Innovative root-end filling materials based on calcium-silicates and calcium-phosphates

This in vitro study evaluated the apical sealing ability, bioactivity and biocompatibility of an experimental calcium silicate-based and two light-curing calcium silicate/calcium-phosphate cements as potential root end filling materials. A calcium silicate Portland-based (Control PC), an experimental calcium silicate (Exp. PC) and two light-curing cements (LC-CaP; LC-Si/CaP) were assessed for their alkalinising activity (pH) and biocompatibility. Single-rooted human canines were endodontically treated, filled with gutta-percha and finally submitted to apicoectomy. Root end fillings were performed using all tested cements, and their apical sealing ability was evaluated up to 4 weeks of immersion in simulated body fluid (SBF). The mineral precipitation at the apical region and the cement adaptation to root dentine were also evaluated through non-destructive optical microscopy both at 24?h and after prolonged water storage (four week). LC-CaP and LC-Si/CaP had neutral pH, the greatest sealing ability (24?h) and excellent cytocompatibility. The Exp. PC cement presented sealing ability after two and four weeks, as well as biocompatibility after four and seven days, similar to LC-CaP and LC-Si/CaP. The control PC cement showed the lowest sealing ability and the greatest cytotoxicity. Mineral precipitation was observed in all groups, while some differences were seen in terms of cement adaptation along the root canal dentine walls. The experimental light-curable cements as well as the experimental PC might be suitable root end filling materials with appropriate (in vitro) sealing ability, biocompatibility and aptitude to induce mineral precipitation.     

Time Reliability Measures in bus Transport Services from the Accurate use of Automatic Vehicle Location raw Data

Archived automatic vehicle location (AVL) data are widely used in bus transportation, but typically contain anomalies, such as missing data points and unseen bus overtakings. These anomalies may alter the measurement of time reliability (i.e., headways and schedule time deviations) of buses at stops with respect to passenger experiences. However, in many studies, anomalies are ignored, neglected, or partially addressed. This paper investigates the effect of AVL anomalies on headways and schedule deviations, which are keys for regularity and punctuality evaluations and are well‐practicized among bus operators worldwide. The analysis is carried out on six scenarios, each representing a combination of AVL data anomalies. The outcomes show that addressing anomalies result in more severe regularity measures, which point out criticalities suffered by passengers, whereas it can be skipped for the measurement of punctuality. In addition, an increase of 5% of missing data results in the increase of 5% in the coefficient of variation of the headway, but it does not lead to meaningful variations in punctuality measures. These results are useful for both practitioners interested in passenger‐oriented measurement of time reliability and researchers working on the disclosure of the determinants of unreliability. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessment of landslide-induced damage to structures: the Agnone landslide case study (southern Italy)

Landslides are among the most important and frequent natural calamities that cause severe socio-economic and human losses. After earthquakes, landslides are responsible for the greatest number of casualties and the largest amount of damage to man-made structures. On average, southern Italy is affected by a high spatial density of landslides due to its complex geological setting, which often predisposes it to slope instability phenomena under both natural and anthropogenic influences. Structurally complex formations are widespread in the southern Apennines and are characterized by high heterogeneity and very poor mechanical properties. Thus, these formations represent one of the main factors contributing to the predisposition of slopes to landsliding. In this paper, landslide-induced damage was investigated and analyzed in an area within the municipality of Agnone (Molise region), which is affected by a complex landslide that involves a structurally complex formation. The approaches used were based on six different methods that have previously been described in the literature, and a comparison of the results was made. Data regarding the damage, which consists largely of cracks observed in buildings and at the ground, were compiled through field surveys. The results were critically analyzed to note the advantages and constraints of each classification scheme. The aim of the work was to apply and compare different approaches in order to test the best and most accurate procedures for assessing damage due to landslides at the scale of individual buildings as well as to provide an objective assessment of the degree of landslide damage to structures and facilities.

     

Preference–Based Matchmaking of Grid Resources with CP–Nets

We deal with the problem of preference-based matchmaking of computational resources belonging to a Grid. We introduce CP–Nets, a recent development in the field of Artificial Intelligence, as a means to deal with user’s preferences in the context of Grid scheduling. We discuss CP–Nets from a theoretical perspective and then analyze, qualitatively and quantitatively, their impact on the matchmaking process, with the help of a Grid simulator we developed for this purpose. Many different experiments have been setup and carried out, and we report here our main findings and the lessons learnt.     

Smart Cities via Data Aggregation

Cities have an ever increasing wealth of sensing capabilities, recently including also internet of things (IoT) systems. However, to fully exploit such sensing capabilities with the aim of offering effective city-sensing-driven applications still presents certain obstacles. Indeed, at present, the main limitation in this respect consists of the vast majority of data sources being served on a “best effort” basis. To overcome this limitation, we propose a “resilient and adaptive IoT and social sensing platform”. Resilience guarantees the accurate, timely and dependable delivery of the complete/related data required by smart-city applications, while adaptability is introduced to ensure optimal handling of the changing requirements during application provision. The associated middleware consists of two main sets of functionalities: (a) formulation of sensing requests: selection and discovery of the appropriate data sources; and (b) establishment and control of the necessary resources (e.g., smart objects, networks, computing/storage points) on the delivery path from sensing devices to the requesting applications. The middleware has the intrinsic feature of producing sensing information at a certain level of detail (geographical scope/timeliness/accuracy/completeness/dependability) as requested by the applications in a given domain. The middleware is assessed and validated at a proof-of-concept level through innovative, dependable and real-time applications expected to be highly reproducible across different cities.     

Endophytic Microbiome Responses to Sulfur Availability in Beta vulgaris (L.)

Sulfur is an essential plant macronutrient, and its adequate supply allows an efficient root storage and sugar extractability in sugar beets (Beta vulgaris L.). In this study, we investigated the effect of changes in sulfur availability on the endophytic community structure of sugar beets. Plants were hydroponically grown in a complete nutrient solution (S-supplied), a nutrient solution without MgSO₄ (S-deprived), and a nutrient solution without MgSO₄ for six days and resupplied with 100 μM MgSO₄ for 48 h (S-resupplied). The sulfur status was monitored by inductively coupled plasma ICP–OES, and combustion analysis together with the evaluation of microRNA395 as a biomarker for sulfate status. Metabarcoding of the bacterial 16S rRNA gene was carried out in order to determine leaf endophytic community structure. The Shannon diversity index significantly differed (p < 0.05) between sulfate-supplied and sulfate-deprived seedlings. Validation by Real-Time PCR showed a significant increase (p < 0.05) of Burkholderia spp. in sulfate-deprived plants as compared to sulfate-supplied ones. The study sheds new light on the effects of nutrient deficiency on the microbiome of sugar beet plants.