Articles

</b>Background: </b>The Cingulo-Opercular Network (CON) is a crucial executive control network involved in regulating actions and facilitating higher-order cognitive processes. Resting-state functional connectivity between the CON and the Default Mode Network (DMN) plays a vital role in cognitive regulation, enabling the transition between internally focused and externally directed tasks. This study investigates whether resting-state functional connectivity between the CON and DMN mediates the effects of social determinants, such as educational opportunities and family structure, on cognitive outcomes in youth. <b>Aims: </b>This study aims to explore how CON-DMN connectivity influences the relationship between social gradients and cognition in youth. Specifically, it examines whether resting-state functional connectivity between these networks mediates the effects of educational opportunities and family structure on cognitive outcomes and seeks to uncover the neural mechanisms underlying these social gradients. <b>Methods: </b>Data were derived from the Adolescent Brain Cognitive Development (ABCD) study, a large longitudinal dataset of over 11,000 children aged 9–10 years. Cognitive outcomes were assessed using standardized NIH toolbox measures: Total Composite, Fluid Reasoning, Picture Vocabulary, Pattern Recognition, and Card Sorting. Social determinants were operationalized using indicators such as parental education, family composition, and neighborhood educational opportunities (COI). Resting-state functional connectivity (rsFC) between the CON and DMN was measured using functional magnetic resonance imaging (fMRI). Structural equation modeling (SEM) was employed to test whether CON-DMN rsFC mediated the relationship between social determinants and cognitive outcomes, adjusting for potential confounders such as age, sex, and race/ethnicity. <b>Results: </b>Stable family structure and greater educational opportunities were significantly associated with improved cognitive performance. These relationships were mediated by reduced functional connectivity between the CON and DMN. <b>Conclusion: </b>Reduced functional connectivity between the CON and DMN serves as a neural mechanism linking social gradients, such as educational opportunities and family structure, to better cognitive outcomes in youth.

Background: </b>Social determinants of health (SDOH) significantly influence health behaviors, including tobacco use among youth. Adversities such as perceived discrimination, perceived neighborhood stress, life trauma, and financial strain are stressors that may mediate the relationship between various SDOH and youth tobacco use. This study aims to investigate whether multidimensional adversities mediate the effects of SDOH on tobacco use among youth. <b>Methods:</b> Data from the Adolescent Brain Cognitive Development (ABCD) study were used to test our hypotheses. The sample included a diverse cohort of youth aged 9-10 years old followed until they were 15-16 years old. We examined the effects of baseline parental education, household income, neighborhood income, and family structure on subsequent youth tobacco use. Structural equation models were used to test if adversities (perceived discrimination, life trauma, financial strain) operate as potential mediators. <b>Results:</b> All ABCD participants were eligible for our analysis, regardless of race, ethnicity, or SDOHs (n = 11,878). The findings indicated that the effects of parental education, household income, neighborhood income, and family structure on youth tobacco use were partially mediated by adversities. Higher levels of parental education and household income were associated with lower tobacco use, and this relationship was weakened when accounting for adversities. Similarly, stable family structures and higher neighborhood income were linked to reduced tobacco use, with adversities playing a mediating role. <b>Conclusions:</b> Multidimensional adversities partially mediate the relationship between SDOH at baseline and subsequent youth tobacco use. Interventions aimed at reducing youth tobacco use should address both the social determinants and multiple adversities experienced by adolescents. Policies to improve the educational and economic situations of families, enhance neighborhood environments, and support stable family structures all reduce youth tobacco use, with lower exposure to adversities explaining this effect.

