Structural models of critical regions in old-type r.c. frames with smooth rebars

Structural assessment of existing reinforced concrete constructions under gravity loads and seismic actions has a high social and economical impact; actually in many European countries, most of the buildings dates back to 1960s and 1970s and cannot ensure satisfactory seismic response, since many areas have been later classified as seismic or since design has been carried out according to obsolete codes. These structures are generally reinforced with smooth bars that exhibit poor bond and need specific anchoring end details. In the present paper, some key aspects of structural models of smooth reinforcement for old-type r.c. frame analysis are reported. Results of experimental tests on smooth reinforcement and circular hook anchoring devices are also used to discuss some aspects of behavioural models of beam to column critical regions.     

Analytical authentication of organic products: an overview of markers

Consumers' interest in organic foods is increasing and so is the need for robust analytical tools for their authentication. This review focuses on the most promising biomarkers/analytical approaches that are available for the authentication of organic produce. Food products have been subdivided into two groups: foods of plant origin (crops) and foods of animal origin (meat, milk and dairy products, eggs and fish). For each food category the most suitable biomarkers are presented and their potential for authentication is discussed. In the light of current knowledge, it is unlikely that the authentication of organic food products can be attained by the measurement of a single marker. Analytical approaches based on the measurement of multiple markers and/or complex chemical or physical profiles/fingerprints supported by multivariate statistical analysis seem considerably more promising in this respect. For the development of robust classification models, well‐designed experimental studies must be performed that rely on data sets that are both well balanced and of sufficient size to ensure that all relevant sources of variation for the target biomarkers are included in the reference database. Copyright © 2012 Society of Chemical Industry     

The behavior of dietary fiber in the gastrointestinal tract determines its physiological effect

A diet rich in dietary fiber (DF) is considered healthy and recommended dietary intake of DF is established all over the world. The physiological effect of DF is mostly related to its behavior during digestion. In this review, the behavior of DF in the human digestive tract is discussed and linked to its physiological effect with special attention to four aspects of such behavior: (i) the modulation of bioavailability by the plant cell walls, (ii) the effect of DF on the rheological and colloidal state of digesta, (iii) the binding of DF with phenolic compounds, bile salts, mineral ions, and digestive enzymes, and (iv) DF fermentation in the large intestine and the corresponding effect on microbiota composition. It is stressed that the detailed chemical characterization of DF is crucial to explain its effect on health and that DF behavior in the digestive tract can be modulated by interactions with other food and meal components so that information of the bare content in DF of food is not sufficient to predict its physiological effect.     

Energy saving in existing buildings by an intelligent use of interoperable ICTs

In this paper, we report a methodology, developed in the context of Smart Energy Efficient Middleware for Public Spaces European Project, aimed at exploiting ICT monitoring and control services to reduce energy usage and CO₂ footprint in existing buildings. The approach does not require significant construction work as it is based on commercial-off-the-shelf devices and, where present, it exploits and integrates existing building management systems with new sensors and actuator networks. To make this possible, the proposed approach leverages upon the following main contributions: (a) to develop an integrated building automation and control system, (b) to implement a middleware for the energy-efficient buildings domain, (c) to provide a multi-dimensional building information modelling-based visualisation, and (d) to raise people’s awareness about energy efficiency. The research approach adopted in the project started with the selection, as case studies, of representative test and reference rooms in modern and historical buildings chosen for having different requirements and constraints in term of sensing and control technologies. Then, according to the features of the selected rooms, the strategies to reduce the energy consumptions were defined, taking into account the potential savings related to lighting, heating, ventilation, and air conditioning (HVAC) systems and other device loads (PC, printers, etc.). The strategies include both the control of building services and devices and the monitoring of environmental conditions and energy consumption. In the paper, the energy savings estimated through simulation, for both HVAC and lighting, are presented to highlight the potential of the designed system. After the implementation of the system in the demonstrator, results will be compared with the monitored data.     

Modeling food matrix effects on chemical reactivity: Challenges and perspectives

ABSTRACT

The same chemical reaction may be different in terms of its position of the equilibrium (i.e., thermodynamics) and its kinetics when studied in different foods. The diversity in the chemical composition of food and in its structural organization at macro-, meso-, and microscopic levels, that is, the food matrix, is responsible for this difference. In this viewpoint paper, the multiple, and interconnected ways the food matrix can affect chemical reactivity are summarized. Moreover, mechanistic and empirical approaches to explain and predict the effect of food matrix on chemical reactivity are described. Mechanistic models aim to quantify the effect of food matrix based on a detailed understanding of the chemical and physical phenomena occurring in food. Their applicability is limited at the moment to very simple food systems. Empirical modeling based on machine learning combined with data-mining techniques may represent an alternative, useful option to predict the effect of the food matrix on chemical reactivity and to identify chemical and physical properties to be further tested. In such a way the mechanistic understanding of the effect of the food matrix on chemical reactions can be improved.     

