983 resultados para Step Length Estimation
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This paper demonstrates that, unlike what the conventional wisdom says, measurement error biases in panel data estimation of convergence using OLS with fixed effects are huge, not trivial. It does so by way of the "skipping estimation"': taking data from every m years of the sample (where m is an integer greater than or equal to 2), as opposed to every single year. It is shown that the estimated speed of convergence from the OLS with fixed effects is biased upwards by as much as 7 to 15%.
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Specialized glucosensing neurons are present in the hypothalamus, some of which neighbor the median eminence, where the blood-brain barrier has been reported leaky. A leaky blood-brain barrier implies high tissue glucose levels and obviates a role for endothelial glucose transporters in the control of hypothalamic glucose concentration, important in understanding the mechanisms of glucose sensing We therefore addressed the question of blood-brain barrier integrity at the hypothalamus for glucose transport by examining the brain tissue-to-plasma glucose ratio in the hypothalamus relative to other brain regions. We also examined glycogenolysis in hypothalamus because its occurrence is unlikely in the potential absence of a hypothalamus-blood interface. Across all regions the concentration of glucose was comparable at a given plasma glucose concentration and was a near linear function of plasma glucose. At steady-state, hypothalamic glucose concentration was similar to the extracellular hypothalamic glucose concentration reported by others. Hypothalamic glycogen fell at a rate of approximately 1.5 micromol/g/h and remained present in substantial amounts. We conclude for the hypothalamus, a putative primary site of brain glucose sensing that: the rate-limiting step for glucose transport into brain cells is at the blood-hypothalamus interface, and that glycogenolysis is consistent with a substantial blood -to- intracellular glucose concentration gradient.
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Time periods composing stance phase of gait can be clinically meaningful parameters to reveal differences between normal and pathological gait. This study aimed, first, to describe a novel method for detecting stance and inner-stance temporal events based on foot-worn inertial sensors; second, to extract and validate relevant metrics from those events; and third, to investigate their suitability as clinical outcome for gait evaluations. 42 subjects including healthy subjects and patients before and after surgical treatments for ankle osteoarthritis performed 50-m walking trials while wearing foot-worn inertial sensors and pressure insoles as a reference system. Several hypotheses were evaluated to detect heel-strike, toe-strike, heel-off, and toe-off based on kinematic features. Detected events were compared with the reference system on 3193 gait cycles and showed good accuracy and precision. Absolute and relative stance periods, namely loading response, foot-flat, and push-off were then estimated, validated, and compared statistically between populations. Besides significant differences observed in stance duration, the analysis revealed differing tendencies with notably a shorter foot-flat in healthy subjects. The result indicated which features in inertial sensors' signals should be preferred for detecting precisely and accurately temporal events against a reference standard. The system is suitable for clinical evaluations and provides temporal analysis of gait beyond the common swing/stance decomposition, through a quantitative estimation of inner-stance phases such as foot-flat.
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Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.
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This paper considers a job search model where the environment is notstationary along the unemployment spell and where jobs do not lastforever. Under this circumstance, reservation wages can be lower thanwithout separations, as in a stationary environment, but they can alsobe initially higher because of the non-stationarity of the model. Moreover,the time-dependence of reservation wages is stronger than with noseparations. The model is estimated structurally using Spanish data forthe period 1985-1996. The main finding is that, although the decrease inreservation wages is the main determinant of the change in the exit ratefrom unemployment for the first four months, later on the only effect comesfrom the job offer arrival rate, given that acceptance probabilities areroughly equal to one.
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We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical {\sc vc} dimension, empirical {\sc vc} entropy, andmargin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.
