Mohi-ud-Din Islamic University

The research question is the ways in which socioeconomic status of parents affects access of and utilization of digital academic services by the university students and their satisfaction with the services and challenges they face in the institutions of higher learning in Azar Jammu and Kashmir (AJK), Pakistan. This work is the result of increased importance of the digital tools in the academic use as well as the overall trend of the digital divide which seems to be correlated with socioeconomic differences. A sample size of 124 university students was picked and the structured questionnaire was carried to them, chosen of various backgrounds. It gathered socio-demographic variables, SES variables (parents education level, occupation, and household income), and digitization access variables (ownership of devices, availability of internet, frequency of use, and number of hours of use per day) and variables of satisfaction (perceived effectiveness, effects of performance, and availability). The initial descriptive statistics was that students who belonged to higher SES families possessed their own personal devices, had good access to internet, and used the digital resources more often than those belonging to lower SES-groups. Chi-square test and ANOVA tests revealed that the digital satisfaction and internet access were dependent on income and education. Lastly, the level of SES groups experienced a higher number of barriers such as financial and lack of connectivity, as well as institutional support that added to the structural discrimination of digital access. The results indicate that this should be done through policy formulation, the institutional investments in infrastructures and developing insights in digital literacy so that the accrued benefits of the entire population can be equally obtained by all and inclusive in accessing to digital educational materials.

In the field of geometric function theory, we use the ( p , q )‐differential operator in the complex unit disk to describe a novel class of symmetrical starlike functions of order η . Several interesting properties of functions belonging to the class are examined, such as growth, distortion, and convolution characteristics.

The widespread use of cosmetic products has raised global concerns regarding their potential toxicity, particularly the heavy metals content. While cosmetics serve economic and aesthetic purposes, their health implications, especially in underdeveloped regions, are becoming increasingly evident. This study investigates the level of toxic heavy metals in both branded and local cosmetic products available in the remote area of Trarkhel, District Sudhnoti, Azad Jammu and Kashmir (AJK), Pakistan, where specific data on cosmetic contamination with heavy metals and associated health risks are lacking. The presence of these metals, whether as intentional additives or impurities from raw materials, is particularly pronounced in unregulated, locally produced, and potentially counterfeit imported cosmetics, posing significant public health challenges. A total of 30 cosmetic samples, comprising lipsticks, foundations, eye shadows, nail polishes, and others, were analyzed using Atomic Absorption Spectroscopy (AAS-700) to determine the levels of lead (Pb), cadmium (Cd), copper (Cu), cobalt (Co), silver (Ag), nickel (Ni), Arsenic (As), manganese (Mn) and mercury (Hg). On comparative basis, different brands of lipsticks contain the highest mean concentrations (mg/kg) of Ni (89.3 ± 0.39), Mn (79.8 ± 0.03), Cu (62.1 ± 0.04), Pb (23.3 ± 0.05), Co (13.8 ± 0.03), Cd (1.35 ± 0.01) and Ag (0.73 ± 0.01), whereas branded and local creams had elevated level of Hg (358.53 ± 0.02) followed by Zn ( 1181 ± 0.04), Co (28.9 ± 0.04), Ni (11.0 ± 0.04), Pb (6.21 ± 0.06) Cu (3.52 ± 0.01), As (1.56 ± 0.01), and Cd (1.35 ± 0.01) mg/Kg, with least concentration in Mn and Ag. The level of heavy metals was lower in nail polishes compared to lipsticks and creams. Multivariate analysis suggested a strong correlation among Pb, Cu, Ni, Cd, and Mn, while Cd showed a negative correlation with Co, Ag, and As, and Mn, indicating disparity in distribution and sources of contamination. Health risk assessment further revealed that Margin of Safety (MoS), Hazard Quotient (HQ), and Hazard Index (HI) values fell above the permissible boundaries for most of the lipsticks, creams, and nail polishes. Regarding carcinogenicity, LCR values surpassed the established threshold in all cosmetic products with the exception of lipsticks. The findings emphasise the urgent need for routine monitoring and enforcing strict quality assurance protocols to safeguard the safety of cosmetics, particularly in vulnerable and underdeveloped areas like Trarkhel. This study not only fills a crucial research gap but also provides a foundation for future studies on cosmetic toxicity and public health awareness in rural regions.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-30439-x.

Enhanced heat transport in triangular fins have promising applications in heat exchangers, electronics cooling, automobile radiators and power plants etc. Use of nanolubricants is an innovative way to enhance the performance of triangular fin. Thus, this work aims to analyze the triangular fin’s performance coated with hybrid nanolubricant (SiC–Co3O4)/diathermic oil and investigate that how the active parameters radiation, convective-conduction, porosity and heating source affect the performance. The formulation is accomplished using the energy equations together with enhanced characteristics of SiC–Co3O4 and diathermic oil. As a result, the second order model obtained. The artificial intelligence (AI) based scheme levenberg marquardt back-propagation (LMBP) method implemented. Further, the results for the model furnished using feasible ranges of the parameters. Authenticity of the scheme is verified through histogram error, functions fitting, regression analysis and validation checks. It is examined that the device can be maintained at low temperature by augmenting the conduction parameter from 1.0 to 4.0. Optimum heat transfer is acquired when the heating source Q and Peclet number Pe increased. Presence of pores at the triangular fin’s surface would be advantageous to cool the device. In conclusion, the use of hybrid nanolubricant subject to radiations, heating source, and porosity effects together with AI scheme provided beneficial results regarding the transport of heat using triangular fin.

