Determinants of Stunting Children Under Five of Age During the COVID-19 in the Working Area of the Liwuto-Primary Public Health Center, Baubau City-Indonesia: A Community-Based Unmatched Case-Control Study

BACKGROUND: In Indonesia, the stunting prevalence has reached 24.4% in 2021. AIM: The study aims to examine the determinants of stunting among children under five of age during the COVID-19 pandemic in the working area of the Liwuto-Primary Public Health Center, Baubau city. METHOD(S): A community-based unmatched case-control study was conducted from January 10, to March 10, 2022, on a sample of 94, cases (n = 21), and controls (n = 73) of children aged 0-59 months with their respective mothers. Data were collected using a face-to-face interviewer-administered questionnaire and physical measurements standard. The data were analyzed using SPSS version 17. The variables were entered into the multivariable model using the backward stepwise regression approach. Multivariable logistic regression analysis was used to identify factors associated with stunting. Adjusted odds ratio (AOR) with a 95% confidence interval (95% CI) and p < 0.05 was used to declare the significance. RESULT(S): There are 22% of the stunting become in children under 5 years. Stunting children under 5 years was associated with maternal age (AOR = 5.71, 95%, CI: 1.91-17.03). While family income (AOR = 1.78, 95%, CI: 0.17-18.86), exclusive breastfeeding (AOR = 3.95, 95%, CI: 0.14-112.72), complementary feeding (AOR = 1.24, 95%, CI: 0.18-8.55), formal education (AOR = 0.74, 95%, CI: 0.36-1.53), and occupation (AOR = 2.98, 95%, CI: 0.24-36.55) were not associated with the stunting. CONCLUSION(S): Young mother under 30 years old was an important risk factor on the incidence of stunting in children under 5 years during the COVID-19 pandemic.Copyright © 2023 Jumadi Muhammadong, Ridwan Malimpo, Dahmar Karim, Yusman Muriman, Andi Tenri Mahmud.

The role of innovativeness and supply chain agility in the Australian service industry: a dynamic capability perspective

PurposeThis paper aims to investigate the conditional indirect effect of innovativeness on performance via supply chain agility (SCA) in the service industry at higher and lower collaborative relationships.Design/methodology/approachThe hypothesised model is operationalised with survey data from 245 Australian service firms collected via LinkedIn and analysed using structural equation modelling and fuzzy set qualitative comparative analysis (fsQCA).FindingsThe analysis found that SCA significantly mediates the relationship between innovativeness and performance. Further, the conditional indirect effect of innovativeness on performance via SCA was significant when the collaborative relationship was high. Results also revealed that a configuration of both innovativeness and agility better predicts performance.Originality/valueThis study is an early attempt to investigate SCA in service industries by scrutinizing SCA from an innovative point of view. While previous studies have demonstrated the role of innovativeness in enhancing a firm's performance, this study explores this link further by investigating the conditional indirect effect of innovativeness on performance via SCA at different levels of collaborative relationships.

Lessons learnt from COVID-19 vaccine operations and distribution performance: challenges and resilience strategies

Purpose: Grounded in dynamic capability view, this research develops a decision support model, which enables determining consistent and sufficient configurations of resilience strategies to mitigate vaccine operations and distributions (O&D) challenges and thus improve O&D performance (i.e. O&DP). Design/methodology/approach: Through qualitative in-depth interviews, the authors first identified challenges and resilience strategies related to vaccine O&D. Next, using the quality function deployment technique, three quantitative case studies were performed to determine the most important challenges and resilience strategies. Finally, utilising fuzzy set qualitative comparative analysis, the authors determine sufficient conditions of challenges and strategies leading to improve vaccine O&DP. Findings: The findings reveal that strategies alone are not effective instead a combination of strategies and nullification of challenges is needed to enhance vaccine O&DP. Further, the findings revealed that not only the presence of challenges, but also the lack of strategies reduces the vaccine O&DP. Practical implications: The authors' findings will assist the health service decision-makers for strategizing an effective and efficient vaccination program by selecting the right combination of challenges and resilience strategies. Originality/value: The authors' study develops a novel decision support model and offers significant learning for the future vaccine O&DP. © 2023, Emerald Publishing Limited.

