Census 2022 of Saudi Arabia was released recently, with 12 years of intercensal interval. Although it appeared provisional having no reports similar to the 2010 census, efforts to analyze, interpret, disseminate, and discuss were essential for building structures and systems at par with demographic trends and patterns. An analysis was carried out with this census data compared to 2004 and 2010 to track population change—demographic pace, trends, and patterns—over the two decades. Data from all three censuses were analyzed with conventional demographic techniques. A reduction in growth was observed with a declining percentage of the childhood population but with an expanding percentage of the adults (working age) indicating a demographic dividend resulted, mostly, from fertility decline. An aging trend established by the previous censuses was lost, recently: the constriction of the pyramid of 2010 was changed to a different shape. Not only the percentage distribution trends were uneven but also the age-based indices. Thus, these trends revealed a demographic difference to an extent, that demands standardized reports, uniform procedures for the data collection and compilation, and geographic distribution equations. The increasing concentration in urban centers of major administrative areas—Al-Riyadh, Makkah Al-Mokarramah, and the Eastern Region demand redistribution policies. Self-contained townships appear as a strategic option in population redistribution, guaranteeing quality standards and lifestyle.

This research uses both quantitative and qualitative research methodologies to examine the complex factors affecting community resilience in various settings. In this case, the research explores how social cohesion, governance effectiveness, adaptability, community involvement, and the specified difficulties influence resilience results by using the five pillars of resilience as variables. Descriptive and inferential statistics are used to test hypotheses on the relationships between social cohesion, governance effectiveness, adaptive capacity, and community resilience variables. Qualitative data provides further insights into the quantitative results by providing broader views and experiences of the community. The study shows how social capital is important in increasing community capacity, stressing the importance of social relations and trust in developing community solutions to disasters. Another major factor that stands out is the governance factor that ensures that decisions are made, and actions taken in line with the community’s best interest in improving its ability to prepare for and respond to disasters. Adaptive capacity is seen as a key component of resilience and this paper emphasizes the importance of communities to come up with measures that can be adjusted to the changing circumstances. In summary, this study enriches theoretical understanding and offers practical applications of the processes that can enhance community resilience based on the principles of social inclusion, sound governance, and context-specific solutions.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.

This qualitative research aimed to study the effectiveness of the local health constitution in controlling the spread of COVID-19. It reports the role of local communities, government agencies, and healthcare providers in implementing and enforcing local health constitutions and how their engagement can be improved to enhance surveillance. We also reported factors that influence compliance and strategies for improving compliance. We also evaluated the long-term sustainability of local health institutions beyond the pandemic. The population and sample group consisted of key members of the local health constitution teams at the provincial, sub-district, and village levels in the rural area of Ubon Ratchathani. Participants were purposively selected and volunteered to provide information. It included health science professionals, public health volunteers, community leaders, and local government officials, totaling 157 individuals. The study was conducted from December 2022 to September 2023. Our research shows that local health constitutions can better engage and educate communities to actively participate in pandemic surveillance and prevention. This approach is a learning experience for responding to emergencies, such as new infectious diseases that may arise in the future. This simplifies the work of officials, as everyone understands the guidelines for action. Relevant organizations contribute to disease prevention efforts, and there is sustainable improvement in work operations.

Magnetite magnetic nanoparticles (MNP) exhibit superparamagnetic behavior, which gives them important properties such as low coercive field, easy superficial modification and acceptable magnetization levels. This makes them useful in separation techniques. However, few studies have experimented with the interactions of MNP with magnetic fields. Therefore, the aim of this research was to study the influence of an oscillating magnetic field (OMF) on polymeric monolithic columns with vinylated magnetic nanoparticles (VMNP) for capillary liquid chromatography (cLC). For this purpose, MNP were synthesized by coprecipitation of iron salts. The preparation of polymeric monolithic columns was performed by copolymerization and aggregation of VMNP. Taking advantage of the magnetic properties of MNP, the influence of parameters such as resonance frequency, intensity and exposure time of a OMF applied to the synthesized columns was studied. As a result, a better separation of a sample according to the measured parameters was obtained, so that a column resolution (R_s) of 1.35 was achieved. The morphological properties of the columns were evaluated by scanning electron microscopy (SEM). The results of the chromatographic properties revealed that the best separation of the alkylbenzenes sample occurs under conditions of 5.5 kHz and 10 min of exposure in the OMF. This study constitutes a first application in chromatographic separation techniques for future research in nanotechnology.