Artificial Intelligence for Skin Cancer Imaging: Performance, Translational Gaps, and a Three-Tier Clinical Readiness Framework
Artificial Intelligence (AI)-driven image analysis has made significant strides in dermatologic cancer care, showing dermatologist-level accuracy in melanoma detection through various publications. However, its integration into routine clinical practice remains limited, resulting in minimal impact in real-world scenarios. This review assesses AI applications across three main imaging methods in skin cancer management: clinical photography, dermoscopy, and histopathological slides. Key factors affecting diagnostic efficacy include image quality, annotation methods, dataset composition, and deployment context. Convolutional neural networks, particularly when provided with high-resolution images and validated biopsy labels, demonstrate effectiveness comparable to skilled dermatologists. However, performance diminishes significantly when models are tested on diverse devices, skin types, or lesion types. Clinical photograph systems, while less accurate, offer advantages in scalable triage and teledermatology. Histopathological models produce robust confirmatory results; however, they face obstacles including inadequate supervision, variability in staining, and substantial computational demands. Common issues across these modalities include dataset bias, underrepresentation of darker skin tones and benign lesions, noisy ground truth, and poor integration into clinical workflows. The authors put forward a three-tier framework to get the medical field ready for AI. They suggest using it in primary care to screen for lesions, as a decision-support tool in dermoscopy, and as a computational biomarker in digital pathology. Future developments will hinge on creating representative datasets, advancing training techniques, ensuring interpretability, long term monitoring of lesions, and achieving regulatory validation. Ultimately, mature AI systems are anticipated to act as diagnostic collaborators rather than replacements for clinicians, focusing on reducing unnecessary procedures, standardizing biopsy criteria, and improving equity in skin cancer management.
Copyright (c) 2025 Pathfinder of Research
Optimizing Cloud Based Data Management for Healthcare Systems Using Intelligent Superiority Computing
Cloud-based data management remains foundational for healthcare organizations in the United States, but these infrastructures continue to struggle with latency, bandwidth constraints, and persistent data-security vulnerabilities. Intelligent Edge Computing (IEC), a distributed architecture, addresses these weaknesses by enabling data processing and AI-driven decision support directly at the point of data generation, thereby reducing dependence on remote cloud servers. This study used a mixed-method design involving 315 healthcare IT professionals from 25 U.S. hospitals. Regression modeling, correlation analysis, and χ² testing were applied to assess changes in system performance, latency patterns, energy-efficiency indicators, and compliance outcomes before and after IEC implementation. Regression outputs indicated that IEC variables were strong predictors of overall system performance, reflected by R = 0.85, R² = 0.72, F = 196.5, p = 0.001. Performance improvement was primarily driven by edge-node density and AI load-balancing efficiency, with coefficients of β = 0.62 and β = 0.57, respectively, both significant at p < 0.001. χ² tests showed notable differences in system-usage frequency across job roles (χ² = 18.9, df = 2, p = 0.001), while gender-based variation was not statistically meaningful (p = 0.29). IEC deployment produced a 26% increase in operational efficiency, a 29% cost reduction, and a 17% improvement in HIPAA compliance. Integrating IEC into cloud-based healthcare systems enhances performance, scalability, and regulatory compliance, positioning it as a critical solution for next-generation clinical data infrastructures.
Copyright (c) 2023 Pathfinder of Research
Integrating Management Information Systems in Marketing: A Survey-Based Analysis of Consumer Engagement and Business Growth through Data Analytics
Modern marketing practice depends simultaneously on precise data, rapid information delivery, and seamless system integration. Management Information Systems (MIS) provide the core technological infrastructure that converts fragmented organizational data into actionable marketing intelligence, and firms employing MIS-driven analytics have been shown to achieve conversion rates up to 30% higher than those relying on traditional marketing approaches. This study used a structured online survey of 155 marketing professionals employed in small, medium, and large enterprises to examine the role of MIS and analytics in marketing performance. A five-point Likert scale was used to measure five key constructs: MIS integration, data analytics utilization, consumer engagement, decision-making efficiency, and business growth. Instrument reliability and sampling adequacy were confirmed with Cronbach’s α = 0.89 and KMO = 0.82 (p < 0.001). Statistical analyses were conducted in SPSS 26, including Pearson correlation, multiple regression, and mediation modeling. Strong positive correlations were found between MIS integration and data analytics utilization (r = 0.82, p = 0.001) and between analytics utilization and consumer engagement (r = 0.81, p = 0.001). Regression results indicated that MIS adoption significantly improves decision-making efficiency (β = 0.64, p = 0.01) and explains a substantial proportion of variance in business growth (R² = 0.70, p = 0.001). The predictive analytics framework yielded a 34% increase in customer retention through repeat purchases and a 29% improvement in campaign targeting precision. Overall, the integration of MIS with data analytics enhances marketing outcomes, leading to higher customer retention and improved profitability.