The purpose of this study was to examine the empirical analysis of lexico-grammatical features used in the rhetorical structure of the Statement of the Research Problems of Master of Philosophy theses in the Faculties of Arts and Education at the University of Cape Coast, Ghana. Qualitatively, content analysis was adopted for this study. Theses from the Faculty of Arts and the Faculty of Education at the University of Cape Coast were selected for this study. These theses were selected from 2012 to 2022 academic years to ensure currency in terms of the stipulated lexico-grammatical features used in the statement of the research problem. Purposive and simple random sampling techniques were used to select the university, two faculties (Faculty of Arts and Faculty of Education) and postgraduate theses for the study. The two faculties were purposively sampled. Eighty (80) theses were simple randomly sampled (Forty (40) theses each from the Faculty of Arts and the Faculty of Education). The main instrument used for data collection was content analysis. The data was analysed by the use of the interpretative technique based on the themes arrived at during the data collection of the statement of research problem from the post-graduate theses. The study indicated that integral citation was dominant in SRPs from the Faculty of Arts theses whereas non-integral citations were rather dominant in SRPs from the Faculty of Education theses. The use of adverbials to boost these claims was also found in only the SRPs from the Faculty of Arts theses. The use of hedging devices in SRPs from both Faculties to indicate a gap, and the use of simple noun phrases such as “<i><b>the problem</b></i>” and “<i><b>the need</b></i>” were mostly used to categorically state the research problem. It is recommended that a comparative study of theses in the two faculties in another university in Ghana be undertaken to identify how similar or otherwise the rhetorical structure and the lexico-grammatical features of the SRPs written by postgraduate students in the two faculties will be.

In Quantum Physics, the spin and angular momentum operators are magnitudes introduced by means of a vector transformation law. However, interpreting the eigenvalues of its Z "components" as projections on said axis leads to certain contradictions supposedly avoided by a mandatory (presented as a freely selected) Z's orientation. It is shown that an oriented physical space almost forces us to project the angular momentum's and spin's eigenvalues onto its orientation's 3-form, which sidesteps entering into inconsistencies. The final conclusion is that this "rare" magnitude called spin, downright naturally comes in and plays thanks to the orientation of our three-dimensional space.

Generative AI refers to deep learning technology that can automatically produce original text, images, audio, video, and other outputs. With its emerging capabilities, Generative AI can radically change the dynamics of key operational processes in most industries. In this document, we illustrate how it is possible to integrate Generative AI technologies into the Financial Reporting System (FRS) of a corporation. The integration will allow the FRS to deliver on demand concise and lucid insights to its associated users on what is happening in the corporation and different aspects of the corporation performance assessment, such as its liquidity, solvency, profitability, organizational structure, and share buy back decision. The integration will also facilitate the delivery of what-if analyses associated with different strategic and tactical decisions taken by the corporation management, such as capital budgeting and profit distribution decisions. The unique added value of several attributes of these insightful analytics is automating the responses to ongoing requests of the FRS users on the corporation. Generative AI capabilities are rapidly expanding. The integration can be applied not only for the corporate FRS but any FRS at the national or global levels delivered by a central bank or an accounting standards setter. Any of these FRS can be made into a unique “hub” for the integrated Generative AI technologies. An equally innovative possible generalized integration could put any corporate process at the center and its supporting FRS tasks and deliverables in its periphery.

Artificial intelligence systems have been previously used to predict post-operative complications in small studies and single institutions. Here we developed a robust artificial intelligence model that predicts the risk of having cardiac, pulmonary, thromboembolic, or septic complications after elective, non-cardiac, non-ambulatory surgery. We combined structured and unstructured electronic health record data from 3.5 million surgical encounters from 25 medical centers between 2009 and 2017. Our neural network model predicted postoperative comorbidities 15 to 80 times faster than classical models. As such, our model can be used to assess the risk of having a specific complication postoperatively in a fraction of a second. With our model, we believe clinicians will be able to identify high-risk surgical patients and use their good judgment to mitigate upcoming risks, ultimately improving patient outcomes [1].

