Miracle-dz/UniFAR-FTUs huggingface dataset:
Relation between dietary intake and nutritional status in cystic fibrosis

This study evaluated adherence to current dietary recommendations of children with cystic fibrosis and mild lung disease and their siblings by comparing energy intake. Fifty children (25 with cystic fibrosis) aged between 7 and 12 years completed the study. Energy intake was assessed by weighed dietary intake, resting energy expenditure was used to calculate recommended daily intakes. The children with cystic fibrosis had significant deficits in Z scores for both height and weight compared with their siblings, but there was no difference in percentage of ideal weight for height. The cystic fibrosis group had a significantly higher energy intake per kilogram body weight per day but there was no difference in the percentage of energy derived from fat, protein or carbohydrate. Energy intake (per kg/day) and fat intake (g/kg) were both significant predictors of weight for height in the cystic fibrosis group. Targets for dietary management in cystic fibrosis should perhaps be related to fat intake per kilogram body weight.
Robust Filtering for Linear Systems with Error Variance Constraints

In this correspondence, we consider the robust filtering problem for linear perturbed systems with steady-state error variance constraints. The purpose of this multiobjective problem is to design a linear filter that does not depend on the parameter perturbations such that the following three performance requirements are simultaneously satisfied. 1) The filtering process is asymptotically stable. 2) The steady-state variance of the estimation error of each state is not more than the individual prespecified value. 3) The transfer function from exogenous noise inputs to error state outputs meets the prespecified norm upper bound constraint. We show that in both continuous and discrete-time cases, the addressed filtering problem can effectively be solved in terms of the solutions of a couple of algebraic Riccati-like equations/inequalities. We present both the existence conditions and the explicit expression of desired robust filters. An illustrative numerical example is provided to demonstrate the flexibility of the proposed design approach.
Classifying Network Intrusions: A Comparison of Data Mining Methods

Network intrusion is an increasingly serious problem experienced by many organizations. In this increasingly hostile environment, networks must be able to detect whether a connection attempt is legitimate or not. The ever-changing nature of these attacks makes them difficult to detect. One solution is to use various data mining methods to determine if the network is being attacked. This paper compares the performance of two data mining methods— i.e., a standard artificial neural network (ANN) and an ANN guided by genetic algorithm (GA)— in classifying network connections as normal or attack. Using connection data drawn from a simulated US Air Force local area network each method was used to construct a predictive model. The models were then applied to validation data and the results were compared. The ANN guided by GA (90.67% correct classification) outperformed the standard ANN (81.75% correct classification) significantly, indicating the superiority of GAbased ANN.
On list sequence turbo decoding

An algorithm for decoding Turbo codes that combines conventional Turbo decoding and list sequence maximum a posteriori probability decoding is presented and evaluated. Compared to previous results on this theme, performance improvements in the order of 0.7 dB are obtained for Turbo codes with 514-b pseudorandom interleaving at a frame error rate of 10/sup -4/ on the additive white Gaussian noise channel.
The addicted human brain: insights from imaging studies.

Imaging studies have revealed neurochemical and functional changes in the brains of drug-addicted subjects that provide new insights into the mechanisms underlying addiction. Neurochemical studies have shown that large and fast increases in dopamine are associated with the reinforcing effects of drugs of abuse, but also that after chronic drug abuse and during withdrawal, brain dopamine function is markedly decreased and these decreases are associated with dysfunction of prefrontal regions (including orbitofrontal cortex and cingulate gyrus). The changes in brain dopamine function are likely to result in decreased sensitivity to natural reinforcers since dopamine also mediates the reinforcing effects of natural reinforcers and on disruption of frontal cortical functions, such as inhibitory control and salience attribution. Functional imaging studies have shown that during drug intoxication, or during craving, these frontal regions become activated as part of a complex pattern that includes brain circuits involved with reward (nucleus accumbens), motivation (orbitofrontal cortex), memory (amygdala and hippocampus), and cognitive control (prefrontal cortex and cingulate gyrus). Here, we integrate these findings and propose a model that attempts to explain the loss of control and compulsive drug intake that characterize addiction. Specifically, we propose that in drug addiction the value of the drug and drug-related stimuli is enhanced at the expense of other reinforcers. This is a consequence of conditioned learning and of the resetting of reward thresholds as an adaptation to the high levels of stimulation induced by drugs of abuse. In this model, during exposure to the drug or drug-related cues, the memory of the expected reward results in overactivation of the reward and motivation circuits while decreasing the activity in the cognitive control circuit. This contributes to an inability to inhibit the drive to seek and consume the drug and results in compulsive drug intake. This model has implications for therapy, for it suggests a multi-prong approach that targets strategies to decrease the rewarding properties of drugs, to enhance the rewarding properties of alternative reinforcers, to interfere with conditioned-learned associations, and to strengthen cognitive control in the treatment of drug addiction.
VISCOSITY SOLUTIONS OF HAMILTON–JACOBI EQUATIONS WITH DISCONTINUOUS COEFFICIENTS

