Abasyn University

The global construction industry faces a crucial challenge reconciling economic growth with environmental sustainability, notably due to the significant environmental impact of cement production, particularly in countries like Pakistan. As the demand for cement grows, so does the carbon footprint and environmental degradation, necessitating the exploration of sustainable alternatives like sugarcane bagasse ash (SBA), a byproduct of sugarcane processing, to mitigate these issues while also addressing rising costs in concrete production. Embracing SBA offers a promising avenue to alleviate environmental concerns and enhance the sustainability of the construction sector. This study investigated the SBA properties and effectiveness as a viscosity modifying agent (VMA) in self-compacting concrete (SCC), examining varying SBA content effects on fresh and hardened SCC properties. The hydration and microstructure properties were evaluated by using X-ray diffraction (XRD), scanning electron microscopy (SEM), and mercury intrusion porosimetry (MIP) to investigate SBA-based SCC. The results indicate that SBA has the potential to enhance mechanical and microstructural properties by possibly increasing the formation of Calcium Silicate Hydrate (CSH) gel. Adding 5% SBA demonstrated favorable fresh properties while incorporating up to 15% SBA showed improvements in compressive strength. Overall, adding SBA to cement manufacturing during clinkerization can reduce environmental pollution and lower production costs.

Water pollution is a burning issue that can originate from both urbanization and industrialization. This study aimed to evaluate the industrial wastewater collected from Hayatabad Industrial Estate and to use indigenous bacteria, Pseudomonas aeruginosa and Enterobacter aerogenes for bioremediation. The water samples collected were analyzed for physicochemical parameters and microbial pollution. To analyze the pollution removal efficiency by indigenous bacterial species, a pot experiment was performed for 14 days. Before and after experiment, the water samples were analyzed for trace metal concentration by Atomic Absorption Spectroscopy. The biochemical and molecular analysis confirmed the presence of two bacterial species (P. aeruginosa and E. aerogenes). The industrial wastewater treated with these isolated bacterial species showed significantly decreased level of electrical conductivity (42.33–86.45%), dissolved oxygen (16.35–63.37%), biological oxygen demand (33.33–80.62%), chemical oxygen demand (00-83.52%), total suspended solids (00–80%), and total dissolved solids (0.00-54.93%). The P. aeruginosa removal efficiency for Cu, Cd, and Pb was ranging 77.58–82.35%, 19.67-50%, and 20.40–91.66%, respectively. Similarly, the E. aerogenes removed Cu, Cd, and Pb in the range of 47.05–60.61%, 54.55–62.29%, and 85.21–91.6%, respectively. Phytotoxicity results revealed that the wastewater treated with both P. aeruginosa and E. aerogenes gives better Triticum sp. % germination rate, leaf length, and root and shoot weight. The highest plant % germination was showed by treated P. aeruginosa in control (100%), followed by E. aerogenes in control (100%). The t- test analysis showed the concentration of trace metals (TM) in industrial wastewater was significantly reduced (p ≤ 0.05) by bacterio-remediation. The study concluded that both bacterial species are active in the removal of pollution and TM from the wastewater.

Vigna sesquipedalis is traditionally used for the treatment of various disorders including diabetes but without scientific rational. Therefore, the current study was designed to evaluate its anti-diabetic potential. Antioxidant activity was assessed through DPPH and ABTS radical scavenging assays, while α-glucosidase and α-amylase inhibitory activities for anti-diabetic potential. Based on in vitro results, acute toxicity tests were performed, followed by in vivo studies using streptozotocin-induced diabetic model in mice. The ethyl acetate fraction exhibited the highest antioxidant potential, followed by crude extract. The methanolic crude extract showed the strongest in vitro antidiabetic activity. It was also found to be non-toxic up to 2000 mg/kg body weight. In vivo, the crude extract significantly (P < 0.05) improved body weight and displayed significant anti-diabetic effects. Further analysis of liver glycogen, serum insulin, glycosylated hemoglobin, and histopathology supported the extract overall performance. The virtual screening results showed highest binding energy of the Cyanidin-3-0-G (Cyanidin) with the amylase, Daucosterol with the GLP1, and Psoralidin with the Glucosidase. Similarly, MD simulation of the top hits was performed to investigate the dynamic stability and results showed that the ligand–protein system remains stable for during the simulation. The thermodynamic stability of the system was assessed by performing the binding free energy calculation using MM-PBSA/GBSA. The results of the binding free energy calculations showed favorable binding energies ligand–protein system. In short, the results illustrated potential as a pharmaceutical drug for insulin-dependent diabetes mellitus.

