Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

The effects of dominance, regular inbreeding and sampling design on Q(ST), an estimator of population differentiation for quantitative traits.

To test whether quantitative traits are under directional or homogenizing selection, it is common practice to compare population differentiation estimates at molecular markers (F(ST)) and quantitative traits (Q(ST)). If the trait is neutral and its determinism is additive, then theory predicts that Q(ST) = F(ST), while Q(ST) > F(ST) is predicted under directional selection for different local optima, and Q(ST) < F(ST) is predicted under homogenizing selection. However, nonadditive effects can alter these predictions. Here, we investigate the influence of dominance on the relation between Q(ST) and F(ST) for neutral traits. Using analytical results and computer simulations, we show that dominance generally deflates Q(ST) relative to F(ST). Under inbreeding, the effect of dominance vanishes, and we show that for selfing species, a better estimate of Q(ST) is obtained from selfed families than from half-sib families. We also compare several sampling designs and find that it is always best to sample many populations (>20) with few families (five) rather than few populations with many families. Provided that estimates of Q(ST) are derived from individuals originating from many populations, we conclude that the pattern Q(ST) > F(ST), and hence the inference of directional selection for different local optima, is robust to the effect of nonadditive gene actions.

Decision-theoretic analysis of forensic sampling criteria using Bayesian decision networks

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.

The Acute STroke Registry and Analysis of Lausanne (ASTRAL): design and baseline analysis of an ischemic stroke registry including acute multimodal imaging.

BACKGROUND AND PURPOSE: Stroke registries are valuable tools for obtaining information about stroke epidemiology and management. The Acute STroke Registry and Analysis of Lausanne (ASTRAL) prospectively collects epidemiological, clinical, laboratory and multimodal brain imaging data of acute ischemic stroke patients in the Centre Hospitalier Universitaire Vaudois (CHUV). Here, we provide design and methods used to create ASTRAL and present baseline data of our patients (2003 to 2008). METHODS: All consecutive patients admitted to CHUV between January 1, 2003 and December 31, 2008 with acute ischemic stroke within 24 hours of symptom onset were included in ASTRAL. Patients arriving beyond 24 hours, with transient ischemic attack, intracerebral hemorrhage, subarachnoidal hemorrhage, or cerebral sinus venous thrombosis, were excluded. Recurrent ischemic strokes were registered as new events. RESULTS: Between 2003 and 2008, 1633 patients and 1742 events were registered in ASTRAL. There was a preponderance of males, even in the elderly. Cardioembolic stroke was the most frequent type of stroke. Most strokes were of minor severity (National Institute of Health Stroke Scale [NIHSS] score ≤ 4 in 40.8% of patients). Cardioembolic stroke and dissections presented with the most severe clinical picture. There was a significant number of patients with unknown onset stroke, including wake-up stroke (n=568, 33.1%). Median time from last-well time to hospital arrival was 142 minutes for known onset and 759 minutes for unknown-onset stroke. The rate of intravenous or intraarterial thrombolysis between 2003 and 2008 increased from 10.8% to 20.8% in patients admitted within 24 hours of last-well time. Acute brain imaging was performed in 1695 patients (97.3%) within 24 hours. In 1358 patients (78%) who underwent acute computed tomography angiography, 717 patients (52.8%) had significant abnormalities. Of the 1068 supratentorial stroke patients who underwent acute perfusion computed tomography (61.3%), focal hypoperfusion was demonstrated in 786 patients (73.6%). CONCLUSIONS: This hospital-based prospective registry of consecutive acute ischemic strokes incorporates demographic, clinical, metabolic, acute perfusion, and arterial imaging. It is characterized by a high proportion of minor and unknown-onset strokes, short onset-to-admission time for known-onset patients, rapidly increasing thrombolysis rates, and significant vascular and perfusion imaging abnormalities in the majority of patients.

Randomized controlled trial of interventions for young people at ultra-high risk of psychosis: study design and baseline characteristics.

