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This paper develops a data-driven model for assessing the availability of flexibility from individual household devices, at house level. The model predicts the potential shift, increase or decrease of the energy consumption of a particular type of device at a given time, in response to a price signal, and for each house separately. Therefore, the location of the flexibility source is known with accuracy. The model has an Auto-Encoder architecture based on Convolution Neural Network. The augmented model demonstrates good performance in terms of predicting the time-shift in load.

1. Marine Heat Waves (MHWs) are episodes of anomalous warming in the ocean that can last from a few days to months. MHWs have different characteristics in terms of intensity, duration, and frequency and generate thermal stress on marine ecosystems. In reef ecosystems, they are one of the main causes of decreased presence and abundance of corals, invertebrates, and fish. The deleterious capacity of thermal stress often depends upon biotic factors such as resource availability (bottom-up control on predators) and predation (top-down control on prey). Despite the evidence of thermal stress and biotic factors affecting individual species, the combined effects of both stressors on the entire reef ecosystems are far less studied. 2. Here, using a food-web modeling approach, we estimated the rate of change in species’ biomass due to different MHW scenarios based on their physical characteristics. Specifically, we modeled the mechanistic link between species’ consumption rate and seawater temperature (thermal stressor), simulating species’ biomass dynamics for different MHW scenarios under different trophic control assumptions (biotic factor). 3. We find that total reef ecosystem biomass declined by 10% ± 5% under MHWs with severe intensity and top-down control assumption. The bottom-up control assumption moderates the total ecosystem biomass reduction by 5% ± 5%. Irrespective of the MHW scenario and the trophic control assumption, the most substantial biomass changes occur among top, meso-predators, and corals (5% to 20% ± 10%).4. Since habitat degradation may lead to reef ecosystems governed by top-down control on prey, our findings point to the critical importance of protecting reef ecosystems as a pivotal strategy to alleviate the impacts of thermal stress induced by MHWs. Overall, our results provide a unified understanding of the interplay between abiotic stressors and biotic factors in reef ecosystems under extreme thermal events, offering insights into present baselines and future ecological states for reef ecosystems.

A theoretical and empirical model is developed to analyze the effect of a biodiesel mandate, a tax exemption (tax credit) and an exogenous diesel price shock on world soybean and canola markets. The jointness in crushing oil and meal from the oilseed reduces the size of the link between biodiesel and oilseed prices. A diesel price shock with a mandate results in a smaller change in oilseed prices compared with a tax exemption. Higher diesel prices increase biodiesel prices under a tax exemption but lower them with a blend mandate. When both canola and soybeans are used to produce biodiesel, an increase in the diesel price leads to higher canola prices, but the effect on soybean prices is ambiguous and depends on relative elasticities of meal demand and canola supply because canola produces more oil than soybeans.

Little is known about the validity of repeated 24-h dietary recalls (24-HDR) as a measure of total energy intake (EI) in young children. This study aimed to evaluate the validity of proxy-reported EI by comparison with total energy expenditure (TEE) measured by the doubly labeled water (DLW) technique.The agreement between EI and TEE was investigated in 36 (47.2% boys) children aged 4-10 years from Belgium and Spain using subgroup analyses and Bland-Altman plots. Low-energy-reporters (LER), adequate-energy-reporters (AER) and high-energy-reporters (HER) were defined from the ratio of EI over TEE by application of age- and sex-specific cut-off values.There was good agreement between means of EI (1500 kcal/day) and TEE (1523 kcal/day) at group level though in single children, i.e. at the individual level, large differences were observed. Almost perfect agreement between EI and TEE was observed in thin/normal weight children (EI: 1511 kcal/day; TEE: 1513 kcal/day). Even in overweight/obese children the mean difference between EI and TEE was only -86 kcal/day. Among the participants, 28 (78%) were classified as AER, five (14%) as HER and three (8%) as LER.Two proxy-reported 24-HDRs were found to be a valid instrument to assess EI on group level but not on the individual level.

It's not only the carbon in the trees Forest loss affects climate not just because of the impacts it has on the carbon cycle, but also because of how it affects the fluxes of energy and water between the land and the atmosphere. Evaluating global impact is complicated because deforestation can produce different results in different climate zones, making it hard to determine large-scale trends rather than more local ones. Alkama and Cescatti conducted a global assessment of the biophysical effects of forest cover change. Forest loss amplifies diurnal temperature variations, increases mean and maximum air temperatures, and causes a significant amount of warming when compared to CO 2 emission from land-use change. Science , this issue p. 600

Pervasive computing and business process modeling are increasingly joining forces, as mobile human users shall be seamlessly integrated into business processes. In respective scenarios, humans use mobile devices and wireless technology to interact with workflows running in a powerful back-end infrastructure. However, the frequent interaction between humans and workflows causes a high communication overhead and, thus, high energy consumption on mobile devices. This impacts the usability and efficiency of the business process due to rapidly drained batteries and the resulting short life-times of the devices and applications. We present an approach based on a minimum-cut algorithm for reducing costly data transmissions during workflow execution by distributing parts of a workflow to the users' devices. Our motivation is to reduce the energy consumption on the mobile devices and, thus, avoid draining batteries in the field. We prove that our algorithm finds the optimal solution for a given network and workflow, decreasing the energy consumed on mobile devices by 32-37% compared to an approach where the entire workflow is executed in the infrastructure. Thus, in typical domains like logistics and health care, one third of the energy can be saved. This either means that devices have to be charged less frequently, leading to less distraction in the business process, or that mobile device specifications can be lowered. Significant cost reductions result in both cases.