Super Resolution of Multispectral Images using ℓ1 Image Models and Interband Correlations

In this paper we propose a novel super-resolution based algorithm for the pansharpening of multispectral images. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images; that is, it imposes smoothness within each band by means of the energy associated with the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation among the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and the quality of the results assessed both qualitatively and quantitatively.     

Robustness of optimal channel reservation using handover prediction in multiservice wireless networks

The aim of our study is to obtain theoretical limits for the gain that can be expected when using handover prediction and to determine the sensitivity of the system performance against different parameters. We apply an average-reward reinforcement learning approach based on afterstates to the design of optimal admission control policies in mobile multimedia cellular networks where predictive information related to the occurrence of future handovers is available. We consider a type of predictor that labels active mobile terminals in the cell neighborhood a fixed amount of time before handovers are predicted to occur, which we call the anticipation time. The admission controller exploits this information to reserve resources efficiently. We show that there exists an optimum value for the anticipation time at which the highest performance gain is obtained. Although the optimum anticipation time depends on system parameters, we find that its value changes very little when the system parameters vary within a reasonable range. We also find that, in terms of system performance, deploying prediction is always advantageous when compared to a system without prediction, even when the system parameters are estimated with poor precision.     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

Signals and Noise in Evoked Brain Potentials

Event-related brain potentials measured with scalp electrodes are always corrupted by unrelated electrical discharges occurring in the brain. These unrelated electrical discharges, generally referred to as noise, have temporal and spectral characteristics similar to evoked potential waveforms, and they greatly increase the difficulty of detecting and estimating the parameters of the evoked potential waveforms themselves. This problem has been analyzed by computing the probability distributions for measured amplitudes and latencies of ERP components measured in the presence of the ongoing EEG. The analytical results have been verified over a wide range of signal-to-noise ratios by computer simulation. Comparisons of theoretical results to measured data indicate that the latency variations found experimentally greatly exceed what would be expected if they were due only to additive noise. It may be concluded, therefore, that the single ERP is not a signal whose components are deterministically related to the stimulus, but is made up of components that shift significantly in both amplitude and latency from one stimulus application to the next. Using the expressions developed in the paper, it is possible to separate the contributions to the variance due to interference from the ongoing EEG and that inherent in the ERP.     

Non-critical saddle-node cycles and robust non-hyperbolic dynamics

We study arcs of diffeomorphisms (f_t) in manifolds of dimension greater than or equal to three bifurcating via non-critical saddle-node cycles. We construct an open set j of such arcs for which, after the bifurcation, every diffeomorphism j does not satisfy Axiom A. We also exhibit an open subset j' of j such that after the bifurcation every diffeomorphism has a partially hyperbolic set of saddle-type which is persistent, locally maximal and transitive. As a consequence, we get a submanifold of codimension-1 of diffeomorphisms with a saddle-node that locally separates the set of Morse-Smale systems from the diffeomorphisms with a partially hyperbolic transitive set.     

The influence of the drawing parameters and temperature rise on the prediction of chevron crack formation in wire drawing

The objective of the present work is to predict the formation of chevron crack in copper wire drawing process. The first part of this paper is to determine the chevron crack formation initiated by a central burst inside the wire material using experimental tests. These results are compared with results from a series of numerical simulations using the Cockcroft?CLatham fracture criterion. The second part of this work concerns the determination of a curve that divides the chevron and safe zones for a better wire drawing process. The conditions of central burst defects formation along the wire axis depend on drawing parameters and friction coefficient between the die and the wire. The friction coefficient is defined as a linear function of temperature rise which is measured close to the wire-die interface. The obtained results show that the friction coefficient depending on temperature rise during wire drawing has an impact on the damage of copper wire.     

Diosgenin quantification,characterisation and chemical composition in a tuber collection of Dioscorea spp. in the state of Jalisco,Mexico

Dioscorea spp. tubers are known commonly as camote de cerro to the state of Jalisco, México. Besides its use as food, it contains diosgenin, a raw material used widely for synthesising steroid hormones. The purpose of the present research was to determine diosgenin contents by gas chromatography‐mass spectrometry (GC‐MS), as well as physical and chemical characteristics of sixty Dioscorea spp. accessions cultivated in mesh shade coming from eleven localities in the state of Jalisco. Extraction protocol for diosgenin was maceration combined with ethanol 80%. Significant statistical differences for diosgenin content were found between accessions, finding levels between 0.02 and 0.16 mg kg^?1 in dry basis. Length, weight tuber, proportion pulp/skin, percentage of pulp and percentage of skin showed significant differences. Chemical composition based in fresh weight presented in moisture percentage a range of 71.93–83.26%, crude protein 1.42–1.74%, ashes 0.80–1.16%, lipid 0.13–0.17%, crude fibre 3.80–4.02% and total carbohydrates 13.97–25.44%. Results show that tubers from Jalisco can be an important source of nutrients for consumers.     

