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The prevalence of type 1 (T1D) and type 2 diabetes mellitus (T2D) has greatly increased worldwide over the last century. Although the exact pathophysiology of both these conditions is distinct and still largely unknown, T1D as well as T2D, have been linked to distinct perturbations of the gut microbiome. Faecal microbiota transplantation (FMT) is a potent, and if performed well, a safe method to modulate the composition of the gut microbiome and thus positively influences the course of these hyperglycaemic conditions in humans. In this review, we provide an overview of how FMT is commonly performed and summarise how this procedure may reduce the insulin-resistance driving T2D, and the underlying auto-immunity driving T1D. Insights derived from FMT studies in T1D and T2D may help identify beneficial microbiota and associated metabolites that may serve as future treatments for these conditions.

PURPOSE: To study the effectiveness of prophylactic embolization of hepaticoenteric arteries to prevent gastrointestinal complications during radioembolization. METHODS: A PubMed, Embase and Cochrane literature search was performed. We included studies assessing both a group of patients with and without embolization. RESULTS: Our search revealed 1401 articles of which title and abstract were screened. Finally, eight studies were included investigating 1237 patients. Of these patients, 456 received embolization of one or more arteries. No difference was seen in the incidence of gastrointestinal complications in patients with prophylactic embolization of the gastroduodenal artery (GDA), right gastric artery (RGA), cystic artery (CA) or hepatic falciform artery (HFA) compared to patients without embolization. Few complications were reported when microspheres were injected distal to the origin of these arteries or when reversed flow of the GDA was present. A high risk of confounding by indication was present because of the non-randomized nature of the included studies. CONCLUSION: It is advisable to restrict embolization to those hepaticoenteric arteries that originate distally or close to the injection site of microspheres. There is no conclusive evidence that embolization of hepaticoenteric arteries influences the risk of complications.

Background and aims Implicit learning mechanisms associated with detecting structural regularities have been proposed to underlie both the long-term acquisition of linguistic structure and a short-term tendency to repeat linguistic structure across sentences (structural priming) in typically developing children. Recent research has suggested that a deficit in such mechanisms may explain the inconsistent trajectory of language learning displayed by children with Developmental Learning Disorder. We used a structural priming paradigm to investigate whether a group of children with Developmental Learning Disorder showed impaired implicit learning of syntax (syntactic priming) following individual syntactic experiences, and the time course of any such effects. Methods Five- to six-year-old Italian-speaking children with Developmental Learning Disorder and typically developing age-matched and language-matched controls played a picture-description-matching game with an experimenter. The experimenter’s descriptions were systematically manipulated so that children were exposed to both active and passive structures, in a randomized order. We investigated whether children’s descriptions used the same abstract syntax (active or passive) as the experimenter had used on an immediately preceding turn (no-delay) or three turns earlier (delay). We further examined whether children’s syntactic production changed with increasing experience of passives within the experiment. Results Children with Developmental Learning Disorder’s syntactic production was influenced by the syntax of the experimenter’s descriptions in the same way as typically developing language-matched children, but showed a different pattern from typically developing age-matched children. Children with Developmental Learning Disorder were more likely to produce passive syntax immediately after hearing a passive sentence than an active sentence, but this tendency was smaller than in typically developing age-matched children. After two intervening sentences, children with Developmental Learning Disorder no longer showed a significant syntactic priming effect, whereas typically developing age-matched children did. None of the groups showed a significant effect of cumulative syntactic experience. Conclusions Children with Developmental Learning Disorder show a pattern of syntactic priming effects that is consistent with an impairment in implicit learning mechanisms that are associated with the detection and extraction of abstract structural regularities in linguistic input. Results suggest that this impairment involves reduced initial learning from each syntactic experience, rather than atypically rapid decay following intact initial learning. Implications Children with Developmental Learning Disorder may learn less from each linguistic experience than typically developing children, and so require more input to achieve the same learning outcome with respect to syntax. Structural priming is an effective technique for manipulating both input quality and quantity to determine precisely how Developmental Learning Disorder is related to language input, and to investigate how input tailored to take into account the cognitive profile of this population can be optimised in designing interventions.

