Blockchain Adoption for Provenance and Traceability in the Retail Food Supply Chain

Blockchain has evolved as one of the disruptive technologies in the landscape of business. The study aims to investigate drivers of consumer adoption of blockchain for product origin and track to trace history before making a purchase. An extended technology adoption model (TAM) has been proposed to examine the consumer perspective for blockchain adoption in the food supply chain. Based on the survey of 208 retail consumers the proposed model was validated using variance-based structure equation modeling. Findings of the study emphasize the significant role of perceived security and privacy in developing trust, ease of use, and usefulness of blockchain-enabled systems. The relationship between perceived ease of use and attitude is mediated through perceived usefulness. The strong influence of attitude on adoption intention represents the consumer interest for blockchain to understand the product provenance. Study provides vital insights for successful blockchain implementation to enhance supply chain effectiveness.

Determinants of e-learning acceptance amongst Iranian postgraduate students

E-learning can address some of the unmet needs of learners and educational communities; however, not all learners and educators accept e-learning as a delivery modality. This research endeavored to study the factors which affect e-learning acceptance among Iranian post-graduate students using the Davis Technology Acceptance Model (TAM) and to identify the changes which would facilitate their improved acceptance and subsequent wider use of e-learning. This descriptive-correlation study was conducted by surveying 320 Iranian postgraduate students using a self-reporting questionnaire. Structural equation modeling was used for data analysis through LISREL software. Results revealed sufficient validity and reliability of the TAM among Iranian postgraduate medical students. Perceived ease of use, perceived usefulness of e-learning, students’ attitudes toward e-learning, and the intention to use e-learning positively affected e-learning’s acceptance (p < 0.05) among Iranian postgraduate students. According to the results, attitudes toward e-learning have more predictive power than other TAM constructs. Therefore, emphasis on students’ favorable attitudes toward e-learning can be effective in accelerating its acceptance and will progress students’ learning outcomes.

Key Factors Affecting User Adoption of Open-Access Data Repositories in Intelligence and Security Informatics: An Affordance Perspective

Rich, diverse cybersecurity data are critical for efforts by the intelligence and security informatics (ISI) community. Although open-access data repositories (OADRs) provide tremendous benefits for ISI researchers and practitioners, determinants of their adoption remain understudied. Drawing on affordance theory and extant ISI literature, this study proposes a factor model to explain how the essential and unique affordances of an OADR (i.e., relevance, accessibility, and integration) affect individual professionals' intentions to use and collaborate with AZSecure, a major OADR. A survey study designed to test the model and hypotheses reveals that the effects of affordances on ISI professionals' intentions to use and collaborate are mediated by perceived usefulness and ease of use, which then jointly determine their perceived value. This study advances ISI research by specifying three important affordances of OADRs; it also contributes to extant technology adoption literature by scrutinizing and affirming the interplay of essential user acceptance and value perceptions to explain ISI professionals' adoptions of OADRs.

Automated Annotations for AI Data and Model Transparency

The data and Artificial Intelligence revolution has had a massive impact on enterprises, governments, and society alike. It is fueled by two key factors. First, data have become increasingly abundant and are often available openly. Enterprises have more data than they can process. Governments are spearheading open data initiatives by setting up data portals such as data.gov and releasing large amounts of data to the public. Second, AI engineering development is becoming increasingly democratized. Open source frameworks have enabled even an individual developer to engineer sophisticated AI systems. But with such ease of use comes the potential for irresponsible use of data. Ensuring that AI systems adhere to a set of ethical principles is one of the major problems of our age. We believe that data and model transparency has a key role to play in mitigating the deleterious effects of AI systems. In this article, we describe a framework to synthesize ideas from various domains such as data transparency, data quality, data governance among others to tackle this problem. Specifically, we advocate an approach based on automated annotations (of both data and the AI model), which has a number of appealing properties. The annotations could be used by enterprises to get visibility of potential issues, prepare data transparency reports, create and ensure policy compliance, and evaluate the readiness of data for diverse downstream AI applications. We propose a model architecture and enumerate its key components that could achieve these requirements. Finally, we describe a number of interesting challenges and opportunities.

