Color vision impairment in type 2 diabetes assessed by the D-15d test and the Cambridge Colour Test

Color vision impairment emerges at early stages of diabetes mellitus type 2 (DM2) and may precede diabetic retinopathy or the appearance of vascular alterations in the retina. The aim of the present study was to compare the evaluation of the color vision with two different tests - the Lanthony desaturated D-15d test (a traditional color arrangement test), and the Cambridge Colour Test (CCT) (a computerized color discrimination test) - in patients diagnosed with DM2 without clinical signs of diabetic retinopathy (DR), and in sex- and age-matched control groups. Both color tests revealed statistically significant differences between the controls and the worst eyes of the DM2 patients. In addition, the degree of color vision impairment diagnosed by both tests correlated with the disease duration. The D-15d outcomes indicated solely tritan losses. In comparison, CCT outcomes revealed diffuse losses in color discrimination: 13.3% for best eyes and 29% for worst eyes. In addition, elevation of tritan thresholds in the DM2 patients, as detected by the Trivector subtest of the CCT, was found to correlate with the level of glycated hemoglobin. Outcomes of both tests confirm that subclinical losses of color vision are present in DM2 patients at an early stage of the disease, prior to signs of retinopathy. Considering the advantages of the CCT test compared to the D-15d test, further studies should attempt to verify and/or improve the efficiency of the CCT test.

A computer-controlled color vision test for children based on the Cambridge Colour Test

The present study aimed at providing conditions for the assessment of color discrimination in children using a modified version of the Cambridge Colour Test (CCT, Cambridge Research Systems Ltd., Rochester, UK). Since the task of indicating the gap of the Landolt C used in that test proved counterintuitive and/or difficult for young children to understand, we changed the target Stimulus to a patch of color approximately the size of the Landolt C gap (about 7 degrees Of Visual angle at 50 cm from the monitor). The modifications were performed for the CCT Trivector test which measures color discrimination for the protan, deutan and tritan confusion lines. Experiment I Sought to evaluate the correspondence between the CCT and the child-friendly adaptation with adult subjects (n = 29) with normal color vision. Results showed good agreement between the two test versions. Experiment 2 tested the child-friendly software with children 2 to 7 years old (n = 25) using operant training techniques for establishing and maintaining the subjects` performance. Color discrimination thresholds were progressively lower as age increased within the age range tested (2 to 30 years old), and the data-including those obtained for children-fell within the range of thresholds previously obtained for adults with the CCT. The protan and deutan thresholds were consistently lower than tritan thresholds, a pattern repeatedly observed in adults tested with the CCT. The results demonstrate that the test is fit for assessment of color discrimination in young children and may be a useful tool for the establishment of color vision thresholds during development.

Chromatic discrimination losses in multiple sclerosis patients with and without optic neuritis using the Cambridge Colour Test

We assessed chromatic discrimination in multiple sclerosis (MS) patients both with (ON) and without (no ON) a history of optic neuritis using the Cambridge color test (CCT). Our goal was to determine the magnitude and chromatic axes of any color vision losses in both patient groups, and to evaluate age-related changes in chromatic discrimination in both patient groups compared to normals. Using the CCT, we measured chromatic discrimination along the protan, deutan and tritan axes in 35 patients with MS (17 ON eyes) and 74 age matched controls. Color thresholds for both patient groups were significantly higher than controls` along the protan and tritan axes (P < 0.001). In addition, the ON and no-ON groups differed significantly along all three-color axes (p < 0.001). MS patients presented a progressive color discrimination impairment with age (along the deutan and tritan axes) that was almost two times faster than controls, even in the absence of ON. These findings suggest that demyelinating diseases reduce sensitivity to color vision in both red-green and blue-yellow axes, implying impairment in both parvocellular and koniocellular visual pathways. The CCT is a useful tool to help characterize vision losses in MS and the relationship between these losses and degree of optic nerve involvement.

Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health

The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Probing the anomalous extinction of four young star clusters: the use of colour-excess, main-sequence fitting and fractal analysis

Aims. We studied four young star clusters to characterise their anomalous extinction or variable reddening and asses whether they could be due to contamination by either dense clouds or circumstellar effects. Methods. We evaluated the extinction law (R-V) by adopting two methods: (i) the use of theoretical expressions based on the colour-excess of stars with known spectral type; and (ii) the analysis of two-colour diagrams, where the slope of the observed colour distribution was compared to the normal distribution. An algorithm to reproduce the zero-age main-sequence (ZAMS) reddened colours was developed to derive the average visual extinction (A(V)) that provides the closest fit to the observational data. The structure of the clouds was evaluated by means of a statistical fractal analysis, designed to compare their geometric structure with the spatial distribution of the cluster members. Results. The cluster NGC 6530 is the only object of our sample affected by anomalous extinction. On average, the other clusters suffer normal extinction, but several of their members, mainly in NGC 2264, seem to have high R-V, probably because of circumstellar effects. The ZAMS fitting provides A(V) values that are in good agreement with those found in the literature. The fractal analysis shows that NGC 6530 has a centrally concentrated distribution of stars that differs from the substructures found in the density distribution of the cloud projected in the A(V) map, suggesting that the original cloud was changed by the cluster formation. However, the fractal dimension and statistical parameters of Berkeley 86, NGC 2244, and NGC 2264 indicate that there is a good cloud-cluster correlation, when compared to other works based on an artificial distribution of points.

A comparison of CA125, HE4, risk ovarian malignancy algorithm (ROMA), and risk malignancy index (RMI) for the classification of ovarian masses

OBJECTIVE: Differentiation between benign and malignant ovarian neoplasms is essential for creating a system for patient referrals. Therefore, the contributions of the tumor markers CA125 and human epididymis protein 4 (HE4) as well as the risk ovarian malignancy algorithm (ROMA) and risk malignancy index (RMI) values were considered individually and in combination to evaluate their utility for establishing this type of patient referral system. METHODS: Patients who had been diagnosed with ovarian masses through imaging analyses (n = 128) were assessed for their expression of the tumor markers CA125 and HE4. The ROMA and RMI values were also determined. The sensitivity and specificity of each parameter were calculated using receiver operating characteristic curves according to the area under the curve (AUC) for each method. RESULTS: The sensitivities associated with the ability of CA125, HE4, ROMA, or RMI to distinguish between malignant versus benign ovarian masses were 70.4%, 79.6%, 74.1%, and 63%, respectively. Among carcinomas, the sensitivities of CA125, HE4, ROMA (pre-and post-menopausal), and RMI were 93.5%, 87.1%, 80%, 95.2%, and 87.1%, respectively. The most accurate numerical values were obtained with RMI, although the four parameters were shown to be statistically equivalent. CONCLUSION: There were no differences in accuracy between CA125, HE4, ROMA, and RMI for differentiating between types of ovarian masses. RMI had the lowest sensitivity but was the most numerically accurate method. HE4 demonstrated the best overall sensitivity for the evaluation of malignant ovarian tumors and the differential diagnosis of endometriosis. All of the parameters demonstrated increased sensitivity when tumors with low malignancy potential were considered low-risk, which may be used as an acceptable assessment method for referring patients to reference centers.

Influence of artificial accelerated ageing on the colour stability of paints used for ocular prosthesis iris painting

Objectives: To evaluate the colour stability of paints used for ocular prosthesis iris painting submitted for accelerated artificial ageing (AAA). Materials and methods: Forty specimens of acrylic resin for sclera (16 x 2 mm) were made and separated into eight groups (n = 10) according to the type of paint (gouache, GP; oil, OP; acrylic AP; and composite resin for characterisation, CR) and the colours used (blue/brown). After drying (72 h), a new layer of colourless acrylic resin was applied and the initial colour readout was performed (Spectrophotometer PCB 6807). New colour readouts were performed after AAA, and Delta E was calculated. Results: Statistical analysis (two-way ANOVA-Bonferroni, p < 0.05) demonstrated that the brown colour showed lower Delta E means in comparison with the blue colour, with statistically significant difference for AP only. Blue colour showed no statistically significant difference with regard to the type of paint used. Brown AP showed lower Delta E than the other groups, with significant difference for OP and GP. GP showed greater alteration in Delta E for the brown colour, being statistically similar only to OP. Conclusions: Only the AP group for brown pigment shows clinically acceptable values for colour stability after AAA.

