Articles

<b>Background:</b><b> </b>Educational attainment is generally associated with reduced reliance on Social Security and disability benefits; however, the Minorities' Diminished Returns (MDRs) theory suggests that the socioeconomic benefits of education are weaker for minoritized populations. This study investigates the relationship between educational attainment and welfare receipt among American Indian/Alaska Native (AIAN) and White adults in the United States. <b>Objective:</b><b> </b>Using the MDRs framework, we analyzed data from the National Health Interview Survey (NHIS) 2023 to examine how educational attainment impacts welfare receipt among AIAN and White adults. <b>Methods:</b><b> </b>We analyzed a nationally representative sample of AIAN and White adults from the NHIS 2023 dataset. Welfare receipt was assessed as the receipt of any public assistance or welfare payments from state or local welfare offices. Educational attainment was categorized into three levels: less than high school (reference), high school diploma to some college, and college degree or higher. Logistic regression models were used to assess the relationship between educational attainment and welfare receipt, with separate analyses for AIAN and White adults to evaluate differential effects. <b>Results:</b> Higher educational attainment (high school diploma to some college and college degree or higher) was associated with lower odds of welfare receipt across both groups. However, the protective effect of a college degree was significantly weaker for AIAN adults compared to White adults. Consequently, AIAN adults remain at a higher risk of welfare reliance even with higher education, consistent with the Minorities' Diminished Returns (MDRs) framework. <b>Conclusions:</b> Although educational attainment generally reduces welfare reliance, this protection is less pronounced for AIAN adults than for White adults. This discrepancy suggests that structural factors, segregation, and social stratification may undermine the economic and health benefits of education for racialized groups in the U.S. Addressing these disparities requires policy interventions that extend beyond education, emphasizing quality job opportunities, healthcare access, and reduced labor market discrimination for individuals with advanced educational credentials, regardless of race.

<b>Background: </b>Research on Minorities’ Diminished Returns (MDRs) consistently reveals that social determinants of health, especially educational attainment, do not yield equal health benefits across racial and ethnic groups in the United States. MDRs suggest that social stratification, segregation, lower education quality, and labor market discrimination contribute to diminished health returns of education among minoritized groups. However, few studies have tested the relevance of MDRs in American Indian and Alaska Native (AIAN) populations compared to non-Hispanic White adults. <b>Objectives:</b> This study aimed to examine the strength of the inverse association between educational attainment and hypertension prevalence, hypothesizing that the protective effect of education on hypertension risk is reduced among AIAN adults relative to non-Hispanic Whites. <b>Methods:</b> Using data from the 2023 National Health Interview Survey (NHIS), we analyzed a nationally representative sample of adults aged 18 and older. Logistic regression models examined the association between educational attainment and self-reported hypertension diagnosis, stratified by racial/ethnic group (AIAN vs. non-Hispanic White). Models were adjusted for key covariates, including age, gender, income, and insurance status. <b>Results:</b> Higher educational attainment was associated with a lower prevalence of hypertension in the combined sample of AIAN and non-Hispanic White adults. However, this protective association was significantly weaker among AIAN adults compared to non-Hispanic White adults, as evidenced by a significant interaction between race and education. <b>Conclusion:</b> AIAN adults exhibit a higher prevalence of hypertension even at higher levels of educational attainment compared to non-Hispanic White adults, supporting the relevance of MDRs for AIAN populations. This finding underscores the need for public health interventions that address structural barriers and contextual factors unique to AIAN populations. Policies focused solely on educational access may be insufficient to reduce hypertension risk among AIAN adults without addressing broader social and structural inequities.

