Is there life in Virtual Globes?

Virtual globes have been widely used during last decade mainly for simulating observations of the earth from the outer space and navigation experiences over its surface which may be portrayed with various types of views and textures. The present work aims to extend virtual globe capabilities by incorporating three dimensional events on them. Such events may include animation and motion effects on 3D models representing real world living or inanimate spatial objects, modeling of natural resources and phenomena representations and any type of geovisualized activities and demonstrations

miRNAs in kidney disease

A l'heure actuelle, les microARNs sont reconnus comme des régulateurs essentiels de l'expression des protéines. Des anomalies dans leur fonction sont associées au développement de nombreuses pathologies. Ainsi, de nombreuses études s'intéressent au potentiel des microARNs en tant que biomarqueurs ou cibles thérapeutiques dans une grande variété de pathologies. De plus, un certain nombre de recherches font le lien entre microARNs et pathologies rénales et soulignent l'intérêt des microARNs en tant que biomarqueurs pour améliorer le diagnostic et le pronostic des maladies rénales en utilisant des échantillons sanguins, sériques, de tissus et d'urine. Dans le cadre de cette thèse, nous avons étudié :1) L'association des microARNs urinaires avec l'évolution de la maladie rénale chronique (MRC) chez l'adulte. La prévalence de la MRC est actuellement estimée à 5-10% de la population et est en constante augmentation. La détection précoce et l'identification de patients ayant une MRC progressant rapidement vers l'insuffisance rénale sont la clé pour une meilleure prise en charge de ces patients. Actuellement les outils non-invasifs comme l'albuminurie ou l'estimation du débit de filtration glomérulaire manquent de précision. Dans notre travail, nous avons tenté d'identifier les modifications urinaires des microRNAs afin d'identifier de nouveaux biomarqueurs non-invasifs associés à la progression de la MRC. Nous avons analysé les modifications des microARNs urinaires par séquençage à haut débit dans des échantillons d'urine de 70 patients atteints de MRC et corrélé leurs profils d'expression à la progression de la maladie. Cela a amené à l'identification de 25 microARNs urinaires (pvalue ajustée <0.05) potentiellement associés à la progression de la MRC. Parmi ceux-là, quatre microARNs (hsa-miR-34c-5p, hsa-miR-410-3p, hsa-miR-301b-3p, and hsa-miR-145-5p) ont été sélectionnés pour être validés dans une cohorte indépendante de 52 patients atteints de MRC. L'augmentation de l'abondance urinaire de hsa-miR-145-5p a été confirmée comme étant associée à la progression de la MRC. Des analyses in vitro de l'effet de l'inhibition de hsa-miR-145-5p dans les cellules rénales ont mis en évidence que ce microARN semblait être impliqué dans le processus de nécrose. En conclusion, cette étude nous a permis d'identifier hsa-miR-145-5p comme marqueur potentiel de la progression de la MRC. 2) La présence de microARNs urinaires associés à la néphropathie obstructive, une maladie fréquemment rencontrée chez les enfants qui peut conduire, dans les cas graves, à l'insuffisance rénale précoce. Dans cette étude, nous avons utilisé la biologie des systèmes et avons combiné des données microARN et ARNm de néphropathie obstructive humaine et animale pour obtenir des informations sur les mécanismes possibles impliqués dans cette maladie. En particulier, nous avons étudié simultanément le miRNome urinaire de nourrissons présentant une obstruction de la jonction pyélo-urétérale et le miRNome et le transcriptome tissulaire rénal chez la souris dans le modèle animal d'obstruction urétérale unilatéral (OUU) partiel et néonatal. Plusieurs centaines de microARNs et d'ARNms étant modifiés, la combinaison des microARNs des deux espèces avec les ARNms cibles associés a permis de sélectionner les 5 microARNs et 35 ARNms les plus fortement associés à la néphropathie obstructive. Une validation in vitro et in vivo a mis en avant que let-7a-5p et miR-29-3p ainsi que deux nouvelles cibles potentielles, l'E3 ubiquitin-protein ligase (DTX4) et neuron navigator 1 (NAV1) étaient dérégulées au cours de cette pathologie. Cette étude est la première à corréler le modèle animal d'OUU partiel et néonatal avec l'obstruction pyélo-urétérale chez l'Homme dans une analyse intégrée de biologie des systèmes. Nos résultats ont révélé let-7a et miR-29b en tant que molécules potentiellement impliquées dans le développement de la fibrose dans la néphropathie obstructive via le contrôle de DTX4 chez l'homme et la souris, ce qui n'aurait pas été identifiable autrement.MicroRNAs are now recognized as key players in the regulation of proteins and any abnormality in their function is a cause for pathway instability, leading to pathological conditions. Numerous reports from a variety of pathologies provide new data about microRNAs function, their targets and their potential as biomarkers and possible ways to control microRNAs' expression for potential therapeutic purpose. A number of reports also connect microRNAs with pathological conditions in the kidney and point to the use of microRNAs as biomarkers for diagnosis and prognosis of kidney disease in blood, serum, tissue and urine samples. In this thesis, we researched:1) A possible role of the microRNAs in the progression of adult chronic kidney disease (CKD), a disease representing a global burden with the tendency to rise worldwide. Progression of CKD is still very hard to detect non-invasively with the currently used clinical tools (eGFR and albuminuria). In our work we studied alterations of the level of the microRNAs in human urine samples of patients with fast or slow progression of CKD, in order to identify new potential biomarkers for non-invasive progression of CKD. Using Next Generation Sequencing, we analyzed urinary microRNA modifications in urine samples of 70 patients with established CKD and correlated their expression profiles to disease progression. This lead to the identification of 25 urinary microRNAs significantly associated to CKD progression (adjusted pvalue<0.05). Among those, four microRNAs (hsa-miR-34c-5p, hsa-miR-410-3p, hsa-miR-301b-3p, and hsa-miR-145-5p) were selected for validation in an independent cohort of 52 patients with CKD. Increased urinary abundance of hsa-miR-145-5p was confirmed to be associated to progression of CKD. In vitro exploration of the effects of hsa-miR-145-5p inhibition in human kidney cells showed that the microRNA seemed to be involved in necrotic processes. In conclusion we have identified hsa-miR-145-5p as potential urinary microRNA marker of CKD progression. 2) The identification of microRNAs associated to obstructive nephropathy, a frequently encountered disease in children that can lead, in severe cases, to end stage renal disease (ESRD). In this study we used a comprehensive system biology analysis in which we combined micro- and mRNA data from human and animal obstructive nephropathy to obtain information on possible mechanisms involved in this disease. In particular, we have studied in parallel the urinary miRNome of infants with ureteropelvic junction (UPJ) obstruction and the kidney tissue miRNome and transcriptome of the corresponding neonatal partial unilateral ureteral obstruction (UUO) mouse model. Several hundreds of microRNAs and mRNAs displayed changed abundance during disease. Combination of microRNAs in both species and associated mRNAs let to the prioritization of 5 microRNAs and 35 mRNAs associated to disease. In vitro and in vivo validation identified consistent dysregulation of let-7a-5p and miR-29-3p and new potential targets, E3 ubiquitin-protein ligase (DTX4) and neuron navigator 1 (NAV1). Our study is the first to correlate a mouse model of neonatal partial UUO with human UPJ obstruction in a comprehensive systems biology analysis. Our data revealed let-7a and miR-29b as molecules potentially involved in the development of fibrosis in UPJ obstruction via the control of DTX4 in both man and mice that would not be identified otherwise

