941 resultados para Vector analysis


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This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to allhadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of s = 7 TeV and correspond to an integrated luminosity of 4.6 fb−1. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum pT > 320 GeV and pseudorapidity |η| < 1.9, is measured to be σ + = ± W Z 8.5 1.7 pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques.

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Four Staphylococcus aureus-Escherichia coli shuttle vectors were constructed for gene expression and production of tagged fusion proteins. Vectors pBUS1-HC and pTSSCm have no promoter upstream of the multiple cloning site (MCS), and this allows study of genes under the control of their native promoters, and pBUS1-Pcap-HC and pTSSCm-Pcap contain the strong constitutive promoter of S. aureus type 1 capsule gene 1A (Pcap) upstream of a novel MCS harboring codons for the peptide tag Arg-Gly-Ser-hexa-His (rgs-his6). All plasmids contained the backbone derived from pBUS1, including the E. coli origin ColE1, five copies of terminator rrnB T1, and tetracycline resistance marker tet(L) for S. aureus and E. coli. The minimum pAMα1 replicon from pBUS1 was improved through either complementation with the single-strand origin oriL from pUB110 (pBUS1-HC and pBUS1-Pcap-HC) or substitution with a pT181-family replicon (pTSSCm and pTSSCm-Pcap). The new constructs displayed increased plasmid yield and segregational stability in S. aureus. Furthermore, pBUS1-Pcap-HC and pTSSCm-Pcap offer the potential to generate C-terminal RGS-His6 translational fusions of cloned genes using simple molecular manipulation. BcgI-induced DNA excision followed by religation converts the TGA stop codon of the MCS into a TGC codon and links the rgs-his6 codons to the 3' end of the target gene. The generation of the rgs-his6 codon-fusion, gene expression, and protein purification were demonstrated in both S. aureus and E. coli using the macrolide-lincosamide-streptogramin B resistance gene erm(44) inserted downstream of Pcap. The new His tag expression system represents a helpful tool for the direct analysis of target gene function in staphylococcal cells.

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Today, there is little knowledge on the attitude state of decommissioned intact objects in Earth orbit. Observational means have advanced in the past years, but are still limited with respect to an accurate estimate of motion vector orientations and magnitude. Especially for the preparation of Active Debris Removal (ADR) missions as planned by ESA’s Clean Space initiative or contingency scenarios for ESA spacecraft like ENVISAT, such knowledge is needed. ESA's “Debris Attitude Motion Measurements and Modelling” project (ESA Contract No. 40000112447), led by the Astronomical Institute of the University of Bern (AIUB), addresses this problem. The goal of the project is to achieve a good understanding of the attitude evolution and the considerable internal and external effects which occur. To characterize the attitude state of selected targets in LEO and GTO, multiple observation methods are combined. Optical observations are carried out by AIUB, Satellite Laser Ranging (SLR) is performed by the Space Research Institute of the Austrian Academy of Sciences (IWF) and radar measurements and signal level determination are provided by the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR). The In-Orbit Tumbling Analysis tool (ιOTA) is a prototype software, currently in development by Hyperschall Technologie Göttingen GmbH (HTG) within the framework of the project. ιOTA will be a highly modular software tool to perform short-(days), medium-(months) and long-term (years) propagation of the orbit and attitude motion (six degrees-of-freedom) of spacecraft in Earth orbit. The simulation takes into account all relevant acting forces and torques, including aerodynamic drag, solar radiation pressure, gravitational influences of Earth, Sun and Moon, eddy current damping, impulse and momentum transfer from space debris or micro meteoroid impact, as well as the optional definition of particular spacecraft specific influences like tank sloshing, reaction wheel behaviour, magnetic torquer activity and thruster firing. The purpose of ιOTA is to provide high accuracy short-term simulations to support observers and potential ADR missions, as well as medium-and long-term simulations to study the significance of the particular internal and external influences on the attitude, especially damping factors and momentum transfer. The simulation will also enable the investigation of the altitude dependency of the particular external influences. ιOTA's post-processing modules will generate synthetic measurements for observers and for software validation. The validation of the software will be done by cross-calibration with observations and measurements acquired by the project partners.

