In this paper, we consider a new class of polynomials which is called the multi-poly-Euler polynomials. Then, we investigate their some properties and relations. We provide that the type 2 degenerate multi-poly-Euler polynomials equals a linear combination of the degenerate Euler polynomials of higher order and the degenerate Stirling numbers of the first kind. Moreover, we provide an addition formula and a derivative formula. Furthermore, in a special case, we acquire a correlation between the type 2 degenerate multi-poly-Euler polynomials and degenerate Whitney numbers.

Solid asperity interactions are common and inevitable under severe loading conditions for any lubricated contact. Heavy-duty machine components (gear, bearings etc.) generally operate under Mixed Lubrication, where uneven surface features contact each other when generated fluid pressure is not enough to support the external load. The Reynolds equation is commonly used to simulate smooth lubricated contacts numerically. In rough lubricated interfaces where opposite surface asperities make contact, the Reynolds equation alone cannot accurately predict pressure using the traditional numerical simulation method. In this paper, Lubrication-Contact interface conditions (LCICs) have been implemented and extended to solve the multiple asperity contact problem using the full-multigrid approach. The developed novel algorithm has significantly accelerated the solution process and improved the accuracy and efficiency of pressure calculation for fluid-solid sub-interactions that can occur under ML regions. The Finite Difference Method (FDM) results have been compared with Computational Fluid Dynamics (CFD) simulation to validate the newly developed model. Hence, the proposed optimized solution method will provide valuable insight to researchers and industry engineers interested in simulating the ML problem where the effect of the fluid-solid interface can be captured effectively to improve reliability in the calculation of the life expectancy of the lubricated parts.

In the present paper, the (p,q)-Hermite based Apostol type Frobenius-Euler polynomials and numbers are firstly considered and then diverse basic identities and properties for the mentioned polynomials and numbers, including addition theorems, difference equations, integral representations, derivative properties, recurrence relations. Moreover, we provide summation formulas and relations associated with the Stirling numbers of the second kind.

In this paper, a new class of q-Hermite based Frobenius type Eulerian polynomials is introduced by means of generating function and series representation. Several fundamental formulas and recurrence relations for these polynomials are derived via different generating methods. Furthermore, diverse correlations including the q-Apostol-Bernoulli polynomials, the q-Apostol-Euler poynoomials, the q-Apostol-Genocchi polynomials and the q-Stirling numbers of the second kind are also established by means of the their generating functions.

We introduce a new kind of extended Hermite-based Frobenius type Eulerian polynomials and then derive diverse explicit and implicit summation equations including some symmetric formulas by utilizing series manupulation method. Multifarious summation formulas and identities given earlier for some well known polynomials such as Eulerian polynomials and Frobenius type Eulerian polynomials are generalized.

Organizational diagnosis (OD) is a comprehensive review of an organization's objectives, re-source allocation, and utilization to achieve those objectives. This study employed OD to en-hance the effectiveness of the Department of Special Education within the Government of Punjab. A questionnaire based on Weisbord's six-box organizational model called the Organ-izational Diagnostic Questionnaire (ODQ), was administered to N=1200 participants, consist-ing of heads of top, middle, and bottom tiers at district and tehsil levels of special education schools, centers, and the main office. Out of these, 506 participants voluntarily completed the ODQ survey. The study findings indicated that the employees of the department possess a good understanding of the organization's objectives. However, there is a lack of opportunities for employee participation in departmental discussions, centralized decision-making, irra-tional task distribution, and unsupportive allocation of human resources. Additionally, there is poor communication, unsatisfactory promotions, incentives, and a lack of knowledge shar-ing among employees, as well as poor inter-relationships, conflicts, and ineffective help-seeking mechanisms. The study also revealed low readiness for change in the organization. Respondents' opinions differed significantly based on their qualifications, job experience, years served, and gender. To improve the department's capacity to absorb change, the study recommends enhancing collaboration and inter-departmental communication, soliciting comprehensive input from all tiers, and promoting employee participation, supportive supervision, and communication. The study contributes to the body of knowledge on OD and highlights the need for improved communication, collaboration, and employee participation, as well as a supportive and supervisory support system to enhance the effectiveness of organizations.

The development of quantum computers seeks software developers' attention regarding security in the era of Information Technology, software security is the primary goal for our quantitative assessment of software security in the development cycle of software. Security assessment of software is identifying the key security factors of the software. A security elective provides ex-tensive strategies and calculations to ensure product safety. The security assessment is the key factor in surveying, administering, and controlling security to further enhance the nature of safety. It should be acknowledged that assessing security early on in the development process is beneficial in identifying worms, hazards, flaws, and threats. The definition and portrayal of Quantum Computing (QC) in software security will be discussed in this study. Researchers use cryptography calculations to secure our financial institutions, medical devices, military weaponry, planes, ships, vehicles, and pilots. Here authors of this study use the Fuzzy Technique for Order Preference by Similarity to Ideal Situation (FTOPSIS) to quantitatively assess the weight/rank of the quantum enable security alternatives like (Diffie-Hellman key-exchange algorithm, Quantum key distribution algorithm, Deutsch-Jozsa Algorithm, Special Deutsch-Jozsa Algorithm, Grover’s Algorithm and Quantum key distribution algorithm in GHZ state) with security factors like (Confidentiality, Integrity, Authenti-cation, Privacy, Reliability, Maintainability, Authorization, Integrity, Possessions, and Availability). Additionally, they critically analyze and select the six alternatives of quantum-based security algorithms. The nature of safety infers the ability to execute a thing on time in this exploration study, specifically 'software security'.

