Dye-sensitized solar cells (DSSCs) have emerged as a promising alternative to conventional photovoltaic technologies due to their low cost, high efficiency, and potential for flexible and transparent design. Over the past few years, there have been attempts to make this technology much more efficient. The utilization of polyethylene oxide (PEO)-carbon nanomaterial composites in DSSCs has shown much interest due to improved ionic conductivity, photochemical, and photovoltaic properties. Furthermore, being a crucial component of DSSCs, gel polymer electrolytes (GPEs) have gained significant research interest over solid-state and liquid electrolytes due to several advantages, including reduced device degradation and costs with improved stability. Here we compare the photochemical and photovoltaic performances of DSSCs fabricated with GPEs composed of PEO-based nanocomposites, including carbon nanotubes, carbon black, and Graphene and discuss the evaluation of their effectiveness as nanofillers for DSSCs. The utilization of these PEO-nanocomposite GPEs has been observed to show potential changes in the overall performance of DSSCs, which could significantly impact future research and the outlook in the field of photovoltaic technologies.
Artificial intelligence (AI) in renewable energy technologies plays a crucial part due to its modeling and performance forecasting. Therefore, a novel AI-based evolving generative adversarial Fuzzy network (EGAFN) has been presented in this paper as a forecasting tool for the efficiency analysis of renewable solar energy for four distinct regions. The power ratings from environmental parameters and solar panels were monitored and recorded for a year. The data pre-processing is primarily applied to improve the system's function using a data filter. Furthermore, the data's energy estimation accuracy is enhanced using feature extraction and selection by a multi-objective lionized manta-ray foraging optimizer (MLMRFO). Finally, the hyperparameters of the EGAFN method are optimized by multi-objective optimization. The proposed technique aims to enhance the energy efficiency of PV systems for solar power production forecasting using an optimized multi-objective algorithm. The findings show that the suggested technique's prediction performance is better than earlier methods. Thus, the proposed methodology can assist in increasing energy efficiency and making better use of renewable energy sources.
Objective This study assessed the reliability and validity of the Stress and Anxiety to Viral Epidemics–9 items (SAVE-9) and Stress and Anxiety to Viral Epidemics–6 items (SAVE-6) scales for measuring viral anxiety among firefighters during the coronavirus disease-2019 pandemic. Methods An online survey was conducted among 304 firefighters assigned in Gyeonggi-do. The SAVE-9 scale, initially developed for healthcare workers, was adapted for firefighters. We compared it with the SAVE-6 scale designed for the general population among the firefighters sample. The confirmatory factor analysis (CFA) was conducted to explore the factor structure of both scales. Internal consistency reliability was checked using Cronbach’s alpha and McDonald’s omega. Convergent validity was assessed in accordance with the Patient Health Questionnaire–9 and Generalized Anxiety Disorder–7 scales. Results The SAVE-9 scale demonstrated a Cronbach alpha of 0.880, while the SAVE-6 scale yielded an alpha of 0.874. CFA indicated good model fits for both SAVE-9 and SAVE-6 scales among firefighters sample. The SAVE-9 and SAVE-6 comparably measures viral anxiety of firefighters. Conclusion Both of the SAVE-9 and SAVE-6 scales are reliable and valid instruments for assessing viral anxiety among firefighters during the pandemic.
Flood hazard mapping using GIS-based statistical model in vulnerable riparian regions of subtropical environment Abstract Floods are a recurrent natural calamity that presents substantial hazards to human lives and infrastructure. The study indicates that a significant proportion of the study area, specifically 27.05%, is classified as a moderate flood risk zone (FRZ), while 20.78% is designated as high or very high FRZ. The region's low and very low FRZ are classified at 52.17%. The GIS-based AHP model demonstrated exceptional predictive precision, achieving a score of 0.749 (74.90%) as determined by the AUC-ROC, a widely used statistical evaluation tool. The current study has identified areas with high FRZ in the affected CD blocks, which are situated in low-lying flood plains, regions with gentle slopes, high drainage density, high TWI, low NDVI, high MNDWI, areas with high population density, intensive agricultural land. The findings of this research offer significant perspectives for decision-makers, city planners, and emergency management agencies in devising efficient measures to mitigate flood risks.