OBJECTIVE: Intervention during the pre-psychotic period of illness holds the potential of delaying or even preventing the onset of a full-threshold disorder, or at least of reducing the impact of such a disorder if it does develop. The first step in realizing this aim was achieved more than 10 years ago with the development and validation of criteria for the identification of young people at ultra-high risk (UHR) of psychosis. Results of three clinical trials have been published that provide mixed support for the effectiveness of psychological and pharmacological interventions in preventing the onset of psychotic disorder. METHOD: The present paper describes a fourth study that has now been undertaken in which young people who met UHR criteria were randomized to one of three treatment groups: cognitive therapy plus risperidone (CogTher + Risp: n = 43); cognitive therapy plus placebo (CogTher + Placebo: n = 44); and supportive counselling + placebo (Supp + Placebo; n = 28). A fourth group of young people who did not agree to randomization were also followed up (monitoring: n = 78). Baseline characteristics of participants are provided. RESULTS AND CONCLUSION: The present study improves on the previous studies because treatment was provided for 12 months and the independent contributions of psychological and pharmacological treatments in preventing transition to psychosis in the UHR cohort and on levels of psychopathology and functioning can be directly compared. Issues associated with recruitment and randomization are discussed.

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The quality of environmental data analysis and propagation of errors are heavily affected by the representativity of the initial sampling design [CRE 93, DEU 97, KAN 04a, LEN 06, MUL07]. Geostatistical methods such as kriging are related to field samples, whose spatial distribution is crucial for the correct detection of the phenomena. Literature about the design of environmental monitoring networks (MN) is widespread and several interesting books have recently been published [GRU 06, LEN 06, MUL 07] in order to clarify the basic principles of spatial sampling design (monitoring networks optimization) based on Support Vector Machines was proposed. Nonetheless, modelers often receive real data coming from environmental monitoring networks that suffer from problems of non-homogenity (clustering). Clustering can be related to the preferential sampling or to the impossibility of reaching certain regions.

Characterizing the impact of minor cannula design modification.

OBJECTIVE: Bench evaluation of the hydrodynamic behavior of venous cannulas is a valuable technique for the analysis of their performance during cardiopulmonary bypass (CPB). The aim of this study was to investigate the effect of the internal diameter of the extracorporeal connecting tube of venous cannulas on flow rate (Q), pressure drop (delta P), and cannula resistance (delta P/Q²) values, using a computer assisted test bench.¦METHODS: An in vitro circuit was set up with silicone tubing between the test cannula encased in a movable reservoir, and a static reservoir. The delta P, defined as the difference between the drainage pressure and the preload pressure, was measured using high-fidelity Millar pressure transducers. Q was measured using an ultrasonic flowmeter. Data display and data recording were controlled using virtual instruments in a stepwise fashion.¦RESULTS: The 27 F smartcanula® with a 9 mm connecting tube diameter showed 17% less resistance compared to that with an 8 mm connecting tube diameter. Q values were 7.22±0.1 and 7.81±0.04 L/min for cannulas with 8 mm and 9 mm connecting tube diameters, respectively. The delta P/Q² ratio values were 72% lower for the Medtronic cannula with a 9 mm connecting tube diameter compared to that with an 8 mm connecting tube diameter. Q values for the Medtronic cannula were 3.94±0.23 and 6.58±0.04 L/min with 8 mm and 9 mm connecting tube diameters, respectively. The 27 F smartcanula® showed 13% more flow rate compared to the 28 F Medtronic cannula using the unpaired Student t-test (p<0.0001).¦CONCLUSIONS: Our results demonstrated that Q was increased but delta P and delta P/Q² values were significantly decreased when the connecting tube diameter was increased for venous cannulas. The connecting tube diameter significantly affected the resistance to liquid flow through the cannula. Smartcanulas® outperform Medtronic cannulas.

Effect of humeral stem design on humeral position and range of motion in reverse shoulder arthroplasty.

