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Association of birth weight with blood pressure and renal function variables in children aged 3 to 6 years
Full text linkINTRODUCTION:Intrauterine growth retardation (IUGR) has recently been related to an increase in blood pressure figures in different countries.OBJECTIVEThe objective of this research was to evaluate the relationship between blood pressure and kidney function with birth weight in children aged 3 to 6 years.MATERIAL AND METHODSThirty-two healthy, normotensive children with a history of low birth weight due to IUGR or normal birth weight, aged between 3 and 6 years, were studied in the Marianao municipality of Havana. Their nutritional status was determined based on their body surface area, using the Haycock formula expressed in square meters. Arterial, systolic and diastolic pressures were measured using the Riva Rocci-Korotkoff method, calculating the average. Glomerular filtration rate (GFR) was determined using the Schwartz 2 formula (GFR WS) and Pottel for serum creatinine and for serum Cystatin C using Pottel. The renal and blood pressure variables were adjusted to body surface area and analyzed using Pearson\u27s correlation. Ethical standards for research on humans were respected.RESULTSSystolic, diastolic and mean arterial pressures, as well as GFR, were inversely correlated with birth weight. Children with a history of low birth weight due to IUGR presented higher blood pressure values, although not pathological with respect to their peers; the IFG values in this group of children were higher with respect to their peers, calculated both by creatinine through the Pottel method and serum Cystatin C.CONCLUSIONThere is a tendency for higher blood pressure values in children with low birth weight due to IUGR. The correlation between IFG and birth weight supports theories about the influence of hyperfiltration on high blood pressure, so we suggest more extensive studies of the variables studied, as well as the use of the Pottel formula for its study
Thermodynamic and Kinetic Assessment of Cobalt II Adsorption Using Green Synthesized NiO/γ-Al2O3 Nanoparticles
Full text linkIntroduction: Disposal of heavy metals into the water as a result of industrial development might cause a threat Health and the environment. aim of this study was to assess the uptake of Co2+ from aqueous solutions via NiO/ γ-Al2O3 nano catalysts. Methods: The main variables that affect the percentage of metal removal were assessed. It took about 50 minutes to attain equilibrium for the elimination of Co+2 ions. It was discovered that raising the adsorbate concentration and increasing the surface weight somewhat lowered the removal of cobalt ions. Results: The removal of cobalt ions was shown to depend on temperature,due to ecothermic natural of this prosess increasing temperature associated with decrease the elemination . Conclusions: The adsorption seems to be spontaneous, exothermic, and less random according to calculated values of the thermodynamic functions (∆G, ∆H, and ∆S) of the adsorption. After the data were fitted into a number of kinetic models, including the Elovich model, pseudo-first order, pseudo-second order, and intraparticle diffusion equations, it was discovered that the pseudo-second-order model performed the best at describing the adsorption, with a high correlation factor (R2).
