990 resultados para threshold random variable
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Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable
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We study the behavior of the random-bond Ising model at zero temperature by numerical simulations for a variable amount of disorder. The model is an example of systems exhibiting a fluctuationless first-order phase transition similar to some field-induced phase transitions in ferromagnetic systems and the martensitic phase transition appearing in a number of metallic alloys. We focus on the study of the hysteresis cycles appearing when the external field is swept from positive to negative values. By using a finite-size scaling hypothesis, we analyze the disorder-induced phase transition between the phase exhibiting a discontinuity in the hysteresis cycle and the phase with the continuous hysteresis cycle. Critical exponents characterizing the transition are obtained. We also analyze the size and duration distributions of the magnetization jumps (avalanches).
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The decay of an unstable state under the influence of external colored noise has been studied by means of analog experiments and digital simulations. For both fixed and random initial conditions, the time evolution of the second moment ¿x2(t)¿ of the system variable was determined and then used to evaluate the nonlinear relaxation time. The results obtained are found to be in excellent agreement with the theoretical predictions of the immediately preceding paper [Casademunt, Jiménez-Aquino, and Sancho, Phys. Rev. A 40, 5905 (1989)].
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Random scale-free networks have the peculiar property of being prone to the spreading of infections. Here we provide for the susceptible-infected-susceptible model an exact result showing that a scale-free degree distribution with diverging second moment is a sufficient condition to have null epidemic threshold in unstructured networks with either assortative or disassortative mixing. Degree correlations result therefore irrelevant for the epidemic spreading picture in these scale-free networks. The present result is related to the divergence of the average nearest neighbors degree, enforced by the degree detailed balance condition.
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We develop a general theory for percolation in directed random networks with arbitrary two-point correlations and bidirectional edgesthat is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions.
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All derivations of the one-dimensional telegraphers equation, based on the persistent random walk model, assume a constant speed of signal propagation. We generalize here the model to allow for a variable propagation speed and study several limiting cases in detail. We also show the connections of this model with anomalous diffusion behavior and with inertial dichotomous processes.
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This paper introduces a nonlinear measure of dependence between random variables in the context of remote sensing data analysis. The Hilbert-Schmidt Independence Criterion (HSIC) is a kernel method for evaluating statistical dependence. HSIC is based on computing the Hilbert-Schmidt norm of the cross-covariance operator of mapped samples in the corresponding Hilbert spaces. The HSIC empirical estimator is very easy to compute and has good theoretical and practical properties. We exploit the capabilities of HSIC to explain nonlinear dependences in two remote sensing problems: temperature estimation and chlorophyll concentration prediction from spectra. Results show that, when the relationship between random variables is nonlinear or when few data are available, the HSIC criterion outperforms other standard methods, such as the linear correlation or mutual information.
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Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.
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Aims :¦Several studies have questioned the validity of separating the diagnosis of alcohol abuse from that of alcohol dependence, and the DSM-5 task force has proposed combining the criteria from these two diagnoses to assess a single category of alcohol use disorders (AUD). Furthermore, the DSM-5 task force has proposed including a new 2-symptom threshold and a severity scale based on symptom counts for the AUD diagnosis. The current study aimed to examine these modifications in a large population-based sample.¦Method :¦Data stemmed from an adult sample (N=2588 ; mean age 51.3 years (s.d.: 0.2), 44.9% female) of current and lifetime drinkers from the PsyCoLaus study, conducted in the Lausanne area in Switzerland. AUDs and validating variables were assessed using a semi-structured diagnostic interview for the assessment of alcohol¦and other major psychiatric disorders. First, the adequacy of the proposed 2- symptom threshold was tested by comparing threshold models at each possible cutoff and a linear model, in relation to different validating variables. The model with the smallest Akaike Criterion Information (AIC) value was established as the best¦model for each validating variable. Second, models with varying subsets of individual AUD symptoms were created to assess the associations between each symptom and the validating variables. The subset of symptoms with the smallest AIC value was established as the best subset for each validator.¦Results :¦1) For the majority of validating variables, the linear model was found to be the best fitting model. 2) Among the various subsets of symptoms, the symptoms most frequently associated with the validating variables were : a) drinking despite having knowledge of a physical or psychological problem, b) having had a persistent desire or unsuccessful efforts to cut down or control drinking and c) craving. The¦least frequent symptoms were : d) drinking in larger amounts or over a longer period than was intended, e) spending a great deal of time in obtaining, using or recovering from alcohol use and f) failing to fulfill major role obligations.¦Conclusions :¦The proposed DSM-5 2-symptom threshold did not receive support in our data. Instead, a linear AUD diagnosis was supported with individuals receiving an increasingly severe AUD diagnosis. Moreover, certain symptoms were more frequently associated with the validating variables, which suggests that these¦symptoms should be considered as more severe.