This study explores the antidiabetic potential of bioactive compounds isolated from Juglans regia Linn. fruit endocarp fractions. The ethanolic extract was screened for α‐amylase inhibition, revealing the chloroform fraction as the most potent (18.45 ± 0.76%), followed by the n‐hexane fraction (12.65 ± 0.52%) and results were compared to acarbose (21.84 ± 1.67%). These results were further supported by the nonenzymatic glycosylation of hemoglobin assay. Five compounds were isolated by employing column chromatography from both fractions and were structurally characterized using ¹H NMR and ¹³C NMR spectroscopy. Density functional theory (DFT) analysis confirmed their stability and reactivity. Molecular docking, molecular dynamics (MD) simulations, and MM/GBSA calculations revealed that compounds 2 and 5 displayed strong interactions with human pancreatic α‐amylase (PDB: 4GQR) and hemoglobin (PDB: 2D60), respectively. MM/GBSA analysis quantified the binding free energies, reinforcing the stability of these interactions, while MD simulations validated the dynamic behavior of these complexes over time, confirming their potential as stable inhibitors. ADMET analysis confirmed favorable pharmacokinetic and toxicity profiles, suggesting these compounds as promising candidates for diabetes treatment. This study provides a strong foundation for further drug development targeting diabetes management.

Objectives The rise in carbapenem‐resistant Enterobacterales (CRE) has reinforced the global quest for developing effective therapeutics. Traditional drug discovery approaches have been inadequate in overcoming this challenge due to their resource and time constraints. Methods English literature was searched by structured queries related to our review between January 1, 2020, and December 31, 2024. Results The key resistance mechanisms in CRE, such as enzymatic hydrolysis, decreased permeability, and efflux pump overexpression, have been examined in this review. Computational technologies have become pivotal in discovering novel antimicrobial agents with improved accuracy and efficiency. Besides this, the review highlights the advances in structure‐ and ligand‐based drug discovery approaches for identifying potential drugs against CRE. Recent studies demonstrating the use of such in silico techniques to develop targeted drugs against CRE have also been explored. Moreover, this review also underscores the significance of integrating both in silico and in vitro techniques to counter resistance in Enterobacterales, supported by the latest studies. However, these promising computational technologies have a few major drawbacks, such as a lack of standardized parameterization, potentially false positives, and the complexity of effective clinical translations. The drug regulatory barriers also restrict the progress of new antimicrobials for market approval. Conclusion The use of computational technologies for antimicrobial inhibitor discovery is gaining popularity, and it can be expedited by refining computational techniques and integrating them with reliable in vitro validation. The use of innovative hybrid in silico and in vitro technologies is the need of the hour to tackle CRE and mitigate the global threat of antimicrobial resistance.

