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The purpose of this study is to describe the design and validation of a three-dimensional (3D)-printed phantom of a uterus to support the development of uterine balloon tamponade devices conceived to stop post-partum haemorrhages (PPHs).

The phantom 3D model is generated by analysing the main requirements for validating uterine balloon tamponade devices. A modular approach is implemented to guarantee that the phantom allows testing these devices under multiple working conditions. Once finalised the design, the phantom effectiveness is validated experimentally.

The modular phantom allows performing the required measurements for testing the performance of devices designed to stop PPH.

PPH is the leading obstetric cause of maternal death worldwide, mainly in low- and middle-income countries. The proposed phantom could speed up and optimise the design and validation of devices for PPH treatment, reducing the maternal mortality ratio.

To the best of the authors’ knowledge, the 3D-printed phantom represents the first example of a modular, flexible and transparent uterus model. It can be used to validate and perform usability tests of medical devices.

During COVID-19, this study aims to evaluate the crisis communication strategies (CCS) of Fortune 500 medical device businesses. These companies’ CCS adoption is evaluated using data from the microblogging site Twitter.

A total of 11,569 tweets were collected over the course of a year, from 31 December 2019 to 31 December 2020, and analysed using COVID-19’s pre-crisis, crisis and new normal stages. The data acquired from Twitter is assessed using latent Dirichlet allocation-based topic modelling, valence aware dictionary for sentiment reasoning sentiment analysis and emotion recognition analysis and then further examined using fuzzy set qualitative comparative analysis to build a configurational model. The findings were compared to Cheng’s (2018, 2020) integrated strategy toolkit for organisational CCS, which included 28 strategies.

With positive sentiments across stages, companies chose “information providing”, “monitoring” and “good intentions” as the CCS. In the crisis and new normal stages of COVID, the emotion of “depression” was observed.

Researchers would be able to assess the CCS used through visual aids in the future by conducting a cross-industry examination using image analytics. Furthermore, by prolonging the study’s duration, long-term changes in the CCS can be investigated.

Companies should send real-time information to their stakeholders via social media during a pandemic, conveying good intentions and positive sentiments while remaining neutral.

To the best of the authors’ knowledge, this is one of the first studies to investigate the CCS patterns used by medical device businesses to communicate via social media during a pandemic.

The increase in the number of healthcare wearable (Internet of Things) IoT options is making it difficult for individuals, healthcare experts and physicians to find the right smart device that best matches their requirements or treatments. The purpose of this research is to propose a framework for a recommender system to advise on the best device for the patient using machine learning algorithms and social media sentiment analysis. This approach will provide great value for patients, doctors, medical centers, and hospitals to enable them to provide the best advice and guidance in allocating the device for that particular time in the treatment process.

This data-driven approach comprises multiple stages that lead to classifying the diseases that a patient is currently facing or is at risk of facing by using and comparing the results of various machine learning algorithms. Hereupon, the proposed recommender framework aggregates the specifications of wearable IoT devices along with the image of the wearable product, which is the extracted user perception shared on social media after applying sentiment analysis. Lastly, a proposed computation with the use of a genetic algorithm was used to compute all the collected data and to recommend the wearable IoT device recommendation for a patient.

The proposed conceptual framework illustrates how health record data, diseases, wearable devices, social media sentiment analysis and machine learning algorithms are interrelated to recommend the relevant wearable IoT devices for each patient. With the consultation of 15 physicians, each a specialist in their area, the proof-of-concept implementation result shows an accuracy rate of up to 95% using 17 settings of machine learning algorithms over multiple disease-detection stages. Social media sentiment analysis was computed at 76% accuracy. To reach the final optimized result for each patient, the proposed formula using a Genetic Algorithm has been tested and its results presented.

The research data were limited to recommendations for the best wearable devices for five types of patient diseases. The authors could not compare the results of this research with other studies because of the novelty of the proposed framework and, as such, the lack of available relevant research.

The emerging trend of wearable IoT devices is having a significant impact on the lifestyle of people. The interest in healthcare and well-being is a major driver of this growth. This framework can help in accelerating the transformation of smart hospitals and can assist doctors in finding and suggesting the right wearable IoT for their patients smartly and efficiently during treatment for various diseases. Furthermore, wearable device manufacturers can also use the outcome of the proposed platform to develop personalized wearable devices for patients in the future.

