University of Asia Pacific

Sikder P., Rahman M.T., Bakibillah A.S.

Visible Light Communication (VLC) has the potential to advance Intelligent Transportation Systems (ITS). This study explores the current advancements of VLC in ITS applications that may enhance traffic flow, road safety, and vehicular communication performance. The potential, benefits, and current research trends of VLC in ITS applications are discussed first. Then, the state-of-the-art VLC technologies including overall concept, IEEE communication protocols, hybrid VLC systems, and software-defined adaptive MIMO VLC systems, are discussed. We investigated different potential applications of VLC in ITS, such as signalized intersection and ramp metering control, collision warning and avoidance, vehicle localization and detection, and vehicle platooning using vehicle–vehicle (V2V), infrastructure–vehicle (I2V), and vehicle–everything (V2X) communications. Besides, VLC faces several challenges in ITS applications, and these concerns, e.g., environmental issues, communication range issues, standards and infrastructure integration issues, light conditions and integration issues are discussed. Finally, this paper discusses various advanced techniques to enhance VLC performance in ITS applications, such as machine learning-based channel estimation, adaptive beamforming, robust modulation schemes, and hybrid VLC integration. With this review, the authors aim to inform academics, engineers, and policymakers about the status and challenges of VLC in ITS. It is expected that, by applying VLC in ITS, mobility will be safer, more efficient, and sustainable.

Fatemi M.N., Rahman T., Shawpnil S.M., Ahmed I.U.

Hassan A., Ahmad G., Shafiullah M., Islam A., Alam M.S.

Rafi M.A., Rodrigues G.N., Mir M.N., Bhuiyan M.S., Mridha M.F., Islam M.R., Watanobe Y.

Alam S., Chowdhury N.R., Hossain M.A., Richi F.T., Emon N.U., Mohammad M., Ahmed N., Taher M.A.

ABSTRACTEthnomedicinal plants in Asia offer a promising, low‐side‐effect alternative to synthetic drugs for treating fungal infections, one of the most widespread communicable diseases caused by pathogenic fungi. Despite being underexplored, the region's rich plant diversity holds the potential for developing effective antifungal drugs. Research is increasingly focused on bioactive compounds from these plants, which show strong antifungal properties and may serve as leads for new drug development. This comprehensive review included 257 articles which are peer‐reviewed and written in english language with reported phytochemicals exerting antifungal potentials. In this review, we have discussed twenty‐seven (27) Asian medicinal plants that contain sixty‐seven (67) responsible phytochemicals deciphering promising antifungal action. This finding revealed that Asian plant diversity can be helpful in treating fungal invasion against several fungal species. Inhibition and reduction of mycelial growth and zoospore germination, fungistatic and fungicidal activities, and inhibition of ergosterol biosynthesis are some common mechanisms reported in this review. Thus, this Asian plant diversity can provide a ray of hope as a modern therapeutic approach to bypass antimicrobial resistance issues noticed in recent days. Further research is still recommended to ascertain their exact mode of action, required dose, and safety and efficacy profile.

Moin A.T., Ullah M.A., Nipa J.F., Rahman M.S., Emran A., Islam M.M., Das S., Arian T.A., Elahi M.M., Akter M., Rahman U.S., Halder A., Saikat S., Hosen M.J.

