Automatic features detection in a fluvial environment through machine learning techniques based on uavs multispectral data

The present work aims to demonstrate how machine learning (ML) techniques can be used for automatic feature detection and extraction in fluvial environments. The use of photogrammetry and machine learning algorithms has improved the understanding of both environmental and an-thropic issues. The developed methodology was applied considering the acquisition of multiple photogrammetric images thanks to unmanned aerial vehicles (UAV) carrying multispectral cam-eras. These surveys were carried out in the Salbertrand area, along the Dora Riparia River, situated in Piedmont (Italy). The authors developed an algorithm able to identify and detect the water table contour concerning the landed areas: the automatic classification in ML found a valid identification of different patterns (water, gravel bars, vegetation, and ground classes) in specific hydraulic and geomatics conditions. Indeed, the RE+NIR data gave us a sharp rise in terms of accuracy by about 11% and 13.5% of F1-score average values in the testing point clouds compared to RGB data. The obtained results about the automatic classification led us to define a new procedure with precise validity conditions

Rock mass characterization by UAV and close-range photogrammetry: A multiscale approach applied along the vallone dell’elva road (Italy)

Geostructural rock mass surveys and the collection of data related to discontinues provide the basis for the characterization of rock masses and the study of their stability conditions. This paper describes a multiscale approach that was carried out using both non-contact techniques and traditional support techniques to survey certain geometrical features of discontinuities, such as their orientation, spacing, and useful persistence. This information is useful in identifying the possible kinematics and stability conditions. These techniques are extremely useful in the case study of the Elva valley road (Northern Italy), in which instability phenomena are spread across 9 km in an overhanging rocky mass. A multiscale approach was applied, obtaining digital surface models (DSMs) at three different scales: large-scale DSM of the entire road, a medium-scale DSM to assess portions of the slope, and a small-scale DSM to assess single discontinuities. The georeferenced point cloud and consequent DSMs of the slopes were obtained using an unmanned aerial vehicle (UAV) and terrestrial photogrammetric technique, allowing topographic and rapid traditional geostructural surveys. This technique allowed us to take measurements along the entire road, obtaining geometrical data for the discontinuities that are statistically representative of the rock mass and useful in defining the possible kinematic mechanisms and volumes of potentially detachable blocks. The main purpose of this study was to analyse how the geostructural features of a rock mass can affect the stability slope conditions at different scales in order to identify road sectors susceptible to different potential failure mechanisms using only kinematic analysis

Silver doping of silica-hafnia waveguides containing Tb3+/Yb3+ rare earths for downconversion in PV solar cells

The aim of this paper is to study the possibility to obtain an efficient downconverting waveguide which combines the quantum cutting properties of Tb3+/Yb3+ codoped materials with the optical sensitizing effects provided by silver doping. The preparation of 70SiO(2)-30HfO(2) glass and glass-ceramic waveguides by sol-gel route, followed by Ag doping by immersion in molten salt bath is reported. The films were subsequently annealed in air to induce the migration and/or aggregation of the metal ions. Results of compositional and optical characterization are given, providing evidence for the successful introduction of Ag in the films, while the photoluminescence emission is strongly dependent on the annealing conditions. These films could find potential applications as downshifting layers to increase the efficiency of PV solar cells. (C) 2016 Elsevier B.V. All rights reserved

Evaluation of Serum 1,5 Anhydroglucitol Levels as a Clinical Test to Differentiate Subtypes of Diabetes

