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Global temperature is increasing at an alarming rate, which increases the number of heatwaves. Heatwaves have significant impacts, both directly and indirectly, on human and natural systems and can create considerable risk to public health. Predicting the occurrence of a heatwave can save lives, increase the production of crops, improve water quality, and reduce transportation restrictions. Because of its geographical location, Bangladesh is particularly vulnerable to cyclones, droughts, earthquakes, floods, and heatwaves. The Bangladesh Meteorological Department collects temperature data at multiple weather stations, and we use data from 10 weather stations in this research. Data show that most heatwaves occur in the summer months, namely, April, May, and June. In this research, we develop Classification and Regression Tree (CART) models that use daily temperature data for the months of March, April, May, and June to predict the likelihood of a heatwave within the next 7 days, the next 28 days, and on any particular day based on daily high temperatures from the previous 14 days. We also use different model parameters to evaluate the accuracy of the models. Finally, we develop treed Stepwise Logistic Regression models to predict the probability of heatwaves occurring. Even though this research uses data from Bangladesh Meteorological Department, the developed modeling approach can be used in other geographic regions. [ABSTRACT FROM AUTHOR]

As agencies consider strategies for meeting the livability goals (e.g., public health, mobility, and access) of communities, they often repurpose the existing right-of-way of arterials to meet traffic operation or safety goals. Agencies need more definitive guidance on when this repurposing of existing right-of-way can be done without negatively affecting safety. Researchers around the world have considered the safety efficacy of lane width, but none defines lane width design recommendations of urban arterials. This study uses treed regression analysis on crash data collected from four cities of Nebraska to develop predictive models for identifying the crash modification factors of different lane widths. The analysis from five treed regression models indicates that narrower lanes increase the likelihood and the frequency of injury and noninjury crashes on high-volume segments; however more specifically, the results also show that narrower lane widths can be adopted for segments with lower volumes, a sufficient number of through lanes, and lower speed limits without degrading safety. Based on these crash modification factors, the research team creates design recommendations for arterial lane widths using combinations of speed limit, average annual daily traffic per lane, and number of through lanes. [ABSTRACT FROM AUTHOR]

Healthcare waste management (HCWM) options are inconsistent in Bangladesh. One of the first critical steps in the process of developing a reliable waste management plan requires a comprehensive understanding of the quantities and characteristics of the waste that needs to be managed. This study took into consideration both the quantity and quality of the generated waste to determine the generation rates and physical properties of healthcare waste (HCW) in Chittagong Medical College Hospital (CMCH) and also to estimate the amount of infectious and non-infectious waste generated in different wards. CMCH, the second largest hospital in Bangladesh, comprises 34 wards, 12 of which were selected randomly. Waste materials were collected from these wards and then segregated and weighed. Waste generation per day was found to be 73.22 kg/ward; 1.28 kg/bed and 0.57 kg/patient. A total of 2490 kg of HCW was produced each day in CMCH (37% being infectious and the rest being non-infectious waste). Infectious waste was 27.07 kg per ward, 0.47 kg per bed and 0.21 kg per patient and the non-infectious waste was 46.15 kg per ward, 0.81 kg per bed and 0.36 kg per patient per day. HCW comprised eight categories of waste materials with vegetable/food waste being the largest component (50.21%) and varied significantly (P < 0.05) among the 12 different wards studied. The greatest amount of HCW was recorded (154 kg) in Orthopaedics followed by 96.66 kg in the Medicine Unit-3 and the smallest amount was recorded in Casualty (8.79 kg). The amount of HCW was positively correlated with the number of occupied beds (rxy = 0.79, P < 0.01). There is no structured form of medical waste treatment in CMCH and most waste materials are dumped in open areas for natural degradation or re-sold by scavengers. It is essential to develop a national policy and implement a comprehensive action plan for HCWM that will provide environmentally sound technological measures to improve HCWM in Bangladesh. [ABSTRACT FROM AUTHOR]