IntroductionIdiopathic pulmonary fibrosis (IPF) is a rare but debilitating lung disease characterized by excessive fibrotic tissue accumulation, primarily affecting individuals over 50 years of age. Early diagnosis is challenging, and without intervention, the prognosis remains poor. Understanding the molecular mechanisms underlying IPF pathogenesis is crucial for identifying diagnostic markers and therapeutic targets.MethodsWe analyzed transcriptomic data from lung tissues of IPF patients using two independent datasets. Differentially expressed genes (DEGs) were identified, and their functional roles were assessed through pathway enrichment and tissue-specific expression analysis. Protein-protein interaction (PPI) networks and co-expression modules were constructed to identify hub genes and their associations with disease severity. Machine learning approaches were applied to identify genes capable of differentiating IPF patients from healthy individuals. Regulatory signatures, including transcription factor and microRNA interactions, were also explored, alongside the identification of potential drug targets.ResultsA total of 275 and 167 DEGs were identified across two datasets, with 67 DEGs common to both. These genes exhibited distinct expression patterns across tissues and were associated with pathways such as extracellular matrix organization, collagen fibril formation, and cell adhesion. Co-expression analysis revealed DEG modules correlated with varying IPF severity phenotypes. Machine learning analysis pinpointed a subset of genes with high discriminatory power between IPF and healthy individuals. PPI network analysis identified hub proteins involved in key biological processes, while functional enrichment reinforced their roles in extracellular matrix regulation. Regulatory analysis highlighted interactions with transcription factors and microRNAs, suggesting potential mechanisms driving IPF pathogenesis. Potential drug targets among the DEGs were also identified.DiscussionThis study provides a comprehensive transcriptomic overview of IPF, uncovering DEGs, hub proteins, and regulatory signatures implicated in disease progression. Validation in independent datasets confirmed the relevance of these findings. The insights gained here lay the groundwork for developing diagnostic tools and novel therapeutic strategies for IPF.

Alam G.M., Arfin Tanim S., Sarker S.K., Watanobe Y., Islam R., Mridha M.F., Nur K.

The transportation industry contributes significantly to climate change through carbon dioxide ( $$\hbox {CO}_{2}$$ ) emissions, intensifying global warming and leading to more frequent and severe weather phenomena such as flooding, drought, heat waves, glacier melting, and rising sea levels. This study proposes a comprehensive approach for predicting $$\hbox {CO}_{2}$$ emissions from vehicles using deep learning techniques enhanced by eXplainable Artificial Intelligence (XAI) methods. Utilizing a dataset from the Canadian government’s official open data portal, we explored the impact of various vehicle attributes on $$\hbox {CO}_{2}$$ emissions. Our analysis reveals that not only do high-performance engines emit more pollutants, but fuel consumption under both city and highway conditions also contributes significantly to higher emissions. We identified skewed distributions in the number of vehicles produced by different manufacturers and trends in fuel consumption across fuel types. This study used deep learning techniques to construct a CO2 emission prediction model, specifically a light multilayer perceptron (MLP) architecture called CarbonMLP. The proposed model was optimized by hyperparameter tuning and achieved excellent performance metrics, such as a high R-squared value of 0.9938 and a low Mean Squared Error (MSE) of 0.0002. This study employs XAI approaches, particularly SHapley Additive exPlanations (SHAP), to improve the model interpretation ability and provide information about the importance of features. The findings of this study show that the proposed methodology accurately predicts CO2 emissions from vehicles. Additionally, the analysis suggests areas for further research, such as increasing the dataset, integrating additional pollutants, improving interpretability, and investigating real-world applications. Overall, this study contributes to the design of effective strategies for reducing vehicle CO2 emissions and promoting environmental sustainability.

Squires A., Dutton H.J., Casales‐Hernandez M.G., Rodriguez López J.I., Jimenez‐Sanchez J., Saldarriaga‐Dixon P., Bernal Cespedes C., Flores Y., Arteaga Cordova M.I., Castillo G., Loza Sosa J.M., Garcia J., Ramirez T., González ‐ Nahuelquin C., Amaya T., et. al.

AbstractAimTo describe the self‐reported mental health of nurses from 35 countries who worked during the COVID‐19 pandemic.BackgroundThere is little occupationally specific data about nurses' mental health worldwide. Studies have documented the impact on nurses’ mental health of the COVID‐19 pandemic, but few have baseline referents.MethodsA descriptive, cross‐sectional design structured the study. Data reflect a convenience sample of 9,387 participants who completed the opt‐in survey between July 31, 2022, and October 31, 2023. Descriptive statistics were run to analyze the following variables associated with mental health: Self‐reports of mental health symptoms, burnout, personal losses during the pandemic, access to mental health services, and self‐care practices used to cope with pandemic‐related stressors. Reporting of this study was steered by the STROBE guideline for quantitative studies.ResultsAnxiety or depression occurred at rates ranging from 23%–61%, with country‐specific trends in reporting observed. Approximately 18% of the sample reported experiencing some symptoms of burnout. The majority of nurses’ employers did not provide mental health support in the workplace. Most reported more frequently engaging with self‐care practices compared with before the pandemic. Notably, 20% of nurses suffered the loss of a family member, 35% lost a friend, and 34% a coworker due to COVID‐19. Nearly half (48%) reported experiencing public aggression due to their identity as a nurse.ConclusionsThe data obtained establish a basis for understanding the specific mental health needs of the nursing workforce globally, highlighting key areas for service development.Implications for nursing policyHealthcare organizations and governmental bodies need to develop targeted mental health support programs that are readily accessible to nurses to foster a resilient nursing workforce.

