Human acclimation and acclimatization to heat: A compendium of research, 1968-1978

Abstracts and annotations of the majority of scientific works that elucidate the mechanisms of short-term acclimation to heat in men and women are presented. The compendium includes material from 1968 through 1977. Subject and author indexes are provided and additional references of preliminary research findings or work of a peripheral nature are included in a bibliography

Prestazioni fuori dal piano di tamponature in laterizio in zona sismica - Parte 2: analisi di dati sperimentali e confronto con i modelli di capacità

Recent Italian seismic events highlighted the high vulnerability frequently shown by non structural elements, especially masonry infill walls, whose severe damage caused heavy socio-economic effects, thus also representing a serious source of risk to life safety. NTC2008 Italian code prescribes a specific safety verification for infill walls whose implementation appears to be rather difficult since no capacity model is provided. In this paper the results of the prominent experimental studies performed on infill types usually adopted in the Italian built environment, and subjected to out-of-plane loads, have been analysed. Aimed at suggesting a capacity model to be used in the safety verifications, the experimental results have been compared with those obtained from some models available in literature (described in a companion paper, Masi et al., 2014) in order to verify their capability in the prediction of the out-of-plane capacity

Prestazioni fuori dal piano di tamponature in laterizio in zona sismica - Parte 1: modelli di capacità

Masonry infills are frequently used as enclosure walls in Reinforced Concrete framed buildings. In the common design practice they are generally modeled as non-structural elements, neglecting their influence on the building seismic response. The current Italian seismic code consider non-structural elements in the definition of the life safety limit state, but safety verifications, in particular with respect to the out-of-plane direction of infill walls, appear to be critical since no capacity models are specifically provided. With the objective of providing suggestions to improve the current Italian seismic code, after a description of the infill walls typically used in Italy, in the present paper the capacity models available in the technical literature are described and compared among them. Besides providing some preliminary suggestions for design practice, this paper prepares the ground to a next work where the capability of the available models in estimating the out-of-plane capacity will be verified by comparing them with experimental results

Sources of indoor air pollution and health effects in the Italian and European schools

Introduzione. Negli ultimi anni, i ricercatori hanno focalizzato la loro attenzione sulle fonti di inquinamento indoor nelle scuole e sul loro impatto sulla salute degli studenti e del personale scolastico. Anche progetti europei (SEARCH, GARD, SINPHONIE) e progetti italiani (INDOOR, CCM) indagano su questo argomento. Questa recensione raccoglie le ultime prove della letteratura su questi temi e mira a promuovere le buone pratiche. Metodi. PubMed e Scopus sono stati utilizzati per identificare articoli correlati a questo argomento. La metodologia della Dichiarazione PRISMA è stata adottata. Da 1102 articoli, abbiamo ottenuto una selezione di 38, in linea con i nostri criteri di inclusione ed esclusione. Inoltre, abbiamo utilizzato le informazioni fornite dai progetti di ricerca europei e italiani su IAQ per avere una panoramica realistica e dettagliata di questo problema. Risultati. Materiali da costruzione e rivestimento, tappeti, arredi, liquidi e prodotti per la pulizia, sistemi di fumo, aria condizionata, fotocopiatrici, pennarelli e altri materiali didattici sono stati riconosciuti, con prove sostanziali, come una varietà di inquinanti indoor nelle scuole, con un potenziale impatto negativo sulla salute . Anche parametri microclimatici scomodi possono contribuire a un cattivo QI. Un'esposizione cronica agli inquinanti può portare a gravi condizioni di salute come allergie (OR 1.80), asma (OR compreso tra 1,18 e 2,40), malattie cardiovascolari e cancro. Più frequentemente, nei bambini e negli adulti esposti, si riscontrano sintomi generici: irritazione oculare e delle vie respiratorie (intervallo OR da 1,06 a 2,86), tosse (intervallo OR da 1,06 a 3,79), starnuti, mal di testa, difficoltà di concentrazione. Conclusioni. Le prove di impatto negativo sulla salute hanno generato buone pratiche e misure: necessità di educazione e consapevolezza degli studenti e del personale scolastico, requisiti igienici standard e corretta pulizia degli ambienti, buone pratiche di ventilazione, adozione di prodotti e materiali sicuri e certificati, progettazione adeguata di nuovi edifici e ristrutturazione di quelli esistenti utilizzando requisiti strutturali specifici, monitoraggio costante di IAQ.Background. During the past few years, researchers have been focused their attention on the sources of indoor pollution in schools and their impact on the health of students and school staff. European projects (SEARCH, GARD, SINPHONIE) and Italian projects (INDOOR, CCM) also investigate this topic. This review collects the latest evidence of literature on these issues and aims to promote good practices. Methods. PubMed and Scopus were used to identify articles related to this topic. PRISMA Statement methodology was adopted. From 1102 articles, we obtained a selection of 38, in line with our inclusion and exclusion criteria. In addition, we used information provided by the European and Italian research projects on IAQ to have a realistic and detailed overview of this issue. Results. Building and coating materials, carpets, furnishings, liquid and cleaning products, smoking, air conditioning systems, photocopiers, markers and other teaching materials have been recognized, with substantial evidence, as a variety of indoor pollutants in schools, with a potential adverse health impact. Uncomfortable microclimatic parameters can also contribute to a poor IAQ. A chronic exposure to pollutants can lead to serious health conditions such as allergies (OR 1.80), asthma (OR range from 1.18 to 2.40), cardiovascular disease and cancer. Most frequently, in exposed children and adults, generic symptoms are found: eye and respiratory track irritation (OR range from 1.06 to 2.86), cough (OR range from 1.06 to 3.79), sneezing, headache, difficulty concentrating. Conclusions. Adverse health impact evidence has generated good practices and measures: need for students and school staff education and awareness, standard hygienic requirements and proper cleaning of environments, good ventilation practices, adoption of safe and certified products and materials, adequate design of new buildings and renovation of existing ones by using specific structural requirements, constant monitoring of IAQ

Measuring the agreement between brain connectivity networks

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing the estimated network with the corresponding ground-truth network; ii) in applications to real data, when it is necessary to compare the structure of a network obtained in a specific subject with a reference (e.g. a baseline condition or normative data). In the simulations, the level of similarity between two networks was manipulated through different factors. We then investigated the effect of such manipulations on the measures of association. Results showed how the three parameters modulated their values according to the level of similarity between the two networks. In particular, the AUC provided the better performances in terms of its capability to synthetize the similarity between two networks, showing high dynamic and sensitivity

Measuring the agreement between brain connectivity networks

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing the estimated network with the corresponding ground-truth network; ii) in applications to real data, when it is necessary to compare the structure of a network obtained in a specific subject with a reference (e.g. a baseline condition or normative data). In the simulations, the level of similarity between two networks was manipulated through different factors. We then investigated the effect of such manipulations on the measures of association. Results showed how the three parameters modulated their values according to the level of similarity between the two networks. In particular, the AUC provided the better performances in terms of its capability to synthetize the similarity between two networks, showing high dynamic and sensitivity