Skylight: a new code for general-relativistic ray-tracing and radiative transfer in arbitrary spacetimes

To reproduce the observed spectra and light curves originated in the neighborhood of compact objects requires accurate relativistic ray-tracing codes. In this work, we present Skylight, a new numerical code for general-relativistic ray tracing and radiative transfer in arbitrary space-time geometries and coordinate systems. The code is capable of producing images, spectra, and light curves from astrophysical models of compact objects as seen by distant observers. We incorporate two different schemes, namely Monte Carlo radiative transfer, integrating geodesics from the astrophysical region to distant observers, and camera techniques with backwards integration from the observer to the emission region. The code is validated by successfully passing several test cases, among them: thin accretion disks and neutron star hot spot emission

NFV service dynamicity with a DevOps approach : demonstrating zero-touch deployment & operations

Next generation network services will be realized by NFV-based microservices to enable greater dynamics in deployment and operations. Here, we present a demonstrator that realizes this concept using the NFV platform built in the EU FP7 project UNIFY. Using the example of an Elastic Router service, we show automated deployment and configuration of service components as well as corresponding monitoring components facilitating automated scaling of the entire service. We also demonstrate automatic execution of troubleshooting and debugging actions. Operations of the service are inspired by DevOps principles, enabling quick detection of operational conditions and fast corrective actions. This demo conveys essential insights on how the life-cycle of an NFV-based network service may be realized in future NFV platforms

Molecularly imprinted polymers combined with electrochemical sensors for food contaminants analysis

Detection of relevant contaminants using screening approaches is a key issue to ensure food safety and respect for the regulatory limits established. Electrochemical sensors present several advantages such as rapidity; ease of use; possibility of on-site analysis and low cost. The lack of selectivity for electrochemical sensors working in complex samples as food may be overcome by coupling them with molecularly imprinted polymers (MIPs). MIPs are synthetic materials that mimic biological receptors and are produced by the polymerization of functional monomers in presence of a target analyte. This paper critically reviews and discusses the recent progress in MIP-based electrochemical sensors for food safety. A brief introduction on MIPs and electrochemical sensors is given; followed by a discussion of the recent achievements for various MIPs-based electrochemical sensors for food contaminants analysis. Both electropolymerization and chemical synthesis of MIP-based electrochemical sensing are discussed as well as the relevant applications of MIPs used in sample preparation and then coupled to electrochemical analysis. Future perspectives and challenges have been eventually given

Peptides, DNA and MIPs in gas sensing. From the realization of the sensors to sample analysis

Detection and monitoring of volatiles is a challenging and fascinating issue in environmental analysis, agriculture and food quality, process control in industry, as well as in ‘point of care’ diagnostics. Gas chromatographic approaches remain the reference method for the analysis of volatile organic compounds (VOCs); however, gas sensors (GSs), with their advantages of low cost and no or very little sample preparation, have become a reality. Gas sensors can be used singularly or in array format (e.g., e-noses); coupling data output with multivariate statical treatment allows un-target analysis of samples headspace. Within this frame, the use of new binding elements as recognition/interaction elements in gas sensing is a challenging hot-topic that allowed unexpected advancement. In this review, the latest development of gas sensors and gas sensor arrays, realized using peptides, molecularly imprinted polymers and DNA is reported. This work is focused on the description of the strategies used for the GSs development, the sensing elements function, the sensors array set-up, and the application in real cases

A little less interaction, a little more action: A modular framework for network troubleshooting

An ideal network troubleshooting system would be an almost fully automated system, monitoring the whole network at once, feeding the results to a knowledge-based decision making system that suggests actions to the operator or corrects the failure automatically. Reality is quite the contrary: operators separated in their offices try to track down complex networking failures in their own way, which is generally a long sequence of manually edited parallel shell commands (mostly ping, traceroute, route, iperf, ofctl etc.). This process requires operators to be "masters of complexity" (which they often are) and continuous interaction. In this paper we aim at narrowing this huge gap between vision and reality by introducing a modular framework capable of (i) formalizing troubleshooting processes as the concatenation of executable functions [called Troubleshooting Graphs (TSGs)], (ii) executing these graphs via an interpreter, (iii) evaluating and navigating between the outputs of the functions and (iv) sharing troubleshooting know-hows in a formalized manner.Comment: 18 pages, 9 figure

