Search

Abstract This article delves into the dynamic constructions of distinctive traveling wave solutions for wave circulation in shallow water mechanics, specifically addressing the time-fractional couple Drinfel’d–Sokolov–Wilson (DSW) equation. Introducing the previously untapped $$exp(-\phi (\xi ))$$ e x p ( - ϕ ( ξ ) ) -expansion method, we successfully generate a diverse set of analytic solutions expressed in hyperbolic, trigonometric, and rational functions, each with permitted parameters. Visualization through three-dimensional (3D) as well two-dimensional (2D) plots, including contour plots, reveals inherent wave phenomena in the DSW equation. These newly obtained wave solutions serve as a catalyst for refining theories in applied science, offering a means to validate mathematical simulations for the proliferation of waves in shallow water as well as other nonlinear scenarios. Obtained wave solutions demonstrate the bright soliton, periodic, multiple soliton, and kink soliton shape. The simplicity and efficacy of the implemented methods are demonstrated, providing a valuable tool for approximating the considered equation. All figures are devoted to demonstrate the complete wave futures of the attained solutions to the studied equation with the collaboration of specific selections of the chosen parameters. Moreover, it may have summarized that the attained wave solutions and their physical phenomena might be useful to comprehend the various kind of wave propagation in mathematical physics and engineering.

Abstract This study retrieves some novel exact solutions to the family of 3D space–time fractional Wazwaz–Benjamin–Bona–Mahony (WBBM) equations in the context of diverse nonlinear physical phenomena resulting from water wave mechanics. The family of WBBM equations is transformed for this purpose using a space and time fractional transformation into an ordinary differential equation (ODE). The ODE then uses a strong method, namely the Unified Method. Consequently, lump solutions, dark-bright soliton, singular and multiple soliton solutions, and periodic solutions are investigated. The disparities between the current study's conclusions and previously acquired solutions via other approaches are examined. All wave solutions produced are determined to be novel in terms of fractionality, unrestricted parameters, and implemented technique sense. The impact of unrestricted parameters and fractionality on the obtained solutions are visually presented, along with physical explanations. It is observed that the wave portents are varied with the increase of unrestricted parameters as well as fractionality. We dynamically showed that the appropriate transformation and the applied Unified approach more proficient in the study of water wave dynamics and might be used in future researches to clarify the many physical phenomena. The novelty of this work validate that the proposed method seem simple and useful tools for obtaining the solutions in PDEs and it is expected to use in mathematical physics and optical engineering.

Introduction: During the COVID-19 pandemic, Bangladeshi students had to deal with drastic changes. In-person education was suspended, and online education was introduced along with movement restrictions within the community. This study aimed to assess the prevalence of stress, depression, and their combination among Bangladeshi students and evaluate their association with demographic factors and media usage during the pandemic. Methods: A cross-sectional study was conducted online using a structured questionnaire between January 2021 and January 2022 on 1377 students by a convenience sampling method. Demographic factors along with media usage frequency were recorded. The Perceived Stress Scale-10 was used to assess stress. Depression was evaluated by the WHO-5 Well-Being Index. Results: The average age of the participants was 20.8 ± 3.1 years; 51.6% of them were male. The prevalence of high stress, depression, and a coexistence of high stress and depression (CHSD) was 24.8%, 49.5%, and 20.9%, respectively. These indices significantly increased in females and with increasing age groups of participants. Students with inferior self-perceived health had higher odds of suffering from stress and CHSD, whereas students with general/poor health had the highest odds of high media usage and to suffer from high stress, depression, and CHSD. Students with high stress were found to have 9.49 times and 27.9 times higher probability to suffer from depression than students with moderate and low stress, respectively. Conclusion: This study has identified some important factors that can act as possible indicators to evaluate the prognosis of mental health problems among Bangladeshi students during public health emergencies.

