889 resultados para Input vector


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A comment about the article “Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling” writen by L. Loosvelt and co-authors. The present comment is centered in three specific points. The first one is related to the fact that the authors avoid the use of ilr-coordinates. The second one refers to some generalization of sensitivity analysis when input parameters are compositional. The third tries to show that the role of the Dirichlet distribution in the sensitivity analysis is irrelevant

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Purpose: We previously demonstrated efficient retinal rescue of RPE65 mouse models (Rpe65-/- (Bemelmans et al, 2006) and Rpe65R91W/R91W mice) using a HIV1-derived lentiviral vector encoding for the mouse RPE65 cDNA. In order to optimize a lentiviral vector as an alternative tool for RPE65-derived Leber Congenital Amaurosis clinical trials, we evaluated the efficiency of an integration-deficient lentiviral vector (IDLV) encoding the human RPE65 cDNA to restore retinal function in the Rpe65R91W/R91W mice. Methods: An HIV-1-derived lentiviral vector expressing either the hrGFPII or the human Rpe65 cDNA under the control of a 0.8 kb fragment of the human Rpe65 promoter (R0.8) was produced by transient transfection of 293T cells. A LQ-integrase mutant was used to generate the IDLV vectors. IDLV-R0.8-hRPE65 or hrGFPII were injected subretinally into 1 month-old Rpe65R91W/R91W mice. Functional rescue was assessed by ERG (1 and 3 months post-injection) and cone survival by immunohistology. Results: An increased light sensitivity was detected by scotopic ERG in animals injected with IDLV-R0.8-hRPE65 compared to hrGFPII-treated animals or untreated mice. However the improvement was delayed compared to integration-proficient LV and observed at 3 months but not 1 month post-injection. Immunolabelling of cone markers showed an increased number of cones in the transduced area compared to control groups. Conclusions: The IDLV-R0.8-hRPE65 vectors allow retinal improvement in the Rpe65R91W/R91W mice. Both rod function and cone survival were demonstrated even if there is a delay in the rescue as assessed by scotopic ERG. Integration-deficient vectors minimize insertional mutagenesis and thus are safer candidates for human application. Further experiments using large animals are now needed to validate correct gene transfer and expression of the RPE65 gene as well as tolerance of the vector after subretinal injection before envisaging a clinical trial application.

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This work investigates novel alternative means of interaction in a virtual environment (VE).We analyze whether humans can remap established body functions to learn to interact with digital information in an environment that is cross-sensory by nature and uses vocal utterances in order to influence (abstract) virtual objects. We thus establish a correlation among learning, control of the interface, and the perceived sense of presence in the VE. The application enables intuitive interaction by mapping actions (the prosodic aspects of the human voice) to a certain response (i.e., visualization). A series of single-user and multiuser studies shows that users can gain control of the intuitive interface and learn to adapt to new and previously unseen tasks in VEs. Despite the abstract nature of the presented environment, presence scores were generally very high.

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This paper presents a model of the Stokes emission vector from the ocean surface. The ocean surface is described as an ensemble of facets with Cox and Munk's (1954) Gram-Charlier slope distribution. The study discusses the impact of different up-wind and cross-wind rms slopes, skewness, peakedness, foam cover models and atmospheric effects on the azimuthal variation of the Stokes vector, as well as the limitations of the model. Simulation results compare favorably, both in mean value and azimuthal dependence, with SSM/I data at 53° incidence angle and with JPL's WINDRAD measurements at incidence angles from 30° to 65°, and at wind speeds from 2.5 to 11 m/s.

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What determines which inputs are initially considered and eventually adopted in the productionof new or improved goods? Why are some inputs much more prominent than others? We modelthe evolution of input linkages as a process where new producers first search for potentially usefulinputs and then decide which ones to adopt. A new product initially draws a set of 'essentialsuppliers'. The search stage is then confined to the network neighborhood of the latter, i.e., to theinputs used by the essential suppliers. The adoption decision is driven by a tradeoff between thebenefits accruing from input variety and the costs of input adoption. This has important implicationsfor the number of forward linkages that a product (input variety) develops over time. Inputdiffusion is fostered by network centrality ? an input that is initially represented in many networkneighborhoods is subsequently more likely to be adopted. This mechanism also delivers a powerlaw distribution of forward linkages. Our predictions continue to hold when varieties are aggregatedinto sectors. We can thus test them, using detailed sectoral US input-output tables. We showthat initial network proximity of a sector in 1967 significantly increases the likelihood of adoptionthroughout the subsequent four decades. The same is true for rapid productivity growth in aninput-producing sector. Our empirical results highlight two conditions for new products to becomecentral nodes: initial network proximity to prospective adopters, and technological progress thatreduces their relative price. Semiconductors met both conditions.

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The decision-making process regarding drug dose, regularly used in everyday medical practice, is critical to patients' health and recovery. It is a challenging process, especially for a drug with narrow therapeutic ranges, in which a medical doctor decides the quantity (dose amount) and frequency (dose interval) on the basis of a set of available patient features and doctor's clinical experience (a priori adaptation). Computer support in drug dose administration makes the prescription procedure faster, more accurate, objective, and less expensive, with a tendency to reduce the number of invasive procedures. This paper presents an advanced integrated Drug Administration Decision Support System (DADSS) to help clinicians/patients with the dose computing. Based on a support vector machine (SVM) algorithm, enhanced with the random sample consensus technique, this system is able to predict the drug concentration values and computes the ideal dose amount and dose interval for a new patient. With an extension to combine the SVM method and the explicit analytical model, the advanced integrated DADSS system is able to compute drug concentration-to-time curves for a patient under different conditions. A feedback loop is enabled to update the curve with a new measured concentration value to make it more personalized (a posteriori adaptation).