The Impact of Student’s Anxiety on u sing Learning Management Systems in Covid 19 Pandemic

The COVID-19 pandemic has compelled many educational institutions worldwide to use learning management systems (LMS) to deliver their courses. This study aims to determine the constituents that affect scholars when using LMS for graduation during the pandemic. This research also examines the impact of the students' anxiety level when using the LMS by conducting multiple group analyses with the partial least square's method. The results show a significant influence on the students' anxiety level when using the LMS. Students who have a low level of anxiety exhibited insignificant communication quality regarding the perceived ease of use and perceived usefulness. Meanwhile, students with a high level of anxiety highlight a consequential effect of communication quality in the perceived ease of use and usefulness. Moreover, students with a low level of anxiety displayed significantly high-perceived usefulness, satisfaction, and subject norm when using the LMS. In contrast, students with a high level of anxiety did not display perceived usefulness, satisfaction, or subject norm when using the LMS. As a result of the findings from this research, concrete effects can be provided for educationalists, policymakers, and practitioners, who want to advance functional procedures to enhance the design of the LMS during COVID-19.

Will proximity mobile payments substitute traditional payments? Examining factors influencing customers' switching intention during the COVID-19 pandemic

PurposeThe objective of this study is twofold: first, to investigate the determinants of customers' switching intention from traditional payments to proximity mobile payments (PMPs) during the COVID-19 pandemic for specific insight on how these factors shape customers' switching intentions; second, this study discusses the relationship between traditional payments and PMP services.Design/methodology/approachThe study data were collected from individual customers who used both traditional payments and PMP in a physical store during the COVID-19 pandemic. Structural equation modeling (SEM) was applied to analyze the validity of the variables and the causal relationships among variables based on 305 valid data.FindingsThe results show that the factor of traditional payments, that is, dissatisfaction positively and significantly influenced customers' switching intention. Factors of PMP, namely perceived usefulness (PUF) and perceived ease of use (EOU), positively and significantly impacted switching intention. In addition, the relationship between traditional payments and PMP, that is, low perceived substitutability was found to negatively influence switching intention, PUF and EOU.Research limitations/implicationsFirst, the study targets are customers with experience in using PMP after the COVID-19 pandemic. It is suggested to compare customers who had experience using PMP before and after the COVID-19 pandemic. Second, although cash and bank cards belong to the category of traditional payments, they have different degrees of contact when transactions occur. The contact rate of bank cards is lower than that of cash. This study did not differentiate between cash and bank cards, which is the main limitation.Originality/valueFirst, this study provides a reference to examine mobile payment usage from the perspective of both incumbent and alternative services conjointly under emergency situations, especially during the COVID-19 pandemic. Second, the application of migration theory to the context of mobile payment extends existing research on mobile payment. Third, this study is among the first to investigate the relationship between traditional payments and PMP.

T2Candida Assay in the Diagnosis of Intraabdominal Candidiasis: A Prospective Multicenter Study

The T2Candida magnetic resonance assay is a direct-from-blood pathogen detection assay that delivers a result within 3–5 h, targeting the most clinically relevant Candida species. Between February 2019 and March 2021, the study included consecutive patients aged >18 years admitted to an intensive care unit or surgical high-dependency unit due to gastrointestinal surgery or necrotizing pancreatitis and from whom diagnostic blood cultures were obtained. Blood samples were tested in parallel with T2Candida and 1,3-β-D-glucan. Of 134 evaluable patients, 13 (10%) were classified as having proven intraabdominal candidiasis (IAC) according to the EORTC/MSG criteria. Two of the thirteen patients (15%) had concurrent candidemia. The sensitivity, specificity, positive predictive value, and negative predictive value, respectively, were 46%, 97%, 61%, and 94% for T2Candida and 85%, 83%, 36%, and 98% for 1,3-β-D-glucan. All positive T2Candida results were consistent with the culture results at the species level, except for one case of dual infection. The performance of T2Candida was comparable with that of 1,3-β-D-glucan for candidemic IAC but had a lower sensitivity for non-candidemic IAC (36% vs. 82%). In conclusion, T2Candida may be a valuable complement to 1,3-β-D-glucan in the clinical management of high-risk surgical patients because of its rapid results and ease of use.

