Estadítiques de crides al sistema en plataforma GNU/Linux

Aquest projecte es basa en la modificació del kernel (nucli) del sistema operatiu GNU/Linux per dotar-lo de la capacitat d'extreure estadístiques de les crides al sistema (syscalls). A partir de la compilació i instal·lació d'un nou nucli es registra la informació del nombre de vegades i la freqüència amb què es fan aquestes crides al sistema, i posteriorment es representa en un informe d'estadístiques explicatives.

A virtual address kernel modification for UNIX /

"February 1980."

Effects of stimulus modality and task condition on blink startle modification and on electrodermal responses

Participants in Experiments 1 and 2 performed a discrimination and counting task to assess the effect of lead stimulus modality on attentional modification of the acoustic startle reflex. Modality of the discrimination stimuli was changed across subjects. Electrodermal responses were larger during task-relevant stimuli than during task-irrelevant stimuli in all conditions. Larger blink magnitude facilitation was found during auditory and visual task-relevant stimuli, but not for tactile stimuli. Experiment 3 used acoustic, visual, and tactile conditioned stimuli (CSs) in differential conditioning with an aversive unconditioned stimulus (US). Startle magnitude facilitation and electrodermal responses were larger during a CS that preceded the US than during a CS that was presented alone regardless of lead stimulus modality. Although not unequivocal, the present data pose problems for attentional accounts of blink modification that emphasize the importance of lead stimulus modality.

Eutectic modification and microstructure development in Al-Si alloys

Recent increasing applications for cast Al-Si alloys are particularly driven by the need for lightweighting components in the automotive sector. To improve mechanical properties, elements such as strontium, sodium and antimony can be added to modify the eutectic silicon from coarse and plate-like to fine and fibrous morphology. It is only recently being noticed that the morphological transformation resulting from eutectic modification is also accompanied by other, equally significant, but often unexpected changes. These changes can include a 10-fold increase in the eutectic grain size, redistribution of low-melting point phases and porosity as well as surface finish, consequently leading to variations in casting quality. This paper shows the state-of-the-art in understanding the mechanism of eutectic nucleation and growth in Al-Si alloys, inspecting samples, both quenched and uninterrupted, on the macro, micro and nano-scale. It shows that significant variations in eutectic nucleation and growth dynamics occur in AI-Si alloys as a function of the type and amount of modifier elements added. The key role of AIP particles in nucleating silicon is demonstrated. (c) 2005 Elsevier B.V. All rights reserved.

Effects of process modification and heat pump drying on physical and sensory properties of Chinese style shredded beef

Chinese-style dried, shredded meat is traditionally prepared by sequential cooking, shredding, pre-drying, and final drying (roasting) of lean meat. In this study, shredded dried beef (a(w)<0.6) was prepared by omitting roasting but prolonging pre-drying. Sensory scores of the modified product were lower than those for the traditional product. When heat pump drying replaced traditional oven drying, drying time was shortened without significant difference in quality attributes. Desorption curves were established for shredded beef at several drying temperatures.

Study of the impact of tissue density heterogeneities on 3-dimensional abdominal dosimetry: comparison between dose kernel convolution and direct monte carlo methods.

Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Characterization, physicochemical stability, and evaluation of in vitro digestibility of solid lipid microparticles produced with palm kernel oil and tristearin

Solid lipid particles have been investigated by food researchers due to their ability to enhance the incorporation and bioavailability of lipophilic bioactives in aqueous formulations. The objectives of this study were to evaluate the physicochemical stability and digestibility of lipid microparticles produced with tristearin and palm kernel oil. The motivation for conducting this study was the fact that mixing lipids can prevent the expulsion of the bioactive from the lipid core and enhance the digestibility of lipid structures. The lipid microparticles containing different palm kernel oil contents were stable after 60 days of storage according to the particle size and zeta potential data. Their calorimetric behavior indicated that they were composed of a very heterogeneous lipid matrix. Lipid microparticles were stable under various conditions of ionic strength, sugar concentration, temperature, and pH. Digestibility assays indicated no differences in the release of free fatty acids, which was approximately 30% in all analises. The in vitro digestibility tests showed that the amount of palm kernel in the particles did not affect the percentage of lipolysis, probably due to the high amount of surfactants used and/or the solid state of the microparticles.

Acceptance of a food of animal origin obtained through genetic modification and cloning in South America: a comparative study among university students and working adults

AbstractWith the aim of comparing the acceptance of milk obtained from cloned, genetically modified (GM) and conventionally bred cows among working adults and university students, and identifying and characterizing typologies among both subsamples in terms of their preferences, a survey was applied to 400 people in southern Chile, distributed using a simple allocation among the subsamples. Using a conjoint analysis, it was found that consumers preferred milk from a conventional cow. Using a cluster analysis, in both subsamples two segments sensitive to production technology were identified. Rejection of cloning was greatest among university students, whereas a higher proportion of working adults rejected GM. The segments differed in terms of area of residence, knowledge about GM, and milk consumption habits. Contrary to what was expected, no differences were found according to education, gender or degree of satisfaction with food-related life.