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OBJECTIVE: To provide an update to the original Surviving Sepsis Campaign clinical management guidelines, "Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock," published in 2004. DESIGN: Modified Delphi method with a consensus conference of 55 international experts, several subsequent meetings of subgroups and key individuals, teleconferences, and electronic-based discussion among subgroups and among the entire committee. This process was conducted independently of any industry funding. METHODS: We used the GRADE system to guide assessment of quality of evidence from high (A) to very low (D) and to determine the strength of recommendations. A strong recommendation indicates that an intervention's desirable effects clearly outweigh its undesirable effects (risk, burden, cost), or clearly do not. Weak recommendations indicate that the tradeoff between desirable and undesirable effects is less clear. The grade of strong or weak is considered of greater clinical importance than a difference in letter level of quality of evidence. In areas without complete agreement, a formal process of resolution was developed and applied. Recommendations are grouped into those directly targeting severe sepsis, recommendations targeting general care of the critically ill patient that are considered high priority in severe sepsis, and pediatric considerations. RESULTS: Key recommendations, listed by category, include: early goal-directed resuscitation of the septic patient during the first 6 hrs after recognition (1C); blood cultures prior to antibiotic therapy (1C); imaging studies performed promptly to confirm potential source of infection (1C); administration of broad-spectrum antibiotic therapy within 1 hr of diagnosis of septic shock (1B) and severe sepsis without septic shock (1D); reassessment of antibiotic therapy with microbiology and clinical data to narrow coverage, when appropriate (1C); a usual 7-10 days of antibiotic therapy guided by clinical response (1D); source control with attention to the balance of risks and benefits of the chosen method (1C); administration of either crystalloid or colloid fluid resuscitation (1B); fluid challenge to restore mean circulating filling pressure (1C); reduction in rate of fluid administration with rising filing pressures and no improvement in tissue perfusion (1D); vasopressor preference for norepinephrine or dopamine to maintain an initial target of mean arterial pressure > or = 65 mm Hg (1C); dobutamine inotropic therapy when cardiac output remains low despite fluid resuscitation and combined inotropic/vasopressor therapy (1C); stress-dose steroid therapy given only in septic shock after blood pressure is identified to be poorly responsive to fluid and vasopressor therapy (2C); recombinant activated protein C in patients with severe sepsis and clinical assessment of high risk for death (2B except 2C for post-operative patients). In the absence of tissue hypoperfusion, coronary artery disease, or acute hemorrhage, target a hemoglobin of 7-9 g/dL (1B); a low tidal volume (1B) and limitation of inspiratory plateau pressure strategy (1C) for acute lung injury (ALI)/acute respiratory distress syndrome (ARDS); application of at least a minimal amount of positive end-expiratory pressure in acute lung injury (1C); head of bed elevation in mechanically ventilated patients unless contraindicated (1B); avoiding routine use of pulmonary artery catheters in ALI/ARDS (1A); to decrease days of mechanical ventilation and ICU length of stay, a conservative fluid strategy for patients with established ALI/ARDS who are not in shock (1C); protocols for weaning and sedation/analgesia (1B); using either intermittent bolus sedation or continuous infusion sedation with daily interruptions or lightening (1B); avoidance of neuromuscular blockers, if at all possible (1B); institution of glycemic control (1B) targeting a blood glucose < 150 mg/dL after initial stabilization ( 2C ); equivalency of continuous veno-veno hemofiltration or intermittent hemodialysis (2B); prophylaxis for deep vein thrombosis (1A); use of stress ulcer prophylaxis to prevent upper GI bleeding using H2 blockers (1A) or proton pump inhibitors (1B); and consideration of limitation of support where appropriate (1D). Recommendations specific to pediatric severe sepsis include: greater use of physical examination therapeutic end points (2C); dopamine as the first drug of choice for hypotension (2C); steroids only in children with suspected or proven adrenal insufficiency (2C); a recommendation against the use of recombinant activated protein C in children (1B). CONCLUSION: There was strong agreement among a large cohort of international experts regarding many level 1 recommendations for the best current care of patients with severe sepsis. Evidenced-based recommendations regarding the acute management of sepsis and septic shock are the first step toward improved outcomes for this important group of critically ill patients.
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Genetic structure of populations of Pissodes castaneus (De Geer) (Coleoptera, Curculionidae) using amplified fragment length polymorphism. The objective of this study was to determine the genetic structure of populations of Pissodes castaneus from different areas and on different species of Pinus using the PCR-AFLP technique. Twenty samples were analyzed, representing 19 populations from Brazil and one from Florence, Italy, which is the region of origin of P. castaneus. The four combinations of primers generated a total of 367 fragments of DNA, and 100% of polymorphic loci, indicating high degree of molecular polymorphism. The dendrogram did not reveal trends for grouping the populations in relation to origin. The low genetic similarity (0.11 between the most distant groups) and genetic distances of 0.13 and 0.44 for 10 out of the 20 samples may indicate several founding events or multiple introductions of heterogeneous strains into Brazil. The allelic fixation index (Fst) was 0.3851, considered high, and the number of migrants (Nm) was 0.3991, indicating low gene flow among populations. The highest genetic distances were between the population from Irani, SC and Cambará do Sul, RS and Bituruna, PR, indicating an independent founding event or a particular allelic fixation in the former location. The high genetic diversity among populations points out that the populations are genetically heterogeneous with a diverse gene pool in the surveyed areas, what makes them to respond differently to control measures.
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We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.