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This work investigates novel alternative means of interaction in a virtual environment (VE).We analyze whether humans can remap established body functions to learn to interact with digital information in an environment that is cross-sensory by nature and uses vocal utterances in order to influence (abstract) virtual objects. We thus establish a correlation among learning, control of the interface, and the perceived sense of presence in the VE. The application enables intuitive interaction by mapping actions (the prosodic aspects of the human voice) to a certain response (i.e., visualization). A series of single-user and multiuser studies shows that users can gain control of the intuitive interface and learn to adapt to new and previously unseen tasks in VEs. Despite the abstract nature of the presented environment, presence scores were generally very high.

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Yeasts are responsible for several traits in fermented beverages, including wine and beer, and their genetic manipulation is often necessary to improve the quality of the fermentation product. Improvement of wild-type strains of Saccharomyces cerevisiae and Saccharomyces pastorianus is difficult due to their homothallic character and variable ploidy level. Homothallism is determined by the HO gene in S. cerevisiae and the Sc-HO gene in S. pastorianus. In this work, we describe the construction of an HO disruption vector (pDHO) containing an HO disruption cassette and discuss its use in generating heterothallic yeast strains from homothallic Saccharomyces species.

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Parasite population structure is often thought to be largely shaped by that of its host. In the case of a parasite with a complex life cycle, two host species, each with their own patterns of demography and migration, spread the parasite. However, the population structure of the parasite is predicted to resemble only that of the most vagile host species. In this study, we tested this prediction in the context of a vector-transmitted parasite. We sampled the haemosporidian parasite Polychromophilus melanipherus across its European range, together with its bat fly vector Nycteribia schmidlii and its host, the bent-winged bat Miniopterus schreibersii. Based on microsatellite analyses, the wingless vector, and not the bat host, was identified as the least structured population and should therefore be considered the most vagile host. Genetic distance matrices were compared for all three species based on a mitochondrial DNA fragment. Both host and vector populations followed an isolation-by-distance pattern across the Mediterranean, but not the parasite. Mantel tests found no correlation between the parasite and either the host or vector populations. We therefore found no support for our hypothesis; the parasite population structure matched neither vector nor host. Instead, we propose a model where the parasite's gene flow is represented by the added effects of host and vector dispersal patterns.

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Pulsewidth-modulated (PWM) rectifier technology is increasingly used in industrial applications like variable-speed motor drives, since it offers several desired features such as sinusoidal input currents, controllable power factor, bidirectional power flow and high quality DC output voltage. To achieve these features,however, an effective control system with fast and accurate current and DC voltage responses is required. From various control strategies proposed to meet these control objectives, in most cases the commonly known principle of the synchronous-frame current vector control along with some space-vector PWM scheme have been applied. Recently, however, new control approaches analogous to the well-established direct torque control (DTC) method for electrical machines have also emerged to implement a high-performance PWM rectifier. In this thesis the concepts of classical synchronous-frame current control and DTC-based PWM rectifier control are combined and a new converter-flux-based current control (CFCC) scheme is introduced. To achieve sufficient dynamic performance and to ensure a stable operation, the proposed control system is thoroughly analysed and simple rules for the controller design are suggested. Special attention is paid to the estimationof the converter flux, which is the key element of converter-flux-based control. Discrete-time implementation is also discussed. Line-voltage-sensorless reactive reactive power control methods for the L- and LCL-type line filters are presented. For the L-filter an open-loop control law for the d-axis current referenceis proposed. In the case of the LCL-filter the combined open-loop control and feedback control is proposed. The influence of the erroneous filter parameter estimates on the accuracy of the developed control schemes is also discussed. A newzero vector selection rule for suppressing the zero-sequence current in parallel-connected PWM rectifiers is proposed. With this method a truly standalone and independent control of the converter units is allowed and traditional transformer isolation and synchronised-control-based solutions are avoided. The implementation requires only one additional current sensor. The proposed schemes are evaluated by the simulations and laboratory experiments. A satisfactory performance and good agreement between the theory and practice are demonstrated.

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En este trabajo se pretende ofrecer una visión del sector Agroalimentario (SAA) catalán, y muy especialmente, de cual es su situación comparativa dentro del SAA español. Analizando por medio de las tablas input-output aquellas ramas del SAA que actúan como motor en cada una de las economías estudiadas, al mismo tiempo que se detectan las analogías o divergencias entre las dos realidades, la autónoma y la nacional. Los indicadores utilizados para el estudio de la tabla input-output son: Chenery-Watanabe, Rasmussen, Backward linkages, Forward linkdages, multiplicador renta y multiplicador de las importaciones.

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This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

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In this present work, we are proposing a characteristics reduction system for a facial biometric identification system, using transformed domains such as discrete cosine transformed (DCT) and discrete wavelets transformed (DWT) as parameterization; and Support Vector Machines (SVM) and Neural Network (NN) as classifiers. The size reduction has been done with Principal Component Analysis (PCA) and with Independent Component Analysis (ICA). This system presents a similar success results for both DWT-SVM system and DWT-PCA-SVM system, about 98%. The computational load is improved on training mode due to the decreasing of input’s size and less complexity of the classifier.