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Abstract The diabetes mellitus model (DMM) is explored in this study. Many health issues are caused by this disease. For this reason, the integer order DMM is converted into the time delayed fractional order model by fitting the fractional order Caputo differential operator and delay factor in the model. It is proved that the generalized model has the advantage of a unique solution for every time t. Moreover, every solution of the system is positive and bounded. Two equilibrium states of the fractional model are worked out i.e. disease free equilibrium state and the endemic equilibrium state. The risk factor indicator, R0 is computed for the system. The stability analysis is carried out for the underlying system at both the equilibrium states. The key role of R0 is investigated for the disease dynamics and stability of the system. The hybridized finite difference numerical method is formulated for obtaining the numerical solutions of the delayed fractional DMM. The physical features of the numerical method are examined. Simulated graphs are presented to assess the biological behavior of the numerical method. Lastly, the outcomes of the study are furnished in the conclusion section.

Abstract In this manuscript, a mathematical model known as the Heimburg model is investigated analytically to get the soliton solutions. Both biomembranes and nerves can be studied using this model. The cell membrane’s lipid bilayer is regarded by the model as a substance that experiences phase transitions. It implies that the membrane responds to electrical disruptions in a nonlinear way. The importance of ionic conductance in nerve impulse propagation is shown by Heimburg’s model. The dynamics of the electromechanical pulse in a nerve are analytically investigated using the Hirota Bilinear method. The various types of solitons are investigates, such as homoclinic breather waves, interaction via double exponents, lump waves, multi-wave, mixed type solutions, and periodic cross kink solutions. The electromechanical pulse’s ensuing three-dimensional and contour shapes offer crucial insight into how nerves function and may one day be used in medicine and the biological sciences. Our grasp of soliton dynamics is improved by this research, which also opens up new directions for biomedical investigation and medical developments. A few 3D and contour profiles have also been created for new solutions, and interaction behaviors have also been shown.

Potato (Solanum tuberosum L.) cultivation in Pakistan faces challenges, with black scurf disease caused by Rhizoctonia solani Kühn being a significant concern. Conventional methods like chemical fungicides partially control it, but an effective solution is lacking. This study explores the potential of biofertilizers and soil amendments from Asteraceae weed biomass to manage the disease. Two potato varieties, Karoda and Sante, were chosen, and two biofertilizers, Fertibio and Feng Shou, were tested alone or with Xanthium strumarium biomass. Disease pressure was highest in the positive control, with significant reduction by chemical fungicide. X. strumarium biomass also decreased disease incidence significantly. Fertibio showed better efficacy than Feng Shou. Physiological and biochemical attributes of plants improved with biofertilizer and biomass application. Tuber weight, photosynthetic pigments, total protein content, and antioxidant enzymes (CAT, POX, and PPO) were positively correlated. Combined application of Fertibio and S. marianum biomass effectively managed black scurf disease. These eco-friendly alternatives could enhance disease management and yield. Future research should explore their cost-effectiveness, commercialization, and safety.

Objective: To compare post-operative pain of Bupivacaine vs placebo in patients undergoing percutaneous nephrolithotomy. Study Design: Quasi-experimental study. Place and Duration of Study: Armed Forces Institute of Urology, Rawalpindi Pakistan, from Aug 21 to Aug 22. Methodology: Eighty-eight patients undergoing percutaneous nephrolithotomy who fulfilled the inclusion criteria were included in study and randomized in two equal groups (44 patients each) by lottery method, Group-A received 20ml/50mg of 0.25% Bupivacaine and Group-B received 20ml normal saline around nephrostomy tube. Post-operatively, the visual analogue scale used to measure pain score at 6, 12 and 24 hours by an independent observer, blinded to randomization. After 24 hours mean of VAS calculated and noted. Results: Mean age of patient in Group-A was 39.40±8.42 years and in Group-B 38.00±8.67 years. There were 65 male (73.86%) and 23 female (26.13%) patients. Mean stone size was 3.00±0.68 cm and 3.006±0.63 cm in Group-A and B respectively. Median pain at 6, 12 and 24 hours was low in Group-A in comparison to Group-B with p-value

Abstract Most of the countries in the world are affected by the coronavirus epidemic that put people in danger, with many infected cases and deaths. The crowding factor plays a significant role in the transmission of coronavirus disease. On the other hand, the vaccines of the covid-19 played a decisive role in the control of coronavirus infection. In this paper, a fractional order epidemic model (SIVR) of coronavirus disease is proposed by considering the effects of crowding and vaccination because the transmission of this infection is highly influenced by these two factors. The nonlinear incidence rate with the inclusion of these effects is a better approach to understand and analyse the dynamics of the model. The positivity and boundedness of the fractional order model is ensured by applying some standard results of Mittag Leffler function and Laplace transformation. The equilibrium points are described analytically. The existence and uniqueness of the non-integer order model is also confirmed by using results of the fixed-point theory. Stability analysis is carried out for the system at both the steady states by using Jacobian matrix theory, Routh–Hurwitz criterion and Volterra-type Lyapunov functions. Basic reproductive number is calculated by using next generation matrix. It is verified that disease-free equilibrium is locally asymptotically stable if $${R}_{0}1$$ R 0 > 1 . Moreover, the disease-free equilibrium is globally asymptotically stable if $${R}_{0}1$$ R 0 > 1 . The non-standard finite difference (NSFD) scheme is developed to approximate the solutions of the system. The simulated graphs are presented to show the key features of the NSFD approach. It is proved that non-standard finite difference approach preserves the positivity and boundedness properties of model. The simulated graphs show that the implementation of control strategies reduced the infected population and increase the recovered population. The impact of fractional order parameter $$\alpha$$ α is described by the graphical templates. The future trends of the virus transmission are predicted under some control measures. The current work will be a value addition in the literature. The article is closed by some useful concluding remarks.

Biodegradable bioplastics provide a promising solution to mitigate environmental harm from petroleum-based plastics. This study focuses on optimizing bioplastic films made from oil palm trunk starch (OPTS), using glycerol (10, 20, and 30 % v/w) as a plasticizer and modified with citric-acid epoxidized palm oil (CEPO). The bioplastics were formed using the solution casting method and analyzed for morphology, functional groups, diffraction peaks, thermal and mechanical properties, degradation time, and compostability. The optimal conditions were achieved with 30 % glycerol (Sample ST-CEPO-GLY30). The addition of glycerol enhances the thermal and mechanical properties, improves the biodegradability, and compostability of the bioplastics.

