Computer-assisted placement technique in hip resurfacing arthroplasty: improvement in accuracy?

Freehand positioning of the femoral drill guide is difficult during hip resurfacing and the surgeon is often unsure of the implant position achieved peroperatively. The purpose of this study was to find out whether, by using a navigation system, acetabular and femoral component positioning could be made easier and more precise. Eighteen patients operated on by the same surgeon were matched by sex, age, BMI, diagnosis and ASA score (nine patients with computer assistance, nine with the regular ancillary). Pre-operative planning was done on standard AP and axial radiographs with CT scan views for the computer-assisted operations. The final position of implants was evaluated by the same radiographs for all patients. The follow-up was at least 1 year. No difference between both groups in terms of femoral component position was observed (p > 0.05). There was also no difference in femoral notching. A trend for a better cup position was observed for the navigated hips, especially for cup anteversion. There was no additional operating time for the navigated hips. Hip navigation for resurfacing surgery may allow improved visualisation and hip implant positioning, but its advantage probably will be more obvious with mini-incisions than with regular incision surgery.

Sistema de monitorització Open Source: projecte d'empresa per Computer Technology Catalunya

L’objectiu del projecte consisteix en l’estudi, simulació i implantació d’un conjunt d’aplicacions que permeten tenir un control sobre possibles problemes que puguin succeir a la nostra xarxa. Aquest projecte és la solució als problemes de detecció d’errors en el funcionament de les infraestructures de networking de les que disposen els nostres clients.

Estudi per a un sistema de mesura de pes per a marmota alpina

Aquest projecte tracta sobre la viabilitat de la construcció d’un sistema per al seguiment del pes d’una població de marmotes en alta muntanya. Bàsicament, es construeix una bàscula amb un sensor de força i un sensor de temperatura. Aquestes sortides analògiques es connecten a un microcontrolador ATmega8 que, mitjançant un algorisme desenvolupat en aquest projecte, està contínuament en escolta fins a detectar un canvi sobtat en el pes. Aleshores les dades s’enregistren i es guarden en una memòria SRAM per a, posteriorment, poder ser descarregades a un ordinador i analitzades per un programa que s’ha creat per a tal finalitat.

A numerical algorithm for finding solutions of a generalized Nash equilibrium problem

A family of nonempty closed convex sets is built by using the data of the Generalized Nash equilibrium problem (GNEP). The sets are selected iteratively such that the intersection of the selected sets contains solutions of the GNEP. The algorithm introduced by Iusem-Sosa (2003) is adapted to obtain solutions of the GNEP. Finally some numerical experiments are given to illustrate the numerical behavior of the algorithm.

A programme for computer aided identification of Phlebotomine sandflies of the Americas (CIPA): presentation and check-list of American species

The CIPA programme is a collaborative project including two entomologists from France and seven South and Central America countries. Its objective is the development of an expert system for computer aided identification of phlebotomine sandflies from the Americas. It also includes the formation of data bases for bibliographic, taxonomic and biogeographic data. Participant consensus on taxonomic prerequisites, standardization in bibliographic data collections and selection of descriptive variables for the final programme has been established through continous communication among participants and annual meetings. The adopted check-list of American sandflies presented here includes 386 specific taxa, ordered into genera and 28 sub-genera or species groups.

Prenatal diagnosis of congenital lung malformations.

Prenatal diagnosis of congenital lung anomalies has increased in recent years as imaging methods have benefitted from technical improvements. The purpose of this pictorial essay is to illustrate typical imaging findings of a wide spectrum of congenital lung anomalies on prenatal US and MRI. Moreover, we propose an algorithm based on imaging findings to facilitate the differential diagnosis, and suggest a follow-up algorithm during pregnancy and in the immediate postnatal period.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

Volumetric quantification of atherosclerotic plaque in CT considering partial volume effect.

Coronary artery calcification (CAC) is quantified based on a computed tomography (CT) scan image. A calcified region is identified. Modified expectation maximization (MEM) of a statistical model for the calcified and background material is used to estimate the partial calcium content of the voxels. The algorithm limits the region over which MEM is performed. By using MEM, the statistical properties of the model are iteratively updated based on the calculated resultant calcium distribution from the previous iteration. The estimated statistical properties are used to generate a map of the partial calcium content in the calcified region. The volume of calcium in the calcified region is determined based on the map. The experimental results on a cardiac phantom, scanned 90 times using 15 different protocols, demonstrate that the proposed method is less sensitive to partial volume effect and noise, with average error of 9.5% (standard deviation (SD) of 5-7mm(3)) compared with 67% (SD of 3-20mm(3)) for conventional techniques. The high reproducibility of the proposed method for 35 patients, scanned twice using the same protocol at a minimum interval of 10 min, shows that the method provides 2-3 times lower interscan variation than conventional techniques.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

A modular approach for integrative analysis of large-scale gene-expression and drug-response data

High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

Parallelization of whole genome alignment

With the advent of High performance computing, it is now possible to achieve orders of magnitude performance and computation e ciency gains over conventional computer architectures. This thesis explores the potential of using high performance computing to accelerate whole genome alignment. A parallel technique is applied to an algorithm for whole genome alignment, this technique is explained and some experiments were carried out to test it. This technique is based in a fair usage of the available resource to execute genome alignment and how this can be used in HPC clusters. This work is a rst approximation to whole genome alignment and it shows the advantages of parallelism and some of the drawbacks that our technique has. This work describes the resource limitations of current WGA applications when dealing with large quantities of sequences. It proposes a parallel heuristic to distribute the load and to assure that alignment quality is mantained.

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.