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The present study tackles the linguistic phenomenon of ‘gradability by focus’ in Arabic from a cognitive linguistic perspective. By and large, the early Arab grammarians have not theorized about gradability despite its importance in the semantic relationships. They address some grammatical and morphological forms that convey either ends of the scale of gradability. Gradable forms include ‘‘’at-Tawwkīd’’ (i.e., emphasis), ‘’al-Mafξūl ’al-Muŧlaq” (i.e., the cognate object), şiyagh ’at-Taşghīr’’ (i.e., diminutive forms), “şiyagh ’al-Mubālaghah” (i.e., maximizers) and many other forms. However, they do not use any of the aforesaid forms under the heading of ‘’at-Tadarruj bit-Tarkīz’’ (i.e., gradability by focus). Therefore, the study grounds for ‘focus’ highlighting its salient lexical, grammatical, and morphological features in Arabic. The present paper provides definitions for gradability, focus, prototypicality and precision. Afterwards, it provides a detailed analysis of the sub-categories of prototypicality and precision unearthing their rhetorical functions. In conclusion, gradability by focus plays a key role in identifying the subtle shades of meaning. Tackling such cognitive linguistic features is of an overwhelming importance at the pure linguistic level as well as the sociolinguistic one.

The aim of the present study was to examine the effect of urbanization, purchasing power, and income on motorcycle ownership and the effects of interactions between these factors. Specifically, we examined how the inverse-U relationship between motorcycle ownership and economic development changed in response to different levels of purchasing power and urbanization. We apply a fixed effects negative binomial panel regression analysis on a panel data of 73 countries between 1963 and 2013. Results revealed evidence of an inverse-U relationship between purchasing power and motorcycle ownership. Motorcycle ownership increases during the beginning stages of consumer price index (CPI), due to higher purchasing power. Once a threshold level was exceeded, higher CPI (lesser purchasing power) created an inverted effect, which led to a decline in motorcycle ownership. Importantly, the turning point increased in accordance with an increase in urbanization. The estimation results also suggested that the inverse-U relationship between motorcycle ownership and per capita GDP varied in accordance with both purchasing power and urbanization.

Background: Due to the high prevalence and wide distribution of coronaviruses, their large genetic diversity, frequent recombination of their genomes, and increasing human-animal interface activities, novel coronaviruses are likely to emerge periodically in humans owing to frequent cross-species infections and occasional spillover event. Objectives: The aim of this research is to study the short-term morbidities, mortalities and trends of international spread of the COVID-19 outbreak. In addition, to study the explosiveness and aggressiveness of the outbreak and the gaps in response. Methodology: Outbreak events were observed and followed up over two months. This study used daily statistical reports issued by the World Health Organization, as well as data from different national authorities, regarding mortalities and morbidities from all over the world, with a specific focus on Chinese statistics as the main source of the outbreak. Results: The current study showed that the number of confirmed COVID-19 infected cases started with 41 cases in early January 2020. The number of cases with COVID-19 kept rising to reach 128000 on March 12, 2020. Moreover, the current study has revealed that the number of deaths was only (1) case in early January 2020 and increased to 25 deaths on January 23, and end up with 170 deaths by the end of January. Deaths have dramatically increased to reach 2462 on Feb 23 and 4717 on March 12. In regards to the geographical spread of the COVID-19 infection outbreak, the number of affected countries increased to 100 by mid- March 2020. The number of fatality cases was 0.0368, compared to 0.533 in recovered cases within two months. Conclusion: The natural history and course of the current outbreak revealed a highly explosive nature linked to considerable aggressiveness in terms of complications and mortalities, within only two months, and spread to 100 countries worldwide with 80000 cases within only two months. The study forecasted that the peak of the outbreak is not yet attained, and events that are more dramatic may occur worldwide.

BACKGROUND: Non-communicable diseases (NCDs) are the leading causes of death worldwide. In the UAE, NCDs account for nearly 77% of all deaths. There is limited empirical research on this topic in the UAE. We aimed to examine the association of non-communicable diseases and the sociodemographic characteristics among the adult population of Dubai. METHODS: The study used secondary data from the Dubai Household Health Survey (DHHS), 2019. DHHS is a cross-sectional complex design, stratified by geographic area, and uses multistage probability sampling. In this survey, 2247 families were interviewed and only adults aged 18+ were included for the analysis. The quasi-binomial distribution was used to identify the socio-demographic characteristics association with NCDs. RESULTS: The prevalence of NCDs among the adult population of Dubai was 15.01%. Individuals aged 60+, local Arabs (Emirati), divorced and widowed individuals, and individuals who were not currently working reported NCDs more than the other groups. In the regression analysis, the association with NCDs were reported among elderly people, males, unmarried individuals, older individuals who are unmarried, and Emiratis. CONCLUSION: The study identified several socio-demographic characteristics associated with reporting NCDs. This is one of the few studies related to NCDs in Dubai. Allocating appropriate resources to the population groups identified is crucial to reduce the incidence of NCDs in the Emirate.

Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive and integration framework. This paper reviews complex network theory related knowledge and discusses its applications in urban traffic network studies in several directions. This includes network representation methods, topological and geographical related studies, network communities mining, network robustness and vulnerability, big-data-based research, network optimization, co-evolution research and multilayer network theory related studies. Finally, new research directions are pointed out. With these efforts, this physics-based concept will be more easily and widely accepted by urban traffic network planners, designers, and other related scholars.