In organizations, knowledge sharing is a major source of innovation, performance, success, and goal achievement. This review-based study aims to extract the determinants of knowledge sharing from previously conducted studies. It also explores the organizational factors that have been most emphasized in studies on knowledge sharing. Following inclusion and exclusion criteria, fifty-four studies were selected for review and analysis to achieve the study objectives. Organizational culture, organizational support, organizational commitment, and organizational rewards are identified as highly important factors, while relationships, organizational justice, organizational trust, organizational leadership, and organizational climate are found to be very important factors. Additionally, some organizational factors are identified as quite important, somewhat important, and less important or ignored factors in the realm of knowledge sharing. Iran emerges as a productive country for producing research on knowledge sharing, with staff members/employees being a prolific population, and academia being a prolific discipline/site. This study will provide guidance to researchers on lesser-explored or ignored organizational variables to consider in their research on knowledge sharing.

Black Scurf is one of the destructive fungal diseases of potato crops caused by fungus Rhizoctonia solani. Cultural practices and fungicide applications are insufficient in effectively combating the pathogen, while utilizing resistant cultivars has become one of the most economical and effective way to control disease. About ten commercial potato varieties were screened out against the disease by artificially inoculating the plants with R. solani and these potato varieties were grouped based on disease incidence and disease severity. Four varieties (Ronoldo, Rubi, Challenge, and Sadaf) were grouped as resistant, three varieties (SH-5, Sante and Astrex) as moderately susceptible and three varieties (Karoda, Mosica and Simply red) as susceptible with significantly highest disease incidence (P ≤ 0.05). Disease also reduced number and size of tubers, while the disease incidence showed negative (P < 0.001) correlation with chlorophyll and protein contents, and activities of catalase (CAT), peroxidase (POX) and polyphenol oxidase (PPO) enzymes. It was concluded that a combination of phenotypic and physiological indices could be used to identify black scurf resistance in potatoes.

Abstract In this study, a novel adapted homotopy perturbation method (HPM) is used to treat the nonlinear phenomena of free vibration in a system with one degree of freedom. This adaptation involves the integration of HPM with a least-squares optimizer, resulting in a hybrid method called the least square homotopy perturbation method (LSHPM). The LSHPM is tested on various nonlinear problems documented in the existing literature. To evaluate the effectiveness of the proposed approach, the identified problems are also tackled using HPM and the MATLAB built-in function bvp5c, and then the results are compared with those obtained using LSHPM. In addition, a comparative analysis is carried out with the results of the AG method as found in the literature. The results show that LSHPM is a reliable and efficient method suitable for solving more complicated initial value problems in the fields of science and engineering.

Abstract Background Wet meadows, a type of wetland, are impacted by significant climate fluctuation and human activity, impacting soil microorganisms that play an essential role in ecosystem processes. Understanding the underlying ecological mechanisms and processes of wet meadows depends on the fungal communities associated with the plant roots. We used Illumina MiSeq profiling for amplicon sequencing to determine how environmental factors and elevation affect the fungal communities of the rhizosphere and rhizoplane related to three plant species, Cremanthodium ellisii, Cremanthodium lineare, and Caltha scaposa, in alpine wet meadows. Results The phyla Ascomycota and Basidiomycota dominated the rhizosphere (54.5% and 20.9%) and rhizoplane (51.6% and 36.4%), while the predominant fungal genera in the rhizosphere and rhizoplane were Unclassified fungi, Unclassified Ascomycota, Pseudeurotium, Tetracladium, Vishniacozyma, Rhodotorula, Cadophora, and Penicillium. Mantel test and network analysis revealed that the soil water content (SWC), soil organic carbon (SOC), and total nitrogen (TN) were the primary drivers of fungal communities. However, the influence of microbial biomass C (MBC), pH, microbial biomass N (MBN), and elevation varied. Stochastic assembly processes were dominant in both rhizosphere and rhizoplane fungal communities. FUNGuild functional prediction revealed site-specific variation in the trophic level and guild of plant-root-associated fungal communities. The rhizosphere contained 58.5% saprotrophs, 11.7% pathotrophs, and 12.6% symbiotrophs. In addition, 60.4% of the observed OTUs were arbuscular mycorrhizae, 13.2% were endophytes, 20.9% were ectomycorrhizae, and 1.09% were orchid mycorrhizae. The rhizoplane comprised 51.3% of OTUs linked with saprotrophs, 13.9% with pathotrophs, and 7.92% with symbiotrophs. Moreover, 36.1% of OTUs represented arbuscular mycorrhizae, 25.0% were endophytes, 30.6% were ectomycorrhizae, and 2.77% were ascribed to orchid mycorrhizae in the rhizoplane. The abundance of saprotrophs and pathotrophs in the rhizosphere was highest in C. ellisii at SI and SIII, while symbiotrophs were highest in C. lineare at SIII. Similar variations among the plant species and sites were observed in the fungal functional groups (guilds). Conclusions It was concluded that although root compartments significantly influenced the fungal communities in the rhizosphere and rhizoplane, environmental factors and plant types exhibited distinct effects. This study explains how physicochemical properties, plant species, and sites can alter the overall structure and functional repertoire of fungal communities in alpine wet meadows. Graphical Abstract

The aim of the current study was to assess the effectiveness of NH 4+ priming to enhance tomato seed germination and plant growth under saline stress. In the absence of light at 25 ± 1 °C, tomato seeds were primed with 50 and 100 mmol of NH 4 NO 3 and with 50 and 100 mmol of (NH 4 ) 2 SO 4 for 12 and 24 h, respectively. In the seed germination test, twenty primed seeds were used for each treatment, along with five replica plates and a control, and were all incubated at 25°C with 25 mL of moistened water. In a second greenhouse experiment, primed seeds were planted in garden soil and watered with tap water, salt water, and a control. The concentration of saline water (50, 100, 150, and 200 mmol NaCl) was gradually raised after a 10-day break. The germination percentages in T5 (50 mmol (NH 4 ) 2 SO 4 , 12 hrs) were 82±3.7% and 80±4.47 %, respectively, followed by T1 and T3 (50 mmol (NH 4 ) 2 SO 4 , 12 h and 100 mmol NH 4 NO 3 , 12 h). When compared to the unprimed tomato seeds, the NH 4+ priming with NH 4 NO 3 and (NH 4 ) 2 SO 4 improved plant height and other growth parameters. Furthermore, the chlorophyll and total flavonoid content were improved in both saline and non-saline treatments. In terms of salinity, the NH 4+ priming increased the proline content while decreasing the total protein content. It is concluded that further research will be needed to clarify the effect of NH 4 NO 3 and (NH 4 ) 2 SO 4 as NH 4+ priming in tomato plants because other factors and nutrition can play a role in seed germination and plant growth development.