Copyright (c) 2022 Pathfinder of Research
Integrating Supply Chain Management and Marketing Strategies for Competitive Advantage in the Digital Economy
The digital economy is driving firms to improve competitiveness by integrating supply chain management with marketing. Many organizations still operate these functions on separate systems, which introduces inefficiencies, slows responses, and obscures potential synergies. This study examines the association between digital SCM marketing integration and operational and customer outcomes using a mixed-methods design. A cross-sector survey of 250 professionals from manufacturing, retail, and service sectors was analysed in SPSS 26, and 10 in-depth managerial interviews were thematically analysed to identify enabling practices and outcomes. Overall, 69 percent of organizations reporting successful integration also reported approximately 25 percent higher operational efficiency and 27 percent higher customer satisfaction compared with lower integration peers. Integration showed a strong positive correlation with competitive advantage (r = 0.74, p = 0.01). Interview insights converged on three enablers: AI-driven forecasting, real-time data sharing, and collaborative digital platforms that connect planning and market execution. These tools were consistently linked with better demand sensing, improved inventory management, and tighter alignment between supply decisions and marketing needs. The findings suggest that digital integration of SCM and marketing is associated with superior efficiency, faster fulfillment, and enhanced customer satisfaction, offering practical guidance on leadership commitment, interoperable data infrastructure, and governance routines that sustain cross functional collaboration.
Optimizing Healthcare Performance with Business Analytics
Healthcare systems face a dense mix of pressures. To sustain high-quality services, providers must absorb rising patient volumes, extend limited resources, and contain escalating costs. In this context, business analytics has shifted from optional to strategic, enabling data-driven decisions that lift both clinical and operational performance. By using different methods to analyze detailed data from sources like electronic health records and clinical registries, organizations can spot trends, predict what patients will need, and improve staffing, capacity, and supply chains. The result is better outcomes, smoother workflows, and improved cost efficiency. Analytics now supports core domains: operations management, clinical decision support, population health, and personalized care. Predictive models, for example, identify people at higher risk and prompt early actions that reduce unnecessary hospital readmissions while strengthening prevention programs. Just as crucial, prescriptive tools recommend targeted actions, helping leaders weigh trade-offs and choose among constrained options with clarity and confidence. Emerging technologies promise to amplify these gains. Artificial intelligence, the Internet of Medical Things, and genomics-informed precision medicine can deliver real-time insights and tailored interventions at the point of care, tightening feedback loops between data, decision, and action. Yet meaningful impact depends on thoughtful execution grounded in clear governance, high-quality data, interoperability, workforce training, and change management. Taken together, the evidence suggests that when implemented deliberately, business analytics can reshape healthcare delivery into systems that are more efficient, resilient, and patient-centered. By addressing adoption barriers proactively and embracing modern analytic capabilities, organizations can secure durable improvements in operational performance, clinical outcomes, and the overall quality and value of care for patients and communities alike.
Prehypertension among Undergraduates: A Cross-Sectional Study of Medical and Non-Medical Students in Bangladesh
Prehypertension in young adults is a modifiable precursor to hypertension and later cardiovascular disease. Robust, stream-wise estimates among Bangladeshi university students are limited. We conducted an analytical cross-sectional study (October 2024-March 2025) among 402 undergraduates recruited via convenience sampling from Bangladesh Medical College (medical stream) and North South University (non-medical stream), Dhaka. Seated blood pressure was measured twice (1min apart) using a validated device; the mean was classified per JNC-7. A structured questionnaire captured sociodemographic and lifestyle factors. We reported prevalence, bivariate associations (χ²), and multivariable logistic regressions for sociodemographic and lifestyle predictors. Overall prehypertension prevalence was 22.6% (91/402). The proportion was higher among medical students (24.9%) than non-medical students (20.4%); the difference was not statistically significant. Descriptively, prehypertension was more common in males, overweight students, smokers, short sleepers (5-6 h), hostel residents, and those reporting moderate stress. In adjusted models, no variable reached statistical significance; point estimates suggested higher odds with obesity and short sleep and lower odds with moderate (vs. mild) stress, with wide confidence intervals. More than one in five undergraduates screened had prehypertension, with concerning patterns across modifiable risks despite no single independent predictor. University health systems should implement routine BP screening and campus-tailored programs for weight management, sleep hygiene, stress reduction, and tobacco control.
Ethical Issues in Business Innovation: Patents, Competition, and Consumer Right
Innovation drives economic progress, but patent arrangements designed to encourage innovation increasingly conflict with market equality and consumer accessibility. This research investigates the ethical difficulties associated with intellectual property protection in various industries, notably with essential goods. Patent holders exert significant influence over markets, price, and accessibility, prompting questions regarding their ethical obligations beyond mere legal compliance. Pharmaceutical patents demonstrate these tensions very well. Government funding for research and lifesaving pharmaceuticals produced through public-private partnerships sometimes remains unattainable for individuals in the most critical situations. Technology patents reveal unique yet equally troubling patterns, as the protection of innovation evolves into commercial exploitation via strategic litigation and portfolio consolidation. These activities indicate that patent regimes may be compromising their fundamental goal of promoting innovation that benefits society. Current regulatory regimes inadequately address these ethical considerations. Patent law primarily focuses on technical originality and financial entitlements, sometimes neglecting wider societal consequences. This restricted focus allows for behaviors that may comply with legal criteria but violate ethical principles of fairness, accessibility, and public welfare. Market failures in patent protected sectors exemplify the costs linked to this approach. Reform requires the recognition that patent rights impose societal responsibilities. Potential solutions include public interest licensing for government-funded research, price restriction for essential patents, and strengthened antitrust enforcement against patent misuse. Innovation policy should go beyond safeguarding inventors to guarantee that innovation serves humanity's interests. This transformation necessitates new frameworks that align corporate incentives with public welfare, making patent systems responsible to the societies that provide them legitimacy.