<b>Background: </b>Chronic medical conditions are major drivers of healthcare spending, morbidity, and mortality in the United States, as well as critical indicators of health disparities. The disproportionately high rates of chronic medical conditions among Black, Latino, and American Indian and Alaska Native adults compared to non-Latino Whites highlight the urgent need to examine the factors contributing to these disparities. While higher socioeconomic status is generally associated with better health outcomes, this benefit may be diminished for racialized and minoritized populations. <b>Objective:</b> This study investigates the protective effects of educational attainment and income-to-poverty ratio on the prevalence of chronic medical conditions and examines whether these effects vary across racial and ethnic groups, specifically among Black, Latino, and American Indian and Alaska Native adults compared to non-Latino White adults. <b>Methods:</b> Using data from the 2023 National Health Interview Survey (NHIS), this cross-sectional study analyzed the association between educational attainment and chronic medical conditions across racial and ethnic groups. Logistic regression models were employed to assess whether the strength of the relationship between education and chronic medical conditions differed by racial/ethnic group, controlling for key demographic and socioeconomic covariates. Sample size was 29,373 which was reflective of 256,566,689 US population. <b>Results:</b> Consistent with the theory of Minorities' Diminished Returns, findings showed that the protective effects of higher educational attainment on chronic medical conditions were significantly weaker for Black, Latino, and American Indian and Alaska Native adults than for their non-Latino White counterparts. Even among individuals with higher education, Black, Latino, and American Indian and Alaska Native adults faced elevated risks of chronic medical conditions. <b>Conclusion:</b> While educational attainment generally reduces the prevalence of chronic medical conditions, this protective effect is moderated by racial and ethnic background. Structural barriers limit the health benefits of educational attainment. This underscores the need for policies that address structural inequities—such as low-quality education and occupational segregation—that constrain the protective health effects of educational attainment for minoritized groups.

Recent field investigations, performed across some of the less floristically known sectors of Calabria, have led to the discovery of <i>Salsola tragus</i> and <i>Thymelaea gussonei</i>, two new species for the regional vascular flora. By providing crucial biogeographical and taxonomic remarks, this work aims to contribute to the improvement of the knowledge of the rich, diversified and still poorly known native flora of Calabria. The biogeographical value of these new findings underlines the decisive role of field survey in the enhancement of the information on regional biodiversity, the essential basis for every further ecological study and conservation effort.

English language has become a global language due to first, the results of British colonial expansion and, global commercial interests. It has become a lingua franca in many countries, including Ghana. Qualitatively, the study adopted case study research design. The purpose of the study was to find out the perception and the attitude of Ghanaian English teachers towards the Native Speakers’ accents. The population of study consists of all ten (10) tutors in the Department of Languages, Offinso College of Education. Purposive and convenient sampling techniques were used to select the college and the tutors for the study. The main tool used for the collection of data was the semi-structured interview. Most of the participants revealed positive attitudes towards their own English accents which were different from that of the native speaker. Ghanaians are often faced with the challenge of which accent to use when communicating with each other and with outsiders. Most of the tutors from Offinso College of Education who participated in this study expressed positive responses to their non-native speaker’s accents. Not only did the idea of having a native speaker’s accent hold no attraction for them but they also found it strange because it would not represent their L1 identity<b>. </b>The majority of participants in this study preferred to use their non-native accents to attempt to adopt those of the native speaker. To them, there is only one distinction between English accents -you are either a native or non-native.

Machine learning operations (MLOps) comprises the practices, methods, and tooling that facilitate the deployment of reliable ML models in production environments. While many aspects of cloud data platforms are designed to enable reliability, only some managed ML services support the MLOps goals of continuous integration, continuous delivery, data lineage tracking, associated reproducibility, governance, and security. Furthermore, reliability encompasses not only the fulfillment of service-level objectives, but also systematic monitoring, alerting, and incident response automation. Architectural patterns are proposed to enable reliable deployment in cloud data platforms, focusing on the implementation of continuous integration and testing pipelines for ML models and the formulation of continuous delivery and rollout strategies. Continuous integration pipelines reduce the risk of regressions and ensure sufficient model performance at the time of deployment, while continuous delivery pipelines enable rapid updates to production models within acceptable risk profiles. The landscape of publicly available MLOps frameworks, tools, and services is also examined, emphasizing the pros and cons of established and rising solutions in containerization, orchestration, model serving, and inference. Containerization and orchestration contributes to the building of reliable deployment pipelines in cloud data platforms, whether general-purpose tools (e.g. Docker and Kubernetes) or solutions tailored for ML workloads. Containerized serving frameworks designed for high-throughput, low-latency inference can benefit a wide range of business applications, while auto-scaling and model versioning capabilities enhance the ease of use of cloud-native ML services.

