Eastern Washington University

ABSTRACT We investigate how Critical Audit Matter (CAM) attribution and auditors' response readability influence investors' perceptions of audit quality and their valuation revision judgements. Using an experiment with nonprofessional investors, we find that investors perceive the highest audit quality when auditors attribute CAMs to management and provide more readable responses. In addition, given a more readable response, CAM attribution to management leads to more negative valuation revisions than attribution to the nature of accounts through a positive indirect effect and a negative direct effect. Our study contributes to the recent CAM literature and provides implications for regulators, auditors, and investors.

In this research, artificial intelligence (AI) and virtual reality (VR) are combined to address challenges in handwriting. A pipeline has been developed to enable users to practice handwriting within their individualized VR workspace. Next, the texts were parsed by a handwritten text recognition (HTR) model. The proposed approach has demonstrated the potential to motivate learners to practice handwriting in VR and could also serve as a valuable tool for mastering a foreign language. With a robust HTR model, this approach also facilitates tracking learning progress through AI-generated feedback. In addition to enhancing learning, the proposed approach can serve as an early intervention and individualized management strategy for individuals experiencing dysgraphia-related challenges.

The current system in e-commerce platforms accepts product feedback in the form of star ratings and textual reviews. However, due to the short length of these textual reviews, the detailed aspects of products are missed most of the time. To overcome these limitations, the current research proposes a framework based on the Large Language Model (LLaMA 3.2) to generate reviews from ratings of the product's aspects. The proposed framework generates reviews in Hindi-English mixed language to make them more engaging for the Indian population. The results show that AI-generated reviews score better than human-written reviews in clarity (3.55 vs. 3.01), accuracy (3.49 vs. 2.51), and keyword relevance (67.4% vs. 35.7%). These AI-generated reviews were found to be very similar to human-written reviews and were indistinguishable in 59.7% of cases of human evaluation.

Disadvantaged populations age faster and develop chronic disease earlier, but the molecular conduit from social adversity to biology is not fully defined. This review synthesizes molecular, epidemiological, and policy evidence along a single axis: p53-governed cellular senescence. Genomic and metabolic stress stabilize p53, induce p21-mediated cell cycle arrest, and trigger a pro-inflammatory secretory program that compromises tissue function. Conditions concentrated in communities with limited resources, such as, air pollution, ultra-processed diets, chronic stress, and obesity activate these pathways and expand senescent populations in vascular, metabolic, and immune tissues, amplifying atherosclerosis, insulin resistance, and cancer progression. Senolytics (dasatinib plus quercetin, navitoclax, and fisetin) and senomorphics (metformin and rapamycin) show early benefit signals, but translation must be equity-first. The next step is to conduct community-engaged, cluster-randomized pilots that pair senotherapeutics with neighborhood exposure abatement, use co-primary endpoints (multi-omic senescence signatures plus exposure indices), stratify by deprivation, apply adaptive dosing, and track affordability and access, yielding decision rules for scalable, equity-ready implementation.

This study examines the relationship between infrastructural labor and the everyday praxis of transportation planners in tribal communities in the Northwest United States. We reveal how the relationship-building and strategic positioning of tribal transit planners constitutes a form of infrastructural labor. This labor yields a form of “community-cultivating” technical-material infrastructure vital for enhancing people’s mobility and, thus, life opportunities in an otherwise starkly immobile lived experience. Illuminated are the socio-political, affective, and (in)formal contours of this labor as it simultaneously contests and sustains colonial legacies, is mobilized by (and mobilizes) strong emotive currents ranging from despair to hope, and operates as the connective tissue between spaces of informal social connection and the domain of formality in which state actors, such as planners, are typically thought to be confined. In the process, the study nuances our understanding of infrastructural politics with a notable twist, as planners are usually depicted as technocratic-state actors, (re)productive of colonial legacies and neoliberal capitalism. Data is drawn from semi-structured interviews whereby tribal transit planners are revealed to tenaciously work through an infrastructure of social relations to collectively secure the resources they need, what we identify as a condition of possibility for generating more fundamental change. We conclude by discussing the theoretical and political implications of the study and offer two contradictory interpretations of our findings.

Abstract Background Asset management organizations have integrated new technologies before, but this trend is expected to reach its peak in the coming years. Investors using technical instruments buy financial products from asset management companies (AMCs). Thus, AMC is working diligently to enhance its operations and processes, enabling investors to have seamless transaction experiences across its various platforms through simplified procedures and efficient management. Objectives This study examines the performance drivers of AMCs, more specifically, how fundamental components contribute to business excellence by improving firm procedures and operations and creating new investor experiences. Methods/Approach The report uses data from 387 asset management professionals from 10 businesses. In India, 10 prominent AMCs provided 387 valid replies to a work survey. The analysis was conducted using the PLS-SEM approach. Results The findings indicate that Industry 4.0, business process management, and Lean Six Sigma facilitate operational excellence and are key drivers of achieving business excellence in asset management firms in India. Conclusions Organizations can achieve business excellence by applying concepts from Industry 4.0, business process management, Lean Six Sigma, and operational excellence. This is among the few empirical studies examining the enablers of business excellence in Indian AMCs.

The rapid proliferation of the Internet of Things (IoT) has brought unprecedented connectivity, transforming industries and daily life. However, this integration comes with critical cybersecurity challenges, exposing IoT networks to sophisticated threats like Distributed Denial-of-Service (DDoS) attacks and other malicious activities. This paper investigates IoT vulnerabilities by analyzing the CICIoT2023 dataset and employing advanced machine learning techniques, specifically Random Forest and XGBoost, to detect and mitigate anomalies in network traffic. Through rigorous preprocessing, feature selection, and model tuning, both algorithms demonstrated exceptional performance, achieving accuracy and F1 scores exceeding 99%. XGBoost outperformed Random Forest in key metrics, showcasing its scalability and precision for complex datasets, while Random Forest proved advantageous for resource-constrained environments due to its simplicity and interpretability. This research not only highlights the strengths of machine learning in IoT security but also provides actionable insights for real-time anomaly detection and adaptive defenses. Future work aims to enhance these models for real-world deployment, adaptive learning, and broader applicability across diverse IoT ecosystems, ensuring a secure and resilient interconnected landscape.

PurposeBlockchain is a nascent technology that has the ability to revolutionize the workings of the educational landscape. However, there are several barriers to the adoption of blockchain technology (BCT). So, this paper aims to determine, rank and analyse the interdependent contextual relationship among the BCT adoption barriers within the education management system (EMS) of higher education institutes.Design/methodology/approachThe present research principally uses the technology-organization-environment model for the classification of BCT adoption barriers in the EMS. An integrated dual phase best-worst method and interpretive structural modelling – cross-impact matrix multiplication applied to classification (BWM-ISM-MICMAC) analysis is used for the identification, prioritization and analysis of the contextual relationships among the BCT barriers.FindingsThe findings of the research show that the environmental barrier among the primary barriers and the lack of government initiatives among the sub-barriers are crucial barriers to BCT adoption in the EMS.Research limitations/implicationsCertain barriers might not be selected during the literature review and expert opinions might be biased. Future studies should use structural equation modelling to validate the relationships between BCT barriers and conduct similar research across other business sectors to provide valuable insights for scholars and practitioners alike.Practical implicationsThe study facilitates a better perspective of BCT barriers and explores possible solutions more comprehensively for policymakers and field managers. Consequently, it offers viable suggestions for the successful and effective implementation of BCT within the EMS.Originality/valueThe concept of using the blockchain in academics is a novel one. This study establishes a crucial research base for the smooth adoption of BCT in EMS.