Therapeutic perspectives of medicinal plants have been considered as a very important aspect in today’s public health research. Researchers focusing on traditional medicine, elucidates various kinds of common ailments and their treatment process through commonly available medicinal plants. However, this practice is ancient but for past two decades it has gained acceleration in biomedical science. The implementation of medicinal plants in medicine is considered as a valuable resource and a real alternative of primary healthcare for economically developing countries, especially in rural areas. We have done a survey-based study to assess the prevalence of common medicinal plants in a random population in West Bengal, India. Our findings broadly highlight the fact that Tulsi (Ocimum tenuiflorum), Neem (Azadirachta indica), Aloe (Aloe vera) are the most used as raw traditional medicine for treating several clinical issues like immunity boosting, cough and cold, dermatological problems etc. These plants have the high growth rate in Indian subcontinent and are easy to maintain in kitchen gardens. We predict that a regulated chronic usage of these medicinal plants can be beneficial for domestic healthcare perspectives and will help to prevent several common diseases.

In recent years, air pollution mitigation policies have become stricter, but air pollution is still worsening in many areas. From this example, we hypothesize that public awareness of air pollution is a more important factor in mitigating air pollution than the strictness of air pollution mitigation policies. This study analyzed air pollution levels and public awareness of air pollution in Southeast and South Asia, where air pollution is severe, by comparing changes over time. Regarding air pollution levels, time-series data on PM2.5 pollution levels, which are the most harmful to the human body, were generated from MODIS products. As for the public awareness of air pollution, we obtained time-series data on the popularity of a search query meaning air pollution from GoogleTrends. These two time-series data were decomposed into seasonal, trend, and residual components by STL decomposition, and compared. As a result, it was found that time-series data on public awareness of air pollution is broadly classified into two patterns. The first is a consistently increasing pattern and the second is a temporary decline pattern. The U-shaped temporary decline in environmental awareness suggests the influence of new Google users. However, in many areas, the increase in public awareness of air pollution did not lead to an improvement in air pollution levels, and research on the relationship between mitigation policies and air pollution levels is warranted.

The textile industries are essential to the economy of Bangladesh. This sector is the largest foreign exchange earner for the country, employing over three million women. However, the unplanned and rapid clustering of industries harms the environment. Unabated untreated textile wastewater discharge is plaguing the water bodies. Compliance issues arise due to the high treatment costs associated with expensive imported chemicals and energy-intensive systems. In the pursuit of a sustainable solution, a pilot-scale technology development project was initiated at an operational textile wastewater treatment plant. The process involved the chemical oxidation of treated wastewater using calcium hypochlorite, followed by rapid sand filtration with the assistance of waste blast furnace iron slag. This approach resulted in the complete removal of colour and further reductions of 95% for COD, 93% for TDS, and 89% for TSS, ensuring that the treated water met Bangladesh's discharge standards. Consequently, this water can be reused in textile wet processes. Fabrics dyed with recycled water exhibited comparable colour fastness in dry and wet conditions. The developed tertiary treatment process, relying on locally available resources and technology within the regional supply chain, holds the potential to serve as a sustainable wastewater treatment option for textile industries in resource-challenged economies. This approach aligns with the objectives of sustainable development by embracing circular economy principles.

The oil palm industry in Malaysia experienced substantial growth in 2021, reaching over 5.7 million ha [1]. However, G. boninense pathogen causing basal stem rot (BSR) disease has posed a severe threat to the industry.

Remote sensing, particularly through ground-based [2,3], airborne [4] and satellite platforms [5], has shown promise in efficiently detecting the BSR disease. Ground-based sensing is impractical for big plantations and has limited data coverage. Satellite images are limited since Malaysia's location at the equator makes it hard to have a cloudless sky. Hence, this study proposes a solution to the threat of BSR disease by leveraging unmanned aerial vehicles (UAVs) equipped with multispectral and thermal sensors, combined with machine learning techniques.

September 2023 marks the 100th commemoration of the 1923 Great Kanto Earthquake, which caused catastrophic damages to the southern part of the Tokyo metropolitan area. Since then, Tokyo has undergone major changes over the past 100 years, experiencing with the Tokyo Air Raid in 1945 and the postwar economic recovery. Regarding expansion of Tokyo Metropolitan Area, Murao et al. (2023) clarified that (1) the total number of houses increased, (2) although the number of wooden houses decreased to about 70%, the number of non-wooden houses increased 4 times in Tokyo, and (3) the relationship between regional vulnerability and building increase/decrease conditions. Following the analysis, this study examines the vertical urban development of Tokyo in view of urban risk in the 21^st century.

Effective management of construction and demolition waste (CDW) is essential for promoting sustainable resource utilization and responsible waste practices. With a notable increase in construction activities across Bangladesh, there has been a surge in CDW production. However, comprehensive data on CDW generation in the country has been lacking until now. This study, conducted in the fiscal year 2022, aims to bridge this knowledge gap by providing waste generation rates (WGR) for specific C&D materials and exploring CDW recycling practices. The research focuses on construction and demolition sites within the 12 city corporations of Bangladesh. The study's results indicate that CDW in Bangladesh is predominantly composed of concrete (56%), brick (15%), mortar (9%), metal (6%), and ceramics (6%). Specific CDW WGRs are quantified using regression analysis. Notably, for Dhaka, the capital of Bangladesh, the Construction and Demolition WGR for the fiscal year 2022 is estimated at 64.68 kg/m2 and 1626.97 kg/m2, respectively. Unfortunately, a significant portion of this waste is improperly disposed of in landfills or unauthorized areas. Furthermore, this research focuses on assessing the recycling potential of concrete, brick, mortar, metal, and ceramics in major cities of Bangladesh. The aim is to reduce the strain on virgin natural resources and lower CO2 emissions by applying circular economy principles. This information serves as a valuable resource for shaping future strategies in CDW management, particularly in economically constrained regions like Bangladesh, while contributing to the achievement of Sustainable Development Goal 12 (SDG12).

