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

Administration of Brevibacillus laterosporus spores as a poultry feed additive to inhibit house fly development in feces: A new eco-sustainable concept

ABSTRACT The success of a microbial pesticide application against house flies developing in manure should accomplish the uniform mixing of active ingredients with this breeding medium, thus enhancing residual effects. The oral administration of the entomopathogenic bacterium Brevibacillus laterosporus to caged poultry species allows the homogeneous incorporation of its active ingredients with fly breeding media. Feces from treated broilers or hens show toxicity against exposed fly adults and larvae. Insecticidal effects are concentration-dependent with a lethal median concentration (LC50) value of 1.34 × 108 and 0.61 × 108 spores/g of feces for adults and larvae, respectively. Manure toxicity against flies was maintained as long as chickens were fed a diet containing adequate concentrations of B. laterosporus spores. Toxicity significantly decreased after spore administration to birds was interrupted. When poultry diet contained 1010 spores/g, mortality of flies reared on feces exceeded 80%. The use of B. lateroporus spores as a feed additive in poultry production systems fostering a more integrated approach to farming is discussed

Multilobular tumor of the zygomatic bone in a dog

Multilobular tumor of bone (MTB) (also known as Multilobular Osteochondrosarcoma) is an uncommon bone tumor frequently located on the skull of dogs, rarely on the ribs or pelvis. These neoplasms are slow growing, locally invasive, and have the potential to compress and invade the brain. A 10-year-old mixed breed dog was presented with a history of approximately 4 months of progressive growth of a left zygomatic mass. Radiographic investigation revealed a finely granular or stippled non homogeneous radiopaque mass involving the zygomatic arch. After surgery, grossly the neoplasm consisted of multiple, variably sized, grayish-white to yellow nodules separated by collagenous septa of different thickness. Histologically, the tumor was characterized by the presence of multiple lobules containing osteoid and cartilage, separated by a net of fibrous septae. This neoplastic pattern was consistent with a typical multilobular tumor of bone and based on clinical, radiographical, gross and light microscopic findings the definitive diagnosis was made. While reviewing veterinary literature only few cases of MTB were found in dogs

Strongly nonexponential time-resolved fluorescence of quantum-dot ensembles in three-dimensional photonic crystals

We observe experimentally that ensembles of quantum dots in three-dimensional (3D) photonic crystals reveal strongly nonexponential time-resolved emission. These complex emission decay curves are analyzed with a continuous distribution of decay rates. The log-normal distribution describes the decays well for all studied lattice parameters. The distribution width is identified with variations of the radiative emission rates of quantum dots with various positions and dipole orientations in the unit cell. We find a striking sixfold change of the width of the distribution by varying the lattice parameter. This interpretation qualitatively agrees with the calculations of the 3D projected local density of states. We therefore conclude that fluorescence decay of ensembles of quantum dots is highly nonexponential to an extent that is controlled by photonic crystals

Particle swarm optimization of GaAs-AlGaAS nanowire photonic crystals as two-dimensional diffraction gratings for light trapping

Semiconductor nanowire ordered arrays represent a class of bi-dimensional photonic crystals that can be engineered to obtain functional metamaterials. Here is proposed a novel approach, based on a particle swarm optimization algorithm, for using such a photonic crystal concept to design a semiconductor nanowire-based two-dimensional diffraction grating able to guarantee an in-plane coupling for light trapping. The method takes into account the experimental constraints associated to the bottom-up growth of nanowire arrays, by processing as input dataset all relevant geometrical and morphological features of the array, and returns as output the optimised set of parameters according to the desired electromagnetic functionality of the metamaterial. A case of study based on an array of tapered GaAs-AlGaAs core-shell nanowire heterostructures is discussed

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)

Sorting of multiple molecular species on cell membranes

Eukaryotic cells maintain their inner order by a hectic process of distillation of molecular factors taking place on the surface of their lipid membranes. To understand the properties of this molecular sorting process, a physical model of the process has been recently proposed [arXiv:1811.06760], based on (a) the phase separation of a single, initially dispersed molecular species into spatially localized sorting domains on the lipid membrane, and (b) domain-induced membrane bending leading to the nucleation of submicrometric lipid vesicles, naturally enriched in the molecules of the engulfed sorting domain. The analysis of the model has shown the existence of an optimal region of the parameter space where sorting is most efficient. Here, the model is extended to account for the simultaneous distillation of a pool of distinct molecular species. We find that the mean time spent by sorted molecules on the membrane increases with the heterogeneity of the pool (i.e., the number of distinct molecular species sorted) according to a simple scaling law, and that a large number of distinct molecular species can in principle be sorted in parallel on a typical cell membrane region without significantly interfering with each other. Moreover, sorting is found to be most efficient when the distinct molecular species have comparable homotypic affinities. We also consider how valence (i.e., the average number of interacting neighbors of a molecule in a sorting domain) affects the sorting process, finding that higher-valence molecules can be sorted with greater efficiency than lower-valence molecules

Emergence of quasiparticle Bloch states in artificial crystals crafted atom-by-atom

The interaction of electrons with a periodic potential of atoms in crystalline solids gives rise to band structure. The band structure of existing materials can be measured by photoemission spectroscopy and accurately understood in terms of the tight-binding model, however not many experimental approaches exist that allow to tailor artificial crystal lattices using a bottom-up approach. The ability to engineer and study atomically crafted designer materials by scanning tunnelling microscopy and spectroscopy (STM/STS) helps to understand the emergence of material properties. Here, we use atom manipulation of individual vacancies in a chlorine monolayer on Cu(100) to construct one- and two-dimensional structures of various densities and sizes. Local STS measurements reveal the emergence of quasiparticle bands, evidenced by standing Bloch waves, with tuneable dispersion. The experimental data are understood in terms of a tight-binding model combined with an additional broadening term that allows an estimation of the coupling to the underlying substrate.Comment: 7 figures, 12 pages, main text and supplementary materia

Differential Kinetics of Aspergillus nidulans and Aspergillus fumigatus Phagocytosis

Acknowledgements: The authors would like to acknowledge Fraser P. Coxon and Ian Ganley for providing LC3-GFP-mCherry BMDMs. M.S.G. was supported by an FEMS research grant and F.L.v.d.V. was supported by ZonMW under the name EURO-CMC frame of E-Rare-2, the ERA-Net for Research on Rare Diseases.Peer reviewedPublisher PD