Materials and techniques of Art Nouveau architecture in Italy and Portugal: a first insight for an European route to consistent restoration

The results of the investigations on building materials and techniques of Casa Major Pessoa, a typical Art Nouveau construction in Aveiro (Portugal), and two coeval Art Nouveau buildings in Bologna (Italy) are presented as a methodological contribution to the restoration of this kind of buildings. This is the first step to ascertain the existence of a common thread between local materials, technologies and architecture in European countries at the same period. A holistic approach was adopted: materials were investigated along with architectural, structural and technological features, in order to achieve a first insight into the Art Nouveau architecture in Europe in particular for its consistent restoration without loss of historical memory

Transcriptional Regulation in Rocket Leaves as Affected by Salinity

Salinity is one of the major abiotic stress causing yield losses and decreasing product quality. The beneficial effects of biostimulant products to enhance plant tolerance to abiotic stresses have been reported in several crops, but their mode of action is poorly understood. This work aims to better understand the effect of salt stress on wild rocket treated with a borage extract. The expression of some of the transcription factors (TFs) typically involved in salt stress response was studied within a 24 h period. Physiological parameters such as chlorophyll, chlorophyll a fluorescence, carotenoids, phenols, and anthocyanin were analyzed. Results obtained showed that salt stress induced a general increase in the expression levels of almost all TFs studied, whereas the treatment with the plant-base extract only induced an increase at specific time points. Moreover, the approach adopted allowed indagating the change in gene expression during time. Different pathways such as sugars metabolism, cuticular wax biosynthesis, and brassinosteroids signaling took part in plant responses

Deep learning for inferring cause of data anomalies

Daily operation of a large-scale experiment is a resource consuming task, particularly from perspectives of routine data quality monitoring. Typically, data comes from different sub-detectors and the global quality of data depends on the combinatorial performance of each of them. In this paper, the problem of identifying channels in which anomalies occurred is considered. We introduce a generic deep learning model and prove that, under reasonable assumptions, the model learns to identify 'channels' which are affected by an anomaly. Such model could be used for data quality manager cross-check and assistance and identifying good channels in anomalous data samples. The main novelty of the method is that the model does not require ground truth labels for each channel, only global flag is used. This effectively distinguishes the model from classical classification methods. Being applied to CMS data collected in the year 2010, this approach proves its ability to decompose anomaly by separate channels.Comment: Presented at ACAT 2017 conference, Seattle, US

Effect of heuristics on serendipity in path-based storytelling with linked data

Path-based storytelling with Linked Data on the Web provides users the ability to discover concepts in an entertaining and educational way. Given a query context, many state-of-the-art pathfinding approaches aim at telling a story that coincides with the user's expectations by investigating paths over Linked Data on the Web. By taking into account serendipity in storytelling, we aim at improving and tailoring existing approaches towards better fitting user expectations so that users are able to discover interesting knowledge without feeling unsure or even lost in the story facts. To this end, we propose to optimize the link estimation between - and the selection of facts in a story by increasing the consistency and relevancy of links between facts through additional domain delineation and refinement steps. In order to address multiple aspects of serendipity, we propose and investigate combinations of weights and heuristics in paths forming the essential building blocks for each story. Our experimental findings with stories based on DBpedia indicate the improvements when applying the optimized algorithm

Monte Carlo Production Management at CMS

The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events. During the RunI of LHC (20102012), CMS has produced over 12 Billion simulated events, organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up). In order to aggregate the information needed for the configuration and prioritization of the events production, assure the book-keeping of all the processing requests placed by the physics analysis groups, and to interface with the CMS production infrastructure, the web- based service Monte Carlo Management (McM) has been developed and put in production in 2013. McM is based on recent server infrastructure technology (CherryPy + AngularJS) and relies on a CouchDB database back-end. This contribution covers the one and half year of operational experience managing samples of simulated events for CMS, the evolution of its functionalities and the extension of its capability to monitor the status and advancement of the events production

SGI como instrumento complementar na avaliação do impacto ambiental da agricultura.

Divulga a metodologia, desenvolvida pelo Núcleo, de caracterização e avaliação do impacto ambiental da agricultura, baseada no uso de SGI. O projeto foi executado sobre conjuntos de pequenas propriedades com diferentes sistemas de produção. Na escala municipal articulou espacialmente, via SGI, o uso das terras e os coeficientes técnicos dos sistemas de produção aferentes. Foram geradas 32 cartas de impacto ambiental da atividade agrícola, por recursos e insumos

Observations on the embryonic development of domestic meat-type guinea fowl (Numida meleagris)

Guinea fowl breeding for meat production is widespread across Europe and the USA. For hatcheries to achieve their output potentials, they need in-depth knowledge about incubation techniques and guinea fowl embryonic development. The aim of this study was to provide updated quantitative data on the developing meat-type strain embryo and to describe its embryonic growth pattern in terms of embryonic weight modelled using Gompertz and logistic functions. Eggs from a 56-week-old genetically controlled flock (Galor S.A.S., Amboise, France) were individually weighed and incubated according to good hatchery practices. 10 embryos were randomly removed every 12 h through to hour 192 of incubation, and thereafter every 24 h. Incubation traits, blastoderm diameter, vitelline circulation diameter, and embryo body weight were recorded, and the mean daily wet embryo-specific mass was calculated. During each session, photographic documentation of the embryos was also obtained, including a general view of the egg content as well as the isolated embryonic body. Embryonic growth curves were estimated using Gompertz and logistic functions, and their parameters are given. High fertility (96%) and hatchability (81%) rates were observed, and the mean keet weight was 32 g at hatch. The accuracy of the curve fit was high for both models. The curves’ inflection points occurred on days 21 and 23 for the logistic and Gompertz models, respectively, demonstrating an embryonic growth pattern typical of a precocial bird species. A photographic chart of the in-ovo chronological development of guinea fowl is provided.HIGHLIGHTS The study follows the incubation and embryonic development of meat-type guinea fowl (Numida meleagris). Daily photographic images and graphical growth models of body weight document the birds’ embryonic development. The results provide effective practical help for hatchery practices by enabling the determination of embryo age