Associations between total, free and bioavailable 25-hydroxyvitamin D forms with adiponectin and irisin in maternal-neonatal pairs at birth from Greece

Background: Apart from the well-established skeletal effects, vitamin D has been explored as a secretagogue influencing various adipokines, including adiponectin and irisin. Recent evidence suggests that specific forms of 25-Hydroxyvitamin D (25(OHD), such as free and bioavailable 25(OH)D, may provide more accurate measurements of vitamin D status. The relationship between vitamin D status and serum irisin and adiponectin concentrations remains largely unexplored, particularly during pregnancy. Methods: We analyzed data from 67 healthy maternal-neonatal pairs from Northern Greece at birth. Biochemical and hormonal tests were conducted on each maternal-neonatal pair. The vitamin D forms were estimated using validated mathematical models. Subsequently, regression analyses were conducted to determine the association between the vitamin D forms and adipokine levels. Results: Bioavailable maternal 25(OH)D was inversely associated with neonatal irisin concentrations [β=-73.46 (-140.573 to -6.341), p=0.034]. No other associations were observed between maternal vitamin D status and neonatal adipokine concentrations. Conclusion: In conclusion, maternal bioavailable vitamin D concentrations are inversely associated with neonatal serum irisin concentrations, warranting further studies to evaluate the underlying mechanisms for this finding

A sentiment analysis approach for understanding users’ perception of metaverse marketplace

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace\u27s revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding security and privacy within the Metaverse, pointing to a critical area for development and assurance. The study also reveals a substantial neutral sentiment, reflecting users’ cautious but interested stance, particularly regarding the marketplace\u27s role in investment and passive income opportunities. This balanced view underscores the evolving nature of user perceptions in this emerging field. Theoretically, the research enriches the discourse on technology adoption, particularly in virtual environments, by highlighting perceived benefits and enjoyment as significant adoption drivers. These insights are invaluable for stakeholders in the Metaverse Marketplace, guiding the development of more secure, engaging, and user-friendly platforms. While providing a pioneering perspective on Metaverse user perceptions, the study acknowledges its limitation to Twitter data, suggesting the need for broader research methodologies for a more holistic understanding

Bernstein polynomials method for solving multi-order fractional neutral pantograph equations with error and stability analysis

In this investigation, we present a new method for addressing fractional neutral pantograph problems, utilizing the Bernstein polynomials method. We obtain solutions for the fractional pantograph equations by employing operational matrices of differentiation, derived from fractional derivatives in the Caputo sense applied to Bernstein polynomials. Error analysis, along with Chebyshev algorithms and interpolation nodes, is employed for solution characterization. Both theoretical and practical stability analyses of the method are provided. Demonstrative examples indicate that our proposed techniques occasionally yield exact solutions. We compare the algorithms using several established analytical methods. Our results reveal that our algorithm, based on Bernstein series solution methods, outperforms others, exhibiting superior performance with higher accuracy orders compared to those obtained from Chebyshev spectral methods, Bernoulli wavelet method, and Spectral Tau method

Adsorption behavior of MB dye on alginate-sepiolite biocomposite beads: Adsorption, kinetics, and modeling

This work is based on the preparation of biocomposite beads Alginate-Sepiolite using a simple preparation method. A series of materials was prepared by varying only the mass of the sepiolite in the biocomposite beads (mass of the sepiolite is varied between 0.5–1.5 g in the reaction mixture). The obtained biocomposites were characterized by XRD, FTIR, TGA, XRF, SEM, and EDX and then tested as adsorbents for the removal of Methylene Blue MB dye in an aqueous solution. To study the adsorption behavior of MB dye on biocomposites, several parameters affecting MB adsorption were investigated and discussed. The results obtained showed that the ALG-Sep composite hydrogels were well formed, and their properties were improved depending on the sepiolite content used. The kinetics and modeling results show that the adsorption process follows first-order kinetics, and the Langmuir model. It was found that the adsorption capacity of MB dye increased with the increase of sepiolite in the composite beads, and adsorption was carried out in the following order ALG-Sep(1.5) \u3e ALG-Sep(1) \u3e ALG-Sep(0.5). The maximum absorption capacity of MB dye on ALG-Sep(1.5) was qmax = 55.49 mg.g−1. Among the advantages of this biocomposite is that it is prepared from natural and non-toxic sources, and it is easily separable after adsorption, which makes it an excellent candidate for the elimination of organic pollutants in polluted waters

Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, reasoning tasks, and translation assessments to assess the model’s language capability. Additionally, GPT-4o’s vision and speech capabilities are tested through image classification and object-recognition tasks, as well as accent classification. The multimodal evaluation assesses the model’s performance in integrating visual and linguistic data. Our findings reveal that GPT-4o demonstrates high accuracy and efficiency across multiple domains in language and reasoning capabilities, excelling in tasks that require few-shot learning. GPT-4o also provides notable improvements in multimodal tasks compared to its predecessors. However, the model shows variability and faces limitations in handling complex and ambiguous inputs, particularly in audio and vision capabilities. This paper highlights the need for more comprehensive benchmarks and robust evaluation frameworks, encompassing qualitative assessments involving human judgment, as well as error analysis. Future work should focus on expanding datasets, investigating prompt-based assessment, and enhancing few-shot learning techniques to test the model’s practical applicability and performance in real-world scenarios