SDIT Kuntum Insan Cemerlang Bondowoso and SMPIT Bina Insan Cemerlang Bondowoso have successfully implemented the learning design for the implementation of the Integrated curriculum compiled by JSIT Indonesia, in this regard, it is certainly necessary to conduct research so that the results are expected to be a model for other institutions. This study aims to analyze the learning design based on Active Deep Learner Experience (ADLX) Integrated curriculum for PAI subjects at SDIT Kuntum Insan Cemerlang Bondowoso and SMPIT Bina Insan Cemerlang Bondowoso. The research method used is qualitative, with data collection techniques of observation, interviews and documentation studies. Data analysis by reducing, displaying, verifying and drawing conclusions and data validity using triangulation and member-check. The results of the study explained that the learning design based on ADLX integrated curriculum in PAI subjects was oriented towards the formation of seven characters, namely: straight aqidah, correct worship, mature personality and noble character, being a serious person, discipline, ability to read, memorize, and understand the Qur'an well, having broad insight into religious and academic fields, having life skills.

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.

Abstract Salmonella Typhi, a bacteria, is responsible for typhoid fever, a potentially dangerous infection. Typhoid fever affects a large number of people each year, estimated to be between 11 and 20 million, resulting in a high mortality rate of 128,000 to 161,000 deaths. This research investigates a robust numerical analytic strategy for typhoid fever that takes infection protection into consideration and incorporates fuzzy parameters. The use of fuzzy parameters acknowledges the variation in parameter values among individuals in the population, which leads to uncertainties. Because of their diverse histories, different age groups within this community may exhibit distinct customs, habits, and levels of resistance. Fuzzy theory appears as the most appropriate instrument for dealing with these uncertainty. With this in mind, a model of typhoid fever featuring fuzzy parameters is thoroughly examined. Two numerical techniques are developed within a fuzzy framework to address this model. We employ the non-standard finite difference (NSFD) scheme, which ensures the preservation of essential properties like dynamic consistency and positivity. Additionally, we conduct numerical simulations to illustrate the practical applicability of the developed technique. In contrast to many classical methods commonly found in the literature, the proposed approach exhibits unconditional convergence, solidifying its status as a dependable tool for investigating the dynamics of typhoid disease.

Abstract Hepatitis C infection and HIV/AIDS contaminations are normal in certain areas of the world, and because of their geographic overlap, co-infection can’t be precluded as the two illnesses have a similar transmission course. This current work presents a co-infection model of HIV/AIDS and Hepatitis C virus with fuzzy parameters. The application of fuzzy theory aids in tackling the issues associated with measuring uncertainty in the mathematical depiction of diseases. The fuzzy reproduction number and fuzzy equilibrium points have been determined in this context, focusing on a model applicable to a specific group defined by a triangular membership function. Furthermore, for the model, a fuzzy non-standard finite difference (NSFD) technique has been developed, and its convergence is examined within a fuzzy framework. The suggested model is numerically validated, confirming the dependability of the devised NSFD technique, which successfully retains all of the key properties of a continuous dynamical system.

The design and development of fluorescent materials for detecting cancer-related enzymes are crucial for cancer diagnosis and treatment. Herein, we present a substituted rhodamine derivative for the chromogenic and fluorogenic detection of the cancer-relevant enzyme γ-glutamyltranspeptidase (GGT). Initially, the probe is non-chromic and non-emissive due to its spirolactam form, which hinders extensive electronic delocalization over broader pathway. However, selective enzymatic cleavage of the side-coupled group triggers spirolactam ring opening, resulting in electronic flow across the rhodamine skeleton, and reduces the band gap for low-energy electronic transitions. This transformation turns the reaction mixture from colorless to intense pink, with prominent UV and fluorescence bands. The sensor’s selectivity was tested against various human enzymes, including urease, alkaline phosphatase, acetylcholinesterase, tyrosinase, and cyclooxygenase, and showed no response. Absorption and fluorescence titration analyses of the probe upon incremental addition of GGT into the probe solution revealed a consistent increase in both absorption and emission spectra, along with intensified pink coloration. The cellular toxicity of the receptor was evaluated using the MTT assay, and bioimaging analysis was performed on BHK-21 cells, which produced bright red fluorescence, demonstrating the probe’s excellent cell penetration and digestion capabilities for intracellular analytical detection. Molecular docking results supported the fact that probe-4 made stable interactions with the GGT active site residues.

Objective: To study the pattern of presentation, diagnosis and management outcome of ureteric injury sustained during obstetric and gynaecological surgery. Study Design: Case series. Place and Duration of Study: Armed Forces Institute of Urology Combined Military Hospital, Lahore Pakistan, from Nov 2010 to Nov 2020. Methodology: Eighty-three patients satisfying inclusion criteria (suspected ureteric injury after gynaecological/obstetric intervention) were included. Demographic details, primary surgeon, presenting features, diagnostic workup, treatment instituted, complications, and success were recorded and analyzed. Results: The study analyzed 83 patients with a mean age of 44.6±10.8 years and a mean parity of 3.4±1.4 children. The ovarian tumour was the most common cause of primary surgery (32, 38.6%), and the majority (64,77.1%) involved less experienced gynaecologists. Flank/abdominal pain was the main presentation (56, 67.5%), followed by oliguria. The left ureter was affected in the majority (58, 69.9%). Ureteric re-implant (37, 44.5%) and JJ stenting (33, 39.8%) constituted major urological interventions. Only three patients (3.6%) had surgical failure; two of them died, while one had redo surgery. Conclusion: Iatrogenic ureteric injury mostly follows radical gynaecological procedures and must be suspected in case of pain in the abdomen or vague constitutional symptoms after pelvic surgery. Management is dictated by location, time interval, diagnosis, and available surgical expertise.