Different solid materials are widely used in various constructions due to their availability and low cost. However, cracks or conversions in the structures can affect their stiffness and vibration signatures. This research aims to evaluate the load distribution, deformation, and the effects of the cracks on the natural frequencies and deformations of iron, steel, and titanium beams. A finite element-based model and COMSOL Multiphysics software were employed to measure and compare the frequencies and strengths of the beams. The results showed that the frequencies increased with the load, and titanium beams had the highest frequencies and deflections, while steel beams had the highest stress resistance. This frequency analysis can help to detect very small cracks (less than 0.05 mm) in the beams. The study concluded that steel is the most suitable material for construction due to its elasticity, availability, and low cost.
This research aims to investigate the future changes in summer monsoon rainfall and temperature in Bangladesh. The study revealed that INM-CM5-0 is the best model for projecting temperature, while BCC-CSM2-MR is the best model for projecting rainfall over Bangladesh. Using data from a large ensemble of 27 models from CMIP6, the study examined the rainfall and temperature change projections of Bangladesh during the 21 st century relative to the reference period (1981-2014) under SSP2-4.5 and SSP5-8.5. Under SSP2-4.5 and SSP5-8.5, the multi-model ensemble monsoon mean rainfall over Bangladesh will fluctuate between 40 and 260 mm and 100 and 900 mm, respectively. In most parts of the country's north, northeastern, and western regions, the projected changes in spatial patterns of monsoon rainfall indicate an increase in rainfall. The projected temperature indicated that Bangladesh's northwest and west-central areas could face the most significant rise in temperatures, surpassing 3.8°C under SSP5-8.5.
Arsenic contamination is a global health concern, primarily through contaminated groundwater and its entry into the food chain. The association between arsenic exposure and cardiovascular diseases (CVDs) is particularly alarming due to CVDs being the leading cause of death worldwide. Arsenic exposure has also been linked to changes in telomere length, mitochondrial DNA copy number (mtDNAcn), and deletion, further increasing the risk of CVDs. We aimed to determine whether arsenic exposure alters telomere length and mtDNAcn and deletion in a total of 50 CVD patients who underwent open heart surgery hailed from known arsenic-affected and unaffected areas in Bangladesh. Amount of arsenic was determined from the collected nails and cardiac tissues. Relative telomere length and mtDNAcn and deletion were quantified by qRT-PCR. The patients from arsenic-contaminated areas had higher average arsenic deposits in their fingers and toenails (P < 0.05) and higher cardiac tissue injury scores (P < 0.05). Moreover, approximately 1.5-fold shorter telomere length (P < 0.05, r = − 0.775), 1.2-fold decreased mtDNAcn (P < 0.05, r = − 0.797), and an 81-fold higher amount of mitochondrial DNA deletion (P < 0.05, r = 0.784) were observed in the patients who had higher arsenic deposition in their nails. Higher levels of arsenic exposure were found to be linked to shorter telomere length, decreased mtDNAcn, and increased mitochondrial DNA deletion in the patients from As-affected areas. It can also be anticipated that the correlation of arsenic exposure with telomere length, mtDNAcn, and deletion can be used as biomarkers for early diagnosis of arsenic-induced cardiovascular diseases.
Background: This study aimed to validate questionnaires on adherence to physical distancing and health beliefs about coronavirus disease 2019 (COVID-19) among patients with cancer and explore their interaction with depression or viral anxiety among them. Methods: Through an online survey, data from 154 cancer patients (female: 82.5%, breast cancer: 66.2%, current cancer treatment, presence: 65.6%) were collected from March to June 2022. The survey gathered responses to questionnaires on adherence to physical distancing, health beliefs about COVID-19, perceived social norms, Stress and Anxiety to Viral Epidemics-6 items, and Patient Health Questionnaire-2. Confirmatory factor analysis (CFA) for construct validity and structural equation model (SEM) were performed. Results: The CFA showed a good model fit for adherence to physical distancing (comparative fit index [CFI] = 1.000, Tucker-Lewis index [TLI] = 0.930, root-mean-square-error of approximation [RMSEA] = 0.000, and standardized root-mean-square residual [SRMR] = 0.050) and a satisfactory model fit for health beliefs about COVID-19 (CFI = 0.978, TLI = 0.971, RMSEA = 0.061, and SRMR = 0.089). Through SEM, we found that personal injunctive norms were the main mediators linking health beliefs with physical distancing in patients with cancer. Depression also mediated the effects of viral anxiety and perceived severity on physical distancing (χ² = 20.073, df = 15, P = 0.169; CFI = 0.984; RMSEA = 0.047). Conclusion: The questionnaires are reliable and valid. Patients with cancer may be able to adhere to physical distancing by addressing perceived severity, viral anxiety, perceived benefits, self-efficacy, perceived barriers, as well as personal injunctive norms.