AI-Driven Renewable Energy Transitions for Suitable Agriculture and Rural Development: Socio-Economic, Technical, and Policy Perspectives
The integration of artificial intelligence (AI) with renewable energy systems presents a robust strategy for enhancing agricultural output and fostering rural development. With the increasing worldwide need for food and the issues faced by agricultural systems, such as resource scarcity, labor shortages, and erratic climate conditions, AI-driven solutions provide unique tools for enhanced energy management, resource allocation, and decision-making processes. Principal uses encompass smart irrigation, which enhances water efficiency; predictive analytics that anticipate yields or market trends; and pest and nutrient management systems that assist farmers in sustaining healthy crops. Agrovoltaic systems that integrate energy generation with agriculture are gaining popularity. These technologies boost efficiency and sustainability while generating new income streams and improving rural livelihoods. Yet, the integration of AI in the sectors of renewable energy and agriculture presents certain hurdles. Substantial obstacles must be surmounted, including elevated initial investment expenses, disparities in internet accessibility, regulatory challenges, ethical dilemmas, and opposition to novel technology. To effectively address these concerns, it is imperative to establish adaptive policies, cultivate public-private partnerships, involve communities, and invest in capacity-building projects that promote equal access and inclusive growth. This study highlights the complex socio-economic, technological, and policy aspects of AI-driven transformations in renewable energy. It underscores the imperative for ethical governance, data openness, and the empowerment of local populations. Through the cultivation of an inclusive, sustainable, and resilient energy ecosystem, AI can profoundly alter agricultural landscapes, promote environmental stewardship, and empower rural people to adequately address the increasing global needs for food and energy.
Fishing Bans as a Conservation Tool: Socioeconomic Impacts and Livelihood Compensation in Practice
Seasonal fishing bans are rigorously implemented to protect fish during critical life phases, especially in less developed countries where fisheries are essential for livelihoods. The Hilsa (Tenualosa ilisha) fishing ban in Bangladesh is designed to protect spawning and juvenile populations, bolstered by a government compensation program. Nonetheless, the practical efficacy and fairness of these treatments remain little investigated. This study looks at how the Hilsa ban affects people's lives and checks how well the relief program works in Lalmohan Upazila, Bhola District, which is important for the environment and has many people in need. We employed a mixed-methods approach to collect data from 150 families, five focus group talks, and eight key informant interviews. Results indicate that 42% of families got no compensation, and 61% of beneficiaries experienced delays or deficiencies. The prohibition exacerbated poverty, food insecurity, and school dropout rates among children, leading households to depend on migration, informal loans, or child labor. Political partiality, obsolete registries, and inadequate accountability compromised assistance distribution. Notwithstanding these limitations, communities articulated conditional support for the ban and suggested implementable improvements. This study emphasizes lived experiences and governance challenges, offering vital details about reconciling ecological preservation with social equity. The results contribute to wider discussions on fair fisheries governance and conservation-related social protection in the Global South.
Technology and Innovation in Healthcare: Adoption of AI and Predictive Analytics in Hospital Management
This review investigates how artificial intelligence (AI) and predictive analytics are reshaping hospital management by enhancing clinical decision-making, operational efficiency, and equitable healthcare delivery. People are increasingly applying AI-driven models to forecast patient demand, optimize workforce planning, improve diagnostic accuracy, and expand telemedicine, especially in the post-pandemic era. When implemented responsibly, predictive tools across healthcare systems can reduce readmissions, strengthen patient outcomes, and support resource utilization. Successful adoption is enabled by robust digital infrastructure, committed leadership, and cross-disciplinary collaboration, yet barriers persist, including fragmented IT systems, interoperability gaps, algorithmic bias, and workforce skill shortages. Ethical and governance challenges centered on transparency, data protection, and accountability remain pivotal to sustainable clinical integration. Comparative insights reveal divergent adoption pathways: high-income countries leverage mature digital ecosystems, while low- and middle-income contexts are innovating with resource-sensitive applications to address workforce constraints and expand access. By synthesizing theoretical frameworks and global case studies, this review underscores that responsible AI adoption can accelerate hospital transformation. Policy recommendations emphasize that it is time for standardized validation, strengthened data ecosystems, inclusive telehealth expansion, and institutional capacity-building to advance efficiency, resilience, and equity in healthcare systems.
