The role of NGOs in ensuring local governance in Bangladesh: from the perception of other actors of governance

Partnerships between Non-Government Organizations (NGOs) and the local government are crucial to ensure optimal governance at the local level. In the last 2 decades in Bangladesh, NGOs have become essential actors in local development and governance. The present study investigated the role of NGOs for ensuring local governance in Bangladesh during the post-pandemic era. Periphery areas (two sub-districts) of the Natore District were selected for the field study. The qualitative analysis was mainly based on primary data. Four categories of respondents were targeted, namely NGOs (11), elected representatives and government officials (28), local elites (20) and general citizens (64) belonging to different genders, and educational and economic levels. In depth interviews, survey questionnaires and focus group discussions were used as the tools for collecting data from sampled respondents. Focus was placed on eleven issues including five development and administration related, five political and participation related, and management of the COVID-19 crisis. A qualitative matrix for the performance of NGOs on governance issues from the perspective of other actors in governance-local elected representatives and executive, local elites and general citizens was developed. The matrix revealed an optimistic story for NGO partnerships and social and governing issues such as women empowerment, disaster management, environment conservation, support during COVID-19 pandemic. On the other hand, indicators such as vote and election, people's awareness, dispute resolution, local tax collection and budget making revealed that the NGOs need to work more with the local government to ensure participation in the processes of governance. The findings directly from the peripheral field were not only based on investigation of the NGOs but also included the perception of other actors of governance so these results can definitely contribute to national social policy reforms and revision of NGO strategies. © 2023, The Japan Section of the Regional Science Association International.

A Hybrid Deep Learning System to Detect Face-Mask and Monitor Social Distance

Coronavirus Disease 2019 (COVID-19) emerged towards the end of 2019, and it is still causing havoc on the lives and businesses of millions of people in 2022. As the globe recovers from the epidemic and intends to return to normalcy, there is a spike of anxiety among those who expect to resume their everyday routines in person.The biggest difficulty is that no effective therapeutics have yet been reported. According to the World Health Organization (WHO), wearing a face mask and keeping a social distance of at least 2 m can limit viral transmission from person to person. In this paper, a deep learning-based hybrid system for face mask identification and social distance monitoring is developed. In the OpenCV environment, MobileNetV2 is utilized to identify face masks, while YoLoV3 is used for social distance monitoring. The proposed system achieved an accuracy of 0.99. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

An IoT Prototype for Monitoring Covid19 Patients Using Real Time Data from Wearable Sensor Through Android App

In the age of modern technology peoples are still facing a great challenges to manage and monitor the infected patients of COVID-19. Many systems have been implemented to track the location of infected person to reduce the spread of diseases. In today's world IoT with the health care system plays an important role specially in this COVID situation. In this research an IoT based monitoring system is designed to monitor and measure different signs of COVID-19 using wearable device. It also sends notification to the proper authority by monitoring the activity of infected patient. To determine the condition of patient, sensor data are analyzed which is passed from edge node, as body sensor are connected to IoT cloud via edge node. Three layered architecture is implemented in our proposed design, wearable sensor layer, Peripheral Interface (API) layer and Android web layer. Different layer have different work, at first health symptom is determined by analyzing data from IoT sensor layer. In next layer information is stored in the cloud database to take immediate actions. Finally android application layer is used to send notifications and alerts for the infected patient. To predict the health condition and alarming the situation both API and mobile application communicate with each other. The designed system has simple structure and helps the authority to find the infected person. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Cardiovascular Outcomes of Patients Referred to Home Based Cardiac Rehabilitation.

BACKGROUND: Home Based Cardiac Rehabilitation (HBCR) has been considered a reasonable alternative to Center-based Cardiac Rehabilitation (CBCR) in patients with established cardiovascular disease, especially in the midst of COVID-19 pandemic. However, the long-term cardiovascular outcomes of patients referred to HBCR remains unknown. OBJECTIVES: To compare outcomes of patients who were referred and attended HBCR vs patients referred but did not attend HBCR (Non-HBCR). METHODS: We performed a retrospective study of 269 patients referred to HBCR at Providence Veterans Affairs Medical Center (PVAMC). From November 2017 to March 2020, 427 patients were eligible and referred for Cardiac Rehabilitation (CR) at PVAMC. Of total patients, 158 patients were referred to CBCR and 269 patients to HBCR based on patient and/or clinician preference. The analysis of outcomes was focused on HBCR patients. We compared outcomes of patients who were referred and attended HBCR vs patients referred but did not attend HBCR (Non-HBCR) from 3 to 12 months of the referral date. HBCR consisted of face-to-face entry exam with exercise prescription, weekly phone calls for education and exercise monitoring, with adjustments where applicable, for 12-weeks and an exit exam. Primary outcome was composite of all-cause mortality and hospitalizations. Secondary outcomes were all-cause hospitalization, all-cause mortality and cardiovascular hospitalizations, separately. We used cox proportional methods to calculate hazard ratios (HR) and 95% CI. We adjusted for imbalanced characteristics at baseline: smoking, left ventricular ejection fraction and CABG status. RESULTS: A total of 269 patients (mean age: 72, 98% Male) were referred to HBCR, however, only 157 (58%) patients attended HBCR. The primary outcome occurred in 30 patients (19.1%) in the HBCR group and 30 patients (30%) in the Non-HBCR group (adjusted HR=0.56, CI 0.33-0.95, P=.03). All-cause mortality occurred in 6.4% of patients in the HBCR group and 13% patients in the Non-HBCR group 3 to 12 months after HBCR referral (adjusted HR=0.43, CI 0.18-1.0, P= .05). There was no difference in cardiovascular hospitalizations (HBCR: 5.7% vs Non-HBCR: 10%, adjusted HR 0.57, CI 0.22-1.4, P= .23) or all cause hospitalizations at 3 to 12 months between the groups (HBCR: 12.7% vs Non-HBCR: 21%, adjusted HR 0.53, CI 0.28-1.01, P= .05). CONCLUSION: Completion of HBCR among referred patients was associated with a lower risk of the combined all-cause mortality and all-cause hospitalizations up to 12 months. Based on the outcomes, HBCR is a reasonable option that can improve access to CR for patients who are not candidates of or cannot attend CBCR. Randomized-controlled studies are needed to confirm these findings.