Background: Here we investigated whether cold chain workers' insomnia, work-related stress, and viral anxiety contributed to their depression. Furthermore, we investigated the role of viral anxiety in mediating the association between work-related stress and depressive symptoms. Methods: All 200 invited cold chain workers voluntarily responded to an online survey. All were working at a market in Taiyuan, Shanxi Province, China, and responsible for testing nucleic acids in imported cold chain foods and disinfecting outer packaging at government request. We collected their demographic variables and rated their symptoms using the Stress and Anxiety to Viral Epidemics-6 Items (SAVE-6), Patient Health Questionnaire-9, Insomnia Severity Index (ISI), Perceived Stress Scale (PSS), and Maslach Burnout Inventory - General Survey (MBI-GS). Results: Cold chain workers' depression was significantly correlated with higher SAVE-6 (r = 0.450, P < 0.01), ISI (r = 0.603, P < 0.01), MBI-GS (r = 0.481, P < 0.01), and PSS (r = 0.390, P < 0.01) scores. SAVE-6 score was significantly correlated with ISI (r = 0.462, P < 0.01), MBI-GS (r = 0.305, P < 0.01), and PSS (r = 0.268, P < 0.01) scores. Linear regression revealed that their depression was predicted by SAVE-6 (β = 0.183, P = 0.003), ISI (β = 0.409, P < 0.001), and MBI-GS (β = 0.236, P = 0.002, adjusted R² = 0.440, F = 40.04, P < 0.001) scores. Mediation analysis showed that their burnout directly influenced their depression, while viral anxiety or insomnia severity mediated the influence of burnout on depression. Conclusion: The study showed that burnout was a direct cause of depression and that viral anxiety and insomnia severity mediated the relationship between burnout and depression.
Objectives: Mindfulness-based interventions are common in contemporary mental health practices. Hence, the assessment of mindfulness is necessary during those interventions, and the 39-item Five Facet Mindfulness Questionnaire (FFMQ) is one of the most frequently used tools. As there is a scarcity of mindfulness scales for Bangla-speaking people, we translated this questionnaire into Bangla and validated it with a Bangladeshi community sample. Method: We collected data from 532 Bangladeshi adults (mean age=30.22; SD=5.19), of which 390 were females and 142 were males. The participants completed FFMQ-Bangla, Mindfulness Attention Awareness Scale, Emotional Intelligence Scale, Depression Scale, and Openness and Neuroticism sub-scales of the Big Five Personality Inventory. Item response theory–based analysis evaluated the item quality of the Bangla FFMQ. Confrmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) assessed the scale’s structural validity. Results: Item response theory–based analysis discarded 10 items. Both CFA and ESEM supported the five-faceted model (CFA: CFI=0.94; TLI=0.94; ESEM: CFI=0.99; TLI=0.99) and indicated satisfactory reliability for the remaining 29-item scale (≥0.80). ESEM revealed two general components (self-regulated attention and orientation to experience) encompassing the five facets (CFI=0.99; TLI=0.93). All those facets exhibited positive correlations with the Mindfulness Attention Awareness Scale, Emotional Intelligence Scale, and the Openness trait and negative correlations with Depression and the Neuroticism trait, revealing the scale’s concurrent validity. Conclusions: Since the FFMQ-Bangla has exhibited satisfactory reliability and structural and concurrent validity, we recommend that researchers and mental health practitioners use this scale to assess mindfulness among Bangla-speaking people. Preregistration: This study is not preregistered
Kratom (Mitragyna speciosa Korth. Havil) has been considered a narcotic drug for years, barred by the law in many parts of the world, while extensive research over the past few decades proves its several beneficial effects, some of which are still in ambiguity. In many countries, including Thailand, the indiscriminate use and abuse of kratom have led to the loss of life. Nonetheless, researchers have isolated almost fifty pure compounds from kratom, most of which are alkaloids. The most prevalent compounds, mitragynine and 7-hydroxy mitragynine, are reported to display agonist morphine-like effects on human μ-opioid receptors and antagonists at κ- and δ-opioid receptors with multimodal effects at other central receptors. Mitragynine is also credited to be one of the modulatory molecules for the Keap1-Nrf2 pathway and SOD, CAT, GST, and associated genes’ upregulatory cascades, leading it to play a pivotal role in neuroprotective actions while evidently causing neuronal disorders at high doses. Additionally, its anti-inflammatory, antioxidative, antibacterial, and gastroprotective effects are well-cited. In this context, this review focuses on the research gap to resolve ambiguities about the neuronal effects of kratom and demonstrate its prospects as a therapeutic target for neurological disorders associated with other pharmacological effects.
