Comparison of topography- and aperture-dependent motion compensation algorithms for airborne SAR

This letter presents a comparison between threeFourier-based motion compensation (MoCo) algorithms forairborne synthetic aperture radar (SAR) systems. These algorithmscircumvent the limitations of conventional MoCo, namelythe assumption of a reference height and the beam-center approximation.All these approaches rely on the inherent time–frequencyrelation in SAR systems but exploit it differently, with the consequentdifferences in accuracy and computational burden. Aftera brief overview of the three approaches, the performance ofeach algorithm is analyzed with respect to azimuthal topographyaccommodation, angle accommodation, and maximum frequencyof track deviations with which the algorithm can cope. Also, ananalysis on the computational complexity is presented. Quantitativeresults are shown using real data acquired by the ExperimentalSAR system of the German Aerospace Center (DLR).

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Genetic variation in the Cytbgene of human cerebral Taenia soliumcysticerci recovered from clinically and radiologically heterogeneous patients with neurocysticercosis

Neurocysticercosis (NC) is a clinically and radiologically heterogeneous parasitic disease caused by the establishment of larval Taenia solium in the human central nervous system. Host and/or parasite variations may be related to this observed heterogeneity. Genetic differences between pig and human-derived T. solium cysticerci have been reported previously. In this study, 28 cysticerci were surgically removed from 12 human NC patients, the mitochondrial gene that encodes cytochrome b was amplified from the cysticerci and genetic variations that may be related to NC heterogeneity were characterised. Nine different haplotypes (Ht), which were clustered in four haplogroups (Hg), were identified. Hg 3 and 4 exhibited a tendency to associate with age and gender, respectively. However, no significant associations were found between NC heterogeneity and the different T. solium cysticerci Ht or Hg. Parasite variants obtained from patients with similar NC clinical or radiological features were genetically closer than those found in groups of patients with a different NC profile when using the Mantel test. Overall, this study establishes the presence of genetic differences in the Cytb gene of T. solium isolated from human cysticerci and suggests that parasite variation could contribute to NC heterogeneity.

LMM: an OWL-DL metamodel to represent heterogeneous lexical knowledge

In this paper we present a Linguistic Meta-Model (LMM) allowing a semiotic-cognitive representation of knowledge. LMM is freely available and integrates the schemata of linguistic knowledge resources, such as WordNet and FrameNet, as well as foundational ontologies, such as DOLCE and its extensions. In addition, LMM is able to deal with multilinguality and to represent individuals and facts in an open domain perspective.

Clinical and Virological Efficacy of Etravirine Plus Two Active Nucleos(t)ide Analogs in an Heterogeneous HIV-Infected Population.

Etravirine (ETV) is recommended in combination with a boosted protease inhibitor plus an optimized background regimen for salvage therapy, but there is limited experience with its use in combination with two nucleos(t)ide reverse-transcriptase inhibitors (NRTIs). This multicenter study aimed to assess the efficacy of this combination in two scenarios: group A) subjects without virologic failure on or no experience with non-nucleoside reverse-transcriptase inhibitors (NNRTIs) switched due to adverse events and group B) subjects switched after a virologic failure on an efavirenz- or nevirapine-based regimen. The primary endpoint was efficacy at 52 weeks analysed by intention-to-treat. Virologic failure was defined as the inability to suppress plasma HIV-RNA to <50 copies/mL after 24 weeks on treatment, or a confirmed viral load >200 copies/mL in patients who had previously achieved a viral suppression or had an undetectable viral load at inclusion. Two hundred eighty seven patients were included. Treatment efficacy rates in group A and B were 88.0% (CI95, 83.9-92.1%) and 77.4% (CI95, 65.0-89.7%), respectively; the rates reached 97.2% (CI95, 95.1-99.3%) and 90.5% (CI95, 81.7-99.3), by on-treatment analysis. The once-a-day ETV treatment was as effective as the twice daily dosing regimen. Grade 1-2 adverse events were observed motivating a treatment switch in 4.2% of the subjects. In conclusion, ETV (once- or twice daily) plus two analogs is a suitable, well-tolerated combination both as a switching strategy and after failure with first generation NNRTIs, ensuring full drug activity. TRIAL REGISTRATION ClinicalTrials.gov NCT01437241.

Heterogeneous metabolic adaptation of C57BL/6J mice to high-fat diet.

C57BL/6J mice were fed a high-fat, carbohydrate-free diet (HFD) for 9 mo. Approximately 50% of the mice became obese and diabetic (ObD), approximately 10% lean and diabetic (LD), approximately 10% lean and nondiabetic (LnD), and approximately 30% displayed intermediate phenotype. All of the HFD mice were insulin resistant. In the fasted state, whole body glucose clearance was reduced in ObD mice, unchanged in the LD mice, and increased in the LnD mice compared with the normal-chow mice. Because fasted ObD mice were hyperinsulinemic and the lean mice slightly insulinopenic, there was no correlation between insulin levels and increased glucose utilization. In vivo, tissue glucose uptake assessed by 2-[(14)C]deoxyglucose accumulation was reduced in most muscles in the ObD mice but increased in the LnD mice compared with the values of the control mice. In the LD mice, the glucose uptake rates were reduced in extensor digitorum longus (EDL) and total hindlimb but increased in soleus, diaphragm, and heart. When assessed in vitro, glucose utilization rates in the absence and presence of insulin were similar in diaphragm, soleus, and EDL muscles isolated from all groups of mice. Thus, in genetically homogenous mice, HFD feeding lead to different metabolic adaptations. Whereas all of the mice became insulin resistant, this was associated, in obese mice, with decreased glucose clearance and hyperinsulinemia and, in lean mice, with increased glucose clearance in the presence of mild insulinopenia. Therefore, increased glucose clearance in lean mice could not be explained by increased insulin level, indicating that other in vivo mechanisms are triggered to control muscle glucose utilization. These adaptive mechanisms could participate in the protection against development of obesity.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.

