The GUISurfer tool: towards a language independent approach to reverse engineering GUI code

Graphical user interfaces (GUIs) are critical components of today's software. Developers are dedicating a larger portion of code to implementing them. Given their increased importance, correctness of GUIs code is becoming essential. This paper describes the latest results in the development of GUISurfer, a tool to reverse engineer the GUI layer of interactive computing systems. The ultimate goal of the tool is to enable analysis of interactive system from source code.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Histamine induces ATP release from human subcutaneous fibroblasts via pannexin-1 hemichannels leading to Ca2+ mobilization and cell proliferation

Changes in the regulation of connective tissue ATP-mediated mechano-transduction and remodeling may be an important link to the pathogenesis of chronic pain. It has been demonstrated that mast cell-derived histamine plays an important role in painful fibrotic diseases. Here we analyzed the involvement of ATP in the response of human subcutaneous fibroblasts to histamine. Acute histamine application caused a rise in intracellular Ca2+ ([Ca2+]i) and ATP release from human subcutaneous fibroblasts via H1 receptor activation. Histamine-induced [Ca2+]i rise was partially attenuated by apyrase, an enzyme that inactivates extracellular ATP, and by blocking P2 purinoceptors with pyridoxal phosphate-6-azo(benzene-2,4-disulfonic acid) tetrasodium salt and reactive blue 2. [Ca2+]i accumulation caused by histamine was also reduced upon blocking pannexin-1 hemichannels with 10Panx, probenecid, or carbenoxolone but not when connexin hemichannels were inhibited with mefloquine or 2-octanol. Brefeldin A, an inhibitor of vesicular exocytosis, also did not block histamine-induced [Ca2+]i mobilization. Prolonged exposure of human subcutaneous fibroblast cultures to histamine favored cell growth and type I collagen synthesis via the activation of H1 receptor. This effect was mimicked by ATP and its metabolite, ADP, whereas the selective P2Y1 receptor antagonist, MRS2179, partially attenuated histamine-induced cell growth and type I collagen production. Expression of pannexin-1 and ADPsensitive P2Y1 receptor on human subcutaneous fibroblasts was confirmed by immunofluorescence confocal microscopy and Western blot analysis. In conclusion, histamine induces ATP release from human subcutaneous fibroblasts, via pannexin-1 hemichannels, leading to [Ca2+]i mobilization and cell growth through the cooperation of H1 and P2 (probably P2Y1) receptors.

Bradykinin-induced Ca2+ signaling in human subcutaneous fibroblasts involves ATP release via hemichannels leading to P2Y12 receptors activation

Background: Chronic musculoskeletal pain involves connective tissue remodeling triggered by inflammatory mediators, such as bradykinin. Fibroblast cells signaling involve changes in intracellular Ca2+ ([Ca2+]i). ATP has been related to connective tissue mechanotransduction, remodeling and chronic inflammatory pain, via P2 purinoceptors activation. Here, we investigated the involvement of ATP in bradykinin-induced Ca2+ signals in human subcutaneous fibroblasts. Results: Bradykinin, via B2 receptors, caused an abrupt rise in [Ca2+]i to a peak that declined to a plateau, which concentration remained constant until washout. The plateau phase was absent in Ca2+-free medium; [Ca2+]i signal was substantially reduced after depleting intracellular Ca2+ stores with thapsigargin. Extracellular ATP inactivation with apyrase decreased the [Ca2+]i plateau. Human subcutaneous fibroblasts respond to bradykinin by releasing ATP via connexin and pannexin hemichannels, since blockade of connexins, with 2- octanol or carbenoxolone, and pannexin-1, with 10Panx, attenuated bradykinin-induced [Ca2+]i plateau, whereas inhibitors of vesicular exocytosis, such as brefeldin A and bafilomycin A1, were inactive. The kinetics of extracellular ATP catabolism favors ADP accumulation in human fibroblast cultures. Inhibition of ectonucleotidase activity and, thus, ADP formation from released ATP with POM-1 or by Mg2+ removal from media reduced bradykinin-induced [Ca2+]i plateau. Selective blockade of the ADP-sensitive P2Y12 receptor with AR-C66096 attenuated bradykinin [Ca2+]i plateau, whereas the P2Y1 and P2Y13 receptor antagonists, respectively MRS 2179 and MRS 2211, were inactive. Human fibroblasts exhibited immunoreactivity against connexin-43, pannexin-1 and P2Y12 receptor. Conclusions: Bradykinin induces ATP release from human subcutaneous fibroblasts via connexin and pannexin-1-containing hemichannels leading to [Ca2+]i mobilization through the cooperation of B2 and P2Y12 receptors.

Global-EDF scheduling of multimode real- time systems considering mode independent tasks

Embedded real-time systems often have to support the embedding system in very different and changing application scenarios. An aircraft taxiing, taking off and in cruise flight is one example. The different application scenarios are reflected in the software structure with a changing task set and thus different operational modes. At the same time there is a strong push for integrating previously isolated functionalities in single-chip multicore processors. On such multicores the behavior of the system during a mode change, when the systems transitions from one mode to another, is complex but crucial to get right. In the past we have investigated mode change in multiprocessor systems where a mode change requires a complete change of task set. Now, we present the first analysis which considers mode changes in multicore systems, which use global EDF to schedule a set of mode independent (MI) and mode specific (MS) tasks. In such systems, only the set of MS tasks has to be replaced during mode changes, without jeopardizing the schedulability of the MI tasks. Of prime concern is that the mode change is safe and efficient: i.e. the mode change needs to be performed in a predefined time window and no deadlines may be missed as a function of the mode change.

Model morphisms (MoMo) to enable language independent information models and interoperable business networks

MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Local Fractional Variational Iteration Method for Local Fractional Poisson Equations in Two Independent Variables

The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.

