The study examined the socio-demographic factors affecting access to and utilization of social welfare services in Yenagoa Local Government Area of Bayelsa State, Nigeria. Quantitative and qualitative approaches were adopted to select 570 respondents from the study area. Probability and non-probability sampling techniques were adopted in the selection of communities, and respondents. The quantitative data were analyzed using frequency distribution tables and percentages, while chi-square statistic was used to determine the relationship between socio-demographic variables and access to and utilization of social welfare services. The qualitative data were analyzed in themes as a complement to the quantitative data. This study reveals that although all the respondents reported knowing available social welfare services, 44.3% reported not having access to existing social services due to factors connected to serendipity variables, such as terrain condition, ethnicity and knowing someone in government. Therefore, the study recommends that the government and other stakeholders should push for the massive delivery of much-needed social welfare services to address the issue of welfare service deficit across the nation, irrespective of the ethnic group and whether the community is connected to the government of the day or not, primarily in rural areas.

Based on the population change data of 2005–2009, 2010–2014, 2015–2019 and 2005–2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of shrinking cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the shrinking cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.

The flipped classroom (FC) model has long brought significant benefits to higher education, secondary, and elementary education, particularly in improving the quality and effectiveness of learning. However, the implementation of FC model to support elementary students in developing self-learning skills (autonomous learning, independent study, self-directed learning) through technology still faces numerous challenges in Vietnam due to various influencing factors. Data for the study were collected through direct questionnaires and online surveys from 517 teachers at elementary schools in Da Nang, Vietnam. Based on SEM analysis, the study identified factors such as perceived usefulness, accessibility, desire, teaching style, and facilitating conditions. The research findings indicate that factors like the perceived effectiveness of the model, teaching style, and facilitating conditions have a positive correlation with the decision to adopt the FC model. Therefore, to encourage the use of the FC model in teaching, it is essential to raise awareness of the model’s effectiveness, improve teaching styles, and create favorable conditions for implementation.

This study aims to elucidate the digital transformation process in Tunisian companies, identify its driving factors, and explain its key success factors. We examine a sample of 70 companies across various economic sectors using a Multinomial Logistic regression to assess the impact of digital strategy, corporate culture, and leadership on digital transformation success. The dependent variable “digital maturity” is categorized into low, medium, and high, with medium serving as the reference category. The results indicate a significant and positive effect of digital strategy on digital transformation success. Leadership influences companies at a low level of digital maturity but does not significantly impact those at a high maturity level. Corporate culture does not significantly affect digital transformation. Digital strategy is crucial for the success of digital transformation in Tunisian companies, while leadership plays a role primarily at lower maturity levels. Corporate culture, however, does not significantly contribute to digital maturity. The study provides insights for Tunisian companies and policymakers to focus on developing robust digital strategies and leadership qualities to enhance digital transformation efforts. This research expands the theoretical base on digital transformation in the Tunisian context, identifying critical success factors and barriers, and confirming the significant role of digital strategy in successful digital transformations.

In higher eukaryotes, the genes’ architecture has become an essential determinant of the variation in the number of transcripts (expression level) and the specificity of gene expression in plant tissue under stress conditions. The modern rise in genome-wide analysis accounts for summarizing the essential factors through the translocation of gene networks in a regulatory manner. Stress tolerance genes are in two groups: structural genes, which code for proteins and enzymes that directly protect cells from stress (such as genes for transporters, osmo-protectants, detoxifying enzymes, etc.), and the genes expressed in regulation and signal transduction (such as transcriptional factors (TFs) and protein kinases). The genetic regulation and protein activity arising from plants’ interaction with minerals and abiotic and biotic stresses utilize high-efficiency molecular profiling. Collecting gene expression data concerning gene regulation in plants towards focus predicts an acceptable model for efficient genomic tools. Thus, this review brings insights into modifying the expression study, providing a valuable source for assisting the involvement of genes in plant growth and metabolism-generating gene databases. The manuscript significantly contributes to understanding gene expression and regulation in plants, particularly under stress conditions. Its insights into stress tolerance mechanisms have substantial implications for crop improvement, making it highly relevant and valuable to the field.

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.