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ABSTRACT This study investigates the morphometry of the Bakkhali watershed (BW) in the hilly districts of Cox’s Bazar and Bandarban, Bangladesh, to analyze its hydrological characteristics. Morphometric parameters were utilized to prioritize sub-watersheds (SWs) through a hybrid approach combining principal component analysis (PCA) and the weighted-sum approach (WSA). Using ArcGIS Pro 2.7.0, streams, the watershed, and SWs were delineated from a 30-m resolution COP30 DEM. Preliminary priority ranks (PPR) were determined based on direct and inverse relationships of morphometric parameters to soil erodibility. Weighted compound factors (CF) were calculated from PCA results for final prioritization. The BW, a fifth-order watershed with a drainage area of 571.52 km², shows a consistent decrease in the number of streams with increasing stream order, indicating an erosional landform. The mean bifurcation ratio of 4.09 suggests a higher tendency for soil erosion. Shape factors indicate an elongated watershed with less pronounced peak flow characteristics. The analysis identified SW2 and SW3 as high-erosion zones, SW4 and SW9 as medium-erosion zones, and SW1 as a low-erosion zone. The study demonstrates the efficacy of combining geospatial and statistical tools for SW prioritization.

One of the most important discoveries and creative developments that is playing a vital role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far they are. In the last couple of years, the upsurge in blockchain technology has obliged scholars and specialists to scrutinize new ways to apply blockchain technology with a wide range of domains. The dramatic increase in blockchain technology has provided many new application opportunities, including healthcare applications. This survey provides a comprehensive review of emerging blockchain-based healthcare technologies and related applications. In this inquiry, we call attention to the open research matters in this fast-growing field, explaining them in some details. We also show the potential of blockchain technology in revolutionizing healthcare industry.

The impact of land use on water quality is becoming a global concern due to the increasing demand for freshwater. This study aimed to assess the effects of land use and land cover (LULC) on the surface water quality of the Buriganga, Dhaleshwari, Meghna, and Padma river system in Bangladesh. To determine the state of water, water samples were collected from twelve locations in the Buriganga, Dhaleshwari, Meghna, and Padma rivers during the winter season of 2015 and collected samples were analysed for seven water quality indicators: pH, temperature (Temp.), conductivity (Cond.), dissolved oxygen (DO), biological oxygen demand (BOD), nitrate nitrogen (NO 3 -N), and soluble reactive phosphorus (SRP) for assessing water quality (WQ). Additionally, same-period satellite imagery (Landsat-8) was utilised to classify the LULC using the object-based image analysis (OBIA) technique. The overall accuracy assessment and kappa co-efficient value of post-classified images were 92% and 0.89, respectively. In this research, the root mean squared water quality index (RMS-WQI) model was used to determine the WQ status, and satellite imagery was utilised to classify LULC types. Most of the WQs were found within the ECR guideline level for surface water. The RMS-WQI result showed that the “fair” status of water quality found in all sampling sites ranges from 66.50 to 79.08, and the water quality is satisfactory. Four types of LULC were categorised in the study area mainly comprised of agricultural land (37.33%), followed by built-up area (24.76%), vegetation (9.5%), and water bodies (28.41%). Finally, the Principal component analysis (PCA) techniques were used to find out significant WQ indicators and the correlation matrix revealed that WQ had a substantial positive correlation with agricultural land ( r  = 0.68, P  < 0.01) and a significant negative association with the built-up area ( r  =  − 0.94, P  < 0.01). To the best of the authors’ knowledge, this is the first attempt in Bangladesh to assess the impact of LULC on the water quality along the longitudinal gradient of a vast river system. Hence, we believe that the findings of this study can support planners and environmentalists to plan and design landscapes and protect the river environment.

The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditional fish farming methods incur enormous economic costs owing to labor-intensive schedule monitoring and care, illnesses, and sudden fish deaths. Another ongoing issue is automated fish species recommendation based on water quality. On the one hand, the effective monitoring of abrupt changes in water quality may minimize the daily operating costs and boost fish productivity, while an accurate automatic fish recommender may aid the farmer in selecting profitable fish species for farming. In this paper, we present AquaBot, an IoT-based system that can automatically collect, monitor, and evaluate the water quality and recommend appropriate fish to farm depending on the values of various water quality indicators. A mobile robot has been designed to collect parameter values such as the pH, temperature, and turbidity from all around the pond. To facilitate monitoring, we have developed web and mobile interfaces. For the analysis and recommendation of suitable fish based on water quality, we have trained and tested several ML algorithms, such as the proposed custom ensemble model, random forest (RF), support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), logistic regression (LR), bagging, boosting, and stacking, on a real-time pond water dataset. The dataset has been preprocessed with feature scaling and dataset balancing. We have evaluated the algorithms based on several performance metrics. In our experiment, our proposed ensemble model has delivered the best result, with 94% accuracy, 94% precision, 94% recall, a 94% F1-score, 93% MCC, and the best AUC score for multi-class classification. Finally, we have deployed the best-performing model in a web interface to provide cultivators with recommendations for suitable fish farming. Our proposed system is projected to not only boost production and save money but also reduce the time and intensity of the producer’s manual labor.

