Linux Based Ethernet Communication for Xilinx FPGAs

This article presents the implementation of an Ethernet communication platform for use on Xilinx FPGAs. The proposed solution relies on a synthesized embedded system to provide network data transfer and control capabilities, for use with synthesizable electronic devices. Most TCP/IP stack services and protocols were implemented and the design is flexible to allow adaptation and/or expansion for different application scenarios. Currently this platform is being used on the development of a FPGA based JTAG controller, with remote access. The embedded system hardware requires a MicroBlaze softcore microprocessor running a Petalinux operating system.info:eu-repo/semantics/publishedVersio

Environmental Impact of Meals: How Big Is the Carbon Footprint in the School Canteens?

The inhabitants of the world are expected to grow by two billion in the next two decades; as population increases, food demand rises too, leading to more intensive resource exploitation and greater negative externalities related to food production. In this paper the environmental impact of meals provided in school canteens are analysed through the Life Cycle Assessment methodology, in order to evaluate the GHGs emissions released by food production. Meals, and not just individual foods, have been considered so as to include in the analysis the nutritional aspects on which meals are based. Results shows that meat, fish and dairy products are the most impacting in terms of greenhouse gas emissions, with values that shift from 31.7 and 24.1 kg CO2 eq for butter and veal, to 2.37 kg CO2 eq for the octopus, while vegetables, legumes, fruit and cereals are less carbon intensive (average of 3.71 kg CO2 eq for the considered vegetables). When the environmental impact is related to the food energy, the best option are first courses because they combine a low carbon footprint with a high energy content. The results of the work can be used both by the consumer, who can base the meal choice on environmental impact information, and by food services, who can adjust menus to achieve a more sustainable production

Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks

BACKGROUND: Protein inter-residue contact maps provide a translation and rotation invariant topological representation of a protein. They can be used as an intermediary step in protein structure predictions. However, the prediction of contact maps represents an unbalanced problem as far fewer examples of contacts than non-contacts exist in a protein structure. In this study we explore the possibility of completely eliminating the unbalanced nature of the contact map prediction problem by predicting real-value distances between residues. Predicting full inter-residue distance maps and applying them in protein structure predictions has been relatively unexplored in the past. RESULTS: We initially demonstrate that the use of native-like distance maps is able to reproduce 3D structures almost identical to the targets, giving an average RMSD of 0.5Å. In addition, the corrupted physical maps with an introduced random error of ±6Å are able to reconstruct the targets within an average RMSD of 2Å. After demonstrating the reconstruction potential of distance maps, we develop two classes of predictors using two-dimensional recursive neural networks: an ab initio predictor that relies only on the protein sequence and evolutionary information, and a template-based predictor in which additional structural homology information is provided. We find that the ab initio predictor is able to reproduce distances with an RMSD of 6Å, regardless of the evolutionary content provided. Furthermore, we show that the template-based predictor exploits both sequence and structure information even in cases of dubious homology and outperforms the best template hit with a clear margin of up to 3.7Å. Lastly, we demonstrate the ability of the two predictors to reconstruct the CASP9 targets shorter than 200 residues producing the results similar to the state of the machine learning art approach implemented in the Distill server. CONCLUSIONS: The methodology presented here, if complemented by more complex reconstruction protocols, can represent a possible path to improve machine learning algorithms for 3D protein structure prediction. Moreover, it can be used as an intermediary step in protein structure predictions either on its own or complemented by NMR restraints

Estimation of local and external contributions of biomass burning to PM2.5 in an industrial zone included in a large urban settlement

A total of 85 PM2.5 samples were collected at a site located in a large industrial zone (Porto Marghera, Venice, Italy) during a 1-year-long sampling campaign. Samples were analyzed to determine water-soluble inorganic ions, elemental and organic carbon, and levoglucosan, and results were processed to investigate the seasonal patterns, the relationship between the analyzed species, and the most probable sources by using a set of tools, including (i) conditional probability function (CPF), (ii) conditional bivariate probability function (CBPF), (iii) concentration weighted trajectory (CWT), and (iv) potential source contribution function (PSCF) analyses. Furthermore, the importance of biomass combustions to PM2.5 was also estimated. Average PM2.5 concentrations ranged between 54 and 16 μg m−3 in the cold and warm period, respectively. The mean value of total ions was 11 μg m−3 (range 1–46 μg m−3): The most abundant ion was nitrate with a share of 44 % followed by sulfate (29 %), ammonium (14 %), potassium (4 %), and chloride (4 %). Levoglucosan accounted for 1.2 % of the PM2.5 mass, and its concentration ranged from few ng m−3 in warm periods to 2.66 μg m−3 during winter. Average concentrations of levoglucosan during the cold period were higher than those found in other European urban sites. This result may indicate a great influence of biomass combustions on particulate matter pollution. Elemental and organic carbon (EC, OC) showed similar behavior, with the highest contributions during cold periods and lower during summer. The ratios between biomass burning indicators (K+, Cl−, NO3−, SO42−, levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM2.5 ratios and was estimated to be 29 and 18 %, respectively

WASTE RECOVERY: Recycling and Waste to Energy

European Union is firmly determined to establish, within the different Countries which belong to it, a recycling society. This is a big challenge to face, because waste management systems in Europe are often still based on traditional options, as landfill or incineration with scarce energy recovery. This situation requires a very severe effort, from political, managerial, technical, social and economical points of view. However, it appears as the only solution to make European development sustainable. The Summer School \u201cWASTE RECOVERY: Recycling and Waste to Energy\u201d focused the attention on these considerations, inviting in Rimini, from 25 to 30 June 2007, some of the main experts, at Italian and European level, of the different aspects related to waste management, within which: - management strategies and guidelines; - regulations and law definitions; - eco-design of products; - technologies for material recovery (composting and recycling of different waste types, with a particular attention to ELV \u2013 End of Life Vehicles); - technologies for energy recovery; - assessment of impacts from different treatment and disposal processes (LCA, environmental monitoring); - related economical effects. The main lectures given at the Summer School converged in the present book, resulting in a description of the different perspectives from which the complex situation of waste management can be observed, integrating the different disciplinary expertises. The content includes also some of the results obtained so far by LITCAR (whose acronym means: Integrated Laboratory Technologies and Environmental Control in Waste Life Cycle), which is included in the Hi-Tech Network, co-funded by Emilia Romagna Region (Northern Italy). The present book can represent a reference mark for students, researchers, technicians, professionals and local administrators dealing with this fiel