Measurement based method for online characterization of generator dynamic behaviour in systems with renewable generation

This paper introduces a hybrid-methodology for online identification and clustering of generator oscillatory behavior, based on measured responses. The dominant modes in generator measured responses are initially identified using a mode identification technique and then introduced, in the next step, as input into a clustering algorithm. Critical groups of generators that exhibit poorly or negatively damped oscillations are identified, in order to enable corrective control actions and stabilize the system. The uncertainties associated with operation of modern power systems, including Renewable Energy Sources (RES) are investigated, with emphasis on the impact of the dynamic behavior of power electronic interfaced RES

Measurement-based analysis of the dynamic performance of microgrids using system identification techniques

The dynamic performance of microgrids is of crucial importance, due to the increased complexity introduced by the combined effect of inverter interfaced and rotating distributed generation. This paper presents a methodology for the investigation of the dynamic behavior of microgrids based on measurements using Prony analysis and state-space black-box modeling techniques. Both methods are compared and evaluated using real operating conditions data obtained by a laboratory microgrid system. The recorded responses and the calculated system eigenvalues are used to analyze the system dynamics and interactions among the distributed generation units. The proposed methodology can be applied to any real-world microgrid configuration, taking advantage of the future smart grid technologies and features

Dynamic performance of a low voltage microgrid with droop controlled distributed generation