Shiitake mushrooms are renowned for their popularity and robust nutritional value, are susceptible to spoilage due to their inherent biodegradability. Nevertheless, because of their lack of protection, these mushrooms have a short shelf life. Throughout the post-harvest phase, mushrooms experience a persistent decline in quality. This is evidenced by changes such as discoloration, reduced moisture content, texture changes, an increase in microbial count, and the depletion of nutrients and flavor. Ensuring postharvest quality preservation and prolonging mushroom shelf life necessitates the utilization of post-harvest preservation techniques, including physical, chemical, and thermal processes. This review provides a comprehensive overview of the deterioration processes affecting mushroom quality, covering elements such as moisture loss, discoloration, texture alterations, increased microbial count, and the depletion of nutrients and flavor. It also explores the key factors influencing these processes, such as temperature, relative humidity, water activity, and respiration rate. Furthermore, the review delves into recent progress in preserving mushrooms through techniques such as drying, cooling, packaging, irradiation, washing, and coating.

This research offers a thorough examination of thermal transmission within the context of the squeezing flow of a Casson fluid that is confined within two circular plates aligned in parallel. The development of a feasible mathematical framework involves combining the principles of conservation with appropriate similarity transformations. The resulting framework generates a couple of strongly non-linear ordinary differential equations. To tackle these equations, established analytical methods like the (HPM) and its variation, the Least Square Homotopy Perturbation Method (LSHPM), are employed.Additionally, for the validation of the analytical findings, a numerical approach using the BVP5C technique is utilized. A comparative evaluation reveals that the LSHPM consistently provides results of exceptional accuracy compared to the traditional HPM. The investigation delves into observing how the flow performs when experiencing diverse variations in physical attributes, elucidating the complexities through comprehensive visual representations. It is worth noting that the presented problem is subject to specific parameter limitations, which are extensively discussed and taken into account throughout the study. The investigation encompasses a thorough analysis across a range of parameters, including the squeeze number, the Casson fluid parameter, the Prandtl number, the Eckert number and. Notably, an acceleration in the rate of motion is observed concerning the squeeze number and the Casson fluid parameter. In terms of the temperature profile, it is revealed that this profile demonstrates a decreasing trend in relation to both the squeeze number and the Casson fluid parameter. Conversely, it displays an increasing trend with respect to the Prandtl number and the Eckert number.

Abstract Increasing insufficiency of freshwater resources is driving many countries in arid and semi-arid regions to use low-quality water for agriculture and related activities. This wastewater may have some useful as well adverse effects on various parameters. In this regard, we design an experimental setup to investigate the impact of irrigation with industrial wastewater on the Praecitrullus fistulosus (Indian baby pumpkin) plant. For this purpose, Praecitrullus fistulous was cultivated in soil irrigated with different concentrations (i.e. 25, 50, 75, 100%) of industrial wastewater, while control contain 0% of wastewater. Before the treatment, physicochemical parameters (pH, TDS, EC, etc.) of industrial wastewater were analysed. It was observed that lower concentration/s of wastewater positively affects various morphological (no. of leaves, fruits etc.) and biochemical (Total protein, Flavonoids, Sugar/s content etc.) attributes in treated plants, whereas elevated concentration may hurt these parameters.

Abstract The terms susceptibility, exposure, infectiousness, and recovered all have some inherent ambiguity because different population members have different susceptibility levels, exposure levels, infectiousness levels, and recovery patterns. This uncertainty becomes more pronounced when examining population subgroups characterized by distinct behaviors, cultural norms, and varying degrees of resilience across different age brackets, thereby introducing the possibility of fluctuations. There is a need for more accurate models that take into account the various levels of susceptibility, exposure, infectiousness, and recovery of the individuals. A fuzzy SEIR model of the dynamics of the measles disease is discussed in this article. The rates of disease transmission and recovery are treated as fuzzy sets. Three distinct numerical approaches, the forward Euler, fourth-order Runge-Kutta, and nonstandard finite difference (NSFD) are employed for the resolution of this fuzzy SEIR model. Next, the outcomes of the three methods are examined. The results of the simulation demonstrate that the NSFD method adeptly portrays convergent solutions across various time step sizes. Conversely, the conventional Euler and RK-4 methods only exhibit positivity and convergence solutions when handling smaller step sizes. Even when considering larger step sizes, the NSFD method maintains its consistency, showcasing its efficacy. This demonstrates the NSFD technique’s superior reliability when compared to the other two methods, while maintaining all essential aspects of a continuous dynamical system. Additionally, the results from numerical and simulation studies offer solid proof that the suggested NSFD technique is a reliable and effective tool for controlling these kinds of dynamical systems.The convergence and consistency analysis of the NSFD method are also studied.

The rapid increase in the application of carbon fiber-reinforced polymer composites in the fabrication and development of modern industrial products is attributed to their lightweight nature, excellent mechanical properties, and corrosion resistance, among other factors. Additive manufacturing of recycled carbon fiber (rCF), which has garnered significant attention in recent years owing to the massive potential waste obtained from carbon fiber-reinforced polymer composites (CFRPC) and the manufacturing of rCF after the surface treatment produced the parts with excellent properties comparable to virgin carbon fiber (vCF). Additive manufacturing of rCF obtained after recycling has received much interest over the past few years because of the massive potential waste of the carbon fiber and the excellent properties after the surface treatment of the rCF. This research examines additive manufacturing of the rCF, surface treatment for enhancing the properties of the printed specimens, the potential waste of the carbon fiber obtained from the different sectors, and applications of reclaimed carbon fiber composites in manufacturing various products. Specifically, the mechanical characteristics of the printed specimens using rCF and the different percentages of the rCF reinforcement in the other polymer's matrix composites are discussed. This work demonstrates that an additive manufacturing-based recycling approach can recycle carbon fiber-reinforced polymer composites (rCFRPC) waste and create high-performance engineering parts with complicated geometries that are both cost-effective and environmentally acceptable. This review also defines the significant challenges and outlook for future developments in manufacturing of rCFRPC.

