The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.

The objective of this study is to examine the extent of awareness, intention, and behavior among university students in relation to green marketing. It is recognized that the present cohort of students, as well as future generations, will have a substantial impact on shaping the course of the world. The respondents for this study consisted of university students, and the collected data was subsequently analyzed using SPSS (Statistical Package for Social Sciences) 25 in order to test the stated hypothesis. University students exhibit a comprehensive understanding of green marketing and a conscious inclination toward embracing favorable intentions and behaviors in relation to this domain. The results of this study suggest that there exists a statistically significant and positive correlation between individuals’ level of green awareness and their intention to participate in environmentally friendly consumer practices. Furthermore, it has been observed that the intention of consumers to engage in green practices has a noteworthy influence on their subsequent behavior in terms of adopting environmentally friendly behaviors. The findings obtained from studies on green marketing are of utmost importance in offering valuable guidance and orientation toward a future characterized by heightened environmental awareness and sustainability. The novelty of this study is to provide a lucid comprehension of students’ perceptions about green marketing. Several factors can potentially impact the intention and behavior of environmentally conscious consumers, including personal values, social norms, and economic factors. Additional research is necessary in order to obtain a more thorough comprehension of the complexity of these variables, and how they interact to impact consumer behavior.

The present study demonstrates the effect of direct solar drying (DSD) and hot air drying (HAD) on the quality attributes of Fuji apple slices. DSD samples took a longer time (150–180 min) to dry and simultaneously reached higher equilibrium moisture content at the end of rehydration than HAD samples. DSD samples have higher rehydration ability, dry matter holding capacity, and water absorption capacity than HAD samples. Among several empirical models, the Weibull model is the best fit with higher R² (0.9977), lower root mean square (0.0029), and chi-square error (0.0031) for describing the rehydration kinetics. Rehydrated HAD samples showed better color characteristics than DSD in terms of overall color change, chroma, and hue angle values. Whereas the hardness and chewiness of rehydrated DSD samples were better than HAD samples because of higher dry matter holding capacity in DSD. Apart from color retention, the DSD samples showed better rehydration capacity and a good texture upon rehydration than HAD slices.

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.

Border cities face significant challenges due to political, environmental, and social issues. Strong urban governance can help resolve many of these problems, but it requires identifying practical factors specific to each city’s location. This study aimed to assess the state of urban governance in Paveh, a border city with a population of 25,771 people. The research used both primary data collection (through a questionnaire) and secondary data sources (local and national databases and documents). The study randomly selected 379 households from Paveh’s population and determined a reliability value of 0.913 using the Cochrane procedure. To assess Paveh’s urban governance, eight criteria were used: participatory, rule-of-law compliance, transparency, responsiveness, consensus-oriented, equitable and inclusive, effective and efficient, and accountability. The findings revealed that Paveh’s urban governance, particularly in the dimensions of transparency and participation, is in an unfavorable situation.