Introduction: Coronavirus is an enveloped RNA virus belongs to Coronaviridae family. It has four genotypes alpha, beta, gamma, delta and size ranges from 80 to 140 nm with incubation period of 1 to 14 days. Objectives: The main purpose of the study was to find out the overall prevalence, antibodies level and Covid-19 variants detection in hospitalized patients of Malakand division as part of the 4 th wave. Methodology: This study was conducted at Saidu Teaching Hospital Swat. This project was completed in six months, from August 2021 to January 2022. In this descriptive cross sectional study, 1500 swab samples were evaluated for Covid-19 using Genrui RT-PCR amplification kit. Among these cases, 200 positive samples having PCR CT value less than 33, were examined for antibodies titer by CLIA (Chemiluminescence immunoassay) method and 100 positive samples with PCR CT value less than 27 done for variant detection by using GSD Nova III amplification kit. Results: According to our findings the overall prevalence in Malakand division was 31.5% (473), with highest prevalence was recorded in district Swat 22.4% (336). According to gender wise distribution the highest frequency was recorded in males 20.7% (311) and old age people 10.3% (155) respectively. The highest antibody levels were recorded in Upper Lower (Mean=12.82), Males (Mean=12.15) and people with age of 21-40 years (Mean=14.57) respectively. According to our findings all obtained samples were positive for (Delta) variant of Coronavirus during 4 th wave. Conclusion: This study concludes that the PCR based detection of positivity ratio is very high during the fourth wave of Covid-19. The antibodies level in patients was very low and vaccination is needed for high antibodies. The delta variants of Coronavirus is found in overall districts of Malakand division.

Emotional regulation is intimately tied to cultural practices, however, research regarding this correlation across socioeconomic lines remains scant. The need to understand cultural context as it regards emotional expression and regulation for the sake of psychological wellness remains salient. To explore cultural norms and emotional regulation strategies in the context of emotional wellbeing with a consideration of the moderating effect of socioeconomic status. A cross-sectional study design with a sample of 300 participants obtained through convenience sampling. The participants completed The Cultural Orientation Scale (Triandis & Gelfand, 1998), the Emotional Regulation Questionnaire (Gross & John, 2003), and the Warwick-Edinburgh Mental Well-Being Scale (Tennant et al., 2007). Data analysis was conducted using Pearson correlation, independent samples t-test, and one-way ANOVA to determine demographic differences. Found strong positive correlations between cultural norms and emotional expression (r = .88, p < .01), as well as cognitive reappraisal and emotional well-being (r = .78, p < .01). Males demonstrated greater self-reported scores on cognitive reappraisal relative to females (t (288) = 3.12, p = .002). Also, socio-economic status served as a significant predictor of reported cultural norms (F (2,297) = 4.89, p = .008) and emotional wellbeing (F (2,297) = 5.90, p = .003). Emotional regulation strategies and the general well-being of an individual are shaped by cultural values which are of immense importance. These relationships, which have been affected by socioeconomic differences, present an opportunity for culturally specific psychological treatment programs.

Brucellosis is a zoonotic disease of global public health concern, with significant impacts on both humans and animals. This study aimed to determine the seroprevalence of brucellosis in human and animal blood samples, while also identifying key risk factors associated with its transmission. A total of n = 1219 blood samples including 250 from humans and 969 from livestock animals (cow = 212, buffaloes = 282 and goats = 282) were collected in gel-clot activator tubes. Brucella antibodies were analysed through the Rose Bengal Plate Test (RBPT) and competitive Enzyme-Linked Immunosorbent Assay (c-ELISA) followed by PCR confirmation of B. abortus and B. melitensis species. Twenty-one human samples (8.4%) were tested positive by RBPT analysis, while 13 samples (5.2%) were reconfirmed by c-ELISA. The disease was highly prevalent (8.5%) (x2 = 4.04; p = 0.04) in people with animals at their homes and those consuming raw milk (12.3%) (x2 = 12.41; 0.001). A total of 139 (14.3%) sera of animals’ origin were found to be positive with RBPT however, c-ELISA reconfirmation gave a seroprevalence of 121 (12.4%). The investigation unveiled the occurrence of B. abortus and B. melitensis as the prevalent species.

