964 resultados para Stendhal, Renate , 1944-
Resumo:
To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.
Resumo:
This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.
Resumo:
This paper presents a new architecture for the MASCEM, a multi-agent electricity market simulator. This is implemented in a Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) provides a DLL interface between Win-Prolog and other applications. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets.
Resumo:
A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.
Resumo:
Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.
Resumo:
Nanoparticles (NPs) are being used or explored for the development of biomedical applications in diagnosis and therapy, including imaging and drug delivery. Therefore, reliable tools are needed to study the behavior of NPs in biological environment, in particular the transport of NPs across biological barriers, including the blood-brain tumor barrier (BBTB), a challenging question. Previous studies have addressed the translocation of NPs of various compositions across cell layers, mostly using only one type of cells. Using a coculture model of the human BBTB, consisting in human cerebral endothelial cells preloaded with ultrasmall superparamagnetic iron oxide nanoparticles (USPIO NPs) and unloaded human glioblastoma cells grown on each side of newly developed ultrathin permeable silicon nitride supports as a model of the human BBTB, we demonstrate for the first time the transfer of USPIO NPs from human brain-derived endothelial cells to glioblastoma cells. The reduced thickness of the permeable mechanical support compares better than commercially available polymeric supports to the thickness of the basement membrane of the cerebral vascular system. These results are the first report supporting the possibility that USPIO NPs could be directly transferred from endothelial cells to glioblastoma cells across a BBTB. Thus, the use of such ultrathin porous supports provides a new in vitro approach to study the delivery of nanotherapeutics to brain cancers. Our results also suggest a novel possibility for nanoparticles to deliver therapeutics to the brain using endothelial to neural cells transfer.
Resumo:
Sertoli cells (SCs), the only somatic cells within seminiferous tubules, associate intimately with developing germ cells. They not only provide physical and nutritional support but also secrete factors essential to the complex developmental processes of germ cell proliferation and differentiation. The SC transcriptome must therefore adapt rapidly during the different stages of spermatogenesis. We report comprehensive genome-wide expression profiles of pure populations of SCs isolated at 5 distinct stages of the first wave of mouse spermatogenesis, using RNA sequencing technology. We were able to reconstruct about 13 901 high-confidence, nonredundant coding and noncoding transcripts, characterized by complex alternative splicing patterns with more than 45% comprising novel isoforms of known genes. Interestingly, roughly one-fifth (2939) of these genes exhibited a dynamic expression profile reflecting the evolving role of SCs during the progression of spermatogenesis, with stage-specific expression of genes involved in biological processes such as cell cycle regulation, metabolism and energy production, retinoic acid synthesis, and blood-testis barrier biogenesis. Finally, regulatory network analysis identified the transcription factors endothelial PAS domain-containing protein 1 (EPAS1/Hif2α), aryl hydrocarbon receptor nuclear translocator (ARNT/Hif1β), and signal transducer and activator of transcription 1 (STAT1) as potential master regulators driving the SC transcriptional program. Our results highlight the plastic transcriptional landscape of SCs during the progression of spermatogenesis and provide valuable resources to better understand SC function and spermatogenesis and its related disorders, such as male infertility.
Resumo:
1918/03/01 (A12,N36).
Resumo:
1918/01/01 (A12,N34).
Resumo:
Etat de collection : N° 29 (15 juil. 1917)-n° 36 (1e mars 1918)
Resumo:
1918/01/15 (A12,N35).
Resumo:
1917/07/15 (A11,N29)-1917/08/15 (A11,N30).
Resumo:
1917/12/15 (A11,N33).
Resumo:
1917/08/15 (A11,N31)-1917/09/15 (A11,N32).