PErsonalized Treatment by Real-time assessment (PETRA): A web-application for personalized diaries in psychiatric care

Background: Smartphone self-monitoring through ecological momentary assessment (EMA) provides insights into the daily lives of people in psychiatric treatment and has the potential to improve their care. Currently, no clinical tools are available that help clients and clinicians with creating personalized EMA diaries and interpreting the gathered data. Integration of EMA in treatment is therefore difficult.Objective: To develop a web-based application for personalized EMA in routine psychiatric care, in close collaboration with all stakeholders (i.e., clients, clinicians, researchers, and software developers). Methods: We engaged 52 clients with mood, anxiety, and/or psychotic disorders and 45 clinicians (psychiatrists, psychologists, and psychiatric nurses) in interviews, focus groups, and usability sessions. We used human-centered design principles to determine important requirements for the web-app and designed high-fidelity prototypes that were continuously reevaluated and adapted. Results: The iterative development process resulted in PETRA (PErsonalized Treatment by Real-time Assessment), which is a scientifically grounded web-app for the integration of personalized EMA in clinical care. PETRA includes a decision aid to support clients and clinicians with constructing personalized EMA diaries, an EMA diary item repository, a text-message-based diary delivery system, and a feedback module for visualizing the gathered EMA data. PETRA is integrated in electronic health record (EHR) systems to ensure ease-of-use and sustainability, and adheres to privacy regulations.Conclusions: PETRA was built to fulfill the needs of clients and clinicians for a user-friendly and personalized EMA tool embedded in routine psychiatric care. PETRA is unique in this co-development process, its extensive yet user-friendly personalization options, its integration in EHR systems, its transdiagnostic focus, and its strong scientific foundation in the design of EMA diaries and feedback. The clinical effectiveness of integrating personalized diaries via PETRA into care awaits further research. As such, PETRA paves the way for a systematic investigation into the utility of personalized EMA for routine mental health care.

The WOOL Dialogue Platform: Enabling Interdisciplinary User-Friendly Development of Dialogue for Conversational Agents

Health coaching applications can include (embodied) conversational agents as coaches. The development of these agents requires an interdisciplinary cooperation between eHealth application developers, interaction designers and domain experts. Therefore, proper dialogue authoring tools and tools to integrate these dialogues in a conversational agent system are essential in the process of creating successful agent-based applications. However, we found no existing open source, easy-to-use authoring tools that support multidisciplinary agent development. To that end, we developed the WOOL Dialogue Platform. The WOOL Dialogue Platform provides the eHealth and conversational agent communities with an open source platform, consisting of a set of easy to use tools that facilitate virtual agent development. The platform consists of a dialogue definition language, an editor, application development libraries and a web service. To illustrate the platform’s possibilities and use in practice, we describe two use cases from EU Horizon 2020 research projects. The WOOL Dialogue Platform is an ‘easy to use, and powerful if needed’ platform for the development of conversational agent applications that is seeing a slow but steady increase in uptake in the eHealth community. Developed to support dialogue authoring for embodied conversational agents in the health coaching domain, this platform’s strong points are its ease of use and ability to let domain experts and agents technology experts work together by providing all parties with tools that support their work effectively.

Ten Good Reasons to Practice Neuroultrasound in Critical Care Setting

In the beginning, cerebral ultrasound (US) was not considered feasible because the intact skull was a seemingly impenetrable obstacle. For this reason, obtaining a clear image resolution had been a challenge since the first use of neuroultrasound (NUS) for the assessment of small deep brain structures. However, the improvements in transducer technologies and advances in signal processing have refined the image resolution, and the role of NUS has evolved as an imaging modality for the brain parenchyma within multiple pathologies. This article summarizes ten crucial applications of cerebral ultrasonography for the evaluation and management of neurocritical patients, whose transfer from and to intensive care units poses a real problem to medical care staff. This also encompasses ease of use, low cost, wide acceptance by patients, no radiation risk, and relative independence from movement artifacts. Bedsides, availability and reliability raised the interest of critical care intensivists in using it with increasing frequency. In this mini-review, the usefulness and the advantages of US in the neurocritical care setting are discussed regarding ten aspects to encourage the intensivist physician to practice this important tool.