A multicentre study reveals dysbiosis in the microbial co-infection and antimicrobial resistance gene profile in the nasopharynx of COVID-19 patients.

The impact of SARS-CoV-2 infection on the nasopharyngeal microbiome has not been well characterised. We sequenced genetic material extracted from nasopharyngeal swabs of SARS-CoV-2-positive individuals who were asymptomatic (n = 14), had mild (n = 64) or severe symptoms (n = 11), as well as from SARS-CoV-2-negative individuals who had never-been infected (n = 5) or had recovered from infection (n = 7). Using robust filters, we identified 1345 taxa with approximately 0.1% or greater read abundance. Overall, the severe cohort microbiome was least diverse. Bacterial pathogens were found in all cohorts, but fungal species identifications were rare. Few taxa were common between cohorts suggesting a limited human nasopharynx core microbiome. Genes encoding resistance mechanisms to 10 antimicrobial classes (> 25% sequence coverages, 315 genes, 63 non-redundant) were identified, with ß-lactam resistance genes near ubiquitous. Patients infected with SARS-CoV-2 (asymptomatic and mild) had a greater incidence of antibiotic resistance genes and a greater microbial burden than the SARS-CoV-2-negative individuals. This should be considered when deciding how to treat COVID-19 related bacterial infections.

Self-reported use of technology by orientation and mobility clients in Australia and Malaysia before the COVID-19 pandemic

Since the 1960s, many electronic travel aids have been developed for people with low vision or blindness to improve their independent travel skills, but uptake of these specialist devices has been limited. This study investigated what technologies orientation and mobility (O&M) clients in Australia and Malaysia have, use, like, and want to support their travel, to inform technology research and development. This two-phase mixed-methods study surveyed O&M clients face-to-face in Malaysia (n = 9), and online in Australia (n = 50). Participants managed safe walking using a human guide, long cane, or guide dog when their vision was insufficient to see hazards, but a smartphone is now a standard travel aid in both Australia and Malaysia. Participants relied on smartphone accessibility features and identified 108 apps they used for travel: for planning (e.g., public transport timetables), sourcing information in transit (e.g., GPS location and directions, finding a taxi), sensory conversion (e.g., camera-to-voice, voice-to-text, video-to-live description), social connections (e.g., phone, email, Facebook), food (e.g., finding eateries, ordering online), and entertainment (e.g., music, games). They wanted to ‘carry less junk', and sought better accessibility features, consistency across platforms, and fast, reliable, real-time information that supports confident, non-visual travel, especially into unfamiliar places. © The Author(s) 2021.

Psychological Impact and Coping Style Among Students of National Defence University of Malaysia during the COVID-19 Pandemic

Introduction: The outbreak of COVID-19 has caused a significant impact on the world's population. This study examines the impact of COVID-19 on the level of depression, anxiety and stress among students of National Defence University of Malaysia (NDUM), and to assess coping styles during this critical time. Method(s): This was a cross-sectional study conducted during the Conditional Movement Control Order (CMCO) on May 2020 during the COVID-19 pandemic. DASS-21 and BRIEF COPE were used as the assessment toolsfor this study. Data was analysed using descriptive statistics, Independent T-test and One-way ANOVA with comparisons of multiple variables using post-hoc Tukey's test. Result(s): A total of 603 participants were included in the study. Respondents' mean age was 21.06 +/- 1.75. They consisted of 52.6% male, 86.9% Malays and 76.9% non-cadets. The prevalence of depression, anxiety and stress were 51.9%, 46.9% and 18.7% respectively. Female, those who are from the Language Centre and non-cadet students, showed a statistically significant higher score of depression, anxiety and stress. A high-stress score was seen in Bachelor degree students compared to Foundation students. Those with no financial sponsorship showed the highest anxiety score. The most common coping style used among the respondents was religion and the least is substance abuse. Conclusion(s): This study has identified the risk groups for developing psychological distress during times of crisis. Thus, there is an urgent need to address the concern on mental health and provide a structured support for them. Copyright © 2023, Ibn Sina Trust. All rights reserved.

