Image staining and differential diagnosis of ultrasound scans based on the Mahalanobis distance

The covariance matrices associated with each state of health or disease from a previous study are used as the basis of an image staining display technique for aid in quantitative differential diagnosis. A state of health or disease is chosen by the clinician: this selects the covariance matrix from the data base. A region of interest (ROI) is then scrolled through an abdominal B-scan. For each position of the ROI a point in the four-dimensional feature space is calculated. A natural measure of the distance of this point from the center of mass (multivariate mean) of the disease class is calculated in terms of the covariance matrix of this class; this measure is the Mahalanobis distance. The confidence level for acceptance or rejection of the hypothesized disease class is obtained from the probability distribution of this distance, the T(2) probability law. This confidence level is color coded and used as a color stain that overlays the original scan at that position. The variability of the calculated features is studied as a function of ROI size, or the spatial resolution of the color coded image, and it is found that for an ROI in the neighborhood of 4 cm(2) most of the variability due to the finite number of independent samples (speckles) is averaged out, leaving the "noise floor" associated with inter- and intra-patient variability. ROIs on the order of 1 cm(2) may result with technical advances in B-scan resolution. A small number of points on organ boundaries are entered by the user, to fit with arcs of ellipses to be used to switch between organ (liver and kidney) data bases as the ROI encounters the boundary. By selecting in turn various state-of-health or state-of-disease databases, such images of confidence levels may be used for quantitative differential diagnosis. The method is not limited to ultrasound, being applicable in principle to features obtained from any modality or multimodality combination.     

Aquaporins Are One of the Critical Factors in the Disruption of the Skin Barrier in Inflammatory Skin Diseases

The skin is the largest organ of the human body, serving as an effective mechanical barrier between the internal milieu and the external environment. The skin is widely considered the first-line defence of the body, with an essential function in rejecting pathogens and preventing mechanical, chemical, and physical damages. Keratinocytes are the predominant cells of the outer skin layer, the epidermis, which acts as a mechanical and water-permeability barrier. The epidermis is a permanently renewed tissue where undifferentiated keratinocytes located at the basal layer proliferate and migrate to the overlying layers. During this migration process, keratinocytes undertake a differentiation program known as keratinization process. Dysregulation of this differentiation process can result in a series of skin disorders. In this context, aquaporins (AQPs), a family of membrane channel proteins allowing the movement of water and small neutral solutes, are emerging as important players in skin physiology and skin diseases. Here, we review the role of AQPs in skin keratinization, hydration, keratinocytes proliferation, water retention, barrier repair, wound healing, and immune response activation. We also discuss the dysregulated involvement of AQPs in some common inflammatory dermatological diseases characterised by skin barrier disruption.     

Subtractive Clustering-Based K-means Technique for Determining Optimum Time-of-Day Breakpoints

In many countries, the most widely used method for timing plan selection and implementation is the time-of-day (TOD) method. In TOD mode, a few traffic patterns that exist in the historical volume data are recognized and used to find the signal timing plans needed to achieve optimum performance of the intersections during the day. Traffic engineers usually determine TOD breakpoints by analyzing 1 or 2?days worth of traffic data and relying on their engineering judgment. The current statistical methods, such as hierarchical and K-means clustering methods, determine TOD breakpoints but introduce a large number of transitions. This paper proposes adopting the Z-score of the traffic flow and time variable in the K-means clustering to reduce the number of transitions. The numbers of optimum breakpoints are chosen based on a microscopic simulation model considering a set of performance measures. By using simulation and the K-means algorithm, it was found that five clusters are the optimum for a major arterial in Al-Khobar, Saudi Arabia. As an alternative to the simulation-based approach, a subtractive algorithm-based K-means technique is introduced to determine the optimum number of TODs. Through simulation, it was found that both approaches results in almost the same values of measure of effectiveness (MOE). The proposed two approaches seem promising for similar studies in other regions, and both of them can be extended for different types of roads. The paper also suggests a procedure for considering the cyclic nature of the daily traffic in the clustering effort.     