Remote-sensing-based drought monitoring methods provide fast and useful information for a sustainable management strategy of drought impact over a region. Common pixel-based monitoring methods are limited in the analysis of the dynamics of this impact at regional scale. For instance, these hardly allow us to quantify the movement of drought in space and time and to compare drought with rainfall deficits without losing the variability of these events within a region. This study proposed an object-based approach that allowed us to visualize and quantify the spatio-temporal movement of drought impact on vegetation, called vegetative drought, in a region. The GIS software Dynomap was used to extract and track objects. Measures of distance and angle were used for determining the speed and direction of vegetative drought and rainfall deficit objects, calculated from the National Oceanic and Atmospheric Administration's (NOAA's) normalized difference vegetation index and rainfall estimates data. The methods were applied to the two rainy seasons during the drought year 1999 in East Africa. Results showed that vegetative drought objects moved into the southwestern direction at an average angle of −138.5° during the first season and −144.5° during the second season. The speed of objects varied between 38 km dekad−1 and 185 km dekad−1 during the first season and between 33 km dekad−1 and 144 km dekad−1 during the second season, reflecting the rate of spread between dekads. Vegetative drought objects close to rainfall deficit objects showed similar trajectories and sometimes regions overlapped. This indicated that the two events are related. We conclude that a spatiotemporal relationship existed between the two types of events and that this could be quantified.

This study aims at improving the characterisation and quantification of vegetative drought as a vague spatial phenomenon. 10-day NOAA-AVHRR NDVI images of East Africa from September 2005 to April 2006 are used. Vegetative drought is characterised using a membership function to model the gradual transition between drought and non-drought classes. Measures are implemented to quantify the areas and vagueness of vegetative drought, and to visualise its evolution in space and time. Results show a severe drought, affecting more than 60% of the vegetated area in the region. Different degrees of vagueness are observed in time, independently of the change of the transition range; the vagueness remains higher at the onset than at the termination of drought, reflecting a more gradual movement to drought and a crisper return to normal conditions. The vagueness was the lowest at the drought peak. The mean-area is less vulnerable to the change of the transition range, compared to the core-area. A Crisp approach, using the median of the transition range as the threshold value, does not quantify the vagueness of vegetative drought. This method can also be used in other regions, or adapted to characterise and quantify other vague spatial phenomena.

In this study we propose a validation method for the Meteosat SEVIRI derived NDVI values in regards to vegetation health from ground observations. The percentage of vegetation cover and the chlorophyll content are selected as vegetation health variables and their variability within and between SEVIRI pixels are assessed. No significant variability was found within pixels but between pixels for each of the variables. These variables are compared first separately with NDVI values, and later combined, with the NDVI values composited at different time steps. Results show that the combination of variables shows a similar trend than the mean NDVI or max NDVI calculated for the whole period of the study, as the presence of clouds influenced the daily NDVI values. We conclude that NDVI values can be used without compromising the variability of chlorophyll content and percentage of vegetation cover within those pixels. This funding can be used to understand the variation of NDVI which can be observed during a drought period. © 2010 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of 1st Conference on Spatial Statistics 2011 - Mapping global change.

We propose an image mining approach to monitor drought using Meteosat Spinning Enhanced Visible and InfraRed Imager (SEVIRI) image data. SEVIRI image data provide frequent Normalized Difference Vegetation Index (NDVI) time series which are important to assess the evolution of drought conditions. Vegetation condition is characterized in space by the deviation of the current NDVI observations at locations from their temporal mean values. In this paper we assume a gradual evolution of vegetation stress caused by drought and hence address this aspect with the use of a membership function applied to vegetation stress values to model drought. Our approach is implemented on subset image data of eastern Africa. Vegetated sites in a drought prone area of the region serve as an illustration using the drought spell at the end of 2005. This study shows that the use of a membership function allows capturing the gradual evolution of drought and can be used to model drought from observed vegetation conditions.

Automatic Facial Expression Recognition is a topic of high interest especially due to the growing diffusion of assistive computing applications, as Human Robot Interaction, where a robust awareness of the people emotion is a key point. This paper proposes a novel automatic pipeline for facial expression recognition based on the analysis of the gradients distribution, on a single image, in order to characterize the face deformation in different expressions. Firstly, an accurate investigation of optimal HOG parameters has been done. Successively, a wide experimental session has been performed demonstrating the higher detection rate with respect to other State-of-the-Art methods. Moreover, an on-line testing session has been added in order to prove the robustness of our approach in real environments.

