Tourists’ Personal Development Through Participatory Consumer-Generated Content

The paper seeks to investigate key factors influencing the personal development of tourists. This study examines the relationship between participatory consumer-generated content and tourists’ capabilities, emotions, and skills, as well as the moderating effect of previous tourists’ experiences. To evaluate the research model, 301 valid responses were examined using the PLS-SEM technique. The empirical findings showed that participatory consumer-generated content positively relates to tourists’ capabilities, emotions, and skills. Moreover, previous tourists’ experiences moderate the relationships of participatory consumer-generated content with tourists’ capabilities and skills; however, previous tourists’ experiences have no moderation effect on tourists’ emotions. Thus, our paper\u27s findings offer valuable contributions to theory and practice. Practitioners and authorities should stimulate users to share their tourism experiences and take the initiative to share easily traceable and searchable data. Moreover, businesses should implement activities that encourage tourists to share their experiences as soon as possible and make travel and tourism websites and social media platforms readily available

Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions

Peer reviewedPostprin

Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions

Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions.© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.fi=vertaisarvioitu|en=peerReviewed

Point prevalence survey of antimicrobial use during the COVID-19 pandemic among different hospitals in Pakistan : findings and implications

The COVID-19 pandemic has significantly influenced antimicrobial use in hospitals raising concerns regarding increased antimicrobial resistance (AMR) through their overuse. The objective of this study was to assess patterns of antimicrobial prescribing during the current COVID-19 pandemic among hospitals in Pakistan, including the prevalence of COVID-19. A point prevalence survey (PPS) was performed among 11 different hospitals from November 2020 to January 2021. The study included all hospitalized patients receiving an antibiotic on the day of the PPS. The Global-PPS web-based application was used for data entry and analysis. Out of 1024 hospitalized patients, 662 (64.64%) received antimicrobials. The top three most common indications for antimicrobial use were pneumonia (13.3%), central nervous system infections (10.4%) and gastrointestinal indications (10.4%). Ceftriaxone (26.6%), metronidazole (9.7%) and vancomycin (7.9%) were the top three most commonly prescribed antimicrobials among surveyed patients, with the majority of antibiotics administered empirically (97.9%). Most antimicrobials for surgical prophylaxis were given for more than one day, which is a concern. Overall, a high percentage of antimicrobial use, including broad-spectrums, was seen among the different hospitals in Pakistan during the current COVID-19 pandemic. Multifaceted interventions are needed to enhance rational antimicrobial prescribing including limiting their prescribing post-operatively for surgical prophylaxis

Progress on the national action plan of Pakistan on antimicrobial resistance (AMR) : a narrative review and the implications

Introduction: The emergence of antimicrobial resistance (AMR) is a threat to public health. In 2015, the World Health Organization (WHO) introduced a global action plan to tackle AMR in the World Health Assembly. Pakistan’s national action plan (NAP) for AMR was released in May 2017 by the Ministry of National Health Services. Based on the NAP, strategies have been initiated on a national and provincial scale in Pakistan. Areas covered: This narrative review of the five components of the Pakistan NAP has been undertaken to discuss some of the challenges in implementation of the NAP for AMR in Pakistan including different opinions and views of key stakeholders, combined with suggestions on potential ways to reduce the burden of the AMR. Expert opinion: Going forward, healthcare authorities should focus on screening and monitoring of all the objectives of the NAP by establishing proper policies as well as promoting antimicrobial stewardship interventions and Infection prevention and control (IPC) practices. Overall, the comprehensive strengthening of the healthcare system is required to adequately implement the NAP, tackle continued inappropriate antimicrobial use and high AMR rates in Pakistan

Mesenchymal stem cell therapy in ischaemic heart failure: Hope or hype?

Ischaemic heart diseases (IHDs) are the leading contributor to mortality worldwide and more than 60% occur in low-to-middle-income countries (LMICs) and 40% of these are specified as premature. Despite notable improvements in treatment options, premature deaths due to IHDs including ischaemic heart failure (IHF) continue to rise in the South Asian population due to prevalent conventional and inherent cardiovascular risk profiles. Stem cell (SCs) therapy has emerged as a potential frontier in regenerative therapy for acute and chronic illnesses. Among various available sources of SCs, the safety and efficacy of mesenchymal stem cells (MSCs) for non-functional cardiomyocytes have been established, but robust evidence necessitates to endorse these preliminary investigations. Little work has been conducted in resource constraints countries and needs immediate attention of all the stakeholders to explore non-conventional cost-effective and sustainable interventions for long term management of IHDs including IHF. This review article provides an overview of basic technical aspects of SCs therapy and a way forward to inspire the scientific community and health authorities to setup priorities via collaborative public and private partnership toward the formulation and execution of sustainable strategies for IHDs to explore the new contextual destination in the field of SCs therapy

Fingertip Gestures Recognition Using Leap Motion and Camera for Interaction with Virtual Environment