Spatiotemporal rainfall trend analysis as an indicator of climatic change provides critical information for improved water resource planning. However, the spatiotemporal changing behavior of rainfall is much less understood in a tropical monsoon-dominated country like Bangladesh. To this end, this research aims to analyze spatiotemporal variations in rainfall for the period 1980–2020 over Bangladesh at seasonal and monthly scales using MAKESENS, the Pettitt test, and innovative trend analysis. Multilayer Perception (MLP) neural network was used to predict the next 8 years' rainfall changes nationally in Bangladesh. To investigate the spatial pattern of rainfall trends, the inverse distance weighting model was adopted within the ArcGIS environment. Results show that mean annual rainfall is 2432.6 mm, of which 57.6% was recorded from July to August. The Mann–Kendall trend test reveals that 77% of stations are declining, and 23% have a rising trend in the monthly rainfall. More than 80% of stations face a declining trend from November to March and August. There is a declining trend for seasonal rainfall at 82% of stations during the pre-monsoon, 75% during the monsoon, and 100% during the post-monsoon. A significant decline trend was identified in the north-center during the pre-monsoon, the northern part during the monsoon, and the southern and northwestern portions during the post-monsoon season. Predicted rainfall by MLP till 2030 suggests that there will be little rain from November to February, and the maximum fluctuating rainfall will occur in 2025 and 2027–2029. The ECMWF ERA5 reanalysis data findings suggested that changing rainfall patterns in Bangladesh may have been driven by rising or reducing convective precipitation rates, low cloud cover, and inadequate vertically integrated moisture divergence. Given the shortage of water resources and the anticipated rise in water demand, the study's findings have some implications for managing water resources in Bangladesh.

This paper represents a penta band square enclosed star-shaped modified split ring resonator (SRR) based single negative meta-atom absorber (MAA) for multi-band microwave regime applications. FR-4 low-cost material has been used as a substrate to make the MAA unit cell with 0.101λ 0  × 0.101λ 0 of electrical size, where λ 0 is the wavelength calculated at the lower resonance frequency of 3.80 GHz. There are two outer square split ring and one inner star ring shape resonator of 0.035 mm thickness of copper placed on the one side, and another side of the substrate has full copper to construct the desired unit cell. The MAA unit cell provides five absorption peaks of 97.87%, 93.65%, 92.66%, 99.95%, and 99.86% at the frequencies of 3.80, 5.65, 8.45, 10.82, and 15.92 GHz, respectively, which covers S-, C-, X-, and Ku- bands. The properties of MAA have been investigated and analyzed in the E-, H-fields and surface current. The EMR and highest Q factor of the designed MAA is 9.87 and 30.41, respectively, and it shows a single negative (SNG) property. Different types of parametric analysis have been done to show the better performance of absorption. Advanced Designed System (ADS) software has been used for equivalent circuit to verify the simulated S 11 result obtained from the CST-2019 software. Experimental outcomes of the MAA unit cell have a good deal with the simulated result and measured result of the 24 × 20 array of unit cells also shown. Since the unit cell provides superior EMR, excellent Q-factor, and highest absorption so the recommended MAA can be effectively used as a penta band absorber in microwave applications, like notch filtering, sensing, reducing the unintended noise generated with the copper component of the satellite and radar antennas.