Preparedness of Students for Future Teaching and Learning in Higher Education: A Bangladeshi Perspective

The COVID-19 pandemic has had a significant impact on higher education (HE) across the globe, including in Bangladesh. The Bangladeshi HE system is going through an abrupt transition and transformation to cope with the crisis. This chapter is based on data collected from teachers and students of Bangladeshi public and private HE institutions regarding teaching and learning during the COVID-19 lockdown. In Bangladesh, some universities switched to online distance teaching and learning quickly during this period, and others lagged behind in this regard. Teachers and students from both groups of public and private universities participated in the study, including those who attended online teaching and learning activities and those who did not participate. This chapter highlights both teachers' and students' perspectives regarding students' future preparedness for participating fully in the changing landscape of HE, especially technology-enhanced teaching and learning. Understanding these perspectives of teachers and students is important to address the digital divide and social justice issues in the policy and practice. Within the HE sector in Bangladesh, it is especially vital while transforming its education system and adapting emerging technologies to address the challenges of education in future emergencies.

Preparing for the next pandemic

Despite COVID-19 being the most severe pandemic to afflict the world since the Spanish Flu of 1918, the Malaysian response has not been outstanding even among developing nations. Pandemic preparation is a national responsibility, and the current Pandemic Preparedness Plan needs to be revised and updated if the country is to prepare properly for another pandemic. It has also become clear that the country needs to go beyond merely revising the Pandemic Preparedness Plan. Indeed, opportunities abound for a reset of the economy and the country in many ways. This reset is a great opportunity to push for widespread automation and adoption of artificial intelligence in the Malaysian economy, adoption of E- in work and life, introduction of a more efficient food supply chain, delivery of education through alternative means and to have vaccines and medicines security. In addition, future pandemic preparedness must heed lessons learned during this pandemic and use a wholeof- community approach in its planning. There is a great need to recognise the combined threats of unsustainable healthcare financing, climate change, the rise in lifestyle diseases, an ageing population and rapidly spreading infectious diseases which must be tackled and included in any future planning. Public health education also needs to change as pandemic resilience is not usually part of the usual public health curriculum. The link between infections and non-communicable diseases needs to be bridged and more research needs to carried out to understand this link better. Public health education also needs to incorporate adaptive thinking and scaling up response at speed and health promotion needs to adapt to social media and to counter misinformation. Advocacy for change is no longer a luxury or an option. It needs to happen quickly, and the country needs to adapt and innovate. If it fails to adapt and innovate then risks will emerge, it will be left further behind, and Malaysia will be even less prepared for another catastrophic health event.

An effective approach to address processing time and computational complexity employing modified CCT for lung disease classification

Early identification and adequate treatment can help prevent lung disorders from becoming chronic, severe, and life-threatening. X-ray images are commonly used and an automated and effective method involving deep learning techniques can potentially contribute to quick and accurate diagnosis of lung disorders. However, in the study of medical imaging using deep learning, two obstacles limit interpretability. One is an insufficient and imbalanced number of training samples in most medical datasets. The other is excessive training time. Although training time can be reduced by decreasing the number of pixels in the images, training with low resolution images tends to result in poor performance. This study represents a solution to overcome these impediments by balancing the number of images and reducing overall processing time while preserving accuracy. The dataset used in this research contains an unequal number of images in the different classes. The quantity of data in the classes is balanced by creating synthetic images based on the patterns and characteristics of the original images, using a Deep Convolutional Generative Adversarial Network (DCGAN). Unwanted regions are removed from the X-ray images, the brightness and contrast of the images are enhanced, and the abnormalities are highlighted by using different artifact removal, noise reduction, and enhancement techniques. We propose a Modified Compact Convolutional Transformer (MCCT) model using 32 × 32 sized images for the categorization of lung disorders into four classes. An ablation study of eleven cases is employed to adjust several hyper parameters and layer topologies. This reduces training time while preserving accuracy. Six transfer learning models, VGG19, VGG16, ResNet152, ResNet50, ResNet50V2, and MobileNet are applied with the same image size the performance is compared with the proposed MCCT model. Our MCCT model records the greatest test accuracy of 95.37%, requiring a short training time, 10-12 s/epoch, whereas the other models only reach near-moderate performance with accuracies ranging from 43% to 79% and training times of 80-90 s/epoch. The robustness of the model with regards to the number of training samples is validated by training the model multiple times reducing the number of training images gradually from 49621 images to 6204 images. Results suggest that even with a smaller dataset, the performance is sustained. Our proposed approach may contribute to an effective CAD based diagnostic system by addressing the issues of insufficient and imbalanced numbers of medical images, excessive training times and low-resolution images. © 2022