Abstract Background The World Health Organization (WHO) recommends balanced energy and protein (BEP) supplementation be provided to all pregnant women living in undernourished populations, usually defined as having a prevalence > 20% of underweight women, to reduce the risk of stillbirths and small-for-gestational-age neonates. Few geographies meet this threshold, however, and a large proportion of undernourished women and those with inadequate gestational weight gain could miss benefiting from BEP. This study compares the effectiveness of individual targeting approaches for supplementation with micronutrient-fortified BEP vs. multiple micronutrient supplements (MMS) alone as control in pregnancy in improving birth outcomes. Methods The TARGET-BEP study is a four-arm, cluster-randomized controlled trial conducted in rural northwestern Bangladesh. Eligible participants are married women aged 15–35 years old identified early in pregnancy using a community-wide, monthly, urine-test-based pregnancy detection system. Beginning at 12–14 weeks of gestation, women in the study area comprising 240 predefined sectors are randomly assigned to one of four intervention arms, with sector serving as the unit of randomization. The interventions involving daily supplementation through end of pregnancy are as follows: (1) MMS (control); (2) BEP; (3) targeted BEP for those with pre-pregnancy body mass index (BMI)

Prostacyclin or prostaglandin I2 (PGI2), a metabolite of arachidonic cyclooxygenase pathway, has been demonstrated as an effector of adipocyte differentiation. However, due to its instability in biological fluid, it is difficult to evaluate the role of PGI2 in regulating adipocyte differentiation in different stages in culture. Therefore, this study aimed to establish a simple and rapid method for the production of monoclonal antibody against 6-Keto PGF1α, a stable PGI2 metabolite, and its quantification to determine the role of PGI2 in culture medium. Eight-week-old female BALB/c mice were immunized with the hapten of 6-Keto PGF1α and BSA for several weeks until a higher antibody titer (absorbance value > 0.9 at 1000-times dilution) against 6-Keto PGF1α was found. Then, fusion of antibody-producing spleen lymphocytes with SP-2 myeloma cells and thymocytes was performed and cultured in HAT-medium supplemented with hypoxanthine, aminopterin, and thymine. Specific antibody-producing cells (M2-A4-B8-D10) against 6-Keto PGF1α were identified and separated. A standard ELISA calibration curve was developed with 100% reactivity for 6-Keto-PGF 1 α ranging from 0.26 pg to 6.44 ng corresponding to 90% and 10% of the maximum binding capacity for the immobilized antigen respectively. This method can easily be applied to monitor PGI2 regulation in different stages of cultured adipocytes to reveal the regulatory roles of PGI2 in maintaining homeostasis and adipocyte differentiation.

Background: The differentiation between COVID-19 and post-COVID-19 syndromes is not properly defined as some patients remain asymptomatic for post-COVID-19. It can be characterized by several signs and symptoms. Risk factors related to post-COVID-19 remain unsolved. Here we aimed to differentiate post-COVID-19 patients among symptomatic and asymptomatic groups to check the percentage among them and the risk factors for post-COVID-19 and the association of different symptoms. Methods: This study was conducted in Chittagong division, Bangladesh at different hospitals. Data were collected from the participants either by in person interview or online (email) or mobile phone calls. Follow up was done after 3 months to check the development of post-COVID-19 syndromes. Relevant data were taken, and symptomatic and asymptomatic patients were divided based on the presence and severity of specific symptoms. Results: Our results showed that 41.88 % patients develop post-COVID-19 symptoms. Fever and Cough were classified as one of the factors of post-COVID-19, followed by dyspnea, fatigue, cough, rhinitis, sore throat, and muscular discomfort. On the other hand, age, respiratory distress, lethargy, duration of illness and severity were classified as risk factors for post-COVID-19. There was a significant difference between symptomatic and asymptomatic patients as only 16.3 % patients showed post-COVID-19 symptoms. Based on the severity grade, 80.7 % of patients had mild COVID-19. We also found that people with ‘B’ positive blood group had a higher chance of developing post-COVID-19 syndrome. Conclusion: It was concluded that age, duration of illness, presence of respiratory distress, blood group, and disease severity are major risk factors for the development of post-COVID-19 syndrome.