Intersections with low visibility are places where there is a high risk of road traffic accidents.
Particularly at intersections on residential areas, roadside trees, hedges, guardrails and fences often obstruct visibility.
This study attempted to develop an evaluation method for visibility using 3D point cloud data for intersections without traffic lights.

Background and Aim: Diarrheal diseases continue to be a major disease burden in developing countries. Although studies described the seasonality of diarrheal diseases, the association of weather variables with diarrheal diseases has not been well characterized in resource-limited settings where the burden remains high. This study examines the short-term associations between weather and hospital visits due to diarrhoea in children in seven low-income and middle-income countries.

Method: The primary health outcome was hospital visits due to diarrhoea among children under five years of age. The data were collected from seven sites in each country via the Global Enteric Multicenter Study project from December 2007 to March 2011. Daily weather data in the same period were downloaded from the ERA5-Land. For each of the seven sites, we fitted a time series regression model to examine the relationship of daily diarrhoeal cases with daily ambient temperature and precipitation for the last 21 days using a generalized linear model with distributed lag nonlinear functions.

Results: The analysis included 66,056 cases of diarrhoea. Daily mean temperatures ranged from 15.2 °C in Bangladesh to 37.7 °C in Mali over the study period. Sites had a highly skewed distribution of precipitations. The associations of diarrhoeal hospital visits with temperature and precipitation varied by country. The relative risk (RR) of diarrhoeal visits for temperature exposure (95^th percentile vs. 1^st percentile) ranged from 0.24 to 8.07, with Mozambique, and Bangladesh showing positive associations, while Mali and Pakistan having negative associations. The RR for precipitation (95^th percentile vs. 1^st percentile) ranged from 0.77 to 1.55, with Mali and India showing positive associations, while the only negative association was observed in Pakistan.

Conclusion: Our findings suggest the essential roles of ambient temperatures and precipitations, especially high temperatures and high precipitation, in increasing diarrhoeal infection both in south Asia and sub-Saharan African countries.

The global quest for achieving Sustainable Development Goals (SDGs) is intricately linked with the utilization of technology and the efficacy of decision-making processes. This research delved into the assessment of the ecological sustainability of thirteen manufacturing facilities in the textile and apparel sector, closely associated with the production of fast fashion in Bangladesh. The study employed a multiple case study methodology, gathering qualitative and quantitate data through brief questionnaire-based interviews followed by focus group discussions. The textiles and apparel manufacturing industry is notorious for generating substantial amounts of material waste, necessitating immediate and efficient management to alleviate its adverse environmental impact. There exists a significant research opportunity in effectively managing waste materials originating from the initial phases of textile and apparel manufacturing, aligning with the principles of a circular economy, and aligning with Bangladesh's pursuit of SDG 12.This study also encompasses the systematic identification and categorization of waste materials generated throughout various production stages, alongside exploring the possibilities of recycling pre and post-consumer textile waste. Additionally, it involves the evaluation of economic consequences and proposes a conceptual model for a circular economy aimed at the recovery and reuse of these textile waste materials. In addition to material waste from the production processes, another pressing concern within the textile sector in Bangladesh is the issue of wastewater. The industry generates substantial volumes of wastewater, often discharged into nearby rivers, leading to the contamination of surface water bodies. The treatment of this wastewater is imperative, as it plays a crucial role in advancing 11 of the 17 SDGs. Another objective of this research was to assess the quality of treated wastewater discharged by textile industries and explore methods for the recovery of valuable resources from this wastewater to achieve and promote SDG 6 and 12. The study investigated the recovery of caustic soda and heat from the raw wastewater generated during the wet processing, subsequently reusing these resources in the wet processing of denim manufacturing. The results demonstrated a material conversion rate of 78% (from cotton to finished apparel). Notably, denim jeans manufactured using these recovered resources and treated wastewater exhibited comparable outcomes in terms of color fastness, both under dry and wet conditions, as well as tear strength, in comparison to those produced using treated groundwater sourced by North American and European brands. The collaboration emphasizes the vital link between sustainable textile practices and effective wastewater management, significantly contributing to SDG achievement. It underscores the importance of technology-driven decision-making and the need for comprehensive strategies to address challenges and promote a sustainable future.

Numerous studies have been conducted to minimize the adversity yet continuous monitoring is required for the Northwest region of Bangladesh. The study introduces a method for forecasting meteorological droughts in the Northwest region of Bangladesh using daily precipitation, and temperature data from 1952 to 2020. The Standard Precipitation Index (SPI) and Standard Precipitation-Evapotranspiration Index (SPEI) parameters were created, and an Artificial Neural Network (ANN) model was used to predict droughts over 3-, 6-, 9-, and 12-month lead time. The findings of the study showed that short lead time prediction was better compared to long lead time predictions. The study also found that SPEI-based predictions were better than SPI for the six stations of the study area. Using the ANN model to predict drought using more parameters, the community of that location can be more resilient.