Unusual etiology for a common problem

Introduction: Diagnosing the etiology of iron deficiency anemia can be very challenging.Hypothesis: Etiology of iron deficiency anemia is not always straightforwardStudy design: Case ReportResults: 2-year-old female presented with fever, cough, pallor for 4 days. CXR showed diffuse pulmonary opacities. CRP 3.45, ESR 21, WBC 6, platelet of 361, Hgb of 4 gm/dl, MCV 54, developed hemoptysis and was transferred to the PICU with respiratory failure. Bronchiolar lavage and lung biopsy showed extensive hemosiderin-laden macrophages. Iron deficiency anemia, progressive cough, dyspnea, and infiltrates on CXR was consistent with idiopathic pulmonary hemosiderosis. Pneumocystis, HIV, histoplasma, SLE, vasculitides were negative. Patient responded to a burst of steroid with normalization of breathing and Hgb level during follow up.16 y/o female marathon runner with iron deficiency anemia refractory to iron supplementation, Hgb 7.4gm/dl over 6 month period despite taking iron supplements. MVC was 68, ferritin of 2, transferrin/TIBC levels were elevated. Hemoccult stool negative. Combination of intense physical exercise, refractory iron deficiency anemia, and lack of GI blood loss led to consideration of march hemoglobinuria. Urinalysis positive for blood, confirming the diagnosis. With IV iron and reduction of intensity of running, Hgb was up to 14.1.Conclusion: These two cases of uncommon causes of blood loss highlight the importance of considering rare causes for iron deficiency anemia especially when it is not responding to iron supplement. Without treatment of underlying cause, anemia would persist

La 3D interactive en temps réel comme aide à l'acquisition des connaissances spatiales: étude de l'influence du mode d'exploration

Cette recherche s’inscrit dans le cadre général de la 3D interactive en temps réel comme outil de représentation, d’aide à la conception et à la communication des idées et hypothèses de design. Un facteur, l’interaction et plus précisément la navigation dans les Environnements Virtuels (EV) 3D non immersifs est l’objet de cette recherche. Par le biais d’une approche expérimentale, l’influence de la 3D interactive en temps réel sur l’acquisition des connaissances spatiales est illustrée par l'étude du mode d’exploration dans un espace virtuel complexe. En effet, les résultats de la recherche montrent une influence positive de la 3D interactive sur la formation d’une compréhension spatiale des environnements en mode d’exploration actif. Alors qu’en mode d’exploration passif, il s’est avéré que les esquisses comportaient plus d’erreurs dans la représentation des espaces.This research is part of the general framework of real time 3D interaction as a tool for representation, aided design and communication of design ideas. A factor, interaction and more precisely, navigation in a non immersive 3D Virtual Environment (VE), is the research subject. Using an experimental approach, the influence of real time 3D interaction on the acquisition of spatial knowledge is demonstrated, through observation of exploration modes in a complex virtual space. The research results stress a positive influence on spatial understanding through 3D interaction of visited environments during an active exploration. However, during passive exploration mode, the results revealed sketches with more spatial representations errors

Proposition d'une méthode mixte d'évaluation de l'incidence des médias sur le processus de conception architecturale

La thèse traite de l'incidence des media d'aide à la conception sur le processus de conception architecturale. Plus spécifiquement, en se basant sur une littérature multidisciplinaire, l’objectif de la thèse est d’analyser l’incidence de trois media, utilisés traditionnellement dans les milieux académique et professionnel, soit l’esquisse à main levée, la maquette et le logiciel de conception assistée par ordinateur (ici, Sketch-UP 7.0) sur le concepteur, le processus de conception architecturale et de la qualité des projets générés. 35 étudiants en architecture ont participé à cette étude. Une méthodologie d’évaluation mixte de cette incidence est proposée, soit d’une part des mesures quantitatives pour évaluer les capacités visuo-spatiales des étudiants-concepteurs (tests psychométriques), la gestion de leur charge cognitive (tâche secondaire) lors du processus de conception et d’autre part, des mesures qualitatives de la gestion de la charge cognitive (questionnaire du NASATLX) et de la qualité des projets générés (évaluation consensuelle d’experts). Les résultats n’ont pas permis de montrer de différence significative entre les media concernant les deux mesures de la charge cognitive, ainsi que pour la qualité des projets générés. De plus, aucune corrélation n’a été établie entre la charge cognitive et la qualité des projets.The thesis discusses the impact of design media upon architectural design. Based on a multidisciplinary literature revue, the objective of the thesis is to analyze the impact of three media, namely the freehand sketch, the physical model and the software (here, Sketch-UP 7.0) on architectural design. 35 students in architecture have participated in the study. A mixed evaluation methodology is proposed to evaluate the impact, namely quantitative measures of visual-spatial abilities (psychometric test), and the cognitive load management (secondary task technique) during the design, and also qualitative measures to evaluate the cognitive load management (NASATLX) and the quality of projects generated (consensual assessment technique). The results show no significant statistical difference between the three media for the cognitive load management, and the project quality. Furthermore, no correlation was found between the cognitive load management and the project quality