Milky Way demographics with the VVV survey I. The 84-million star colour-magnitude diagram of the Galactic bulge

Context. The Milky Way (MW) bulge is a fundamental Galactic component for understanding the formation and evolution of galaxies, in particular our own. The ESO Public Survey VISTA Variables in the Via Lactea is a deep near-IR survey mapping the Galactic bulge and southern plane. Particularly for the bulge area, VVV is covering similar to 315 deg(2). Data taken during 2010 and 2011 covered the entire bulge area in the JHKs bands. Aims. We used VVV data for the whole bulge area as a single and homogeneous data set to build for the first time a single colour-magnitude diagram (CMD) for the entire Galactic bulge. Methods. Photometric data in the JHK(s) bands were combined to produce a single and huge data set containing 173 150 467 sources in the three bands, for the similar to 315 deg(2) covered by VVV in the bulge. Selecting only the data points flagged as stellar, the total number of sources is 84 095 284. Results. We built the largest colour-magnitude diagrams published up to date, containing 173.1+ million sources for all data points, and more than 84.0 million sources accounting for the stellar sources only. The CMD has a complex shape, mostly owing to the complexity of the stellar population and the effects of extinction and reddening towards the Galactic centre. The red clump (RC) giants are seen double in magnitude at b similar to -8 degrees-10 degrees, while in the inner part (b similar to -3 degrees) they appear to be spreading in colour, or even splitting into a secondary peak. Stellar population models show the predominance of main-sequence and giant stars. The analysis of the outermost bulge area reveals a well-defined sequence of late K and M dwarfs, seen at (J - K-s) similar to 0.7-0.9 mag and K-s greater than or similar to 14 mag. Conclusions. The interpretation of the CMD yields important information about the MW bulge, showing the fingerprint of its structure and content. We report a well-defined red dwarf sequence in the outermost bulge, which is important for the planetary transit searches of VVV. The double RC in magnitude seen in the outer bulge is the signature of the X-shaped MW bulge, while the spreading of the RC in colour, and even its splitting into a secondary peak, are caused by reddening effects. The region around the Galactic centre is harder to interpret because it is strongly affected by reddening and extinction.

Modeling and measuring the spatial relation "along": Regions, contours and fuzzy sets

The analysis of spatial relations among objects in an image is an important vision problem that involves both shape analysis and structural pattern recognition. In this paper, we propose a new approach to characterize the spatial relation along, an important feature of spatial configurations in space that has been overlooked in the literature up to now. We propose a mathematical definition of the degree to which an object A is along an object B, based on the region between A and B and a degree of elongatedness of this region. In order to better fit the perceptual meaning of the relation, distance information is included as well. In order to cover a more wide range of potential applications, both the crisp and fuzzy cases are considered. In the crisp case, the objects are represented in terms of 2D regions or ID contours, and the definition of the alongness between them is derived from a visibility notion and from the region between the objects. However, the computational complexity of this approach leads us to the proposition of a new model to calculate the between region using the convex hull of the contours. On the fuzzy side, the region-based approach is extended. Experimental results obtained using synthetic shapes and brain structures in medical imaging corroborate the proposed model and the derived measures of alongness, thus showing that they agree with the common sense. (C) 2011 Elsevier Ltd. All rights reserved.