Mixed Criticality Reward-Based Systems Using Resource Reservation

Real-time systems mostly interact with the external world and each input operation must meet predetermined deadlines to be useful. However, in many real-time applications, a partial result is also acceptable. We developed a reward-based mixed criticality system based on the resource reservation approach to address the problem of ensuring the effective execution of low- and high-criticality tasks in both low- and high modes, even under heavy workloads. Using dedicated servers with pessimistic resource allocation for each high criticality task ensured their execution in both modes unaffected by low criticality tasks. The surplus resources are reclaimed and assigned to low critical tasks\u27 server by utilizing a greedy reclamation of unused bandwidth (GRUB) algorithm. Three strategies were suggested for server allocation to low criticality tasks: a dedicated server for all low criticality tasks, a single server for each low criticality task, and two servers (mandatory and optional) for each low criticality task. Our analysis revealed efficiency of the first approach by achieving 100% schedulability at a 1.1 target utilization, scheduling 20% and 50% more task sets than the second and third approaches, respectively. Moreover, the effectiveness of the proposed approach over existing imprecise mixed criticality approaches were demonstrated through comprehensive experimentation

Advances in Physiochemical and Molecular Mechanisms of Abiotic Stress Tolerance in Plants

Climate change has exacerbated the rate and intensity of abiotic stresses such as drought and salinity, posing significant threats to the crop growth and yield. This review comprehensively explores recent physiochemical and molecular approaches to abiotic stress tolerance in plants. It highlights the complex physiological adjustments, including stomatal regulation, osmotic balance, and altered growth patterns, that plants undergo in response to environmental stressors. The review delves into the biochemical pathways involved in stress response, notably the glyoxalase system and ascorbate-glutathione pathway, emphasizing their roles in maintaining cellular homeostasis and detoxifying reactive oxygen species. A significant portion of the review is dedicated to elucidating the molecular mechanisms underlying plant stress tolerance, focusing on the modulation of gene expression, regulation of stress-responsive genes, and the potential of genetic engineering to enhance resilience. We also discuss the contribution of secondary metabolites and both enzymatic and non-enzymatic antioxidants in mitigating the adverse effects of stress. Moreover, the review addresses the advancements in technological tools that have revolutionized our understanding of stress physiology, including genomic editing and transcriptomic analyses. The comprehensive synthesis of current research findings provides valuable insights into the development of innovative strategies to enhance plant tolerance to abiotic stress, contributing significantly to the field of sustainable agriculture and global food security in the era of climate change

An MCDA composite index of bank stability using CAMELS ratios and shannon entropy

This study uses the multi-criteria decision-analysis (MCDA) approach to construct a composite performance index (CPI) directly from the CAMELS financial ratios. The CPI has several promising characteristics, such as (i) being an absolute measure of performance that allows for adding or removing data without affecting the existing scores; (ii) employing CAMELS ratios directly in its calculation without the need for normalization or imputation of positive values; (iii) employing the dynamic weighting system of data envelopment analysis (DEA); (iv) providing more robust insights on the Vietnamese banking system under the Shannon entropy approach; and (v) can be an alternative measure of bank stability, compared to the CAMELS ratings and z-scores. Based on a rich dataset of 45 Vietnamese banks spanning from 2002 to 2020, our findings suggest that the proposed CPI could offer an overall view consistent with other approaches for measuring banking sector performance and stability and identifying specific strengths and weaknesses of banks

On deterministic approximation for nearly critical branching processes with dependent immigration

In this paper, we investigate the asymptotic behavior of a triangular array of branching processes with non-stationary immigration. In the nearly critical case, we prove weak convergence of properly normalized and scaled branching processes with immigration to a deterministic function when the immigration process is generated by dependent random variables

The right information for the right career selection: can it assist Japan to achieve agricultural sustainability?

The sustainability of farming communities in Japan has become quite challenging because of the current aging population phenomenon. This situation gets more complicated with the fact that more than 70% of secondary school youth desire to have jobs related to science and technology, and no one wishes to adopt farming as their career path. The latest studies indicate that misinformation related to agricultural farming is the main reason that youth move away from adopting farming as their career option. In this research, all three pillars of sustainability have been encircled and the youth’s perception related to typhoons and farmers’ perception related to delayed snowfall tendency in recent times have been examined by using remote sensing data. A survey was conducted to observe the career selection trends of the youth at Sapporo Kaisei Secondary School located in Hokkaido. Though the students have prior information about the farming activities related to this research, it was found that among 313 participants, no one wanted to become a farmer. The cited reasons were mainly related to misinformation. With the help of Japan Agricultural Cooperatives (JA) officials, a follow-up event was arranged at Sapporo Kaisei Secondary School, and the youth were provided with correct information related to the farming profession. A questionnaire was administered to observe the effectiveness of the event. The results indicate that once correct information was provided, around 82% (23 out of 28) of the participants either strongly agreed or agreed to adopt farming as their career path. These results indicate that appropriate career counseling should be designed after analyzing the youth’s perceptions related to the specific field and understanding the accuracy of the information that the youth has for a specific field. This can help not only to achieve agricultural sustainability but could also assist in solving the challenges associated with the persistent flat unemployment rate of Japan. Furthermore, this research indicated that contrary to youth perception related to the increased frequency and related losses from climate change-associated typhoons, there has been no significant rise in typhoons over the last 5 years. Moreover, farmers’ perceptions related to late snowfall start time over the past few years can be validated using the albedo data