Nuclear energy in Bangladesh: A SWOT analysis.

Zero-emission energy sources like nuclear energy are taken into account worldwide due to the negative environmental consequences of fossil fuels and their limited availability over the years. Bangladesh plans to add nuclear energy to its portfolio of energy sources by 2024. Under the scope of this study, the country's nuclear energy strategy was looked at in terms of its strengths, weaknesses, opportunities, and threats.

Enhancing vaccination strategies for epidemic control through effective lockdown measures.

Evolutionary epidemiology models have substantially impacted the study of various infections and prevention methods in the biology field. These models are called Susceptible, Lockdown, Vaccinated, Infected, and Recovered (SLVIR) epidemic dynamics. We explore how human behavior, particularly in the context of disease transmission, is influenced by two intervention strategies: vaccination and lockdown, both of which are grounded in the principles of evolutionary game theory (EGT).

Service quality, satisfaction, and intention to use Pourasava Digital Center in Bangladesh: The moderating effect of citizen participation.

This study describes how, as part of the administrative reform of Bangladesh, most of the urban local governments have set up some public service center like Pourasava Digital Center (PDC), where ICT (Information and Communication Technology) has been commonly applied to make e-services more convenient, efficient and transparent. The current study measures the Service Quality Satisfaction and Continuous Use Intention to use Pourasava Digital Center (PDC) in Bangladesh by adopting citizen participation as a moderator. Theoretically, this study has used the DeLone & McLean Information Systems (D&M IS) Success Model and Zhang's two-dimensional satisfaction model.

The experimental significance of isorhamnetin as an effective therapeutic option for cancer: A comprehensive analysis.

Isorhamnetin (CHO), a 3'-O-methylated derivative of quercetin from the class of flavonoids, is predominantly present in the leaves and fruits of several plants, many of which have traditionally been employed as remedies due to its diverse therapeutic activities. The objective of this in-depth analysis is to concentrate on Isorhamnetin by addressing its molecular insights as an effective anticancer compound and its synergistic activity with other anticancer drugs. The main contributors to Isorhamnetin's anti-malignant activities at the molecular level have been identified as alterations of a variety of signal transduction processes and transcriptional agents.

Probability and kinetics of rupture and electrofusion in giant unilamellar vesicles under various frequencies of direct current pulses.

Irreversible electroporation induces permanent permeabilization of lipid membranes of vesicles, resulting in vesicle rupture upon the application of a pulsed electric field. Electrofusion is a phenomenon wherein neighboring vesicles can be induced to fuse by exposing them to a pulsed electric field. We focus how the frequency of direct current (DC) pulses of electric field impacts rupture and electrofusion in cell-sized giant unilamellar vesicles (GUVs) prepared in a physiological buffer.

Ratiometric nonfluorescent CRISPR assay utilizing Cas12a-induced plasmid supercoil relaxation.

Most CRISPR-based biosensors rely on labeled reporter molecules and expensive equipment for signal readout. A recent approach quantifies analyte concentration by sizing λ DNA reporters via gel electrophoresis, providing a simple solution for label-free detection. Here, we report an alternative strategy for label-free CRISPR-Cas12a, which relies on Cas12a trans-nicking induced supercoil relaxation of dsDNA plasmid reporters to generate a robust and ratiometric readout.

Amplified and distinctive genotoxicity of titanium dioxide nanoparticles in transformed yeast reporters with human cytochrome P450 (CYP) genes.

Titanium dioxide nanoparticles (nTiO) have been considered a possible carcinogen to humans, but most existing studies have overlooked the role of human enzymes in assessing the genotoxicity of nTiO. Here, a toxicogenomics-based in vitro genotoxicity assay using a GFP-fused yeast reporter library was employed to elucidate the genotoxic potential and mechanisms of nTiO. Moreover, two new GFP-fused yeast reporter libraries containing either human CYP1A1 or CYP1A2 genes were constructed by transformation to investigate the potential modulation of nTiO genotoxicity in the presence of human CYP enzymes.