Preventable Readmissions and Financial Management in Healthcare: A Comparative Study of Cost Containment in Non-Profit and For-Profit Hospitals
Efficient financial management is crucial for the sustainability and efficacy of contemporary healthcare systems. This analysis rigorously assesses cost containment initiatives implemented by Non-Profit (NFP) and For-Profit (FP) institutions and examines the financial consequences of avoidable hospital readmissions. The study does a narrative synthesis in accordance with PRISMA 2020 guidelines, analyzing 62 peer-reviewed papers published from 2010 to 2025. The assessment classifies cost conservation measures into four principal themes: operational efficiency, technological investment, administrative reorganization, and value-based care delivery. It indicates that FP hospitals primarily employ assertive cost-reduction and revenue-maximization strategies, such as outsourcing, performance-based contracting, and digital billing optimization. NFP hospitals prioritize long-term sustainability by focusing on community-oriented initiatives, care integration, and workforce development. The analysis emphasizes that unnecessary hospital readmissions intensify cost burdens, particularly for disadvantaged populations, affecting reimbursement schemes and institution rankings. The results demonstrate the need to synchronize financial management with fairness, policy adherence, and health outcomes. Policy proposals highlight the integration of value-based incentives, the standardization of readmission penalties, and the assurance of openness in ownership-driven financial practices. The analysis indicates that a hybrid framework for cost reduction that balances efficiency, accountability, and equity is essential for promoting sustainable and equitable healthcare delivery across various institutional systems.
Post-COVID-19 Workforce Management in U.S. Healthcare: Burnout, Retention, and Strategies for Enhancing Cultural Competency
The COVID-19 pandemic magnified persistent structural weaknesses within the U.S. healthcare workforce, intensifying psychological strain, professional exhaustion, and staff turnover. This scoping review synthesizes 40 peer-reviewed studies published between 2020 and 2024 to examine key drivers of post-pandemic burnout, identify system-level factors influencing workforce attrition, and assess the role of cultural competency in enhancing organizational resilience. Findings indicate that a lack of work-life balance, moral injury, and inadequate institutional support remain the dominant contributors to burnout. Thematic analysis highlights several effective retention strategies, including inclusive leadership, flexible scheduling, and trauma-informed support systems. Cultural competence implemented through equity audits, diverse hiring panels, and culturally responsive mental health resources emerged as a critical moderator of employee engagement and psychological safety. Institutions that embedded cultural inclusion within governance frameworks reported notable improvements in job satisfaction, reduced attrition, and enhanced workforce cohesion. This study advocates for equity-centred leadership, the institutionalization of DEI practices, and a redefinition of burnout and retention as strategic, not peripheral, concerns. Policy recommendations include mandated DEI metrics, psychological safety standards, and intersectional workforce accommodations. Overall, this review positions cultural competency as a foundational pillar of post-pandemic workforce recovery and sustainability in American healthcare.
Integrating Artificial Intelligence into Business Analytics: Sectoral Adoption Patterns and Strategic Implications in the United States
Artificial Intelligence (AI) is reshaping the landscape of business analytics by enabling a shift from retrospective evaluation to predictive, autonomous, and strategic decision-making. This review critically examines the patterns of AI adoption across key U.S. sectors finance, healthcare, retail, and manufacturing highlighting sector-specific enablers, institutional readiness, regulatory landscapes, and performance implications. Employing a thematic qualitative framework supported by organizational maturity models and sectoral readiness matrices, the study uncovers both the transformative potential and systemic barriers to scalable AI integration. Issues such as data fragmentation, ethical ambiguity, skill deficits, and governance inconsistencies are identified as key obstacles. Cross-sector innovation spillovers are analyzed to demonstrate how transferable AI solutions can enhance organizational learning and adaptability. The study concludes with actionable recommendations for aligning technological investment with ethical governance, workforce capability, and regulatory compliance. These findings provide a policy-relevant knowledge base for industry leaders, regulators, and researchers aiming to implement sustainable, responsible, and context-sensitive AI strategies.
The Evolution of Business Analytics: Frameworks, Tools, and Real-World Impact on Strategic Decision-Making in the Digital Age
In the digital age, as data is increasingly recognized as a strategic asset, business analytics (BA) has become a critical factor in organizational decision-making. From common decision support systems to advanced concentrated analytics platforms and AI used in modern business environments, this review provides an inspection of business analytics development. The integration of cloud computing and machine learning (ML) is one of the main topics tested in this article, emphasizing how these technologies change their business strategy. The review also examines the number of methods and tools created to process and analyze large data sets, such as real-time analytics, data visualization, and prediction analytics. The autonomous decision-making capabilities of AI-driven manufacturing systems and the growing importance of ethical issues in data analytics are two examples of how testing demonstrates the future path of business analytics. By emphasizing the essential role that business analytics plays as a navigation role in the sophistication of the digital economy, this assessment finds ways to provide deep information to researchers and students. The analysis further explores the security, data security, and data combinations that aren't structured in the decision-making processes. Finally, the paper assesses a complete perspective on how business analytics changes decisions and the amendment of the competitive environment of industries worldwide. This analysis emphasizes the importance of advanced analytics techniques to maintain a competitive advantage while businesses continue to change in a world that focuses on data.
