Articles

There is a growing body of evidence that the number of individuals suffering from chronic and acute pain is under-reported and the burden of the veteran, aging, athletic, and working populations is rising. Current pain management is limited by our capacity to collaborate with individuals continuing normal daily functions and self-administration of pain treatments outside of traditional healthcare appointments and hospital settings. In this review, the current gap in clinical care for real-time feedback and guidance with pain management decision-making for chronic and post-operative pain treatment is defined. We examine the recent and future applications for predictive analytics of opioid use after surgery and implementing real-time neural networks for personalized pain management goal setting for particular individuals on the path to discharge to normal function. Integration of personalized neural networks with longitudinal data may enable the development of future treatment personalizations paired with electrical simulations.

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.

Data warehousing is a technique for collecting, managing, and presenting data to help people analyze and use that data effectively. It involves a large database designed to support management-level staff by providing all the relevant historical data for analysis. This chapter begins with a definition of data warehousing, followed by an overview of large-scale policy management to highlight the need for data warehousing. Next, an overview of an ETL framework is presented, along with a discussion of advanced ETL techniques. The chapter concludes with an outline of performance optimization techniques for data warehousing. Data warehousing is considered a key enabler for efficient reporting and analysis, with implementation choices ranging from cost-effective desktop systems to large-scale, mission-critical data marts and warehouses containing petabytes of data. Extract, transform, and load (ETL) systems remain one of the largest cost and effort areas within data warehouse development projects, requiring significant planning and resources to build, manage, and monitor the flow of data from source systems into the data warehouse. The technology and techniques used for ETL can greatly influence the success or failure of a data warehouse. Complex business requirements for data cleansing, loading, transformation, and integration have intensified, while operational plans for real-time and near-real-time reporting add additional challenges. Parallel loading mechanisms, incremental data loading, and runtime update and insert strategies not only improve ETL performance but also optimize data warehousing performance, particularly for large-scale policy management.

Seamless integration of information in organizations promotes not only the operational efficiency but also the quality of decisions made by managers. Real-time decision support systems enable organizations to evaluate organizational changes immediately and ideally gives a hint of problems before they even appear in the organization. Such real time systems are nowadays regarded as the front-line solutions for managing organizations effectively. The technological possibilities seem not to conquer management. For most companies the data is still dealt with traditional solutions, data is collected and reports are generated to evaluate the past occurrences which only gives information on what has happened in the organization. The problem with these non-real-time systems is the reflection of organizational condition very late. These are the common rear-mirror descriptions for what already has been. Managers are receiving information from their organizations too late and often too little to make optimal decisions. Is it not possible to manage operations in real-time? Is real-time decision support really needed? If so, why most organizations still rely on traditional reporting systems.

Global colocation services provision mission-critical infrastructure in secure and reliable facilities, typically within a zero-tolerance SLA environment. Strength of colocation services is the volume of incidents and service requests, and the case management workflow is a critical determinant of the improvement of the end-to-end response capacity and quality. An objective, evidence-based exploration of the principles of colocation operations case management covering design, metrics, and pathways for continuous enhancement has been conducted. A structured inquiry engaged diverse sources: primary and secondary research, case study analysis following global delivery and service operation models, information provided by subject matter experts, and management performance benchmarks proposing KPIs. The investigation results in the articulation of fundamental principles and frameworks that govern the management of incidents and requests in colocation operations. Evidence of the natural path to optimization supports their formulation. Continuous awareness, evaluation, and reinforcement of the principles and frameworks contribute significantly to performance enhancement.

Introduction:</b> The city of Wuhan in China reported the first case of coronavirus, termed as SARS-CoV-2, in December 2019. To date, 187,827,660 cases have been reported to the WHO (3). With current research focusing on potential therapeutic agents for the coronavirus disease and vaccines, there remain major gaps in our understanding of the pathophysiology and clinical course of this viral pneumonia. Secondary infections are one of them. In this systematic review, we analyze the outcomes of two fungal infections in patients of COVID-19, viz. Mucormycosis and candida. <b>Methodology:</b> A systematic review has been done on secondary infections with mucor and candida fungi in patients of COVID-19. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were used. Twenty-three studies were included in the final analysis. Our review included studies from various countries across the globe. The risk of bias was analyzed using the NIH Quality Assessment Tool for Case Series Studies. This study did not require ethical approval as data was obtained from already available databases, and patients were not directly involved. <b>Results:</b> A total of 23 articles were included in the final review and the total number of patients included was 79 Male: female ratio was calculated to be 1.6 and the average age of patients was 52 years (ranging from 24-86 years). Various types of comorbidities were seen in the included patients, the most common being diabetes mellitus. Among the 18 patients in the cohort of mucormycosis, 7 patients died and four studies did not report patient outcomes. Among the 61 patients, 13 patients died and one patient was still ventilated at the time of publication. <b>Conclusion:</b> Secondary infections after COVID-19 are a cause of major concerns. Further studies and case reports are needed to better understand the various other types of secondary infections and also to formulate strategies to prevent these.

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.

This paper shows how Big Data Analytics (BDA) and Artificial Intelligence (AI) automation facilitate regulatory compliance in Finance. Regulatory compliance is essential in helping institutions to mitigate reputational, litigation, and financial risk. Existing literature reveals several preconditions for compliance. However, much of the literature has adopted an internal view of compliance without considering external regulatory frameworks. This research draws on the cognitive model of regulation that looks at regulatory compliance as a social construct. It uses a triangulation research method comprising literature review, interview of trade compliance experts, and questionnaire survey of compliance practitioners to understand how regulation affects compliance and what role ICTs play in implementing compliance. The findings of this study present a regulatory compliance framework comprising four cognitive stages and a conceptual regulatory compliance system that presents how BDA and AI automation are applied to mitigate regulatory complexity and enhance regulatory compliance. The conceptual regulatory compliance system shows how BDA and AI enable institutions to dynamically assess regulatory risk, automatically monitor compliance, and intelligently predict risk violations mitigating regulatory complexity and preventing producing unnecessary documents. It provides theoretical contributions to understanding regulatory evolution and compliance and practical implications for understanding how regulation evolves to be more complicated and elements of a regulatory compliance system mitigate proliferating regulations. Additionally, it provides avenues for future research into the relationship between competing regulatory mandates and how institutions cope with that. Regulations are important for ensuring compliance and governance in finance and to curb systemic risk. Complying with regulations is difficult due to their growing volume, complexity, and fragmentation. Institutions use large-scale Information and Communication Technologies (ICTs), such as Big Data Analytics (BDA) and Artificial Intelligence (AI) automation, to monitor compliance and mitigate regulatory complexity. However, less is known about how firms comply with regulation. Most literature does not thoroughly investigate regulatory elements nor explicitly relate them to compliance.