We consider Hamilton–Jacobi equations, where the Hamiltonian depends discontinuously on both the spatial and temporal location. Our main result is the existence of viscosity solution to the Cauchy problem, and that the front tracking algorithm yields an L∞ contractive semigroup. We define a viscosity solution by treating the discontinuities in the coefficients analogously to "internal boundaries". The existence of viscosity solutions is established constructively via a front tracking approximation, whose limits are viscosity solutions, where by "viscosity solution" we mean a viscosity solution that posses some additional regularity at the discontinuities in the coefficients. We then show a comparison result that is valid for these viscosity solutions.
Natural semantics as a static program analysis framework

Natural semantics specifications have become mainstream in the formal specification of programming language semantics during the last 10 years. In this article, we set up sorted natural semantics as a specification framework which is able to express static semantic information of programming languages declaratively in a uniform way and allows one at the same time to generate corresponding analyses. Such static semantic information comprises context-sensitive properties which are checked in the semantic analysis phase of compilers as well as further static program analyses such as, for example, classical data and control flow analyses or type and effect systems. The latter require fixed-point analyses to determine their solutions. We show that, given a sorted natural semantics specification, we can generate the corresponding analysis. Therefore, we classify the solution of such an analysis by the notion of a proof tree. We show that a proof tree can be computed by solving an equivalent residuation problem. In case of the semantic analysis, this solution can be found by a basic algorithm. We show that its efficiency can be enhanced using solution strategies. We also demonstrate our prototype implementation of the basic algorithm which proves its applicability in practical situations. With the results of this article, we have established natural semantics as a framework which closes the gap between declarative and operational specification methods for static semantic properties as well as between specification frameworks for the semantic analysis. In particular, we show that natural semantics is expressive enough to define fixed-point program analyses.
Hazardous fuel treatments, suppression cost impacts, and risk mitigation

Land management agencies face uncertain tradeoffs regarding investments in preparedness and fuels management versus future suppression costs and impacts to valued resources and assets. Prospective evaluation of fuel treatments allows for comparison of alternative treatment strategies in terms of socioeconomic and ecological impacts, and can facilitate tradeoff analysis. This presentation will demonstrate recently developed methodologies for estimating potential suppression cost impacts of fuel treatments. The approach pairs wildfire simulation outputs with a regression cost model, estimating the influence of fuel treatments on distributions of wildfire size and suppression cost. A case study focuses on a landscape within the Deschutes National Forest in central Oregon, USA, and results suggest substantial treatment effects. An auxiliary analysis demonstrates the impacts of fuel treatments in terms of reduced exposure of values at risk, to quantify the broader potential benefits of fuel treatments. Effectiveness of treatments in the case study is contingent on large-scale implementation of fuel treatments across the landscape, and sufficient maintenance to ensure treatment effectiveness over the duration of the analysis period. Future applications and integration with other modeling approaches will be highlighted.
Factores de riesgo asociados a trastornos temporomandibulares

Introduccion: los trastornos temporomandibulares conforman un conjunto de condiciones musculo-esqueleticas que afectan la articulacion temporomandibular, musculos de la masticacion y estructuras anatomicas adyacentes; complejas y moldeadas por diversos factores de riesgo interactuantes. Resulta de gran valor el conocimiento de los mismos para poder actuar sobre ellos e impedir la aparicion y/o agravamiento de la enfermedad. Objetivo: caracterizar a la poblacion objeto de estudio segun las variables sociodemograficas: edad y sexo, factores precipitantes, habitos parafuncionales y trastornos oclusales. Metodos: se realizo un estudio observacional, descriptivo, de corte transversal, en el Hospital Clinicoquirurgico Universitario «Miguel Enriquez», en una poblacion constituida por 181 pacientes que acudieron a la Consulta Multidisciplinaria de Atencion Integral de la articulacion temporomandibular en el periodo comprendido de enero del 2010 a enero del 2012. Resultados: del total de pacientes, 133 pertenecian al sexo femenino, para un 73 %. El grupo de edades de 25-35 anos estuvo representado por 45 pacientes para un 24 %. En el 79 % se observo bruxismo, en el 24 % interposicion lingual en tanto que el 52 % presento dientes ausentes no restituidos. Conclusiones: el sexo predominante fue el femenino y el grupo de edades mas representado es el de 25-35 anos. El factor predisponente que mas se observo fue los dientes ausentes no restituidos protesicamente. El factor precipitante que predomino fue el bruxismo y no se observaron factores perpetuantes de los trastornos temporomandibulares.
Modal Tableaux with Propagation Rules and Structural Rules