The Ebola virus (EBOV) is a lethal pathogen causing hemorrhagic fever syndrome which remains a global health challenge. In the EBOV, two multifunctional proteins, VP35 and VP40, have significant roles in replication, virion assembly, and budding from the cell and have been identified as druggable targets. In this study, we employed in silico methods comprising molecular docking, molecular dynamic simulations, and pharmacological properties to identify prospective drugs for inhibiting VP35 and VP40 proteins from the myxobacterial bioactive natural product repertoire. Cystobactamid 934-2, Cystobactamid 919-1, and Cittilin A bound firmly to VP35. Meanwhile, 2-Hydroxysorangiadenosine, Enhypyrazinone B, and Sorangiadenosine showed strong binding to the matrix protein VP40. Molecular dynamic simulations revealed that, among these compounds, Cystobactamid 919-1 and 2-Hydroxysorangiadenosine had stable interactions with their respective targets. Similarly, molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations indicated close-fitting receptor binding with VP35 or VP40. These two compounds also exhibited good pharmacological properties. In conclusion, we identified Cystobactamid 919-1 and 2-Hydroxysorangiadenosine as potential ligands for EBOV that target VP35 and VP40 proteins. These findings signify an essential step in vitro and in vivo to validate their potential for EBOV inhibition.

Objective: This study examines the asymmetric impact of both internal (military, education, and health expenditures) and external (trade opening and foreign direct investment) factors that contribute to poverty reduction. Methodology: To find an asymmetric relationship between the proposed variables, we used a non-linear ARDL co-integration approach for the period ranging from 1981-2019. Findings: The findings of the study confirm the asymmetric impact of internal (education, military, health expenditures, quality of governance) and external (foreign direct investment, openness) factors on poverty. The finding confirms that ignoring nonlinear or asymmetric properties of macroeconomic variables may mislead inferences. This study has policy implications for government officials to reduce poverty. Novelty: theeconomic theory of poverty is studied from different perspectives by using internal and external factors that have direct and indirect effects on poverty. Furthermore, for in-depth analysis, a nonlinear approach is used to determine which factor has a strong contribution to eliminating poverty. Doi: 10.28991/ESJ-2023-07-03-07 Full Text: PDF

In this study, the abundant families of soliton solutions are constructed for the mussel-algae model which provides information about represents the concentration of algae in the water layer, and mussel biomass of sediment surface in the per square meter. These solutions are extracted in the form of shock singular, complex solitary-shock, shock-singular and periodic-singular. Also, the rational solutions are also emerged during the derivation. For these solutions we are used the new modified extended direct algebraic (NMEDA) technique. These solutions are gained by the help of Mathematica. Additionally, the physical behaviors of some solutions are shown for different values of parameters, the graphs in 3D-dimensions along with their contour diagrams are also drawn.

Drought is a complex natural hazard that occurs when a region experiences a prolonged period of dry conditions, leading to water scarcity and negative impacts on the environment. This study analyzed the recurrence of drought and wet spells in Baluchistan province, Pakistan. Reconnaissance Drought Index (RDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Vegetation Condition Index (VCI) were used to analyze droughts in Baluchistan during 1986-2021. Statistical analysis i.e. run theory, linear regression, and correlation coefficient were used to quantify the trend and relationship between meteorological (RDI, SPEI) and agricultural (VCI) droughts. The meteorological drought indices (1, 3, 6, and 12-month RDI and SPEI) identified severe to extreme drought spells during 1986, 1988, 1998, 2000-2002, 2004, 2006, 2010, 2018-2019, and 2021 in most meteorological stations (met-stations). The Lasbella met-station experienced the most frequent extreme to severe droughts according to both the 12-month RDI (8.82%) and SPEI (15.38%) indices. The Dalbandin met-station (8.34%) follows closely behind for RDI, while Khuzdar (5.88%) comes in second for the 12-month SPEI. VCI data showed that Baluchistan experienced severe to extreme drought in 2000, 2001, 2006, and 2010. The most severe drought occurred in 2000 and 2001, affecting 69% of the study region. A positive correlation was indicated between meteorological (RDI, SPEI) and agricultural drought index (VCI). The multivariate indices can provide valuable knowledge about drought episodes and preparedness to mitigate drought impacts.

Objective: To determine the 30-day morbidity and mortality after radical cystectomy in carcinoma urinary bladder using a validated system. Study Design: Retrospective longitudinal study. Place and Duration of study: Armed Forces Institute of Urology, Rawalpindi Pakistan, from Jun 2016 to Jul 2021. Methodology: After Institutional Ethical Review Board approval, data of all patients of carcinoma urinary bladder who underwent radical cystectomy during five years at Armed Forces Institute of Urology, was collected. Data was retrieved retrospectively from the hospital operative database, indoor patient records and by contacting the patients on their given telephone numbers. Results: In the study population (n=39), a male preponderance was found (36,92.3%). Mean age was 56.7±8.96 years (range 32-72). 26(66.7%) patients were smokers and 16(41%) received neoadjuvant chemotherapy. 9(23.7%) patients had Clavien-DindoGrade-I complications, 6(15.38%) had Grade-II, 2(5.12%) had Grade- IIIA, 2(5.12%) Grade IIIB, 1(2.56%) Grade-IVA, 1(2.56%)had Grade IVB, 2(5.12%) had Grade V complications. The total complications were 23(58.97%), and 16(41.03%) patients had nopost-operative complications. 21(53.85%) patients had less than 14 days post-op operative hospital stay, and 18(46.15%) hadmore than 14 days post-op operative hospital stay. Conclusion: Radical cystectomy is still associated with high early post-op mortality and morbidity. Careful patient selection and thorough counselling before the procedure are very important.

