991 resultados para Prediction of scholastic success.


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Fruit damage during harvesting and handling is a standing problem, particularly for susceptible fruits like peaches and apricots. The resulting mechanical damage is a combination of fruit properties and damage inflicting effects due to procedures and to the equipment. Nine packing lines in the region of Murcia (SE Spain) have been tested with the aid of two different-size electronic fruits IS-100. Probabilities of impacts above three preset thresholds (50 g's, 100 g's and 150 g's) were calculated for each transfer point. Interaction fruit-packing line tests have been also performed in order to study the real incidence of packing lines on natural produce: apricots (1 variety), peaches (3 v.), lemons (1 v.) and oranges (3 v.). Bruises of handled and not handled samples of fruits were compared.

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Fuel cycles are designed with the aim of obtaining the highest amount of energy possible. Since higher burnup values are reached, it is necessary to improve our disposal designs, traditionally based on the conservative assumption that they contain fresh fuel. The criticality calculations involved must consider burnup by making the most of the experimental and computational capabilities developed, respectively, to measure and predict the isotopic content of the spent nuclear fuel. These high burnup scenarios encourage a review of the computational tools to find out possible weaknesses in the nuclear data libraries, in the methodologies applied and their applicability range. Experimental measurements of the spent nuclear fuel provide the perfect framework to benchmark the most well-known and established codes, both in the industry and academic research activity. For the present paper, SCALE 6.0/TRITON and MONTEBURNS 2.0 have been chosen to follow the isotopic content of four samples irradiated in the Spanish Vandellós-II pressurized water reactor up to burnup values ranging from 40 GWd/MTU to 75 GWd/MTU. By comparison with the experimental data reported for these samples, we can probe the applicability of these codes to deal with high burnup problems. We have developed new computational tools within MONTENBURNS 2.0. They make possible to handle an irradiation history that includes geometrical and positional changes of the samples within the reactor core. This paper describes the irradiation scenario against which the mentioned codes and our capabilities are to be benchmarked.

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During the last two decades the topic of human induced vibration has attracted a lot of attention among civil engineering practitioners and academics alike. Usually this type of problem may be encountered in pedestrian footbridges or floors of paperless offices. Slender designs are becoming increasingly popular, and as a consequence, the importance of paying attention to vibration serviceability also increases. This paper resumes the results obtained from measurements taken at different points of an aluminium catwalk which is 6 m in length by 0.6 m in width. Measurements were carried out when subjecting the structure to different actions:1)Static test: a steel cylinder of 35 kg was placed in the middle of the catwalk; 2)Dynamic test: this test consists of exciting the structure with singles impulses; 3)Dynamic test: people walking on the catwalk. Identification of the mechanical properties of the structure is an achievement of the paper. Indirect methods were used to estimate properties including the support stiffness, the beam bending stiffness, the mass of the structure (using Rayleigh method and iterative matrix method), the natural frequency (using the time domain and frequency domain analysis) and the damping ratio (by calculating the logarithmic decrement). Experimental results and numerical predictions for the response of an aluminium catwalk subjected to walking loads have been compared. The damping of this light weight structure depends on the amplitude of vibration which complicates the tuning of a structural model. In the light of the results obtained it seems that the used walking load model is not appropriate as the predicted transient vibration values (TTVs) are much higher than the measured ones.

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We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in large state spaces. We provide a mean-square-error performance analysis under constant step-sizes. The gain of cooperation in the form of more stability and less bias and variance in the prediction error, is illustrated in the context of a classical model. We show that the improvement in performance is especially significant when the behavior policy of the agents is different from the target policy under evaluation.

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Outline: • Introduction • Numerical model SHOCKLAS© • Single LSP pulses • Overlapped LSP pulses • Discussion and Outlook

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Crowd induced dynamic loading in large structures, such as gymnasiums or stadium, is usually modelled as a series of harmonic loads which are defined in terms of their Fourier coefficients. Different values of these coefficients that were obtained from full scale measurements can be found in codes. Recently, an alternative has been proposed, based on random generation of load time histories that take into account phase lag among individuals inside the crowd. This paper presents the testing done on a structure designed to be a gymnasium. Two series of dynamic test were performed on the gym slab. For the first test an electrodynamic shaker was placed at several locations and during the second one people located inside a marked area bounced and jumped guided by different metronome rates. A finite element model (FEM) is presented and a comparison of numerically predicted and experimentally observed vibration modes and frequencies has been used to assess its validity. The second group of measurements will be compared with predictions made using the FEM model and three alternatives for crowd induced load modelling.

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To develop a Support Vector Machine (SVM) algorithm as a predictive tool for diagnostic outcome in patients with FE-EOP, based on clinical and biomedical data at the emergence of the illness.

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A method is presented for computing the average solution of problems that are too complicated for adequate resolution, but where information about the statistics of the solution is available. The method involves computing average derivatives by interpolation based on linear regression, and an updating of a measure constrained by the available crude information. Examples are given.

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Operon structure is an important organization feature of bacterial genomes. Many sets of genes occur in the same order on multiple genomes; these conserved gene groupings represent candidate operons. This study describes a computational method to estimate the likelihood that such conserved gene sets form operons. The method was used to analyze 34 bacterial and archaeal genomes, and yielded more than 7600 pairs of genes that are highly likely (P ≥ 0.98) to belong to the same operon. The sensitivity of our method is 30–50% for the Escherichia coli genome. The predicted gene pairs are available from our World Wide Web site http://www.tigr.org/tigr-scripts/operons/operons.cgi.

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Single-stranded regions in RNA secondary structure are important for RNA–RNA and RNA–protein interactions. We present a probability profile approach for the prediction of these regions based on a statistical algorithm for sampling RNA secondary structures. For the prediction of phylogenetically-determined single-stranded regions in secondary structures of representative RNA sequences, the probability profile offers substantial improvement over the minimum free energy structure. In designing antisense oligonucleotides, a practical problem is how to select a secondary structure for the target mRNA from the optimal structure(s) and many suboptimal structures with similar free energies. By summarizing the information from a statistical sample of probable secondary structures in a single plot, the probability profile not only presents a solution to this dilemma, but also reveals ‘well-determined’ single-stranded regions through the assignment of probabilities as measures of confidence in predictions. In antisense application to the rabbit β-globin mRNA, a significant correlation between hybridization potential predicted by the probability profile and the degree of inhibition of in vitro translation suggests that the probability profile approach is valuable for the identification of effective antisense target sites. Coupling computational design with DNA–RNA array technique provides a rational, efficient framework for antisense oligonucleotide screening. This framework has the potential for high-throughput applications to functional genomics and drug target validation.

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A method for the quantitative estimation of instability with respect to deamidation of the asparaginyl (Asn) residues in proteins is described. The procedure involves the observation of several simple aspects of the three-dimensional environment of each Asn residue in the protein and a calculation that includes these observations, the primary amino acid residue sequence, and the previously reported complete set of sequence-dependent rates of deamidation for Asn pentapeptides. This method is demonstrated and evaluated for 23 proteins in which 31 unstable and 167 stable Asn residues have been reported and for 7 unstable and 63 stable Asn residues that have been reported in 61 human hemoglobin variants. The relative importance of primary structure and three-dimensional structure in Asn deamidation is estimated.