In vitro intestinal absorption of amino acid mixtures extracted from codfish (Gadus morhua L.) salting wastewater

This study reports on the intestinal permeability of salt‐containing mixtures of amino acids extracted from codfish salting wastewater. Permeability was evaluated in vitro using the Caco‐2 cell line model; cell integrity during exposure to mixtures of amino acids was estimated by measuring the transepithelial electrical resistance (TEER). The effect of salt (NaCl) on the permeability and on the intestinal cell's integrity was also examined. Permeation rate (i.e. transport) was ≥95% for all amino acids except for creatine, for which it was 6%. Values for apparent permeability coefficients, P_app > 10^?5 cm s^?1, for mixture with isotonic concentration of NaCl suggest that amino acids are very likely to be absorbed in humans. Mixture with a hypertonic level of NaCl exerts a cytotoxic effect in intestinal cells resulting in a loss of epithelium integrity. Results show that isotonic mixture of amino acids extracted from codfish salting wastewater could be used in food, feed, cosmetic and pharmaceutical formulations. These applications could contribute to the fish industry sustainability.     

Hyperbaric storage at and above room temperature of a highly perishable food

Hyperbaric storage at naturally variable room temperature (RT) conditions (18–21 °C) and above (30 °C) was evaluated as a possible new food preservation method, regardless of temperature. Preservation of watermelon juice (used as a case study of a highly perishable food) at RT and 5 °C at atmospheric pressure was compared to preservation under 100 MPa at RT. After 8 h of hyperbaric storage at 100 MPa, the initial microbial loads of the watermelon juice were reduced by 1 log unit for total aerobic mesophiles, and 1–2 log units for Enterobacteriaceae and yeasts and moulds, to levels of about 3 log units for the former and below the detection limit for the latter, and remained thereafter unchanged up to 60 h. Similar results were obtained at 30 °C at 100 MPa after 8 h. At atmospheric pressure at RT (24 h) and 30 °C (8 h), microbial levels were already above quantification limits and unacceptable for consumption. Furthermore, pressure attenuated the increase in titratable acidity verified at atmospheric pressure, but caused higher colour changes, especially a higher lightness and a lower browning degree. Post-hyperbaric storage at 5 °C revealed an extended shelf life, as an additional benefit of hyperbaric storage. These results show that hyperbaric storage is a very promising food preservation methodology.     

Use of Response Surface Methodology to Investigate the Effectiveness of Commercial Enzymes on Buckwheat Malt for Brewing Purposes

The influence of two factors, total concentration and fraction of three pairs of commercial enzymes, which showed statistical significance (Biocellulase W with Hitempase 2XL, Biocellulase W with Amylo 300 and Amylo 300 with Hitempase 2XL), were studied for their overall effect on buckwheat wort quality using response surface methodology (RSM). This study revealed that the addition of increasing levels of Hitempase 2XL to the buckwheat mash increased colour, extract levels, wort filtration, fermentability and total fermentable extract (TFE), along with decreasing viscosity values. Results also determined a high level of fermentability when an enzyme combination of 30% Biocellulase and 70% Hitempase was added to the mash. The addition of increasing levels of Amylo 300 to buckwheat mashes resulted in increases in fermentability and total fermentable extract (TFE), along with increases in total soluble nitrogen (TSN), free amino nitrogen (FAN) and Kolbach index (KI). With regard to the proposed optimal regime, although no synergistic effect was found when the three enzymes were used together, the optimum conditions for the production of buckwheat wort with lowest viscosity, highest extract and optimal fermentability were achieved using a joint model. Overall, the findings of this study demonstrate the feasibility of producing wort suitable for the brewing of gluten‐free beer from 100% malted buckwheat with careful optimisation of enzyme types and dosage levels.