An inductively tuned modified split-ring resonator-based metamaterial (MTM) is presented in this article that provides multiple resonances covering S, C, X, and Ku-bands. The MTM is designed on an FR-4 substrate with a thickness of 1.5 mm and an electrical dimension of 0.063λ × 0.063λ where wavelength, λ is calculated at 2.38 GHz. The resonator part is a combination of three squared copper rings and one circular ring in which all the square rings are modified shaped, and the inner two rings are interconnected. The resonance frequency is tuned by adding inductive metal strips in parallel two vertical splits of the outer ring that causes a significant shift of resonances towards the lower frequencies and a highly effective medium ratio (EMR) of 15.75. Numerical simulation software CST microwave studio is used for the simulation and performance analysis of the proposed unit cell. The MTM unit cell exhibits six resonances of transmission coefficient (S 21 ) at 2.38, 4.24, 5.98, 9.55, 12.1, and 14.34 GHz covering S, C, X, and Ku-bands with epsilon negative (ENG), near-zero permeability, and near-zero refractive index (NZI). The simulated result is validated by experiment with good agreement between them. The performance of the array of the unit cells is also investigated in both simulation and measurement. The equivalent circuit modeling has been accomplished using Advanced Design Software (ADS) that shows a similar S 21 response compared to CST simulation. Noteworthy to mention that with the copper backplane, the same unit cell provides multiband absorption properties with four major absorption peaks of 99.6%, 95.7%, 99.9%, 92.7% with quality factors(Q-factor) of 28.4, 34.4, 23, and 32 at 3.98, 5.5, 11.73 and 13.47 GHz, respectively which can be applied for sensing and detecting purposes. The application of an array of the unit cells is investigated using it as a superstrate of an antenna that provides a 73% (average) increase of antenna gain. Due to its simple design, compact dimension with high EMR, ENG property with near-zero permeability, this multiband NZI metamaterial can be used for microwave applications, especially for multiband antenna gain enhancement.

The purpose of this study is to evaluate the adverse impact of groundwater flow path fluctuations and velocity in the water-stressed drought-prone northern region of Bangladesh. By the integrating geospatial technique and the Darcy flow model computes the volume balance and flows velocity of groundwater flow path fluctuations visualization and flow trends. The residual volume of groundwater flow are decreased gradually, and the flow velocity increased in the last twenty years due to the changes of saturated thickness and hydraulic head. The mean value of flow velocity ranged between 5900 and 7300 m/year and increased in every season from 2001 to 2020. The volume balance residual shows a slight increase from 2001 to 2010, followed by a decrease in 2010–2020. The groundwater flow path fluctuations of the study area are intensely falling and changing its drifts. This findings are indicated that the groundwater flow paths fluctuation is in the Northern Bangladesh are dramatically falling and changing its pattern. This depletion is found on such areas, where occur more groundwater withdrawal for different purposes. Over 31% of the region of the study site is now experiencing severe and extreme drought owing to variations in the groundwater levels. The extraction of groundwater for irrigation, which has a substantial adverse impact on ecological systems and agro-agricultural output of the study area. The current situation of the Northern Bangladesh will be deteriorated significantly if we do not reduce the groundwater discharge from deep aquifers for irrigation and reduce the use of surface water.

Herein, we present an interfacial engineering strategy to construct an efficient hydrothermal approach by in situ growing cobalt-doped@MnO2 nanocomposite on highly conductive nickel foam (Ni foam) for supercapacitors (SCs). The remarkably high specific surface area of Co dopant provides a larger contacting area for MnO2. In the meantime, the excellent retentions of the hierarchical phase-based pore architecture of the cobalt-doped surface could beneficially condense the electron transportation pathways. In addition, the nickel foam (Ni foam) nanosheets provide charge-transport channels that lead to the outstanding improved electrochemical activities of cobalt-doped@MnO2. The unique cobalt-doped@MnO2 nanocomposite electrode facilitates stable electrochemical architecture, multi-active electrochemical sites, and rapid electro-transports channels; which act as a key factor in enhancing the specific capacitances, stability, and rate capacities. As a result, the cobalt-doped@MnO2 nanocomposite electrode delivered superior electrochemical activities with a specific capacitance of 337.8 F g–1 at 0.5 A g–1; this is greater than pristine MnO2 (277.9 F g–1). The results demonstrate a worthy approach for the designing of high-performance SCs by the grouping of the nanostructured dopant material and metal oxides.

One of the widely used methods for evaluating the overall quality of a diet is the Healthy Eating Index. In the present study protocol, we lay out the methodological approach to the development and validation of a healthy eating index specific for the Bangladeshi population (hereinafter referred to as Bangladesh Healthy Eating Index (BD-HEI)). Bangladesh Healthy Eating Index will be developed based on the Food-based dietary guidelines (FBDG) of Bangladesh. Using a scoring system that aligns with the eleven food groups outlined in the FBDG, the index will consist of eleven eating components. A cross-sectional community nutrition survey will be carried out among 1080 reproductive-aged women. Through this survey, quantitative dietary data will be collected following multiple pass 24h dietary recall method. Repeated 24-hour dietary data (of two consecutive days) will be collected from one-third of the respondents. Evaluating usual food and nutrient intake as well as the probability of nutrient intake adequacy, the study will examine the validity of the BD-HEI. Following a suitable statistical procedure, the reliability and construct validity of BD-HEI will be evaluated. Country-specific HEI can be used to assess the dietary quality of the people of that country. The findings from this research can inform policy decisions and strategies to promote healthier eating habits and combat the rising burden of diet-related diseases in the country.