28 resultados para likelihood-based inference


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Major histocompatibility complex (MHC) antigen-presenting genes are the most variable loci in vertebrate genomes. Host-parasite co-evolution is assumed to maintain the excessive polymorphism in the MHC loci. However, the molecular mechanisms underlying the striking diversity in the MHC remain contentious. The extent to which recombination contributes to the diversity at MHC loci in natural populations is still controversial, and there have been only few comparative studies that make quantitative estimates of recombination rates. In this study, we performed a comparative analysis for 15 different ungulates species to estimate the population recombination rate, and to quantify levels of selection. As expected for all species, we observed signatures of strong positive selection, and identified individual residues experiencing selection that were congruent with those constituting the peptide-binding region of the human DRB gene. However, in addition for each species, we also observed recombination rates that were significantly different from zero on the basis of likelihood-permutation tests, and in other non-quantitative analyses. Patterns of synonymous and non-synonymous sequence diversity were consistent with differing demographic histories between species, but recent simulation studies by other authors suggest inference of selection and recombination is likely to be robust to such deviations from standard models. If high rates of recombination are common in MHC genes of other taxa, re-evaluation of many inference-based phylogenetic analyses of MHC loci, such as estimates of the divergence time of alleles and trans-specific polymorphism, may be required.

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In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.

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Monte Carlo simulation was used to evaluate properties of a simple Bayesian MCMC analysis of the random effects model for single group Cormack-Jolly-Seber capture-recapture data. The MCMC method is applied to the model via a logit link, so parameters p, S are on a logit scale, where logit(S) is assumed to have, and is generated from, a normal distribution with mean μ and variance σ2 . Marginal prior distributions on logit(p) and μ were independent normal with mean zero and standard deviation 1.75 for logit(p) and 100 for μ ; hence minimally informative. Marginal prior distribution on σ2 was placed on τ2=1/σ2 as a gamma distribution with α=β=0.001 . The study design has 432 points spread over 5 factors: occasions (t) , new releases per occasion (u), p, μ , and σ . At each design point 100 independent trials were completed (hence 43,200 trials in total), each with sample size n=10,000 from the parameter posterior distribution. At 128 of these design points comparisons are made to previously reported results from a method of moments procedure. We looked at properties of point and interval inference on μ , and σ based on the posterior mean, median, and mode and equal-tailed 95% credibility interval. Bayesian inference did very well for the parameter μ , but under the conditions used here, MCMC inference performance for σ was mixed: poor for sparse data (i.e., only 7 occasions) or σ=0 , but good when there were sufficient data and not small σ .

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In the setting of high-dimensional linear models with Gaussian noise, we investigate the possibility of confidence statements connected to model selection. Although there exist numerous procedures for adaptive (point) estimation, the construction of adaptive confidence regions is severely limited (cf. Li in Ann Stat 17:1001–1008, 1989). The present paper sheds new light on this gap. We develop exact and adaptive confidence regions for the best approximating model in terms of risk. One of our constructions is based on a multiscale procedure and a particular coupling argument. Utilizing exponential inequalities for noncentral χ2-distributions, we show that the risk and quadratic loss of all models within our confidence region are uniformly bounded by the minimal risk times a factor close to one.

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A close to native structure of bulk biological specimens can be imaged by cryo-electron microscopy of vitreous sections (CEMOVIS). In some cases structural information can be combined with X-ray data leading to atomic resolution in situ. However, CEMOVIS is not routinely used. The two critical steps consist of producing a frozen section ribbon of a few millimeters in length and transferring the ribbon onto an electron microscopy grid. During these steps, the first sections of the ribbon are wrapped around an eyelash (unwrapping is frequent). When a ribbon is sufficiently attached to the eyelash, the operator must guide the nascent ribbon. Steady hands are required. Shaking or overstretching may break the ribbon. In turn, the ribbon immediately wraps around itself or flies away and thereby becomes unusable. Micromanipulators for eyelashes and grids as well as ionizers to attach section ribbons to grids were proposed. The rate of successful ribbon collection, however, remained low for most operators. Here we present a setup composed of two micromanipulators. One of the micromanipulators guides an electrically conductive fiber to which the ribbon sticks with unprecedented efficiency in comparison to a not conductive eyelash. The second micromanipulator positions the grid beneath the newly formed section ribbon and with the help of an ionizer the ribbon is attached to the grid. Although manipulations are greatly facilitated, sectioning artifacts remain but the likelihood to investigate high quality sections is significantly increased due to the large number of sections that can be produced with the reported tool.

