Unboxing the dilemma associated with online shopping and purchase behavior for remanufactured products: A smart strategy for waste management.

Despite an unprecedented shift in favor of sustainable consumer purchase patterns globally, the overall adoption of refurbished products is still scarce. Earlier empirical investigations have tested aspects affecting consumer purchase intentions concerning remanufactured products, yet they largely ignored risks hindering consumers from opting for them. In order to fill the given theoretical gap, the study tests both inhibiting and igniting factors affecting consumer's remanufacturing products purchase behavior through the use of Stimulus Organism Response (SOR) theory. SOR assists in better understanding consumers' digital purchase behavior toward remanufactured products. Moreover, the study extends the knowledge by examining the impact of Perceived Environmental Benefits, Seller's Reputation, Price Sensitivity, and Social Influence on Consumer's Purchase behavior for remanufactured products. It also investigates the mediating role of the Perceived Risk of Remanufactured Products, followed by the moderating role of Consumers Trust. A useable sample data of 361 was collected through structured questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicated the inverse relationship between increased price sensitivity and purchase behavior concerning remanufactured products, and all other stated variables reflected a significant association with consumer purchase behavior. Likewise, both mediating and moderating roles were found to be significant. Along with theoretical contributions, the study contains numerous practical directions for policymakers, industry stakeholders, and researchers to increase consumers' purchase behavior toward remanufactured products.

A Novel Markov Model-Based Traffic Density Estimation Technique for Intelligent Transportation System.

An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things-intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic.

How self leadership enhances normative commitment and work performance by engaging people at work?

Leadership and its connection with social sustainability are frequently prescribed for effective management. Integrating self-leadership among the employees is an emerging area to focus on empowering an organization. The principal objective of this study was to empirically investigate the impact of self-leadership on normative commitment and work performance through the mediating role of work engagement. This phenomenon of self-leadership was explained by using the theoretical lens of the social cognitive theory and intrinsic motivation theory. Data was collected from 318 employees who worked in the telecom sector in Pakistan and analyzed using Structural Equation Modeling (SEM) AMOS. The findings revealed that in the presence of self-leadership, employee's work engagement, commitment to the organization, and overall work performance elevated significantly. Furthermore, the results also illustrated the occurrence of two significant mediating paths. First, the mediating role of work engagement in the relationship between self-leadership and normative commitment, and second, the mediation of work engagement in the relationship between self-leadership and work performance. The findings of the study significantly contribute practically, and theoretically to the existing literature.

A Two-Phase Machine Learning Framework for Context-Aware Service Selection to Empower People with Disabilities.

The use of software and IoT services is increasing significantly among people with special needs, who constitute 15% of the world's population. However, selecting appropriate services to create a composite assistive service based on the evolving needs and context of disabled user groups remains a challenging research endeavor. Our research applies a scenario-based design technique to contribute (1) an inclusive disability ontology for assistive service selection, (2) semi-synthetic generated disability service datasets, and (3) a machine learning (ML) framework to choose services adaptively to suit the dynamic requirements of people with special needs. The ML-based selection framework is applied in two complementary phases. In the first phase, all available atomic tasks are assessed to determine their appropriateness to the user goal and profiles, whereas in the subsequent phase, the list of service providers is narrowed by matching their quality-of-service factors against the context and characteristics of the disabled person. Our methodology is centered around a myriad of user characteristics, including their disability profile, preferences, environment, and available IT resources. To this end, we extended the widely used QWS V2.0 and WS-DREAM web services datasets with a fusion of selected accessibility features. To ascertain the validity of our approach, we compared its performance against common multi-criteria decision making (MCDM) models, namely AHP, SAW, PROMETHEE, and TOPSIS. The findings demonstrate superior service selection accuracy in contrast to the other methods while ensuring accessibility requirements are satisfied.

Moisture Computing-Based Internet of Vehicles (IoV) Architecture for Smart Cities.

