Shah Abdul Latif University (Urdu: جامعہ شاہ عبداللطیف, Sindhi: شاه عبداللطيف يونيورسٽي; abbreviated as SALU), is a public research university located in rural Khairpur of Sindh, Pakistan. The university is named after the mystic poet and spiritualist Shah Abdul Latif Bhittai.The university also maintains teaching campuses in Shikarpur, Shahdadkot and Ghotki. Founded in 1976 as a single campus, the university has grown in both keeping its reputation and physical enlargement whilst developing a strong and transparent system of higher education in the north of Sindh. The university offers undergraduate, post-graduate, and doctorate programmes in various academic disciplines. The university is noted for its academic staff consisting of foreign scholars, and research directed towards the development of humanities, archaeology, Sindh studies, natural and social sciences.In addition, it is ranked as one of the top institution of high learning by the HEC on "general" category. its ranking as per country rank is 97 in Pakistan and world rank 7968. Nearly ~7000 students currently enrolled in the university, the university's main focus is committed to enabling its graduates to lead and serve the nation apart from their own better well-being.
In this study, a ZnO/rGO nanocomposite opto-catalyst was successfully designed and applied for sunlight-driven photocatalytic degradation of Rhodamine B dye. The structural, morphological, elemental, and optical properties of the nanocomposite were comprehensively characterized using Raman spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray photoelectron (XPS), and photoluminescence (PL) spectroscopy. The XRD confirmed the formation of crystalline ZnO with an average crystallite size of 47.6 nm, while the disappearance of the GO (001) peak and the emergence of the rGO (002) peak signaled the successful reduction of graphene oxide. SEM analysis revealed a well-exfoliated layered morphology, and EDX verified the expected elemental composition as (45.0% Zn, 34.7% O, and 20.3% C). The optical band gap was estimated by the Tauc plot method. The photocatalytic performance was systematically optimized by varying key operational parameters, including catalyst dose, NaBH 4 concentration, and sunlight irradiation time. The optimal conditions, as 7 mg of ZnO/rGO, 15 µL of NaBH 4 (0.01 M), and 12 min solar irradiation yielded the highest degradation efficiency of 98%. Besides, the composite showed strong reproducibility over multiple cycles, confirming the reliability of the optimized conditions. The results highlight the strong synergistic interaction between the ZnO and rGO, enhanced charge separation, and light absorption; thus, the composite ZnO/rGO demonstrated to be an efficient, sunlight-activated, and environmentally friendly photocatalyst for wastewater treatment.
The rapid expansion of nanotechnology has opened novel opportunities to share for addressing global challenges related to food security, environmental sustainability, and human health. Conventional physical and chemical methods for the synthesis of nanoparticles (NPs) often involve hazardous chemicals, high energy demands, and poor biocompatibility. In contrast, bacterial-synthesized NPs are considered eco-friendly and multifunctional with their enormous potential in agriculture, bioremediation, and biomedical applications. The study highlights the importance of Bacteriogenic NPs as a sustainable alternative to chemically and physically produced NPs due to their reduced toxicity and lower energy consumption. Hence, bacteriogenic NPs, particularly those derived from Bacillus and Pseudomonas species, exhibit remarkable stability, biocompatibility, and multifunctional spectrum due to inherent reducing and capping biomolecules secreted by those bacteria. This review highlights the biosynthetic mechanisms, characterization techniques, and diverse applications of bacterial-based NPs. Initially, in agriculture, silver NPs synthesized by Bacillus xiamenesis enhanced rice growth while suppressing Xanthomonas oryzae, the causal agent of bacterial blight. Then, in environmental remediation, Bacillus pumilus-derived silver nanoparticles demonstrated 96.99
Resource allocation in sixth-generation (6G) networks must meet throughput, latency, and reliability targets while network conditions keep changing. At the same time, the telemetry needed to train good models is distributed across many devices and edge nodes, so sending it to a central server can violate privacy or data-sharing constraints. Federated learning (FL) helps, but two practical concerns usually determine whether it works in practice: how much communication is needed to achieve strong performance, and whether weaker (tail) clients benefit-not only the average client. In this study, we run large-scale FL on 6G telemetry with 200 clients and quantify the communication fairness trade-off. We evaluate FedAvg and FedProx under multiple settings and benchmark them against a strong centralized model and a local-only baseline. Results are reported as mean ± 95% confidence intervals over five random seeds. We measure the accuracy, macro-F1, AUC, and AP, and we also focus on tail behavior using the worst eligible client accuracy, p10 client accuracy, and fairness gap. By plotting the accuracy/macro-F1 against cumulative communication (bytes), we show that some configurations match the average performance while transmitting far fewer data. Finally, we find that the worst client performance improves early and then stabilizes, and a sensitivity study suggests that FedProx’s μ has a limited impact in this setup. These findings offer actionable guidance for 6G operators and system designers by quantifying how participation and dropout policies translate into concrete communication budgets and tail client behavior.
PurposeThis study investigates a complex interplay of socio-ecological aspects that increases maternal health vulnerability (MHV) in rural Sindh, Pakistan.Design/methodology/approachThis study uses a cross-sectional design involving 352 women aged 18-49 years from rural Sindh, Pakistan. The analysis included descriptive statistics and parametric and nonparametric tests, including t-test, ANOVA with Tukey's correction and Spearman's correlation test. A four-step multiple linear regression was used to identify SEM-level factors associated with MHV. Data analysis was done in STATA version 17.0.FindingsMHV was higher among women with post-natal health issues (beta = 2.67, 95% CI: 1.11-4.23), no hospital nearby (beta = 5.17, 95% CI: 4.06-6.28), irregular LHW visits with those receiving only one visit (beta = 5.11, 95% CI: 2.63-7.59), significant gender inequality (beta = 0.98, 95% CI: 0.74-1.23) and poverty (beta = 0.42, 95% CI: 0.29-0.56) while lower vulnerability was linked to ANC at public facilities (beta = -0.72, 95% CI: 2.20-0.74) and exposure to health information through lady heath workers (beta = -4.12, 95% CI: 7.16 to -1.08).Originality/valueThis study identifies several interconnected barriers to accessing maternal health services. Many women lack the education necessary to make timely decisions, which leads to delays in attending antenatal care (ANC) visits. Additionally, the combination of educational gaps and structural factors, including poverty, often drives women to rely on traditional birth attendants for assistance. The study underscores the importance of using a variety of approaches to tackle gender inequalities, improve health knowledge and invest in women's social connections. This means building support networks, trust and sharing information, which can significantly impact women's health habits and pregnancy results.