Effect of the nonlinear dispersive coefficient on time-dependent variable coefficient soliton solutions of the Kolmogorov-Petrovsky-Piskunov model arising in biological and chemical science.

In this article, we study the soliton solutions with a time-dependent variable coefficient to the Kolmogorov-Petrovsky-Piskunov (KPP) model. At first, this model was used as the genetics model for the spread of an advantageous gene through a population, but it has also been used as a number of physics, biological, and chemical models. The enhanced modified simple equation technique applies to get the time-dependent variable coefficient soliton solutions from the KPP model.

Computational and experimental study on the aerodynamic performance of NACA 4412 airfoil with slot and groove.

Since the Wright Brothers' first flight in 1903, extensive research has been dedicated to improving the aerodynamic performance of aircraft. This study investigates the effect of two distinct wing geometric modifications on airfoil performance at high angles of attack (AOAs). These two modifications are slot, specifically the NACA 4412 with only a slot, and groove, specifically the NACA 4412 with both a slot and a groove.

Compressive strength assessment of concrete with brick chips using the CAPO-test.

This study presents the findings of an extensive investigation to evaluate the precision and reliability of a non-destructive CAPO-Test in estimating the in situ compressive strength of concrete made from machine-crushed brick aggregates. To estimate the compressive strength of concrete built from brick and stone aggregates for several target strengths at various ages, the CAPO-Test, core test, and standard cylinder test were used. The results of the core test and cylinder test are correlated with the CAPO pullout force, demonstrating a strong relationship between pullout force and compressive strength.

BananaSet: A dataset of banana varieties in Bangladesh.

This article introduces a primary dataset sourced from diverse marketplaces in Bangladesh, encompassing six distinct banana varieties predominantly consumed locally. The dataset comprises the following banana types: . High-resolution images of bananas from each category were acquired using a smartphone camera.

Nanocellulose-based porous lightweight materials with flame retardant properties: A review.

This review discusses the development and application of nanocellulose (NC)-aerogels, a sustainable and biodegradable biomaterial, with enhanced flame retardant (FR) properties. NC-aerogels combine the excellent physical and mechanical properties of NC with the low density and thermal conductivity of aerogels, making them promising for thermal insulation and other fields. However, the flammability of NC-aerogels limits their use in some applications, such as electromagnetic interference shielding, oil/water separation, and flame-resistant textiles.

Analysis and interpretability of machine learning models to classify thyroid disease.

Thyroid disease classification plays a crucial role in early diagnosis and effective treatment of thyroid disorders. Machine learning (ML) techniques have demonstrated remarkable potential in this domain, offering accurate and efficient diagnostic tools. Most of the real-life datasets have imbalanced characteristics that hamper the overall performance of the classifiers.

Sustainable development of three distinct starch based bio-composites reinforced with the cotton spinning waste collected from fiber preparation stage.

Composites are new materials that combine two or more distinct components with diverse properties to create a new material with improved properties. The goal of this endeavor was to use fiber preparation wastes, or waste from cotton spinning mill blow room and carding, to produce bio composites based on starch. The matrix was prepared using the starches of potatoes, maize, and arrowroot, and any remaining reinforcing material was used.

First-principles study of a SiC nanosheet as an effective material for nitrosourea and carmustine anti-cancer drug delivery.

The development of novel nanosheet-based drug delivery systems requires a systematic understanding of the interactions between the drug and the nanosheet carrier under various physiological environments. In this work, we investigated electronic and quantum molecular descriptors of a SiC monolayer adsorbed with the anticancer drugs nitrosourea (NU) and carmustine (BCNU) using density functional theory (DFT). Our calculations revealed negative adsorption energies for both drugs, indicating a spontaneous and energetically favorable adsorption process.

Investigation of the performance of the combined moving bed bioreactor-membrane bioreactor (MBBR-MBR) for textile wastewater treatment.

The present study focused on the investigation of the performance of a Moving Bed Bioreactor coupled with a Membrane Bioreactor (MBBR-MBR) on a small scale for textile wastewater treatment. The parameters examined in this study included the removal efficiency of chemical oxygen demand (COD), biochemical oxygen demand (BOD), total suspended solids (TSS), turbidity, color, and heavy metals (HM). The two reactors were operated consecutively and maintained aerobic conditions.

