An enhanced jellyfish search optimizer for stochastic energy management of multi-microgrids with wind turbines, biomass and PV generation systems considering uncertainty.

The energy management (EM) solution of the multi-microgrids (MMGs) is a crucial task to provide more flexibility, reliability, and economic benefits. However, the energy management (EM) of the MMGs became a complex and strenuous task with high penetration of renewable energy resources due to the stochastic nature of these resources along with the load fluctuations. In this regard, this paper aims to solve the EM problem of the MMGs with the optimal inclusion of photovoltaic (PV) systems, wind turbines (WTs), and biomass systems. In this regard, this paper proposed an enhanced Jellyfish Search Optimizer (EJSO) for solving the EM of MMGs for the 85-bus MMGS system to minimize the total cost, and the system performance improvement concurrently. The proposed algorithm is based on the Weibull Flight Motion (WFM) and the Fitness Distance Balance (FDB) mechanisms to tackle the stagnation problem of the conventional JSO technique. The performance of the EJSO is tested on standard and CEC 2019 benchmark functions and the obtained results are compared to optimization techniques. As per the obtained results, EJSO is a powerful method for solving the EM compared to other optimization method like Sand Cat Swarm Optimization (SCSO), Dandelion Optimizer (DO), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and the standard Jellyfish Search Optimizer (JSO). The obtained results reveal that the EM solution by the suggested EJSO can reduce the cost by 44.75% while the system voltage profile and stability are enhanced by 40.8% and 10.56%, respectively.

The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems.

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

Neoteric approach for peanuts biofilm using the merits of Moringa extracts to control aflatoxin contamination.

Aflatoxigenic fungi and aflatoxins are still a principal challenge that threatened peanut production, marketing, and handling. This study aimed to face the problem using bioactive materials, which reduce fungi and mycotoxin contamination, Moringa extracts may be suitable for solving this challenge. Also, the study was compared the extracts of leaves and oil-free seeds. Fresh leaves and seeds were collected, dried, and milled, while oil was collected by cold pressing. The extracts were evaluated for total phenols, flavonoids, and antioxidants, the oil contents of fatty acids, tocopherol, and sterols were determined. An emulsion for protecting peanuts compositing of leaves extract carried by Moringa oil, and commercial emulsifier. Leaves extract evaluation reflected distinct properties of its fibers, total phenols, and flavonoids. It was recorded a microbial inhibition of bacteria and fungi. The values ​​for both minimal inhibition and fungicidal concentrations were recorded at 3.2 mg/mL and 490 µg/L, respectively. For oil, it showed a unique content, as oleic acid was the main fatty acid, with an affinity between palmitic and behenic in their ratios. Also, oil was recorded by high contents of alpha-tocopherol and Δ7-Campesterol, with 1.166 mg/kg oil as total sterols content. The leaves extract has also a unique capacity to inhibit toxigenic fungi. By applying the composite emulsion for peanut coating, results expressed a high CFU-count inhibition when it was inoculated by A. flavus strain compared to the control.

Properties of concrete with binary binder system of calcined dolomite powder and rice husk ash.

This study investigates the properties of a binary binder system consisting of calcined dolomite powder (CDP) and rice husk ash (RHA). To conduct the study, a reference mixture containing 100% ordinary Portland cement (OPC) and six other concrete mixtures containing a binary binder system with different proportions of CDP and RHA were prepared and tested. Testing was conducted for workability, setting time, dry shrinkage, and mechanical strength at different curing times. The results indicate that the binary system CDP-RHA have mechanical properties better than that of OPC. In addition, the results indicate that the mixture containing 50% CDP and 50% RHA is optimal in terms of mechanical strength.