Safety Measures of Journalists during Corona Pandemic in Bangladesh

Among other frontline fighters journalists have been the first responders to the pandemic of the COVID-19 virus Because of following professional responsibilities they have become highly vulnerable to get exposed to the risk As a result providing safety measures to them has received the highest priority at this time It has been urged by national and international organizations and associations to media employers to provide safety measures to their respective journalists This study aims to examine the management of media employers of Bangladesh in providing safety measures to journalists The study interviews 48 journalists of 12 newspapers and 12 television channels selecting one reporter and one copy editor from each media The results reveal that the majority of journalists received inadequate nonstandard irregular imbalanced and improper safety measures while the rest got nothing because of the employer s total negligence and financial crisis The study also shows that the media employers failed to distribute safety measures between reporters and copy editors equally Based on the findings the study concludes by calling for a proper safety plan to protect journalists from health risk

A computationally efficient robust voltage control for a single phase dual active bridge

This paper proposes fractional and integer order sliding mode controllers (SMC) for the high voltage (HV) bridge control in a bidirectional dual active (DAB) converter. The proposed controllers are derived based on nonlinear model of DAB converter and the closed loop stability is ensured using integer and fractional order Lyapunov theorems. Fractional order controllers offer more degree of freedom to adjust the desired response of the system, however the implementation issues of such controllers are rarely explored. Both variants of control schemes are implemented on a DSP control card, and hardware-in-the-loop (HIL) and processor-in-the-loop (PIL) experiments are conducted using rapid control prototyping technique. In order to choose the most suitable robust controller, experimental data for the two performance indices namely robustness and computational resources utilization is compared for both integer and fractional order control schemes. The experimental results demonstrate that the integer order SMC utilizes reduced computational resources as compared to the fractional order SMC. Moreover it is further verified that integer order SMC exhibits comparable robustness as fractional order SMC under all test conditions

Processed Radio Frequency towards Pancreas Enhancing the Deadly Diabetes Worldwide

Diabetes is a chronic and debilitating disease, which is associated with a range of complications putting tremendous burden on medical, economic and socio-technological infrastructure globally. Yet the higher authorities of health services are facing the excruciating cumulative reasons of diabetes as a very imperative worldwide issue in the 21st century. The study aims to relook at the misapplication of the processed radio frequency that frailties in the pancreas within and around the personal body boundary area. The administered sensor data were obtained at laboratory experiments from the selected specimens on dogs and cats in light and dark environments. The study shows the frequent urine flow speed varies with sudden infection due to treated wireless sensor networks in active open eyes. The overweight and obese persons are increasingly affected in diabetes with comprehensive urinary pressure due to continuous staying at dark environment. The findings replicate the increasing tide of diabetes globally. The study also represents the difficulties of physicians to provide adequate diabetic management according to their expectancy due to insecure personal area network control unit.Dynamic sensor network is indispensable for healthcare but such network is at risk to health security due to digitalized poisoning within GPS positions. The study recommends the anti-radiation integrated system policy with user’s security alternative approach to inspire dealing with National Health Policy and Sustainable Development Goals 2030

Comprehensive characterization and kinetic analysis of coconut shell thermal degradation : Energy potential evaluated via the Coats-Redfern method

Coconut shell represents a promising biomass for energy production, given their wide availability. In this study, the thermo-kinetics of coconut shells were examined through thermogravimetric analysis from 30 °C to 1000 °C at 5 °C/min under N2. Advanced analytical tools assessed the elemental, microstructural, and morphological attributes of the samples. The thermal degradation unveiled three phases: dehydration, devolatilization, and combustion. Notably, the Coats-Redfern method detailed the devolatilization stage, pinpointing the coconut shell's thermal and kinetic attributes. The Zhuravlev diffusion equation (DM6) emerged as the most suitable model, with an activation energy (Ea) and pre-exponential factor of 68.9 kJ mol−1 and 0.05 min−1, respectively. Thermodynamic values such as enthalpy (ΔH), Gibbs free energy (ΔG), and entropy (ΔS) for devolatilization were 65.2, 193.1, and −0.28117, respectively. Collectively, the findings underscore the significant bioenergy potential of coconut shells, positioning them as a sustainable alternative to traditional energy. Such insights play a crucial role in improving pyrolysis reactor designs and comprehending the mechanisms of coconut shell pyrolysis, offering potential solutions for energy deficits and environmental concerns

Advancements in hydrogen generation, storage, and utilizations: A comprehensive review of current trends in Bangladesh

Bangladesh is a developing country heavily reliant on fossil fuels, which emits toxic gases during its combustion. In that scenario, hydrogen is an eco-friendly fuel source with a calorific value of 120 MJ/kg which is significantly higher than fossil fuels. With a density of 0.09 kg/m3 at 273 K, hydrogen is just 1/14th that of air. Considering the enriched agricultural resources of Bangladesh, biomass gasification emerges as the most advantageous method for hydrogen production. Compared to other methods like steam reforming and electrolysis, biomass gasification offers significant cost advantages. Furthermore, being an overpopulated country generates significant organic waste annually. The mismanagement of these wastes creates problematic situations for both lives and surroundings. This review approaches the way of waste management and hydrogen production and additionally discusses the current scenario, several hydrogen production pathways, utilization, and storage. This study focused on hydrogen production and utilization in Bangladesh, which will help the researchers to identify suitable and cost-effective methods to obtain the decarbonization goal in the energy sector