Cloud native ETL pipelines support the extract and transform phases of real time claims processing in large scale insurers. The cloud native approach offers dramatic improvements in scalability, reliability, resiliency and agility as well as seamless integration with the diverse set of data sources, destinations and technologies characteristic of large scale insurers. The ETL process extracts data from source systems such as core transaction, fraud, customer and accounting processes, transforms the data to create a usable format for analytics and other applications, and loads the resulting tables into business intelligence or data lake systems for subsequent storage and analysis. By addressing these two phases of the overall ETL process, cloud native ETL pipelines can provide timely, reliable and consistent data to data scientists, actuaries, underwriters and other analysts. Real time processing represents a key priority within the overall claims process: faster, more accurate claim approvals reduce insurer costs, improve customer service and enhance premium pricing. As a result, a variety of claims related use cases are moving from batch to real time.

Calabria is a floristic hotspot just at the center of Mediterranean Sea. Unfortunately, an increasing number of alien plant species threats this natural heritage, exactly while the crucial role of botany in secondary schools of Italy has been definitely dismantled. Calabrian Native Project is an environmental education project planned by Istituto Tecnico Agrario of Catanzaro that, reintroducing some key concepts of botany and biogeography, allowing pupils to experience a botanical excursion in the close-to-the-school Mediterranean Biodiversity Park, gives them the opportunity to become acquainted with both native and alien species. Pupils are asked to collect native plant propagules and to seed or cultivate the material in the school greenhouses, and to take care of these plants until their use. The prevalent outdoor and laboratory approach to the issue of bioinvasions, make the project very effective. This feature, with the low cost and reduced technology inputs, make the project highly replicable in other contexts, just focusing appropriate target species.

To ensure maximum flexibility, service providers offer a variety of computing options with regard to CPU, memory capacity, and network bandwidth. At the same time, the efficient operation of current cloud applications requires an infrastructure that can adjust its configuration continuously across multiple dimensions, which are generally not statically predefined. Our research shows that these requirements are hardly met with today's typical public cloud and management approaches. To provide such a highly dynamic and flexible execution environment, we propose the application-driven autonomic management of data center resources as the core vision for the development of a future cloud infrastructure. As part of this vision and the required gradual progress toward it, we present the concept of composable infrastructure and its impact on resource allocation for multi-cloud environments. We introduce relevant techniques for optimizing resource allocation strategies and indicate future research opportunities [1]. Many cloud service providers offer computing instances that can be configured with arbitrary capacity, depending on the availability of certain hardware resources. This level of configurability provides customers with the desired flexibility for executing their applications. Because of the large number of such prerequisite instances with often varying characteristics, service consumers must invest considerable effort to set up or reconfigure elaborate resource provisioning systems. Most importantly, they must differentiate the loads to be distributed between jobs that need to be executed versus placeholder jobs, i.e., jobs that trigger the automatic elasticity functionality responsible for resource allocator reconfiguration. Operations research reveals that the optimization of resource allocator reconfiguration strategies is a fundamentally difficult problem due to its NP-hardness. Despite these challenges, dynamic resource allocation in multi-clouds is becoming increasingly important since modern Internet-based service settings are dispersed across multiple providers [2].