Copyright (c) 2024 Pathfinder of Research
Coastal Livelihoods under Pressure: Vulnerability and Adaptation among Bangladesh’s Small-Scale Fishers
The Small-scale fisheries are crucial for sustaining livelihoods and ensuring food security in coastal Bangladesh. These communities encounter increasing socio-ecological challenges stemming from climatic unpredictability, institutional neglect, and policy deficiencies. This research combines the Livelihood Vulnerability Index (LVI) and the Sustainable Livelihoods Approach (SLA) to evaluate household vulnerability and adaptation capability in Char Bhaga Union, in the Lower Meghna River estuary. The study used a mixed-methods methodology, comprising 130 household surveys, eight focus group discussions (FGDs), and 12 key informant interviews (KIIs), therefore offering both quantitative data and qualitative insights. The LVI score of 0.62 signifies substantial vulnerability, especially among households with less education, erratic income, and restricted access to institutional safety nets. Gender studies indicate the structural marginalization of women from fishing cooperatives, training initiatives, and compensation programs, despite their significant involvement in post-harvest operations. Institutional deficiencies, such as ineffective enforcement of sanctuary legislation, politicized allocations of aid, and insufficient participatory planning, further erode resilience. Coping mechanisms are predominantly reactive (e.g., seasonal relocation, asset liquidation), whereas proactive adaptation is confined to households with access to remittances or NGO assistance. The study provides a thorough understanding of resilience pathways by integrating LVI measurement with SLA's asset-based perspective. The findings enhance the literature on fisheries governance in South Asia and promote inclusive co-management, gender-responsive initiatives, and focused livelihood investments in accordance with Sustainable Development Goals 1, 5, 13, and 14. The suggested dual-framework approach functions as a repeatable instrument for policymakers seeking to include vulnerability diagnostics in national adaptation programs.
Advancing Fish Farming Through Deep Learning: Applications, Opportunities, Challenges, and Future Directions
Deep learning (DL) has changed aquaculture by offering automated solutions for species identification, health assessment, biomass calculation, feeding optimization, and water quality forecasting. Conventional aquaculture encounters obstacles like ineffective resource management, disease epidemics, and environmental deterioration; nevertheless, deep learning applications provide intelligent decision-making skills that improve sustainability and economic feasibility. This study carefully looks at 41 peer-reviewed papers from 2015 to 2024 to find out how useful deep learning is in aquaculture. It focuses on main AI models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). The results indicate that AI-driven solutions boost fish health evaluations, optimize feeding strategies, and improve water quality monitoring, hence minimizing waste and augmenting production efficiency. Nonetheless, obstacles like substantial computing demands, dataset restrictions, and regulatory limits impede extensive implementation. Comparative assessments demonstrate that deep learning models surpass conventional aquaculture methods in precision and prediction efficacy. In the future, researchers should investigate new AI technologies like federated learning, edge computing, and AI-integrated robotics to make deep learning easier to use and more scalable for aquaculture applications. By surmounting these obstacles and utilizing advanced AI technology, aquaculture may evolve into a more sustainable, efficient, and intelligent sector.
Public Health, Risk Perception, and Governance Challenges in the 2025 Los Angeles Wildfires: Evidence from a Community-Based Survey
The January 2025 wildfires in Southern California, notably the Palisades and Eaton Fires, were among the most catastrophic in the state's history, leading to nearly 18,000 structural losses, extensive evacuations, and considerable public health repercussions. This study examines the social, psychological, and policy-related effects of these wildfires via a mixed-methods survey of 90 residents impacted by or near the events. Participants indicated elevated incidences of smoke-related health complications (52%), psychological discomfort (45%), and property or financial losses (35%), with several individuals demonstrating diminished faith in governmental response systems. Awareness of wildfire dangers was moderate; nonetheless, preparatory behaviours, such as establishing evacuation plans, were adopted inconsistently. Confidence in official communication was significantly diminished among historically marginalised populations. Nonetheless, a majority expressed a readiness to engage in community-driven mitigation efforts, encompassing educational programmes and Firewise USA techniques. The study's results correspond with and enhance current literature on climate-induced fire regimes, emphasising deficiencies in prevention-focused governance, mental health interventions, and risk communication. The statistics further underscore the importance of including Indigenous fire stewardship and locally informed preparedness strategies. This research provides timely, community-based evidence to enhance wildfire resilience strategies and facilitates a shift towards more equitable and adaptive fire control systems in California and other high-risk areas.
Improving Treatments for Oral Diseases, Head and Neck Cancers, as well as Developing New Technologies
Head and neck cancers, encompassing malignancies of the oral cavity, pharynx, and larynx, represent a considerable worldwide health concern, with over 890,000 new cases and 450,000 deaths each year. Notwithstanding progress in conventional therapies like surgery, radiation, and chemotherapy, the outcomes remain inadequate, particularly for recurrences or metastases. This review synthesizes current medicinal and technological breakthroughs aimed at improving clinical outcomes and patient quality of life in oral and head and neck cancers. Molecular profiling has discovered changes in genes like TP53 mutations, EGFR overexpression, and issues with the PI3K/AKT/mTOR system, which assist in developing personalized cancer treatments. Immunotherapy, particularly treatments that focus on PD-1/PD-L1, offers long-lasting results for certain groups of patients identified by specific markers. Nanotechnology-based drug delivery systems improve targeted therapy by increasing the amount of medicine at tumor sites and reducing side effects in nearby tissues. Artificial intelligence (AI) has transformed disease diagnostics, facilitating earlier identification and customized treatment strategies. Liquid biopsies facilitate the early detection of illnesses and their ongoing monitoring. Regenerative medicine employs stem cell treatment, 3D bioprinting, and CRISPR gene editing to restore bodily functions and enhance tumor targeting. Digital health instruments such as wearable biosensors, tele-oncology, and patient reporting systems enhance therapy precision and monitoring.