Effects of low-salinity and high-turbidity waters one mpirical ocean colour algorithms: an example for Southwestern Atlantic waters

The spectral reflectance of the sea surface recorded using ocean colour satellite sensors has been used to estimate chlorophyll-a concentrations for decades. However, in bio-optically complex coastal waters, these estimates are compromised by the presence of several other coloured components besides chlorophyll, especially in regions affected by low-salinity waters. The present work aims to (a) describe the influence of the freshwater plume from the La Plata River on the variability of in situ remote sensing reflectance and (b) evaluate the performance of operational ocean colour chlorophyll algorithms applied to Southwestern Atlantic waters, which receive a remarkable seasonal contribution from La Plata River discharges. Data from three oceanographic cruises are used, in addition to a historical regional bio-optical dataset. Deviations found between measured and estimated concentrations of chlorophyll-a are examined in relation to surface water salinity and turbidity gradients to investigate the source of errors in satellite estimates of pigment concentrations. We observed significant seasonal variability in surface reflectance properties that are strongly driven by La Plata River plume dynamics and arise from the presence of high levels of inorganic suspended solids and coloured dissolved materials. As expected, existing operational algorithms overestimate the concentration of chlorophyll-a, especially in waters of low salinity (S<33.5) and high turbidity (Rrs(670)>0.0012 sr−1). Additionally, an updated version of the regional algorithm is presented, which clearly improves the chlorophyll estimation in those types of coastal environment. In general, the techniques presented here allow us to directly distinguish the bio-optical types of waters to be considered in algorithm studies by the ocean colour community.

Fuzzy linguistic model for bioelectrical impedance vector analysis

Backgrounds Ea aims: The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty. Methods: An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case. Results: The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001). Conclusions: fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Using the National Institute of Health Stroke Scale to Predict Dysphagia in Acute Ischemic Stroke

Background and Purpose: Oropharyngeal dysphagia is a common manifestation in acute stroke. Aspiration resulting from difficulties in swallowing is a symptom that should be considered due to the frequent occurrence of aspiration pneumonia that could influence the patient's recovery as it causes clinical complications and could even lead to the patient's death. The early clinical evaluation of swallowing disorders can help define approaches and avoid oral feeding, which may be detrimental to the patient. This study aimed to create an algorithm to identify patients at risk of developing dysphagia following acute ischemic stroke in order to be able to decide on the safest way of feeding and minimize the complications of stroke using the National Institutes of Health Stroke Scale (NHISS). Methods: Clinical assessment of swallowing was performed in 50 patients admitted to the emergency unit of the University Hospital, Faculty of Medicine of Ribeirao Preto, Sao Paulo, Brazil, with a diagnosis of ischemic stroke, within 48 h after the beginning of symptoms. Patients, 25 females and 25 males with a mean age of 64.90 years (range 26-91 years), were evaluated consecutively. An anamnesis was taken before the patient's participation in the study in order to exclude a prior history of deglutition difficulties. For the functional assessment of swallowing, three food consistencies were used, i.e. pasty, liquid and solid. After clinical evaluation, we concluded whether there was dysphagia. For statistical analysis we used the Fisher exact test, verifying the association between the variables. To assess whether the NIHSS score characterizes a risk factor for dysphagia, a receiver operational characteristics curve was constructed to obtain characteristics for sensitivity and specificity. Results: Dysphagia was present in 32% of the patients. The clinical evaluation is a reliable method of detection of swallowing difficulties. However, the predictors of risk for the swallowing function must be balanced, and the level of consciousness and the presence of preexisting comorbidities should be considered. Gender, age and cerebral hemisphere involved were not significantly associated with the presence of dysphagia. NIHSS, Glasgow Coma Scale, and speech and language changes had a statistically significant predictive value for the presence of dysphagia. Conclusions: The NIHSS is highly sensitive (88%) and specific (85%) in detecting dysphagia; a score of 12 may be considered as the cutoff value. The creation of an algorithm to detect dysphagia in acute ischemic stroke appears to be useful in selecting the optimal feeding route while awaiting a specialized evaluation. Copyright (C) 2012 S. Karger AG, Basel

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

Modeling and Identification of an Open-frame Underwater Vehicle: The Yaw Motion Dynamics

A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.