Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation,analysis and validation

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.     

Construction of a radial basis function network using an evolutionary algorithm for grade estimation in a placer gold deposit

This paper presents a study highlighting the predictive performance of a radial basis function (RBF) network in estimating the grade of an offshore placer gold deposit. In applying the radial basis function network to grade estimation of the deposit, several pertinent issues regarding RBF model construction are addressed in this study. One of the issues is the selection of the RBF network along with its center and width parameters. Selection was done by an evolutionary algorithm that utilizes the concept of cooperative coevolutions of the RBFs and the associated network. Furthermore, the problem of data division, which arose during the creation of the training, calibration and validation of data sets for the RBF model development, was resolved with the help of an integrated approach of data segmentation and genetic algorithms (GA). A simulation study conducted showed that nearly 27% of the time, a bad data division would result if random data divisions were adopted in this study. In addition, the efficacy of the RBF network was tested against a feed-forward network and geostatistical techniques. The outcome of this comparative study indicated that the RBF model performed decisively better than the feed-forward network and the ordinary kriging (OK).     

A stabilized volume‐averaging finite element method for flow in porous media and binary alloy solidification processes

A stabilized equal‐order velocity–pressure finite element algorithm is presented for the analysis of flow in porous media and in the solidification of binary alloys. The adopted governing macroscopic conservation equations of momentum, energy and species transport are derived from their microscopic counterparts using the volume‐averaging method. The analysis is performed in a single domain with a fixed numerical grid. The fluid flow scheme developed includes SUPG (streamline‐upwind/Petrov–Galerkin), PSPG (pressure stabilizing/Petrov–Galerkin) and DSPG (Darcy stabilizing/Petrov–Galerkin) stabilization terms in a variable porosity medium. For the energy and species equations a classical SUPG‐based finite element method is employed. The developed algorithms were tested extensively with bilinear elements and were shown to perform stably and with nearly quadratic convergence in high Rayleigh number flows in varying porosity media. Examples are shown in natural and double diffusive convection in porous media and in the directional solidification of a binary‐alloy. Copyright © 2004 John Wiley & Sons, Ltd.     

Neutrophil N1 and N2 Subsets and Their Possible Association with Periodontitis: A Scoping Review

Periodontitis is a chronic non-communicable disease caused by dysbiotic changes that affect the subgingival microbiota. During periodontitis, neutrophils play a central role in the initial recognition of bacteria, and their number increases with the appearance of the first signs of periodontal inflammation. Recent evidence has led to the proposition that neutrophils can also functionally polarize, determining selective activity patterns related to different diseases. Two well-defined neutrophil phenotypes have been described, the pro-inflammatory N1 subset and the suppressor N2 subset. To date, it has not been established whether these different neutrophil subtypes play a role in the pathogenesis of periodontitis. Thus, this scoping review aimed to determine whether there was evidence to suggest that the neutrophils present in periodontal tissues can be associated with certain phenotypes. The research question, population, concept, and context sought to identify original articles, in humans, that detected the presence of neutrophils in the periodontal tissues of people affected by periodontitis. Based on the search strategy, we found 3658 studies. After removing the papers with abstracts not related to the outcome measures and eligibility criteria, 16 articles were included for qualitative analysis. Several studies identified the presence of different neutrophil subsets, specifically, the naive, pro- and para-inflammatory, hyper-reactive and hyper-active, and high- and low-responder phenotypes. The existing evidence demonstrates the presence of pro-inflammatory, hyper-reactive and high-responder neutrophils in periodontal tissues affected with periodontitis. There is no evidence demonstrating the presence of the N1 or N2 phenotypes in periodontal tissues during periodontitis. However, the existence of pro-inflammatory phenotypes, which increase NETosis and degranulation, and increase the production of pro-inflammatory cytokines, could be suggestive of the N1 phenotypes.     

Multilevel segmentation of Hippocampus images using global steered quantum inspired firefly algorithm

Applied Intelligence - Microscopic Image segmentation has a crucial role in detecting and diagnosing numerous critical diseases like Alzheimer’s disease, Kidney disease, Cancer, many...     

Artificial neural networks and genetic algorithm for bearing fault detection

A study is presented to compare the performance of three types of artificial neural network (ANN), namely, multi layer perceptron (MLP), radial basis function (RBF) network and probabilistic neural network (PNN), for bearing fault detection. Features are extracted from time domain vibration signals, without and with preprocessing, of a rotating machine with normal and defective bearings. The extracted features are used as inputs to all three ANN classifiers: MLP, RBF and PNN for two- class (normal or fault) recognition. Genetic algorithms (GAs) have been used to select the characteristic parameters of the classifiers and the input features. For each trial, the ANNs are trained with a subset of the experimental data for known machine conditions. The ANNs are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a rotating machine. The roles of different vibration signals and preprocessing techniques are investigated. The results show the effectiveness of the features and the classifiers in detection of machine condition.     

Green fire retardant finishing and combined dyeing of proteinous wool fabric

Flame retardancy was imparted to a scoured and bleached, proteinous woollen textile by using banana pseudostem sap, an ecofriendly waste agricultural product, at different pH levels. The flame retardancy characteristics of both the control and the treated fabrics were analysed in terms of the limiting oxygen index and the vertical flammability measurement. Thermal degradation and fire retardancy mechanisms were studied using thermogravimetry, scanning electron microscopy, and energy dispersive X‐ray analysis. Moreover, the charring mechanism of both the control and the banana‐pseudostem‐sap‐treated fabrics with varying pH was analysed and reported in detail. The wool fabric was also dyed with CI Acid Blue 25 using banana pseudostem sap as well as water as the medium. The fabric dyed with the banana pseudostem sap medium at pH 5.5 showed more colour exhaustion, colour strength, and thermal stability compared with the control wool fabric. The mechanism by which superior fire retardancy and colour strength are imparted to the woollen textile by the application of banana pseudostem sap is proposed.     

Coalescence of bubbles and stability of foams in aqueous solutions of Tween surfactants

Coalescence of air bubbles and stability of foams in aqueous solutions of Tween 20, 40, 60 and 80 are reported in this work. Adsorption of the surfactants at air–water interface was studied by measuring the surface tension of the surfactant solutions. The surface tension profiles were fitted using a surface equation of state derived from the Gibbs and Langmuir adsorption equations. The critical micelle concentration and surface tension at this concentration were determined. The effect of surfactant concentration on coalescence of air bubbles at flat air–water interface was studied. The role of steric force on coalescence time was investigated. The coalescence time distributions were fitted by the stochastic model. The mean values of the distributions were compared with the predictions of seven film-drainage models. Stability of foams was analyzed by the Ross–Miles test. The initial and residual foam heights were measured at different surfactant concentrations. The stability of foams was compared with the coalescence time of the bubbles.