This study took place in the Far North region of Cameroon. The general objective was to assess the floristic diversity of the undergrowth of Agrosystems in <i>Azadirachta</i><i> </i><i>indica</i>. The data were collected in 100 m long by 20 m wide transects surveyed in plantations of different ages. In total, 5 transects were carried out, ie a total area of 1 ha per site. The sampling bands were established using the compass, decameter, GPS and wires. The experimental set-up used was a 5-repetition split plot. A total of 7689 individuals divided into 9 families, 13 genera and 16 species have been identified. <i>Guiera</i><i> </i><i>senegalensis</i> and <i>Piliostigma</i><i> </i><i>thonningii</i> are the most common in terms of relative abundance. The analysis of the Family Importance Index (VIF) shows overall that the Combretaceae, and Mimosaceae are the most important in ecological terms. While those of the species show that <i>Guiera</i><i> </i><i>senegalensis</i>, <i>Combretum</i><i> </i><i>micranthum</i> and <i>Acacia</i><i> </i><i>nilotica</i> finally for the genera, it is Acacia, Guiera and Combretum which contains the most important ecological indices. The overall density of species within the plots varies between 129 and 105 ind / ha. The basal area varies from 2.02 to 3.88 m² / ha. The Importance Value Index (IVI) is of the order of 300 in the different plots. The floristic diversity of the undergrowth of Agrosystems (average ISH> 2) shows homogeneity and an even distribution between the different plots. Plots with similarity indices of less than 50% do not meet floristic affinity while similarity indices are high in plots with floristic affinities greater than or equal to 50%. The diameter structure showed a predominance of young individuals. This information drawn from the conclusion of the present study shows that they constitute an important argumentation of the advantages so that the services of agricultural development should be interested in the conservation and valuation of such an agroforestry system for the protection of the environment against the climate change mitigation and sustainable development of local communities.

The increasing popularity of carbon nanotubes has created a demand for greater scientific understanding of the characteristics of thermal transport in nanostructured materials. However, the effects of impurities, misalignments, and structure factors on the thermal conductivity of carbon nanotube films and fibers are still poorly understood. Carbon nanotube films and fibers were produced, and the parallel thermal conductance technique was employed to determine the thermal conductivity. The effects of carbon nanotube structure, purity, and alignment on the thermal conductivity of carbon films and fibers were investigated to understand the characteristics of thermal transport in the nanostructured material. The importance of bulk density and cross-sectional area was determined experimentally. The results indicated that the prepared carbon nanotube films and fibers are very efficient at conducting heat. The structure, purity, and alignment of carbon nanotubes play a fundamentally important role in determining the heat conduction properties of carbon films and fibers. Single-walled carbon nanotube films and fibers generally have high thermal conductivity. The presence of non-carbonaceous impurities degrades the thermal performance due to the low degree of bundle contact. The thermal conductivity may present power law dependence with temperature. The specific thermal conductivity decreases with increasing bulk density. At room temperature, a maximum specific thermal conductivity is obtained but Umklapp scattering occurs. The specific thermal conductivity of carbon nanotube fibers is significantly higher than that of carbon nanotube films due to the increased degree of bundle alignment.

<b>Background and aim:</b> Developing clinical skills and its assessment is one of the most important components in nursing education which prepares the student for the reality of practice. Objective structured clinical examination (OSCE) is extensively used and widely accepted by nurse educators across the globe to assess the competency skills of nursing students. The present study aimed at identifying the attitude and perceptions of faculty, and exploring their feedback and experience in conducting OSCE as an assessment tool. <b>Methods:</b> A triangulation research approach was used with convenience sampling. Data collection was carried out using questionnaires and semi-structured interviews. Participants were ten faculty members who were involved in conducting OSCE for students. <b>Results and conclusion</b>: Most of the faculty felt that OSCE reflected the skills of delivery of safe patient care, and the structure reflected mastery of knowledge and skills, which are related to course objectives. OSCE was regarded by the faculty as a consistent, reliable, valid, and objective measure to assess students’ performance and to improve students’ confidence in clinical skills. Concerns were raised about a high level of stress in students, the time required for the proper performance of tasks, OSCE scenarios lacking real-life situations in assessment, and the need for repeated practice and intensive mock training sessions. The applicability of OSCE in terms of limitations in human and material resources with a large number of students would necessitate rethinking in developing other assessment strategies to improve the overall process.