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AIM: This study evaluates the effect of front suspension (FS) and dual suspension (DS) mountain-bike on performance and vibrations during off-road uphill riding. METHODS: Thirteen male cyclists (27+/-5 years, 70+/-6 kg, VO(2max)59+/-6 mL.kg(-1).min(-1), mean+/-SD) performed, in a random sequence, at their lactate threshold, an off-road uphill course (1.69 km, 212 m elevation gain) with both type of bicycles. Variable measured: a) VO(2) consumption (K4b2 analyzer, Cosmed), b) power output (SRM) c) gain in altitude and d) 3-D accelerations under the saddle and at the wheel (Physilog, EPFL, Switzerland). Power spectral analy- sis (Fourier) was performed from the vertical acceleration data. RESULTS: Respectively for the FS and DS mountain bike: speed amounted to 7.5+/-0.7 km.h(-1) and 7.4+/-0.8 km.h(-1), (NS), energy expenditure 1.39+/-0.16 kW and 1.38+/-0.18, (NS), gross efficiency 0.161+/-0.013 and 0.159+/-0.013, (NS), peak frequency of vibration under the saddle 4.78+/-2.85 Hz and 2.27+/-0.2 Hz (P<0.01) and median-frequency of vertical displacements of the saddle 9.41+/-1.47 Hz and 5.78+/-2.27 Hz (P<0.01). CONCLUSION: Vibrations at the saddle level of the DS bike are of low frequencies whereas those of the FS bike are mostly of high frequencies. In the DS bike, the torque produced by the cyclist at the pedal level may generate low frequency vibrations. We conclude that the DS bike absorbs more high frequency vibrations, is more comfortable and performs as well as the FS bicycle.
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Variation in queen number alters the genetic structure of social insect colonies, which in turn affects patterns of kin-selected conflict and cooperation. Theory suggests that shifts from single- to multiple-queen colonies are often associated with other changes in the breeding system, such as higher queen turnover, more local mating, and restricted dispersal. These changes may restrict gene flow between the two types of colonies and it has been suggested that this might ultimately lead to sympatric speciation. We performed a detailed microsatellite analysis of a large population of the ant Formica selysi, which revealed extensive variation in social structure, with 71 colonies headed by a single queen and 41 by multiple queens. This polymorphism in social structure appeared stable over time, since little change in the number of queens per colony was detected over a five-year period. Apart from queen number, single- and multiple-queen colonies had very similar breeding systems. Queen turnover was absent or very low in both types of colonies. Single- and multiple-queen colonies exhibited very small but significant levels of inbreeding, which indicates a slight deviation from random mating at a local scale and suggests that a small proportion of queens mate with related males. For both types of colonies, there was very little genetic structuring above the level of the nest, with no sign of isolation by distance. These similarities in the breeding systems were associated with a complete lack of genetic differentiation between single- and multiple-queen colonies, which provides no support for the hypothesis that change in queen number leads to restricted gene flow between social forms. Overall, this study suggests that the higher rates of queen turnover, local mating, and population structuring that are often associated with multiple-queen colonies do not appear when single- and multiple-queen colonies still coexist within the same population, but build up over time in populations consisting mostly of multiple-queen colonies.
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We develop an analytical approach to the susceptible-infected-susceptible epidemic model that allows us to unravel the true origin of the absence of an epidemic threshold in heterogeneous networks. We find that a delicate balance between the number of high degree nodes in the network and the topological distance between them dictates the existence or absence of such a threshold. In particular, small-world random networks with a degree distribution decaying slower than an exponential have a vanishing epidemic threshold in the thermodynamic limit.