Sustainable finance initiatives have become a pivotal force in shaping the international financial arena, aiming to incorporate environmental, social, and governance (ESG) considerations into investment decision-making procedures. This investigation analyzes the ramifications of these undertakings on monetary markets and economic equilibrium, imparting scholarly discernment into the advantages, difficulties, and ramifications of sustainable financing. By meticulously examining the dynamic relationships between sustainable finance and the broader economy, this study scrutinizes the incorporation of environmental, social, and governance (ESG) considerations, alterations in investment approaches, risk mitigation techniques, and the resultant economic repercussions. This research endeavor advances a more profound comprehension of the function of sustainable finance in shaping financial markets and fostering economic stability amidst urgent global impediments. This paper undertakes a meticulous and exhaustive analysis of the available literature to discern inadequacies and insufficiencies in current knowledge, thereby underscoring the imperative for subsequent inquiry. The current study utilizes a mixed-methods design, consisting of both quantitative analysis and qualitative interviews, to present empirical evidence on the financial implications of sustainable investments and evaluate the efficacy of sustainable finance initiatives. This work presents significant contributions to policymakers, investors, and financial institutions by providing valuable insights into the potential benefits and challenges accompanying initiatives related to sustainable finance.

Understanding both the motivations for vaccination and the causes of vaccine reluctance is necessary for the present worldwide immunization campaigns against the COVID-19 pandemic. The intention of the article is to compile local perspectives and misconceptions about vaccination choices. The intention of this study is to assemble what is usually recognized in cultural context as conspiracies and post-traumatic phase affects in decision making. This is ethnographic exploratory study of Faisalabad, Pakistan. Purposive sampling is used to acquire data, while in-depth interviews and focus group discussions are used as data collecting strategies. Study reveals the experience of people who faced traumatic events and decision about getting vaccinated, and that impact may arise from social and cultural factors related to both the traumatic event and the vaccination experience. Vaccination decisions can be impacted by the impacts of traumatic experiences, which can be influenced by cultural norms as well as social and cultural variables. During this traumatic period, it is natural for conspiracies to emerge in order to influence people's decisions to get vaccinated. The ability of the COVID-19 vaccine to control the population and its unpleasant side effects are significant topics in this disinformation.

The continuous evolution of technology is forcing companies in varying fields to keep pace and adapt accordingly. To stay competitive, businesses must successfully integrate new technologies into their strategies rather than just staying up to date with them. The present study investigates the revolutionary potential of nascent technologies and offers valuable perspectives on how commercial enterprises can efficiently exploit these technologies to attain a competitive advantage. This study investigates the transformative influence of several key emerging technologies, namely artificial intelligence (AI), blockchain, Internet of Things (IoT), and virtual reality (VR), on various business functions such as operations, marketing, customer experience, and supply chain management. Additionally, the text emphasizes the significance of taking a proactive stance towards integrating technology and offers pragmatic suggestions for entities to optimize the advantages of emerging technologies while minimizing the accompanying risks. Organizations that incorporate transformative technologies into their strategic framework can distinguish themselves as industry leaders and tap into innovative avenues for expansion.

Purpose: Colistin resistant Acinetobacter baumannii poses a growing challenge in neonatal intensive care units (NICUs) due to the emergence of plasmid-mediated Mobile Colistin Resistance (mcr) genes that can rapidly spread among neonates. This pioneering study conducted a comprehensive analysis of mcr-1, mcr-2, mcr-3, mcr-4, and mcr-5 genes in A. baumannii strains isolated from NICU. Notably, this investigation marks the first of its kind in this setting. In addition to genotypic analyses, the study incorporated phenotypic assays to identify the most effective method for detecting colistin resistance in these A. baumannii strains. Methods: In the genotypic investigation, DNA was extracted from strains of colistin-resistant A. baumannii, collected from the NICU of a local hospital of Islamabad, Pakistan. The specific set of primers for each mcr gene was used to detect their presence. Various phenotypic methods such as, disc diffusion, broth macro dilution, Minimum Inhibitory Concentration (MIC), disc elusion and colistin agar methods were performed using predetermined calculations for phenotypic studies. Results:The study confirms the distribution of the mcr-1 gene among the eight strains, which contributes 62% of the total number, whereas mcr-2, 3, 4 and 5 genes were not detected in all strains. Based on phenotypic analysis, A. baumannii had shown resistance against colistin at < 2µg/mL. In contrast, MIC varies from strain to strain. Conclusions: The horizontal transfer of the mcr-1 gene is responsible for developing resistance against colistin among A. baumannii in neonates. All phenotypic methods adopted in this study generated the same results, so the method selection depends upon individual comfort. However, we propose that the colistin agar method offers multiple advantages over other methods as it is more economical, easy to perform, multiple samples can be assessed simultaneously, and fewer calculations are involved for colistin resistance determination and finding out clinical breakpoints.