Recently, the concept of combining 'things' on the Internet to provide various services has gained tremendous momentum. Such a concept has also impacted the automotive industry, giving rise to the Internet of Vehicles (IoV). IoV enables Internet connectivity and communication between smart vehicles and other devices on the network. Shifting the computing towards the edge of the network reduces communication delays and provides various services instantly. However, both distributed (i.e., edge computing) and central computing (i.e., cloud computing) architectures suffer from several inherent issues, such as high latency, high infrastructure cost, and performance degradation. We propose a novel concept of computation, which we call moisture computing (MC) to be deployed slightly away from the edge of the network but below the cloud infrastructure. The MC-based IoV architecture can be used to assist smart vehicles in collaborating to solve traffic monitoring, road safety, and management issues. Moreover, the MC can be used to dispatch emergency and roadside assistance in case of incidents and accidents. In contrast to the cloud which covers a broader area, the MC provides smart vehicles with critical information with fewer delays. We argue that the MC can help reduce infrastructure costs efficiently since it requires a medium-scale data center with moderate resources to cover a wider area compared to small-scale data centers in edge computing and large-scale data centers in cloud computing. We performed mathematical analyses to demonstrate that the MC reduces network delays and enhances the response time in contrast to the edge and cloud infrastructure. Moreover, we present a simulation-based implementation to evaluate the computational performance of the MC. Our simulation results show that the total processing time (computation delay and communication delay) is optimized, and delays are minimized in the MC as apposed to the traditional approaches.

An Innovative Method for Preserving Privacy in Internet of Things.

Preservation of privacy of users' personal data has always been a critical issue to deal with. This issue in the Internet of Things (IoT), which facilitates millions of applications, has become even more challenging. Currently, several approaches and methods are available to safeguard privacy but each of them suffers from one or more anomalies. In particular, Trusted Third-Party approach relies on the trust of a third-party server, Cooperation needs the trust of other peers, Obfuscation is known to return inaccurate results, and Dummy generates too much overhead. Moreover, these and most of the other well-known approaches deal only with specific types of applications linked to the location-based services. In this paper, we present two new methods, namely: Blind Third Party (BTP) and Blind Peers ( B L P ), and combine them to form a new one to be known as the Blind Approach ( B L A ). With the help of simulation results we shall demonstrate the effectiveness and superiority of B L A over the other available methods. The simulation results also exhibit that B L A is free from all the existing problems of the other approaches. However, B L A causes a slight increase in the average (response) time, which we consider to be a minor issue. We shall also discuss the capability and superiority of the Blind Approach in the cases of E-health, Smart Transportation, and Smart Home systems.

Evaluation of some 1H-pyrazole derivatives as a dual acting antimalarial and anti-leishmanial agents.

The synthesis of a novel series of 1H-pyrazole derivatives was achieved by condensation of pyrazole aldehyde 1 with hydrazine hydrate to give hydrazone 7. On the other hand, cyclization of α,ß-unsaturated ketone counterpart 2 using hydrazine hydrate in liquid aliphatic acids rendered compounds 4-6 and hydrazine hydrate in ethanol afforded compound 3. The later was allowed to react with aroyl chloride giving rise to compounds 8, 9. All compounds were tested for their in vivo anti-malarial and in vitro antileishmanial activities. The anti-malarial activity was performed using Plasmodium berghei infected mice, while the anti-leishmanial activity of the compounds was determined against Leishmania aethiopica promastigotes using alamar blue reduction assay. Compound 3, 1-(4-methylphenyl)-3-phenyl-4-[3-(2-thienyl)-2-pyrazolin-5-yl]-1H-pyrazole, possessed the highest anti-malarial activity with suppression of 70.26%. The highest anti-leishmanial activity was exhibited by compound 2, 1-(4-methylphenyl)-3-phenyl-4-[1-(2-thienyl)-prop-2-en-1-one]-1H-pyrazole, with an IC50 of 0.079µg/ml. Hydrazone 7 showed appreciable dual anti-malarial (suppression = 62.30%) and anti-leishmanial activity (IC50 = 1.823µg/ml).

Evaluation of the skeletal and dental effects of a hybrid aesthetic functional appliance (HAF) in skeletal class II division 1 malocclusion: A prospective uncontrolled clinical trial.

