Search

Efficient offloading and scientific task scheduling are crucial for managing computational tasks in research environments. This involves determining the optimal location for executing a workflow task and allocating the task to computing resources to optimize performance. The challenge is to minimize completion time, energy consumption, and cost. This study proposes three methods: latency-centric offloading (LCO) for delay-sensitive applications; energy-based offloading (EBO) for energy-saving; and efficient offloading (EO) for balanced task distribution across tiers. Scheduling in this paper uses a genetic algorithm (GA) with a weighted sum objective function considering makespan, cost, and energy for internet of things-cloud-fog (IoT-fog-cloud). Comparative studies involving montage, Cybershake, and epigenomics workflows indicate that LCO excels in terms of makespan and cost but ranks the lowest in energy. EBO excels in energy efficiency, aligning closely with the base method. EO competes effectively with the base method in terms of makespan and cost but consumes more energy. This research enables the selection of the most suitable method based on the type of application and its prioritization of makespan, energy, or cost. [ABSTRACT FROM AUTHOR]

The aim of this paper is to use the second derivative of Chebyshev polynomials (SDCHPs) as basis functions for solving linear and nonlinear boundary value problems (BVPs). Then, the operational matrix for the derivative was established by using SDCHPs. The established matrix via mixing between two spectral methods, collocation and Galerkin, has been applied to solve BVPs. Consequently, an error analysis is investigated to ensure the convergence of the technique used. Finally, we solved some problems involving real-life applications and compared their solutions with exact and other solutions from different methods to verify the accuracy and efficiency of this method. [ABSTRACT FROM AUTHOR]

Lead mobilization in aquaculture and its generated health hazards prompted the use of a cheap and reusable method for its removal within a short duration. A 3D macroporous microbial biomat formed of Trichoderma viride immobilized on luffah was used for Pb removal. The biomat was used to remove 79% of initial 400 mg/kg Pb in 24 h that increased to 87% under optimized conditions of pH, temperature, and contact time. In order to reduce the time needed for Pb bioremoval to 1 h, pretreated biomats were used, resulting in an increase in removal from 58% to 96% upon exposure to gamma radiation (0.01 kilogray [kGy]). The irradiated biomat was studied in terms of morphology, elemental analysis of surface biosorbed Pb and surface functional groups using scanning electron microscopy (SEM), energy dispersive X‐ray (EDX), and Fourier transform infrared (FTIR) spectroscopy. The results show a difference in the adsorption pattern. The biomat was reused efficiently for 3 consecutive cycles and was also used in fixed bed column showing 89% removal for downward flow and in real aquaculture samples. Pretreated microbial biomats are very suitable for use in fixed bed reactors or as a biofilter and can be tested in recirculating aquaculture systems (RASs), thereby contributing to water conservation and aquaculture sustainability. Integr Environ Assess Manag 2020;16:508–516. © 2020 SETAC KEY POINTS: Fungal immobilized biomat is cheap and efficient in Pb removal.Pretreatment using gamma radiation increases adsorptive capacity of the adsorbate.Regeneration for reuse offers sustainability.Fungal immobilized biomat can be used in both metal removal and metal retrieval. [ABSTRACT FROM AUTHOR]

Background: Antenatal depression is not uncommon and is associated with a greater risk of negative pregnancy outcomes. Aim: Exploring the effect of exercise in preventing and treating antenatal depression. Methods: This was a prospective interventional controlled study carried out in 100 pregnant women treated at the Ain-Shams Family Medicine Center and Maadi Outpatient Clinic, Cairo, Egypt. The participants were divided into two groups (n=50 in the exercise group and n=50 in the control group). The exercise group regularly attended supervised sessions for 12 weeks. The activities in each session included walking, aerobic exercise, stretching, and relaxation. The control group completed their usual antenatal care. The Center for Epidemiological Studies Depression Scale (CES-D) was used to assess depression symptoms at the first interview and immediately after the 12-week intervention. Results: Compared to the control group, the exercise group showed significantly improved depressive symptoms as measured with the CES-D after the 12-week intervention on the CES-D (P=0.001). Within groups, the exercise group demonstrated a significant improvement of depressive symptoms from baseline to intervention completion, while the control group demonstrated no significant changes over time. Conclusion: Exercise during pregnancy was positively associated with reduced depressive symptoms. [ABSTRACT FROM AUTHOR]