A two-phase model for the Narrow Line Region of NGC 4151

NGC 4151 is one of the brightest and best-studied Seyfert galaxies. Here, we present a two-phase model of the narrow-line region (NLR) of NGC 4151. This study is motivated by (i) the fact that the X-ray spectrum of NGC 4151 is among the flattest known for Seyferts, and (ii) the recent Chandra detection of an X-ray narrow-line region in this galaxy. X-ray spectra as flat as that of NGC 4151 (Gamma_x = -1.5) are expected to favor the presence of two gas phases in pressure equilibrium (Krolik, McKee & Tarter 1981). In the present study, we show that a pronounced two-phase equilibrium develops in the extended emission-line region if we use the observed multi-wavelength spectrum of NGC 4151 to ionize the clouds. The material is stable to isobaric perturbations over a wide range of temperatures. We therefore propose that such a condition has arisen in the NLR of NGC 4151, and that it explains the detection of hot, extended X-ray gas which we identify as the NLR-cloud confining medium.Comment: 5 pages, A&A in press (scheduled for June/July issue). Preprint and related papers also available at http://www.xray.mpe.mpg.de/~skomossa

Assessing the environmental impact of logistics sites through CO2eq footprint computation

The environmental sustainability of logistics facilities is widely acknowledged as an important issue, but a comprehensive standardised methodology for assessing their environmental impact is lacking. This study proposes a structured model for quantifying both consumptions and generated greenhouse gas (GHG) emissions, adopting a three-phase methodology that combines multiple methods. A literature-based conceptual framework was leveraged to design an analytical model, and in-depth interviews with 11 senior logistics managers were conducted. The study offers a replicable methodology that considers heterogeneous sources of consumption and related end-use types, further splitting consumptions and emissions by warehouses' functional areas. It offers a set of Environmental Performance Indicators (EPIs) that could bolster a clearer understanding of the warehouse environmental performance. A robust tool is offered to managers to support their decision-making processes, allowing for both internal assessments and benchmarking with competitors or other players along the supply chain, thus contributing to shape company's, or even supply chain, sustainability strategies

Neural-Symbolic Monitoring and Adaptation

Runtime monitors check the execution of a system under scrutiny against a set of formal specifications describing a prescribed behaviour. The two core properties for monitoring systems are scalability and adaptability. In this paper we show how RuleRunner, our previous neural-symbolic monitoring system, can exploit learning strategies in order to integrate desired deviations with the initial set of specification. The resulting system allows for fast conformance checking and can suggest possible enhanced models when the initial set of specifications has to be adapted in order to include new patterns

Explainability Methods for Natural Language Processing: Applications to Sentiment Analysis

Sentiment analysis is the process of classifying natural lan-guage sentences as expressing positive or negative sentiments, and it is a crucial task where the explanation of a prediction might arguably be as necessary as the prediction itself. We analysed di fierent explanation techniques, and we applied them to the classification task of Sentiment Analysis. We explored how attention-based techniques can be exploited to extract meaningful sentiment scores with a lower computational cost than existing XAI methods

a decoupled numerical procedure for modelling soil interaction in the computation of the dynamic response of a rail track

Abstract The problem of vibration transmitted by train traffic to the soil in the case of railway lines in urban areas is gaining increasing attention in environmental impact analysis. An efficient method to consider both the train-track interaction in detail and the vibration transmitted to the soil nearby with an affordable computational cost is desirable. The paper proposes a numerical procedure based on a substructuring approach, in which the system is divided into three main subdomains: the train running on the track, the rail subjected to the loads coming from the train and the reactions from the sleepers and the "ground" sub-system, composed by the sleepers, the ballast with its subgrade and the actual ground. The overall procedure is divided into subsequent steps: first, the finite element modelling of the sleeper-ballast-subgrade combined system, characterized within the linear elastic field by means of frequency response functions at rail-sleeper interfaces. In a second step, moving loads transmitted to the track are computed by numerical time domain integration of the equations of motion of the train running on a model of the track only, in which the subgrade is modelled as a series of spring-damper elements, whose parameters are tuned according to the results of the FE model used in the first step and therefore consistent with it. Non-linear behavior of the rail-wheel interaction can be accounted for by the time-domain procedure. The track dynamics is finally computed via direct frequency domain analysis; the track is again modelled by Finite Elements, loaded by the forces transmitted by the train wheels and by the supporting sleepers. Finally, the vibrations propagated through the soil to a general receiver point are evaluated. The procedure can exploit favorable properties of frequency domain analysis in treating moving loads; in addition, frequency dependent properties of materials can be introduced

Using the Sound Card as a Timer

Experiments in mechanics can often be timed by the sounds they produce. In such cases, digital audio recordings provide a simple way of measuring time intervals with an accuracy comparable to that of photogate timers. We illustrate this with an experiment in the physics of sports: to measure the speed of a hard-kicked soccer ball.Comment: 3 pages, 4 figures, Late

Sensing of DVB-T signals for white space cognitive radio systems

In cognitive radio networks, systems operating in digital television white spaces are particularly interesting for practical applications. In this paper, we consider single- antenna and multi-antenna spectrum sensing of real DVB-T signals under different channel conditions. Some of the most important algorithms are considered and compared, including energy detection, eigenvalue based techniques and methods exploiting OFDM signal knowledge. The obtained results show the algorithm performance and hierarchy in terms of ROC and detection probability under fixed false alarm rate, for different channel profiles in case of true DVB-T signal