Background: The present study investigated the skeletal and dental effect in class II division I growing patients due to mandibular deficiency treated with the hybrid aesthetic functional (HAF) appliance. Methods: A sample of 16 growing patients (5 boys and 11 girls; mean age: 9.50 years, standard deviation: 1.15) with class II division I malocclusion were treated using the HAF appliance for an average period of 10±3 months. For each patient, a cephalometric radiograph was taken before and after treatment, and digital analysis was applied using the WebCeph program. The statistical analysis was performed to evaluate dental and skeletal changes associated with the HAF appliance and determine if there were any statistically significant variations in anatomical measurements between the start and completion of the treatment. Results: The data showed a significant increase in SNB angle (P=0.002), leading to a significant decrease in ANB angle (P=0.001). The mandibular length significantly increased (P=0.008), the lower incisors were flared significantly (P=0.028), and the lower molars were extruded significantly (P≤0.001). Also, this study revealed a significant decrease in Wits appraisal (P≤0.001), overjet (P≤0.001), and overbite (P=0.041). Additionally, a significant increase in lower anterior facial height (P≤0.001), total facial height (P=0.001), and posterior facial height (P=0.037) were observed. Conclusion: The HAF appliance showed that it could be used to correct class II division 1 skeletal discrepancy by mandibular advancement. The HAF appliance increased all facial heights significantly.

Corporate social responsibility-an antidote for sustainable business performance: interconnecting role of digital technologies, employee eco-behavior, and tax avoidance.

Small- and medium-sized enterprises (SMEs) have consistently contributed significantly to the economy's gross domestic product (GDP). Organizations are motivated to achieve sustainable performance by mitigating the adverse impacts of company operations by improving productivity and optimizing resource utilization. In order to achieve this objective, the businesses are making all their efforts and developing the systems to ensure sustainable performance. Based on the prevailing research gaps, the current study examines the role of a portfolio of responsible digital technologies (DT), which provides a competitive advantage and helps achieve sustainable firm performance (SFP). Using a simple random sampling technique, data from 294 textile manufacturing SMEs is collected and analyzed using the structural equation model (SEM) in AMOS v.24. The results indicated that digital technologies, tax avoidance, green employee behavior, and corporate social responsibility facilitated improving the SFP of SMEs. Furthermore, it is worth noting that the link connecting TA and SFP is unaffected by CSR activities aimed at the environment. This finding, however, should not lessen the importance of TA, which deserves significant attention and thought from management.

Synthesis, antileishmanial, antimalarial evaluation and molecular docking study of some hydrazine-coupled pyrazole derivatives.

Pyrazole-bearing compounds are known for their diverse pharmacological effects including potent antileishmanial and antimalarial activities. Herein, some hydrazine-coupled pyrazoles were successfully synthesized and their structures were verified by employing elemental microanalysis, FTIR, and 1H NMR techniques. The in vitro antileishmanial and in vivo antimalarial activities of the synthesized pyrazole derivatives (9-15) were evaluated against Leishmania aethiopica clinical isolate and Plasmodium berghei infected mice, respectively. The result revealed that compound 13 displayed superior antipromastigote activity (IC50 = 0.018) that was 174- and 2.6-fold more active than the standard drugs miltefosine (IC50 = 3.130) and amphotericin B deoxycholate (IC50 = 0.047). The molecular docking study conducted on Lm-PTR1, complexed with Trimethoprim was acquired from the Protein Data Bank (PDB ID:2bfm), justified the better antileishmanial activity of compound 13. Furthermore, the target compounds 14 and 15 elicited better inhibition effects against Plasmodium berghei with 70.2% and 90.4% suppression, respectively. In conclusion, the hydrazine-coupled pyrazole derivatives may be considered potential pharmacophores for the preparation of safe and effective antileishmanial and antimalarial agents.

Phytochemical screening, antioxidant, immunomodulatory and analgesic potential of aqueous-ethanolic extracts of Euphorbia prostrata ait. and Crotalaria burhia Buch-Ham.

