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

Ballistic accretion on a point seed

We carefully discuss the two-dimensional ballistic aggregation process. Studying the microscopic discrete process, we theoretically derive the probability density function describing the single-particle accretion. Using this function, we describe the properties of the “fan”, obtained for ballistic aggregation on the single seed, and we predict its mean density and its opening angle. We discuss the shadowing effect on a microscopic scale, between the single particles and, on a larger scale, between grown structures, deriving the columnar microstructure direction law. Comparisons with numerical experiments are shown

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)

Volumetric analysis of carotid plaque components and cerebral microbleeds: a correlative study

PURPOSE: The purpose of this work was to explore the association between carotid plaque volume (total and the subcomponents) and cerebral microbleeds (CMBs). MATERIALS AND METHODS: Seventy-two consecutive (male 53; median age 64) patients were retrospectively analyzed. Carotid arteries were studied by using a 16-detector-row computed tomography scanner whereas brain was explored with a 1.5 Tesla system. CMBs were studied using a T2*-weighted gradient-recalled echo sequence. CMBs were classified as from absent (grade 1) to severe (grade 4). Component types of the carotid plaque were defined according to the following Hounsfield unit (HU) ranges: lipid less than 60 HU; fibrous tissue from 60 to 130 HU; calcification greater than 130 HU, and plaque volumes of each component were calculated. Each carotid artery was analyzed by 2 observers. RESULTS: The prevalence of CMBs was 35.3%. A statistically significant difference was observed between symptomatic (40%) and asymptomatic (11%) patients (P value = .001; OR = 6.07). Linear regression analysis demonstrated an association between the number of CMBs and the symptoms (P = .0018). Receiver operating characteristics curve analysis found an association between the carotid plaque subcomponents and CMBs (Az = .608, .621, and .615 for calcified, lipid, and mixed components, respectively), and Mann-Whitney test confirmed this association in particular for the lipid components (P value = .0267). CONCLUSIONS: Results of this study confirm the association between CMBs and symptoms and that there is an increased number of CMBs in symptomatic patients. Moreover, we found that an increased volume of the fatty component is associated with the presence and number of CMBs

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