Simulation of atmospheric phenomena

This paper presents a physically based simulation of atmospheric phenomena. It takes into account the physics of non-homogeneous media in which the index of refraction varies continuously, creating curved light paths. As opposed to previous research on this area, we solve the physically based differential equation that describes the trajectory of light. We develop an accurate expression of the index of refraction in the atmosphere as a function of wavelength, based on real measured data. We also describe our atmosphere profile manager, which lets us mimic the initial conditions of real-world scenes for our simulations. The method is validated both visually (by comparing the images with the real pictures) and numerically (with the extensive literature from other areas of research such as optics or meteorology). The phenomena simulated include the inferior and superior mirages, the Fata Morgana, the Novaya–Zemlya, the Viking's end of the world, the distortions caused by heat waves and the green flash.     

A framework to visualize equivalences between computational models of regular languages

We discuss how to increase and simplify the understanding of the equivalence relations between machine models and/or language representations of formal languages by means of the animation tool SAGEMoLiC. Our new educational tool permits the simulation of the execution of models of computation, as many other animation systems do, but its philosophy goes further than these of the usual systems since it allows for a true visualization of the key notions involved in the formal proofs of these equivalences. In contrast with the proposal of previous systems, our approach to visualize equivalence theorems is not a simple “step by step animation” of specific conversion algorithms between computational models and/or grammatical representations of formal languages, because we make emphasis on the key theoretical notions involved in the formal proofs of these equivalences.     

GaAs-based modulation-doped quantum-well infrared photodetectors for single- and two-color detection in 3-5 /spl mu/m

Double-barrier quantum-well infrared photodetectors are promising for operation in the midinfrared region. In this paper, we present a series of novel molecular beam epitaxy (MBE)-grown devices based on modulation-doped (MD) AlGaAs-AlAs-GaAs structures that exhibit a remarkable responsivity at zero bias (0.05 A/W) at 4.6 /spl mu/m. Since the photovoltaic properties are strongly dependent on the symmetry of the potential profile, we have systematically varied the position of the dopant in the barriers for a series of single-color detectors. Low-temperature photocurrent spectra and current-voltage (I-V) characteristics (in the dark and under illumination) show that the location of the dopant is a relevant design parameter, due to its role in the photovoltaic behavior (i.e., the presence or absence of zero bias signal). The performance of the MD devices is compared with that of a detector with doping in the center of the well and otherwise the same structure. In particular, the responsivity and detectivity seem to be higher for the MD detectors than for well-doped samples, especially when the dopant is located in the barrier closest to the substrate. Therefore, we have chosen that MD dopant profile when designing and growing, to our knowledge, the first 3-5 /spl mu/m two-color detector, with simultaneous detection at 3.8 and 4.4 /spl mu/m.     

The autonomous mobile robot AURORA for greenhouse operation

AURORA has been conceived in order to substitute hard and unhealthy human work inside greenhouses by means of an autonomous mobile robot outfitted with appropriate sensors and operation devices. Emphasis has been put in the development of a new robotic platform specifically designed for greenhouse tasks, governed by a control architecture that supports both autonomous navigation and shared human control     

Strong Negation and Equivalence in the Safe Belief Semantics

The safe belief semantics uses intermediate logics to definean extension of answer sets to all propositional formulas, butonly considering one kind of negation. In this work we extendsafe beliefs adding the strong negation connective. The mainfeature of our extension is that strong negation can occur beforeany formula, and not only at the atomic level. We give resultsconcerning the relation between strong negation extensions ofintermediate logics and safe beliefs and consider the way inwhich strong negation can be eliminated from any formula whilepreserving its semantics. We also propose two new notions ofequivalence: substitution equivalence and contextualized equivalence.We prove that they are both more general than strong equivalenceand, for propositional formulas where strong negation may occurat the non-atomic level, substitution equivalence captures anotion of equivalence that cannot be captured by strong equivalencealone.     

High prevalence of subclinical hypothyroidism and nodular thyroid disease in patients on hemodialysis

Chronic kidney disease has been known to affect thyroid hormone metabolism. Low serum levels of T3 and T4 are the most remarkable laboratorial findings. A high incidence of goiter and nodules on thyroid ultrasonography has been reported in patients with end‐stage renal disease (ESRD). Our objective is to evaluate the prevalence of laboratorial and morphologic alterations in the thyroid gland in a cohort of patients with ESRD on hemodialysis (HD). Sixty‐one patients with ESRD on HD were selected and compared with 43 healthy subjects matched by age, gender, and weight. Patients were submitted to thyroid ultrasonography. T3, free T4 (FT4), thyroid‐stimulating hormone, antithyroglobulin, and antithyroperoxidase antibodies were measured. The mean age of patients with ESRD was 47.4 ± 12.3 and 61% were women. ESRD was mainly caused by hypertensive nephrosclerosis and diabetic nephropathy. Mean thyroid volume, as determined by ultrasonography, was similar in both groups. Patients with ESRD had more hypoechoic nodules when compared with the control group (24.1% vs. 7.9%, P = 0.056). Mean serum FT4 and T3 levels were significantly lower in patients with ESRD, and subclinical hypothyroidism was more prevalent in patients with ESRD (21.82% vs. 7.14% control group, P = 0.04). Titers of antithyroid antibodies were similar in both groups. ESRD was associated with a higher prevalence of subclinical hypothyroidism and lower levels of T3 and FT4. Almost a quarter of patients showed thyroid nodules >10 mm. Periodic ultrasound evaluation and assessment of thyroid function are recommended in patients with ESRD on HD.     

State-based predictions with self-correction on Enterprise Desktop Grid environments

The abundant computing resources in current organizations provide new opportunities for executing parallel scientific applications and using resources. The Enterprise Desktop Grid Computing (EDGC) paradigm addresses the potential for harvesting the idle computing resources of an organization’s desktop PCs to support the execution of the company’s large-scale applications. In these environments, the accuracy of response-time predictions is essential for effective metascheduling that maximizes resource usage without harming the performance of the parallel and local applications. However, this accuracy is a major challenge due to the heterogeneity and non-dedicated nature of EDGC resources. In this paper, two new prediction techniques are presented based on the state of resources. A thorough analysis by linear regression demonstrated that the proposed techniques capture the real behavior of the parallel applications better than other common techniques in the literature. Moreover, it is possible to reduce deviations with a proper modeling of prediction errors, and thus, a Self-adjustable Correction method (SAC) for detecting and correcting the prediction deviations was proposed with the ability to adapt to the changes in load conditions. An extensive evaluation in a real environment was conducted to validate the SAC method. The results show that the use of SAC increases the accuracy of response-time predictions by 35%. The cost of predictions with self-correction and its accuracy in a real environment was analyzed using a combination of the proposed techniques. The results demonstrate that the cost of predictions is negligible and the combined use of the prediction techniques is preferable.