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The objective of this study was to determine the inter- and intra-examiner reliability of pain pressure threshold algometry at various points of the abdominal wall of healthy women. Twenty-one healthy women in menacme with a mean age of 28 ± 5.4 years (range: 19-39 years) were included. All volunteers had regular menstrual cycles (27-33 days) and were right-handed and, to the best of our knowledge, none were taking medications at the time of testing. Women with a diagnosis of depression, anxiety or other mood disturbances were excluded. Women with previous abdominal surgery, any pain condition or any evidence of inflammation, hypertension, smoking, alcoholism, or inflammatory disease were also excluded. Pain perception thresholds were assessed with a pressure algometer with digital traction and compression and a measuring capacity for 5 kg. All points were localized by palpation and marked with a felt-tipped pen and each individual was evaluated over a period of 2 days in two consecutive sessions, each session consisting of a set of 14 point measurements repeated twice by two examiners in random sequence. There was no statistically significant difference in the mean pain threshold obtained by the two examiners on 2 diferent days (examiner A: P = 1.00; examiner B: P = 0.75; Wilcoxon matched pairs test). There was excellent/good agreement between examiners for all days and all points. Our results have established baseline values to which future researchers will be able to refer. They show that pressure algometry is a reliable measure for pain perception in the abdominal wall of healthy women.
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Les polymères sensibles à des stimuli ont été largement étudiés ces dernières années notamment en vue d’applications biomédicales. Ceux-ci ont la capacité de changer leurs propriétés de solubilité face à des variations de pH ou de température. Le but de cette thèse concerne la synthèse et l’étude de nouveaux diblocs composés de deux copolymères aléatoires. Les polymères ont été obtenus par polymérisation radicalaire contrôlée du type RAFT (reversible addition-fragmentation chain-transfer). Les polymères à bloc sont formés de monomères de méthacrylates et/ou d’acrylamides dont les polymères sont reconnus comme thermosensibles et sensible au pH. Premièrement, les copolymères à bloc aléatoires du type AnBm-b-ApBq ont été synthétisés à partir de N-n-propylacrylamide (nPA) et de N-ethylacrylamide (EA), respectivement A et B, par polymérisation RAFT. La cinétique de copolymérisation des poly(nPAx-co-EA1-x)-block-poly(nPAy-co-EA1-y) et leur composition ont été étudiées afin de caractériser et évaluer les propriétés physico-chimiques des copolymères à bloc aléatoires avec un faible indice de polydispersité . Leurs caractères thermosensibles ont été étudiés en solution aqueuse par spectroscopie UV-Vis, turbidimétrie et analyse de la diffusion dynamique de la lumière (DLS). Les points de trouble (CP) observés des blocs individuels et des copolymères formés démontrent des phases de transitions bien définies lors de la chauffe. Un grand nombre de macromolécules naturels démontrent des réponses aux stimuli externes tels que le pH et la température. Aussi, un troisième monomère, 2-diethylaminoethyl methacrylate (DEAEMA), a été ajouté à la synthèse pour former des copolymères à bloc , sous la forme AnBm-b-ApCq , et qui offre une double réponse (pH et température), modulable en solution. Ce type de polymère, aux multiples stimuli, de la forme poly(nPAx-co-DEAEMA1-x)-block-poly(nPAy-co-EA1-y), a lui aussi été synthétisé par polymérisation RAFT. Les résultats indiquent des copolymères à bloc aléatoires aux propriétés physico-chimiques différentes des premiers diblocs, notamment leur solubilité face aux variations de pH et de température. Enfin, le changement d’hydrophobie des copolymères a été étudié en faisant varier la longueur des séquences des blocs. Il est reconnu que la longueur relative des blocs affecte les mécanismes d’agrégation d’un copolymère amphiphile. Ainsi avec différents stimuli de pH et/ou de température, les expériences effectuées sur des copolymères à blocaléatoires de différentes longueurs montrent des comportements d’agrégation intéressants, évoluant sous différentes formes micellaires, d’agrégats et de vésicules.
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We analyze a finite horizon, single product, periodic review model in which pricing and production/inventory decisions are made simultaneously. Demands in different periods are random variables that are independent of each other and their distributions depend on the product price. Pricing and ordering decisions are made at the beginning of each period and all shortages are backlogged. Ordering cost includes both a fixed cost and a variable cost proportional to the amount ordered. The objective is to find an inventory policy and a pricing strategy maximizing expected profit over the finite horizon. We show that when the demand model is additive, the profit-to-go functions are k-concave and hence an (s,S,p) policy is optimal. In such a policy, the period inventory is managed based on the classical (s,S) policy and price is determined based on the inventory position at the beginning of each period. For more general demand functions, i.e., multiplicative plus additive functions, we demonstrate that the profit-to-go function is not necessarily k-concave and an (s,S,p) policy is not necessarily optimal. We introduce a new concept, the symmetric k-concave functions and apply it to provide a characterization of the optimal policy.