Carbon accounting in the context of multi-criteria assessment for SLES: challenges and opportunities

In the UK, national carbon emission reduction targets aim to reach Net Zero by 2050, with a fully decarbonised electricity system by 2035. Smart Local Energy Systems (SLES) are being deployed to combine and intelligently control complementary low and zero carbon technologies within micro-gridsto amplify their impacts and accelerate this ambitious transition towards a decarbonized energy system and low-carbon society. Today, national and local governments monitor the potential carbon reduction of energy system retrofitting and policy implementation through simplified carbon accounting methods, which allow for calculation of the accumulated carbon emissions. This focus on carbon may, however, neglect broader socioeconomic impacts and benefits of these actions. This paper describes the how the application of a multi-criteria assessment tool focusing on SLES can be used to evaluate (i) the carbon emissions from an energy system and (ii) the carbon reduction potential of renewable and smart energy technology implementation. Alongside the carbon accounting this MCA-SLES tool provides assessment and insights into the local socioeconomic and environmental benefits and impacts of the SLES development. The application of such a complex assessment tool has challenges in application, such as data collection, the intensity of the stakeholder approach, and the large volume of information for user dissemination. This paper illustrates how the developed assessment tool mitigates for these challenges and highlights the opportunity for small-scale energy development projects to employ it to assess project feasibility and progress towards economic, social, and environmental co-benefits

Internal Friction and Vulnerability of Mixed Alkali Glasses

Based on a hopping model we show how the mixed alkali effect in glasses can be understood if only a small fraction c_V ofthe available sites for the mobile ions is vacant. In particular, we reproduce the peculiar behavior of the internal friction and the steep fall (''vulnerability'') of the mobility of the majority ion upon small replacements by the minority ion. The single and mixed alkali internal friction peaks are caused by ion-vacancy and ion-ion exchange processes. If c_V is small, they can become comparable in height even at small mixing ratios. The large vulnerability is explained by a trapping of vacancies induced by the minority ions. Reasonable choices of model parameters yield typical behaviors found in experiments.Comment: 4 pages, 4 figure

Dynamic Analysis of Executables to Detect and Characterize Malware

It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life. We examine the use of machine learning algorithms to detect malware using the system calls generated by executables-alleviating attempts at obfuscation as the behavior is monitored rather than the bytes of an executable. We examine several machine learning techniques for detecting malware including random forests, deep learning techniques, and liquid state machines. The experiments examine the effects of concept drift on each algorithm to understand how well the algorithms generalize to novel malware samples by testing them on data that was collected after the training data. The results suggest that each of the examined machine learning algorithms is a viable solution to detect malware-achieving between 90% and 95% class-averaged accuracy (CAA). In real-world scenarios, the performance evaluation on an operational network may not match the performance achieved in training. Namely, the CAA may be about the same, but the values for precision and recall over the malware can change significantly. We structure experiments to highlight these caveats and offer insights into expected performance in operational environments. In addition, we use the induced models to gain a better understanding about what differentiates the malware samples from the goodware, which can further be used as a forensics tool to understand what the malware (or goodware) was doing to provide directions for investigation and remediation.Comment: 9 pages, 6 Tables, 4 Figure

Dynamic mooring simulation with Code_Aster with application to a floating wind turbine

This is the final version of the article. Available from Elsevier via the DOI in this record.The design of reliable station-keeping systems for permanent floating structures such as offshore renewable energy devices is vital to their lifelong integrity. In highly dynamic and/or deep-water applications, including hydrodynamics and structural dynamics in the mooring analysis is paramount for the accurate prediction of the loading on the lines and hence their dimensioning. This article presents a new workflow based on EDF R&D's open-source, finite-element analysis tool Code_Aster, enabling the dynamic analysis of catenary mooring systems, with application to a floating wind turbine concept. The University of Maine DeepCwind-OC4 basin test campaign is used for validation, showing that Code_Aster can satisfactorily predict the fairlead tensions in both regular and irregular waves. In the latter case, all of the three main spectral components of tension observed in the experiments are found numerically. Also, the dynamic line tension is systematically compared with that provided by the classic quasi-static approach, thereby confirming its limitations. Robust dynamic simulation of catenary moorings is shown to be possible using this generalist finite-element software, provided that the inputs be organised consistently with the physics of offshore hydromechanics.IDCORE is funded by the ETI and the RCUK Energy programme, grant number EP/J500847/1. The authors are grateful for the funding provided by these institutions, and to EDF R&D for hosting and supervising the industrial doctorate which expressed the present work

