanocovax did not induce any adverse effects in mice (Mus musculus var. albino) and rats (Rattus norvegicus). These preclinical results indicate that Nanocovax is safe and effective.

Innovative marketing practices are essential for firms to increase sales and profitability. This paper aims to investigate the determinants of firms’ marketing innovation based on the employment of resource-based view and stakeholder theory. A probit regression model linking marketing innovation with proxies of firms’ resources and pressures from firms’ stakeholders was tested based on a dataset of 5,857 Vietnamese enterprises taken from a survey by the Ministry of Science and Technology of Vietnam in 2016. The findings indicate that firms’ size decreases the probability of marketing innovation by 1%, while internal knowledge gained from internal R&D causes the probability of marketing innovation to increase by 0.18%. Besides, the political connection and collaborations with competitors and private consultants drive the probability that firms implement the marketing innovation up by 0.09%, 0.12%, and 0.09%, respectively. On the other hand, export-oriented firms are more likely to implement marketing innovation by 0.03%, while foreign ownership reduces the chance of this decision by 0.05%. This research also reveals the essential role of the firm’s market pressures to enter into new markets or improve product quality in encouraging marketing innovation by 0.16% and 0.13%, respectively. AcknowledgmentThis research was supported by National Economics University, Grant Number: 343-QĐ-ĐHKTQD.

COVID-19 is caused by a coronavirus called SARS-CoV-2. Many countries around the world implemented their own policies and restrictions designed to limit the spread of Covid-19 in recent months. Businesses and schools transitioned into working and learning remotely. In the United States, many states were under strict orders to stay home at least in the month of April. In recent weeks, there are some significant changes related restrictions include social-distancing, reopening states, and staying-at-home orders. The United States surpassed 2 million coronavirus cases on Monday, June 15, 2020 less than five months after the first case was confirmed in the country. The virus has killed at least 115,000 people in the United States as of Monday, June 15, 2020, according to data from Johns Hopkins University. With the recent easing of coronavirus-related restrictions and changes on business and social activity such as stay-at-home, social distancing since late May 2020 hoping to restore economic and business activities, new Covid-19 outbreaks are on the rise in many states across the country. Some researchers expressed concern that the process of easing restrictions and relaxing stay-at-home orders too soon could quickly surge the number of infected Covid-19 cases as well as the death toll in the United States. Some of these increases, however, could be due to more testing sites in the communities while others may be are the results of easing restrictions due to recent reopening and changed policies, though the number of daily death toll does not appear to be going down in recent days due to Covid-19 in the U.S. This raises the challenging question: • How can policy decision-makers and community leaders make the decision to implement public policies and restrictions and keep or lift staying-at-home orders of ongoing Covid-19 pandemic for their communities in a scientific way? In this study, we aim to develop models addressing the effects of recent Covid-19 related changes in the communities such as reopening states, practicing social-distancing, and staying-at-home orders. Our models account for the fact that changes to these policies which can lead to a surge of coronavirus cases and deaths, especially in the United States. Specifically, in this paper we develop a novel generalized mathematical model and several explicit models considering the effects of recent reopening states, staying-at-home orders and social-distancing practice of different communities along with a set of selected indicators such as the total number of coronavirus recovered and new cases that can estimate the daily death toll and total number of deaths in the United States related to Covid-19 virus. We compare the modeling results among the developed models based on several existing criteria. The model also can be used to predict the number of death toll in Italy and the United Kingdom (UK). The results show very encouraging predictability for the proposed models in this study. The model predicts that 128,500 to 140,100 people in the United States will have died of Covid-19 by July 4, 2020. The model also predicts that between 137,900 and 154,000 people will have died of Covid-19 by July 31, and 148,500 to 169,700 will have died by the end of August 2020, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the Covid-19 death data available on June 13, 2020. The model also predicts that 34,900 to 37,200 people in Italy will have died of Covid-19 by July 4, and 36,900 to 40,400 people will have died by the end of August based on the data available on June 13, 2020. The model also predicts that between 43,500 and 46,700 people in the United Kingdom will have died of Covid-19 by July 4, and 48,700 to 51,900 people will have died by the end of August, as a result of the SARS-CoV-2 coronavirus that causes COVID-19 based on the data available on June 13, 2020. The model can serve as a framework to help policy makers a scientific approach in quantifying decision-makings related to Covid-19 affairs.

The role of renewable and fossil fuel energy consumption on environmental sustainability remains inconclusive due to varied economic and technological structure. This study provides new insight by assessing the nexus between the utilization of two energy categories — renewable and conventional, environmental quality and economic growth embodying capital, trade openness and government expenditure. A panel data of 45 Emerging Market and Developing Economies (EMDEs) from 1990 to 2014 was employed in the study. We applied heterogeneous panel data approach and second-generational econometric techniques that permit cross-sectional dependence and slope heterogeneity. The evaluation of long-term effects conducted by AMG, along with CCEMG and MG estimators revealed that besides other factors such as government expenditure, capital, and trade openness, non-renewable and renewable energy utilization significantly contributes to the economic growth of the selected EMDEs. The study acknowledges the trade-off effect between environmental quality and economic growth. Using Dumitrescu and Hurlin test, we found strong evidence to support the feedback hypotheses among renewable energy, consumption of conventional fuels, economic growth and CO2emissions. From a policy perspective, the empirical findings recommend the implementation of effective policies that promote green power and economic structural adjustment in order to diminish the level of atmospheric CO2 emissions.