In this study, by considering patient health, disease-detection algorithm, wearable and IoT social media sentiment analysis, and healthcare wearable device dataset, we were able to propose and test a framework for the intelligent recommendation of wearable and IoT devices helping healthcare professionals and patients find wearable devices with a better understanding of their demands and experiences.

Telemedicine, similarly to social media, accelerates information exchange, enriches information, provides better access to information and, furthermore, has an impact on mobilizing resources in business-to-business relationships. This paper aims to contribute to the understanding of the changes brought about by telemedicine, as a new technology, in patient routes.

This case study method was applied to examine five health-care protocols through their patient routes (series of activities) with and without telemedicine technology. The ARA model was applied to examine the changes telemedicine engendered in relation to activities, resources and actors. The strategy of visual mapping was applied for the comparative analysis.

The analyzed cases show that the new resources applied through telemedicine technology modified the number and substance of relevant activities and the set and role of actors who were involved. The quantity or the availability of output information increased in patient routes when new resources were added by telemedicine technology. When technology change occurred, any change in data or information systems – the two building blocks of information – could result in new or modified activities. If data that is used or produced while undertaking an activity change simultaneously along with the information system used for encrypting this data, then this “joint change” will certainly entail some kind of change in the set of activities, resources or actors that are involved. If not, then the activities continued the same as with the face-to-face protocol (without the new technology).

The novelty of the paper is that the results highlight the role of information in the extent of change in interactions induced by new technology. Findings about such changes show how information influenced by activities, resources and actors can help decision-makers in relation to the use of telemedicine.

This study aims to investigate the supply chain gaps during the COVID-19 pandemic in Tanzania amid the pandemic era.

This study adopted a mixed approach, using both structured questionnaires and individual interviews to gather raw data (quantitative and qualitative data). To assess quantitative data for statistical (descriptive and inferential) analysis, this study used a sample of 57 wholesale and retail pharmacies and 10 hospital pharmacies, which were randomly selected. The thematic analysis was applied to the gathered qualitative data to authenticate the quantitative findings and conclusions which were the outcome of the descriptive and inferential analysis (binary logistics regression) analysed by the SPSS.

The results revealed the presence of various supply chain gaps in terms of target gaps, time gaps and coverage gaps. This study highlighted the disruption on demand and uncertainty in business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

The results revealed the presence of various supply chain gaps (in terms of target gaps, time gaps and coverage gaps), underlined the disruption in demand and uncertainty in the business environment as ways that the COVID-19 pandemic contributed to the gaps and revealed the negative effects of the supply chain gaps on the effectiveness of medical supplies in Tanzania.

Data generated and used in this study is from participants from one country only (Tanzania), despite the supply chain gaps being common to many developing countries in general.

This study provides a novel framework in medical supply chain literature by identifying numerous disruptions in the medical supply chain which emerged during the COVID-19 emergence and serves as a basis for future studies on how to counter the gaps and rebuild a resilient and sustainable medical supply chain in developing countries.

This study aims to investigate determinants such as performance expectancy (PE), health beliefs (HB), technological compatibility, trust and social influence (SI) of customers' efforts to cope with problems associated with using wearable health technology, thereby determining their use intention of such products. The moderating effect of the demographic variables is also investigated.

An online survey was used to collect panel data from 285 respondents in China. Structural equation modeling was used to test the hypotheses, and interaction moderation was applied to test the moderating effect of the demographic variables.

The results show that HB, technological compatibility, trust and SI significantly impact coping efforts associated with usage, which significantly influences intention to use. Only income significantly moderated the effect of coping efforts on the intention to use.

This is the first study combining coping theory and UTAUT to develop a model of drivers that encourages customers to overcome the constraints of using wearable technologies.

The Covid-19 pandemic generated significant changes in the operating methods of hospital logistics departments. The objective of this research is to understand how these changes took place, what collaboration mechanisms were developed with clinical authorities and, to what extent, logistics and clinical care activities should be decoupled to maximize each area's contribution?

The case study is selected to investigate practices implemented during the COVID-19 pandemic in hospitals in Canada. The pandemic presented an opportunity to contrast practices implemented in response to this crisis with those historically used in this environment.

The strategy of decoupling logistical tasks of an operational nature from clinical activities is well-founded and helps free clinical staff from tasks for which they are not trained. However, the decoupling of operational tasks should be combined with an integration of the clinical information flow to the logistics hub players. With this clinical information, the logistics hub can generate its full potential enabling better inventory management decisions to be made.

The concept of decoupling is studied to identify configurations that offer the best benefits for clinical staff.