ANALYSIS, MODIFICATION, AND EVALUATION OF THE COLD FLOW PROPERTIES OF VEGETABLE OILS AS BASE OIL FOR INDUSTRIAL LUBRICANTS

Poor cold flow properties of vegetable oils are a major problem preventing the usage of many abundantly available vegetable oils as base stocks for industrial lubricants. The major objective of this research is to improve the cold flow properties of vegetable oils by various techniques like additive addition and different chemical modification processes. Conventional procedure for determining pour point is ASTM D97 method. ASTM D97 method is time consuming and reproducibility of pour point temperatures is poor between laboratories. Differential Scanning Calorimetry (DSC) is a fast, accurate and reproducible method to analyze the thermal activities during cooling/heating of oil. In this work coconut oil has been chosen as representative vegetable oil for the analysis and improvement cold flow properties since it is abundantly available in the tropics and has a very high pour point of 24 °C. DSC is used for the analysis of unmodified and modified vegetable oil. The modified oils (with acceptable pour points) were then subjected to different tests for the valuation of important lubricant properties such as viscometric, tribological (friction and wear properties), oxidative and corrosion properties.A commercial polymethacrylate based PPD was added in different percentages and the pour points were determined in each case. Styrenated phenol(SP) was added in different concentration to coconut oil and each solution was subjected to ASTM D97 test and analysis by DSC. Refined coconut oil and other oils like castor oil, sunflower oil and keranja oil were mixed in different proportions and interesterification procedure was carried out. Interesterification of coconut oil with other vegetable oils was not found to be effective in lowering the pour point of coconut oil as the reduction attained was only to the extent of 2 to 3 °C.Chemical modification by acid catalysed condensation reaction with coconut oil castor oil mixture resulted in significant reduction of pour point (from 24 ºC to -3 ºC). Instead of using triacylglycerols, when their fatty acid derivatives (lauric acid- the major fatty acid content of coconut oil and oleic acid- the major fatty acid constituents of monoand poly- unsaturated vegetable oils like olive oil, sunflower oil etc.) were used for the synthesis , the pour point could be brought down to -42 ºC. FTIR and NMR spectroscopy confirmed the ester structure of the product which is fundamental to the biodegradability of vegetable oils. The tribological performance of the synthesised product with a suitable AW/EP additive was comparable to the commercial SAE20W30 oil. The viscometric properties (viscosity and viscosity index) were also (with out additives) comparable to commercial lubricants. The TGA experiment confirmed the better oxidative performance of the product compared to vegetable oils. The sample passed corrosion test as per ASTM D130 method.

An Improved Color Video Super-Resolution Using Kernel Regression and Fuzzy Enhancement

An improved color video super-resolution technique using kernel regression and fuzzy enhancement is presented in this paper. A high resolution frame is computed from a set of low resolution video frames by kernel regression using an adaptive Gaussian kernel. A fuzzy smoothing filter is proposed to enhance the regression output. The proposed technique is a low cost software solution to resolution enhancement of color video in multimedia applications. The performance of the proposed technique is evaluated using several color videos and it is found to be better than other techniques in producing high quality high resolution color videos

Modification and Analysis of Group-13-Nitride Semiconductor Surfaces: Influence of Adsorbates on Device Characteristics and Processing