Skin Lesion Analysis Toward Melanoma Detection Using Deep Learning Techniques

In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnosis of melanoma. These deep learning networks work through making coarse segmentation, conventional filters and pooling layers. However, this segmentation of the skin lesions results in image of lower resolution than the original skin image. In this paper, we present deep learning based approaches to solve the problems in skin lesion analysis using a dermoscopic image containing skin tumor. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2018 Challenge. The proposed method achieves an accuracy of 96.67% for the validation set .The experimental tests carried out on a clinical dataset show that the classification performance using deep learning-based features performs better than the state-of-the-art technique

Skin Lesion Analysis Toward Melanoma Detection Using Deep Learning Techniques

In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnosis of melanoma. These deep learning networks work through making coarse segmentation, conventional filters and pooling layers. However, this segmentation of the skin lesions results in image of lower resolution than the original skin image. In this paper, we present deep learning based approaches to solve the problems in skin lesion analysis using a dermoscopic image containing skin tumor. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2018 Challenge. The proposed method achieves an accuracy of 96.67% for the validation set .The experimental tests carried out on a clinical dataset show that the classification performance using deep learning-based features performs better than the state-of-the-art technique

Design Optimization of Composite Deployable Bridge Systems Using Hybrid Meta-heuristic Methods for Rapid Post-disaster Mobility

Recent decades have witnessed an increase in the transportation infrastructure damage caused by natural disasters such as earthquakes, high winds, floods, as well as man-made disasters. Such damages result in a disruption to the transportation infrastructure network; hence, limit the post-disaster relief operations. This led to the exigency of developing and using effective deployable bridge systems for rapid post-disaster mobility while minimizing the weight to capacity ratio. Recent researches for assessments of mobile bridging requirements concluded that current deployable metallic bridge systems are prone to their service life, unable to meet the increase in vehicle design loads, and any trials for the structures’ strengthening will sacrifice the ease of mobility. Therefore, this research focuses on developing a lightweight deployable bridge system using composite laminates for lightweight bridging in the aftermath of natural disaster. The research investigates the structural design optimization for composite laminate deployable bridge systems, as well as the design, development and testing of composite sandwich core sections that act as the compression bearing element in a deployable bridge treadway structure. The thesis is organized into two parts. The first part includes a new improved particle swarm meta-heuristic approach capable of effectively optimizing deployable bridge systems. The developed approach is extended to modify the technique for discrete design of composite laminates and maximum strength design of composite sandwich core sections. The second part focuses on developing, experimentally testing and numerically investigating the performance of different sandwich core configurations that will be used as the compression bearing element in a deployable fibre-reinforced polymer (FRP) bridge girder. The first part investigated different optimization algorithms used for structural optimization. The uncertainty in the effectiveness of the available methods to handle complex structural models emphasized the need to develop an enhanced version of Particle Swarm Optimizer (PSO) without performing multiple operations using different techniques. The new technique implements a better emulation for the attraction and repulsion behavior of the swarm. The new algorithm is called Controlled Diversity Particle Swarm Optimizer (CD-PSO). The algorithm improved the performance of the classical PSO in terms of solution stability, quality, convergence rate and computational time. The CD-PSO is then hybridized with the Response Surface Methodology (RSM) to redirect the swarm search for probing feasible solutions in hyperspace using only the design parameters of strong influence on the objective function. This is triggered when the algorithm fails to obtain good solutions using CD-PSO. The performance of CD-PSO is tested on benchmark structures and compared to others in the literature. Consequently, both techniques, CD-, and hybrid CD-PSO are examined for the minimum weight design of large-scale deployable bridge structure. Furthermore, a discrete version of the algorithm is created to handle the discrete nature of the composite laminate sandwich core design. The second part focuses on achieving an effective composite deployable bridge system, this is realized through maximizing shear strength, compression strength, and stiffness designs of light-weight composite sandwich cores of the treadway bridge’s compression deck. Different composite sandwich cores are investigated and their progressive failure is numerically evaluated. The performance of the sandwich cores is experimentally tested in terms of flatwise compressive strength, edgewise compressive strength and shear strength capacities. Further, the cores’ compression strength and shear strength capacities are numerically simulated and the results are validated with the experimental work. Based on the numerical and experimental tests findings, the sandwich cores plate properties are quantified for future implementation in optimized scaled deployable bridge treadway