OBJECTIVE: Assignment of the correct molecular diagnosis in diabetes is necessary for informed decisions regarding treatment and prognosis. Better clinical markers would facilitate discrimination and prioritization for genetic testing between diabetes subtypes. Serum 1,5 anhydroglucitol (1,5AG) levels were reported to differentiate maturity-onset diabetes of the young due to HNF1A mutations (HNF1A-MODY) from type 2 diabetes, but this requires further validation. We evaluated serum 1,5AG in a range of diabetes subtypes as an adjunct for defining diabetes etiology. RESEARCH DESIGN AND METHODS: 1,5AG was measured in U.K. subjects with: HNF1A-MODY (n = 23), MODY due to glucokinase mutations (GCK-MODY, n = 23), type 1 diabetes (n = 29), latent autoimmune diabetes in adults (LADA, n = 42), and type 2 diabetes (n = 206). Receiver operating characteristic curve analysis was performed to assess discriminative accuracy of 1,5AG for diabetes etiology. RESULTS: Mean (SD range) 1,5AG levels were: GCK-MODY 13.06 microg/ml (5.74-29.74), HNF1A-MODY 4.23 microg/ml (2.12-8.44), type 1 diabetes 3.09 microg/ml (1.45-6.57), LADA 3.46 microg/ml (1.42-8.45), and type 2 diabetes 5.43 (2.12-13.23). Levels in GCK-MODY were higher than in other groups (P < 10(-4) vs. each group). HNF1A-MODY subjects showed no difference in unadjusted 1,5AG levels from type 2 diabetes, type 1 diabetes, and LADA. Adjusting for A1C revealed a difference between HNF1A-MODY and type 2 diabetes (P = 0.001). The discriminative accuracy of unadjusted 1,5AG levels was 0.79 for GCK-MODY versus type 2 diabetes and 0.86 for GCK-MODY versus HNF1A-MODY but was only 0.60 for HNF1A-MODY versus type 2 diabetes. CONCLUSIONS: In our dataset, serum 1,5AG performed well in discriminating GCK-MODY from other diabetes subtypes, particularly HNF1A-MODY. Measurement of 1,5AG levels could inform decisions regarding MODY diagnostic testing

Stat3 controls tubolointerstitial communication during CKD

Functional Genomics of Systemic Disorder

ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems

ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3′UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster’s functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org

PPARγ contributes to PKM2 and HK2 expression in fatty liver

Rapidly proliferating cells promote glycolysis in aerobic conditions, to increase growth rate. Expression of specific glycolytic enzymes, namely pyruvate kinase M2 and hexokinase 2, concurs to this metabolic adaptation, as their kinetics and intracellular localization favour biosynthetic processes required for cell proliferation. Intracellular factors regulating their selective expression remain largely unknown. Here we show that the peroxisome proliferator-activated receptor gamma transcription factor and nuclear hormone receptor contributes to selective pyruvate kinase M2 and hexokinase 2 gene expression in PTEN-null fatty liver. Peroxisome proliferator-activated receptor gamma expression, liver steatosis, shift to aerobic glycolysis and tumorigenesis are under the control of the Akt2 kinase in PTEN-null mouse livers. Peroxisome proliferator-activated receptor gamma binds to hexokinase 2 and pyruvate kinase M promoters to activate transcription. In vivo rescue of peroxisome proliferator-activated receptor gamma activity causes liver steatosis, hypertrophy and hyperplasia. Our data suggest that therapies with the insulin-sensitizing agents and peroxisome proliferator-activated receptor gamma agonists, thiazolidinediones, may have opposite outcomes depending on the nutritional or genetic origins of liver steatosis

A High Statistics Measurement of the Lambdac+ Lifetime

A high statistics measurement of the Lambdac+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis technique with particular attention to the determination of the systematic uncertainty. The measured value of 204.6 +/- 3.4 (stat.) +/- 2.5 (syst.) fs from 8034 +/- 122 Lambdac -> pKpi decays represents a significant improvement over the present world average.Comment: Submitted to Physical Review Letter

A Measurement of the Ds+ Lifetime

A high statistics measurement of the Ds+ lifetime from the Fermilab fixed-target FOCUS photoproduction experiment is presented. We describe the analysis of the two decay modes, Ds+ -> phi(1020)pi+ and Ds+ -> \bar{K}*(892)0K+, used for the measurement. The measured lifetime is 507.4 +/- 5.5 (stat.) +/- 5.1 (syst.) fs using 8961 +/- 105 Ds+ -> phi(1020)pi+ and 4680 +/- 90 Ds+ -> \bar{K}*(892)0K+ decays. This is a significant improvement over the present world average.Comment: 5 pages, 3 figures, 2 tables, submitted to PR