Groundwater contaminant transport in presence of colloids II: sensitivity and uncertainty analysis on literature case studies

In a previous paper, the authors have presented a newly developed stochastic model of groundwater contaminant transport which is capable of accounting for the contribution of colloids flowing in the porous medium. The model is nonlinear and accounts explicitly for the exchange interactions among contaminants, colloids and the porous matrix, by means of properly introduced transition rates. The physical model is straightforward and intuitive, and it results in a system of differential equations whose dimensionality, in practical cases, is such to entail a Monte Carlo simulation to approach its solution. In this second part of the work, we explore in details the role played by those parameters which characterize the contaminant-colloid and the colloid-solid matrix interactions. A case study of Pu-239 transport inspired by a potential site for high level waste deposit at Mol (Belgium) is considered and the effects of colloid-facilitated transport is investigated under various conditions. Furthermore, an uncertainty analysis is performed to account for the uncertainties which in realistic situations affect the system and the transport phenomena. In this regard, a case study of Pu-239 transport inspired by the test site in Nevada has been considered.     

Proteomics and Extracellular Vesicles as Novel Biomarker Sources in Peritoneal Dialysis in Children

Peritoneal dialysis (PD) represents the dialysis modality of choice for pediatric patients with end-stage kidney disease. Indeed, compared with hemodialysis (HD), it offers many advantages, including more flexibility, reduction of the risk of hospital-acquired infections, preservation of residual kidney function, and a better quality of life. However, despite these positive aspects, PD may be associated with several long-term complications that may impair both patient’s general health and PD adequacy. In this view, chronic inflammation, caused by different factors, has a detrimental impact on the structure and function of the peritoneal membrane, leading to sclerosis and consequent PD failure both in adults and children. Although several studies investigated the complex pathogenic pathways underlying peritoneal membrane alterations, these processes remain still to explore. Understanding these mechanisms may provide novel approaches to improve the clinical outcome of pediatric PD patients through the identification of subjects at high risk of complications and the implementation of personalized interventions. In this review, we discuss the main experimental and clinical experiences exploring the potentiality of the proteomic analysis of peritoneal fluids and extracellular vesicles as a source of novel biomarkers in pediatric peritoneal dialysis.     

On‐Chip Magnetic Platform for Single‐Particle Manipulation with Integrated Electrical Feedback

Methods for the manipulation of single magnetic particles have become very interesting, in particular for in vitro biological studies. Most of these studies require an external microscope to provide the operator with feedback for controlling the particle motion, thus preventing the use of magnetic particles in high‐throughput experiments. In this paper, a simple and compact system with integrated electrical feedback is presented, implementing in the very same device both the manipulation and detection of the transit of single particles. The proposed platform is based on zig‐zag shaped magnetic nanostructures, where transverse magnetic domain walls are pinned at the corners and attract magnetic particles in suspension. By applying suitable external magnetic fields, the domain walls move to the nearest corner, thus causing the step by step displacement of the particles along the nanostructure. The very same structure is also employed for detecting the bead transit. Indeed, the presence of the magnetic particle in suspension over the domain wall affects the depinning field required for its displacement. This characteristic field can be monitored through anisotropic magnetoresistance measurements, thus implementing an integrated electrical feedback of the bead transit. In particular, the individual manipulation and detection of single 1‐μm sized beads is demonstrated.     

Polymer-derived silicon nitride aerogels as shape stabilizers for low and high-temperature thermal energy storage

This work presents a new skeleton material for thermal energy storage (TES), a silicon nitride aerogel obtained through the pyrolysis of a pre-ceramic polymer. Silicon nitride offers a good combination of thermal conductivity, high-temperature resistance, and chemical inertness. The aerogel porosity can be spontaneously infiltrated with molten NaNO₃, which is a typical phase change material (PCM) in high-temperature TES. The Si₃N₄/NaNO₃ composite exhibits excellent thermal properties with a thermal energy storage efficiency of 82 %, a limited molten salt leakage, and good stability to thermal cycling. The aerogel withstands oxidation up to high temperature and is chemically inert even in contact with salts. This novel aerogel shows also a notable paraffin absorption ability (used in room temperature TES) with negligible leakage even when in contact with absorbent paper. The so-obtained composite reached ≈ 82.4 vol % of organic PCM and a thermal energy storage efficiency of ≈ 62 % compared to neat paraffin.