Research on Employability Enhancing Strategies for Students in Ordinary Undergraduate Colleges and Universities
Full text linkIntroduction: This study aims to analyze the various factors influencing the employability of students in ordinary undergraduate institutions and to propose targeted strategies for improvement.Methods: The research examines key determinants of employability, including educational background, vocational skills, and social resources. Through a comprehensive investigation of the employment status of college graduates, the study employs reliability testing and principal component analysis to identify pivotal variables affecting employability.Results: The analysis reveals several key factors impacting the employability of ordinary undergraduate students. These include the alignment of educational curricula with market demands, the adequacy of vocational training, and the availability of social networks and resources.Conclusions: In light of the findings, the study recommends strategies to improve employability, such as optimizing curricula, enhancing career guidance services, and promoting personalized training programs. These recommendations aim to bolster the employment competitiveness of graduates from ordinary undergraduate colleges and universities, providing a theoretical framework for educational reforms and supporting graduate employability initiatives
Exploring contemporary socio-cultural shifts in Ukraine and their effects on strengthening national identity and resilience in times of war
Full text linkEstablishing a Ukrainian political nation is contingent upon a complex set of circumstances. Ukraine is compelled to wage a war against Russia for its independence, sovereignty, and territorial integrity. In such times, national self-identification becomes pivotal in consolidating efforts across all resistance fronts. The formation of Ukrainian identity is complicated by the dichotomy within Ukraine\u27s socio-cultural space, where Russian culture, alongside Ukrainian, has had significant influence. Russia\u27s full-scale aggression has facilitated the ultimate dissolution of Russian influence on the self-identification of Ukrainians. This article aims to identify the main socio-cultural trends that influence the transformation of national identity and resilience in Ukraine. Constructivism serves as the principal methodological approach to the research, enabling the analysis of the critical elements of national identity during its formation and development. The research methods include document analysis and sociological data, case studies, comparison, synthesis, deduction, generalisation, and systematisation. The findings of the research indicate that the war has significantly impacted the self-identification processes of Ukrainians, hastening the decolonisation of Ukraine\u27s socio-cultural space. Ukrainians are creating distance from Russian influences, including its culture and cultural outputs like music, literature, and cinema. There is a notable shift towards the use of the Ukrainian language and the gradual adoption of Ukrainian and European symbols over Russian ones. These changes are fostering a more robust national identity, enhancing the societal aspect of this identity, and catalysing a shift from feelings of inferiority to a rise in national pride and patriotism.
Using Adobe Creative Cloud to create multimedia content in higher education institutions
Full text linkIntroduction: Digital content is a powerful tool for enhancing students’ interest in the learning process. The aim of the work is to determine the effectiveness of using Adobe Creative Cloud to create multimedia content in higher education institutions (HEIs).
Methods: He research employed the methods of observation, deduction, Thurstone scale, calculations of priority coefficient, knowledge coefficient and Student’s coefficient.
Results: It was established that during training, Adobe Creative Cloud can be used to conduct theoretical and practical classes and develop students’ creative skills. It was established that charts ( 1.2) and illustrations ( 1.1) have the greatest importance in the created content for students’ perception. Textual information is less important for the perception of educational materials ( 0.73). The students were found to perceive learning using Adobe Creative Cloud at a high level, which is associated with not overloading students with unnecessary materials and ensuring visual perception. The authors determined that students of Group 1 (Software Engineering) and Group 2 (History) achieved high academic results — ( =1.01), ( =1.0), respectively.
Conclusions: The practical significance of the work is the possibility of expanding students’ approaches to building professional competence on the basis of content created using Adobe Creative Clou
The Concept of Interactive Arabic Learning Media Uses the First-Person Shooter Gamification Method
Full text linkArabic was a fundamental language for studying and advancing knowledge in the Qur\u27an and Hadith, which are essential guides for Muslims. This research aimed to develop a gamification concept using 3D First-Person Shooter (FPS) game technology for Arabic language learning in Integrated Islamic Elementary Schools (SDIT) in East Java. The study employed a Research and Development (R&D) approach combined with the waterfall model in the Software Development Life Cycle (SDLC). The results indicated that the concept and design of interactive Arabic learning media based on the first-person shooter gamification method using the flow of the Mechanic Dynamic Aesthetic (MDA) framework method have been successfully developed well and can be employed to aid teachers in developing easily Arabic-comprehensible teaching media for students. In conclusion, this game-based learning media was expected to improve the effectiveness and enjoyment of learning Arabic while increasing students\u27 interest in Arabic language learning
Deep learning vs. conventional methods for parkinson\u27s disease diagnosis: a systematic review
Full text linkA neurological condition called Parkinson\u27s disease (PD) primarily affects movement, but it can also have an impact on speaking, thinking, and a host of other bodily processes. Machine learning models can be trained by systems to examine clinical data, genetic information, speech patterns, and even speech patterns in order to identify early indicators of Parkinson\u27s disease before symptoms manifest. One of the main issues with machine learning models is their inability to handle inconsistent, noisy, or missing input, which can have a negative effect on the model\u27s performance. By building a system that supports both transfer learning techniques and multi-modal fusion, these shortcomings can be addressed. In order to determine the model\u27s efficacy, this study examines many deep learning techniques based on speech, image, and handwritten patterns. In order to improve diagnosis accuracy, deep learning techniques can look at complex data patterns from a range of sources, such as speech, signals, images of medical conditions, and walking patterns. By using convolutional neural networks, recurrent neural networks, and transfer learning, deep learning models are able to identify Parkinson\u27s disease early on, monitor its progression, and offer personalized treatment. Traditional Parkinson\u27s disease diagnosis techniques rely on manually defined features extracted from a range of data sources, such as speech, gait, and medical images. These characteristics are subsequently incorporated into machine learning models. To automatically detect and extract aspects of Parkinson\u27s disease, deep learning approaches make use of transfer learning and end-to-end learning.
