Gonad development and reproduction in the monoecious species Chlorophthalmus agassizi (Actinopterygii: Aulopiformes: Chlorophthalmidae) from the Sardinian Waters (Central-Western Mediterranean)

Background. The shortnose greeneye, Chlorophthalmus agassizi Bonaparte, 1840, is a species with a circumglobal distribution and is among the most abundant commercial fishes in some Mediterranean areas. The knowledge of the biology and ecology of this species is poor and geographically limited, then the aim of this study is to provide a contribution to the knowledge on the reproductive biology of this monoecious deep-sea fish in Sardinian waters. Materials and Methods. In this paper the morphology and the development of the gonads, the mean size at maturity, the monthly evolution in the percent frequency of the maturity stages, and of the indices related to reproduction of the shortnose greeneye were examined. Individuals were caught by trawls, between 270 and 504 m of depth in the Sardinian seas. Results. The ovarian pattern is of an asynchronous type, characterized by releasing of eggs in successive batches. Seven stages of development for the ovary and four for the testis were identified on the basis of macroscopic and histological features. The female portion is the most evident component and shows a later maturation than the male portion. The spawning period is unique and takes place from May to September. Conclusion. The identification of spawning period and the adopted reproductive strategy is essential to obtain a better understanding of its biology and a good management of its fisheries

Towards the prediction of the quality of experience from facial expression and gaze direction

In this paper we investigate on the potentials to implicitly estimate the Quality of Experience (QoE) of a user of video streaming services by acquiring a video of her face and monitoring her facial expression and gaze direction. To this, we conducted a crowdsourcing test in which participants were asked to watch and rate the quality when watching 20 videos subject to different impairments, while their face was recorded with their PC's webcam. The following features were then considered: the Action Units (AU) that represent the facial expression, and the position of the eyes' pupil. These features were then used, together with the respective QoE values provided by the participants, to train three machine learning classifiers, namely, Support Vector Machine with quadratic kernel, RUSBoost trees and bagged trees. We considered two prediction models: only the AU features are considered or together with the position of the eyes' pupils. The RUSBoost trees achieved the best results in terms of accuracy, sensitivity and area under the curve scores. In particular, when all the features were considered, the achieved accuracy is of 44.7%, 59.4% and 75.3% when using the 5-level, 3level and 2-level quality scales, respectively. Whereas these results are not satisfactory yet, these represent a promising basis

Evolution of drop size distribution in natural rain

Both numerical modeling and laboratory experiments document the possibility of a raindrop size distribution (DSD) to evolve to an equilibrium stage (EDSD), where all the principal processes occur at steady rates. The aim of this work is to observe the temporal behavior of the DSD and to directly investigate the conditions favorable to the onset of the EDSD in natural rain. We exploited a large disdrometer dataset collected in the framework of the Ground Validation activities related to the NASA Global Precipitation Measurement mission. More than 200,000 one-minute data of two-dimensional video disdrometer (2DVD) are collected over USA to represent a wide range of precipitation types. The original data are averaged over 2 min and an automatic algorithm is used on a selected subset to identify samples with EDSD. Results show that the EDSD occurs mainly in convective events and lasts for very short time intervals (2 to 4 min). It is more frequent for rain rate between 20 and 40 mm h−1 and it mostly occurs during sharp increase of precipitation rates

A Catalytic One-Pot Synthesis of Indolyl Cyclobutanones

A general strategy for the synthesis of indolyl cyclobutanones via a tandem Bronsted acid catalyzed 2-hydroxycyclobutanone activation-indole nucleophilic addition has been exploited. The procedure leads to a wide range of 2- and 3-functionalized indole derivatives in good to high yields with broad substrate scope

Self-propagating reactions for environmental protection: Treatment of wastes containing asbestos

A thermochemical process based on the occurrence of self-propagating reactions that is able to convert asbestos fibers into harmless, nonfibrous species is proposed. Specifically, a mixture consisting of a waste (containing about 85 wt % of chrysotile), ferric oxide, and magnesium is able, once locally ignited by a thermal source, to generate a self-propagating reaction that travels through the mixture without requiring additional energy. The process is accompanied by a dramatic change in the material from both the chemical and microstructural points of view. In addition, front velocity and maximum combustion temperature decrease as the amount of waste in the starting mixture increases, with the self-propagating character being maintained if the waste content is equal to or below 60 wt %. It is also observed that, when nonasbestos (nontoxic) materials, i.e., sepiolite and glass fibers, are used instead of the hazardous waste, the front velocity, combustion temperature, propagation limits, and apparent activation energies are found to be very similar to those observed in the case of asbestos

An iot-based smart building solution for indoor environment management and occupants prediction

Smart buildings use Internet of Things (IoT) sensors for monitoring indoor environmental parameters, such as temperature, humidity, luminosity, and air quality. Due to the huge amount of data generated by these sensors, data analytics and machine learning techniques are needed to extract useful and interesting insights, which provide the input for the building optimization in terms of energy-saving, occupants’ health and comfort. In this paper, we propose an IoT-based smart building (SB) solution for indoor environment management, which aims to provide the following main functionalities: monitoring of the room environmental parameters; detection of the number of occupants in the room; a cloud platform where virtual entities collect the data acquired by the sensors and virtual super entities perform data analysis tasks using machine learning algorithms; a control dashboard for the management and control of the building. With our prototype, we collected data for 10 days, and we built two prediction models: a classification model that predicts the number of occupants based on the monitored environmental parameters (average accuracy of 99.5%), and a regression model that predicts the total volatile organic compound (TVOC) values based on the environmental parameters and the number of occupants (Pearson correlation coefficient of 0.939)

Non-linear analyses to assess the seismic performance of RC buildings retrofitted with FRP

Post-seismic reinforcement is extensively used to repair structural elements of buildings hit by strong earthquakes, while pre-seismic reinforcement can be very convenient to improve the seismic performance of buildings designed according to less stringent standards than current. One of the most commonly used techniques for both pre and post-seismic retrofit of structures is that of wrapping elements previously identified as weak or damaged with sheets of fiber-reinforced polymers (FRP). This technique may be in fact more advantageous than other strengthening approaches, due to speed of placement, low environmental impact and small load increase. Non-linear methods of analysis can be very helpful for planning the retrofit strategy and assessing in advance its effectiveness. Based on non-linear static and dynamic numerical analyses, the effectiveness of the FRP pre-seismic reinforcement on the global performance of buildings was investigated in this paper with reference to a residential Italian building designed according to obsolete standards. The seismic capacity of the building, before and after the FRP retrofit, was assessed and the efficacy of the seismic rehabilitation was evaluated. The results show that, by improving the local resistance of the most vulnerable elements and the global ductility of the building, the FRP wrapping of the ground-floor columns of the considered building has an important impact on the overall seismic response of the structure, although it cannot entirely avoid undesirable global collapse mechanisms