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This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.

This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.

The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.

This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.

This study aims to explore the effects of cat-assisted therapy (Ca-AT) on a patient in their homes, specifically investigating the effects on patient’s memory, behavioral pathology and ability to perform activities of daily living, independently.

A case study design was used in patient’s homes using three measuring scales, namely, Mini-Mental State Examination (MMSE), Barthel index (BI) and Behavioral Pathology in Alzheimer’s Disease (AD) Rating Scale.

The MMSE and BI mean scores were increased, whereas the Behavioral Pathology mean score was decreased. Patient negative behaviors were improved specifically, aggressiveness, anxieties, phobias, and caregiver burden was decreased.

Patients with AD could significantly benefit from Ca-AT in their own homes, and it could decrease caregiving burden.

Ca-AT is a newly developed type of animal-assisted therapy that uses cats to treat patients, especially elderly people with AD, in their homes.

Scholarly interest in the business effects of organised crime (OC) has recently increased. This study aims to conduct a systematic literature review (SLR) on the conditions under which OC could pose a threat to or take control of firms within a particular context.

We use narrative synthesis and thematic analysis, with a sample of 46 theoretical and empirical studies published over the past 30 years on the relationship between OC and firms within the disciplines of Business, Management and Accounting (BMA).

SLR and thematic analysis show that scholarly interest has focused on four key domains: OC as a firm, the impact of OC on firms, firms’ efforts to counter OC’s influence and governmental interventions. Using medical metaphors, we also develop a diagram depicting the interplay between OC and firms within the BMA literature.

This study contributes to the literature shaping an agenda to steer future research towards these four key themes. The effectiveness of anti-OC tools and measures depends on a thorough understanding of local norms, behaviours and business practices. In addition to measurement and methodological challenges, several grey areas remain, including the distinction between criminal enterprises and legitimate businesses. Ambiguities also surround the circumstances under which the OC preys upon firms or employs them to establish dominance over a territory.

This study aims to investigate the consumer behavior toward telemedicine services in India during the COVID-19 pandemic onset. With lockdown restrictions and safety concerns in visiting brick-and-mortar clinics or hospitals during the pandemic, Telemedicine had emerged as a potent alternative for seeking redressal to health issues. Based on theory and focus interviews with the telemedicine users, the researchers proposed a model to understand the intent and actual usage of telemedicine in India.

The cross-sectional study undertaken used a questionnaire designed on a seven-point Likert scale and administered to respondents with the objective of identifying the determinants of intent and actual usage of telemedicine services. Simple random sampling was used to collect primary data. The data was cleaned and finally a sample of 405 responses complete in all respects was considered for analysis. The questionnaire comprised of 34 items and following the recommendation of Hair et al. (2016), which says the minimum sample size in structural equation modeling should be ten times the number of indicator variables, a sample size of 405 was deemed adequate.

The research paper finds that performance expectancy, attitude, credibility and self-efficacy positively impact the intention of consumers to use telemedicine services. As the effort expectancy or risk perception toward telemedicine increases the intent and actual usage of telemedicine decreases. The intention to use telemedicine emerged as a strong predictor of the actual usage of telemedicine. Intent to use telemedicine was explained 81.4% by its predictors of performance expectancy, effort expectancy, attitude, risk, credibility and self-efficacy, and actual usage was explained 79.9% by its predictors. This study also reports that telemedicine was found to be popular among chronic as well as episodic patients though the preference was skewed in favor of the episodic patients. One of the advantages of telemedicine is its availability round the clock, and the study found that 8 a. m. to 12 noon time slot as the most preferred slot for seeking telemedicine services.

Chang (2004) opined that telemedicine can fulfill the needs of all stakeholders: citizens, health-care consumers, medical doctors and health-care professionals, policymakers, and so on. Considering the promise telemedicine holds, this realm must be studied and leveraged to the full potential. The study found that patients were using telemedicine even for their day-to-day aliments. This indicates a growing popularity of telemedicine and as such an opportunity for telemedicine companies to leverage it. In India, pharmaceutical companies cannot give commercial advertisements for medicines, and the same can only be sold through a registered medical practitioner’s prescription. As such there is total dependency on the medical practitioner for the sale of medicines. Telemedicine companies offer services of home delivering medicines clubbed with medical consultation thus giving them forward integration in their business models. Using telemedicine the patients had control over the timings of the services offered, and as such the waiting time to get a consultation and subsequent treatment was reduced considerably. Best medical advice from across the globe is available to the patient at less cost. Medical practitioners also stand to benefit as they can treat a variety of cases, collaborate among the medical fraternity and give consultation safely in case of fatal contagious diseases.

This study points to a definite growing popularity of telemedicine services not only in episodic patients but also chronic patients. Telemedicine with its unique advantages holds the promise to grow exponentially in the future and is a compelling health-care segment to focus on for delivering health-care solution to the geographically distant consumers.

Everyone is extremely concerned about environmental protection and health safety due to the rise in living standards. Plant-derived natural dyes have garnered much industrial attention in food, pharmaceutical, textile, cosmetics, etc. owing to their health and environmental benefits. The present study aims to focus on the elimination of the use of synthetic dyes and provides brief information about natural dyes, their sources, extraction procedures with characterization and various advantages and disadvantages.