Impact of Various Social Media Marketing Dimensions on Intention to Purchase Electronic Goods
Full text linkThis paper discusses the intention of consumers to purchase electronic devices using structural equation modeling, or SEM. This is based on an analysis of data from 221 respondents. This cross-sectional study shows that Purchase Intention (PI) of electronic devices is highly influenced by Customization (CUS), Online Community (ONC), Brand Equity (BEQ), and Electronic Word of Mouth (E-WOM). This study was completed using the structural equation modeling (SEM) and hypothesis testing approaches. The goal of this study is to show how important it is to determine whether SMM is acceptable in today\u27s culture. It also goads businesses to put even more effort into maximizing social media marketing techniques to enhance online visibility
The Impact of the Shadow Economy on the Stability of the Financial System of the State
Full text linkThe problems of shadow economy and financial stability have always been a concern for both in developed and developing countries. It is important for policymakers trying to create economic resilience and stability to understand how the shadow sector affects finances. This aim of this research is to examine the impact of shadow economy on macroeconomic factors such as GDP growth, inflation and interest rate. The study also analysed the impact of the shadow economy on financial stability in different countries. The research employs econometric analysis, including panel data regression, structural equation modelling, and case studies to reveal these dynamics. Model specifications are determined using lagged variables, group analysis, fixed and random effects models, and the Hausman test. Direct and indirect effects are estimated simultaneously using structural equation modelling, showing that shadow economic activity plays a mediating role in the financial sphere. The results show that deeper shadow economy reduces stability and undermines it particularly strongly in countries with a large shadow sector. It was proved that countries with a small size of shadow economy demonstrate a higher financial stability. This study emphasizes the need to create effective rules and strategies to integrate that share of shadow economies into the generally accepted. Further research may focus on examining the long-term impact of shadow economy on financial stability across economic cycles
Artificial intelligence and its impact on tourism spending and revenues in Jordan
Full text linkIntroduction: The present research investigates the application of tourism AI in Jordan by analyzing the periods from 2020 to 2027. Follow-up research targets destinations to, let\u27s say, market it better and raise the quality of customer service in the scope of tourism activities to increase tourism expenditures. also addresses the optimization of tourist spending by utilizing smart recommendations and data analysis to improve the quality of the services offered.Method: The paper attempts to analyze the gap between the actual figures for tourist expenditure and tourism revenue in 2020, especially 2023, and the expected figures when AI is utilized in central tourism AI in 2024 and 2027. The application of automation systems can cut down costs and give businesses a lean operating framework, which in return allows for more profits to be generated, and this is more important regarding the growth of the tourism economy of Jordan as a whole. Results: This research endeavored to use regression, correlation, structural modeling, variance, and other statistical analyses to test the hypotheses regarding the effects of artificial intelligence on tourism. Conclusion: The final submission implicates the way forward for enhancing the effectiveness of artificial intelligence investment in Jordan\u27s tourism sector to boost competitiveness and make revenue growth