Solanum procumbens L. (Solanaceae) were extracted respectively with n-hexane, ethyl acetate, and methanol to obtain the corresponding extracts. The methanolsoluble extract was acidified by adding HCl 0.5 M; this was followed by liquid-liquid partition with CHCl3 to afford CHCl3-soluble fraction. From this fraction, four compounds were isolated and identified as ergosterol peroxide (1), 9,11-dehydroergosterol peroxide (2), N-(N-benzoyl-L-phenylalanyl)-L-phenylalanol (3), and moupinamide (4). Their structures were elucidated based on the NMR spectroscopic analysis and comparison with the literature. All isolated compounds were first reported from S. procumbens.

A straightforward method for the preparation of benzo[4,5]imidazo[1,2-a]pyrimidine derivatives catalysed by an acidic deep eutectic solvent from choline chloride (ChCl) and phenol via the Biginelli reaction of 2-aminobenzimidazole, ethyl acetoacetate, and aldehydes has been developed under metal- and solvent-free conditions. The desired products were obtained in moderate to good yield (49-79%) and the DESs were known as an economical and environmentally friendly catalyst.

BACKGROUND: The amygdala is highly implicated in an array of psychiatric disorders but is not accessible using currently available noninvasive neuromodulatory techniques. Low-intensity transcranial focused ultrasound (TFUS) is a neuromodulatory technique that has the capability of reaching subcortical regions noninvasively. METHODS: We studied healthy older adult participants (N = 21, ages 48-79 years) who received TFUS targeting the right amygdala and left entorhinal cortex (active control region) using a 2-visit within-participant crossover design. Before and after TFUS, behavioral measures were collected via the State-Trait Anxiety Inventory and an emotional reactivity and regulation task utilizing neutral and negatively valenced images from the International Affective Picture System. Heart rate and self-reported emotional valence and arousal were measured during the emotional reactivity and regulation task to investigate subjective and physiological responses to the task. RESULTS: Significant increases in both self-reported arousal in response to negative images and heart rate during emotional reactivity and regulation task intertrial intervals were observed when TFUS targeted the amygdala; these changes were not evident when the entorhinal cortex was targeted. No significant changes were found for state anxiety, self-reported valence to the negative images, cardiac response to the negative images, or emotion regulation. CONCLUSIONS: The results of this study provide preliminary evidence that a single session of TFUS targeting the amygdala may alter psychophysiological and subjective emotional responses, indicating some potential for future neuropsychiatric applications. However, more work on TFUS parameters and targeting optimization is necessary to determine how to elicit changes in a more clinically advantageous way.

PurposeThe purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC).Experimental designRB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss.ResultsRB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.ConclusionsCo-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Abstract Precise determination of glomerular filtration rate (GFR) is essential for the management of patients with muscle-invasive bladder cancer (MIBC). We aim to describe the early evolution of measured GFR (mGFR) after radical cystectomy and urinary diversion (RCUD) and to identify risk factors for GFR decline. GFR measurement using 51Cr-EDTA continuous infusion, estimated GFR (eGFR) from five published equations and renal scintigraphy with split renal function determination were performed before and 6 months after RCUD. Chronic Kidney Disease (mGFR

The random variable X represents the stress placed on the system by the operating environment and random variable Y represents the strength of the system. A system is able to perform its intended function if its strength is greater than the stress imposed upon it. Reliability of the system is defined as the probability that the system is strong enough to overcome the stress. That is, R = P(Y >X). In other words, reliability is the probability that the strengths of the unit are greater than the stresses. The stress-strength model has found interests in many applications include mechanical engineering and human heart monitoring conditions. The interval-system is defined as a system with a series of chance events that occur in a given interval of time. A k-out-of-n interval-system is a system with a series of n events in a given interval of time which successes (or functions) if and only if at least k of the events succeed (function). In short, the k-out-of-n interval-system is an interval-system which successes if and only if at least k of n events succeeds. The stress-strength reliability inference of the interval-system with a series of n independent events that occurs in a given interval of time is considered. The reliability of the interval-system is the probability that at least k out of n events in a given interval of time succeed. This paper derives uniform minimum variance unbiased and maximum likelihood reliability estimates of k-out-of-n interval-system based on stress-strength inference events where X (stress) and Y (strength) are independent two-parameter exponential random variables. An application in human heart conditions to illustrate the results is discussed.