Solutions and algorithms for inertial navigation of railroad vehicles

Obiettivo di questa tesi è lo studio e lo sviluppo di soluzioni innovative di navigazione inerziale per applicazioni ferroviarie, strumento utile per il tracciamento del moto durante l'assenza prolungata di sistemi di localizzazione esterni, tipo GPS, come può avvenire in galleria. Definiti gli strumenti di lavoro, è stata poi eseguita un'analisi dello stato dell'arte al fine di mettere in evidenza le metodologie teoriche utilizzate, nonchè le prestazioni dei sistemi già esistenti. Sono poi caratterizzati i sensori e le misure disponibili. Sono proposte varie soluzioni al problema della navigazione inerziale, con l'obiettivo di valutarne le prestazioni durante periodi prolungati assenza del GPS e con varie condizioni al contorno. Dopo una prima versione basata su un singolo EKF, si è scelto di svilupparne una seconda classe in cui il problema di stimadi assetto (AHRS) e diposizione/velocità sono separati e risolti mediante due algoritmi distinti. È stato implementato un AHRS basato su EKF e uno mediante un osservatore non lineare; inoltre, sono stati sviluppati un EKF di ordine completo e uno ridotto per le dinamiche di traslazione. È stata poi sviluppata una soluzione per l'integrazione dei dati delle mappe, in modo da fornire correzioni più frequenti all'INS, mantenendo inoltre un ridotto carico computazionale e facilità di integrazione. Si è infine proceduto implementando e simulando la soluzione a singolo stadio e le varie combinazioni di INS a due stadi in ambiente Matlab-Simulink. Gli algoritmi a due stadi hanno mostrato in simulazione prestazioni migliori rispetto alla struttura a EKF singolo la quale presenta un dominio di convergenza troppo limitato per fini pratici. A conclusione del lavoro, svolto avvalendosi della collaborazione di Sadel, sono state gettate le basi per una successiva analisi atta a verificare se la struttura a due stadi consente la convergenza anche dei bias di accelerometr

Revisiting a Receptor-Based Pharmacophore Hypothesis for Human A2AAdenosine Receptor Antagonists

The application of both structure- and ligand-based design approaches represents to date one of the most useful strategies in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)[1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol), we revisited a general pharmacophore hypothesis for the human A2A adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated by using an external test set of 29 newly synthesized human adenosine receptor antagonists

Revisiting a Receptor-Based Pharmacophore Hypothesis for Human A2A Adenosine Receptor Antagonists.

Adenosine is a neuromodulator whose biological functions are accomplished through the activation of specific proteins belonging to the G protein-coupled receptors (GPCRs) superfamily. To date, four distinct Adenosine Receptors (ARs) subtypes, termed A1, A2A, A2B and A3, have been identified.1 Owing to the wide range of effects exerted in numerous organ systems, the activation or blockade of ARs finds potential therapeutic applications in the treatment of several pathologies, such as cardiac and cerebral ischemia, asthma, Parkinson\u2019s disease, cancer, and kidney diseases.2 In view of their potential application for pharmaceutical purposes, several groups have focused their attention on the synthesis of both ARs agonists and antagonists, especially aimed by the pharmacological and biophysical characterization of the receptors.3 The application of both structure- and ligand-based design approaches represents to date one of the most challenging strategy in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)[1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol) we revisited a general pharmacophore hypothesis for the human A2A adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated using an external test set of 29 new synthesized human adenosine receptors antagonists. References (1) Fredholm, BB, et al. Pharmacol. Rev. 2001, 53, 527\u2013552. (2) Fredholm, BB. Exp. Cell Res. 2010, 316, 1284-1288. (3) Muller, C, et al. Biochim. Biophys. Acta 2010, 1808, 1290-1308

Revisiting a receptor-based pharmacophore hypothesis for human A(2A) adenosine receptor antagonists

The application of both structure- and ligand-based design approaches represents to date one of the most useful strategies in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)[1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol), we revisited a general pharmacophore hypothesis for the human A(2A) adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated by using an external test set of 29 newly synthesized human adenosine receptor antagonists

Combining selectivity and affinity predictions using an integrated Support Vector Machine (SVM) approach: An alternative tool to discriminate between the human adenosine A(2A) and A(3) receptor pyrazolo-triazolo-pyrimidine antagonists binding sites.