Integrating Internet of Things and EEG in Controlling Fan Speed

The limitations of the assistive devices for amputees and the prevention of Covid-19 spread have risen the need for a device that can be controlled without using hands. The availability of the internet of things allows data to be transferred between devices without a physical connection. This paper describes the integration of the Internet of things (IoT) and electroencephalogram (EEG) in controlling fan speed via intention. The controlling process includes EEG signals acquisition in real-time, the intention detection from the signal, the transmission of the fan speed to the cloud and the retrieval of the stored data from the cloud to change the fan speed accordingly via Wi-fi. The system could detect the intention of increasing and decreasing the fan speed with an accuracy of 95% and 75% respectively. The accuracy of detecting the intention from EEG signals is affected by the frame length and electrode duration on the scalp, Wi-fi strength and wireless connection stability. With the utilization of IoT and EEG in the whole system, the fan could be controlled from far without using hands which is suitable for amputees and at the same time, the transmission of Covid-19 through hands could be reduced © 2020 Faculty of Mechanical Engineering, Universiti Teknologi MARA (UiTM), Malaysia

Editorial introduction to the special issue: Social customer journey – behavioural and social implications of a digitally disruptive environment

This editorial provides an overview of this Special Issue of Technological Forecasting & Social Change on “Social Customer Journey - Behavioural and Social Implications of a Digitally Disruptive Environment”, bringing together insights from the papers accepted for inclusion in this special issue. Fifteen articles on a variety of topics relevant to this special issue have been accepted for publication. These articles examine the behavioural and social implications of a digitally disruptive environment from a variety of theoretical, contextual and methodological perspectives.

The Role of Big Data Analytics in Digital Health for COVID-19 Prevention and Control in Asia

Big data analytics (BDA) in digital health is critical for gaining the knowledge needed to make decisions, with Asia at the forefront of utilising this technology for the Coronavirus disease 2019 (COVID-19). This review aims to study how BDA was incorporated into digital health in managing the COVID-19 pandemic in six selected Asian countries, discuss its advantages and barriers and recommend measures to improve its adoption. A narrative review was conducted. Online databases were searched to identify all relevant literature on the roles of BDA in digital health for COVID-19 preventive and control measures. The findings showed that these countries had used BDA for contact tracing, quarantine compliance, outbreak prediction, supply rationing, movement control, information update, and symptom monitoring. Compared to conventional approaches, BDA in digital health plays a more efficient role in preventing and controlling COVID-19. It may inspire other countries to adopt this technology in managing the pandemic. © 2022 UPM Press. All rights reserved.

Human Resource Management in the Healthcare Setting During COVID-19Pandemic:PolicyRecommendations,Implementation Challenges, and the Way Forward

The Coronavirus disease 2019 (COVID-19) pandemic has caused a worldwide human resource crisis in the healthcare setting due to the continuous and overwhelming demand of the workforce. Failure in managing the human resource will negatively affect the clinical management, prevention, and control of the pandemic;while a well-planned human resource policy can ensure sustainable and sufficient skilful workers to meet the demand. This article presents policies that are recommended by the World Health Organization (WHO) and other significant studies in addressing the issues faced by many countries during this COVID-19 pandemic. As with all policies, there are various challenges in the implementation of policies related to COVID-19. Therefore, this article also discusses the challenges in the implementation of these policies. This article ends with the proposal for the way forward in human resource management during a pandemic, should another pandemic hit the world. © 2022 UPM Press. All rights reserved.