Many people around the world are still unable to get access to clean drinking water. Escherichia coli is a common waterborne pathogen that frequently results from insufficient hygiene measures and needs attention to address health problems. The present study aimed to evaluate antibiotic resistance of Escherichia coli isolated from wastewater and drinking water samples of hospital and non-hospital settings at Peshawar. Out of 462 samples collected, 111 tested positive for E. coli. The majority of isolates were resistant to many antibiotics including Ampicillin, Gentamicin, Tobramycin, Imipenem, Meropenem, Tetracycline, Cefepime, Amikacin, Piperacillin, Levofloxacin, Ciprofloxacin, Ceftriaxone, and Cefazolin. However, they showed susceptibility to Chloramphenicol, Fosfomycin 200 mg, Colistin, and Tigecycline. Genetic analysis revealed various antibiotic resistance genes within the isolates, i.e., marA(20%), marB(40%) marR(30%), rob(30%), and soxS(35%). Following PCR, the resulting products underwent next-generation sequencing. marA exhibited T10P and D101H mutations, while MarR showed substitutions at M1G, V142S, L143P, and P144C positions. In Rob, D2I, A4P, L10F, I12N, and L253P mutations were observed. The SoxS displayed alterations at H105P, R106A, and L107V positions. Asinex antibacterial library was used to study molecular docking based on virtual screening. SWISS ADME was used to in silico evaluate the pharmacokinetics of these substances. 100 ns molecular dynamics simulation was conducted to estimate free binding energies, confirmation, and stability of the binding mode of the identified compounds. Screening results revealed that LAS-52505571, LAS52171241, LAS52202332, and LAS22461675 compounds showed high affinity to MarA, MarR, SoxS, and Rob proteins, respectively, with the lowest binding energies across the library. In brief, the current study aimed at establishing potential chemical entities that could facilitate the evolution of silicon drugs against antibiotic-resistant E. coli strains.

Background Antibiotic resistance to Salmonella is a significant threat to public health globally, particularly in low- and middle-income countries like Pakistan. This study reviews the existing literature to determine the pooled prevalence of antibiotic resistance among Salmonella typhi and Salmonella paratyphi strains across Pakistan in the past decade, including the emergence of extended-spectrum beta-lactamase (ESBL). Methods Six databases were searched for studies published from January 2014 to December 2024. Studies were screened for relevance, and data on antibiotic susceptibility among human S. typhi and S. paratyphi isolates were extracted. Their quality was assessed using the Joanna Briggs Institute checklist. The random-effects model was employed using the R statistical software (V 4.4) to calculate the pooled resistance rates. Results Thirty-one studies met the inclusion criteria after full-text screening. The analysis revealed significant resistance rates to commonly used antibiotics for S. typhi, including nalidixic acid (92%; confidence interval [CI]: 88–95%), ampicillin (80%; CI: 66–89%), ciprofloxacin (64%; CI: 48–77%), azithromycin (7%; CI: 3–16%), and meropenem (2%; CI: 1–3%), with notable variations across different cities, and for S. paratyphi, such as nalidixic acid (91%; CI: 82–96%), ampicillin (34%; CI: 21–50%), ciprofloxacin (51%; CI: 25–77%), azithromycin (4%; CI: 1–12%), and meropenem (2%; CI: 1–5%) resistance, respectively. In S. typhi, 29% and 25% of patients were found to have multidrug resistance (MDR; CI: 21–41%) and extensive drug resistance (XDR; CI: 12–44%), respectively. S. paratyphi with MDR (9%; CI: 2–28%) and XDR (2%; CI: 1–7%). Conclusion The findings revealed the alarming prevalence of antibiotic-resistant Salmonella in Pakistan and the need for updated treatment guidelines. Public health strategies must focus on improving antibiotic use and developing alternative treatment options to mitigate the rising threat of resistant Salmonella strains. Continued research, policy intervention, and national and international cooperation are essential to safeguard public health and ensure effective management of enteric fever.