The emergence in computing and the latest hardware technologies realized the use of natural interaction with computers. Gesture-based interaction is one of the prominent fields of natural interactions. The recognition and application of hand gestures in virtual environments (VEs) need extensive calculations due to the complexities involved, which directly affect the performance and realism of interaction. In this paper, we propose a new interaction technique that uses single fingertip-based gestures for interaction with VEs. The objective of the study is to minimize the computational cost, increase performance, and improve usability. The interaction involves navigation, selection, translation, and release of objects. For this purpose, we propose a low-cost camera-based system that uses a colored fingertip for the fastest and accurate recognition of gestures. We also implemented the proposed interaction technique using the Leap Motion controller. We present a comparative analysis of the proposed system with the Leap Motion controller for gesture recognition and operation. A VE was developed for experimental purposes. Moreover, we conducted a comprehensive analysis of two different recognition setups including video camera and the Leap Motion sensor. The key parameters for analysis were task accuracy, interaction volume, update rate, and spatial distortion of accuracy. We used the Standard Usability Scale (SUS) for system usability analysis. The experiments revealed that camera implementation was found with good performance, less spatial distortion of accuracy, and large interaction volume as compared to the Leap Motion sensor. We also found the proposed interaction technique highly usable in terms of user satisfaction, user-friendliness, learning, and consistency

An Adaptive Topology Management Scheme to Maintain Network Connectivity in Wireless Sensor Networks

The roots of Wireless Sensor Networks (WSNs) are tracked back to US military developments, and, currently, WSNs have paved their way into a vast domain of civil applications, especially environmental, critical infrastructure, habitat monitoring, etc. In the majority of these applications, WSNs have been deployed to monitor critical and inaccessible terrains; however, due to their unique and resource-constrained nature, WSNs face many design and deployment challenges in these difficult-to-access working environments, including connectivity maintenance, topology management, reliability, etc. However, for WSNs, topology management and connectivity still remain a major concern in WSNs that hampers their operations, with a direct impact on the overall application performance of WSNs. To address this issue, in this paper, we propose a new topology management and connectivity maintenance scheme called a Tolerating Fault and Maintaining Network Connectivity using Array Antenna (ToMaCAA) for WSNs. ToMaCAA is a system designed to adapt to dynamic structures and maintain network connectivity while consuming fewer network resources. Thereafter, we incorporated a Phase Array Antenna into the existing topology management technologies, proving ToMaCAA to be a novel contribution. This new approach allows a node to connect to the farthest node in the network while conserving resources and energy. Moreover, data transmission is restricted to one route, reducing overheads and conserving energy in various other nodes’ idle listening state. For the implementation of ToMaCAA, the MATLAB network simulation platform has been used to test and analyse its performance. The output results were compared with the benchmark schemes, i.e., Disjoint Path Vector (DPV), Adaptive Disjoint Path Vector (ADPV), and Pickup Non-Critical Node Based k-Connectivity (PINC). The performance of ToMaCAA was evaluated based on different performance metrics, i.e., the network lifetime, total number of transmitted messages, and node failure in WSNs. The output results revealed that the ToMaCAA outperformed the DPV, ADPV, and PINC schemes in terms of maintaining network connectivity during link failures and made the network more fault-tolerant and reliable

Experimental investigation of NaOH and KOH mixture in SCBA-based geopolymer cement composite

This research aimed at exploring the effects of a mixture of sodium hydroxide (NaOH) and potassium hydroxide (KOH) activators in a sugar cane bagasse ash (SCBA)-based geopolymer cement paste. Bagasse ash replacement was 20% of cement by weight. The mixture of NaOH and KOH comprised 4, 8, and 12 M solutions with mixing percentages of 0%, 20%, 40%, 60%, 80%, and 100% for all possible combinations. A pH test was performed on each possible combination of solutions. A Chapelle’s test, XRD, X-ray fluorescence (XRF), and SEM analysis were used to check whether the SCBA exhibited pozzolanic reactivity. Subsequently, the SCBA geopolymer cement paste was tested for compressive strength, water absorption, permeable porosity, and sorptivity. It was estimated that the geopolymer cement paste exhibited higher absorption and sorptivity values than control mixtures when molarity increased. However, the samples prepared with combinations of the 8 M activator solution exhibited consistent absorption, sorptivity, and compressive strength values when compared to the control and other geopolymer mixtures with 4 and 12 M activator solutions. Thus, the two activator solutions G8N408K60 and G8N208K80—where GxNayKb represents the geopolymer concrete sample prepared by adding solutions of two bases, i.e., ‘xNayKb’ showing an ‘a’ percentage of ‘x’ molar NaOH and a ‘b’ percentage of ‘y’ molar KOH—were obtained as the optimum molar ratio of the activator in geopolymer concrete. The geopolymer cement pastes, along with the optimum and control samples, were further tested for concrete durability, SEM, and TGA tests. The G8N208K80 sample exhibited a better mechanical and durability performance than the G8N408K60 sample. The durability performance of the geopolymer concrete was also superior to ordinary concrete. Moreover, the geopolymer concrete achieved a 21% reduction in global warming potential compared to the control mixture. Thus, it can be concluded that the use of SCBA in geopolymer concrete can address the ash disposal and CO2 emission problems with enhanced durability