Obesity is a known risk factor for many chronic diseases and a substantial threat to public health. We investigated the effects of figs sourced from Ficus hispida on a high fat-fed experimental rat model. We found that a 500-mg dose of ethanolic extract of figs (EFH) reduced oxidative stress markers nitric oxide (NO), malondialdehyde (MDA), and advanced oxidation protein products (AOPP), which were increased in high fat-fed rats. Antioxidant enzymes superoxide dismutase (SOD), catalase, reduced glutathione (GSH), and myeloperoxidase (MPO), found elevated in high fat-fed rats, were also normalized to nearly regular levels by fig treatment. Administration of EFH further reduced fat deposition and expression of adipogenic genes leptin, fatty acid synthase (FAS), peroxisome proliferator-activated receptor gamma (PPARγ), and sterol regulatory element-binding protein-1c (SERBP-1c). Our results suggest that figs have significant effects on reducing oxidative stress and mitigating obesity-associated liver and adipose tissue abnormalities via suppressing adipogenesis. Thus, we propose that F. hispida has potential benefits in reducing obesity.

Abstract DNA-binding proteins (DBPs) play a significant role in all phases of genetic processes, including DNA recombination, repair, and modification. They are often utilized in drug discovery as fundamental elements of steroids, antibiotics, and anticancer drugs. Predicting them poses the most challenging task in proteomics research. Conventional experimental methods for DBP identification are costly and sometimes biased toward prediction. Therefore, developing powerful computational methods that can accurately and rapidly identify DBPs from sequence information is an urgent need. In this study, we propose a novel deep learning-based method called Deep-WET to accurately identify DBPs from primary sequence information. In Deep-WET, we employed three powerful feature encoding schemes containing Global Vectors, Word2Vec, and fastText to encode the protein sequence. Subsequently, these three features were sequentially combined and weighted using the weights obtained from the elements learned through the differential evolution (DE) algorithm. To enhance the predictive performance of Deep-WET, we applied the SHapley Additive exPlanations approach to remove irrelevant features. Finally, the optimal feature subset was input into convolutional neural networks to construct the Deep-WET predictor. Both cross-validation and independent tests indicated that Deep-WET achieved superior predictive performance compared to conventional machine learning classifiers. In addition, in extensive independent test, Deep-WET was effective and outperformed than several state-of-the-art methods for DBP prediction, with accuracy of 78.08%, MCC of 0.559, and AUC of 0.805. This superior performance shows that Deep-WET has a tremendous predictive capacity to predict DBPs. The web server of Deep-WET and curated datasets in this study are available at https://deepwet-dna.monarcatechnical.com/ . The proposed Deep-WET is anticipated to serve the community-wide effort for large-scale identification of potential DBPs.

The research aims to find out the reusability of jute stick charcoal (JSC) to remove Remazol Red (RR) from textile effluents. The JSC was characterized by scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, and Fourier-transform infrared (FTIR) spectroscopy to analyze the morphology, functional groups, and chemical composition, respectively. The batch adsorption method was applied in this study, and it disclosed that dye uptake depends on various factors, namely, pH, contact time, adsorbent dose, and dye concentration. Notably, 93.12% of the dye was removed with the best removal efficiency at a pH of 1, an adsorbent dose of 0.6 g, and an equilibrium time of 120 min, where the adsorption occurred rapidly in the first 20 min. The Langmuir isotherm model successfully defined the adsorption phenomena, yielding an R2 value of 0.995. The kinetic experimental data followed the pseudo-second-order model (R2 = 0.999). The optimum adsorption parameters were implemented for the effluent obtained from a dye bath where a fabric sample (5 g) was dyed with RR, and 62.4% dye was removed. For the scaled application of JSC to a wastewater stream, the raw textile effluent was also treated, which resulted in 52.6% of dye removal. These results show that JSC is a promising adsorbent for treating textile wastewater. HIGHLIGHTS Adsorption of RR dye on JSC and characterization of JSC were studied.; The adsorption process is highly pH-specific (pH = 1).; Nearly 93.12% of the dye removal was observed at optimized conditions.; The experimental findings fit well with pseudo-second-order and Langmuir models.; The optimum conditions have been implemented on both the dyed sample fabric bath (62.4% removal) and actual raw textile effluent (52.6%).;