In this paper we generalize the existing tableau methods for modal logics. First of all, while usual modal tableaux are based on trees, our basic structures are rooted directed acyclic graphs (RDAG). This allows natural tableau rules for some modal logics that are difficult to capture in the usual way (such as those having an accessibility relation that is dense or confluent). Second, tableau rules rewrite patterns, which are (schemas of) parts of a RDAG. A particular case of these rules are the single-step rules recently proposed by Massacci. This allows in particular tableau rule presentations for K5, KD5, K45, KD45, and S5 that respect the subformula property. Third, we divide modal tableau rules into propagation rules and structural rules. Structural rules construct new edges and nodes (without adding formulas to nodes), while propagation rules add formulas to nodes. This distinction allows to prove completeness in a modular way.
Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) Motionmaster: Authoring and Choreographing Kung-fu Motions by Sketch Drawings

Sketch-drawings is an intuitive and comprehensive means of conveying movement ideas in character animation. We proposed a novel sketch-based approach to assisting the authoring and choreographing of Kungfu motions at the early stage of animation creation. Given two human figure sketches corresponding to the initial and closing posture of a Kungfu form, and the trajectory drawings on specific moving joints, MotionMaster can directly rapid-prototype the realistic 3D motion sequence by sketch-based motion retrieval and refinement based on a motion database. The animators can then preview and evaluate the recovered motion sequence from any viewing angles. After the 3D motion sequence has been associated with the 2D sketch drawing, the animator can also interactively and iteratively make changes on the 2D sketch drawing, and the system will automatically transfer the 2D changes to the 3D motion data of current interests. It greatly helps the animator focus on the movement idea development during the evolutionary process of building motion data for articulated characters.
Reprints Available Directly from the Publisher Photocopying Permitted by License Only the Effect of Intrinsic Rigidity on the Optical Properties of Ppv Derivatives

Light scattering and optical spectroscopy experiments were performed on [2-methoxy, 5-(2'-ethyl-hexyloxy-p-phenylene-vinylene] (MEH-PPV), poIy[2-butoxy, 5-(2'-ethyl-hexyloxy-p-phenylene-vinylene] (BEH-PPV), and poIy[2-dicholestanoxy-p-phenylene-vinylene] (BCHA-PPV) in solution with p-xylene to determine the effects of side chain size on the structure and optical properties of PPV. We find that increasing the size of the solubilizing side chains increases the intrinsic persistence length of the PPV backbone and this change in rigidity has dramatic effects on the photoluminescence of PPV. Quantum yield determination relative to Rhodamine 6G shows the luminescence efficiency of the rigid BCHA-PPV is 0.66 k 0.05 and that the yield decreases to 0.20 f 0.05 for MEH-PPV, the most coiled derivative. Excitation profiles show an increase in non-radiative decay at high energies when the backbone is more flexible. There is currently much interest in PPV because of its application in luminescent d e ~ i c e s l-~. Like many conjugated polymers, PPV is insoluble in its pure form due to a high dielectric mismatch with conventional solvents. This intractability has been addressed by chemically attaching side chains to the polymer backbone. Side chains provide an organic layer that surrounds the polymer backbone, much like a surfactant, and make the polymer more compatible with organic solvents. While many conjugated polymers are processed in the derivatized form, very little is understood about the effects of functionalization on the structural, optical, and electronic properties of these polymers. Both experimental and theoretical studies have shown that the steric interactions of the side chains induce significant rigidity of the polymer b a c k b ~ n e ~ ? ~. The effect of macroscopic disorder on the optical properties of PPV and PPV derivatives have been studied e ~ t e n s i v e l y ~. ~. With techniques such as tensile drawing and gel processing, these experiments have shown that increased orientation and improved structural order produces a narrowing of both the absorption and emission spectra along with a reduction in apparent Stokes shift. These results have been interpreted as an increase in effective conjugation length, Leff as a result of increased chain order. Still to be understood is how the effective conjugation length is derived from intrinsic polymer features.
Reducing language barriers for tourists using handwriting recognition enabled mobile application

Modern mobile devices and networks permit to develop applications that reduce the language barrier for tourists and visitors in foreign countries. This paper describes a mobile application built on a distributed architecture that allows tourists to obtain additional information about location names and menu entries in Arabic language. By simply taking a photo, translation and additional information are displayed to users in their preferred language. While several mobile applications exist to translate the texts into photos, the present application offers the advantage of translating both handwritten and printed texts. The work was focused on two important aspects: the recognition system and the mobile application. The major challenge was to build a recognition system able to recognize handwritten or printed texts of various writing styles or fonts. Therefore, we propose an original approach consisting of recognizing handwritten and printed words using the Balamand-ENST handwriting recognition system, trained on handwritten texts. Experiments conducted on a collected database have shown that the recognition system trained on handwritten text provides excellent performance when used in recognizing printed text. This recognition system and its performance in both modalities are briefly described in this paper. In addition, a full description on how the mobile application was designed and its functionality is presented.
Gene expression after freshwater transfer in gills and opercular epithelia of killifish: insight into divergent mechanisms of ion transport