Impact of Sensor Networks on Aquatic Biodiversity in Wetland: An Innovative Approach

Aquatic biodiversity is in the central field of environmental conservation issues in a wetland. Yet it determinately faced aquatic conservation authorities the loss of biodiversity as a very important global issue for several years due to misuse wireless sensor technology. The study attempts to re-look at the sensor networks that affect the aquatic biodiversity within and around the Tanguar Haor- wetland study at Sunamganj district in Bangladesh. Key aquatic conservation tools provided at the Tanguar Haor and its challenges with gaps in policies for wetland management practices are highlighted. The study shows the aquatic biodiversity-related rules and regulations amended were apex in Bangladesh from 2010 to 2018. The study represents the impact of processed sensor networks on aquatic biodiversity in a wetland to be compared to larger, medium, and smaller animals in a bright, dark and optimum environment, facilitating the design and misuse of wireless sensor networks within GPS locations. Approximately 64% of the respondents agreed on the development of aquatic biodiversity for managing the wetland at Sunamganj with secure peripheral sensor networks. The research also found that the Tanguar Haor is at risk due to misuse of wireless sensor networks compared to other wetlands in the Sylhet Division. Scientific knowledge is indispensable in wetland resource management but it poorly identified such knowledge while various performances are still below par. The research is unique and represents the innovative idea to improve the existing wetland policy linking with the appropriateness for the Ramsar Wetland Conservation Strateg

Feasibility Study of Perovskite Solar Cell Recycling

Thesis (M.Sc., Sustainable Energy Management)--Prince of Songkla University, 201

An investigation of machine learning algorithms and data augmentation techniques for diabetes diagnosis using class imbalanced BRFSS dataset

© 2023 The Author(s) cc-by-nc-ndDiabetes is a prevalent chronic condition that poses significant challenges to early diagnosis and identifying at-risk individuals. Machine learning plays a crucial role in diabetes detection by leveraging its ability to process large volumes of data and identify complex patterns. However, imbalanced data, where the number of diabetic cases is substantially smaller than non-diabetic cases, complicates the identification of individuals with diabetes using machine learning algorithms. This study focuses on predicting whether a person is at risk of diabetes, considering the individual's health and socio-economic conditions while mitigating the challenges posed by imbalanced data. We employ several data augmentation techniques, such as oversampling (Synthetic Minority Over Sampling for Nominal Data, i.e.SMOTE-N), undersampling (Edited Nearest Neighbor, i.e. ENN), and hybrid sampling techniques (SMOTE-Tomek and SMOTE-ENN) on training data before applying machine learning algorithms to minimize the impact of imbalanced data. Our study sheds light on the significance of carefully utilizing data augmentation techniques without any data leakage to enhance the effectiveness of machine learning algorithms. Moreover, it offers a complete machine learning structure for healthcare practitioners, from data obtaining to machine learning prediction, enabling them to make informed decisions

Eco-Friendly Reduced Graphene Oxide Nanofilter Preparation and Application for Iron Removal

In this paper, the green synthesis of reduced graphene oxide (r-GO) nanomaterials using Callistemon viminalis leaf extract as a reducing and stabilizing agent is reported for the first time. The synthesized r-GO nanomaterials were characterized using UV–Vis, XRD, FE-SEM, TEM, and energy dispersive X-ray (EDX) analyses. The nanofilter membrane was prepared by varying the amounts of r-GO nanomaterials in a Polysulfone-N,N-dimethyl formamide (DMF) solution. The nanofilter membrane was characterized by the contact angle, atomic force microscopy (AFM), UV–Vis, and FTIR. The results confirm the formation of r-GO nanomaterials. Higher amounts of r-GO nanomaterials in the membrane show a lower contact angle, thus confirming their hydrophilic nature. Iron water filtration was performed with different amounts of r-GO nanomaterials in the membrane filter, and the water flux was smooth over an increased time period. Inductively Coupled Plasma (ICP) analysis showed a higher percentage of iron rejection (95.77%) when higher amounts (0.10 g) of r-GO nanomaterials were used in a mixed membrane (i.e., sample C). In conclusion, the findings illustrate that Callistemon viminalis mediates the synthesis of r-GO nanomaterials, which is useful in water filtration, and can be incorporated into membrane filters, since it removes iron

Techno-economic and environmental analysis of organic municipal solid waste for energy production

Addressing the critical conundrum of escalating municipal solid waste (MSW) and shrinking landfill spaces in urban areas, this research pioneers a sustainable approach for Bangladesh by exploring the potential of biogas production from MSW. Distinctly, it fills the research gap by providing a detailed techno-economic and environmental analysis of decentralized fixed-dome anaerobic digestion facilities in the urban context of Chittagong, Bangladesh, a domain previously underexplored. Our findings demonstrate the feasibility of converting MSW into a renewable energy source, offering an innovative solution that simultaneously tackles waste management and energy generation challenges. Each proposed plant showcases the capability to generate 536 m³ of biogas daily, sufficient to power a 50 kW gas engine and supply 44 households, thereby contributing significantly to urban waste reduction and CO2 emissions mitigation by approximately 500 tons monthly. The economic analysis reveals an attractive investment payback period of two years, underscoring the model's viability and its potential as a replicable framework for similar urban settings grappling with waste management crises. This study not only bridges a critical knowledge gap but also introduces a novel, sustainable waste-to-energy model, marking a pivotal step towards achieving energy security and environmental sustainability in developing nations