In producing natural colors, extraction and purification are essential steps. Various conventional methods used till date have a low yield, as these consume a lot of solvent volume, time, labor and energy or may destroy the coloring behavior of the actual molecules. The establishment of proper characterization and certification protocols for natural dyes would improve the yielding of natural dyes and benefit both producers and users.

However, scientists have found modern extraction methods to obtain maximum color yield. They are also modifying the fabric surface to appraise its uptake behavior of color. Various extraction techniques such as solvent, aqueous, enzymatic and fermentation and extraction with microwave or ultrasonic energy, supercritical fluid extraction and alkaline or acid extraction are currently available for these natural dyes and are summarized in the present review article.

If natural dye availability can be increased by the different extraction measures and the cost of purified dyes can be brought down with a proper certification mechanism, there is a wide scope for the adoption of these dyes by small-scale dyeing units.

The emergence of the COVID-19 pandemic changed the way in which education was delivered in early 2020, and the impacts of these changes continue to be questionable. The aims of this study were to evaluate: (1) the results obtained by students of the Dentistry course in the progress test carried out both before and after the pandemic, (2) the results obtained by a specific group of students who took the test in 2019–2022, and compare their results and (3) subjects that showed a reduction in the percentage of correct answers when the two tests were compared.

The progress test consisting of 100 multiple choice questions was applied before and after the pandemic to all students in the Dentistry course. The analyses were performed using the IBM SPSS for Statistics v.26 software program. The level of significance of 5% was adopted (<0.05).

The test was applied to 320 students in 2019 and to 272 in 2022, of whom the sample of this study was composed. The mean score values in 2019 (M = 49.10; SD = 12.03) were significantly (p = 0.026) higher than those in the year 2022 (M = 46.97; SD = 12.15), with the disciplines in the area of specific knowledge showing a greater drop in the percentage of correct answers by students. This study showed that the emergency remote education had a negative effect on the academic performance of students, based on the progress testing as an evaluation method.

Many studies that assessed the impacts of the pandemic on teaching were focused on the opinions of students. However, the great advantage of our study was the use of a theoretical assessment tool to verify student performance. The post-pandemic landscape beckons for comprehensive inquiries into these domains. This type of research would be valuable for gathering evidence relative to the performance of students after the emergency remote education.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Interprofessional practice (IPP) is one way to structure collaborations to more effectively meet the complex needs of students in educational settings. This article explores the lessons learned when one research team implemented interprofessional education (IPE) experiences in partnership with a public elementary school and pre-service professionals from elementary education, special education and communication science and disorders.

This reflective article explores the lived experiences of researchers and partners who completed an IPE experience within one professional development school’s site. Researcher anecdotes are included to support the viewpoints shared.

It was discovered that IPE experiences are essential to facilitate meaningful collaborations for pre-service professionals to learn with and from one another; however, this requires time, preparation and is most effective when teacher mentors and university professors lead with vulnerability and model flexibility. Investment in IPE is challenging but worth the effort when learning outcomes are realized.

Specific details regarding the structure of this experience are shared as well as future directional goals for programs hoping to implement IPE in their professional practice programs.

The purpose of this paper is to identify the potential and the challenges for different firms in adopting an AI-first strategy. The study attempts to discern if any company can prioritize AI at the forefront of their strategic plans.

Drawing from illustrative examples from well-known AI-leaders like Netflix and Spotify, as well as from upcoming AI startups and industry incumbents, the paper explores the strategic role of AI in core business processes and customer value creation. It also discusses the advent and implications of generative AI tools since late 2022 to firms’ business strategies.

The authors identify three types of AI-first strategies, depending on firms’ starting points: digital tycoon, niche carver and asset augmenter. The authors discuss how each strategy can aim to achieve data, algorithmic and execution advantages, and what the strategic bottlenecks and risks are within each strategy.

To the best of the authors’ knowledge, this paper is the first to systematically describe how companies can form “AI-first” strategies from different starting points. This study includes actionable examples from known industry players to more emerging startups and industrial incumbents.

Surgical services are settings where resilient performance (RP) is necessary to cope with a wide range of variabilities. Although RP can benefit from a supportive built environment (BE), prior studies have focused on the operating room, giving scant attention to support areas. This study takes a broader perspective, aiming at developing BE design knowledge supportive of RP at the surgical service as a whole.

Seven BE design prescriptions developed in a previous work in the context of internal logistics of hospitals, and thus addressing interactions between workspaces, were used as a point of departure. The prescriptions were used as a data analysis framework in a case study of the surgical service of a medium-sized private hospital. The scope of the study included surgical and support areas, in addition to workflows involving patients and family members, staff, equipment, sterile instruments and materials, supplies, and waste. Data collection included document analysis, observations, interviews, and meetings with hospital staff.

Results identified 60 examples of using the prescriptions, 77% of which were related to areas other than the operating rooms. The developed design knowledge is framed as a set of prescriptions, examples, and their association to workflows and areas, indicating where it should be applied.

The design knowledge is new in surgical services and offers guidance to both BE and logistics designers.