UBEM's archetypes improvement via data-driven occupant-related schedules randomly distributed and their impact assessment

In Urban Building Energy Models (UBEMs), buildings are usually modelled via archetypes describing occupants’ behaviour via fixed schedules. This research (i) creates data-driven schedules for electric use and occupancy from smart meter readings randomly distributed in the model to improve residential archetypes, (ii) assesses the impact of these schedules on UBEMs’ energy results at different temporal resolutions and spatial scales. The novel assessment procedure exploits integrated heat maps based on coefficients of variation of the root means square error (CVRMSE). The outcomes show that differences in energy needs, with randomized schedules, range based on temporal and spatial aggregation. Yearly, for the entire neighbourhood, heating and cooling energy needs, and electric uses are estimated -2%, +1%, and +18% compared to the base case. The outputs show that, when simulations are focused on the entire district, fixed schedules can be enough to describe energy patterns. However, if the simulation is focused on small groups of buildings (e.g., 5 or fewer), randomising the schedules can create variability in the model in terms of electric use and occupancy among buildings characterized by the same archetype. The followed methodology can be exploited also with larger databases and eventually verified with also other types of data

Retrospective evaluation of the ST segment electrocardiographic features in 180 healthy dogs

Objectives Normal features of the ST segment are poorly characterised in dogs. This study aimed to describe ST segment characteristics in a population of healthy dogs. Materials and Methods Medical records were reviewed to identify healthy dogs that underwent an electrocardiogram. Several ST segment qualitative parameters were evaluated: presence/absence of deviation, type of deviation (depression/elevation) and morphological patterns of depression (horizontal, downsloping, upsloping and sagging) and elevation (horizontal, concave and convex). Moreover, the amplitude of ST segment depression/elevation was measured. The potential effect of sex, bodyweight, age and somatotype on the presence/absence of ST segment deviation was evaluated through binary logistic regression. Results One hundred and eighty dogs were enrolled. The deviation was evident in 43 of 180 dogs (23.9%), among which 36 showed depression and seven showed elevation. The median depression amplitude was 0.1 (range 0.05 to 0.3) mV. The mean elevation amplitude was 0.136 +/- 0.055 mV. Concerning depression morphology, the horizontal pattern was overrepresented, followed by the downsloping and upsloping ones. Concerning elevation morphology, all dogs showed a concave pattern. No meaningful effect of sex, bodyweight, age and somatotype on the presence/absence of ST segment deviation was documented. Clinical Significance Normal features of canine ST segment were described and made available for clinical use

Automating the measurement of physiological parameters: a case study in the image analysis of cilia motion

International audienceAs image processing and analysis techniques improve, an increasing number of procedures in bio-medical analyses can be automated. This brings many benefits, e.g improved speed and accuracy, leading to more reliable diagnoses and follow-up, ultimately improving patients outcome. Many automated procedures in bio-medical imaging are well established and typically consist of detecting and counting various types of cells (e.g. blood cells, abnormal cells in Pap smears, and so on). In this article we propose to automate a different and difficult set of measurements, which is conducted on the cilia of people suffering from a variety of respiratory tract diseases. Cilia are slender, microscopic, hair-like structures or organelles that extend from the surface of nearly all mammalian cells. Motile cilia, such as those found in the lungs and respiratory tract, present a periodic beating motion that keep the airways clear of mucus and dirt. In this paper, we propose a fully automated method that computes various measurements regarding the motion of cilia, taken with high-speed video-microscopy. The advantage of our approach is its capacity to automatically compute robust, adaptive and regionalized measurements, i.e. associated with different regions in the image. We validate the robustness of our approach, and illustrate its performance in comparison to the state-of-the-art