Optimal Power Dispatch in Energy Systems Considering Grid Constraints

In this research, an energy system dispatch optimization model is employed. It includes an iterative approach for generating grid constraints, which is decoupled from the linear unit commitment problem. The dispatch of all energy carriers in the system is optimized while considering the physical electrical grid limits

HOLISMOKES -- II. Identifying galaxy-scale strong gravitational lenses in Pan-STARRS using convolutional neural networks

We present a systematic search for wide-separation (Einstein radius >1.5"), galaxy-scale strong lenses in the 30 000 sq.deg of the Pan-STARRS 3pi survey on the Northern sky. With long time delays of a few days to weeks, such systems are particularly well suited for catching strongly lensed supernovae with spatially-resolved multiple images and open new perspectives on early-phase supernova spectroscopy and cosmography. We produce a set of realistic simulations by painting lensed COSMOS sources on Pan-STARRS image cutouts of lens luminous red galaxies with known redshift and velocity dispersion from SDSS. First of all, we compute the photometry of mock lenses in gri bands and apply a simple catalog-level neural network to identify a sample of 1050207 galaxies with similar colors and magnitudes as the mocks. Secondly, we train a convolutional neural network (CNN) on Pan-STARRS gri image cutouts to classify this sample and obtain sets of 105760 and 12382 lens candidates with scores pCNN>0.5 and >0.9, respectively. Extensive tests show that CNN performances rely heavily on the design of lens simulations and choice of negative examples for training, but little on the network architecture. Finally, we visually inspect all galaxies with pCNN>0.9 to assemble a final set of 330 high-quality newly-discovered lens candidates while recovering 23 published systems. For a subset, SDSS spectroscopy on the lens central regions proves our method correctly identifies lens LRGs at z~0.1-0.7. Five spectra also show robust signatures of high-redshift background sources and Pan-STARRS imaging confirms one of them as a quadruply-imaged red source at z_s = 1.185 strongly lensed by a foreground LRG at z_d = 0.3155. In the future, we expect that the efficient and automated two-step classification method presented in this paper will be applicable to the deeper gri stacks from the LSST with minor adjustments.Comment: 18 pages and 11 figures (plus appendix), submitted to A&

Anatomical adjustments of the tree hydraulic pathway decrease canopy conductance under long-term elevated CO2_2

The cause of reduced leaf-level transpiration under elevated CO$_2$ remains largely elusive. Here, we assessed stomatal, hydraulic, and morphological adjustments in a long-term experiment on Aleppo pine (Pinus halepensis) seedlings germinated and grown for 22–40 months under elevated (eCO$_2$; c. 860 ppm) or ambient (aCO$_2$; c. 410 ppm) CO$_2$. We assessed if eCO$_2$-triggered reductions in canopy conductance (g$_c$) alter the response to soil or atmospheric drought and are reversible or lasting due to anatomical adjustments by exposing eCO$_2$ seedlings to decreasing [CO$_2$]. To quantify underlying mechanisms, we analyzed leaf abscisic acid (ABA) level, stomatal and leaf morphology, xylem structure, hydraulic efficiency, and hydraulic safety. Effects of eCO$_2$ manifested in a strong reduction in leaf-level g$_c$ (−55%) not caused by ABA and not reversible under low CO$_2$ (c. 200 ppm). Stomatal development and size were unchanged, while stomatal density increased (+18%). An increased vein-to-epidermis distance (+65%) suggested a larger leaf resistance to water flow. This was supported by anatomical adjustments of branch xylem having smaller conduits (−8%) and lower conduit lumen fraction (−11%), which resulted in a lower specific conductivity (−19%) and leaf-specific conductivity (−34%). These adaptations to CO$_2$ did not change stomatal sensitivity to soil or atmospheric drought, consistent with similar xylem safety thresholds. In summary, we found reductions of g$_c$ under elevated CO$_2$ to be reflected in anatomical adjustments and decreases in hydraulic conductivity. As these water savings were largely annulled by increases in leaf biomass, we do not expect alleviation of drought stress in a high CO$_2$ atmosphere

TOWARDS FOURTH-PARTY LOGISTICS PROVIDERS A Business Model for Cloud-Based Autonomous Logistics

Abstract: Cloud computing denotes a paradigm shift in computing that enables a flexible allocation of hardware and software resources on demand. Therewith, it is particularly appealing for applications with a high degree of computational complexity and dynamics. This paper identifies logistics planning and control as a promising application for clouds. However, two prerequisites must be met for cloud-based logistics control. Firstly, the platform-as-a-service layer must provide a synchronisation of the physically distributed real-world material flows and the data flows in the cloud. Secondly, appropriate and scalable control software must be implemented on the software-as-a-service layer. Apart from outlining the technical foundations, this paper describes how both steps enable a business model that is usually referred to as fourth-party logistics

The Fermi energy in oxides: assessing and understanding the limits using XPS

The Fermi energy in semiconductors can often be freely controlled across the whole energy gap by doping. This is not the case in oxides, where different mechanisms exist, which can limit the range of the Fermi energy. These limits can be caused by i) dopants having deep rather than shallow charge transition levels, ii) self-com­pen­sation where the Fermi energy dependence of the defect formation energy leads to spontaneous formation of compensating defects, iii) the change of the oxidation state of either the cations or the oxygen. The latter is particularly relevant for compounds with transition metal or rare earth cations and has been recently demonstrated to explain the low water splitting efficiency of hematite [1]. Please click Additional Files below to see the full abstract