AbstractThe primary purpose of this research is to explain the importance of a significant aspect of a sustainable environment: green packaging. Green packaging has been revealed to have an astounding effect on a sustainable environment. Misuse of carbon products negatively affects the environment and pollutes the surroundings to a great extent, for which one feasible solution is green packaging. The phenomenon has been investigated using two independent variables: green packaging and multi-sensory packaging. Consumer environmental knowledge has been used as a mediating variable, and consumer perception has been used as a moderating variable, whereas the dependent variable is ecological sustainability. Current research is quantitative, and data were collected from 302 FMCG customers through a Self-Administered questionnaire survey. The research approach was deductive, and the nature of the study was explanatory. AMOS software and the Structural Equation Modelling (SEM) technique have been used to test the proposed hypotheses. According to the study’s findings, green packaging has a significant and positive effect on environmental sustainability, while multisensory packaging has a negative impact. Consumer perception positively moderates the relationship between green packaging and ecological sustainability. At the same time, consumer environmental knowledge had no mediating effect between green packaging, multisensory packaging, and ecological sustainability. This research fills the literature gap, as few studies exist on the relationship between green packaging and environmental sustainability. The mediating and moderating model has been tested for the first time in the FMCG sector of Pakistan. This study benefits manufacturers and marketers to know the importance of green packaging to enhance a sustainable environment. FMCG companies can use reusable and recyclable materials instead of substances like Plastic and Styrofoam for Packing, which is environmentally friendly and affordable for daily usage.

The United Nation's adaptation of the 2030 sustainable Development Goals (SDG) agenda has swung the attention toward sustainability. However, in achieving SDGs, this study investigates the nexus between agricultural productivity, renewable energy, ICT, human capital, CO2 emissions, and natural resources in a panel of ten European Union (EU) countries from 1996 to 2019. Our study uses the panel autoregressive distributed lag (ARDL) model of the Pool Mean Group (PMG) to estimate the long-run and short-run effects and heterogeneous causality approach. The empirical results ratify that a 1 % upsurge in the coefficient of renewable energy, ICT, and human capital increases agricultural productivity by 0.174 %, 0.030 %, and 2.158 % in the long run. Whereas, CO2 emission and natural resources decrease agricultural productivity. Finally, various causality exists among variables for EU countries. Our empirical results for the EU countries are notionally reliable and offer important policy implications accordingly.

Corona virus disease (Covid-19) which has caused frustration in the human community remains the concern of the globe as every government struggles to defeat the pandemic. To deal with the situation, we have extensively studied a deadly Covid-19 model to provide a deep insight into the disease dynamics. A mathematical analysis of the model utilizing preventive measures is performed with the aim to reduce the disease burden. Some comprehensive mathematical techniques are employed to demonstrate several essential properties of solutions. To start with, we proved the existence and uniqueness of solutions. Equilibrium points are stated both in the absence and presence of the pandemic. Biologically important quantity known as threshold parameter is computed to handle the future disease dynamics and analyzed for its sensitivity. We proved the stability of the proposed model at equilibrium points by employing necessary conditions on threshold parameter. A reliable and competitive numerical analysis is conducted to observe the effectiveness of implemented strategies and to verify obtained analytical results. The most sensitive parameters are determined through sensitivity analysis. An important feature of this study is to employ Non-Standard Finite Difference (NSFD) numerical scheme to solve the system instead of other standard methods like Runge–Kutta method of order 4 (RK4). Finally, several numerical simulations are performed to validate our former theoretical analysis. Numerical results exhibiting dynamical behavior of Covid-19 system under the influence of involved parameters suggest that both the implemented strategies, especially quarantine of exposed individuals, are effective for the substantial reduction in the diseased population and to achieve the herd immunity.

Abstract In this article, the ratio-dependent prey-predator system perturbed with time noise is numerically investigated. It relates to the population densities of the prey and predator in an ecological system. The initial prey-predator models only depend on the time and a couple of the differential equations. We are considering a model where the prey-predator interaction is influenced by both space and time and the need for a coupled nonlinear partial differential equation with the effect of the random behavior of the environment. The existence of the solutions is guaranteed by using Schauder’s fixed point theorem. The computation of the underlying model is carried out by two schemes. The proposed stochastic forward Euler scheme is conditionally stable and consistent with the system of the equations. The proposed stochastic non-standard finite difference scheme is unconditionally stable and consistent with the system of the equations. The graphical behavior of a test problem for different values of the parameters is shown which depicts the efficacy of the schemes. Our numerical results will help the researchers to consider the effect of the noise on the prey-predator model.

This article investigates the transmission of polio-virus disease in the human population. The classical model is considered for studying fatal disease. First of all, the model is converted into the fractal fractional epidemic model. Then, the existence of the solution for the said model is ensured with the help of the fixed point theory. Points of equilibria for the model are worked out. The basic reproduction number is described and its role in the disease communication and stability of the model is examined by some standard results. Simulated graphs are also plotted to support the pre-results and claims. Lastly, the findings of the study are presented.

This work attempts to study the numerical solution of nonlinear delayed Immunized Susceptible Latent Infected and Recovered (MSLIR) epidemic model of HBV disease. Reproduction number, equilibria and stability are discussed. Three different numerical techniques, Euler, RK-4 and the non-standard finite difference (NSFD) techniques are used for the numerical solution of the model. The proposed technique is independent of the size of the time step, while forward Euler and RK-4 depend on the size of a time step and retains all essential characteristics of the continuous MSLIR epidemic model like positivity and stability of equilibrium, while well-known forward Euler and RK-4 cannot sustain these characteristics. Therefore, the proposed (NSFD) technique becomes a more efficient and reliable numerical technique than the forward Euler and RK-4 scheme. Numerical simulations are presented for the validation of the obtained results.

Wireless sensor networks (WSNs) have gained much interest due to their enormous potential in civil and military applications. The power and radio communication capabilities of the sensor nodes are limited. Because sensor nodes have limited resources, they have weak defense capabilities and are attractive targets for software attacks. Worm-based cyberattacks are among the most significant threats to computers and WSNs’ security and integrity. In this article, a five-compartmental WSN epidemic model is considered. We conducted an investigation into equilibrium analysis and the reproductive number, followed by the development of a nonstandard finite difference numerical scheme for our model. The outcomes of our numerical simulations are then presented. This method yields reliable predictions, which can be valuable for regulators when making decisions related to designing and implementing control strategies. Furthermore, some interesting properties of the developed scheme are investigated, such as positivity, convergence, and consistency. The developed scheme preserves the essential characteristics of disease epidemic models like positivity, convergence, and consistency.