The green, biodegradable, and cost-effective properties of natural fiber-reinforced polymer composite materials have attracted significant interest when compared to synthetic polymer composites. Jute is a naturally occurring bast fiber that is inexpensive, durable, and often utilized. In contrast, glass is a composite material that is frequently used in various applications, despite its high cost and potential environmental risks. Owing to jute's superior mechanical properties, there is a great deal of potential for combining it with glass, which would lower the amount of glass used and the composite's overall cost. This study employed bleached jute fabric and non-woven glass fabric to develop neat jute, neat glass, and hybrid composites by using different stacking sequences. The composites were fabricated utilizing a thermoset polymer matrix by following the hand layup process. Subsequently, an investigation was carried out to examine the mechanical, physical, thermal, and morphological properties of these composites. Out of the developed samples, the neat jute presents the least tensile and bending strength at 31.35 MPa and 41.138 MPa respectively, whereas the neat glass composite demonstrates exceptional tensile and bending strengths at 132.03 MPa and 184.86 MPa respectively. In the case of hybrid samples, they exhibited mechanical capabilities that fell between neat jute and neat glass, which was attributed to the combination of glass with jute fabric and the placement of glass as the outer layer. Apart from that, we observed that the moisture take-up% and thermal conductivity of hybrids composite were within 4–4.3% and 0.28–0.32 Wm−1 K-1 respectively. Moreover, thermogravimetric analysis and morphological behavior were also assessed. However, this study suggested that jute and nonwoven glass fabric with different stacking sequences may be combined to create a reinforced hybrid composite that may have potential use in furniture, interior design, and inner sections of cars.

Machine learning (ML) and deep learning (DL) models have been extensively explored for the early diagnosis of various cancer diseases, including Leukemia, with many of them achieving significant performance improvements comparable to those of human experts. However, challenges like limited image data, inaccurate annotations, and prediction reliability still hinder their broad implementation to establish a trustworthy computer-aided diagnosis (CAD) system. This paper introduces a novel weighted-average ensemble model for classifying Acute Lymphoblastic Leukemia, along with a reliable Computer-Aided Diagnosis (CAD) system that combines the strengths of both ML and DL approaches. Initially, a variety of filtering methods are extensively analyzed to determine the most suitable image representation, with subsequent data augmentation techniques to expand the training data. Second, a modified VGG-19 model was proposed with fine-tuning that was utilized as a feature extractor to extract meaningful features from the training samples. Third, A small-loss approach and probabilistic local outlier factor (pLOF) have been developed on the extracted features to address the label noise issue. Fourth, we proposed an weighted-average ensemble model based on the top five models as base learners, with weights calculated based on their model uncertainty to ensure reliable predictions. Fifth, we calculated Shapley values based on cooperative game theory and performed feature selection with different feature combinations to determine the optimal number of features using SHAP. Finally, we integrate these strategies to develop an interpretable CAD system. This system not only predicts the disease but also generates Grad-CAM images to visualize potential affected areas, enhancing both clarity and diagnostic insight. All of our code is provided in the following repository: https://github.com/taareek/leukemia-classification

