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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.

Environmental and intrinsic factors interact to determine energy requirements in vertebrates. Glucocorticoid hormones (GCs) are key mediators of this interaction, as they fluctuate with energetic demands and regulate physiological and behavioral responses to environmental challenges. While a great body of research has focused on GC variation among individuals, the mechanisms driving GC variation across species and at broad spatial scales remain largely unexplored. Here, we adopted a macrophysiological approach to investigate the environmental factors and life-history traits driving variation in baseline GCs across lizard species. We tested three hypotheses: (1) If GCs increase with body temperature to meet higher metabolic demand, we expect an association between average baseline GCs and the mean species’ body temperature in the field (GC-temperature dependence hypothesis); (2) If GCs mediate behavioral responses to avoid thermal extremes, we expect that individuals frequently exposed to extreme conditions exhibit higher baseline GC levels (Behavioral thermoregulation hypothesis); (3) If GCs increase to support higher energy demands in active foragers during their period of activity, we expect that active foraging species have higher baseline GCs than sit-and-wait foragers, and that GC levels increase in relation to the duration of daily activity windows (Activity hypothesis). We used biophysical models to calculate operative temperatures and the activity patterns of lizards in sun-exposed and shaded microenvironments. Then, we tested the association between baseline GCs, body temperature, operative temperatures, foraging mode, and activity windows across 37 lizard species, using data from HormoneBase. Our comparative analyses showed that variation in baseline GCs was primarily related to the mean field body temperature and foraging mode, with higher baseline GCs in active foragers with higher body temperatures. Our results suggest that body temperature and foraging mode drive GC variation through their effects on energy requirements across lizard species.

In the amphoteric membrane-less decoupled water electrolysis, hydrogen and oxygen are co-produced in separate cells with higher energy efficiency. Ion exchange is mediated by the auxiliary electrodes – HxWO3 for acid and NiOOH for alkaline cell.

Optimising the photoelectrochemical performance of hematite photoanodes for solar water splitting requires better understanding of the relationships between dopant distribution, structural defects and photoelectrochemical properties. Here, we use complementary characterisation techniques including electron microscopy, conductive atomic force microscopy (CAFM), Rutherford backscattering spectroscopy (RBS), atom probe tomography (APT) and intensity modulated photocurrent spectroscopy (IMPS) to study this correlation in Ti-doped (1 cat.%) hematite films deposited by pulsed laser deposition (PLD) on F:SnO2 (FTO) coated glass substrates. The deposition was carried out at 300 ��C, followed by annealing at 500 deg C for 2 h. Upon annealing, Ti was observed by APT to segregate to the hematite/FTO interface and into some hematite grains. Since no other pronounced changes in microstructure and chemical composition were observed by electron microscopy and RBS after annealing, the non-uniform Ti redistribution seems to be the reason for a reduced interfacial recombination in the annealed films, as observed by IMPS. This results in a lower onset potential, higher photocurrent and larger fill factor with respect to the as-deposited state. This work provides atomic-scale insights into the microscopic inhomogeneity in Ti-doped hematite thin films and the role of defect segregation in their electrical and photoelectrochemical properties.

The presented Report forms Deliverable D6.2 resulted from the realization of Workpackage WP.6.3 titled “Overview of market drivers, fiscal measures and subsidies” in frame of the EU-Project “Geothermal communities – demonstrating the cascaded use of geothermal energy for district heating with small scale RES integration and retrofitting measures” (GEOCOM). The following seven countries were covered by WP6.3 works and this Deliverable D6.2: o Macedonia, o Hungary, o Italy, o Poland, o Romania, o Serbia, o Slovakia. The work was done with the contribution of all GEOCOM Project Partner teams and appointed experts, coordinated, interpreted and summarized by the Mineral and Energy Economy Research Institute of PAS team, WP6 leader. FP7

Abstract The dynamics of isolated-photon plus two-jet production in pp collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb−1. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, γ + jet + jet. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from Sherpa and Pythia as well as the next-to-leading-order QCD predictions from Sherpa are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.