Integrated Risk and Compliance Frameworks for Global Data Center Operations: A Governance-Centric Approach presents an objective, evidence-based analysis through a governance-focused lens, emphasizing strategic alignment, stakeholder engagement, and measurable outcomes. Specific risk and compliance paradigms governing data center operations are identified, and the impact of these paradigms on oversight, control, and reporting is assessed. A comparative study of traditional operational controls and a governance-led compliance-centric methodology demonstrates the latter's potential to become the primary driver of data center risk and compliance. Governance encompasses the continued alignment of business goals with risk appetite, regulatory requirements, and operational capabilities; a defined structure for accountability, including oversight committees and established roles and responsibilities for risk and compliance decision rights; and a mechanism for stakeholder engagement that enables periodic and continuous validation of strategic decisions. Integrated risk management frameworks leveraging these principles are a prerequisite for effective risk and compliance management in the context of global data center operations.

The evolution of supply chains (SC) from a linear to a network structure created an opportunity for new processes, product/service offerings, and provider-business. Rising customer service expectations have led to the need for innovative SC designs to develop and sustain competitive performance globally. Firms are forced to respond and adapt accordingly, thereby leading to design, network, operational, and performance dynamics. Traditionally, SCs are treated as static structures, focusing solely on design and/or operational optimization. Such perspectives are not viable options for SC domains, as they address only a portion of the dynamic problem space, use a deterministic assumption of dominant design variables, capitalize on past data to predict future decisions, and offer pre-classified forecasting options complemented with a limited comprehension of systemic SC elasticity. Novel self-learning agentic systems are proposed that blend the sciencematics of SC decisions and dynamics. The designs guide firms seeking to build adaptive SCs using operational decision processes. The designs address the agentic nature of SC, embedding computational interaction models of firm SC networks. The designs contrast the stochastic action-taking and thereby the performance outcomes, discovering opportunities for adaptive operational designs of SC tasks. Fine-tuning and meta-learning are new design capabilities that adapt to evolving dynamic environments. Frameworks for behavioral customization and systematic exploration of the design space are provided as user guides. Exemplar designs are also provided to serve as a translation template for users to express operational models of their own contexts. To account for the dynamics of supply chains (SC), agent-based models are increasingly adopted. Such models exhibit SC structure and/or formulation dynamics. Though existing efforts commence adjacent-only structural changes, dynamism with respect to tasks is crucial for SC design and operational strategy development. Proposed is a process modeling library and workflow for discovering intricate designs of adaptive agentic systems. The library revises Dataflow and Structure, concealing sequencing and context designs of processes. Prompted specifications describe and enact designs. Applications in SC formulation discovery are provided.

Key business objectives for digital infrastructure cloud adoption are often framed in terms of reducing cost, improving fault tolerance and resilience, simplifying scale, and enabling innovation. Given the critical nature of the financial sector, however, where timeliness and price can significantly determine an outcome, cloud migration in delivery environments demands greater throughput on the critical path and, in many enterprise-scale settings, forgoes hybrid complexity and multi-cloud risks. Nevertheless, slack in system designs does exist; financial institutions enable market functionality—trading, clearing/best execution—despite potentially being able to meet such sets with lower service levels than other verticals. A cloud multi-account structure for sensitive data, for example, naturally limits exposure when combined with observed risk. Fulfilling predictions of elasticity during periods of high demand usually requires support from a dedicated environment (or environments) located nearer to the operations. Components can consequently be allocated on a per-account basis or maintained as shared sink systems to which the dedicated streams write. The automation code can similarly be targeted for dedicated accounts, avoiding the resource constraints that beset such operations during industry events like emergency triage/contact desking.