In order to systematically investigate the correlating capability of viscosity models, six well-known correlative models of Grunberg-Nissan (GN), Hind (HND), Heric (HRC), Ausländer (AUS) for dynamic viscosity, η, and McAllister 3-body (MAC3) and McAllister 4-body (MAC4) for kinematic viscosity, ν, were employed and tested for viscosity data of 83 organic binary liquid systems consisting of 33 different aromatic hydrocarbons (ArH), alkanes (RH), cycloalkanes (CyRH) and alkanols (ROH). Keeping ArH as a common component and increasing the chain length of other components, the systems were categorized as Category 1: ArH + RH, Category 2: ArH + CyRH, Category 3: ArH + ArH and Category 4: ArH + ROH. For all the models fitting parameters along with the statistical parameters such as SPD σ(%), ASPD σ(%), OASPD σ(%) and GOASPD σ(%) were computed by the Nonlinear Least Squares Minimization (NLSM) technique with the ‘Solver’ add-in package. Among the four categories, Category 3, OASPD, σ(%) values lie between 0.16 and 0.21, indicating that all the models fitted extremely well. However, for dynamic viscosities, the η AUS model demonstrated the best correlating capabilities with GOASPD σ(%) of 0.48, while the HND model performed the poorest with GOASPD σ(%) at 3.8. For the kinematic viscosities, ν in both the MAC3 and MAC4 models yielded satisfactory results with GOASPD σ(%) as < 1.0 %.

In this study, we solve fractional order PDEs with free parameters that regulate wave motion in a low-pass electrical transmission line equation (LPET) using the unified technique. To convert the governing equation into an ordinary differential equation (ODE), we have used a simple linear fractional transformation. The unified technique can therefore be used to find various single and extracting wave solutions to the equation of attention. Using Maple-18 software, all of the established solutions are validated and verified. By selecting appropriate values for the fractional order and free parameters, the two dimensional (2D) and three dimensional (3D) profiles of some of the assimilation solutions demonstrating kink, singular kink, cross kink, bright-dark kink, lump type kink, anti-kink, dark-anti kink, singular periodic, periodic, singular soliton solutions are displayed. The effect of free parameters and fractionality on the dynamical properties of the precise and exploited solutions are graphically illustrated and discussed in detail. We have also compared our results to those found in the literature review. Wherever possible, the judgment demonstrates no significant differences between our realized and published solutions. The results of this investigation show that the adopting technique is both productive and powerful in extracting wave solutions to nonlinear evolution problems that arise in the areas of applied mathematics, mathematical physics, and engineering.

The motive of this research work is to unravel the mysteries of nature through fractional-order partial differential equations (PDEs). Here, we focus on two important fractional order nonlinear PDEs, namely the fractional order (4+1)-dimensional Fokas equation, which is used to give the model of many physical phenomena and dynamical processes, and the other one is the fractional order (2+1)-dimensional breaking soliton equation which is used to analyze the nonlinear problems like optical fiber communications, ocean engineering, etc. Recently, it has been an essential topic to extract the new soliton solutions which are used to investigate the hidden physical conditions of the nonlinear fractional PDEs. So, it is essential to solve those nonlinear fractional PDEs which have a physical impact in the fields of science and modern engineering. In our investigation, we attempt to provide nonlinear wave propagation patterns and investigate the equations, as mentioned earlier, through a computational method. A computing operating software called Mathematica has been applied to get a clear visualization of our gained outcomes, and we ascertain such types of shapes as the bell shape soliton, the anti-bell shape soliton, the singular bell shape soliton, the periodic solution, and the singular periodic solution. Our obtained results can keep an indispensable role in explaining various physical phenomena of nature shortly, and the applied method is the very cogent, efficient, and interesting to extract such types of solutions. Since we extract abundant solutions of these models, so we hope that this article is the best applications of mention method.

Given the extreme need for vaccines to flatten the curve of COVID-19 cases and deaths worldwide, many researchers, some governments and donor agencies have initiated a good number of vaccine development projects. COVID-19 vaccines have been approved for use in mass population immunization programmes in a much shorter time than is usual for new pharmaceuticals. This does not indicate cut corners or skipped safety trials, however. It is vitally important to explain the why and how of expedited vaccine development to a potentially sceptical public in order to head-off potential issues with vaccine hesitancy. This is particularly important in the case of elderly patients with comorbidities, as such people may be under-represented in clinical trials, raising concerns over whether or not the vaccine is safe for them. In particular, care needs to be taken regarding media reporting of deaths that occur in the weeks following vaccination of the very elderly and frail. Coincidental deaths amongst such demographics can be misunderstood and misreported as vaccine-related: it is important for medical sources to rule out such links and for public health communication to ensure that this knowledge is incorporated into programmes to help build vaccine confidence. Detailed planning for vaccination roll-out to this group is necessary to ensure the safety of those most at risk.