GPS/Galileo simulation for reduced dynamic LEO satellite orbit determination

Global Navigation Satellite Systems (GNSS) have an endless number of applications in industry, science, military, transportation and recreation & sports. Two systems are currently in operation namely GPS (the USA Global Positioning System) and GLONASS (the Russian GLObal NAvigation Satellite System), and a third is planned, the European satellite navigation system GALILEO. The potential performance improvements achievable through combining these systems could be significant and expectations are high. Computer software can be used to simulate the overall process of GNSS (signal transmission and reception) and produce realistic simulated GNSS measurements. Using such simulated measurements, current and future GNSS systems and possible new applications of GNSS can be investigated. Thus data simulation is the perfect research tool in GNSS fields. Oceanography, is one application of GNSS, which requires position determination with a high accuracy. LEO satellites are used to measure the precise height of the sea surface for studying the dynamics of the world's oceans. Achieving maximum benefit from the altimetric data collected by LEO satellites requires a radial orbit accuracy of 10 cm, or better. It is in determining this orbit where GNSS may be utilised. GPS already delivers high quality position information for LEO satellite orbits such as Topex/Poseidon (1992- present). However LEO satellite orbits determination can still benefit from using GPS combined with GALILEO as there will be more visible satellites and a higher quality of measurements. Investigation of LEO satellite orbit determination using GPS or GALILEO or both systems requires GPS and GALILEO measurements. Due to the lack of real GALILEO measurements, as the system is still in development, the simulation of GPS and GALILEO measurements is required. In order to generate realistic simulated GPS and GALILEO data, the errors, which predominate in GNSS measurements, must be accurately modelled. During this research, it has been shown that it is possible to generate realistic simulated GPS data through the more realistic simulation of the ionospheric, tropospheric and multipath delays. Models with a high spatial resolution have been implemented to simulate the real behaviour of the ionosphere and troposphere. The behaviour of the resulting simulated GPS data is shown to follow the behaviour of real GPS data with a strong agreement. It has also been possible to generate GALILEO simulated data through modifying the simulation software using the GALELEO Design technical specifications. The potential impact of using GPS and GALILEO on LEO satellite orbit determination could be investigated on Topex/Poseidon mission which real GPS data was available from the beginning of this study. The performance of GPS, GALILEO, combined GPS/GALILEO and combined GPS-modernised/GALELEO constellations have been investigated in relation to the reduced dynamic orbit determination of the LEO satellite Topex/Poseidon. It can be concluded that the GALILEO constellation will provide high quality real time LEO satellite orbits compared with GPS. GALELEO constellation will provide slightly better quality real time LEO satellite orbits over the combined GPS-present/GALELEO constellation. However the best quality real time LEO satellite orbits will result from the combined GPS-modernised/GALILEO constellation

Does obesity affect the plasma level of Plasminogen Activator Inhibitor-1? And does CO2 pneumoperitoneum affect it?

AbstractBackgroundThis prospective controlled study was designed to evaluate the effect of obesity on the plasma level of Plasminogen Activator Inhibitor-1 (PAI-1) and also to evaluate the effect of CO2 pneumoperitoneum on the plasma level of PAI-1 in patients underwent laparoscopic surgery.MethodsThe study included two groups; first group (non obese) included 30 patients with normal average BMI underwent laparoscopic cholecystectomy while the second group included 30 obese patients with BMI>30kg/m2 underwent laparoscopic band ligation or fundoplication surgery. Five ml of venous blood was collected from each patient in the non obese group once before induction of anesthesia while three venous blood samples (5ml) were collected from each patient in the obese group as follows: first sample was taken before induction of anesthesia to compare it with the non obese group, second sample was taken after 1h of CO2 insufflations (to know the effect of CO2 insufflations on PAI-1 level) and third sample was taken 1week after surgery (to know the remaining effect in the postoperative period).ResultsThe level of PAI-1 was significantly high (5.423±2.5ng/ml) in the obese patients compared to non obese patients (1.4±0.641ng/ml) (P value=0.001). The level of PAI-1 was significantly high after CO2 insufflations compared to baseline level (6.396±2.542ng/ml vs. 5.423±2.5ng/ml) in obese group (P value=0.001). And this level also showed significant increase up to 1week (6.01±2.492ng/ml vs. 5.423±2.5ng/ml) (P value=0.028) in the obese group.ConclusionThe PAI-1 level was higher in obese patients when compared to non obese patients. PAI-1 level was elevated after CO2 insufflations and this elevation did not reach base line level up to 1week after laparoscopic surgery