Zika virus infection is a vastly transmitted disease among humans. It was carried worldwide by international travelers. In 2016, Zika virus infection was present in more than 20 countries and territories in America. Thousands of cases were diagnosed in Cabo Verde, western Africa. Fifty-seven regions suffered from Zika virus in 2020, and the World Health Organization reported more than one hundred thousand cases worldwide. In this work, the modeling and transmission dynamics of Zika virus are studied dynamically and numerically. Positivity, boundedness, reproduction number, equilibria, and local stability are part of the numerical analysis. New nonstandard numerical techniques are examined for the said model. The primary purpose is to maintain the continuous model’s behavior and dynamical properties. The proposed nonstandard finite approximation is studied according to the consistency and local stability of the solutions. Some numerical examples clearly show the improvement of the new schemes compared to other well-known methods.

While the significance of cross-cultural research has been acknowledged over time, there remains a gap in understanding its relationship with employee outcomes. This study delves into the associations between organizational trust climate (TC) and job performance (JP), as well as turnover intention (TI), seeking to ascertain if work engagement (WE) plays a mediating role. Additionally, the research investigates potential differences in the mediating effect between China and Pakistan. Data gathered from 270 participants in China and 242 in Pakistan were subjected to structural equation modeling (SEM) for analysis. Findings indicated that perceptions of individual WE serve as a bridge between organizational TC and JP, with the effect on JP being notably stronger among the Chinese participants. Moreover, the mediating role of WE in the link between organizational TC and TI was more pronounced for the Pakistani participants. On a practical front, such insights can equip managers with a nuanced understanding of the ripple effect that a trust-infused environment can have on employee engagement, subsequently influencing performance and retention rates.

This work investigates the computational study of a six-compartmental mathematical model of tuberculosis disease dynamics with the impact of vaccination. Traditional mathematical models presume that all variables are precise and can be measured or calculated precisely. However, in many real-world scenarios, variables may need to be more accurate or easier to quantify, resulting in model uncertainty. Considering this, fuzziness is introduced into the model by taking the contact, recovery, and death rates due to disease as fuzzy membership functions. Two numerical computational schemes, forward Euler and nonstandard finite difference (NSFD), are designed to solve the model. The positivity and convergence for the developed method are investigated, which are significant characteristics of these dynamical models, and it is revealed that these features are preserved in the extended scheme. Numerical computations are performed to support the analytical results. The numerical and computational results indicate that the proposed NSFD method adequately represents the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to design and develop control strategies to support decision-making.

Water, especially drinking water, should be clean and free of disease-causing bacteria because of its critical role in life. However, it isn’t easy to identify and classify them rapidly at an early stage. Primarily, the examination of water is performed manually to check the contamination level. Some researchers have proposed techniques to detect and classify bacteria images, but this field still needs more attention. In this research work, a robust Quantum Convolutional Neural Network (QCNN) classification model is proposed to classify the six major categories of pathogenic bacteria. For the acquisition of pathogen images, different slides are created through the gram-staining process, and then images are captured from those slides. DIBaS is the publicly available dataset that provides these slides captured through gram-staining, which is used to evaluate the proposed methodology. So, in the first step, database preprocessing, small patches are extracted from slide images. However, the extracted patches were not clear and very useful, so the Enhanced Super-Resolution Generative Adversarial Network Model (ESRGAN) was applied to images to improve the image quality of extracted patches. The third step is to extract the deep features and classify bacterial images using the QCNN model, in which the Quantum Convolutional layer is added, and classical data is converted into quantum data to perform classification. Based on the results of classification experiments using the QCNN model, the accuracy is 96.54%.

A thorough analysis and comprehension of the entire cue set in visual data are indispensable for an ideal video description model. As outlined in recent algorithm proposals, video descriptions have primarily been generated by learning RGB and optical flow representations rather than exploring and incorporating the media’s spectral components referring to the patterns or characteristics in the distribution of colors or intensities across different frequencies or wavelengths of light. These components may enhance the description quality and impact the generated text for accuracy, diversity, and coherence. We propose a novel Fourier-based algorithm for extracting spectral features in 3D visual volume by decomposing the video signal into its frequency components, to fill this research gap. Further, the captured spectral features are fused with learned spatial and temporal representations in recurrent transformer architecture for accurate content understanding and appropriate description generation in natural language. The transformer includes an external memory module that produces summarized memory states based on the history of previously observed video fragments and already-generated sentences. These memory states ensure the establishment of sound semantic and linguistic cues. As a result, our proposed algorithm integrates spatial, temporal, spectral, and semantic representations for precise and grammatically accurate descriptions. The effectiveness of our proposed algorithm for the coherent and diverse video description is demonstrated through qualitative and quantitative experimentation on the DeepRide driving trip description dataset. A comprehensive ablation study validates the efficacy of the spectral features fusion with spatial and temporal visual representations for the rich video-to-textual narration generation.

This article deals with coupled nonlinear stochastic partial differential equations. It is a reaction-diffusion system, known as the stochastic Gray-Scott model. The numerical approximation of the stochastic Gray-Scott model is discussed with the proposed stochastic forward Euler (SFE) scheme and the proposed stochastic non-standard finite difference (NSFD) scheme. Both schemes are consistent with the given system of equations. The linear stability analysis is discussed. The proposed SFE scheme is conditionally stable and the proposed stochastic NSFD is unconditionally stable. The convergence of the schemes is also discussed in the mean square sense. The simulations of the numerical solution have been obtained by using the MATLAB package for the various values of the parameters. The effects of randomness are discussed. Regarding the graphical behavior of the stochastic Gray-Scott model, self-replicating behavior is observed.

In this article, an analytical and numerical analysis of a computer virus epidemic model is presented. To more thoroughly examine the dynamics of the virus, the classical model is transformed into a fractional order model. The Caputo differential operator is applied to achieve this. The Jacobian approach is employed to investigate the model's stability. To investigate the model's numerical solution, a hybridized numerical scheme called the Grunwald Letnikov nonstandard finite difference (GL-NSFD) scheme is created. Some essential characteristics of the population model are scrutinized, including positivity boundedness and scheme stability. The aforementioned features are validated using test cases and computer simulations. The mathematical graphs are all detailed. It is also investigated how the fundamental reproduction number $ \mathfrak{R}_0 $ functions in stability analysis and illness dynamics.