Euphorbia prostrata (E. prostrata) and Crotalaria burhia (C. burhia) are widely found in flora of the Cholistan Desert of Bahawalpur, Pakistan and are traditionally used to treat pain and chronic disease. The current study aimed to evaluate their phytochemical screening, antioxidant activity, in-vivo phagocytic activity, and analgesic activity. Both the plant extracts were investigated for phytochemical screening, Fourier Transform Infrared (FTIR) analysis, in-vitro antioxidant by 2, 2-diphenyl-1-picrylhydrazyl (DPPH) method, in-vivo immunomodulatory activity by macrophages phagocytosis using carbon clearance rate assay and analgesic activity by acetic acid produced writhing method. Phytochemical screening showed the presence of carbohydrates, saponins, tannins, phenols, quinines, proteins, terpenes, glycosides, and alkaloids. FTIR analysis revealed the existence of different functional groups in both extracts. The DPPH method showed that E. prostrata exhibited a high antioxidant potential with an IC50 of 62.5 µg/ml whereas C. burhia showed a lower antioxidant potential. At the dose of 200 mg/kg body weight (b. wt), both the extracts showed a significant increase in the phagocytic index by 5.2 ± 0.2, and, 4.8 ± 0.1 (p < 0.001) respectively which was close to the 100 mg/kg b. wt of the standard drug (Levamisole) 5.4 ± 0.2. Both the extracts at the dose of 200 mg/kg b. wt also significantly reduced the writhing (abdominal contractions) count by 13.7 ± 0.3 and, 25.3 ± 1.5 (p < 0.001), showing 71.8% and 47.6% of reduced analgesic activity compared to the standard drug dicloran (diclofenac sodium), respectively. In conclusion, extracts of both plants indicate their role in the management of various disorders to relieve pain and modulate the immune system.

Functional Outcome of Subvastus versus Medial Parapatellar Approaches for Total Knee Replacement in Patients with Knee Osteoarthritis: A Prospective Cohort Study.

Background: Subvastus approach and medial parapatellar approach are two major approaches for total knee replacement (TKR). There is no global consensus on the superiority of either approach in terms of functional outcomes. Objective: The present study aimed to evaluate the functional outcome of TKR through subvastus approach and medial parapatellar approach by using patient-reported scores at 3-, 6-, and 12-month post-operative follow-ups. Methods: This prospective cohort follow-up study included patients with knee osteoarthritis who underwent elective primary TKR either through the subvastus or medial parapatellar approaches at King Abdullah Medical City, Makkah city, Kingdom of Saudi Arabia, from January 2019 to December 2022. Scores from the self-reported Oxford Knee Score (OKS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were compared in the two groups of patients at 3-, 6-, and 12-month post-operative follow-ups. Results: A total of 98 patients were included, of which 37 underwent TKR through the subvastus approach and 61 through the medial parapatellar approach. There was an overall significant change over time in both WOMAC and OKS scores (P < 0.001). Patients who underwent the subvastus approach had significantly higher mean of WOMAC and OKS than patients with the medial parapatellar approach at the 3- and 6-month follow-ups (P < 0.05), but not at the 12-month follow-up. Conclusions: For TKR, the medial parapatellar approach results in better functional outcomes at the 3- and 6- month follow-up periods compared with the subvastus approach.

Outcome of colorectal cancer resection in octogenarians.

INTRODUCTION: Octogenarians constitute a rapidly growing segment of patients undergoing colorectal cancer resection, but their outcomes remain understudied and under-reported. Our aims were to analyse outcomes of octogenarian patients undergoing curative colorectal resections compared with a similar cohort 2 decades younger. METHODS: Data from a prospectively collected database of consecutive patients undergoing colorectal resection between 2004 and 2006 were analysed. Primary endpoints were 30-day mortality and morbidity. The secondary endpoint was long-term survival. RESULTS: Eighty-one consecutive patients aged >80 years and 61 patients aged 60 - 70 years undergoing elective and emergency resections were identified. In the octogenarian group, 75.3% of resections were elective compared with 78.0% in the younger cohort (p=0.9), with pelvic procedures accounting for 34.6% and 44.3%, respectively (p=0.34). The elderly had a significantly higher median CR-Possum (performance status) score than the younger cohort (18.0 v. 14.0; p=0.001). Permanent stoma rates were similar (22% for octogenarians v. 27% for younger patients; p=0.8), as was pathological stage (p=0.24). There was 1 death within 30 days after resection in each group. Median survival in the octogenarian cohort was 73 months compared with 74 months in the younger cohort, and 5-year survival rates were 53.1% and 66.0%, respectively (p=0.2, Mantel-Cox). CR-Possum score did not affect overall survival (p=0.711, Mantel-Cox), but a higher score correlated with more postoperative complications in both groups. CONCLUSIONS: Octogenarians have poor performance status, but can undergo resection with acceptable mortality and morbidity. Overall survival in the two age groups studied was similar, with poor performance status being associated with higher postoperative complications but no long-term difference in survival.

