Dynamic yacht strategy optimisation

Yacht races are won by good sailors racing fast boats. A good skipper takes decisions at key moments of the race based on the anticipated wind behaviour and on his position on the racing area and with respect to the competitors. His aim is generally to complete the race before all his opponents, or, when this is not possible, to perform better than some of them. In the past two decades some methods have been proposed to compute optimal strategies for a yacht race. Those strategies are aimed at minimizing the expected time needed to complete the race and are based on the assumption that the faster a yacht, the higher the number of races that it will win (and opponents that it will defeat). In a match race, however, only two yachts are competing. A skipper’s aim is therefore to complete the race before his opponent rather than completing the race in the shortest possible time. This means that being on average faster may not necessarily mean winning the majority of races. This thesis sets out to investigate the possibility of computing a sailing strategy for a match race that can defeat an opponent who is following a fixed strategy that minimises the expected time of completion of the race. The proposed method includes two novel aspects in the strategy computation: A short-term wind forecast, based on an Artificial Neural Network (ANN) model, is performed in real time during the race using the wind measurements collected on board. Depending on the relative position with respect to the opponent, decisions with different levels of risk aversion are computed. The risk attitude is modeled using Coherent Risk Measures. The proposed algorithm is implemented in a computer program and is tested by simulating match races between identical boats following progressively refined strategies. Results presented in this thesis show how the intuitive idea of taking more risk when losing and having a conservative attitude when winning is confirmed in the risk model used. The performance of ANN for short-term wind forecasting is tested both on wind speed and wind direction. It is shown that for time steps of the order of seconds and adequate computational power ANN perform better than linear models (persistence models, ARMA) and other nonlinear models (Support Vector Machines). The outcome of the simulated races confirms that maximising the probability of winning a match race does not necessarily correspond to minimising the expected time needed to complete the race

Validation study of WindTrax reverse dispersion model coupled with a sensitivity analysis of model-specific settings

In last years, atmospheric dispersion models have reached considerable popularity in environmental research field. In this regard, given the difficulties associated to the estimation of emission rate for some kind of sources, and due to the importance of this parameter for the reliability of the results, Backward dispersion models may represent promising tools. In particular, by knowing a measured downwind concentration in ambient air, they provide a numerical value for the emission rate. This paper discusses a critical validation of the WindTrax Backward model: the investigation does not only deal with the strict reliability of the model but also assesses under which conditions (i.e. stability class, number, and location of the sensors) the model shows the greatest accuracy. For this purpose, WindTrax results have been compared to observed values obtained from available experimental datasets. In addition, a sensitivity study regarding model-specific parameters required by WindTrax to replicate the physics and the random nature of atmospheric dispersion processes is discussed. This is a crucial point, since, for these settings, indications on the numerical values to be adopted are not available. From this study, it turns out that the investigated model specific settings do not lead to a significant output variation. Concerning the validation study, a general tendency of the model to predict the observed values with a good level of accuracy has been observed, especially under neutral atmospheric conditions. In addition, it seems that WindTrax underestimates the emission rate during unstable stratification and overestimates during stable con-ditions. Finally, by the definition of alternative scenarios, in which only a portion of the concentration sensors was considered, WindTrax performance appears better than acceptable even with a small number of concen-tration sensors, as long as the positioning is in the middle of the plume and not in the strict vicinity of the source

Circulating MicroRNA Profiling in Cancer Biomarker Discovery

MicroRNAs (miRNAs) are a class of small non-coding RNA molecules of approximately 22 nucleotides that regulate gene expression at the post-transcriptional level. Alterations in miRNA expression patterns correlate with a wide spectrum of pathological conditions, including cancer. miRNA profiling was mostly performed, in solid tissues, obtained by invasive diagnostic procedures. However, miRNAs in biofluids, such as serum and plasma, show high stability resulting from the formation of complexes with specific protein or incorporation within circulating exosomes or other microvesicles. Circulating miRNAs could be reliable biomarkers for early-stage cancer diagnosis, prognosis and response to therapy. In this chapter, we analyze the major pre-analytical and analytical challenges in experimental design for circulating miRNA detection, focusing on exosome fraction and microarray-based approach

Late Onset Cobalamin Disorder and Hemolytic Uremic Syndrome: A Rare Cause of Nephrotic Syndrome

Hemolytic uremic syndrome (HUS) is an unrare and severe thrombotic microangiopathy (TMA) caused by several pathogenetic mechanisms among which Shiga toxin-producing Escherichia coli infections and complement dysregulation are the most common. However, very rarely and particularly in neonates and infants, disorders of cobalamin metabolism (CblC) can present with or be complicated by TMA. Herein we describe a case of atypical HUS (aHUS) related to CblC disease which first presented in a previously healthy boy at age of 13.6 years. The clinical picture was initially dominated by nephrotic range proteinuria and severe hypertension followed by renal failure. The specific treatment with high dose of hydroxycobalamin rapidly obtained the remission of TMA and the complete recovery of renal function. We conclude that plasma homocysteine and methionine determinations together with urine organic acid analysis should be included in the diagnostic work-up of any patient with TMA and/or nephrotic syndrome regardless of age