Comparative Life Cycle Assessment (LCA) of Porous Asphalt Mixtures with Sustainable and Recycled Materials: A Cradle-to-Gate Approach

: The road and construction sectors consume a large number of natural resources and energy, contributing significantly to waste generation and greenhouse gas emissions (GHG). The use of recycled aggregate from construction and demolition waste as a substitute for virgin aggregate is a current practice in the construction of new road sections. Additionally, in recent years, there has been an increasing focus on finding alternatives to bitumen for binders used in asphalt mixes. This study investigates and compares the impacts associated with two porous asphalt mixtures produced with CDW aggregates, virgin aggregates, and a polyolefin-based synthetic transparent binder through an LCA methodology. A cradle-to-gate approach was employed. Model characterization for calculating the potential environmental impacts of each porous asphalt mixture was performed using the ReCipe 2016 assessment method at the midpoint and endpoint levels. The results are presented with reference to a baseline scenario corresponding to a porous asphalt mixture, confirming the benefits associated with the use of recycled aggregates and in some cases the benefits of not using bitumen-based binders. This work contributes to the understanding of the importance of choosing the least environmentally damaging solution during the production or rehabilitation of road pavement infrastructure

Building a Risk Model for the Patient-centred Care of Multiple Chronic Diseases

With the increase of multimorbidity due to population ageing, managing multiple chronic health conditions is a rising challenge. Machine-learning can contribute to a better understanding of persons with multimorbidity (PwMs) and how to design an effective framework of care and support for them. We present a risk model of older PwMs that was derived from the TILDA dataset, a longitudinal study of the ageing Irish population. This model is based on a 26-nodes Bayesian network that represents patients possibly having one or more chronic conditions among diabetes, chronic obstructive pulmonary disease and arthritis, through a joint probability distribution of demographic, symptomatic and behavioral dimensions. We describe our method, give an exploratory analysis of the risk model, and assess its prediction accuracy in a cross-validation experiment. Finally we discuss its use in supporting management of care for PwMs, drawing on comments from health practitioners on the model

Low temperature district heating networks for complete energy needs fulfillment

In order to reduce fossil fuels consumption and pollutant emissions, high contribution is given by district heating. In particular, the integration with renewable energy may lead to a significant increase in energy conversion efficiency and energy saving. Further benefits can be achieved with low temperature district heating, reducing the thermal dissipations through the network and promoting the exploitation of low enthalpy heat sources. The aim of the paper is the analysis of the potential related to the conversion of existing district heating networks, to increase the exploitation of renewable sources and eliminate pollutant emissions in the city areas. Further aim, in this context, is the optimization – from both energy production and operation management viewpoints – of a low temperature district heating network for the fulfillment of the connected users’ energy needs. To this respect, a traditional network with a fossil fuel driven thermal production plant has been considered and compared with a low temperature district heating scenario, including geothermal heat pumps, photovoltaic panels and absorption chillers. These scenarios have been analyzed and optimized with an in-house developed software, allowing to demonstrate the reduction of primary energy consumption and CO2 pollutant emissions achievable with low temperature networks. In addition, a preliminary economic evaluation has been carried out to compare the proposed solution with traditional district heating

QueryOR: a comprehensive web platform for genetic variant analysis and prioritization

Background: Whole genome and exome sequencing are contributing to the extraordinary progress in the study of human genetic variants. In this fast developing field, appropriate and easily accessible tools are required to facilitate data analysis. Results: Here we describe QueryOR, a web platform suitable for searching among known candidate genes as well as for finding novel gene-disease associations. QueryOR combines several innovative features that make it comprehensive, flexible and easy to use. Instead of being designed on specific datasets, it works on a general XML schema specifying formats and criteria of each data source. Thanks to this flexibility, new criteria can be easily added for future expansion. Currently, up to 70 user-selectable criteria are available, including a wide range of gene and variant features. Moreover, rather than progressively discarding variants taking one criterion at a time, the prioritization is achieved by a global positive selection process that considers all transcript isoforms, thus producing reliable results. QueryOR is easy to use and its intuitive interface allows to handle different kinds of inheritance as well as features related to sharing variants in different patients. QueryOR is suitable for investigating single patients, families or cohorts. Conclusions: QueryOR is a comprehensive and flexible web platform eligible for an easy user-driven variant prioritization. It is freely available for academic institutions at http://queryor.cribi.unipd.it/

GASTon: A Graph-Exploration System for Indexing, Annotating and Visualizing PubMed Articles to Enhance the Analysis of Social deTerminants of Health

Many works have shown associations between social determinants of health (SDoH) –the social circumstances in which people live– and health-related outcomes. However, the lack of SDoH data increases the challenges in measuring and understanding their effect on people’s health and health systems. In this paper, we present GASTon, a system for the indexing, annotation, and graph-based rendering of PubMed information to enable the search and retrieval of SDoHs in scientific literature. Our work provides a way to associate specific concepts with peer-reviewed articles to simplify the search for social factors. It builds a knowledge graph based on PubMed publications and associates them with concepts extracted from the Unified Medical Language System (UMLS) Metathesaurus. GASTon allows a full-text search and graph-based navigation and supports an overview of the concepts and related publications. Moreover, the architecture allows scale-up thanks to its containerized nature and parallelizat ion capabilities. The system is open-source under the Apache V2 license

Muon Simulations for Super-Kamiokande, KamLAND and CHOOZ

Muon backgrounds at Super-Kamiokande, KamLAND and CHOOZ are calculated using MUSIC. A modified version of the Gaisser sea level muon distribution and a well-tested Monte Carlo integration method are introduced. Average muon energy, flux and rate are tabulated. Plots of average energy and angular distributions are given. Implications on muon tracker design for future experiments are discussed.Comment: Revtex4 33 pages, 16 figures and 4 table

Setup and Validation of a Targeted Next-Generation Sequencing Approach for the Diagnosis of Lysosomal Storage Disorders.

Lysosomal storage disorders (LSDs) are monogenic diseases, due to accumulation of specific undegraded substrates into lysosomes. LSD diagnosis could take several years because of both poor knowledge of these diseases and shared clinical features. The diagnostic approach includes clinical evaluations, biochemical tests, and genetic analysis of the suspected gene. In this study, we evaluated an LSD targeted sequencing panel as a tool capable to potentially reverse this classic diagnostic route. The panel includes 50 LSD genes and 230 intronic sequences conserved among 33 placental mammals. For the validation phase, 56 positive controls, 13 biochemically diagnosed patients, and nine undiagnosed patients were analyzed. Disease-causing variants were identified in 66% of the positive control alleles and in 62% of the biochemically diagnosed patients. Three undiagnosed patients were diagnosed. Eight patients undiagnosed by the panel were analyzed by whole exome sequencing: for two of them, the disease-causing variants were identified. Five patients, undiagnosed by both panel and exome analyses, were investigated through array comparative genomic hybridization: one of them was diagnosed. Conserved intronic fragment analysis, performed in cases unresolved by the first-level analysis, evidenced no candidate intronic variants. Targeted sequencing has low sequencing costs and short sequencing time. However, a coverage >60× to 80× must be ensured and/or Sanger validation should be performed. Moreover, it must be supported by a thorough clinical phenotyping