Im Rahmen dieser interdisziplinären Doktorarbeit wird eine (Al)GaN Halbleiteroberflächenmodifikation untersucht, mit dem Ziel eine verbesserte Grenzfläche zwischen dem Material und dem Dielektrikum zu erzeugen. Aufgrund von Oberflächenzuständen zeigen GaN basierte HEMT Strukturen üblicherweise große Einsatzspannungsverschiebungen. Bisher wurden zur Grenzflächenmodifikation besonders die Entfernung von Verunreinigungen wie Sauerstoff oder Kohlenstoff analysiert. Die nasschemischen Oberflächenbehandlungen werden vor der Abscheidung des Dielektrikums durchgeführt, wobei die Kontaminationen jedoch nicht vollständig entfernt werden können. In dieser Arbeit werden Modifikationen der Oberfläche in wässrigen Lösungen, in Gasen sowie in Plasma analysiert. Detaillierte Untersuchungen zeigen, dass die inerte (0001) c-Ebene der Oberfläche kaum reagiert, sondern hauptsächlich die weniger polaren r- und m- Ebenen. Dies kann deutlich beim Defektätzen sowie bei der thermischen Oxidation beobachtet werden. Einen weiteren Ansatz zur Oberflächenmodifikation stellen Plasmabehandlungen dar. Hierbei wird die Oberflächenterminierung durch eine nukleophile Substitution mit Lewis Basen, wie Fluorid, Chlorid oder Oxid verändert, wodurch sich die Elektronegativitätsdifferenz zwischen dem Metall und dem Anion im Vergleich zur Metall-Stickstoff Bindung erhöht. Dies führt gleichzeitig zu einer Erhöhung der Potentialdifferenz des Schottky Kontakts. Sauerstoff oder Fluor besitzen die nötige thermische Stabilität um während einer Silicium-nitridabscheidung an der (Al)GaN Oberfläche zu bleiben. Sauerstoffvariationen an der Oberfläche werden in NH3 bei 700°C, welches die nötigen Bedingungen für die Abscheidung darstellen, immer zu etwa 6-8% reduziert – solche Grenzflächen zeigen deswegen auch keine veränderten Ergebnisse in Einsatzspannungsuntersuchungen. Im Gegensatz dazu zeigt die fluorierte Oberfläche ein völlig neues elektrisches Verhalten: ein neuer dominanter Oberflächendonator mit einem schnellen Trapping und Detrapping Verhalten wird gefunden. Das Energieniveau dieses neuen, stabilen Donators liegt um ca. 0,5 eV tiefer in der Bandlücke als die ursprünglichen Energieniveaus der Oberflächenzustände. Physikalisch-chemische Oberflächen- und Grenzflächenuntersuchung mit XPS, AES oder SIMS erlauben keine eindeutige Schlussfolgerung, ob das Fluor nach der Si3N4 Abscheidung tatsächlich noch an der Grenzfläche vorhanden ist, oder einfach eine stabilere Oberflächenrekonstruktion induziert wurde, bei welcher es selbst nicht beteiligt ist. In beiden Fällen ist der neue Donator in einer Konzentration von 4x1013 at/cm-2 vorhanden. Diese Dichte entspricht einer Oberflächenkonzentration von etwa 1%, was genau an der Nachweisgrenze der spektroskopischen Methoden liegt. Jedoch werden die elektrischen Oberflächeneigenschaften durch die Oberflächenmodifikation deutlich verändert und ermöglichen eine potentiell weiter optimierbare Grenzfläche.

Sparse Correlation Kernel Analysis and Reconstruction

This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing. To choose the appropriate features from this large dictionary, we use Support Vector Machine (SVM) regression and compare this to traditional Principal Component Analysis (PCA) for the tasks of signal reconstruction, superresolution, and compression. The testbed we use in this paper is a set of images of pedestrians. This paper also presents results of experiments in which we use a dictionary of multiscale basis functions and then use Basis Pursuit De-Noising to obtain a sparse, multiscale approximation of a signal. The results are analyzed and we conclude that 1) when used with a sparse representation technique, the correlation function is an effective kernel for image reconstruction and superresolution, 2) for image compression, PCA and SVM have different tradeoffs, depending on the particular metric that is used to evaluate the results, 3) in sparse representation techniques, L_1 is not a good proxy for the true measure of sparsity, L_0, and 4) the L_epsilon norm may be a better error metric for image reconstruction and compression than the L_2 norm, though the exact psychophysical metric should take into account high order structure in images.

Enhanced effects of combined cognitive bias modification and computerised cognitive behaviour therapy on social anxiety

This study examines whether combined cognitive bias modification for interpretative biases (CBM-I) and computerised cognitive behaviour therapy (C-CBT) can produce enhanced positive effects on interpretation biases and social anxiety. Forty socially anxious students were randomly assigned into two conditions, an intervention group (positive CBM-I + C-CBT) or an active control (neutral CBM-I + C-CBT). At pre-test, participants completed measures of social anxiety, interpretative bias, cognitive distortions, and social and work adjustment. They were exposed to 6 × 30 min sessions of web-based interventions including three sessions of either positive or neutral CBM-I and three sessions of C-CBT, one session per day. At post-test and two-week follow-up, participants completed the baseline measures. A combined positive CBM-I + C-CBT produced less negative interpretations of ambiguous situations than neutral CBM-I + C-CBT. The results also showed that both positive CBM-I + C-CBT and neutral CBM-I + C-CBT reduced social anxiety and cognitive distortions as well as improving work and social adjustment. However, greater effect sizes were observed in the positive CBM-I + C-CBT condition than the control. This indicates that adding positive CBM-I to C-CBT enhanced the training effects on social anxiety, cognitive distortions, and social and work adjustment compared to the neutral CBM-I + C-CBT condition.

Surface modification and crystallization of the BaO-B2O3-SiO2 glassy system using CO2 laser irradiation

The surface modification and crystallization process of BaO-B2O3-SiO2 glass compositions when exposed to CO2 laser irradiation was evaluated as a function of the laser power, irradiation time and surface condition. The glass surface was modified by the application of laser power exceeding 0.40 W and an irradiation time of more than 300 s. Micro-Raman and X-ray diffraction measurements revealed at high laser power the formation of beta-BaB2O4 (beta-BBO) crystalline phase. The crystallization of the irradiated region was enhanced when beta-BBO micrometer sized particles were dispersed on the surface of the glass sample. The intensity of the second harmonic generation observed in the crystallized region was found to depend mainly on the condition of the glassy surface prior to glass irradiation. (C) 2007 Elsevier B.V. All rights reserved.