The purpose of this study is, to compare laser-based additive manufacturing and subtractive methods. Laser-based manufacturing is a widely used, noncontact, advanced manufacturing technique, which can be applied to a very wide range of materials, with particular emphasis on metals. In this paper, the governing principles of both laser-based subtractive of metals (LB-SM) and laser-based powder bed fusion (LB-PBF) of metallic materials are discussed and evaluated in terms of performance and capabilities. Using the principles of both laser-based methods, some new potential hybrid additive manufacturing options are discussed.

Production characteristics, such as surface quality, dimensional accuracy, material range, mechanical properties and applications, are reviewed and discussed. The process parameters for both LB-PBF and LB-SM were identified, and different factors that caused defects in both processes are explored. Advantages, disadvantages and limitations are explained and analyzed to shed light on the process selection for both additive and subtractive processes.

The performance of subtractive and additive processes is highly related to the material properties, such as diffusivity, reflectivity, thermal conductivity as well as laser parameters. LB-PBF has more influential factors affecting the quality of produced parts and is a more complex process. Both LB-SM and LB-PBF are flexible manufacturing methods that can be applied to a wide range of materials; however, they both suffer from low energy efficiency and production rate. These may be useful when producing highly innovative parts detailed, hollow products, such as medical implants.

This paper reviews the literature for both LB-PBF and LB-SM; nevertheless, the main contributions of this paper are twofold. To the best of the authors’ knowledge, this paper is one of the first to discuss the effect of the production process (both additive and subtractive) on the quality of the produced components. Also, some options for the hybrid capability of both LB-PBF and LB-SM are suggested to produce complex components with the desired macro- and microscale features.

While the COVID-19 pandemic wreaked havoc across the globe in 2020 and early 2021, Vietnam made some achievements in containing this virus. This study aims to focus on how government response could influence public compliance in Vietnam in 2020 (the first pandemic year).

The authors used data gathered from individuals residing in Vietnam during the COVID-19 social distancing in April 2020. An online survey was used to collect the data. To conduct the empirical analysis, we used a structural equation model (SEM). The data were analyzed using SPSS 25 and AMOS 24.

Government response was positively associated with public compliance through the mediating roles of trust in government and support for government.

This research provides implications for crisis management in developing countries during a public health crisis, especially when or where vaccines are unavailable.

This research is among the first attempts that examine how government response enhances citizen compliance directly and indirectly through the mediating roles of citizen trust in government and citizen support for government.

The purpose of this study is to numerically investigate the geometric influence of different corrugation profiles (rectangular, trapezoidal and triangular) of varying heights on the flow and the natural convection heat transfer process over isothermal plates.

This work is an extension and finalization of previous studies of the leading author. The numerical methodology was proposed and experimentally validated in previous studies. Using OpenFOAM® and other free and open-source numerical-computational tools, three-dimensional numerical models were built to simulate the flow and the natural convection heat transfer process over isothermal corrugation plates with variable and constant heights.

The influence of different geometric arrangements of corrugated plates on the flow and natural convection heat transfer over isothermal plates is investigated. The influence of the height ratio parameter, as well as the resulting concave and convex profiles, on the parameters average Nusselt number, corrected average Nusselt number and convective thermal efficiency gain, is analyzed. It is shown that the total convective heat transfer and the convective thermal efficiency gain increase with the increase of the height ratio. The numerical results confirm previous findings about the predominant effects on the predominant impact of increasing the heat transfer area on the thermal efficiency gain in corrugated surfaces, in contrast to the adverse effects caused on the flow. In corrugations with heights resulting in concave profiles, the geometry with triangular corrugations presented the highest total convection heat transfer, followed by trapezoidal and rectangular. For arrangements with the same area, it was demonstrated that corrugations of constant and variable height are approximately equivalent in terms of natural convection heat transfer.

The results allowed a better understanding of the flow characteristics and the natural convection heat transfer process over isothermal plates with corrugations of variable height. The advantages of the surfaces studied in terms of increasing convective thermal efficiency were demonstrated, with the potential to be used in cooling systems exclusively by natural convection (or with reduced dependence on forced convection cooling systems), including in technological applications of microelectronics, robotics, internet of things (IoT), artificial intelligence, information technology, industry 4.0, etc.

To the best of the authors’ knowledge, the results presented are new in the scientific literature. Unlike previous studies conducted by the leading author, this analysis specifically analyzed the natural convection phenomenon over plates with variable-height corrugations. The obtained results will contribute to projects to improve and optimize natural convection cooling systems.