Microgrids are small-scale highly controlled networks designed to supply electrical energy. From the operational point of view, microgrids are active distribution networks, facilitating the integration of distributed generation units. Major technical issues in this concept include system stability and protection coordination which are significantly influenced by the high penetration of inverter-interfaced distributed energy sources. These units often adopt the frequency-active power and voltage-reactive power droop control strategy to participate in the load sharing of an islanded microgrid. The scope of the paper is to investigate the dynamic performance of a low voltage laboratory-scale microgrid system, using experimental results and introduce the concept of Prony analysis for understanding the connected components. Several small disturbance test cases are conducted and the investigations focus on the influence of the droop controlled distributed generation sources

Photovoltaic Power Plants as a Source of Electromagnetic Interference to Metallic Agricultural Pipelines

AbstractThe electromagnetic interference of power lines to nearby metallic pipelines has been a subject of research for many decades. Usually attention was given to gas or oil pipelines that shared the same rights-off-way with a power line for large distances. However, the recent advancement of renewable energy sources and specifically Photovoltaic (PV) power, due to generous incentives provided in many countries, has resulted in installations of large PV power stations even in agricultural areas. This brought up cases where such power stations in the MWp level, typically connected in medium voltage through buried cables, are located in the vicinity of metallic irrigation pipelines. Under certain conditions, these situations may result in induced voltages and currents on the pipeline that can pose threats to operating personnel. This work presents an analysis of the problems through a quasi-real case study adapted from a real case of a PV power station. The calculation methodology involves a hybrid method that is used in a way to reduced computational time. Results are presented both for normal operating conditions and faults in the power station and may be useful for both agriculture professionals and engineers

Methodology for evaluating equivalent models for the dynamic analysis of power systems

The increasing penetration of distributed renewable energy sources drastically alters the dynamic characteristics of distribution networks (DNs). Therefore, several equivalent models have been recently proposed, to analyze more accurately the complex behavior of modern DNs. However, relatively simple models are still commonly used in practice for dynamic power system studies. In addition, dynamic equivalent models for DNs are sensitive to different operating conditions and there is lack of systematic understanding of their performance. Scope of this paper is to propose a methodology for identifying the applicability range in terms of accuracy and generalization capability of several conventional and newly developed equivalent models for the dynamic analysis of modern DNs. A set of metrics is used for the modelling accuracy assessment and a sensitivity analysis framework is introduced to fully quantify the generalization capabilities of DN equivalent models. Based on the above, guidelines and recommendations for the development of robust equivalent models for DN analysis are proposed

A three-level distributed architecture for the real-time monitoring of modern power systems

To monitor network operation in real-time, power system operators have developed wide-area monitoring systems (WAMS). However, the centralized communication and information processing architecture of WAMS cannot be extended easily to distribution networks. In this aspect, a three-level distributed network monitoring architecture is proposed in this paper, concerning the dynamic analysis of transmission, primary and secondary distribution networks by exploiting measurements of ambient data and transient responses. In the proposed architecture, operators are responsible for the operation and analysis of their own grid but also can share an overview of the system performance to facilitate their operational coordination. Different online and offline applications are supported within the architecture, including small-signal, transient and frequency stability analysis as well as dynamic equivalencing and real-time inertia estimation. Measurement-based algorithms and models are proposed for each case. Finally, the performance of the developed algorithms has been tested by using a combined transmission and distribution power system model

Study on the effectiveness of commercial anti‐islanding algorithms in the prospect of mass penetration of PVs in low‐voltage distribution networks

In the coming years, distribution grids will be progressively flooded by renewable energy sources (RES) that will be interconnected with the main grid through power electronic converters. Photovoltaics (PVs) are one of the most promising renewable technologies even for densely built-up areas where space problems are inevitable. The high penetration prospect of PV facilities on low-voltage distribution networks raises questions regarding the necessity of advanced functions that will enable electronically coupled RES to support the operation of distribution grids and to enhance their reliability. In this context, the objective of this study is to investigate the effectiveness of various islanding prevention measures installed in commercial PV inverters, when multiple inverters are operating in parallel with a low-voltage distribution network (LVDN). Extensive experiments were performed under various PV penetration levels, linear/non-linear load and over/under voltage and over/under frequency conditions, as well as for various values of total harmonic distortion of the mains voltage. Further to the primary statistical analysis, the results were analysed in depth by advanced mathematical methods such as box plot and cluster analysis. The findings of this study indicate that commercial anti-islanding techniques present a high probability of failure in the case of multiple PV units at the same point of common coupling, calling for new and more advanced algorithms.European Commission, H2020, 65411