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PURPOSE To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. PATIENTS AND METHODS 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers' errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder's evaluations of the situation and personal characteristics. RESULTS Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%-96% would speak up towards a supervisor failing to check a prescription, 45%-81% would point a coworker to a missed hand disinfection, 82%-94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%-92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. CONCLUSIONS Clinicians' willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns.

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We present new visible and infrared observations of the hot Jupiter Kepler-7b to determine its atmospheric properties. Our analysis allows us to (1) refine Kepler-7b's relatively large geometric albedo of Ag = 0.35 ± 0.02, (2) place upper limits on Kepler-7b thermal emission that remains undetected in both Spitzer bandpasses and (3) report a westward shift in the Kepler optical phase curve. We argue that Kepler-7b's visible flux cannot be due to thermal emission or Rayleigh scattering from H2 molecules. We therefore conclude that high altitude, optically reflective clouds located west from the substellar point are present in its atmosphere. We find that a silicate-based cloud composition is a possible candidate. Kepler-7b exhibits several properties that may make it particularly amenable to cloud formation in its upper atmosphere. These include a hot deep atmosphere that avoids a cloud cold trap, very low surface gravity to suppress cloud sedimentation, and a planetary equilibrium temperature in a range that allows for silicate clouds to potentially form in the visible atmosphere probed by Kepler. Our analysis does not only present evidence of optically thick clouds on Kepler-7b but also yields the first map of clouds in an exoplanet atmosphere.

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Dynamically typed languages lack information about the types of variables in the source code. Developers care about this information as it supports program comprehension. Ba- sic type inference techniques are helpful, but may yield many false positives or negatives. We propose to mine information from the software ecosys- tem on how frequently given types are inferred unambigu- ously to improve the quality of type inference for a single system. This paper presents an approach to augment existing type inference techniques by supplementing the informa- tion available in the source code of a project with data from other projects written in the same language. For all available projects, we track how often messages are sent to instance variables throughout the source code. Predictions for the type of a variable are made based on the messages sent to it. The evaluation of a proof-of-concept prototype shows that this approach works well for types that are sufficiently popular, like those from the standard librarie, and tends to create false positives for unpopular or domain specific types. The false positives are, in most cases, fairly easily identifiable. Also, the evaluation data shows a substantial increase in the number of correctly inferred types when compared to the non-augmented type inference.

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Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

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Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald–Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

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Allostatic load (AL) is a marker of physiological dysregulation which reflects exposure to chronic stress. High AL has been related to poorer health outcomes including mortality. We examine here the association of socioeconomic and lifestyle factors with AL. Additionally, we investigate the extent to which AL is genetically determined. We included 803 participants (52% women, mean age 48±16years) from a population and family-based Swiss study. We computed an AL index aggregating 14 markers from cardiovascular, metabolic, lipidic, oxidative, hypothalamus-pituitary-adrenal and inflammatory homeostatic axes. Education and occupational position were used as indicators of socioeconomic status. Marital status, stress, alcohol intake, smoking, dietary patterns and physical activity were considered as lifestyle factors. Heritability of AL was estimated by maximum likelihood. Women with a low occupational position had higher AL (low vs. high OR=3.99, 95%CI [1.22;13.05]), while the opposite was observed for men (middle vs. high OR=0.48, 95%CI [0.23;0.99]). Education tended to be inversely associated with AL in both sexes(low vs. high OR=3.54, 95%CI [1.69;7.4]/OR=1.59, 95%CI [0.88;2.90] in women/men). Heavy drinking men as well as women abstaining from alcohol had higher AL than moderate drinkers. Physical activity was protective against AL while high salt intake was related to increased AL risk. The heritability of AL was estimated to be 29.5% ±7.9%. Our results suggest that generalized physiological dysregulation, as measured by AL, is determined by both environmental and genetic factors. The genetic contribution to AL remains modest when compared to the environmental component, which explains approximately 70% of the phenotypic variance.

