Anatomical and functional brain approach along short abrupt changes in G-levels

To conduct experiments under abrupt changes in g-levels, a single-engine aerobatic aircraft has been used, providing 6-8 seconds of reduced gravity, preceded and followed by 5-7 seconds of hypergravity periods. Due to the specific conditions of the flight and previous findings [1], the hypothesis of the present work lies on the idea that some sensory inputs could have a notorious effect on brain final responses when gravity is altered. Therefore, this study focuses on the evaluation of such hypothesis, based on the analysis of the evolution in time of intracranial activity of limbic, visual and auditory cortices. Five subjects (N=5, age 41¿14 years) have flown in parabolic flight with their eyes both open and closed. Electroencephalogram signals were recorded with an Emotive Epoc headset, synchronized with a triaxial accelerometer. The intracranial brain bioelectric activity (standardized current density) throughout the parabola, was calculated by applying Standard Low Resolution Brain Electromagnetic Tomography, and it was analyzed for the limbic, visual and auditory cortices. Intracranial activity of the Temporal, Parietal and Occipital lobes were carried out as well in order to compare the different periods/phases of the flight. Results detected a lower brain activity during the hypogravity phase in all lobes and cortices, only in the case of open eyes. The bioelectrical brain activity along the parabola showed similar patterns in all lobes and cortices, when visual inputs are highlighted. Suppressing the sight, two major behaviors were detected in brain activity: one for temporal lobe and auditory cortex, and second one for the rest of the lobes and visual cortex. It Seemed that, flying with closed eyes, other sensory stimuli were enhanced, in this case the auditory cortex. To confirm the validity of the results two-way ANOVA (factors lobe/phases) and Fisher post hoc test have been applied on mean intracranial activity values in all cases. Spectral entropy evolution in time has been considered as a fast indicator of the sudden extracranial brain activity variation during short g-changes. For open eyes, spectral entropy values indicated a slight decrease at the onset of the hypogravity phase, whereas in case of closed eyes, this change was detected in the last seconds of the parabola, even though these fluctuations were statistically non-significant. Results suggest that some of the sensory inputs can indeed have an impact on brain final response, when gravity conditions are altered.Peer ReviewedPostprint (published version

The colour and golden shine of early silver Islamic lustre

A selection of lustres including 9th century AD polychrome and 10th century AD monochrome Abbasid lustres from Iraq, and 10th to 12th centuries AD Fatimid lustres from Egypt and Syria is studied in the present paper. The selection is based on previous studies that demonstrated that all of them contain metal silver nanoparticles and copper, which, when present, appears either as Cuþ or Cu2þ dissolved in the glaze. They show different colours, green, yellow, amber, and brown, and may also show or lack a golden-like reflectivity, which results mainly from average size and concentration in the layer of the silver nanoparticles. In this paper, a depth profile composition of the lustre layers is determined using Rutheford Backscattering Spectroscopy, allowing the determination of the total silver content, concentration of silver, copper to silver ratio, and thickness of the lustre layers. We show that the enhanced golden-like reflectivity occurs only for layers with a high concentration of silver, and that the addition of PbO to the alkaline glaze helps the formation of more concentrated layers. The results obtained provide new hints concerning the lead enrichment of the glazes during this period.Peer ReviewedPostprint (published version

Rotation correlation maps

A correlation map shows the correlation between an image region and another image computed at the neighbourhood of each point of the second image. Most cross-correlation techniques fail when the viewpoint rotation grows over a certain value, usually around 20 degrees. The approach presented here aims at resolving this problem and at the same time provide an estimate of the actual rotation. This paper presents a method to obtain a correlation map robust to rotation together with an orientation map that gives an estimate of the rotation between the region and the image at each point. We call this a Rotation Correlation Map (RCM) and is built using texture and intensity information consecutively. The gradient histogram (texture distribution) of the region is used as a fast strategy to locate possible points of high correlation and an estimate of their orientation with respect to the region that is compared. Among the candidates with high histogram similarity, Normalised Cross Correlation (NCC) (using intensity) is computed using the orientation estimated in the previous step. Results show the accuracy in correlation and orientation and the overall higher performance when compared to similar map

Video-Based Camera Tracking Using Rotation-Discriminative Template Matching

This paper presents a video-based camera tracker that combines marker-based and feature point-based cues in a particle filter framework. The framework relies on their complementary performance. Marker-based trackers can robustly recover camera position and orientation when a reference (marker) is available, but fail once the reference becomes unavailable. On the other hand, feature point tracking can still provide estimates given a limited number of feature points. However, these tend to drift and usually fail to recover when the reference reappears. Therefore, we propose a combination where the estimate of the filter is updated from the individual measurements of each cue. More precisely, the marker-based cue is selected when the marker is available whereas the feature point-based cue is selected otherwise. Feature points are dynamically found in scene and used for further tracking. Evaluations on real cases show that the fusion of these two approaches outperforms the individual tracking results. A critical aspect of the feature point-based cue is to robustly recognise the feature points depite rotations of the camera. A novelty of the proposed framework is the use of a rotation-discriminative method to match feature points