Modeling the effect of immobilization of microorganisms on the rate of biodegradation of phenol under inhibitory conditions

The main objective of this research is to model the effect of biodegradation process of phenol at high initial concentrations using a well known immobilization technique of the biomass. This work focused on testing the effect of activated carbon and clay while considering the diffusive internal mass transfer limitations. Biodegradation of phenol was performed by using enriched microorganisms from a compost of agricultural wastes. The average phenol biodegradation rate (uptake) of free biomass system was 235.3 mg g⁻¹ h⁻¹ at initial concentration range of 212-260 mg/L. However, the values for the systems of immobilized biomass in alginate and activated carbon (1 mm), alginate, activated carbon (4 mm), alginate, activated carbon and clay (1 mm) and alginate, activated carbon and clay (4 mm) were 64.9, 27.6, 27.5, and 8 mg g⁻¹ h⁻¹ respectively. The effective diffusion factors in different matrix were obtained using an intra-particle diffusion-based mathematical model. Diffusion limitation was observed when the matrix contained clay in addition to activated carbon. The diffusion coefficient was decreased from 1.6 × 10⁻⁸ to 1.2 × 10⁻⁹ cm²/s when clay was added to the matrix of 1 mm of alginate and activated carbon. Also, slight differences between the diffusion factors were observed for larger beads. The combination of clay and AC contributes to better mineralization of phenol at high concentrations. This could be attributed to the synergism of both additives.     

Cooperative OFDM for semi distributed detection in wireless sensor networks

In this paper, parallel distributed detection in wireless sensor network (WSN) is investigated. Sensors are assumed to be transmitting their local decisions to a fusion center through a wireless fading channel using cooperative transmission. To enable cooperative transmission, sensors are divided into groups where sensors in each group help each other in transmitting their decisions in a way that the fusion center receives each local decision as an orthogonal frequency division multiplexed (OFDM) block. The fusion center detects all OFDM blocks sent by all groups to process them in order to obtain a final (global) decision. Using this cooperative transmission scheme enables the fusion center to apply diversity combining methods in order to reduce the fading effects of the channel. Optimal and sub-optimal fusion rules are derived for such system. Simulation results are provided to show the performance improvement that can be obtained compared to the conventional system where each local decision is transmitted to the fusion center individually and no diversity technique is applied at the fusion center.     

Repairing an aggregation-based smart metering system

International Journal of Information Security - Smart meters inform the electricity suppliers about the consumption of their clients in short intervals. Fine-grained electricity consumption...     

Optimum consultation for parallel distributed detection systems

Wireless Networks - An optimum consultation scheme for parallel distributed detection system is proposed. Two-way communication links are assumed between a set of local sensors and the fusion...     

Fluorescence Microscopy Analysis of Particulate Matter from Biomass Burning: Polyaromatic Hydrocarbons as Main Contributors

New efficient approaches to the characterization of fly ash and particulate matter (PM) have to be developed in order to better understand their impacts on environment and health. Polycyclic aromatic hydrocarbons (PAH) contained in PM from biomass burning have been identified as genotoxic and cytotoxic, and some tools already exist to quantify their contribution to PM. Optical fluorescence microscopy is proposed as a rapid and relatively economical method to allow the quantification of PAH in different particles emitted from biomass combustion. In this study samples were collected in the flue gas of biomass-combustion facilities with nominal output ranging from 40 kW to 17.3 MW. The fly ash samples were collected with various flue gas treatment devices (multicyclone, baghouse filter, electrostatic precipitator); PM samples were fractionated from the flue gas with a DEKATI® DGI impactor. A method using fluorescence observations (at 470 nm), white-light observations and image processing has been developed with the aim of quantifying fluorescence per sample. Organic components of PM and fly ash, such as PAH, humic-like substances (HULIS) and water-soluble organic carbon (WSOC) were also quantified. Fluorescence microscopy analysis method assessment was first realized with fly ash that was artificially coated with PAH and HULIS. Total amounts of PAH in the three size fractions of actual PM from biomass burning strongly correlated with the intensities of fluorescence. These encouraging results contribute to the development of a faster and cheaper method of quantifying particle-bound PAH.

Copyright 2015 American Association for Aerosol Research