Background: The rapid adoption of Artificial Intelligence (AI) is changing the library and information services and automates the main processes and introduces new principles of user interaction and accessibility. This change in technology requires librarians to acquire another set of competencies that are related to AI in order to be relevant and effective. Nonetheless, there is a wide disparity between the established potential of AI and the AI literacy and skills that present-day library professionals possess. Objectives: The research will aim to explore the skills in artificial intelligence every contemporary library should possess, evaluate the current extent of AI in libraries and awareness, and reveal the major obstacles that prevent its use. The study aims at developing plans of improving AI literacy and professional growth in the area. Methods: In this study, a quantitative cross-sectional research design was adopted, where the study involved the application of a structured questionnaire to 104 library professionals. The survey tool included demographic variables and a five-point Likert scale gauging the perceptions of the participants in three areas, i.e., awareness of AI, self-reported AI skills, and difficulties in integrating AI. Data analysis was done using descriptive statistics. Results: Results show that there is a high level of optimism about AI in improving affairs in libraries and eliminating workload. Nevertheless, there was also a high level of a confidence gap, and self-reported proficiency in such main areas as AI-based cataloging, data analytics, and chatbot management were low. Although the ethical issues and the lack of technical expertise were mentioned as the key obstacles, the early introduction of AI tools in libraries is still in its infancy. It was overwhelmingly stated that most of the respondents were willing to learn and they needed more professional development. Conclusion: The conclusion of the study is that Librarians have a positive attitude towards AI, but a significant skills gap and moral issues prevent its successful implementation. To bridge this gap, targeted training programs, modernization of LIS curricula, and the development of ethical frameworks are urgently recommended. Empowering librarians with AI literacy is crucial for the evolution of user-centric, efficient, and future-ready library services.

Ternary hybrid nanofluid have been revealed to possess a wide range of application disciplines reaching from biomedical engineering, detection of cancer, over or photovoltaic panels and cells, nuclear power plant engineering, to the automobile industry, smart cells and and eventually to heat exchange systems. Inspired by the recent developments in nanotechnology and in particular the high potential ability of use of such nanofluids in practical problems, this paper deals with the flow of a three phase nanofluid of MWCNT-Au/Ag nanoparticles dispersed in blood in the presence of a bidirectional stretching sheet. The model derived in this study yields a set of linked nonlinear PDEs, which are first transformed into dimensionless ODEs. From these ODEs we get a dataset with the help of MATHEMATICA environment, then solved using AI-based technique utilizing Levenberg Marquardt Feedforward Algorithm. In this work, flow characteristics under varying physical parameters have been studied and analyzed and the boundary layer phenomena has been investigated. In detail horizontal, vertical velocity profiles as well as temperature distribution are analyzed. The findings reveal that as the stretching ratio of the surface coincide with an increase the vertical velocity as the surface has thinned in this direction minimizing resistance to the fluid flow.

The aim of the study was to check the Teachers prospective about school climate at secondary school level: A Comparative Study. The objectives of the study were to find out the teachers prospective about school climate at secondary school level and to compare the gender base teachers prospective about school climate at secondary level. The quantitative and descriptive research design was used. The population of this study was 110 secondary school teachers in district Kotli. In sample of the study 86 male and female teachers were selected by simple random sampling technique. The data was collected through survey technique with the help of self-developed questionnaire based on four dimensions. This study examined four dimensions each with ten statements (Physical Environment, Social Environment, Learning Environment, and intellectual Environment. The collected data was analyzed by mean and T-test for results. It was concluded that while teachers view the overall school climate positively, they highlight the need for greater focus on improving physical conditions and social relationships to match the strength of the learning environment. The findings show that male and female teachers have different opinions about the overall school climate at the secondary level. Furthermore, male and female teachers perceive the school climate differently, with male teachers having a more favorable view, highlighting the need to address gender-specific concerns to create an inclusive and supportive environment for all. It is recommended that school leaders ensure equal involvement of male and female teachers in decision-making and access to resources to promote a more inclusive and supportive school climate.

Abstract This research utilizes machine learning to investigate Marangoni convection in a hybrid nanofluid (MnZnFe 2 O 4 +NiZnFe 2 O 4 ⁄H 2 O) within a Darcy-Forchheimer porous framework. We conduct both qualitative and quantitative assessments of heat transfer, mass transfer, and viscous dissipation irreversibility during the flow. Numerical results are obtained using a Python finite difference algorithm, after which MATLAB is employed for AI-based analysis. Additionally, the Levenberg-Marquardt neural network algorithm is trained and utilized. Our findings show that fluid velocity diminishes as the inverse Darcy parameter, Marangoni ratio, and Forchheimer parameter increase. Moreover, the temperature rises with the Eckert number and Prandtl ratio. As concentration increases, activation energy and Schmidt parameter also grow. Mean Square Error (MSE) for the results reaches up to 10 -11 across various impacts.