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We analyzed observations of interstellar neutral helium (ISN He) obtained from the Interstellar Boundary Explorer (IBEX) satellite during its first six years of operation. We used a refined version of the ISN He simulation model, presented in the companion paper by Sokol et al. (2015b), along with a sophisticated data correlation and uncertainty system and parameter fitting method, described in the companion paper by Swaczyna et al. We analyzed the entire data set together and the yearly subsets, and found the temperature and velocity vector of ISN He in front of the heliosphere. As seen in the previous studies, the allowable parameters are highly correlated and form a four-dimensional tube in the parameter space. The inflow longitudes obtained from the yearly data subsets show a spread of similar to 6 degrees, with the other parameters varying accordingly along the parameter tube, and the minimum chi(2) value is larger than expected. We found, however, that the Mach number of the ISN He flow shows very little scatter and is thus very tightly constrained. It is in excellent agreement with the original analysis of ISN He observations from IBEX and recent reanalyses of observations from Ulysses. We identify a possible inaccuracy in the Warm Breeze parameters as the likely cause of the scatter in the ISN He parameters obtained from the yearly subsets, and we suppose that another component may exist in the signal or a process that is not accounted for in the current physical model of ISN He in front of the heliosphere. From our analysis, the inflow velocity vector, temperature, and Mach number of the flow are equal to lambda(ISNHe) = 255 degrees.8 +/- 0 degrees.5, beta(ISNHe) = 5 degrees.16 +/- 0 degrees.10, T-ISNHe = 7440 +/- 260 K, nu(SNHe) = 25.8 +/- 0.4 km s(-1), and M-ISNHe = 5.079 +/- 0.028, with uncertainties strongly correlated along the parameter tube.

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A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

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West Nile Virus (WNV) is an arboviral disease that has affected hundreds of residents in Harris County, Texas since its introduction in 2002. Persistent infection, lingering sequelae and other long-term symptoms of patients reaffirm the need for prevention of this important vector-borne disease. This study aimed to determine if living within 400m of a water body increases one’s odds of infection with WNV. Additionally, we wanted to determine if one’s proximity to a particular water type or water body source increased one’s odds of infection with WNV.^ 145 cases’ addresses were abstracted from the initial interview and consent records from a cohort of patients (Epidemiology of Arboviral Encephalitis in Houston study, HSC-SPH-03-039). After applying inclusion criteria, 140 cases were identified for analysis. 140 controls were selected for analysis using a population proportionate to size model and US Census Bureau data. MapMarker USA v14 was used to geocode the cases’ addresses. Both cases’ and controls’ coordinates were uploaded onto a Harris County water shapefile in MapInfo Professional v9.5.1. Distance in meters to the closest water source, closest water source type, and closest water source name were recorded.^ Analysis of Variance (p=0.329, R2 = 0.0034) indicated no association between water body distance and risk of WNV disease. Living near a creek (x2 = 11.79, p < 0.001), or the combined group of creek and gully (x 2 = 14.02, p < 0.001) were found to be strongly associated with infection of WNV. Living near Cypress Creek and its feeders (x2 = 15.2, p < 0.001) was found to be strongly associated with WNV infection. We found that creek and gully habitats, particularly Cypress Creek, were preferential for the local disease transmitting Culex quinquefasciatus and reservoir avian population.^

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Traditional comparison of standardized mortality ratios (SMRs) can be misleading if the age-specific mortality ratios are not homogeneous. For this reason, a regression model has been developed which incorporates the mortality ratio as a function of age. This model is then applied to mortality data from an occupational cohort study. The nature of the occupational data necessitates the investigation of mortality ratios which increase with age. These occupational data are used primarily to illustrate and develop the statistical methodology.^ The age-specific mortality ratio (MR) for the covariates of interest can be written as MR(,ij...m) = ((mu)(,ij...m)/(theta)(,ij...m)) = r(.)exp (Z('')(,ij...m)(beta)) where (mu)(,ij...m) and (theta)(,ij...m) denote the force of mortality in the study and chosen standard populations in the ij...m('th) stratum, respectively, r is the intercept, Z(,ij...m) is the vector of covariables associated with the i('th) age interval, and (beta) is a vector of regression coefficients associated with these covariables. A Newton-Raphson iterative procedure has been used for determining the maximum likelihood estimates of the regression coefficients.^ This model provides a statistical method for a logical and easily interpretable explanation of an occupational cohort mortality experience. Since it gives a reasonable fit to the mortality data, it can also be concluded that the model is fairly realistic. The traditional statistical method for the analysis of occupational cohort mortality data is to present a summary index such as the SMR under the assumption of constant (homogeneous) age-specific mortality ratios. Since the mortality ratios for occupational groups usually increase with age, the homogeneity assumption of the age-specific mortality ratios is often untenable. The traditional method of comparing SMRs under the homogeneity assumption is a special case of this model, without age as a covariate.^ This model also provides a statistical technique to evaluate the relative risk between two SMRs or a dose-response relationship among several SMRs. The model presented has application in the medical, demographic and epidemiologic areas. The methods developed in this thesis are suitable for future analyses of mortality or morbidity data when the age-specific mortality/morbidity experience is a function of age or when there is an interaction effect between confounding variables needs to be evaluated. ^