The current study was formulated with the aim of assessing the impact of the Extent of Drug addiction on the Family environment and interventions for drug-addicted youth in rural areas of Dir Lower Khyber Pakhtunkhwa, Pakistan. The study comprised a dependent variable (Extent of Drug addiction) and an independent variable (Family Environment). A sample size of 266 was randomly selected for primary data collection through structured interviews. The collected information was evaluated through descriptive analysis (frequency and percentage distribution) and inferential analysis, specifically utilizing the Chi-square Statistical Test. The study concluded that drug addiction among youth has an adverse impact on the family environment, leading to instability and violent behavior. Further, families of drug-addicted youth experience a high level of dissatisfaction in relationships, often culminating in divorce. Similarly, the families of drug-addicted are characterized by low cohesion, role conflict, and tolerance. Thus, the government should formulate polices and strategies for the prevention of drug addiction, with speedy implementation across all institutional dynamics, including family. Moreover, It is also crucial to rehabilitate the lifeblood of a nation (youth) in terms of socio-economic, emotional and psychological growth. These recommendations were put forward in the light of the current study.

This study was to designed to develop sorafenib-loaded polymeric nanoparticles, surface-modified with pluronic F-127 for the effective treatment of hepatocellular (HCC) and renal cell carcinomas (RCC). Poly lactic coglycolic acid (PLGA) was used to encapsulate different concentrations of sorafenib by a simple modified solvent evaporation method applying pluronic F-127 as a surfactant and coating agent. The preformulation and characterization studies were conducted to evaluate the incompatibilities among sorafenib, PLGA and pluronic F-127, and physicochemical properties of the formulations, respectively. The sizes of the coated and plain PLGA nanoparticles were ~140 ± 14.7 nm and ~ 120 ± 10.1 nm, respectively. It has been confirmed from the in vitro release studies that PLGA sustained the release of sorafenib, avoiding the initial burst release, while the in vivo studies demonstared that surface-modified nanoparticles have greater affinity in the target aorgans than plain PLGA nanoparticles and free drug keeping the dose constant (20 mg/kg body weight). The delivery of sorafenib-loaded polymeric PLGA nanoparticles into the target tissues and their pharmacokinetic parameters have been improved significantly compared to the reported formulations.

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

Potentilla nepalensis belongs to the Rosaceae family, and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in our earlier studies. However, the PCs affecting human genes and their roles in the body are not disclosed till now. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDS), and MMGBSA methodologies. SMILES format of PCs from the PubChem used as input to DIGEP-Pred, 764 identified as the inducing genes. Their enrichment studies have shown inducing genes gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analysing parameters done in Cytoscape v3.10 revealed three biomarkers, TP53 from MS, NR, and NS induced genes; HSPCB and Nf-kB1 from MR induced genes. From 40 PCs, two PCs 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6, and -8.0; three PCs 3a, (NR) 4a and 4c (NS) with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Biomarkers identified in this study, have a prominent role in numerous cancers. Thus, further investigations such as in-vivo and in-vitro should be done to find the molecular functions and interlaying mechanism of the identified biomarkers on numerous cancer cell lines in considering the PCs of P.nepalensis.

Background: The proportion of dietary protein may play a key role in the development of obesity in children and adolescents. Methods: Cross-sectional data of 4,336 children and adolescents from the National Health and Nutrition Survey (NHANES) during 2011 to March 2020 were analyzed. Multivariate logistic regression analysis was used to estimate odds ratios (OR) and 95% confidence intervals, and restriction cubic spline was uesd to explore nonlinear relationships of dietary protein energy supply ratio and obesity in children and adolescents. Results:In the adjusted logistic regression model, for every 1% increase in dietary protein energy ratio in children and adolescents, the increased risk of obesity was 4% (OR=1.04,95%CI:1.01-1.08). The restrictive cubic spline showed a nonlinear relationship between dietary protein energy ratio and obesity in children aged 6-11 years (P <0.05). The dietary protein energy supply ratio was included in the logistic regression model after converting to quartiles into categorical variables. The adjusted OR of children aged 6-11 years was 2.08 (95%CI:1.34, 3.23,P <0.01) for the highest quartile of dietary protein energy supply ratio compared with the lowest quartile. Conclusion: In American children, dietary protein energy supply ratios was positively correlated with obesity, independent of individual characteristics and energy.