Abstract Being a deltaic country and for its geographic location, Bangladesh faces devastating damages every year. In a new global index, Bangladesh has been ranked 7th among the countries most affected by extreme weather events in 20 years since 1998. The ability of a community to recover from a disaster is very much associated with strong social connections. For this research, both secondary and primary data sources have been considered. Socio‐demographic characteristics have been identified from a community‐based general questionnaire and BBS. Also, a newly developed integrated method has been used to measure the social capital of the community. Several statistical methods were used to analyse the data, such as factor analysis (PCA), ROC curve analysis and several GIS techniques, throughout the research. Results show that significant socio‐demographic variables help to develop a specific type of social capital. Consequently, social capital indirectly works as a key for recovering from any disaster impact and could build resilience to hazards.

Abstract Background and Aims Breast cancer is a leading cause of mortality in Bangladesh. An early‐stage screening is the best way to reduce both the morbidity and mortality burden of breast cancer. The study evaluated awareness, practice, and perceived barriers toward breast cancer screening in Bangladesh. Methods A community‐based cross‐sectional study was conducted from October 2021 to December 2022 in Chattogram, Bangladesh, where 869 women (18 years or above) were randomly selected in this study. Results Among 869 participants, 47.3% of women were recruited from urban areas and 52.7% participated from rural areas. Only 32.68% of respondents (urban vs. rural: 44.28% vs. 22.27%) were aware of breast self‐examination (BSE) and 52.47% of respondents (urban vs. rural: 63.75% vs. 42.36%) had ever heard Clinical Breast Examination (CBE), respectively. Among the respondents, 27.73% (urban vs. rural: 40.15% vs. 16.59%) performed their BSE, and only 14.61% of respondents (urban vs. rural: 21.90% vs. 8.08%) had ever visited for CBE. Women residing in rural areas were approximately three times (AOR: 0.36 [95% CI: 0.25–0.52], AOR: 0.37 [95% CI: 0.23–0.58]) less likely to perform BSE and CBE, respectively, than urban dwellers. We found that higher‐educated women tend to do more BSE and CBE than women with low levels of education. Perceptions of having “no symptoms” and being “risk‐free” are leading barriers to breast screening among women. Conclusion Poor awareness and practice were observed in screening among the urban and rural women in Bangladesh. Urban area dwellers had comparatively better understanding and practice than rural dwellers. We think extending health education and health promotion activities toward breast cancer screening is essential in this region.

Background Global prevalence of neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. Methods In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. Results From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from −11.7 to −10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Conclusion Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

The frequency of landslides and related economic and environmental damage has increased in recent decades across the hilly areas of the world, no exception is Bangladesh. Considering the first step in landslide disaster management, different methods have been applied but no methods found as best one. As a result, landslide assessment using different methods in different geographical regions has significant importance. The research aims to prepare and evaluate landslide susceptibility maps (LSMs) of the Chattogram district using three machine learning algorithms of Logistic Regression (LR), Random forest (RF) and Decision and Regression Tree (DRT). Sixteen landslide conditioning factors were determined considering topographic, hydro-climatic, geologic and anthropogenic influence. The landslide inventory database (255 locations) was randomly divided into training (80 %) and testing (20 %) sets. The LSMs showed that almost 9–12 % of areas of the Chattogram district are highly susceptible to landslides. The highly susceptible zones cover the Chattogram district's hill ranges where active morphological processes (erosion and denudation) are dominant. The ROC values for training data were 0.943, 0.917 and 0.947 and testing data were 0.963, 0.934 and 0.905 for LR, RF and DRT models, respectively. The accuracy is higher than the previous research in comparison to the extent of the study area and the size of the inventory. Among the models, LR showed the highest prediction rate and DRT showed the highest success rate. According to susceptibility zones, DRT is the more realistic model followed by LR. The maps can be applied at the local scale for landslide hazard management.