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p53 plays a role in cell cycle arrest and apoptosis. p53 has also been shown to be involved in DNA replication. To study the effect of p53 on DNA replication, we utilized a SV40 based shuttle vector system. The pZ402 shuttle vector, was constructed with a mutated T-antigen unable to interact with p53 but able to support replication of the shuttle vector. When a transcriptional activation domain p53 mutant was tested for its ability to inhibit DNA replication no inhibition was observed. Competition assays with the DNA binding domain of p53 was also able to block the inhibition of DNA replication by p53 suggesting that p53 can inhibit DNA replication through the transcriptional activation of a target gene. One likely target gene, p21$\sp{\rm cip/waf}$ was tested to determine whether p53 inhibited DNA replication by transcriptionally activating p21$\sp{\rm cip/waf}$. Two independent approaches utilizing p21$\sp{\rm cip/waf}$ null cells or the expression of an anti-sense p21$\sp{\rm cip/waf}$ expression vector were utilized. p53 was able to inhibit pZ402 replication independently of p21$\sp{\rm cip/waf}$. p53 was also able to inhibit DNA replication independent of the p53 target genes Gadd45 and the replication processivity factor PCNA. The inhibition of DNA replication by p53 was also independent of direct DNA binding to a consensus site on the replicating plasmid. p53 mutants can be classified into two categories: conformational and DNA contact mutants. The two types of p53 mutants were tested for their effects on DNA replication. While all conformational mutants were unable to inhibit DNA replication three out of three DNA contact mutants tested were able to inhibit DNA replication. The work here studies the effect wild-type and mutant p53 has on DNA replication and demonstrated a possible mechanism by which wild-type p53 could inhibit DNA replication through the transcriptional activation of a target gene. ^

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This research investigates the spatial market integration of the Chilean wheat market in relation with its most representative international markets by using a vector error correction model (VECM) and how a price support policy, as a price band, affect it. The international market was characterized by two relevant wheat prices: PAN from Argentina and Hard Red Winter from the United States. The spatial market integration level, expressed in the error correction term (ECT), allowed concluding that there is a high integration degree among these markets with a variable influence of the price band mechanism mainly related with its estimation methodology. Moreover, this paper showed that Chile can be seen as price taker as long as the speed of its adjustment to international shocks, being these reactions faster than in the United States and Argentina. Finally, the results validated the "Law of the One Price", which assumes price equalization across all local markets in the long run.

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This paper empirically analyzes India’s money demand function during the period of 1980 to 2007 using monthly data and the period of 1976 to 2007 using annual data. Cointegration test results indicated that when money supply is represented by M1 and M2, a cointegrating vector is detected among real money balances, interest rates, and output. In contrast, it was found that when money supply is represented by M3, there is no long-run equilibrium relationship in the money demand function. Moreover, when the money demand function was estimated using dynamic OLS, the sign onditions of the coefficients of output and interest rates were found to be consistent with theoretical rationale, and statistical significance was confirmed when money supply was represented by either M1 or M2. Consequently, though India’s central bank presently uses M3 as an indicator of future price movements, it is thought appropriate to focus on M1 or M2, rather than M3, in managing monetary policy.

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This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

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The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

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This paper outlines an automatic computervision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the SupportVectorMachines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the SupportVectorMachines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

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In this paper, we use ARIMA modelling to estimate a set of characteristics of a short-term indicator (for example, the index of industrial production), as trends, seasonal variations, cyclical oscillations, unpredictability, deterministic effects (as a strike), etc. Thus for each sector and product (more than 1000), we construct a vector of values corresponding to the above-mentioned characteristics, that can be used for data editing.

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Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.