Aging of CKN:Modulus Versus Conductivity Analysis

It was recently reported that the electrical modulus peaks narrows upon annealing of the ionic system CKN [Paluch et al., Phys. Rev. Lett. 110, 015702 (2013)], which was interpreted as providing evidence of dynamic heterogeneity of this glass-forming liquid. An analysis of the same data in terms of the ac conductivity shows no shape changes, however. We discuss the relation between both findings and show further that the ac conductivity conforms to the prediction of the random barrier model (RBM) at all times during the annealing

The geometry of the hot corona in MCG-05-23-16 constrained by X-ray polarimetry

We report on the second observation of the radio-quiet active galactic nucleus MCG-05-23-16 performed with the Imaging X-ray Polarimetry Explorer (IXPE). The observation started on 2022 November 6 for a net observing time of 640 ks, and was partly simultaneous with NuSTAR (86 ks). After combining these data with those obtained in the first IXPE pointing on 2022 May (simultaneous with XMM-Newton and NuSTAR) we find a 2-8 keV polarization degree Π = 1.6 ± 0.7 (at 68 per cent confidence level), which corresponds to an upper limit Π = 3.2 per cent (at 99 per cent confidence level). We then compare the polarization results with Monte Carlo simulations obtained with the monk code, with which different coronal geometries have been explored (spherical lamppost, conical, slab, and wedge). Furthermore, the allowed range of inclination angles is found for each geometry. If the best-fitting inclination value from a spectroscopic analysis is considered, a cone-shaped corona along the disc axis is disfavoured.</p

Detection of Very Low-Frequency Quasi-Periodic Oscillations in the 2015 Outburst of V404 Cygni

In June 2015, the black hole X-ray binary (BHXRB) V404 Cygni went into outburst for the first time since 1989. Here, we present a comprehensive search for quasi-periodic oscillations (QPOs) of V404 Cygni during its recent outburst, utilizing data from six instruments on board five different X-ray missions: Swift/XRT, Fermi/GBM, Chandra/ACIS, INTEGRAL's IBIS/ISGRI and JEM-X, and NuSTAR. We report the detection of a QPO at 18 mHz simultaneously with both Fermi/GBM and Swift/XRT, another example of a rare but slowly growing new class of mHz-QPOs in BHXRBs linked to sources with a high orbital inclination. Additionally, we find a duo of QPOs in a Chandra/ACIS observation at 73 mHz and 1.03 Hz, as well as a QPO at 136 mHz in a single Swift/XRT observation that can be interpreted as standard Type-C QPOs. Aside from the detected QPOs, there is significant structure in the broadband power, with a strong feature observable in the Chandra observations between 0.1 and 1 Hz. We discuss our results in the context of current models for QPO formation.Comment: 17 pages, 9 figures, published in Ap

Towards understanding interactions between Sustainable Development Goals: the role of environment–human linkages

Only 10 years remain to achieve all Sustainable Development Goals (SDGs) globally, so there is a growing need to increase the effectiveness and efficiency of action by targeting multiple SDGs. The SDGs were conceived as an ‘indivisible whole’, but interactions between SDGs need to be better understood. Several previous assessments have begun to explore interactions including synergies and possible conflicts between the SDGs, and differ widely in their conclusions. Although some highlight the role of the more environmentally-focused SDGs in underpinning sustainable development, none specifically focuses on environment-human linkages. Assessing interactions between SDGs, and the influence of environment on them, can make an important contribution to informing decisions in 2020 and beyond. Here, we review previous assessments of interactions among SDGs, apply an influence matrix to assess pairwise interactions between all SDGs, and show how viewing these from the perspective of environment-human linkages can influence the outcome. Environment, and environment-human linkages, influence most interactions between SDGs. Our action-focused assessment enables decision makers to focus environmental management to have the greatest impacts, and to identify opportunities to build on synergies and reduce trade-offs between particular SDGs. It may enable sectoral decision makers to seek support from environment managers for achieving their goals. We explore cross-cutting issues and the relevance and potential application of our approach in supporting decision making for progress to achieve the SDGs