tThe present research verified the presence of important phytochemicals in the dichloromethane extract of Y. elephantipes Regel roots through qualitative screening, GC-MS analysis, and evaluation of antioxidant and anti-inflammatory potential. Phytochemical analysis confirmed flavonoids, phenols, saponins, and tannins. GC-MS detected 41 components, including benzaldehyde 2,4-dinitrophenyl hydrazone (100%), heptanoic acid docosyl ester (83.01%), phthalic acid benzyl isobutyl ester (77.41%), stigmasterol (23.37%), and cholesterol (22.04%). Antioxidant activity was determined by hydrogen peroxide and ferrous reducing assays. The extract showed antioxidant activity increased in concentration-dependent manner with 67.94 ± 1.04% inhibition in the hydrogen peroxide assay and 71.51 ± 0.69% in the ferrous reducing assay, compared to ascorbic acid 85.14 ± 0.82% and 86.75 ± 1.05%, respectively. The extract exhibited significant anti-inflammatory activity (55.04 ± 2.3%, IC50 = 29.2 ± 2.4 µg/ml) via the ROS method, compared to ibuprofen (73.20 ± 1.7%, IC50 = 11.2 ± 1.9 µg/ml). Molecular docking explored ligand-target interactions, while SwissADME predicted ADME properties. These findings highlight Y. elephantipes as a source of phytochemicals with potential antioxidant and anti-inflammatory applications for oxidative stress and inflammatory conditions..

The issue of antibiotic resistance is increasing with time because of the quick rise of microbial strains. Overuse of antibiotics has led to multidrug-resistant, pan-drug-resistant, and extensively drug-resistant bacterial strains, which have worsened the situation. Different techniques have been considered and applied to combat this issue, such as developing new antibiotics, practicing antibiotic stewardship, improving hygiene levels, and controlling antibiotic overuse. Vaccine development made a substantial contribution to overcoming this issue, although it has been underestimated. In the recent era, reverse vaccinology has contributed to developing different kinds of vaccines against pathogens, revolutionizing the vaccine development process. Reverse vaccinology helps to prioritize better vaccine candidates by using various tools to filter the pathogen’s complete genome. In this review, we will shed light on computational vaccine designing, immunoinformatic tools, genomic and proteomic data, and the challenges and success stories of computational vaccine designing.

Burkholderia pseudomallei causes melioidosis, a deadly infection having high fatality rates (20–50%) and antibiotic resistance, however, there’s no effective drug or vaccine available. Trehalose is a vital sugar for B. pseudomallei which influences the pathogen resilience and pathogenicity. This proposed computational strategy focuses on developing novel drugs against Trehalose-6-phosphate Phosphatase (TPP) to combat infections. This study found three novel drugs from Asinex, Zinc, Chembridge, and Drugbank databases through a comprehensive structure-based virtual screening. The process screened the top three compounds: BDG_34042863, BDF_33738612, and DB00139 along with control (2-methyl-6-phenoxytetrahydro-2 H-pyran-3,4,5-triol) with a binding energy score of -8.8 kcal/mol, -8.4 kcal/mol, and − 7.7 kcal/mol, -6.4 kcal/mol respectively. In a molecular dynamics simulation, the Ligand-protein complexes demonstrated substantial non-covalent interactions as well as a stable docked intermolecular binding conformation. Throughout the MDS (molecular dynamic simulation) period, the studied compounds showed stable consistent interactions; there were no noticeable changes in the interactions or binding mode. The BDG_34042863, BDF_33738612, and DB00139 had a mean deviation of 4.04, 7.18, and 7.10 measured in Å, respectively. In addition, the simulation trajectories of complexes underwent MM/GBSA analysis, which revealed binding affinity scores of -33.39, -41.1, -49.16, and − 41.29 measured in kcal/mol for the control, BDG_34042863, BDF_33738612, and DB00139, respectively. According to DFT Analysis, BDF_33738612 showed the smallest energy gap (0.46 eV), indicating high reactivity, while DB00139 showed the largest energy gap (5.66 eV), illustrating good kinetic stability compared to the control. The compounds exhibit notable differences in reactivity and stability levels as their HOMO-1 to LUMO + 1 and HOMO-2 to LUMO + 2 orbitals have greater energy gaps, ranging from 5.06 eV to 6.69 eV and 5.66 eV to 7.09 eV, respectively. The compounds also had favorable pharmacokinetic characteristics and were categorized as druglike. Among the selected compounds, BDF_33738612 demonstrated the most promising findings followed by BDG_34042863 and DB00139. The compounds may be employed in an experimental study to examine their anti-TPP activity against B. pseudomallei.