Rice seeds biofortification using biogenic ıron oxide nanoparticles synthesized by using Glycyrrhiza glabra: a study on growth and yield ımprovement.

Iron, a crucial micronutrient, is an integral element of biotic vitality. The scarcity of iron in the soil creates agronomic challenges and has a detrimental impact on crop vigour and chlorophyll formation. Utilizing iron oxide nanoparticles (IONPs) via nanopriming emerges as an innovative method to enhance agricultural efficiency and crop health.

Application of extreme learning machine (ELM) forecasting model on CO emission dataset of a natural gas-fired power plant in Dhaka, Bangladesh.

Understanding and predicting CO emissions from individual power plants is crucial for developing effective mitigation strategies. This study analyzes and forecasts CO emissions from an engine-based natural gas-fired power plant in Dhaka Export Processing Zone (DEPZ), Bangladesh. This study also presents a rich dataset and ELM-based prediction model for a natural gas-fired plant in Bangladesh.

Decision support system for community managed rainwater harvesting: A case study in the salinity-prone coastal region of Bangladesh.

Climate change-induced saline intrusion into both surface and groundwater, extreme weather events, and unregulated water usage are serious threats to the drinking water supply in coastal areas worldwide, especially in least-developed countries. This research developed a data-driven decision-making methodology to evaluate the performance of rainwater harvesting (RWH) systems in the saline-prone southwestern coastal region of Bangladesh. Twenty-five community managed RWH systems, recently piloted in two major coastal districts, were considered the case study to develop and validate this evaluation tool.

Evolution of dispersal and the analysis of a resource flourished population model with harvesting.

This study explores a spatially distributed harvesting model that signifies the outcome of the competition of two species in a heterogeneous environment. The model is controlled by reaction-diffusion equations with resource-based diffusion strategies. Two different situations are maintained by the harvesting effects: when the harvesting rates are independent in space and do not exceed the intrinsic growth rate; and when they are proportional to the time-independent intrinsic growth rate.

Size-dependent deleterious effects of nano- and microplastics on sperm motility.

Introduction: Growing concerns regarding the reproductive toxicity associated with daily life exposure to micro-/nano-plastics (abbreviated as MNPs) have become increasingly prevalent. In reality, MNPs exposure involves a heterogeneous mixture of MNPs of different sizes rather than a single size.

Methods: In this study, an oral exposure mouse model was used to evaluate the effects of MNPs of four size ranges: 25-30 nm, 1-5 µm, 20-27 µm, and 125-150 µm.

The Rohingya refugee crisis in Bangladesh: assessing the impact on land use patterns and land surface temperature using machine learning.

Bangladesh, a third-world country with the seventh highest population density in the world, has always struggled to ensure its residents' basic needs. But in recent years, the country is going through a serious humanitarian and financial crisis that has been imposed by the neighboring country Myanmar which has forced the government to shelter almost a million Rohingya refugees in less than 3 years (2017-2020). The government had no other option but to acquire almost 24.

Microplastics from face mask impairs sperm motility.

The COVID-19 pandemic has resulted in unprecedented plastic pollution from single-used personal protective equipment (PPE), especially face masks, in coastal and marine environments. The secondary pollutants, microplastics from face masks (mask MP), rise concern about their detrimental effects on marine organisms, terrestrial organisms and even human. Using a mouse model, oral exposure to mask MP at two doses, 0.

PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information.

The dynamic evolution of the severe acute respiratory syndrome coronavirus 2 virus is primarily driven by mutations in its genetic sequence, culminating in the emergence of variants with increased capability to evade host immune responses. Accurate prediction of such mutations is fundamental in mitigating pandemic spread and developing effective control measures. This study introduces a robust and interpretable deep-learning approach called PRIEST.

Distance plus attention for binding affinity prediction.

Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related proteins. Accurate affinity predictions can significantly reduce both the time and cost involved in drug development. However, highly precise affinity prediction remains a research challenge.