Characteristics and effectiveness of diabetes self-management educational programs targeted to racial/ethnic minority groups: a systematic review, meta-analysis and meta-regression.

BACKGROUND It is not clear to what extent educational programs aimed at promoting diabetes self-management in ethnic minority groups are effective. The aim of this work was to systematically review the effectiveness of educational programs to promote the self-management of racial/ethnic minority groups with type 2 diabetes, and to identify programs' characteristics associated with greater success. METHODS We undertook a systematic literature review. Specific searches were designed and implemented for Medline, EMBASE, CINAHL, ISI Web of Knowledge, Scirus, Current Contents and nine additional sources (from inception to October 2012). We included experimental and quasi-experimental studies assessing the impact of educational programs targeted to racial/ethnic minority groups with type 2 diabetes. We only included interventions conducted in countries members of the OECD. Two reviewers independently screened citations. Structured forms were used to extract information on intervention characteristics, effectiveness, and cost-effectiveness. When possible, we conducted random-effects meta-analyses using standardized mean differences to obtain aggregate estimates of effect size with 95% confidence intervals. Two reviewers independently extracted all the information and critically appraised the studies. RESULTS We identified thirty-seven studies reporting on thirty-nine educational programs. Most of them were conducted in the US, with African American or Latino participants. Most programs obtained some benefits over standard care in improving diabetes knowledge, self-management behaviors and clinical outcomes. A meta-analysis of 20 randomized controlled trials (3,094 patients) indicated that the programs produced a reduction in glycated hemoglobin of -0.31% (95% CI -0.48% to -0.14%). Diabetes knowledge and self-management measures were too heterogeneous to pool. Meta-regressions showed larger reduction in glycated hemoglobin in individual and face to face delivered interventions, as well as in those involving peer educators, including cognitive reframing techniques, and a lower number of teaching methods. The long-term effects remain unknown and cost-effectiveness was rarely estimated. CONCLUSIONS Diabetes self-management educational programs targeted to racial/ethnic minority groups can produce a positive effect on diabetes knowledge and on self-management behavior, ultimately improving glycemic control. Future programs should take into account the key characteristics identified in this review.

Multicast algorithms evaluation using an adaptative routing in ATM networks

This paper proposes a multicast implementation based on adaptive routing with anticipated calculation. Three different cost measures for a point-to-multipoint connection: bandwidth cost, connection establishment cost and switching cost can be considered. The application of the method based on pre-evaluated routing tables makes possible the reduction of bandwidth cost and connection establishment cost individually

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.

Implementation of zonal control algorithms in adaptive optical systems with sparse control matrices

Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.

Analysis and Monte Carlo simulations of a model for the spread of infectious diseases in heterogeneous metapopulations

We present a study of the continuous-time equations governing the dynamics of a susceptible infected-susceptible model on heterogeneous metapopulations. These equations have been recently proposed as an alternative formulation for the spread of infectious diseases in metapopulations in a continuous-time framework. Individual-based Monte Carlo simulations of epidemic spread in uncorrelated networks are also performed revealing a good agreement with analytical predictions under the assumption of simultaneous transmission or recovery and migration processes

Continuous-time formulation of reaction-diffusion processes on heterogeneous metapopulations

We present the derivation of the continuous-time equations governing the limit dynamics of discrete-time reaction-diffusion processes defined on heterogeneous metapopulations. We show that, when a rigorous time limit is performed, the lack of an epidemic threshold in the spread of infections is not limited to metapopulations with a scale-free architecture, as it has been predicted from dynamical equations in which reaction and diffusion occur sequentially in time

Phase-sensitive black-blood coronary vessel wall imaging.

Black-blood MR coronary vessel wall imaging may become a powerful tool for the quantitative and noninvasive assessment of atherosclerosis and positive arterial remodeling. Although dual-inversion recovery is currently the gold standard, optimal lumen-to-vessel wall contrast is sometimes difficult to obtain, and the time window available for imaging is limited due to competing requirements between blood signal nulling time and period of minimal myocardial motion. Further, atherosclerosis is a spatially heterogeneous disease, and imaging at multiple anatomic levels of the coronary circulation is mandatory. However, this requirement of enhanced volumetric coverage comes at the expense of scanning time. Phase-sensitive inversion recovery has shown to be very valuable for enhancing tissue-tissue contrast and for making inversion recovery imaging less sensitive to tissue signal nulling time. This work enables multislice black-blood coronary vessel wall imaging in a single breath hold by extending phase-sensitive inversion recovery to phase-sensitive dual-inversion recovery, by combining it with spiral imaging and yet relaxing constraints related to blood signal nulling time and period of minimal myocardial motion.