The increasing use of bicycles highlights the need for enhanced road safety measures, particularly in interactions between vehicles and cyclists on rural mixed-traffic roads. This study investigates the impact of driver age and behavior on the effectiveness of advanced driver assistance systems (ADASs) in improving cyclist safety. Utilizing a driving simulator, the study analyzed the overtaking maneuvers of 300 male participants, categorized by aggressive and passive driving styles, across three age groups: young (20–34), middle-aged (35–49), and older (50–64) drivers. Results showed that younger drivers exhibited more dynamic and erratic behaviors, with significant variations in lateral control (LC) and time to danger (TTD). Specifically, younger driver’s TTD increased by 20% on average, while older drivers maintained consistent caution with a 10% improvement in LC. Aggressive drivers showed a negligible change in behavior, whereas passive drivers demonstrated a 25% improvement in TTD and a 15% enhancement in LC when using ADAS. The findings suggest that tailored ADAS features are necessary to address the diverse responses of different driver demographics. Future ADAS development should incorporate real-world testing, consider psychological factors, and conduct longitudinal studies to optimize safety outcomes. This study provides critical insights for enhancing the design and implementation of ADAS to protect vulnerable road users such as cyclists.

The Internet of Vehicles (IoV) transforms the automobile industry through connected vehicles with communication infrastructure that improves traffic control, safety and information, and entertainment services. However, some issues remain, like data protection, privacy, compatibility with other protocols and systems, and the availability of stable and continuous connections. Specific problems are related to energy consumption for transmitting information, distributing energy loads across the vehicle’s sensors and communication units, and designing energy-efficient approaches to processing received data and making decisions in the context of the IoV environment. In the realm of IoV, we propose OptiE2ERL, an advanced Reinforcement Learning (RL) based model designed to optimize energy efficiency and routing. Our model leverages a reward matrix and the Bellman equation to determine the optimal path from source to destination, effectively managing communication overhead. The model considers critical parameters such as Remaining Energy Level (REL), Bandwidth and Interference Level (BIL), Mobility Pattern (MP), Traffic Condition (TC), and Network Topological Arrangement (NTA), ensuring a comprehensive approach to route optimization. Extensive simulations were conducted using NS2 and Python, demonstrating that OptiE2ERL significantly outperforms existing models like LEACH, PEGASIS, and EER-RL across various performance metrics. Specifically, our model extends the network lifetime, delays the occurrence of the first dead node, and maintains a higher residual energy rate. Furthermore, OptiE2ERL enhances network scalability and robustness, making it a superior choice for IoV applications. The simulation results highlight the effectiveness of our model in achieving energy-efficient routing while maintaining network performance under different scenarios. By incorporating a diverse set of parameters and utilizing RL techniques, OptiE2ERL provides a robust solution for the challenges faced in IoV networks. This research contributes to the field by presenting a model that optimizes energy consumption and ensures reliable and efficient communication in dynamic vehicular environments.