The Role of AI and Generative AI in US Business Innovations, Applications, Challenges, and Future Trends
The accelerated progression of machine intelligence and generative AI (GenAI) is escalating the landscape of U.S. business, introducing transformative opportunities while raising critical societal questions. This review article systematically examines four key dimensions of AI's impact: technological innovations, practical applications, emerging challenges, and future directions. Regarding innovation, we analyse the way automatic learning breakthroughs and the ability of the GenAI to change data analysis and decision-making processes and interact with the machine. Real-world deployment is being applied in key areas such as personal health diagnosis, smart financial forecasts, dynamic commitments from retail customers, and smart production systems. However, these technological dance moves come with significant challenges, especially related to the transformation of the labour force, the moral significance of automatic decision-making, data security issues and the need for an updated legal framework. Our analysis shows that solving these problems requires cooperation among decision-makers, business leaders and technology developers. By looking at future trends, we find exciting advancements in AI systems that are user-friendly, training models for a flexible workforce, and strategies for integrating AI that ensure innovation is balanced with social responsibility. This assessment, by synthesizing current experimental studies with real-world data, offers valuable insights for companies pursuing AI applications. We emphasize the importance of developing AI solutions that focus on improving human abilities rather than replacing them, and we propose active management methods to achieve this goal. The results provide a roadmap for responsible AI implementation in American companies and the basis for future research in this rapidly developing field.
Advancements and Challenges in Software Engineering and Project Management: A 2021 Perspective
In the twenty-first century, major advancements emerged in software engineering and project management, propelled by the integration of artificial intelligence, cloud computing, automation, and innovative development approaches. Agile and DevOps consistently augmented software delivery efficiency, while AI-driven solutions advanced predictive analytics and automation. The emergence of low-code and no-code platforms enhanced software accessibility for non-technical users, while blockchain integration bolstered security and transparency. Nonetheless, obstacles including scalability concerns, cybersecurity risks, and regulatory compliance persisted as substantial impediments. Remote and hybrid work patterns need innovative project management tactics, including AI-based tracking tools and improved communication frameworks. Ethical issues related to AI bias and data privacy underscore the necessity for enhanced control in software development. This paper presents a thorough examination of these accomplishments and obstacles, providing insights into comparative trends from prior years and delineating future research areas. We advise researchers and practitioners to prioritize ethical AI, enhance project management frameworks, and fortify cybersecurity techniques. By tackling these issues, the discipline can progress toward more efficient, safe, and scalable software solutions.
Database Management in the Era of Big Data: Trends, Challenges, and Breakthroughs
The rapid development of Big Data has profoundly transformed database management systems, necessitating novel solutions to address the escalating complexity, volume, and variety of data. This analysis examines the principal trends, difficulties, and technological advancements impacting database administration due to the rapid increase in data volume. Significant innovations, including NoSQL databases, cloud computing, distributed architectures, and AI-driven automation, have transformed the methods by which businesses store, process, and analyze extensive datasets. Nevertheless, enduring issues persist, encompassing data security concerns, scalability constraints, and the necessity for enhanced performance. This study brings together recent research to look at how modern database systems have changed over time to deal with these problems and make them more efficient, secure, and able to process data in real time. Additionally, new technologies like blockchain and edge computing are examined for their contributions to improving security and decentralization in database administration. The results underscore the significance of hybrid database models, intelligent automation, and regulatory compliance frameworks in influencing the future of database systems. As enterprises adjust to the needs of Big Data, the integration of new technologies will be essential for achieving scalable, secure, and high-performance database management systems.
Evolution and Future Trends in Web Development: A Comprehensive Review
Web development has greatly advanced from basic static web pages to dynamic, datadriven applications utilizing modern technology. Specifically, this article looks at the past, present, and future of web development, focusing on the importance of artificial intelligence (AI), progressive web apps (PWAs), security measures, and performance improvement. The adoption of contemporary frontend and backend technologies has improved user experience, scalability, and security, while nascent trends like Web3, blockchain integration, and decentralized apps (DApps) are poised to transform the digital environment. Even with these advances, there are still problems, such as cybersecurity risks, accessibility issues, and the need to keep improving online performance. This evaluation shows how important it is to welcome new technologies while also addressing important problems in order to create a safe, effective, and welcoming digital world. Future research must concentrate on enhancing cybersecurity frameworks, refining AI-driven web development, and investigating decentralized computing paradigms. Utilizing advanced technology, web developers may design more intelligent, responsive, and user-centric online apps that satisfy the increasing expectations of the digital age.