Automatic facial expression recognition is one of the most interesting problem as it impacts on important applications in human-computer interaction area. Many applications in this field require real-time performance but not all the approach are suitable to satisfy this requirement. Geometrical features are usually the most light in terms of computational load but sometimes they exploits a huge number of features and do not cover all the possible geometrical aspect. In order to face up this problem, we propose an automatic pipeline for facial expression recognition that exploits a new set of 32 geometric facial features from a single face side covering a wide set of geometrical peculiarities. As a results, the proposed approach showed a facial expression recognition accuracy of 95,46% with a six-class expression set and an accuracy of 94,24% with a seven-class expression set.

In this work, ferroelectric (Bi0.5Na0.5)1 – xBaxTiO3 thin films were fabricated by chemical solution deposition (CSD) with compositions x = 0.050–0.150. Stoichiometric thin films (here-inafter BNBT) and others containing 10 mol% excesses of Bi3+ and Na+ (BNBTxs) were spin coated onto Pt/TiO2/ SiO2/(100)Si substrates and crystallized by rapid thermal processing at 650°C for 60 s in oxygen atmosphere. Crystalline structure is studied by X-ray diffraction using Cu anode (kCu = 1.5406 A) and synchrotron radiation (k = 0.97354 A). Rietveld refinement showed the coexistence of rhombohedral/ tetragonal phases in the BNBT films for x values close to those reported for (Bi0.5Na0.5)1 – xBaxTiO3 bulk ceramics. Different volume fractions of the rhombohedral/tetragonal phases are detected as a function of the Ba2+ content. An apparent shift of the position of the morphotropic phase boundary (MPB) is observed in the BNBTxs films. Here, the MPB region appears for nominal Ba2+ molar values of x ~ 0.10 and the experiments using a grazing-incidence synchrotron radiation indicate the existence of a crystalline phase with pyrochlore structure at the film surface. Rutherford backscattering experiments (RBS) revealed that the bismuth excess is not volatilized during the crystallization of the BNBTxs films which present inhomogeneous compositional depth profile and thick BixPt bottom interfaces. The MPB BNBT films with x ~ 0.055 have a homo geneous compositional depth profile without appreciable bottom interfaces. Scanning electron micrographs reveal less porosity and higher grain sizes in the stoichiometric films than in those with Bi3+ and Na+ excesses.

Increasing evidence supports the role of epigenetics in the development of autoimmune disorders and the possibility of using epigenetic modifying drugs in the context of MS has not yet been investigated. We have explored the effect of the hypomethylating agent 5-aza-2'-deoxycytidine (DAC) in two murine models of experimental allergic encephalomyelitis (EAE). DAC treatment was associated with a significant amelioration of the clinical and histological hallmarks of EAE in both models. These effects were observed both in prophylactic and therapeutic regimens. The milder course of the disease was associated with a reduction in the number of spinal cord infiltrating lymphocytes and amelioration of the histopathological signs associated with EAE. In addition, increased transcript levels of anti-inflammatory cytokines and decreased mRNA expression of pro-inflammatory mediators were also observed. Finally, DAC treatment increased the percentage of circulating regulatory T cells by inducing Foxp3 expression via demethylation of a CpG island in Foxp3.

A 3-day international workshop on atmospheric monitoring and calibration for high-energy astroparticle detectors, with a view towards next-generation facilities. The atmosphere is an integral component of many high-energy astroparticle detectors. Imaging atmospheric Cherenkov telescopes and cosmic-ray extensive air shower detectors are the two instruments driving the rapidly evolving fields of very-high- and ultra-high-energy astrophysics. In these instruments, the atmosphere is used as a giant calorimeter where cosmic rays and gamma rays deposit their energy and initiate EASs; it is also the medium through which the resulting Cherenkov light propagates. Uncertainties in real-time atmospheric conditions and in the fixed atmospheric models typically dominate all other systematic errors. With the improved sensitivity of upgraded IACTs such as H.E.S.S.-II and MAGIC-II and future facilities like the Cherenkov Telescope Array (CTA) and JEM-EUSO, statistical uncertainties are expected to be significantly reduced, leaving the atmosphere as the limiting factor in the determination of astroparticle spectra. Varying weather conditions necessitate the development of suitable atmospheric monitoring to be integrated in the overall instrument calibration, including Monte Carlo simulations. With expertise distributed across multiple collaborations and scientific domains, an interdisciplinary workshop is being convened to advance progress on this critical and timely topic.