Silver nanoparticles (NPs) were synthesized using an efficient bioreducing agent from Fagonia cretica extract having the advantage of eco-friendliness over chemical and physical methods. The sharp color change and appearance of representative absorption peaks in the UV-visible spectra confirm the quick reduction of the Ag salt and evolution of Ag NPs. Morphological and structural aspects showed that the resulting Ag NPs are highly crystalline with an average size of 16 nm. Furthermore, compositional analysis of the extract confirmed the existence of active bioreducing and stabilizing agents in the Fagonia cretica extract. Furthermore, various concentrations of AgNO₃ and the Fagonia cretica extract were employed to obtain a higher yield with better stability of Ag NPs. The resulting Ag NPs showed effective antibacterial activity against Proteus vulgaris, Escherichia coli, and Klebsiella pneumoniae. It is found that the Ag NPs induce maximum production of reactive oxygen species (ROS) in Proteus vulgaris as compared to Escherichia coli and Klebsiella pneumoniae which induce cell toxicity, while ROS production in the presence of Ag NPs is 30% higher than that in the presence of only the plant extract and control in all three bacterial strains. Thus, present findings show that plant extracts can be a useful natural resource to prepare functional nanomaterials for targeted applications especially in the field of biotechnology.

The increasing metal release into the environment warrants investigating their impact on plants, which are cornerstones of ecosystems. Here, Lactuca sativa L. (lettuce) seedlings were exposed hydroponically to different concentrations of silver ions and nanoparticles (Ag NPs) for 25 days to evaluate their impact on plant growth. Seedlings taking Ag⁺ ions showed an increment of 18% in total phenolic content and 12% in total flavonoid content, whereas under Ag NPs, 7% free radical scavenging activity, 12% total phenolic contents (TPC), and 10% total reducing power are increased. An increase in 31% shoot length, 25% chlorophyll, 11% carbohydrate, and 16% protein content of the lettuce plant is observed in response to Ag NPs, while silver nitrate (AgNO₃) has a reduced 40% growth. The lettuce plant was most susceptible to toxic effects of Ag+ ions at a lower concentration, i.e., 0.01 mg/L, while Ag NPs showed less toxicity, only when higher concentrations >100 mg/L were applied. Further, biomolecules other than antioxidant enzymes showed higher phytotoxicity for Ag⁺ ions, followed by Ag NPs with the concentration of 25, 50, and 100 mg/L compared to the control. Thus, moderate concentrations of Ag NPs have a stimulatory effect on seedling growth, while higher concentrations induced inhibitory effects due to the release of Ag⁺ ions. These results suggest that optimum metallic contents are desirable for the healthier growth of plants in a controlled way.

Loureirin B (LB) is the most radioactive compound of dragon’s blood, but its poor pharmacokinetics due to its hydrophobic nature limits its clinical applications. Owing to the excellent biocompatibility of liposomes with body fluid, here phospholipids and cholesterol-based nanoliposomes (NLs) were synthesized using the thin-film evaporation technique as a nanocarrier for LB to overcome associated clinical issues. The NLs exhibited overall vesicular shape, which is favorable for enhanced drug uptake (up to 74.5%), while the particle size of NLs was found to be strongly dependent on lipid concentration that ranges from 58 to 94 nm. Further, a high ζ-potential of −51.2 mV shown by the LB-loaded NLs confirms their high stability and better dispersion in designated solvents/cell plasma as well as proves their ability for homogeneous drug delivery. In vitro flow cytometry results revealed that LB-loaded NLs recover the radiation injury in viable cell from 79.4 to 89.9%, early apoptosis from 3.5 to 0.2%, necrosis from 14.8 to 9.8%, and late apoptosis from 2.3 to 0.0%. In vivo assay showed that LB-loaded NLs successfully improved the pharmacokinetic parameters such as maximum concentration of LB-loaded NLs formulation, elimination rate half-life, area under the curve, and plasma clearance to 3.247 ± 0.631 ng/mL h, 14.765 ± 10.780 min, 2.957 ± 0.201 ng/mL h, and 0.132 ± 0.901 ng/mL h, respectively. Thus, we believe that designing such unique LB-loaded NLs composite not only improved the antiradiation characteristics of LB but also make it suitable for other biomedical applications like drug delivery by enhancing its solubility and dispersion.

Numerical modelling increasingly generates massive, high-dimensional spatio-temporal datasets. Exploring such datasets relies on effective visualization. This study presents a generic workflow to (i) project high-dimensional spatio-temporal data on a two-dimensional (2D) plane accurately (ii) compare dimensionality reduction techniques (DRTs) in terms of resolution and computational efficiency (iii) represent 2D projection spatially using a 2D perceptually uniform background color map. Machine learning (ML) based DRTs for data visualization i.e., principal component analysis (PCA), generative topographic mapping (GTM), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) are compared in terms of accuracy, resolution and computational efficiency to handle massive datasets. The accuracy of visualization is evaluated using a quality metric based on a co-ranking framework. The workflow is applied to an output of an Australian Water Resource Assessment (AWRA) model for Tasmania, Australia. The dataset consists of daily time series of nine components of the water balance at a 5 km grid cell resolution for the year 2017. The case study shows that PCA allows rapid visualization of global data structures, while t-SNE and UMAP allows more accurate representation of local trends. Furthermore, UMAP is computationally more efficient than t-SNE and least affected by the outliers compared to GTM.

Local communities in mining regions are vulnerable to water scarcity risks caused by extensive mining and changing climate. To mitigate such risks, we adopt a non-market valuation of low income communities’ preferences for improved access to water services, as an effort to develop pro-poor policies that bring long-term water security and benefits to the local people. Using data collected from 268 households from the mining site in the Thar coalfield (Pakistan), we examine the household willingness to pay (WTP) for all major uses based on hypothetical policy scenarios. Results show that the mean WTP was estimated to be PKR 3921 (USD 38) for risk averting services (S1) and PKR 4927 (USD 48.13) for domestic pipelines and more decentralized water systems (S2) per month. We found that the mean WTP for S1 is 11.8% and for S2 is 16.6% more than the existing water-related expenditures of households. Age of household head, income level, project employment, livestock, farm income, and water quality are the significant factors influencing their WTP. These findings provide empirical evidence to policymakers and resource managers to implement cost-effective water management plans that provide multiple ecosystem service benefits, thereby potentially aiding pro-poor and sustainable economic growth in mining regions.

The aim of the present study is to determine the collaborative activities of Asian library and information science (LIS) researchers through bibliometric, social network analysis at the author, institution, and country levels of the LIS publications produced by Asian researchers. For the study, research articles were derived from the 1994–2013 Web of Science (WoS) archives. Coauthor analysis software was used to analyze author contributions on the New Modified Author Activity Index (NMAAI_{1, 2, 3})—a measurement tool to evaluate author research activities. Results reveal (a) that LIS “institutions collaboration pattern” outcomes did not yield strong collaboration with Asian countries or regions, (b) intracontinent and intercontinent collaboration was less harmonious on institutional and author levels, and (c) interpretation through NMAAI_1,2,3 revealed that Asian countries did not produce sufficient collaborative LIS publications. Taiwan, South Korea, Singapore, India, Iran, Israel, and Turkey have been producing ample LIS papers, but the United States and United Kingdom emerged as leaders. This work provides a holistic view of Asian LIS development and emphasizes individual levels of collaboration, finding that most influential authors serve on coauthor networks, which differentiates this study from previous studies in the LIS field. There is immense need to develop liaisons, sign memoranda of understanding (MOUs), and participate in combined research plans and short-term research exchange programs.