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Two methods were evaluated for scaling a set of semivariograms into a unified function for kriging estimation of field-measured properties. Scaling is performed using sample variances and sills of individual semivariograms as scale factors. Theoretical developments show that kriging weights are independent of the scaling factor which appears simply as a constant multiplying both sides of the kriging equations. The scaling techniques were applied to four sets of semivariograms representing spatial scales of 30 x 30 m to 600 x 900 km. Experimental semivariograms in each set successfully coalesced into a single curve by variances and sills of individual semivariograms. To evaluate the scaling techniques, kriged estimates derived from scaled semivariogram models were compared with those derived from unscaled models. Differences in kriged estimates of the order of 5% were found for the cases in which the scaling technique was not successful in coalescing the individual semivariograms, which also means that the spatial variability of these properties is different. The proposed scaling techniques enhance interpretation of semivariograms when a variety of measurements are made at the same location. They also reduce computational times for kriging estimations because kriging weights only need to be calculated for one variable. Weights remain unchanged for all other variables in the data set whose semivariograms are scaled.
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Understanding the factors that drive geographic variation in life history is an important challenge in evolutionary ecology. Here, we analyze what predicts geographic variation in life-history traits of the common lizard, Zootoca vivipara, which has the globally largest distribution range of all terrestrial reptile species. Variation in body size was predicted by differences in the length of activity season, while we found no effects of environmental temperature per se. Females experiencing relatively short activity season mature at a larger size and remain larger on average than females in populations with relatively long activity seasons. Interpopulation variation in fecundity was largely explained by mean body size of females and reproductive mode, with viviparous populations having larger clutch size than oviparous populations. Finally, body size-fecundity relationship differs between viviparous and oviparous populations, with relatively lower reproductive investment for a given body size in oviparous populations. While the phylogenetic signal was weak overall, the patterns of variation showed spatial effects, perhaps reflecting genetic divergence or geographic variation in additional biotic and abiotic factors. Our findings emphasize that time constraints imposed by the environment rather than ambient temperature play a major role in shaping life histories in the common lizard. This might be attributed to the fact that lizards can attain their preferred body temperature via behavioral thermoregulation across different thermal environments. Length of activity season, defining the maximum time available for lizards to maintain optimal performance, is thus the main environmental factor constraining growth rate and annual rates of mortality. Our results suggest that this factor may partly explain variation in the extent to which different taxa follow ecogeographic rules.
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Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.
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The geochemical compositions of biogenic carbonates are increasingly used for palaeoenvironmental reconstructions. The skeletal delta O-18 temperature relationship is dependent on water salinity, so many recent studies have focused on the Mg/Ca and Sr/Ca ratios because those ratios in water do not change significantly on short time scales. Thus, those elemental ratios are considered to be good palaeotemperature proxies in many biominerals, although their use remains ambiguous in bivalve shells. Here, we present the high-resolution Mg/Ca ratios of two modern species of juvenile and adult oyster shells, Crassostrea gigas and Ostrea edulis. These specimens were grown in controlled conditions for over one year in two different locations. In situ monthly Mn-marking of the shells has been used for day calibration. The daily Mg/Ca.ratios in the shell have been measured with an electron microprobe. The high frequency Mg/Ca variation of all specimens displays good synchronism with lunar cycles, suggesting that tides strongly influence the incorporation of Mg/Ca into the shells. Highly significant correlation coefficients (0.70<R<0.83, p<0.0001) between the Mg/Ca ratios and the seawater temperature are obtained only for juvenile C. gigas samples, while metabolic control of Mg/Ca incorporation and lower shell growth rates preclude the use of the Mg/Ca ratio in adult shells as a palaeothermometer. Data from three juvenile C. gigas shells from the two study sites are selected to establish a relationship: T = 3.77Mg/Ca + 1.88, where T is in degrees C and Mg/Ca in mmol/mol. (c) 2012 Elsevier B.V. All rights reserved.
Estimation of surface roughness in a semiarid region from C-band ERS-1 synthetic aperture radar data
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In this study, we investigated the feasibility of using the C-band European Remote Sensing Satellite (ERS-1) synthetic aperture radar (SAR) data to estimate surface soil roughness in a semiarid rangeland. Radar backscattering coefficients were extracted from a dry and a wet season SAR image and were compared with 47 in situ soil roughness measurements obtained in the rocky soils of the Walnut Gulch Experimental Watershed, southeastern Arizona, USA. Both the dry and the wet season SAR data showed exponential relationships with root mean square (RMS) height measurements. The dry C-band ERS-1 SAR data were strongly correlated (R² = 0.80), while the wet season SAR data have somewhat higher secondary variation (R² = 0.59). This lower correlation was probably provoked by the stronger influence of soil moisture, which may not be negligible in the wet season SAR data. We concluded that the single configuration C-band SAR data is useful to estimate surface roughness of rocky soils in a semiarid rangeland.