Anthropogenic and Environmental Factors Affecting Biodiversityand Human Well-being in an Ecologically Sensitive Wetland
Wetlands in Bangladesh have a crucial role in sustaining biodiversity, fisheries, and local livelihoods; however, they face considerable threats from human activity and environmental influences. This study examines fish diversity, species distribution, and critical socio-ecological issues in Tanguar Haor, an ecologically vulnerable wetland in northeastern Bangladesh. To find out about fish conservation and how communities are connected, a mixed-method approach was used that included both biodiversity assessments and socio-economic analyses. A total of 71 fish species in eight taxonomic groups were identified, with 39 species classified as non-endangered, while 29% were designated as endangered, vulnerable, or critically endangered. The fish assemblage mostly consisted of Cypriniformes (58%), followed by Siluriformes (15%) and Perciformes (09%). Substantial threats include illegal fishing, habitat destruction, agricultural runoff, and poor governance, leading to declining fish populations and socio-economic instability for communities dependent on wetlands. To deal with these problems, the paper suggests setting up fish sanctuaries, using community-based fisheries management (CBFM), making sure that sustainable fishing rules are followed, and supporting programs that help people find other ways to make a living. These results are very important for policymakers, conservationists, and local stakeholders because they help them come up with long-term wetland management plans that will restore biodiversity and make Tanguar Haor's economy and society more stable.
The application of business analytics in accounting
Joining business analytics (BA) in bookkeeping has become progressively basic due to the rising request for data-driven decision-making in a quickly advancing budgetary environment. As bookkeeping experts confront challenges such as complex information sets and a growing mechanical scene, the part of BA in bookkeeping hones is becoming more noticeable. Despite its potential, the broad appropriation of BA remains conflicting, with numerous organizations, however, completely tackling its benefits. This survey synthesizes the existing writing on the crossing point of business analytics and bookkeeping, looking at the openings and challenges related to this integration. A comprehensive investigation of peer-reviewed articles, case considerations, and industry reports distinguishes key subjects, counting the effect of BA on decision-making, operational productivity, and vital arranging. The discoveries demonstrate that whereas BA has the potential to improve bookkeeping homes, its appropriation is ruined by components such as a need for skill, asset imperatives, and resistance to altering inside conventional bookkeeping situations. The survey emphasizes the expanding significance of counterfeit insights (AI) and machine learning in reshaping bookkeeping forms, recommending that future headways in advances will play a basic part in quickening BA appropriation. The think tank moreover investigates the suggestions for bookkeeping experts and organizations, advertising proposals for overcoming these selection boundaries. Generally, the survey concludes that overcoming these challenges through ventures in instruction, mechanical foundation, and altered administration techniques is fundamental for bookkeeping experts to completely capitalize on the benefits of business analytics within the advanced time.
From Crisis to Opportunity: How Covid-19 Accelerated the Global Shift to Online Business
The COVID-19 pandemic served as an unparalleled driver for digital transformation, compelling firms globally to swiftly transition to online operations. The crisis caused significant changes to global supply chains, consumer behavior, and conventional business structures, while simultaneously expediting the adoption of digital technology and creating new prospects for innovation and resilience. This paper examines how the global health crisis accelerated the transition to e-commerce, cloud computing, artificial intelligence (AI), and remote labor, transforming sectors and changing the future of business. The transformation faced hurdles, including cybersecurity concerns, digital divisions, and operational inefficiencies that disproportionately affected small firms and underprivileged groups. Businesses that adopted digitalization acquired a competitive advantage, exhibiting enhanced agility, sustainability, and potential for long-term growth. As the economy recovers from the pandemic, the move to online shopping is expected to be a long-lasting structural change that will speed up both economic growth and technological progress. Governments and institutions will be essential in promoting digital inclusion, closing technical disparities, and cultivating a more equal digital environment. The pandemic-induced digital acceleration has fundamentally transformed global business dynamics, demonstrating that a catastrophe can serve as a crucial turning point for long-lasting economic transformation and opportunity.
Tanveer Ehsan Chowdhury Tanveer Ehsan Chowdhury
From Shadows to Sunrise: The Impact of Solar Power Plants on Enhancing Bangladesh's Economy
Bangladesh has had a substantial evolution in its energy sector, mostly propelled by the emergence of solar energy as a catalyst for economic development and stability. The government has deliberately utilized solar energy solutions to address ongoing power shortages, reduce dependence on fossil fuels, and enhance electricity availability for isolated and rural regions, capitalizing on ample sunlight. The transition to solar energy has markedly enhanced energy security, generated new job possibilities, and stimulated technical innovation, accompanied by considerable investments in renewable energy infrastructure. The extensive deployment of solar facilities has significantly improved industrial productivity and agricultural efficiency, bolstering economic resilience across several sectors. Moreover, solar energy projects have enabled small enterprises, expedited rural electrification efforts, and significantly diminished carbon emissions, establishing Bangladesh as a model for renewable energy implementation in underdeveloped countries. Even though Bangladesh has made a lot of progress, it still faces big problems. These include high initial investment costs, technical issues, and regulatory gaps that make it hard to use solar energy on a large scale. This review paper analyzes the transformational economic effects of solar energy in Bangladesh, highlighting its essential contribution to sustainable development, poverty reduction, and long-term energy autonomy. This assessment highlights the necessity for supporting government policies, financial incentives, and ongoing technology breakthroughs to enhance the growth and effectiveness of Bangladesh's solar energy initiatives by meticulously examining current difficulties and potential prospects.