Breakfast patterns in relation to physical activity among school adolescents in Karachi, Pakistan.

BACKGROUND: Unhealthy habits and poor diet patterns are significant concerns among adolescents, impacting their overall quality of life. This study aimed to assess and improve these habits in adolescents. METHODS: This is a cross-sectional study conducted in 2017-2018 in Karachi. The research participants, aged 11-17 years, were drawn from lower-middle-income secondary schools using multistage random selection. Sociodemographics, the Physical Activity Questionnaire for Adolescents (PAQ-A), and breakfast consumption were determined through questionnaire and a food frequency survey. RESULTS: A study of 334 school-going adolescents in Karachi, Pakistan, found that 82% consumed breakfast daily, with chapatti being the preferred choice (72.2%). Physical activity levels varied, but 56.6% engaged in regular activity. No significant differences were found in breakfast consumption by age or parental education. CONCLUSIONS: Understanding South Asian adolescents' breakfast habits is crucial. Promoting healthier breakfast options and increased physical activity are recommended for long-term well-being, with further research needed for targeted interventions.

Interconnection between the role of blockchain technologies, supply chain integration, and circular economy: A case of small and medium-sized enterprises in Pakistan.

Increased industrialization has led to unprecedented resource depletion on a global scale. The current state of affairs has compelled practitioners and academics to investigate the role of sustainable technologies in greening the operations of businesses. Previous studies have attempted to examine the number of operational aspects for their role in making firms sustainable, yet the utility of blockchain technologies is in its infancy. The role of BT in enhancing integration across supply chains has been in the limelight in the recent past. At the same time, its ability to cause sustainable supply chain performance (SSCP) in sync with the circular economy (CE) and supply chain integration (SCI) has largely remained unexplored. Therefore, this study intends to examine the association between blockchain technologies (BTs) and SSCPs through integration to fill the empirical gaps. The study was pursued to investigate the moderating role of the CE on the relationship between multiple extents of SCI and SSCP. Based on dynamic capability theory (DCT), the study considered BT a dynamic resource. BTs are used to integrate and reenergize the relationships with upstream and downstream channel members in pursuit of sustainable performance outcomes. The study opted for a cross-sectional design, where data was collected through convenience sampling from 475 managers from SMEs operating across Pakistan. PLS-SEM was used to analyze the data and to generate the required empirical outcomes. Study results favored the significant association between BT and SSCP, followed by a significant mediating role of SCI dimensions and moderating role of the CE. The study's findings propagate the utility of BTs adoption for SMEs, which holds the potential for firms to achieve system-wide integration to achieve sustainable outcomes. The given empirical investigation holds valuable insights for practitioners and scholars intending to pursue research on the subject matter.

An empirical investigation into the altering health perspectives in the internet of health things.

Healthcare is on top of the agenda of all governments in the world as it is related to the well-being of the people. Naturally, this domain has attracted the attention of many researchers globally, who have studied the development of its different phases, including E-Health and the Internet of Health Things (IoHT). In this paper, the difference between the recent concepts of healthcare (E-health, M-Health, S-Health, I-Health, U-Health, and IoHT/IoMT) is analyzed based on the main services, applications, and technologies in each concept. The paper has also studied the latest developments in IoHT, which are linked to existing phases of development. A classification of groups of services and constituents of IoHT, linked to the latest technologies, is also provided. In addition, challenges, and future scope of research in this domain concerning the wellbeing of the people in the face of ongoing COVID-19 and future pandemics are explored.

Validation of an HPLC method for the simultaneous determination of diminazene diaceturate and phenazone in injectable veterinary granules and bulk powders.

A validated HPLC method for the simultaneous determination of diminazene diaceturate and phenazone has been established for the analysis of the compounds in veterinary granules for injection and in bulk powders. The compounds were separated using a Symmetry RP 18 analytical column and detected by UV absorbance at 250 nm. Linearity, accuracy as well as the intra-assay precision, inter-day precision and specificity of the method were established. The limits of detection and quantification were 3.2 and 9.7 µg mL-1 for diminazene diaceturate and 9.57 and 28.99 µg mL-1 for phenazone. Method had the potential to determine these drugs simultaneously from dosage forms without any interference with each other.