SUMMARY We have explored the molecular basis for differences in physiological function between the gills and opercular epithelium of the euryhaline killifish Fundulus heteroclitus. These tissues are functionally similar in seawater, but in freshwater the gills actively absorb Na+ but not Cl–, whereas the opercular epithelium actively absorbs Cl– but not Na+. These differences in freshwater physiology are likely due to differences in absolute levels of gene expression (measured using real-time PCR), as several proteins important for Na+ transport, namely Na+,H+-exchanger 2 (NHE2), carbonic anhydrase 2 (CA2), Na+,HCO3–cotransporter 1, and V-type H+-ATPase, were expressed at 3- to over 30-fold higher absolute levels in the gills. In gills, transfer from 10% seawater to freshwater increased the activity of Na+,K+-ATPase by twofold (from 12 h to 7 days), increased the expression of NHE2 (at 12 h) and CA2 (from 12 h to 7 days), and decreased the expression of NHE3 (from 12 h to 3 days). In opercular epithelium, NHE2 was not expressed; furthermore, Na+,K+-ATPase activity was unchanged after transfer to freshwater, CA2 mRNA levels decreased, and NHE3 levels increased. Consistent with their functional similarities in seawater, killifish gills and opercular epithelium expressed Na+,K+-ATPase α1a, Na+,K+,2Cl–cotransporter 1 (NKCC1), cystic fibrosis transmembrane conductance regulator (CFTR) Cl– channel and the signalling protein 14-3-3a at similar absolute levels. Furthermore, NKCC1 and CFTR were suppressed equally in each tissue after freshwater transfer, and 14-3-3a mRNA increased in both. These results provide insight into the mechanisms of ion transport by killifish gills and opercular epithelia, and demonstrate a potential molecular basis for the differences in physiological function between these two organs.
Relativistic simulations of the phase-transition-induced collapse of neutron stars

An increase in the central density of a neutron star may trigger a phase transition from hadronic matter to deconfined quark matter in the core, causing it to collapse to a more compact hybrid star configuration. We present a study of this, building on previous work by Lin et al. We follow them in considering a supersonic phase transition and using a simplified equation of state, but our calculations are general relativistic (using 2D simulations in the conformally flat approximation) as compared with their 3D Newtonian treatment. We also improved the treatment of the initial phase transformation, avoiding the introduction of artificial convection. As before, we find that the emitted gravitational wave spectrum is dominated by the fundamental quasi-radial and quadrupolar pulsation modes but the strain amplitudes are much smaller than suggested previously, which is disappointing for the detection prospects. However, we see significantly smaller damping and observe a non-linear mode resonance which substantially enhances the emission in some cases. We explain the damping mechanisms operating, giving a different view from the previous work. Finally, we discuss the detectability of the gravitational waves, showing that the signal-to-noise ratio for current or second generation interferometers could be high enough to detect such events in our Galaxy, although third generation detectors would be needed to observe them out to the Virgo cluster, which would be necessary for having a reasonable event rate.
Solving the dilemma of long range generalization by feedforward neural networks

This paper discusses the problem of generalization of training samples over long distances in the input space of a feedforward learning machine. Such a generalization type might produce a significant dilemma of how great the contribution of different training samples should be in generalizing of that input space. A structure of a neuron in a feedforward neural network is analyzed and it is concluded, that the resolution of the discussed dilemma in such neural networks may be problematic – while such neural networks might be capable for long range generalization, a highly random and spurious generalization may occur. To illustrate the sharp differences in generalizing of the same function by different learning machines, results given by the support vector machines are also presented.
Prevention and Management of Gastroesophageal Varices in Cirrhosis

Variceal hemorrhage is one of the major complications of liver cirrhosis associated with significant mortality and morbidity. Its management has evolved over the past decade and has substantially reduced the rate of first and recurrent bleeding while decreasing mortality. In general, treatment of esophageal varices can be divided into three categories: primary prophylaxis (prevention of first episode of bleeding), management of acute bleeding, and secondary prophylaxis (prevention of recurrent hemorrhage). The goal of this paper is to describe the current evidence behind the management of esophageal varices. We will discuss indications for primary prophylaxis and the different modes of therapy, pharmacological and interventional treatment in acute bleeding, and therapeutic options in preventing recurrent bleeding. The indications for TIPS will also be reviewed including its possible benefits in acute variceal hemorrhage.