The human immunodeficiency virus (HIV) is the primary cause of acquired immune deficiency syndrome (AIDS), one of the deadliest pandemic diseases. Various mechanisms and procedures have been pursued to synthesise several anti-HIV agents, but due to the severe side effects and multidrug resistance spawning from the treatment of HIV/AIDS using highly active retroviral therapy (HAART), it has become imperative to design and synthesise novel anti-HIV agents. Literature has shown that natural sources, particularly the plant kingdom, can release important metabolites that have several biological, mechanistic and structural representations similar to chemically synthesised compounds. Certainly, compounds from natural and ethnomedicinal sources have proven to be effective in the management of HIV/AIDS with low toxicity, fewer side effects and affordability. From plants, fungi and bacteria, coumarin can be obtained, which is a secondary metabolite and is well known for its actions in different stages of the HIV replication cycle: protease, integrase and reverse transcriptase (RT) inhibition, cell membrane fusion and viral host attachment. These, among other reasons, are why coumarin moieties will be the basis of a good building block for the development of potent anti-HIV agents. This review aims to outline the synthetic pathways, structure-activity relationship (SAR) and POM analyses of coumarin hybrids with anti-HIV activity, detailing articles published between 2000 and 2023.
The Nipah virus (NiV) poses a pressing global threat to public health due to its high mortality rate, multiple modes of transmission, and lack of effective treatments. NiV glycoprotein G (NiV-G) emerges as a promising target for NiV drug discovery due to its essential role in viral entry and membrane fusion. Therefore, in this study we applied an integrated computational and biophysics approach to identify potential inhibitors of NiV-G within a curated dataset of Peruvian phytochemicals. Our virtual screening results indicated that these compounds could represent a natural source of potential NiV-G inhibitors with ∆G values ranging from -8 to -11 kcal/mol. Among them, Procyanidin B2, B3, B7, and C1 exhibited the highest binding affinities and formed the most molecular interactions with NiV-G. Molecular dynamics simulations revealed the induced-fit mechanism of NiV-G pocket interaction with these procyanidins, primarily driven by its hydrophobic nature. Non-equilibrium free energy calculations were employed to determine binding affinities, highlighting Procyanidin B3 and B2 as the ligands with the most substantial interactions. Overall, this work underscores the potential of Peruvian phytochemicals, particularly procyanidins B2, B3, B7, and C1, as lead compounds for developing anti-NiV drugs through an integrated computational biophysics approach.
One of the most important aspects of the ‘sub-tropical’ monsoon-influenced environment is the issue of ‘soil erosion’ and its related ‘land degradation’. On the other hand, the climate in this area has become quite extreme. According to this viewpoint, it is important to research a future ‘soil erosion’ scenario in front of the probable effects of climate change and land use change. For the objective of assessing the extent of soil erosion in this area, this study took into account both the USLE and the RUSLE. Compared to the USLE that has been validated, RUSLE has a comparatively greater quantitative efficiency. In RUSLE, the ‘very high’ (>20) and ‘high’ (15–20) ‘soil erosion’ zones tend to be associated with the ‘north-western, western, south-western, and southern’ regions of the river basin. The ‘soil erosion’ that will occur in the future has been estimated by taking into account the projected rainfall, land use and land cover (LULC). ‘Soil erosion’ has increased from the previous time to the projected time. Predicted R factor values for SSP 585 range from 399.92 to 493.72. In addition, a growing erosion tendency associated with increased shared socio-economic pathways (SSPs) has been found.
Aramid fabric/fiber (AF), which possesses outstanding comprehensive qualities such as low density, high specific strength, and high specific modulus, is widely used for dresses of defense applications. Different dyes and chemicals are required to give the specific coloration effect of AF. AF are relatively difficult to dye due to their very crystalline structure and remarkable compactness. The different techniques, including supercritical carbon dioxide, microwave irradiation, liquid ammonia, ultraviolet treatment, co-polymerization, high temperature, carrier method, and ozone treatment, have already been utilized for the dyeing of AF. Among the processes, some of them show excellent dyeing performances in color fastness to wash, rubbing, and light. The AF also frequently used in harsh environments and cannot be cleaned in a timely manner; bacteria that develop on their surface might pose a health concern, making AF with antibacterial properties are extremely desirable. There have been a number of antibacterial treatments for AF to develop protection against gram-positive and gram-negative bacteria. The in-situ treatment of AF using silver nanoparticles (AgNPs) showed a high level of antibacterial activity. However, there are no reviews that discuss the coloration and antibacterial activity of AF. Therefore, this review summarized the coloration and antibacterial activity of AF using different dyes and nanoparticles.