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PURPOSE To compare patient outcomes and complication rates after different decompression techniques or instrumented fusion (IF) in lumbar spinal stenosis (LSS). METHODS The multicentre study was based on Spine Tango data. Inclusion criteria were LSS with a posterior decompression and pre- and postoperative COMI assessment between 3 and 24 months. 1,176 cases were assigned to four groups: (1) laminotomy (n = 642), (2) hemilaminectomy (n = 196), (3) laminectomy (n = 230) and (4) laminectomy combined with an IF (n = 108). Clinical outcomes were achievement of minimum relevant change in COMI back and leg pain and COMI score (2.2 points), surgical and general complications, measures taken due to complications, and reintervention on the index level based on patient information. The inverse propensity score weighting method was used for adjustment. RESULTS Laminotomy, hemilaminectomy and laminectomy were significantly less beneficial than laminectomy in combination with IF regarding leg pain (ORs with 95% CI 0.52, 0.34-0.81; 0.25, 0.15-0.41; 0.44, 0.27-0.72, respectively) and COMI score improvement (ORs with 95% CI 0.51, 0.33-0.81; 0.30, 0.18-0.51; 0.48, 0.29-0.79, respectively). However, the sole decompressions caused significantly fewer surgical (ORs with 95% CI 0.42, 0.26-0.69; 0.33, 0.17-0.63; 0.39, 0.21-0.71, respectively) and general complications (ORs with 95% CI 0.11, 0.04-0.29; 0.03, 0.003-0.41; 0.25, 0.09-0.71, respectively) than laminectomy in combination with IF. Accordingly, the likelihood of required measures was also significantly lower after laminotomy (OR 0.28, 95% CI 0.17-0.46), hemilaminectomy (OR 0.28, 95% CI 0.15-0.53) and after laminectomy (OR 0.39, 95% CI 0.22-0.68) in comparison with laminectomy with IF. The likelihood of a reintervention was not significantly different between the treatment groups. DISCUSSION As already demonstrated in the literature, decompression in patients with LSS is a very effective treatment. Despite better patient outcomes after laminectomy in combination with IF, caution is advised due to higher rates of surgical and general complications and consequent required measures. Based on the current study, laminotomy or laminectomy, rather than hemilaminectomy, is recommendable for minimum relevant pain relief.

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Chironomid-temperature inference models based on North American, European and combined surface sediment training sets were compared to assess the overall reliability of their predictions. Between 67 and 76 of the major chironomid taxa in each data set showed a unimodal response to July temperature, whereas between 5 and 22 of the common taxa showed a sigmoidal response. July temperature optima were highly correlated among the training sets, but the correlations for other taxon parameters such as tolerances and weighted averaging partial least squares (WA-PLS) and partial least squares (PLS) regression coefficients were much weaker. PLS, weighted averaging, WA-PLS, and the Modern Analogue Technique, all provided useful and reliable temperature inferences. Although jack-knifed error statistics suggested that two-component WA-PLS models had the highest predictive power, intercontinental tests suggested that other inference models performed better. The various models were able to provide good July temperature inferences, even where neither good nor close modern analogues for the fossil chironomid assemblages existed. When the models were applied to fossil Lateglacial assemblages from North America and Europe, the inferred rates and magnitude of July temperature changes varied among models. All models, however, revealed similar patterns of Lateglacial temperature change. Depending on the model used, the inferred Younger Dryas July temperature decrease ranged between 2.5 and 6°C.