The continuous integration (CI) and continuous delivery/deployment (CD) methods are key tools in the field of modern software development, and they assist in the rapid, reliable and quality delivery of software. These DevOps methods are automated, and the code development, testing, and deployment processes are streamlined, which reduces the risk of integration, enhances productivity, and minimizes human labor. To implement CI/CD, Java cloud applications can utilize cloud-native services such as AWS Code Pipeline, Azure DevOps, and Google Cloud Build, as well as tools like Jenkins, GitLab CI/CD, GitHub Actions, CircleCI, Travis CI, and Bamboo. Basic concepts of CI/CD include automation, regular integration, testing, intensive testing, constant feedback, and process improvement. Some of the major pipeline phases include deployment, monitoring, testing, artefact management, build automation, and source code management. Despite clear benefits, challenges remain, including infrastructure complexity, dependency management, test reliability, and cultural barriers, particularly in large-scale or enterprise Java projects. This work provides a thorough analysis of CI/CD procedures and resources, including frameworks, best practices, and challenges for Java cloud applications. It highlights strategies to optimize adoption, improve software quality, and accelerate delivery cycles.

Native Middle Egypt Rabbit breed (NMER) was crossbred with Gaint Flander rabbits to create a synthetic line. This study was aimed to evaluate the genetic estimates of this synthetic line with comparing to the purebreds. A crossbreeding was carried out by mating bucks of Gaint Flander (G) with does of NMER (N) to get F1 (½N½G), then does and bucks of F1 were mated to get F2 (½N½G)2, followed by two generations of inter se-mating to get a new synthetic line is called Egy-line with a genetic structure of ((½N½G)2)2. Heritability estimates for body weights were generally moderate and ranged from 0.10 to 0.24, while the estimates of heritability for growth rate were low and moderate and ranging from 0.01 to 0.23. Common little effects of body weight were large as weaning (0.61), then declined gradually as the rabbit grew older. Also, the same trends were observed for relative growth rate (RGR). The direct additive effects were positive and highly significant for all body weights at different ages, favoring Gaint Flander and heavier comparing with NMER rabbits. Most relative growth rates during different intervals were non-significant. Gaint Flander was highly significant and heavier in maternal additive effects it in different weeks of age comparing with NMER rabbits. Direct heterosis effect for most bodyweight was positive and highly significant, and percentages of direct heterosis increased generally with the advance of age. Maternal heterosis for growth rates from 5 to 6, 8 to 10, and 10 to 12 week was positive, only. Direct recombination effects for most bodyweight were positive and highly significantly exclude weight at 5 and 6 weeks. It is concluded that a new synesthetic line (Egy-line) has proven its superiority and performance well in all different body weights and most growth rates compared to other parents and crossbreds.

The supply chain ecosystem plays a very important role in the success or failure of organizations, markets, and economies. Supply chain ecosystems are broadly defined as supply chain organizations and their collaborators. Today's combined challenges of pandemic shutdowns, rising internet usage, and skyrocketing climate change concerns demand that the supply chain ecosystem better connect with customers, when and how they want, to provide products and services with high levels of availability and zero defects, yet collaboratively do this to reduce transportation and production risks, often at the same time reducing operational costs and carbon footprints. Addressing these challenges, this work explores the cloud delivery capabilities of cloud-native architectures to enable the big data integrations and analytics that are needed to grow smarter supply chain ecosystems. This work describes what smart supply chain ecosystems are and how they are planning to grow their technology and integration capabilities. Discussing the industry-leading advanced and manufacturing technology producer ecosystems, it is explained how their technology collaboration and investment plans are driven by climate change and job creation goals. With these background models, the work examines the new digital reality of customer-driven experiences and economies that are demanding cloud-native and intelligent technology partnerships to deliver climate objectives, operational responsiveness, and compatibility to avoid trading economies of scale for economies of integration. The final objectives of this paper are to share key ideas about the need to balance the growing customer service direct-to-consumer business models with those for collaborative investment by market and industry. In doing this, it hopes to promote an intelligent supply chain ecosystem foundation for helping its different participating countries survive and thrive in the digital economy.