Is type 1 diabetes a chaotic phenomenon?

A database of ten type 1 diabetes patients wearing a continuous glucose monitoring device has enabled to record their blood glucose continuous variations every minute all day long during fourteen consecutive days. These recordings represent, for each patient, a time series consisting of 1 value of glycaemia per minute during 24 hours and 14 days, i.e., 20,160 data point. Thus, while using numerical methods, these time series have been anonymously analyzed. Nevertheless, because of the stochastic inputs induced by daily activities of any human being, it has not been possible to discriminate chaos from noise. So, we have decided to keep only the 14 nights of these ten patients. Then, the determination of the time delay and embedding dimension according to the delay coordinate embedding method has allowed us to estimate for each patient the correlation dimension and the maximal Lyapunov exponent. This has led us to show that type 1 diabetes could indeed be a chaotic phenomenon. Once this result has been confirmed by the determinism test, we have computed the Lyapunov time and found that the limit of predictability of this phenomenon is nearly equal to half the 90-minutes sleep-dream cycle. We hope that our results will prove to be useful to characterize and predict blood glucose variations

A Comparison of an Alternative Weight-Grading Model Against Chronological Age Group Model for the Grouping of Schoolboy Male Rugby Players

ObjectivesConcerns regarding marked differences in the weights and body composition of young rugby players competing within the same age groups have led to the suggestion of alternative models for grouping young players. The aims of this study were (1) to compare variance in the body size and body composition of schoolboy rugby players (9 to 14 years), across weight- and age-grading models, and (2) to identify morphotypes for the weight model using Hattori’s body composition chart.Materials and MethodsSkinfold thickness measurements were used to assess body fat mass (BF), fat-free mass (FFM), body fat mass index (BFMI), and fat-free mass index (FFMI). Standardized measure of height and weight were taken for all participants. Data were grouped according to the age categories of the French Rugby Federation (U11: Under 11 years, U13: Under 13 years, and U15: Under 15 years), and to the weight categories (W30–44.9; W45–59.9; and W60–79.9) carried out from 25th and 75th weight percentile in each age category. Body mass index status (NW normal-weight versus OW/OB overweight/obese) was considered. Extreme morphotypes are characterized from BFMI and FFMI in the weight-grading model on Hattori’s body composition chart.ResultsThe dispersion of anthropometric characteristics decreased significantly for the weight model, except for height in all groups and BFMI for U13. Among NW, 3, 1.8, and 0% upgraded; 18.2, 68.7, and 45.5% downgraded; among OW, 50, 21.5, and 12.5%; and among OB, 91.3, 83.3, and 74.6% upgraded, respectively, in U11, U13, U15. FFMI/BFMI were correlated in U11 (r = 0.80, p < 0.001), U13 (r = 0.66, p < 0.001), and U15 (r = 0.77, p < 0.001). There was no significant correlation in W45–59.9 and low correlations in W30–44.9 (r = 0.25, p < 0.001) and W60–79.9 (r = 0.29, p < 0.001). Significant grading difference between the centroids (p < 0.05) and the distribution deviates from centroids of BFMI and FFMI (p < 0.0001) were noted between the two models. Thirteen players were located in adipo-slender, twenty-three in adipo-solid, twenty-two in lean-slender, and two located in the lean-solid morphotype in weight model.ConclusionA weight-grading model should be considered to limit mismatches in anthropometric variables. However, variations of body composition also persisted for this model. Hattori’s body composition chart allowed more detailed examination of morphological atypicalities among schoolboy rugby players

Differential Effects of Bartonella henselae on Human and Feline Macro- and Micro-Vascular Endothelial Cells

Bartonella henselae, a zoonotic agent, induces tumors of endothelial cells (ECs), namely bacillary angiomatosis and peliosis in immunosuppressed humans but not in cats. In vitro studies on ECs represent to date the only way to explore the interactions between Bartonella henselae and vascular endothelium. However, no comparative study of the interactions between Bartonella henselae and human (incidental host) ECs vs feline (reservoir host) ECs has been carried out because of the absence of any available feline endothelial cell lines

Comparison of two semantic segmentation databases for smoke detection

International audienceResearchers have found strong correlation between warm summer and the frequency and intensity of fires around the world. Climate models due to global warming tells us that average summer temperature will increase drastically in the next few decades entailing an increase of wildfire. Computer vision is a good tools to detect and locate an incipient fire and prevent a rapid spread of fire destroying huge forest areas as in Australia or Brazil. Smoke is the first clue of an incipient fire that can be detected by a camera to warn firemen to act as quickly as possible. Convolutional neural networks and semantic segmentation can achieve this task by giving location and scale of the fire to firemen. In order to efficiently train this type of network architectures, we need a database composed of many images and corresponding masks. The complexity of the smoke in terms of shape, texture, color and intensity is difficult to segment properly. The diversity of smoke types in the image database is crucial for generalizing prediction in real-world circumstances. Numerous research papers proposed new network architectures for segmenting smoke in visible images spectrum and tested the accuracy of the segmentation on their database. Database that, for the most of the time, was not available. This article deals with comparison of a network performances on two smoke databases and highlight the importance of a rich images database in terms of quality rather than quantity

A Neural Adaptive Level Set Method for Wildland Forest Fire Tracking

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A camera self-calibration technique for mobile wheelchairs

International audienceThe Robotic systems for disabled people, aims at bringing a piloting assistance to powered wheelchairs in answer to the needs of mobility aid using dynamic vision techniques from mobile robotics. People start to design the robot with the fastest computers to process the information, together with high quality camera to serve as its eye, and precise mechanical motion control. The main working mode for this purpose is a contribution to dynamic vision, in the aim to improve a visio-space behavior of handicapped children. A self-calibration technique of a visual sensor is described: self-calibration implying the adoption of methods allowing to calibrate automatically a camera without using of special calibration set-ups. This paper examines what can be done within a Euclidean calibration, when the internal parameters must remain constant any more. So, we look at a Euclidean basis being a projective and one where some constraints must be observed. This work shows theoretically along with real experiments, how it is possible to completely calibrate a camera in line, that is to determine the intrinsic parameters and the relative displacement between two or three images, without any a priori knowledge of the scenes. The infinite homography computing method is used to estimate intrinsic and extrinsic parameters. This procedure consists of a closed-form solution, followed by a nonlinear refinement based on a bundle adjustment criterion

A Genetic Algorithm Application to Stereo Calibration

International audienceIn this paper, we propose a method, which adopts a global optimization algorithm based on a hybrid scheme. It consists of a genetic algorithm (GA) combined with a local search process. In the GA phase, an efficient fitness evaluation procedure based on a non-linear camera model is proposed. The local search step is a non-linear local approach using the Levenbergh-Marquardt algorithm. The experimental results show that the proposed method performs very well in terms of robustness to outliers and quality of camera parameters estimation