Development of a computer-aided tool for detection of COVID-19 pneumonia from CXR images using machine learning algorithm

The novel coronavirus (SARS-CoV-2) is spreading rapidly worldwide, and it has become a greater risk for human beings. To curb the community transmission of this virus, rapid detection and identification of the affected people via a quick diagnostic process are necessary. Media studies have shown that most COVID-19 victims endure lung disease. For rapid identification of the affected patient, chest CT scans and X-ray images have been reported to be suitable techniques. However, chest X-ray (CXR) shows more convenience than the CT imaging techniques because it has faster imaging times than CT and is also simple and cost-effective. Literature shows that transfer learning is one of the most successful techniques to analyze chest X-ray images and correctly identify various types of pneumonia. Since SVM has a remarkable aspect that tremendously provides good results using a small data set thus in this study we have used SVM machine learning algorithm to diagnose COVID-19 from chest X-ray images. The image processing tool called RGB and SqueezeNet models were used to get more images to diagnose the available data set. Our adopted model shows an accuracy of 98.8% to detect the COVID-19 affected patient from CXR images. It is expected that our proposed computer-aided detection tool (CAT) will play a key role in reducing the spread of infectious diseases in society through a faster patient screening process.

“Lost All Hope in Government”: Learned Helplessness of Professionals Working in Specialised Education Settings in England During COVID-19

COVID-19 has had substantial impact on children’s educational experiences, with schools and educators facing numerous challenges in adapting to the new reality of distance learning and/or social distancing. However, previous literature mostly focuses on the experiences of families [including families of children with special educational needs and disabilities (SEND)] and those of teachers, predominantly working in mainstream settings. This article aims to gauge the perspectives of educators working in specialised education settings that serve children with SEND in England on how they experienced working in those settings during the pandemic, including in during lockdown. A mixed (qualitative and quantitative) online survey was responded to by 93 educators. Responses denote emotionally charged views and a sense of learned helplessness. Most special schools were unable to implement social distancing measures in full or provide adequate protective equipment. The main challenges the respondents mentioned included lack of guidance from Governmental authorities, staff shortages, work overload, challenging relationship with parents and issues in meeting children’s complex needs. Professionals working for less than 3 years in a special school were more likely to say they would change jobs if they could, when compared to professionals with more years of experience. No effects of demographic characteristics were found in relation to professionals’ ratings of their own wellbeing during lockdown. Findings are discussed in light of the concept of learned helplessness and suggest that there is a need to reform provision in special schools in England to foster its sustainability and positive outcomes for children. Copyright © 2022 Mahmud and Castro-Kemp.

Performance Analysis on Multiple Device Connections of Small Office Home Office Network

Malaysia has been supported by one of the high-speed fiber internet connections called TM UniFi. TM UniFi is very familiar to be used as a medium to apply Small Office Home Office (SOHO) concept due to the COVID-19 pandemic. Most of the communication vendors offer varieties of network services to fulfill customers' needs and satisfaction during the pandemic. Quality of Services is queried by most users by the fact of increased on users from time to time. Therefore, it is crucial to know the network performance contrary to the number of devices connected to the TM UniFi network. The main objective of this research is to analyze TM UniFi performance with the impact of multiple device connections or users' services. The study was conducted to analyze the QoS on its traffic, packets transfer, RTT, latency, and throughput. Wireshark simulation program has been used as a network traffic capture where PCAP files have been analyzed by using PCAP Analyzer for Splunk. Traffic filtering has been enabled to capture selected traffic to measure network performance. The result shows that better network performance can be achieved if a smaller number of devices are connected at the same time. The percentage of packet loss, RTT, latency is increased when more users connected at the same time. The throughput also shows a decrease for multidevice connections. Based on the analysis it can be concluded that TM UniFi still can provide good network services for the SOHO network environment and sufficient bandwidth despite the rapid user growth in Malaysia. © 2021 University of Baghdad. All rights reserved.