Epidemiology is the study of how and why an infectious disease occurs in a group of people. Several epidemiological models have been developed to get information on the spread of a disease in society. That information is used to plan strategies to prevent illness and manage patients. But, most of these models consider only random diffusion of the disease and hence ignore the number of interactions among people. To take into account the interactions among individuals, the network approach is becoming increasingly popular. It is novel to consider the dynamics of infectious disease using various networks rather than classical differential equation models. In this paper, we numerically simulate the Susceptible-Infected-Recoverd (SIR) model on Barabási-Albert network and Erdös-Rényi network to analyze the spread of COVID-19 in Pakistan so that we know the severity of the disease. We also show how a situation becomes alarming if hubs in a network get infected.

The outburst of COVID-19 epidemic has enforced the higher education sector to revamp customary mode of teaching and assessing students learning. This study is a portrayal of online education and intended to critically examine how online education during COVID-19 fostered a combination of favorable and unfavorable outcomes which might disrupt and redesign academic routine process. Data were collected from professors, associate professors and rectors affiliated with higher education system through focused group discussions and semi-structured interviews. The interpretivism paradigm analysis was performed to examine the data using qualitative methodology. This study delivers a comprehensive review of enduring online education mode through the lock-down tenure. It outlines details on how quality of education was ensured through online teaching-learning process, E-portal access, self-reliant technological system, online assessment, and quality standards. Findings delineated that higher education sector converted challenge into opportunity without wasting students semester and facilitated them in achieving academic quality, thereby overcoming the continuous academic distortion and subsequently ensuring the renewal of educational procedures. Results also reported numerous challenges faced by teachers and management in delivering quality education. This research refills the existing gap by adding to the literature on online education from the perspectives of key academias concerns during the COVID-19 epidemic. It also provides practical implications to governing bodies and policy makers of higher education sector

Leishmaniasis is a group of contagious diseases having high surveillance among dogs. According to World Health Organization (WHO), ninety-two territories were infected around the world in 2018. One billion dogs live in areas endemic for Leishmaniasis and are at risk of infection. Almost one million cases are reported annually. The dog's population is categorized into five classes like susceptible (S), latent (L), infectious (I), uninfected (R), and infected (Q). The Leishmaniasis delayed model is developed to analyze and control its spread. Equilibria, positivity, boundedness, reproduction number, and parameter sensitivity are the model's essential features. The stability of the model is investigated in a local and global sense with the help of the Routh Hurwitz criterion and Lyapunov theory. In the end, simulations are presented to verify the theoretical analysis of the delayed model.

This article presents the dynamical analysis of the stochastic leprosy epidemic model. Positivity and boundedness are the criteria used in the deterministic model. A primary technique is known as the Euler Maruyama used in the solution of the said model. The standard computational methods will evaluate the design stability and efficiency based on the chosen criteria. The traditional computational methods like the stochastic Euler and the stochastic Runge Kutta fail to restore the essential features of biological problems. However, our proposed approach, the stochastic non-standard finite difference (NSFD), is used and found to be efficient, cost-effective, and accommodates all the desired feasible properties. Our method achieves all-time convergence against the backdrop of other classical techniques that perform conditionally or fail over a long period. In the end, a comparison between this scheme and the existing ones reviews the novelty of our approach.

The sowing date is very crucial among agronomic techniques for ensuring productivity and controlling insect pest. In 2018 and 2019, sowings were carried out 15 days intervals, starting on March 1 and ending on June 16. The dates were: March 1, March 16, April 1, May 1, May 16, and June 1. On advanced cultivars of Bt cotton, namely MNH-1026, MNH-1050, and IUB-13, the whitefly, Bemisia tabaci (Aleyrodidae: Hemiptera), and beneficial/predatory fauna were researched (control). The statistical analysis was multivariate. The relationship between the predatory fauna and the prey (whiteflies) in the correlogram was favourable. Predators showed a positive association with whitefly (0.592), boll weight (0.681), boll number (0.872), and seed cotton production (0.886) per acre, in that order. It was determined through Principal Components Analysis (PCA) that PC1 had an Eigen value >1 and accounted for 79.3% of the overall variation due to the greatest positive loading vectors. It was determined that because late planting had a short growing period, whiteflies attacked it less frequently. It was determined that short-season crop cultivation and the breeding of resistant germplasm are advantageous in the face of climate change.

This study employing a non-standard computational method for a stochastic anthrax epidemic model can enhance accuracy, evaluate control measures, and identify critical factors. The mathematical modeling of an anthrax disease includes the four-compartment of the population as susceptible animals (s), infected animals (i), carcasses animals (c), and grams spores of animals in the environment (a). The continuous model analysis (equilibria, reproduction number, and local stability of equilibria) is studied rigorously. The stochastic model is based on transition probabilities and parametric perturbation techniques. The fundamental properties of the model with standard computational methods such as Euler Maruyama, stochastic Euler, and stochastic Runge Kutta are studied. Unfortunately, these methods are time-dependent and even valid for short-period analysis of the disease. In comparison, the non-standard computational method, like the non-standard finite difference method nonstandard finite difference in the sense of stochastic, is designed for the given model. The non-standard computational method and its dynamical properties (positivity, boundedness, and dynamical consistency) are studied thoroughly. In the end, numerical results of the non-standard computational method with the existing standard computational methods are provided. These benefits contribute to a more comprehensive understanding of anthrax epidemiology and support effective decision-making in public health interventions.

In recent decades, the mathematical modeling of infectious diseases, real-world problems, non-linear dynamical complex systems, etc., has increased significantly. According to World Health Organization, tobacco use is the cause of about 22% of cancer deaths. Another 10% are due to obesity, poor diet, lack of physical activity, and excessive drinking of alcohol. Approximately 5%–10% of cancers are due to inherited genetic defects. The objective is to investigate the impact of time delays in implementing control measures on the epidemic dynamics. The classification of cell population has four compartments: susceptible cells (x), cancer-infected cells (y), virus-free cells (v), and immune cells (z). Our focus is to find the equilibria of the problem and their stability. The stability of the solutions is of two types: locally asymptotic and globally asymptotic. The Routh–Hurwitz criterion, Volterra-type Lyapunov function, and LaSalle’s invariance principle are used to verify the stability of solutions. The graphical behavior depicts the stable solutions to a real-world problem and supports the stability analysis of the problem. The findings contribute to the understanding of epidemic dynamics and provide valuable information for designing and implementing effective intervention strategies in public health systems.