G Protein-coupled receptors (GPCRs) selectivity is an important aspect of drug discovery process, and distinguishing between related receptor subtypes is often the key to therapeutic success. Nowadays, very few valuable computational tools are available for the prediction of receptor subtypes selectivity. In the present study, we present an alternative application of the Support Vector Machine (SVM) and Support Vector Regression (SVR) methodologies to simultaneously describe both A(2A)R versus A(3)R subtypes selectivity profile and the corresponding receptor binding affinities. We have implemented an integrated application of SVM-SVR approach, based on the use of our recently reported autocorrelated molecular descriptors encoding for the Molecular Electrostatic Potential (autoMEP), to simultaneously discriminate A(2A)R versus A(3)R antagonists and to predict their binding affinity to the corresponding receptor subtype of a large dataset of known pyrazolo-triazolo-pyrimidine analogs. To validate our approach, we have synthetized 51 new pyrazolo-triazolo-pyrimidine derivatives anticipating both A(2A)R/A(3)R subtypes selectivity and receptor binding affinity profiles

Combining selectivity and affinity predictions using an integrated Support Vector Machine (SVM) approach: An alternative tool to discriminate between the human adenosine A2A and A3 receptor pyrazolo-triazolo-pyrimidine antagonists binding sites

10.1016/j.bmc.2009.05.038Bioorganic and Medicinal Chemistry17145259-5274BMEC

Revisiting a Receptor-Based Pharmacophore Hypothesis for Human A_2A Adenosine Receptor Antagonists

The application of both structure- and ligand-based design approaches represents to date one of the most useful strategies in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)­[1,2,4]-triazolo­[2,3-<i>a</i>]­[1,3,5]­triazin-5-ylamino]­ethyl)­phenol), we revisited a general pharmacophore hypothesis for the human A_2A adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated by using an external test set of 29 newly synthesized human adenosine receptor antagonists

Impacts of Grapevine Leafroll Disease on Fruit Yield and Grape and Wine Chemistry in a Wine Grape (Vitis vinifera L.) Cultivar

Grapevine leafroll disease (GLD) is an economically important virus disease affecting wine grapes (Vitis viniferaL.), but little is known about its effect on wine chemistry and sensory composition of wines. In this study, impacts of GLD on fruit yield, berry quality and wine chemistry and sensory features were investigated in a red wine grape cultivar planted in a commercial vineyard. Own-rooted Merlot vines showing GLD symptoms and tested positive forGrapevine leafroll-associated virus 3and adjacent non-symptomatic vines that tested negative for the virus were compared during three consecutive seasons. Number and total weight of clusters per vine were significantly less in symptomatic relative to non-symptomatic vines. In contrast to previous studies, a time-course analysis of juice from grapes harvested at different stages of berry development from symptomatic and non-symptomatic vines indicated more prominent negative impacts of GLD on total soluble solids (TSS) and berry skin anthocyanins than in juice pH and titratable acidity. Differences in TSS between grapes of symptomatic and non-symptomatic vines were more pronounced after the onset ofvéraison, with significantly lower concentrations of TSS in grapes from symptomatic vines throughout berry ripening until harvest. Wines made from grapes of GLD-affected vines had significantly lower alcohol, polymeric pigments, and anthocyanins compared to corresponding wines from grapes of non-symptomatic vines. Sensory descriptive analysis of 2010 wines indicated significant differences in color, aroma and astringency between wines made from grapes harvested from GLD-affected and unaffected vines. The impacts of GLD on yield and fruit and wine quality traits were variable between the seasons, with greater impacts observed during a cooler season, suggesting the influence of host plant × environment interactions on overall impacts of the disease