Digital transformation, smart technologies, and eco-innovation are paving the way toward sustainable supply chain performance.

The world has limited resources and resource depletion has been a serious concern for many years. To ensure that ecological balance is maintained, the United Nations has developed 17 Sustainable Development Goals (SDGs). This study attempts to meet the 12th SDG of "responsible production and consumption" and provide a guideline to manufacturing organizations in Pakistan. Many scholars have examined the role of different technologies on sustainable performance. However, research using eco-innovation (EI), digital transformation (DT), and smart technologies (ST) is still scarce. The current study develops the conceptual model based on the resource-based view (RBV) and technology, organization, and environment (TOE) theories, and using a simple random sampling technique, valid data from 375 professionals in the manufacturing industry is collected to test the relationship between sustainable development strategy (SDS), EI, DT, ST, and sustainable supply chain performance (SSCP). The results indicate strong positive relationships between SDS, EI, DT, ST, and SSCP. Results indicate that even if organizations are executing SDS and EI, without DT and ST, organizations cannot achieve SSCP. Therefore, it is recommended to the managers that they must apply DT and ST to guarantee their pursuit of achieving sustainable performance and contribution toward SDGs.

Lightweight Deep Learning Classification Model for Identifying Low-Resolution CT Images of Lung Cancer.

With an astounding five million fatal cases every year, lung cancer is among the leading causes of mortality worldwide for both men and women. The diagnosis of lung illnesses can benefit from the information a computed tomography (CT) scan can offer. The major goals of this study are to diagnose lung cancer and its seriousness and to identify malignant lung nodules from the provided input lung picture. This paper applies unique deep learning techniques to identify the exact location of the malignant lung nodules. Using a DenseNet model, mixed ground glass is analyzed in low-dose, low-resolution CT scan images of nodules (mGGNs) with a slice thickness of 5 mm in this study. This was done to categorize and identify many histological subtypes of lung cancer. Low-resolution CT scans are used to pathologically classify invasive adenocarcinoma (IAC) and minimally invasive adenocarcinoma (MIA). 105 low-resolution CT images with 5 mm thick slices from 105 patients at Lishui Central Hospital were selected. To detect and distinguish, IAC and MIA, extend and enhance deep learning two- and three-dimensional DenseNet models are used. The two-dimensional DenseNet model was shown to perform much better than the three-dimensional DenseNet model in terms of classification accuracy (76.67%), sensitivity (63.3%), specificity (100%), and area under the receiver operating characteristic curve (0.88). Finding the histological subtypes of persons with lung cancer should aid doctors in making a more precise diagnosis, even if the image quality is not outstanding.

Synthesis, antimalarial, antileishmanial evaluation, and molecular docking study of some 3-aryl-2-styryl substituted-4(3H)-quinazolinone derivatives.

Quinazolinones are a diverse group of nitrogen-containing heterocyclic compounds with promising antimalarial and antileishmanial activities. Herein, some 3-aryl-2-styryl substituted-4(3H)-quinazolinones were synthesized via cyclization, condensation, and hydrolysis reactions. 1H NMR, FTIR and elemental microanalysis was used to verify the structures of the synthesized compounds. The in vivo antimalarial and in vitro antileishmanial activities of the target compounds were investigated using mice infected with Plasmodium berghi ANKA and Leishmania donovani strain, respectively. Among the test compounds, 8 and 10 showed better antimalarial activities with percent suppression of 70.01 and 74.18, respectively. In addition, (E)-2-(4-nitrostyryl)-3-phenylquinazolin-4(3H)-one (6) showed promising antileishmanial activity (IC50 = 0.0212 µg/mL). It is two and 150 times more active than the standard drugs amphotericin B deoxycholate (IC50 = 0.0460 µg/mL) and miltefosine (IC 50 = 3.1911 µg/mL), respectively. Its superior in vitro antileishmanial activity was supported by a molecular docking study conducted in the active site of Lm-PTR1. Overall, the synthesized 3-aryl-2-styryl substituted-4(3H)-quinazolinones showed promising antileishmanial and antimalarial activities and are desirable scaffolds for the synthesis of different antileishmanial and antimalarial agents.