Economic Growth Sustainable Development Bangladesh
Naznin Sultana Chaity Naznin Sultana Chaity
Empowering Change: The Impact of Microcredit on Social Business Development
Microcredit has developed as a transformational financial application, greatly influencing social business growth by promoting financial inclusion, entrepreneurship, and economic resilience within marginalized communities. This paper analyses the several functions of microcredit, emphasizing its impact on job creation, women's empowerment, and sustainable company development. Although microcredit has effectively improved economic mobility and self-sufficiency, its sustained efficacy is sometimes undermined by systemic obstacles, such as exorbitant interest rates, repayment hurdles, financial illiteracy, and regulatory discrepancies. This study consolidates recent work to evaluate how digital financial services, hybrid financing models, and regulatory interventions might mitigate these constraints and enhance the impact of microcredit on social entrepreneurs. Research suggests that the incorporation of financial literacy initiatives, the enhancement of digital microfinance options, and the adoption of gender-sensitive lending practices will enhance borrower results and ensure company viability. Moreover, a more robust regulatory framework is needed to guarantee responsible lending practices and fair access to credit. This study further offers a methodological analysis to improve dependability and build trust. The research highlights the necessity for ongoing innovation and flexible policy frameworks to transform microcredit into a sustainable development tool, therefore promoting social entrepreneurship, economic growth, and financial inclusion.
Sustainable Merchandising: Integrating Eco-Friendly Practices in Retail Product Presentation
The retail industry significantly contributes to worldwide economic development while simultaneously being a major cause of environmental deterioration due to energy consumption, packaging waste, and unsustainable resource utilization. With the escalation of environmental concerns, sustainable merchandising has become a pivotal strategy to diminish the ecological impact of retail operations. This study examines the incorporation of sustainable practices in the display of retail products, specifically within the textile sector. A thorough literature review and secondary data analysis were both used in the study to look into important topics like sustainable supply chain management, strategies for positioning environmentally friendly products, and the ethical and environmental problems that retailers face. The results emphasize that sustainable methods, including the use of recyclable materials, renewable energy systems, and circular economy principles, may improve a brand's reputation, cultivate customer confidence, and adhere to changing legal requirements. Researchers have recognized new strategies like digital commerce and sustainable transportation as effective ways to mitigate environmental consequences. Case studies of prominent organizations, such as Patagonia and Kotn, illustrate the concrete advantages of sustainability measures, including enhanced consumer loyalty, market expansion, and less environmental impact. This study highlights the increasing consumer inclination towards environmentally sustainable items and offers practical recommendations for retailers to synchronize with sustainability objectives, enhance operational efficiency, and support global climate initiatives.
Innovative Visual Merchandising Strategies in the Digital Era:Enhancing Retail Consumer Engagement
The review study analyses the impact of innovative visual merchandising tactics, facilitated by evolving technology, on customer engagement at the point of sale, specifically within the fashion sector. As the retail landscape changes toward a digital era, emerging technologies such as augmented reality (AR), interactive displays, and digital signage are transforming the way customers engage with items and the shopping environment. We performed a comprehensive analysis of the current literature, utilizing ideas related to consumer behaviour, purchasing experience, visual communication, and the integration of technology in visual merchandising. Although much contemporary study focuses on Generation Y (Gen Y), the results are relevant to a wider array of cohorts, including Generation Z and older generations, who are increasingly interacting with digital technology in retail environments. The study asserts that visual merchandising, in conjunction with digital technology, may profoundly affect customer behaviour by improving the buying experience across cognitive, emotional, sensory, and behavioural dimensions. The technologies used in visual merchandising are not just utilitarian instruments; they act as influencers, crafting immersive, personalized experiences that cultivate profound emotional ties with the brand. These technologies help merchants to attract new consumers, retain existing ones, and drive purchase choices through a more engaging and memorable shopping trip. The article ultimately finds that the use of digital technology in visual merchandising tactics is revolutionizing traditional retail experiences into dynamic, interactive environments that are crucial for influencing contemporary customer behaviour.
Chowdhury Tauhid Mahmud Chowdhury Tauhid Mahmud
Md. Estehad Chowdhury Md. Estehad Chowdhury
Shahriar Kabir Selim Shahriar Kabir Selim
Globalization and Textile Merchandising: How Global Supply ChainsInfluence Product Positioning and Market Research
Globalization has had a significant impact on the textile and garment industries, improving supply chains and market access. This article analyses the influence of global supply chains on product positioning and market research within the textile merchandising sector, emphasizing enhanced production efficiency, market variety, and innovation. It also tackles ethical concerns, environmental sustainability, and supply chain weaknesses. The research demonstrates the significance of contemporary technology and sustainable methodologies in influencing the future trajectory of the textile industry. Globalization has profoundly influenced the fast fashion industry, transforming supply chains, marketing strategies, and customer engagement. Nonetheless, the swift proliferation of globalization has also prompted concerns over sustainability, equity, and resource exploitation. The study underscores the necessity for a balanced strategy that prioritizes sustainability and ethical standards while capitalizing on the benefits of globalization to guarantee the equitable and environmentally responsible prosperity of the textile and garment sector.