The effectiveness of plant-based therapies depends on precise botanical identification. However, tribal communities and practitioners sometimes misclassify medicinal plants due to a lack of scientific understanding. Plants cannot always be identified simply by morphology; the DNA-based approach uses a small segment of genomic DNA to authenticate medicinal plant species. Many tribal communities in Bangladesh have utilized plants for healing purposes for centuries. Therefore, this research used DNA sequences to identify Bangladeshi ethnomedicinal plants. DNA was extracted from the fresh leaves of eight important medicinal plants using the AddPrep Genomic DNA Extraction Kit and stored at − 20 °C. Three important loci (matK, rbcL and psbA-trnH) were amplified using PCR, and the sequences of these regions were analyzed for identification. rbcL and matK showed amplification success rates of 100% and 75% respectively, while for psbA-trnH the level was 50%, which subsequently led to the production of a total of 18 novel sequences. To validate the taxonomic identity of the samples, a MEGABLAST sequence comparison was performed, with nine species-level (50%) and nine genus-level (50%) identifications confirmed. The neighbor-joining method was used to construct four phylogenetic trees. The sequences obtained from the plant (leaf) samples and downloaded sequences from NCBI were employed, with the topologies of the trees being identical. Our findings demonstrate that partial genome sequencing is a viable way of identifying medicinal plants and closely related species utilizing the three plastid loci rbcL, matK and psbA-trnH, which are efficient and feasible DNA markers for plant authenticity.
MytiLec-1, the recombinant form of a mussel lectin from Mytillus galloprovincialis, was purified by affinity chromatography and showed the maximum hemagglutination activity at a temperature range of 10°C to 40°C and at pH 7.0 to 9.0. Denaturants like urea and acidic-guanidine inhibited its hemagglutination activity significantly. MytiLec-1 was found to be metal-independent though Ca2+ slightly increased the activity of chelated MytiLec-1. The lectin suppressed 65% growth of Pseudomonas aeruginosa (ATCC 47085) at 200 μg/ml and reduced the formation of biofilm (15% at 200 μg/ml). Comparing to Shigella sonnei (ATCC 29930), Shigella boydii (ATCC 231903) and Shigella dysenteriae (ATCC 238135), Bacillus cereus (ATCC 14579) was slightly more sensitive to MytiLec-1. At a concentration of 200 μg/disc and 100 μg/ml, MytiLec-1 prevented the growth of Aspergillus niger and agglutinated the spores of Aspergillus niger and Trichoderma reesei, respectively. Amino acid sequences, physicochemical properties and antimicrobial activities of MytiLec-1 were compared with three other lectins (CGL, MTL and MCL from Crenomytilus grayanus, Mytilus trossulas and Mytilus californianus, respectively) from the mytilectin family of bivalve mollusks. It reconfirms the function of these lectins to recognize pathogens and perform important roles in innate immune response of mussels.
Background: In dentistry, association between bruxism and individuals with autism spectrum disorders (ASD) and Down Syndrome (DS) is high. Bruxism is one of the most common oral and psychophysiological disorders, that is still an unsolved issue with limited data. Objectives: The purpose of this systematic review (SR) was to evaluate evidence about bruxism and its management in individuals with ASD and DS. Materials and methods: The researchers performed an electronic search using keywords on three databases, reference lists and complemented by manual searching from January 2000 to February 2023 to find out the relevant documents. An extensive literature review using the "Preferred Reporting Items for Systematic Review and Meta Analysis" method was carried out. PICO parameters were formulated, and studies risk of bias was evaluated using the JBI critical appraisal checklist tool for case reports. Results: Out of 527 documents, 8 case studies and one review paper were identified as final articles for data synthesis. The findings showed, bruxism was reduced for all the participants with ASD and DS after implementation of functional analysis or dental treatment. Conclusion: The current SR found that despite the positive results of all the studies, there was a lack of evidence due to a limited number of studies and only case studies were conducted through functional analysis and dental treatment. Novelty: This SR is the first study on bruxism treatments in individuals with ASD and DS that included all the available studies (n = 9) since last 23 years and the first study that specifically addresses the incorporation of case reports in a systemic review.
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4331, Chittagong, Bangladesh
Head of institution
Professor Dr. Shireen Akhter
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