Calcifying odontogenic cyst associated with compound odontoma: A study on undemineralized material

In a minority of cases of calcifying odontogenic cyst (COC) it is possible to observe the formation of dental hard tissues in the cyst wall. The use of undemineralized sections has allowed an evaluation of the mineralized tissues normally lost with the use of demineralizing agents. All the dental hard tissues presented a high degree of morpho- and histodifferentiation. The histochemical staining for calcium salts (von Kossa) showed the presence of areas of low mineralization in the portion of the lesion, where the tissue maturation was not complete. In conclusion the appearance of the dental hard tissues in this case of compound odontoma arising in the cyst wall of a COC is similar to that already described in compound odontoma not associated with COC.Il est possible d’observer la formation de tissus dentaires durs dans la paroi d’une minorité de cas de kystes odontogènes calcifiants (KOC). L’utilisation de coupes de tissus non déminéralisés a permis une évaluation des tissus minéralisés qui sont habituellement perdus après décalcification. Tous les tissus dentaires durs présentent un degré important de morpho- en d’histodifférenciation. La coloration histochimique des sels calcaires (von Kossa) montre la présence de territoires de faible minéralisation dans les régions dans lesquelles la maturation tissulaire est incomplète.En conclusion, l’apparence des tissus dentaires durs dans ce cas d’odontome composé développé dans la paroi d’un kyste odontogène calcifié est semblable à celle déjà décrite dans les odontomes composés non associé à un KOC

Looking at flavonoid biodiversity in horticultural crops: A colored mine with nutritional benefits

Flavonoids represent a wide group of plant secondary metabolites implicated in many physiological roles, from the attraction of pollinators to the protection against biotic or abiotic stresses. Flavonoids are synthetized in a number of horticultural crops that are important components of our daily diet. In the last decades, the consumption of vegetables rich in antioxidants has been strongly promoted from the perspective of prevention/protection against chronic diseases. Therefore, due to their nutritional importance, several attempts have been made to enhance flavonoid levels in species of agronomic interest. In this review, we focus on the flavonoid biodiversity among the major horticultural species, which is responsible of differences among closely related species and influences the qualitative/quantitative composition. We also review the role of flavonoids in the nutritional quality of plant products, contributing to their organoleptic and nutritional properties, and the main strategies of biofortification to increase their content

EXPERIENCES OF UAV SURVEYS APPLIED TO ENVIRONMENTAL RISK MANAGEMENT

In this paper the results of some surveys carried out in an area of Apulian territory affected by serious environmental hazard are presented. Unmanned Aerial Vehicles (UAV) are emerging as a key engineering tool for future environmental survey tasks. UAVs are increasingly seen as an attractive low-cost alternative or supplement to aerial and terrestrial photogrammetry due to their low cost, flexibility, availability and readiness for duty. In addition, UAVs can be operated in hazardous or temporarily inaccessible locations, that makes them very suitable for the assessment and management of environmental risk conditions. In order to verify the reliability of these technologies an UAV survey and A LIDAR survey have been carried outalong about 1 km of coast in the Salento peninsula, near the towns of San Foca, Torre dellOrso and SantAndrea( Lecce, Southern Italy). This area is affected by serious environmental risks due to the presence of dangerous rocky cliffs named falesie. The UAV platform was equipped with a photogrammetric measurement system that allowed us to obtain a mobile mapping of the fractured fronts of dangerous rocky cliffs. UAV-images data have been processed using dedicated software (AgisoftPhotoscan). The point clouds obtained from both the UAV and LIDAR surveys have been processed using Cloud Compare software, with the aim of testing the UAV results with respect to the LIDAR ones. The total error obtained was of centimeter-order that is a very satisfactory result. The environmental information has been arranged in an ArcGIS platform in order to assess the risk levels. The possibility to repeat the survey at time intervals more or less close together depending on the measured levels of risk and to compare the output allows following the trend of the dangerous phenomena. In conclusion, for inaccessible locations of dangerous rocky bodies the UAV survey coupled with GIS methodology proved to be a key engineering tool for the management of environmental risks

A possible solution of the puzzling variation of the orbital period of MXB 1659-298

