Intense urbanization alters the microclimate and ecology of cities by converting naturally vegetated and permeable surfaces into impervious built-up surfaces. These artificial impermeable surfaces re-balance the surface energy budget by storing solar heat due to their higher thermal conductivity, and consequently, increase the Land Surface Temperature (LST). The higher LST affects the city dwellers' Human Thermal Comfort (HTC). To address these issues, unlike most prior research, we assess not only the influence of Land Use and Land Cover (LULC) alterations on summer LST but also on winter LST in Chittagong City of Bangladesh between 1993 and 2020 by using Remote Sensing (RS) and Geographic Information Systems (GIS). Additionally, the study evaluates the impact of LULC changes on the HTC during summer as LST substantially affects HTC in summer. The LULC analysis shows an increase in built-up area by 204% from bare lands, vegetated lands, lowlands, and water bodies between 1993 and 2020. In contrast, bare lands were converted from naturally vegetated surfaces, followed by lowlands and water bodies because of anthropogenic activities. The LSTs of Chittagong city, derived from remote sensing data, show a strong upward trend, with summer (winter) ranges of 20.62–34.07 °C (7.50–27.52 °C), 22.82–37.62 °C (14.92–29.32 °C), and 22.32–43.52 °C (17.08–31.83 °C) for 1993, 2007, and 2020, respectively. Between 1993 and 2020, the spatial mean winter and summer LSTs increased by 4.04 °C and 6.45 °C, respectively, or 0.15 °C and 0.24 °C per year. Chittagong had the highest mean LST in built-up areas for all the years. In addition, the study area's HTC gradually shifted to intense heat stress. The summer LST strongly correlated with normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI) while winter LST exhibited poor correlation with these indices.

Catalytic membrane reactors have been widely used in different production industries around the world. Applying a catalytic membrane reactor (CMR) reduces waste generation from a cleaner process perspective and reduces energy consumption in line with the process intensification strategy. A CMR combines a chemical or biochemical reaction with a membrane separation process in a single unit by improving the performance of the process in terms of conversion and selectivity. The core of the CMR is the membrane which can be polymeric or inorganic depending on the operating conditions of the catalytic process. Besides, the membrane can be inert or catalytically active. The number of studies devoted to applying CMR with higher membrane area per unit volume in multi-phase reactions remains very limited for both catalytic polymeric and inorganic membranes. The various bio-based catalytic membrane system is also used in a different commercial application. The opportunities and advantages offered by applying catalytic membrane reactors to multi-phase systems need to be further explored. In this review, the preparation and the application of inorganic membrane reactors in the different catalytic processes as water gas shift (WGS), Fisher Tropsch synthesis (FTS), selective CO oxidation (CO SeLox), and so on, have been discussed.

Dengue virus (DENV) is an enveloped, single-stranded RNA virus, a member of the Flaviviridae family (which causes Dengue fever), and an arthropod-transmitted human viral infection. Bangladesh is well known for having some of Asia’s most vulnerable Dengue outbreaks, with climate change, its location, and it’s dense population serving as the main contributors. For speculation about DENV outbreak characteristics, it is crucial to determine how meteorological factors correlate with the number of cases. This study used five time series models to observe the trend and forecast Dengue cases. Current data-based research has also applied four statistical models to test the relationship between Dengue-positive cases and meteorological parameters. Datasets were used from NASA for meteorological parameters, and daily DENV cases were obtained from the Directorate General of Health Service (DGHS) open-access websites. During the study period, the mean of DENV cases was 882.26 ± 3993.18, ranging between a minimum of 0 to a maximum of 52,636 daily confirmed cases. The Spearman’s rank correlation coefficient between climatic variables and Dengue incidence indicated that no substantial relationship exists between daily Dengue cases and wind speed, temperature, and surface pressure (Spearman’s rho; r = −0.007, p > 0.05; r = 0.085, p > 0.05; and r = −0.086, p > 0.05, respectively). Still, a significant relationship exists between daily Dengue cases and dew point, relative humidity, and rainfall (r = 0.158, p < 0.05; r = 0.175, p < 0.05; and r = 0.138, p < 0.05, respectively). Using the ARIMAX and GA models, the relationship for Dengue cases with wind speed is −666.50 [95% CI: −1711.86 to 378.86] and −953.05 [−2403.46 to 497.36], respectively. A similar negative relation between Dengue cases and wind speed was also determined in the GLM model (IRR = 0.98). Dew point and surface pressure also represented a negative correlation in both ARIMAX and GA models, respectively, but the GLM model showed a positive association. Additionally, temperature and relative humidity showed a positive correlation with Dengue cases (105.71 and 57.39, respectively, in the ARIMAX, 633.86, and 200.03 in the GA model). In contrast, both temperature and relative humidity showed negative relation with Dengue cases in the GLM model. In the Poisson regression model, windspeed has a substantial significant negative connection with Dengue cases in all seasons. Temperature and rainfall are significantly and positively associated with Dengue cases in all seasons. The association between meteorological factors and recent outbreak data is the first study where we are aware of the use of maximum time series models in Bangladesh. Taking comprehensive measures against DENV outbreaks in the future can be possible through these findings, which can help fellow researchers and policymakers.

To limit the cross-sectional size of concrete structures, high-strength, lightweight concrete is preferred for the design and construction of structural elements. However, the main drawback of high-strength, lightweight concrete is its brittleness over normal-weight concrete. The ductility of concrete is a crucial factor, which plays an important role when the concrete structures are subjected to extreme situations, such as earthquakes and wind. This study aims to improve the ductility of high-strength, lightweight concrete by incorporating steel fibers. The palm oil clinker (POC)-based, high-strength, lightweight concrete specimens reinforced with steel fibers were prepared and their ductility was systematically examined. POC was used as aggregates and supplementary cementitious materials. Steel fibers from 0–1.50% (by volume), with an increment of 0.5%, were used in the concrete mix. Compression ductility, displacement ductility and energy ductility were used as indicators to evaluate the enhancement of ductility. Moreover, the compressive strength, flexural strength, stress-strain behavior, modulus of elasticity, load-displacement characteristics, energy absorption capacity and deformability of the concrete samples were investigated. The compression ductility, displacement ductility and energy ductility indexes were found to be increased by up to 472%, 140% and 568% compared to the control specimens (concrete with 0% steel fibers), respectively. Moreover, the deformability and energy absorption capacity of the concrete were increased by up to 566% and 125%, respectively. Therefore, POC-based, high-strength, fibrous, lightweight concrete could perform better than conventional concrete under extreme loading conditions as it showed significantly higher ductility.