COVID-19 Effects on Students' Teaching and Learning Perspectives in Malaysian Varsities

The COVID-19 pandemic has had dramatic effects on the socio-economic and well beings of Malaysians. The objective of the study is to find the effects of the pandemic on university students both on the technical side, such as the sufficiency of infrastructure and the internet to support online teaching and learning (T&L), as well as on the social side, such as stress level and focus on the study. The nationwide study on the effect of the pandemic on Malaysian varsities students was conducted at the end of 2020. There are many important issues uncovered in this study ranging from the technical side, such as internet-ready programs, socio-economic side, to the psychological perspectives. It shall provide invaluable insights to the related ministries while preparing appropriate reactions during the recovery period. The survey revealed that almost 74% of students highlighted that internet coverage and connectivity was the main issue in online T&L. Although statistics show that 90% of Malaysian households have access to the internet, 49% of students reported that their internet connections were poor. The effects of the pandemic are far-reaching, students belonging to the most vulnerable category find themselves in the most non-conducive place to learn, and they are disturbed by siblings. The socio-economics impacts brought about by the pandemic cause ripple effects onto their families. The government distribution of relief aids has lessened the burden of many people, including students;nevertheless, much improvement could be made, especially in the internet facility and coverage. © Universiti Putra Malaysia Press

Examining the effects of enterprise social media on operational and social performance during environmental disruption

Building on resource-based, dynamic capabilities and knowledge-based views, we examine how enterprise social media (ESM) usage leads to organisational decision-making effectiveness, and consequently improves organisational (operational and social) performance during environmental disruption. We also investigate the mediating roles of organisational agility, ESM infrastructure and knowledge sharing on the relationship between ESM usage and decision-making effectiveness. To empirically test this model, data was collected through a survey from the employees of public/private emergency and disaster management organisations during COVID-19 pandemic in Bangladesh. The results confirm that ESM usage indirectly affects decision-making effectiveness, which ultimately improves organisations’ operational and social performance. Organisational agility and ESM infrastructure are strong mediators of the link between ESM usage and decision-making effectiveness, while the mediating effect of knowledge sharing through ESM is weaker. In addition to presenting theoretical rationale and empirical evidence, the study enables us to outline policy guidelines for social media managers of disaster management organisations, who must develop ESM strategies in order to boost operational and social performance. This study makes a preliminary attempt to empirically investigate ESM's innovative usage in emergency and disaster management situations.

A Qualitative Study on Emergency Health Care Worker (EHCW) Perception towards COVID-ACLS Simulation Training in Resuscitating Suspected COVID-19 Patients

The emergence of COVID-19 pandemic has caused difficulty to emergency-HCW (EHCW) in resuscitating high-risk patients. We set out to explore EHCW's perception after undergoing COVID-ACLS resuscitation training and address their anxiety of working in this pandemic. A qualitative case study using focused group discussion was conducted among EHCW who have undergone COVID-ACLS training. Five semi-structured questions exploring respondent's confidence level, anxiety factors, areas of improvement for COVID-ACLS and if this COUD-ACES training is sufficient. Inductive and deductive thematic analysis approach was done to analyse the result. 20 EHCW participated in this study. Out of 4 themes, 11 subthemes were identified based on the respondents. They were acquired new knowledge, self-precaution, method of delivery, concerns of self and family members, stigmatisation, insufficient protective methods, underappreciation, regular training sessions, other modalities for learning, course duration;and unsatisfactory reading material. New knowledge and self-precaution were noted to be an important aspect that boosts confidence among EHCW. The main factor that increased anxiety was safety issues and disease spreading to family members, colleagues, and society. In conclusion, COVID-ACLS training is able to boost EHCW confidence in resuscitating high-risk patients. Factors leading to anxiety among EHCW should also be addressed during this pandemic to ensure psychological welfare and mental health are not affected Regular training and utilisation of other teaching modalities such as video are perceived as a helpful adjunct in boosting their confidence. The utilisation of new training approach should be explored in enhancing EHCW's knowledge and confidence.