Design and Implementation of a Universal Multimedia Access Environment

The objective of Universal Multimedia Access (UMA) is to permit any user equipped with whatever device the access to multimedia information. To handle the problems of UMA, two different approaches are commonly used: store variations of the same content and send the most appropriate one, and store the original content and adapt it on-the-fly. In this project a UMA environment using a mixture of both approaches is proposed. The tools allowing to reach this goal are: an Annotation Tool which describes media using MPEG-7, and a Client-Server Application that takes all the steps for the browsing and retrieval of media. After an overview of the designed UMA system, the function of the MPEG-7 annotation tool is explained. In particular, a descriptor list for content annotation is proposed. These descriptors are meant for content as well as for media feature description. The client-server application is then explained. Particular insight is given into the handling of user preferences and device capabilities. Finally, the UMA environment is tested on a Personal Computer simulating diverse devices and users. These tests show that the system behaves as expected and that possible extensions and improvements can be added

Particle filter-based camera tracker fusing marker- and feature point-based cues

This paper presents a video-based camera tracker that combines marker-based and feature point-based cues in a particle filter framework. The framework relies on their complementary performances. Marker-based trackers can robustly recover camera position and orientation when a reference (marker) is available, but fail once the reference becomes unavailable. On the other hand, filter-based camera trackers using feature point cues can still provide predicted estimates given the previous state. However, these tend to drift and usually fail to recover when the reference reappears. Therefore, we propose a fusion where the estimate of the filter is updated from the individual measurements of each cue. More precisely, the marker-based cue is selected when the reference is available whereas the feature point-based cue is selected otherwise. Evaluations on real cases show that the fusion of these two approaches outperforms the individual tracking results

Feature point tracking combining the Interacting Multiple Model filter and an efficient assignment algorithm

An algorithm for feature point tracking is proposed. The Interacting Multiple Model (IMM) filter is used to estimate the state of a feature point. The problem of data association, i.e. establishing which feature point to use in the state estimator, is solved by an assignment algorithm. A track management method is also developed. In particular a track continuation method is presented. The evaluation of the tracking system on real sequences shows that the IMM filter combined with the assignment algorithm outperforms the Kalman filter, used with the Nearest Neighbor (NN) filter, in terms of data association performance and robustness to sudden feature point maneuvers

Mapping tropical disturbed forests using multi-decadal 30 m optical satellite imagery

Tropical disturbed forests play an important role in global carbon sequestration due to their rapid post-disturbance biomass accumulation rates. However, the accurate estimation of the carbon sequestration capacity of disturbed forests is still challenging due to large uncertainties in their spatial distribution. Using Google Earth Engine (GEE), we developed a novel approach to map cumulative disturbed forest areas based on the 27-year time-series of Landsat surface reflectance imagery. This approach integrates single date features with temporal characteristics from six time-series trajectories (two Landsat shortwave infrared bands and four vegetation indices) using a random forest machine learning classification algorithm. We demonstrated the feasibility of this method to map disturbed forests in three different forest ecoregions (seasonal, moist and dry forest) in Mato Grosso, Brazil, and found that the overall mapping accuracy was high, ranging from 81.3% for moist forest to 86.1% for seasonal forest. According to our classification, dry forest ecoregion experienced the most severe disturbances with 41% of forests being disturbed by 2010, followed by seasonal forest and moist forest ecoregions. We further separated disturbed forests into degraded old-growth forests and post-deforestation regrowth forests based on an existing post-deforestation land use map (TerraClass) and found that the area of degraded old-growth forests was up to 62% larger than the extent of post-deforestation regrowth forests, with 18% of old-growth forests actually being degraded. Application of this new classification approach to other tropical areas will provide a better constraint on the spatial extent of disturbed forest areas in Tropics and ultimately towards a better understanding of their importance in the global carbon cycle

Technology of production of Syrian lustre (11th to 13th century)

Lustre is a decoration consisting of a surface layer of silver and copper metal nanoparticles, a few hundreds of nanometres thick and incorporated into the glaze. It shows a colourful metallic and iridescent appearance which makes use of the quantum confined optical response of the metallic nanoparticles. Three apparently unrelated lustre decorations, yellow-orange golden (Tell Minis), a dark brown-reddish with iridescences (Raqqa) and yellow-brown golden (Damascus) were produced in the same area in successive periods over tin and lead-free glazes which is known to require specific strategies to obtain a metallic shiny lustre. The composition and nanostructure of the lustre layers are analysed and the materials and specific firing conditions followed in their production determined. The optical properties of the lustre layers have been analysed in terms of the nanostructure obtained and correlated to the specific processing conditions.Peer ReviewedPostprint (author's final draft

Validation of a rapid, saliva-based, and ultra-sensitive SARS-CoV-2 screening system for pandemic-scale infection surveillance

Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large-scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput integrated screening platform, incorporating saliva-based loop-mediated isothermal amplification (LAMP) technology, that is designed for population-scale sensitive detection of infectious carriers of SARS-CoV-2 RNA. Central to this surveillance system is the “Sentinel” testing instrument, which is capable of reporting results within 25 min of saliva sample collection with a throughput of up to 3840 results per hour. It incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Independent validation of our saliva-based RT-LAMP technology on an automated LAMP instrument coined the “Sentinel”, found 98.7% sensitivity, 97.6% specificity, and 98% accuracy against a RT-PCR comparator assay, confirming its suitability for surveillance screening. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants, and control future pandemics to save lives