Multi-scale genetic network inference based on time series gene expression profiles

This work integrates multi-scale clustering and short-time correlation to estimate genetic networks with different time resolutions and detail levels. Gene expression data are noisy and large scale. Clustering is widely used to group genes with similar pattern. The cluster centers can be used to infer the genetic networks among these clusters. This work introduces the Multi-scale Fuzzy K-means clustering algorithm to uncover groups of coregulated genes and capture the networks in different levels of detail.;Time series expression profiles provide dynamic information for inferring gene regulatory relationships. Large scale network inference, identifying the transient interactions and feedback loops as well as differentiating direct and indirect interactions are among the major challenges of genetic network inference. Time correlation can estimate the time delay and edge direction. Partial correlation and directed-separation theory help differentiate direct and indirect interactions and identify feedback loops. This work introduces the constraint-based time-correlation (CBTC) network inference algorithm that combines these methods with time correlation estimation to more fully characterize genetic networks. Gene expression regulation can happen in specific time periods and conditions instead of across the whole expression profile. Short-time correlation can capture transient interactions.;The network discovery algorithm was mainly validated using yeast cell cycle data. The algorithm successfully identified the yeast cell cycle development stages, cell cycle and negative feedback loops, and indicated how the networks dynamically changes over time. The inferred networks reflect most interactions previously identified by genome-wide location analysis and match the extant literature. At detailed network level, the inferred networks provide more detailed information about genes (or clusters) and the interactions among them. Interesting genes, clusters and interactions were identified, which match the literature and the gene ontology information and provide hypotheses for further studies

Numerical Drag Prediction of NASA Common Research Models Using Different Turbulence Models

The goal of this research is to perform 3D turbulence flow simulations to predict the drag of Wing-body-tail (WBT) and Wing-body-nacelle-Pylon (WBNP) aircraft configurations from NASA Common Research Models. These configurations are also part of the 4th and 6th AIAA Drag Prediction Workshops in which CFD modelers have participated worldwide. The computations are performed using CFD solver ANSYS FLUENT. The compressible Reynolds-Averaged Navier-Stokes (RANS) equations are solved using two turbulence models – the Spalart-Allmaras (SA) and SST k-ω. Drag polar and drag rise curves are obtained by performing computations at different angles of attack at a constant Mach number. Pressure distributions and flow separation analysis are presented at different angles of attack. Comparison of computational results for WBT and WBNP models is made with the experimental data using the two turbulence models; good agreements is obtained. For WBNP, an aero-elastically deformed model of the wing is also considered at an angle of attack of 2.75°; the computations again are in reasonable agreement with the experiment. The computed WBNP results are compared with WB results for the drag increment study

Tris(ethyl­enediamine-κ2 N,N′)cobalt(III) aqua­tris­(oxalato-κ2 O 1,O 2)indate(III)

In the cation of the title compound, [Co(C2H8N2)3][In(C2O4)3(H2O)], the CoIII atom is coordinated by six N atoms from three ethyl­enediamine mol­ecules. The CoIII—N bond lengths lie in the range 1.956 (4)–1.986 (4) Å. In the anion, the InIII atom is seven-coordinated by six O atoms from three oxalate ligands and by a water mol­ecule. The cations and anions are linked by extensive O—H⋯O and N—H⋯O hydrogen bonds, forming a supermolecular network

Study of the control for the recovery of a rocket's launch system

La investigació sobre l’avenç i la innovació tecnològica és un dels principals objectes d’estudi en la indústria aeroespacial. El reús de vehicles espacials és un d’ells i es tracta d’un important aspecte per disminuir els grans costos i recursos que una missió espacial implica, minimitzant també l’impacte ambiental. Aquest treball desenvolupa l’estudi i la implementació del control per la recuperació segura dels sistemes de llançament d’un coet. Per tal d’assolir aquest anàlisis, s’avaluen els actuals coets reutilitzables, seleccionant el Falcon 9 del SpaceX com a model principal en el qual el projecte es centra. Un cop caracteritzat aquest sistema en particular, es determina la modelització d’equacions del problema amb l’objectiu de crear un programa en l’entorn de Matlab i efectuar simulacions. La necessitat d’un sistema de control és inferida mitjançant els resultats de les primeres simulacions a causa de l’absència dels paràmetres d’aterratge segur, d’entre els quals el més important és una velocitat final pròxima a 0. Conseqüentment, es proposen i comparen diferents controladors lineals a fi d’aconseguir el comportament desitjat del sistema. No obstant, les no-linealitats del problema sumades a les limitacions d’aquests controladors incrementa la complexitat, a causa de la considerable quantitat d’entrades de control. Per aquests motius, el sistema es simplifica englobant les forces i els moments en les corresponents resultants amb les quals la totalitat de les superfícies de control han de contribuir. Seguint aquesta metodologia, el sistema desenvolupat consisteix en controlar la velocitat mitjançant les forces i l’angle de capcineig amb els moments. D’aquest últim, s’extreu com a conclusió que el Control Predictiu basat en Model disposa d’una tendència a ajustar-se millor a la consigna que el PID. En definitiva, les limitacions d’aquests controladors tenen un impacte en la resposta final i, per aquesta raó, es requereixen de propostes més complexes per tal d’adquirir una aproximació encara més propera al problema real, com per exemple controladors no lineals o un segon nivell d’aquests per determinar les accions que cada dispositiu de control haurien d’efectuar a partir de les resultants de les forces i els moments, les quals són les entrades del sistema que ja ha estat controlat.The research of advanced and innovative technologies is one of the main concerns within the aerospace industry. Spacecraft reusability is one of them, being an important aspect to diminish the huge costs and resources that a space mission implicate, minimising also the environmental impact. This thesis develops the study and the implementation of the control for the safe recovery of the launch system of a rocket. In order to accomplish this analysis, the current successful reusable rockets are evaluated and the Falcon 9 from the SpaceX is selected as the main model in which the project is focused on. Once characterised this particular system, the problem equation modelling is determined to create a framework within a Matlab environment and perform simulations. The need of a control system is inferred through the first simulations results due to the lack of the safe landing parameters, being the most important a final velocity close to 0. Consequently, different linear controllers are proposed and compared to achieve the desired behaviour from the system. Nevertheless, the non-linearity of the problem added to these controllers limitations increase the complexity, due to the considerable quantity of control inputs. For these reasons, the system is simplified by computing the resultant forces and moments that the overall control surfaces must contribute. Following this methodology, the developed system consists in controlling the velocity with the forces and the pitch angle with the moments. From this last, the extracted conclusion is the Model Predictive Control tendency to dispose of a better adjustment to the setpoint rather than the PID. In definitive, the limitations of these controllers have an impact to the final response and, for this reason, more complex proposals would be required to acquire an even closer approach to the real problem, such as nonlinear controllers or a second level of these type of controllers to determine the performance of each control device from the resultants of the forces and the moments, which are the inputs of the already controlled system