Introduction: In the marginalised countries most neglected health issue is Newborn mortality. A study was undertaken to assess the influence of factors and newborn care practices influencing newborn health in the rural area of Bareilly district. Methodology: The Descriptive cross-sectional study was organized in the rural areas of Bareilly. Study participants were selected based on the mothers who gave birth to a baby during the last six months. The mothers who delivered in that area within six months were included, and using the semi-structured questionnaire, data was collected. Data analyzed using Microsoft Excel and SPSS 2021 version for windows. Results: Mothers initiating early breastfeeding were more commonly 78 (52.3%) observed in the younger mothers at 24-29 years, followed by 48(32.3%) at 30-35 years, the difference was statistically significant (p<0.05). Delayed bathing was observed in nearly 125 (70.1%) three fourth in the age of 24-29 years, followed by 29 (16.8%) in the age period 30-35 years. It was observed that unsafe cord care practices were observed more among 8(53.4%) nuclear families than 7(46.6%) joint families, and it was found to be statistically insignificant. Conclusion: The practice of essential newborn care still needs to improve in Bareilly; there is a need to create awareness to the mothers and family members on newborn and early neonatal care aspects, such as promoting exclusive and early initiation of breastfeeding and delayed bathing practices.

Hydrogels can provide instant relief to pain and facilitate the fast recovery of wounds. Currently the incorporation of medicinal herbs/plants in polymer matrix is being investigated due to their anti-bacterial and wound healing properties. Herein, we investigated the novel combination of chitosan (CS), chondroitin sulfate (CHI) and garlic (Gar) to synthesize hydrogels through freeze gelation process for faster wound healing and resistance to microbial growth at the wound surface. The synthesized hydrogels were characterized via Fourier transform infrared spectroscopy (FTIR), which confirmed the presence of relevant functional groups. The scanning electron microscopy (SEM) images exhibited the porous structure of the hydrogels, which is useful for the sustained release of Gar from the hydrogels. The synthesized hydrogels showed significant inhibition zones against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). Furthermore, cell culture studies confirmed the cyto-compatibility of the synthesized hydrogels. Thus, the novel hydrogels presented in this study can offer antibacterial effect during wound healing and promote tissue regeneration.

Introduction: Child stunting remains a public health concern. It is characterized as poor cognitive and physical development in children due to inadequate nutrition during the first 1,000 days of life. Across South Asia, Pakistan has the second-highest prevalence of stunting. This study has assessed the most recent nationally representative data, the National Nutrition Survey (NNS) 2018, to identify the stunting prevalence and determinants among Pakistani children under five. Methods: The NNS 2018, a cross-sectional household-level survey, was used to conduct a secondary analysis. Data on malnutrition, dietary practices, and food insecurity was used to identify the prevalence of stunting among children under five years by demographic, socioeconomic, and geographic characteristics. The prevalence of stunting was calculated using the World Health Organization (WHO) height for age z-score references. Univariate and multivariable logistic regressions were conducted to identify factors associated with child stunting. Results: Analysis showed that out % of 52,602 children under five, 40.0% were found stunted. Male children living in rural areas were more susceptible to stunting. Furthermore, stunting was more prevalent among children whose mothers had no education, were between 20 and 34, and were employed. In the multivariable logistic regression, male children (AOR=1.08, 95% CI[1.04-1.14], P<0.001) from rural areas (AOR=1.07, 95% CI [1.01-1.14], P=0.014), with the presence of diarrhea in the last two weeks (AOR=1.15, 95% CI [1.06-1.25], P<0.001), with mothers who have no education (AOR=1.57, 95% CI [1.42-1.73], P<0.001) or lower levels of education (Primary: AOR=1.35, 95% CI [1.21-1.51], P<0.001; Middle: AOR=1.29, 95% CI [1.15-1.45], P<0.001) had higher odds of stunting. Younger children aged <6 months (AOR=0.53, 95% CI [0.48-0.58], P<0.001) and 6-23 months (AOR=0.89, 95% CI [0.84-0.94], P<0.001), with mothers aged 35-49 years (AOR=0.78, 95% CI [0.66-0.92], P=0.003) had lower odds of stunting. At the household level, the odds of child stunting were higher in the poorest households (AOR=1.64, 95% CI [1.46-1.83], P<0.001), with ≥7 members (AOR=1.09, 95% CI [1.04-1.15], P<0.001), with no access to improved sanitation facilities (AOR=1.14, 95% CI [1.06-1.22], P<0.001) and experiencing severe food insecurity (AOR=1.07, 95% CI [1.01-1.14], P=0.02). Conclusion: Child stunting in Pakistan is strongly associated with various factors, including gender, age, diarrhea, residence, maternal age and education, household size, food and wealth status, and access to sanitation. To address this, interventions must be introduced to make locally available food and nutritious supplements more affordable, improve access to safe water and sanitation, and promote female education for long-term reduction in stunting rates.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.