MXB 1659-298 is a transient neutron star Low-Mass X-ray binary system that shows eclipses with a periodicity of 7.1 hr. The source went to outburst in August 2015 after 14 years of quiescence. We investigate the orbital properties of this source with a baseline of 40 years obtained combining the eight eclipse arrival times present in literature with 51 eclipse arrival times collected during the last two outbursts. A quadratic ephemeris does not fit the delays associated with the eclipse arrival times and the addition of a sinusoidal term with a period of $2.31 \pm 0.02$ yr is required. We infer a binary orbital period of $P=7.1161099(3)$ hr and an orbital period derivative of $\dot{P}=-8.5(1.2) \times 10^{-12}$ s s$^{-1}$. We show that the large orbital period derivative can be explained with a highly non conservative mass transfer scenario in which more than 98\% of the mass provided by the companion star leaves the binary system. We predict an orbital period derivative value of $\dot{P}=-6(3) \times 10^{-12}$ s s$^{-1}$ and constrain the companion star mass between $\sim$0.3 and $0.9 \pm 0.3$ M$_{\odot}$. Assuming that the companion star is in thermal equilibrium the periodic modulation can be due to either a gravitational quadrupole coupling due to variations of the oblateness of the companion star or with the presence of a third body of mass M$_3 >21$ Jovian masses.Comment: 10 pages, 6 figures. Accepted by MNRA

On the Effect of Channel Knowledge in Underwater Acoustic Communications: Estimation, Prediction and Protocol

Underwater acoustic communications are limited by the following channel impairments: time variability, narrow bandwidth, multipath, frequency selective fading and the Doppler effect. Orthogonal Frequency Division Modulation (OFDM) is recognized as an effective solution to such impairments, especially when optimally designed according to the propagation conditions. On the other hand, OFDM implementation requires accurate channel knowledge atboth transmitter and receiver sides. Long propagation delay may lead to outdated channel information. In this work, we present an adaptive OFDM scheme where channel state information is predicted through a Kalman-like filter so as to optimize communication parameters, including the cyclic prefix length. This mechanism aims to mitigate the variability of channel delay spread. This is cast in a protocol where channel estimation/prediction are jointly considered, so as to allow efficiency. The performance obtained through extensive simulations using real channels and interference show the effectiveness of the proposed scheme, both in terms of rate and reliability, at the expense of an increasing complexity. However, this solution is significantly preferable to the conventional mechanism, where channel estimation is performed only at the receiver, with channel coefficients sent back to the transmit node by means of frequent overhead signaling

Blind fractionally spaced channel equalization for shallow water PPM digital communications links

Underwater acoustic digital communications suffer from inter-symbol interference deriving from signal distortions caused by the channel propagation. Facing such kind of impairment becomes particularly challenging when dealing with shallow water scenarios characterized by short channel coherence time and large delay spread caused by time-varying multipath effects. Channel equalization operated on the received signal represents a crucial issue in order to mitigate the effect of inter-symbol interference and improve the link reliability. In this direction, this contribution presents a preliminary performance analysis of acoustic digital links adopting pulse position modulation in severe multipath scenarios. First, we show how the spectral redundancy offered by pulse position modulated signals can be fruitfully exploited when using fractional sampling at the receiver side, which is an interesting approach rarely addressed by the current literature. In this context, a novel blind equalization scheme is devised. Specifically, the equalizer is blindly designed according to a suitably modified Bussgang scheme in which the zero-memory nonlinearity is replaced by a M-memory nonlinearity, M being the pulse position modulation order. Numerical results not only confirm the feasibility of the technique described here, but also assess the quality of its performance. An extension to a very interesting complex case is also provided

Econometric and Machine Learning Methods to Identify Pedestrian Crash Patterns

Walking plays an important role in overcoming many challenges nowadays, and governments and local authorities are encouraging healthy and environmentally sustainable lifestyles. Nevertheless, pedestrians are the most vulnerable road users and crashes with pedestrian involvement are a serious concern. Thus, the identification of pedestrian crash patterns is crucial to identify appropriate safety countermeasures. The aims of the study are (1) to identify the road infrastructure, environmental, vehicle, and driver-related patterns that are associated with an overrepresentation of pedestrian crashes, and (2) to identify safety countermeasures to mitigate the detected pedestrian crash patterns. The analysis carried out an econometric model, namely the mixed logit model, and the association rules and the classification tree algorithm, as machine learning tools, to analyse the patterns contributing to the overrepresentation of pedestrian crashes in Italy. The dataset consists of 874,847 crashes—including 101,032 pedestrian crashes—that occurred in Italy from 2014 to 2018. The methodological approach adopted in the study was effective in uncovering relations among road infrastructure, environmental, vehicle, and driver-related patterns, and the overrepresentation of pedestrian crashes. The mixed logit provided a clue on the impact of each pattern on the pedestrian crash occurrence, whereas the association rules and the classification tree detected the associations among the patterns with insights on how the co-occurrence of more factors could be detrimental to pedestrian safety. Drivers’ behaviour and psychophysical state turned out to be crucial patterns related to pedestrian crashes’ overrepresentation. Based on the identified crash patterns, safety countermeasures have been proposed