The Women University Multan

The Thar Desert, one of South Asia largest arid ecosystems, is renowned for its rich cultural heritage and ecological diversity. It supports unique indigenous communities whose livelihoods depend on agriculture, animal husbandry, and traditional crafts such as woodworking, wool weaving, and jewelry making. Despite its ecological and medicinal significance, much of the region’s ethnobotanical knowledge remains undocumented. To systematically characterize the distribution, diversity, and medicinal potential of Thar Desert flora, an extensive literature review was conducted using scientific databases including Flora of Pakistan, Global Biodiversity Information Facility (GBIF), and Plants of the World Online (POWO), as well as search engines such as Google Scholar, Scopus, PubMed, Web of Science, and ScienceDirect (1980–2024). A total of 162 plant species belonging to 69 families were documented and evaluated for their phytochemical composition, ethnomedicinal relevance, and conservation status across the Thar Desert. The dominant families—Poaceae (27

Lead (Pb) pollution in water bodies poses significant threats to aquatic biodiversity, highlighting the need for assessment through suitable bioindicators for monitoring and evaluating ecosystem health. This field study was carried out to evaluate the bioaccumulation potential of freshwater snail species in Sargodha, Pakistan. The snail species were collected between September and November, 2023, from two different types of freshwater bodies (lentic and lotic) and identified as Indoplanorbis exustus and Lymnaea acuminata. The Pb concentration was assessed in snail soft bodies and water samples through atomic absorption spectrometry. The results showcased the mean Pb concentration of 0.1572 ppm (dw) in I. exustus, 0.1487 ppm (dw) in L. acuminata, and 0.0344 ppm (ww) in both types of water samples. There were significant differences among the water bodies, with stagnant water bodies having more Pb contamination than flowing ones. Additionally, significant differences were ascertained between the mean Pb concentration of both snail species and water samples. However, linear regression analysis showed an inverse relationship between the concentrations of Pb in water and both snail species. In addition, the bioconcentration factor (BCF) values calculated for snail species showed that both I. exustus and L. acuminata were equally good bioaccumulators of Pb in lentic and lotic water bodies. In conclusion, the study findings emphasized the urgent need for freshwater monitoring and pollution management in the region.

The rapid expansion of textile and dye-intensive industries has led to the discharge of large volumes of dye-contaminated wastewater, posing severe threats to aquatic ecosystems and human health. Conventional treatment methods often suffer from limited efficiency, secondary pollution, and high operational costs, underscoring the need for sustainable alternatives. Biomass-modified nanoparticles (BMNPs) have therefore gained significant attention as green photocatalysts, where plant extracts and other biomass resources are utilized in NPs synthesis to achieve environmental compatibility and high catalytic efficiency. This review highlights the recent advances in BMNPs- and hybrid nanocomposite-assisted photocatalytic dye degradation, with a special focus on their synthesis, fundamental degradation mechanisms, and structure-activity relationships. Different classes of BMNPs, including metal nanoparticles (MNPs), metal oxide nanoparticles (MONPs), and hybrid nanocomposites (hNCs), are critically analyzed for their performance in photocatalytic dye degradation under diverse operational conditions. The economic aspects of BMNP production are discussed in relation to large-scale feasibility, with a focus on linking green chemistry principles to industrial implementation. The environmental risks and sustainable end-of-life management of spent BMNPs adsorbents are also discussed, emphasizing the need for safe disposal, regeneration, and circular reuse strategies to prevent secondary contamination. Additionally, challenges such as stability, recovery, and reusability are evaluated, alongside strategies to overcome these barriers. By explicitly framing BMNPs as a waste-to-wealth innovation, this review highlights how biomass valorization can transform low-value agricultural and industrial residues into high-performance nanomaterials, thereby creating both environmental solutions and new economic opportunities.

PurposeThe objective of this research is to compile a thorough review of existing literature, highlighting how artificial intelligence and personalized learning have shaped emerging research opportunities.Research methodologyThis study employs the PRISMA review protocol alongside a meta-literature review to analyze pertinent works sourced from the Scopus database, spanning the years 2013 to 2025.FindingsThe study examines the progress and deficiencies in the integration of artificial intelligence and personalized learning in education. It underscores a transition in global research priorities from dominant regions such as China, USA and Europe to broader Asia, signaling new opportunities for educational improvement. However, the findings reveal that the swift expansion of AI, combined with persistent concerns about educational standards in developing countries, may create additional institutional pressures that influence the effectiveness of education.ImplicationsThe findings from this review present significant implications for research, practice, and policy. For educators and academic institutions, the results highlight the necessity of professional development that goes beyond technical proficiency, emphasizing pedagogical integration and digital literacy. Furthermore, policymakers are urged to develop ethical frameworks for AI implementation in education, addressing critical issues such as data privacy, algorithmic bias, and unequal access.OriginalityThe significance of this study lies in its effort to bridge a gap in the existing literature by systematically analyzing and reviewing research on Artificial Intelligence and Personalized Learning using PRISMA and meta-literature review methodologies. This comprehensive analysis offers researchers a clearer understanding of key developments and emerging trends within the field. Moreover, it identifies promising avenues for future inquiry and serves as a foundational reference for subsequent investigations.

The study investigated the adsorption of Methylene Blue (MB) and Congo Red (CR) dyes from a solution using Wheat Straw (WS), an adsorbent. The WS surface contained OH and other functional groups, and its pHpzc value was 6.7. The optimal pH for MB adsorption was 8-9, and for CR adsorption, it was 5-6. The kinetics of MB and CR dye adsorption onto WS were evaluated using pseudo-first-order, pseudo-second-order kinetic models, Elovich model, intra-particle, and liquid film diffusion models. The data were best fitted to pseudo-first-order kinetics. The maximal removal percentage for MB was 89.5% at 293 K with an adsorbent dose of 0.2 g and an interaction time of 30 minutes. And the Langmuir adsorption capacity (Qmax) was recorded to be 34.27 mg/g for MB. For CR, the maximal removal percentage was 76.7% at 293 K with an adsorbent dosage of 0.1 g and a contact time of 40 minutes. And the Langmuir adsorption capacity (Qmax) was recorded to be 35.07 mg/g for CR. The reaction was exothermic and spontaneous. After five cycles of adsorption and desorption, the percentage removal of MB decreased from 89.580% to 50.970% and CR dye from 76.053% to 36.341%. The study concluded that WS is an economical and environmentally friendly adsorbent for removing cationic and anionic dyes from solutions.