PURPOSE: The impacts of humeral offset and stem design after reverse shoulder arthroplasty (RSA) have not been well-studied, particularly with regard to newer stems which have a lower humeral inclination. The purpose of this study was to analyze the effect of different humeral stem designs on range of motion and humeral position following RSA. METHODS: Using a three-dimensional computer model of RSA, a traditional inlay Grammont stem was compared to a short curved onlay stem with different inclinations (155°, 145°, 135°) and offset (lateralised vs medialised). Humeral offset, the acromiohumeral distance (AHD), and range of motion were evaluated for each configuration. RESULTS: Altering stem design led to a nearly 7-mm change in humeral offset and 4 mm in the AHD. Different inclinations of the onlay stems had little influence on humeral offset and larger influence on decreasing the AHD. There was a 10° decrease in abduction and a 5° increase in adduction between an inlay Grammont design and an onlay design with the same inclination. Compared to the 155° model, the 135° model improved adduction by 28°, extension by 24° and external rotation of the elbow at the side by 15°, but led to a decrease in abduction of 9°. When the tray was placed medially, on the 145° model, a 9° loss of abduction was observed. CONCLUSIONS: With varus inclination prostheses (135° and 145°), elevation remains unchanged, abduction slightly decreases, but a dramatic improvement in adduction, extension and external rotation with the elbow at the side are observed.

Test result-based sampling: an efficient design for estimating the accuracy of patient safety indicators.

OBJECTIVE: Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. METHODS: We considered 3 real PSIs, whose rates were calculated using 3 years of discharge data from a university hospital and a hypothetical screen of very rare events. Sample size estimates, based on the expected sensitivity and precision, were compared across 4 study designs: random and VBS, with and without constraints on the size of the population to be screened. RESULTS: Over sensitivities ranging from 0.3 to 0.7 and PSI prevalence levels ranging from 0.02 to 0.2, the optimal VBS strategy makes it possible to reduce sample size by up to 60% in comparison with simple random sampling. For PSI prevalence levels below 1%, the minimal sample size required was still over 5000. CONCLUSIONS: Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.

Design and evaluation of a solid sampler for the monitoring of airborne 1,6-hexamethylene diisocyanate (HDI) and its prepolymers in 2-component spray painting

An active, solvent-free solid sampler was developed for the collection of 1,6-hexamethylene diisocyanate (HDI) aerosol and prepolymers. The sampler was made of a filter impregnated with 1-(2-methoxyphenyl)piperazine contained in a filter holder. Interferences with HDI were observed when a set of cellulose acetate filters and a polystyrene filter holder were used; a glass fiber filter and polypropylene filter cassette gave better results. The applicability of the sampling and analytical procedure was validated with a test chamber, constructed for the dynamic generation of HDI aerosol and prepolymers in commercial two-component spray paints (Desmodur(R) N75) used in car refinishing. The particle size distribution, temporal stability, and spatial uniformity of the simulated aerosol were established in order to test the sample. The monitoring of aerosol concentrations was conducted with the solid sampler paired to the reference impinger technique (impinger flasks contained 10 mL of 0.5 mg/mL 1-(2-methoxyphenyl)piperazine in toluene) under a controlled atmosphere in the test chamber. Analyses of derivatized HDI and prepolymers were carried out by using high-performance liquid chromatography and ultraviolet detection. The correlation between the solvent-free and the impinger techniques appeared fairly good (Y = 0.979X - 0.161; R = 0.978), when the tests were conducted in the range of 0.1 to 10 times the threshold limit value (TLV) for HDI monomer and up to 60-mu-g/m3 (3 U.K. TLVs) for total -N = C = O groups.

Application of detection probabilities to the design of amphibian monitoring programs in temporary ponds

Failure to detect a species in an area where it is present is a major source of error in biological surveys. We assessed whether it is possible to optimize single-visit biological monitoring surveys of highly dynamic freshwater ecosystems by framing them a priori within a particular period of time. Alternatively, we also searched for the optimal number of visits and when they should be conducted. We developed single-species occupancy models to estimate the monthly probability of detection of pond-breeding amphibians during a four-year monitoring program. Our results revealed that detection probability was species-specific and changed among sampling visits within a breeding season and also among breeding seasons. Thereby, the optimization of biological surveys with minimal survey effort (a single visit) is not feasible as it proves impossible to select a priori an adequate sampling period that remains robust across years. Alternatively, a two-survey combination at the beginning of the sampling season yielded optimal results and constituted an acceptable compromise between sampling efficacy and survey effort. Our study provides evidence of the variability and uncertainty that likely affects the efficacy of monitoring surveys, highlighting the need of repeated sampling in both ecological studies and conservation management.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.