Learning-based Calibration of Flux Crosstalk in Transmon Qubit Arrays

Superconducting quantum processors comprising flux-tunable data and coupler qubits are a promising platform for quantum computation. However, magnetic flux crosstalk between the flux-control lines and the constituent qubits impedes precision control of qubit frequencies, presenting a challenge to scaling this platform. In order to implement high-fidelity digital and analog quantum operations, one must characterize the flux crosstalk and compensate for it. In this work, we introduce a learning-based calibration protocol and demonstrate its experimental performance by calibrating an array of 16 flux-tunable transmon qubits. To demonstrate the extensibility of our protocol, we simulate the crosstalk matrix learning procedure for larger arrays of transmon qubits. We observe an empirically linear scaling with system size, while maintaining a median qubit frequency error below $300$ kHz

A first assessment of the impact of the extreme 2018 summer drought on Central European forests

In 2018, Central Europe experienced one of the most severe and long-lasting summer drought and heat wave ever recorded. Before 2018, the 2003 millennial drought was often invoked as the example of a “hotter drought”, and was classified as the most severe event in Europe for the last 500 years. First insights now confirm that the 2018 drought event was climatically more extreme and had a greater impact on forest ecosystems of Austria, Germany and Switzerland than the 2003 drought. Across this region, mean growing season air temperature from April to October was more than 3.3°C above the long-term average, and 1.2°C warmer than in 2003. Here, we present a first impact assessment of the severe 2018 summer drought and heatwave on Central European forests. In response to the 2018 event, most ecologically and economically important tree species in temperate forests of Austria, Germany and Switzerland showed severe signs of drought stress. These symptoms included exceptionally low foliar water potentials crossing the threshold for xylem hydraulic failure in many species and observations of widespread leaf discoloration and premature leaf shedding. As a result of the extreme drought stress, the 2018 event caused unprecedented drought-induced tree mortality in many species throughout the region. Moreover, unexpectedly strong drought-legacy effects were detected in 2019. This implies that the physiological recovery of trees was impaired after the 2018 drought event, leaving them highly vulnerable to secondary drought impacts such as insect or fungal pathogen attacks. As a consequence, mortality of trees triggered by the 2018 events is likely to continue for several years. Our assessment indicates that many common temperate European forest tree species are more vulnerable to extreme summer drought and heat waves than previously thought. As drought and heat events are likely to occur more frequently with the progression of climate change, temperate European forests might approach the point for a substantial ecological and economic transition. Our assessment also highlights the urgent need for a pan-European ground-based monitoring network suited to track individual tree mortality, supported by remote sensing products with high spatial and temporal resolution to track, analyse and forecast these transitions

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Change but no climate change: discourses of climate change in corporate social responsibility reporting in the oil industry

Using corpus linguistic tools and methods, this paper investigates the discourses of climate change in corporate social responsibility (CSR) and environmental reports produced by major oil companies from 2000 to 2013. It focuses on the frequency of key references to climatic changes and examines in detail discourses surrounding the most frequently used term ‘climate change’. The analysis points to shifting patterns in the ways in which climate change has been discursively constructed in the studied sample. Whereas in the mid-2000s, it was seen as a phenomenon that something could be done about, in recent years the corporate discourse has increasingly emphasised the notion of risk portraying climate change as an unpredictable agent. A pro-active stance signalled by the use of force metaphors is offset by a distancing strategy often indicated through the use of hedging devices and ‘relocation’ of climate change to the future and other stakeholders. In doing so, the discourse obscures the sector’s large contribution to environmental degradation and ‘grooms’ the public perception to believe that the industry actively engages in climate change mitigation. At the methodological level, this study shows how a combination of quantitative corpus-linguistic and qualitative discourse-analytical techniques can offer insights into the existence of salient discursive patterns and contribute to a better understanding of the role of language in performing ideological work in corporate communications

Heat treatment significantly increases the sharpness of silcrete stone tools

Humans were regularly heat-treating stone tool raw materials as early as 130,000 years ago. The late Middle Stone Age (MSA) and Late Stone Age (LSA) of South Africa's Western Cape region provides some of the earliest and most pervasive archaeological evidence for this behaviour. While archaeologists are beginning to understand the flaking implications of raw material heat treatment, its potential functional benefits remain unanswered. Using silcrete from the Western Cape region, we investigate the impact of heat treatment on stone tool cutting performance. We quantify the sharpness of silcrete in its natural, unheated form, before comparing it with silcrete heated in three different conditions. Results show that heat-treated silcrete can be significantly sharper than unheated alternatives, with cutting forces halving and energy requirements reducing by approximately two-thirds. The data suggest that silcrete may have been heat treated during the South African MSA and LSA to increase the sharpness and performance of stone cutting edges. This early example of material engineering has implications for understanding Stone Age populations’ technological capabilities, inventiveness and raw material choices. We predict that heat-treatment behaviours in other prehistoric and ethnographic contexts may also be linked to increases in edge sharpness and concerns about functional performance