Rahaman M., Islam M.F., Moushumy Z.M., Hossain M.M., Islam M.N., Hasan M., Rahman M.A., Tanjila N.A., Hasnat M.A.

The pursuit of electrochemical carbon dioxide reduction reaction (CO2RR) as a means of energy generation and mitigation of global warming is of considerable interest. In this study, a novel RuO2-incorporated SnO2-fabricated glassy carbon electrode (GCE) with a Nafion binder was used for the electrochemical reduction of CO2 in an aqueous alkaline imidazole medium. The electrode fabrication process involved the drop-casting method, where RuO2.SnO2 was incorporated onto the surface of the GCE. Electrochemical studies demonstrated that the GCE-RuO2.SnO2 electrode facilitated CO2 reduction at −0.58 V vs. the reversible hydrogen electrode (RHE) via a diffusion-controlled pathway with the transfer of two electrons. Importantly, the first electron transfer step was identified as the rate-determining step (RDS). A Tafel slope of 144 mV dec−1 confirmed the association of two-electron transfer kinetics with CO2RR. Moreover, the standard rate constant (ko) and formal potential (E°′) were evaluated as 2.89 × 10−5 cm s−1 and 0.0998 V vs. RHE, respectively. Kinetic investigations also reveal that the deprotonation and electron release steps took place simultaneously in the CO2RR. Based on the reported results, the GCE-RuO2.SnO2 electrode could be a promising candidate for CO2 reduction, applicable in renewable energy generation.

Toma F.M., Kalam K.T., Haque M.A., Reza S., Akter R., Islam M.S., Islam M.R., Nahar Z.

Background Epidemiological research suggests that altered levels of cytokine are associated with pathophysiology and the development of major depressive disorder (MDD). Based on earlier study, IL-1β rs16944 and rs1143627 polymorphisms may increase the risk of depression. Here, we aimed to evaluate the correlation between these polymorphisms and MDD susceptibility among the population in Bangladesh. Methods Blood samples were collected from 100 MDD patients and 70 matched controls. Study participants were evaluated by DSM-5 criteria and PCR-RFLP method were applied for genotyping. Results The IL1β rs1143627 and rs16944 polymorphisms were found to have a significant association with the risk of MDD. In case of rs1143627 CT heterozygous genotype (OR = 2.22, 95% CI = 1.08–4.55, p-value = 0.029) and combined CT+TT (OR = 2.35, 95% CI = 1.15–4.79, p-value = 0.019) genotype was strongly associated with the increased risk of MDD in comparison to CC common genotype. Moreover, the over-dominant model indicated a 2.15-fold higher risk for MDD development (OR = 2.15, 95% CI = 1.05–4.40, p-value = 0.036). On the other hand, the IL1β rs16944 polymorphisms revealed that the TC+CC combined genotype in the dominant model showed a 2.06-fold increased risk for MDD development compared to the TT common homozygote (OR = 2.06, 95% CI = 1.06–3.99, p-value = 0.032). Conclusion Studies suggests that IL1β rs16944 and rs1143627 polymorphisms are associated with an increased risk of MDD. These findings will provide us with valuable insights into the pathophysiology of MDD.

Fatemi M.N., Rahman T., Shawpnil S.M., Ahmed I.U.

