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In the present study, the extracts of Cytinus hypocistis (L.) L using both traditional solvents (hexane, ethyl acetate, dichloromethane, ethanol, ethanol/water, and water) and natural deep eutectic solvents (NADESs) were investigated in terms of their total polyphenolic contents and antioxidant and enzyme-inhibitive properties. The extracts were found to possess total phenolic and total flavonoid contents in the ranges of 26.47–186.13 mg GAE/g and 0.68–12.55 mg RE/g, respectively. Higher total phenolic contents were obtained for NADES extracts. Compositional differences were reported in relation to antioxidant potential studied by several assays (DPPH: 70.19–939.35 mg TE/g, ABTS: 172.56–4026.50 mg TE/g; CUPRAC: 97.41–1730.38 mg TE/g, FRAP: 84.11–1534.85 mg TE/g). Application of NADESs (choline chloride—urea 1:2, a so-called Reline) allowed one to obtain the highest number of extracts having antioxidant potential in the radical scavenging and reducing assays. NADES-B (protonated by HCl L-proline-xylitol 5:1) was the only extractant from the studied solvents that isolated a specific fraction without chelating activity. Reline extract exhibited the highest acetylcholinesterase inhibition compared to NADES-B and NADES-C (protonated by H2SO4 L-proline-xylitol 5:1) extracts, which showed no inhibition. The NADES extracts were observed to have higher tyrosinase inhibitory properties compared to extracts obtained by traditional organic solvents. Furthermore, the NADES extracts were relatively better inhibitors of the diabetic enzymes. These findings provided an interesting comparison in terms of total polyphenolic content yields, antioxidant and enzyme inhibitory properties (cholinesterase, amylase, glucosidase, and tyrosinase) between traditional solvent extracts and NADES extracts, used as an alternative. While the organic solvents showed better antioxidant activity, the NADES extracts were found to have some other improved properties, such as higher total phenolic content and enzyme-inhibiting properties, suggesting functional prospects for their use in phytonutrient extraction and fractionation. The obtained results could also be used to give a broad overview of the different biological potentials of C. hypocistis.

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with mid-century climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations’ resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

Abstract Water management is one of the important factors which determine the performance of a Proton Exchange Membrane (PEM) fuel cell using hydrogen as fuel. For developing efficient water management systems, it is important to know the potential locations of formation and the nature of distribution of liquid water in the fuel cell. In the present study a PEM fuel cell with three different types of flow distributors are modeled and numerically simulated to find out the water formation and distribution characteristics. The model is validated by comparing the simulated polarization curve to experimental data. It is found that the type of flow distributor used plays a major role in determining the distribution of liquid water in the cell. A parallel flow distributor exhibits poor water removal capabilities whereas a serpentine flow distributor exhibits better water removal. A mixed flow distributor is found to give better water distribution characteristics compared to the parallel and serpentine distributors. Further the effect of liquid water formation and distribution on the species transport, temperature distribution and current generation are also investigated.

Abstract As the rising concern of waste management around the world, landfills are stacking up the waste due to a shortage of land. Researchers are finding different ways to convert this waste heat to produce useful energy. Effective treatments of these waste results in the utilization of products generated by the system. Many limitations of the Organic Rankine Cycle (ORC) and anaerobic digestion are yet to be solved. Anaerobic digestion is the biological system which helps in degradation of organic waste into useful products. The product generated is burnt to heat organic working fluid present in Organic Rankine Cycle (ORC) by supplying heated medium through the evaporator. Although pre-treatment is required for food waste. The paper reviews the combined heat and power (CHP) systems between biomass and regenerative Organic Rankine Cycle (ORC), which affects requirement and efficiency of system using dry fluid as the medium of Organic Rankine Cycle (ORC). In this reviewed paper, the steady-state conditions are kept into consideration to observe the factors affecting the efficiency of the system done by various authors to get a better performing system.

AbstractAchieving gender equality and women’s empowerment in food systems can result in greater food security and better nutrition, as well as more just, resilient and sustainable food systems for all. This chapter uses a scoping review to assess the current evidence on pathways between gender equality, women’s empowerment and food systems. The chapter uses an adaptation of the food system framework to organize the evidence and identify where evidence is strong, and where gaps remain. Results show strong evidence on women’s differing access to resources, shaped and reinforced by contextual social gender norms, and on links between women’s empowerment and maternal education and important outcomes, such as nutrition and dietary diversity. However, evidence is limited on issues such as gender considerations in food systems for women in urban areas and in aquaculture value chains, best practices and effective pathways for engaging men in the process of women’s empowerment in food systems, and how to address issues related to migration, crises and indigenous food systems. While there are gender-informed evaluation studies examining the effectiveness of gender- and nutrition-sensitive agricultural programs, evidence indicating the long-term sustainability of such impacts remains limited. The chapter recommends key areas for investment: improving women’s leadership and decision-making in food systems, promoting equal and positive gender norms, improving access to resources, and building cross-contextual research evidence on gender and food systems.

Snow cover plays an important role in hydrological modelling and influences the energy balance. Daily Moderate Resolution Imaging Spectroradiometer (MODIS) snow products are widely used for snow cover monitoring; however, the cloud cover causes a discontinuity in spatial and temporal scale. Therefore, we have implemented a composite (five-step) methodology for cloud removal over the Karakoram and Himalayan (KH) region during 2000���2019. The cloud-gap-filled snow cover area (SCA) was compared with Landsat-8 data, and the relationship with in situ observations (snowfall and temperature) was examined. The annual SCA illustrates an increasing trend for the entire KH except in the eastern Himalayas. The snow cover day and nine snow cover timing indices were assessed to explore the snow cover characteristics. The relationships between SCA and meteorological variables were evaluated, suggesting a higher correlation with temperature and shortwave radiation. A sensitivity analysis was performed, indicating higher sensitivity of SCA to radiation than to other selected variables.

Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.