Black Death is a virosis caused by the Tomato Spotted Wilt Virus (TSWV), transmitted by thrips, and represents a complex problem since weed hosts for thrips vectors and the virus is accentuated as virus reservoir and vector sustenance. The objective was to generate, from a list of weeds that act as hosts for the four vector thrips species in the horticultural belt of La Plata, a relative risk categorization as an epidemiological component. Between 2000 and 2003, three sites were selected within the horticultural belt of La Plata (Buenos Aires, Argentina) where flowers of 21 weed hosts of Frankliniella occidentalis, Frankliniella schultzei, Frankliniella gemina and Thrips tabaci were sampled monthly (60 in total). For analysis, the sampling results were grouped into three annual seasons, corresponding to the phenology of greenhouse crops in the region. For the four thrips vectors, the abundance of adult thrips and the presence of their larvae were considered using an unsupervised hierarchical cluster analysis and the DGC multivariate mean comparison test to obtain the number of significant groups. From this base grouping, three risk groups (RG) were defined as a source of inoculum for these vectors: high (H), medium (M) and low (L) according to the status of the reproductive host (RH). The groups that emerged were: (H): RH of F occidentalis, (M): RH of F. schultzei and T. tabaci, and (L): RH of F. gemina or non-vector thrips. Periodic survey and early flowering suppression of nine weed species categorized as high risk is proposed. This implies the continuous monitoring of three weed species, to which other companion weeds are added according to the growing season.

This study aimed to analyze government policies in education during the Covid-19 pandemic and how teachers exercised discretion in dealing with limitations in policy implementation. This research work used the desk review method to obtain data on government policies in the field of education during the Covid-19 pandemic. In addition, interviews were conducted to determine the discretion taken in implementing the learning-from-home policy. There were three learning models during the pandemic: face-to-face learning in turns (shifts), online learning, and home visits. Online learning policies did not work well at the pandemic’s beginning due to limited infrastructure and human resources. To overcome various limitations, the government provided internet quota assistance and curriculum adjustments and improved online learning infrastructure. The discretion taken by the teachers in implementing the learning-from-home policy was very dependent on the student’s condition and the availability of the internet network. The practical implication of this research is that street-level bureaucrats need to pay attention to discretionary standards when deciding to provide satisfaction to the people they serve.

The research aims to explore the degree of acceptance of digital work culture among the youth in the Emirati society within the study sample. Additionally, it aims to reveal the relationship between “gender” and “educational status” as sociodemographic factors among the youth in the study sample and their level of acceptance of digital work culture. Furthermore, the study aims to identify prospective trends in digital work culture among young individuals in Emirati society. Due to the nature of the descriptive research, it employed the “sample social survey” approach. The field study primarily utilized a quantitative tool for data collection, namely the “digital questionnaire.” This questionnaire was administered to a purposefully chosen random sample comprising young individuals actively seeking employment opportunities (unemployed individuals) or those new to the labor market. The participants fell within the age group of 15 to 35 years, totaling 184 individuals. Care was taken to ensure that this sample was representative of all youth categories in Emirati society, considering demographic factors such as gender, place of residence, and educational status. The research findings indicate that an overwhelming majority of young individuals in the study sample (97.8%) have no obstacles to accepting job opportunities that necessitate digital and technological skills. Moreover, the study uncovered a direct and statistically significant relation between “gender” and the “level of acceptance of digital work culture,” favoring females. This implies that females are more inclined to accept digital job opportunities compared to males. Additionally, the results highlighted a positive and statistically significant relation between both “educational status” and the “level of acceptance of digital work culture.” In other words, individuals with higher levels of education demonstrate a greater interest in digital job opportunities. Utilizing Step-wise Regression, the study also made predictions about the spread of “future digital work culture” in the United Arab Emirates based on the variable of “education.”

Improving the competitiveness of tourism destinations is crucial for driving local economies and achieving income growth. In light of this evidence, numerous government departments strive to assess specific factors that impact the competitiveness of tourism destinations, enabling them to issue appropriate new tourism policies that promote more effective forms of tourism business. Therefore, the primary objective of this paper is to investigate how various elements such as tourism resources, tourism support, tourism management, location conditions, and tourism demand influence regional competitiveness in the Northern Bay region of Guangxi Province in China. To accomplish this goal, an online survey was conducted to collect data from 420 visitors who had experienced North Gulf Tourism; yielding an impressive response rate of 95 percent. The findings reveal that all aforementioned factors—namely: Tourism resources, tourism support, tourism management, location conditions and tourist demand—significantly impact destination competitiveness. Notably though, it was found that among these factors influencing destination competitiveness; it is primarily determined by effective local-level management (β = 0.345). Following closely behind are tourist demand (β = 0.133) as the second most influential factor affecting destination competitiveness; followed by location conditions (β = 0.116) ranking third; then comes tourist support (β = 0.03) as fourth in line impacting destination competitiveness; finally with least impact being exerted by available tourist resources (β = 0.016). Consequently, highlighting that regional competitiveness within Guangxi’s Northern Bay area predominantly hinges on efficient local-level management practices thus strongly recommending relevant authorities formulate novel work policies aimed at enhancing levels of local-level competitive advantage within the realm of regional touristic offerings.