ABSTRACT Due to the rapid urbanization and expansion of cities, many urban waters, such as canals and streams, have disappeared from the surface in metropolitan areas like Dhaka. Identifying the potential socioeconomic and ecological value of these long-lost urban waters, particularly to ensure urban resilience, efforts to restore these streams are being emphasized as a prevalent practice in green-blue infrastructure design. The Begunbari Canal was strategically interconnected to the eastern fringe, central, and western parts of Dhaka and served as a crucial outlet for drainage and stormwater, making it geographically and environmentally vital for the city. This study intends to restore the Begunbari Canal of Central Dhaka by de-culverting it and to assess the restoration criteria for this particular ‘canal daylighting’ initiative. It has been conducted as a mixed-method research approach through historical and contextual analysis, map regression, thematic analysis, experts' opinions, transect walks, and photographic documentation to explore the criteria and possibilities for resurfacing the Begunbari Canal. Findings reveal the possibilities of resurrecting the forgotten presence of this buried canal, indicating a set of guidelines for its resurfacing. These insights will benefit policymakers, urban planners, urban designers, and local citizens to regenerate a green-blue network for interconnectivity and communication.

Samadd M.A., Patwary F.T., Islam M.M., Munia A.T., Sikdar K.M., Sarkar M.R.

ABSTRACTBackground and AimsDrug‐drug interactions (DDIs) are a significant health issue that may adversely affect the health and well‐being of patients. This study assesses and compares potential DDI (pDDI) patterns, severity, and associated risk factors in government and private hospitals in Dhaka, Bangladesh.MethodsA total of 188 and 206 prescriptions were collected from various government and private hospitals' outdoor departments, respectively, by capturing pictures of the prescriptions. Bivariate analyses were performed through STATA 15. MedScape drug interaction checker was applied to identify pDDIs, while their consequences were obtained from DrugBank and MedScape.ResultsPrivate hospitals had more pDDIs containing prescriptions than government hospitals (62.62% and 57.97%, respectively). The mean pDDIs cases were 3.29 in the private hospitals, while at government hospitals they were 3.02. Among the detected pDDIs, pharmacodynamic pDDIs were predominat, accounting for 63.32% and 66.23% of total events in government and private hospitals, respectively. Severity‐wise, both types of hospitals had almost equal amounts of serious (10.34% vs. 9.18%), moderate (68.96% vs. 59.61%), and minor (20.06% vs. 21.79%) pDDIs. Polypharmacy was crucial in pDDI cases, responsible for 70.21% and 81.83% of pDDIs in government and private hospitals, respectively. Multiple comorbidities with pDDIs were more common in private hospitals (24.46% vs. 18.93%), while government hospitals displayed a higher frequency of pDDIs with one comorbidity (24.75% vs. 17.55%). Non‐mention of comorbidities was correlated with both types of hospitals (p ≤ 0.01) in pDDIs cases. Furthermore, considerable amounts of pDDIs in prescription error categories were detected. Both types of hospitals had a prevalence of antihypertensive, antidiabetic, psychotic, and antiplatelet‐related pDDIs.ConclusionThe two kinds of hospitals exhibited similar pDDI patterns, while their associations were random with the risk variables. When prescribing pharmacokinetics and pharmacodynamics pDDIs, physicians should evaluate the risk‐benefit ratio.

Deb Nath U.K., Sarma S.

Precise assessment of building components’ exposure to driving rain is imperative for enhancing building durability, safeguarding occupant health, and mitigating economic and environmental costs. In this study, Annual Driving Rain Indices (aDRI) have been estimated for Bangladesh’s coastal districts using meteorological data of various temporal resolutions (i.e., daily, monthly and annual, yielding daDRI, maDRI and aaDRI, respectively) and corresponding driving rain maps, illustrating buildings’ exposure levels to driving rain, have been produced. Correlations between driving rain indices (i.e., daDRI – maDRI, daDRI – aaDRI, and maDRI—aaDRI) have been established to facilitate the daDRI estimation for locations lacking daily data. Further analyses have been conducted to observe the temporal trend of daDRI, rainfall and wind speed over years, to explore the directional distribution of driving rain exposure to buildings, and to estimate the wind-driven rain (WDR) load on building façades with various orientations using the ISO semi-empirical model. Results show that the entire coastal area of Bangladesh (and hence the buildings in this region) is susceptible to significant amount of driving rain, even while using coarser-resolution data which has been found to underestimate driving rain amounts. The daDRI, rainfall and wind speed trends indicate the direct impact of increasing rainfall on the rising driving rain index values. The relationships between different driving rain indices suggest the dominant influence of prevailing rainfall characteristics, rather than geographic location, on driving rain exposure. Estimates of WDR loads on building façades have indicated that the south-facing façades of coastal buildings in Bangladesh are the most susceptible to high levels of such loads.