Background: The COVID-19 pandemic enhances mental health burden worldwide as well as people experiencing several psychiatric problems (e.g., Post-Traumatic Stress Disorder) due to its intensive consequences. Therefore, this study aimed to envisage the factors associated with PTSD symptoms among university students in Bangladesh after living with COVID-19 outbreak for a year. Methods: An online cross-sectional survey was conducted among 2100 Bangladeshi university students aged ≥ 18 years from April 29 to May 15, 2021. The questionnaire comprised socio-demographics along with COVID-19 related physical and psychosocial factors (CRPPF), preventive response to psychological stress, and PTSD Checklist for DSM-5 (PCL-5). Descriptive statistics and logistic regression were performed for statistical analysis. Results: About 56.76% of the students had provisional PTSD. Female students were more likely to suffer from PTSD symptoms than male students (AOR= 1.68; 95% CI: 1.35 to 2.08). Being a victim of social media bullying (AOR= 1.57; 95% CI: 1.17 to 2.11), having relationship problems (AOR= 2.25; 95% CI: 1.82 to 2.79), and feeling own self as a burden to their families (AOR= 2.84; 95% CI: 2.27 to 3.56) had a significant association with a higher possibility of suffering from PTSD symptoms in this outbreak. Conclusion: University students experienced PTSD symptoms during the COVID-19 pandemic which call for detailed in-depth explorations, confirmatory clinical diagnosis, and adoption of preventive strategies to minimize their suffering amid this pandemic.

Abstract Previously, we observed curcumin improves aging-associated memory impairment in d-galactose (D-gal) and normal-aged (NA) mice. Evidence showed that multiple agents can be used in managing aging-induced memory dysfunction, drawn by the contribution of several pathways. Curcumin and Epigallocatechin 3 gallate (EGCG) combination substantially reduced the oxidative stress that commonly mediates aging. This study examined the combined effect of EGCG and curcumin on memory improvement in two recognized models, D-gal and normal-aged (NA) mice. The co-administration of EGCG and curcumin significantly (p

Abstract Liver disease is a serious health problem affecting people worldwide at an alarming rate. The present study aimed to investigate the protective effects of Ganoderma lucidum against CCl4-induced liver toxicity in rats. The experimental Long Evans rats were divided into five groups, of which four groups were treated with carbon tetrachloride (CCl4). Among the CCl4 treated groups, one of the groups was treated with silymarin and two of them with ethanolic extract of G. lucidum at 100 and 200 mg/Kg body weight. The oxidative stress parameters and endogenous antioxidant enzyme concentrations were assessed by biochemical tests. Liver enzymes ALT, AST, and ALP were determined spectrophotometrically. Histopathological examinations were carried out to assess hepatic tissue damage and fibrosis. Reverse transcription PCR (RT-PCR) was performed to determine the expression of IL-1β, IL-6, IL-10, TNF-α, and TGF-β genes. Gas Chromatography-Mass Spectroscopy (GC–MS) analysis revealed that G. lucidum is rich in several phytochemicals including 6-Octadecanoic acid (55.81%), l-( +)-Ascorbic acid 2,6-dihexadecanoate (18.72%), Cis-11-Eicosenamide (5.76%), and Octadecanoic acid (5.26%). Treatment with the G. lucidum extract reduced the elevated ALT, AST, ALP levels, and cellular oxidative stress markers and increased the endogenous antioxidant levels. Histopathology observations revealed that the inflammation, infiltration of immune cells, and aberration of collagen fibers in the hepatocytes were altered by the G. lucidum treatment. The increased expression of inflammatory cytokines TNF-α, TGF-β, IL-1 β, and IL-6 were markedly suppressed by G. lucidum extract treatment. G. lucidum also prevented the suppression of protective IL-10 expression by CCl4. This study strongly suggests that G. lucidum extract possesses significant hepatoprotective activity as evidenced by reduced oxidative stress and inflammation mediated by suppression in inflammatory cytokine expression and increased protective IL-10 cytokine expression.