Sami M.R., Rani N.A., Elahi M.M., Hossain M.S., Al Mueid M.A., Rahim Z., Patil R.B., Moin A.T., Bithi I.J., Nahar S., Konika I.J., Roy S., Preya J.A., Ahmed J.

Cryptococcosis is a lethal mycosis instigated by the pathogenic species Cryptococcus neoformans and Cryptococcus gattii, primarily affects the lungs, manifesting as pneumonia, and the brain, where it presents as meningitis. Mortality rate could reach 100% if infections remain untreated in cryptococcal meningitis. Treatment options for cryptococcosis are limited and and there are no licensed vaccines clinically available to treat or prevent cryptococcosis. Our study utilizes an integrated bioinformatics approaches to develop a polyvalent multiepitope subunit vaccine focusing on the key virulent proteins Heat shock transcription factor and Chaperone DnaK of both C. neoformans and C. gatti. Then in silico analysis was done to predict highly antigenic epitopes by assessing antigenicity, transmembrane topology screening, allergenecity, toxicity, and molecular docking approaches. Following this analysis, we designed two vaccine constructs integrating a compatible adjuvant and suitable linkers. These constructs exhibited notable characteristics including high antigenicity, non-toxicity, solubility, stability, and compatibility with Toll-like receptors (TLRs). The interaction between both vaccine constructs and TLR2, TLR3, and TLR9 was assessed through molecular docking analysis. Molecular dynamics simulations and MM-PBSA calculations suggest the substantial stabilizing property and binding affinity of Vaccine Construct V1 against TLR9. Both the vaccines revealed to have a higher number of interchain hydrogen bond with TLR9. These findings serve as a crucial stepping stone towards a comprehensive solution for combating cryptococcus infections induced by both C. neoformans and C. gattii. Further validation through in vivo studies is crucial to confirm the effectiveness and potential of the vaccine to curb the spread of cryptococcosis. Subsequent validation through in vivo studies is paramount to confirm the effectiveness and potential of the vaccine in reducing the spread of cryptococcosis.

Urmi T.J., Islam M.R.

ABSTRACTBackground and AimIn 2022, the monkeypox (mpox) outbreak was declared a public health emergency of international concern. The emergence of a new strain in the Democratic Republic of the Congo and its identification with neighboring countries led to the declaration of a public health emergency in 2024. The objective is to focus on the recent outbreak that led to its declaration as a Public Health Emergency of International Concern, assess the significant global public health threat posed by the newly identified class, and explore effective strategies to address this situation.MethodsThe present review searched information from databases (PubMed and Scopus), WHO, and the European Centre for Disease Prevention and Control. The search methods followed database‐specific criteria. Key terms included mpox, prevalence, public health emergency, treatment, new variant, prevention, and strategy. We reviewed and extracted information from the relevant literature.ResultsMpox has been endemic in the Democratic Republic of the Congo for over a decade, with a consistent annual rise in reported cases. In August 2024, at least 13 African countries have confirmed 2,863 cases and 517 fatalities. The recent emergence and transmission of a new strain, which appears to be predominantly spreading through sexual networks, along with its identification in neighboring countries, raises significant concerns for public health.ConclusionThe emergence of the new clade of mpox represents a critical public health challenge that necessitates immediate and coordinated global response efforts. By addressing the current outbreak comprehensively, we can mitigate its impact and safeguard public health across affected regions.