The inhibitory activity of synthetic compounds and ions against transporters of multi-drug resistant bacteria

RESUMO: Sessenta e três derivados de hidantoína foram utilizados para avaliar possíveis efeitos de modulação na actividade das bombas de efluxo (BE) na Salmonella NCTC 13349 utilizando um método fluorimétrico semi-automático. Nenhum dos compostos apresentaram actividade anti-bacteriana até concentrações de 240 mg/L. Entre todos os compostos, SZ-7 demonstrou possuir propriedades de modulação de effluxo na presença de glucose. Para testar esta actividade, estirpes de Salmonella resistentes à ciprofloxacina, induzidas a elevados níveis de resistência com sobre-expressão de BE, foram expostas ao SZ-7. Este derivado afectou a susceptibilidade das estirpes à ciprofloxacina. Uma vez que os 63 compostos estudados apresentaram pouco efeito inibitório /cumulativo, apesar de serem conhecidos pelos seus efeitos moduladores de BE-dependentes de iões em eucariotas, foi questionado o papel dos iões na regulação de BE bacterianas, que poderão influenciar a eficácia de novos compostos. Para este estudo, utilizamos a Escherichia coli AG100 como modelo, devido ao extenso conhecimento no que respeita a estrutura e actividade das BE. Devido à importância de iões de cálcio (Ca2+) nos canais de transporte membranar e na actividade de ATPases, a sua actividade na modulação do efluxo foi investigada. De resultados anteriormente obtidos concluiu-se que a pH 5 o efluxo é independente de energia metabólica; contudo, a pH 8 é absolutamente dependente, sendo que o Ca2+ é indispensável para manter a actividade das ATPases bacterianas. A acumulação/effluxo de EtBr pela E. coli AG100 foi determinada na presença/ausência de Ca2+, clorpromazina (inibidor de ligação de Ca2+ a proteínas), e ácido etilenodiamino tetra-acético (quelante de Ca2+). Acumulação/effluxo aumentou a pH 8, contudo o Ca2+ reverte estes efeitos evidenciando a sua importância no funcionamento das BE bacterianas. Em resumo este trabalho colocou em evidência que muitos aspectos bioquímicos e bioenergéticos devem ser tomados em consideração no estudo da resistência bacteriana mediada por BE.------- ABSTRACT: Sixty-three hydantoin derivatives were evaluated for their modulating effects on efflux pump (EP) activity of Salmonella NCTC 13349 utilizing a semi-automatic fluorometric method. None of the compounds presented antibacterial activities at concentrations as high as 240 mg/L. Among all compounds, SZ-7 showed possible efflux modulating activity in the presence of glucose, indicative of a potential EP inhibitor. To verify its potential effects, ciprofloxacin-resistant Salmonella strains, induced to high level resistance with over-expressing EPs, were exposed to SZ-7. This derivative affected the susceptibility of the ciprofloxacin-resistant strains. Since the 63 compounds studied had very low inhibitory/accumulative effects, even though their known for being efficient in modulating ion-driven eukaryotic EPs, we questioned whether ions had a leading role in regulating bacterial EPs, influencing the effectiveness of new compounds. For this study we used Escherichia coli AG100 as a model, due to the extensive knowledge on its EPs structure and activity. Owing the importance of calcium ions (Ca2+) for membrane transport channels and activity of ATPases, the role of Ca2+ was investigated. From previous results we concluded that at pH 5 efflux is independent of metabolic energy; however, at pH 8 it is entirely dependent of metabolic energy and the Ca2+ ions are essential to maintain the activity of bacterial ATPases. Accumulation and efflux of ethidium bromide (EtBr) by E. coli AG100 was determined in the presence and absence of Ca2+, chlorpromazine (inhibitor of Ca2+-binding to proteins), and ethylenediaminetetraacetic acid (Ca2+ chelator). Accumulation of EtBr increased at pH 8; however Ca2+ reversed these effects providing information as to the importance of this ion in the regulation of bacterial EP systems. Overall this work puts in evidence that many biochemical and bioenergetic aspects related to the strains physiology need to be taken into consideration in bacterial drug resistance mediated by EPs.

Analysis of the EEG Dynamics of Epileptic Activity in Gelastic Seizures Using Decomposition in Independent Components

Objective: Gelastic seizures are a frequent and well established manifestation of the epilepsy associated with hypothalamic hamartomas. The scalp EEG recordings very seldom demonstrate clear spike activity and the information about the ictal epilepsy dynamics is limited. In this work, we try to isolate epileptic rhythms in gelastic seizures and study their generators. Methods: We extracted rhythmic activity from EEG scalp recordings of gelastic seizures using decomposition in independent components (ICA) in three patients, two with hypothalamic hamartomas and one with no hypothalamic lesion. Time analysis of these rhythms and inverse source analysis was done to recover their foci of origin and temporal dynamics. Results: In the two patients with hypothalamic hamartomas consistent ictal delta (2–3 Hz) rhythms were present, with subcortical generators in both and a superficial one in a single patient. The latter pattern was observed in the patient with no hypothalamic hamartoma visible in MRI. The deep generators activated earlier than the superficial ones, suggesting a consistent sub-cortical origin of the rhythmical activity. Conclusions: Our data is compatible with early and brief epileptic generators in deep sub-cortical regions and more superficial ones activating later. Significance: Gelastic seizures express rhythms on scalp EEG compatible with epileptic activity originating in sub-cortical generators and secondarily involving cortical ones.

Low Socioeconomic Status is an Independent Risk Factor for Survival After Abdominal Aortic Aneurysm Repair and Open Surgery for Peripheral Artery Disease

OBJECTIVE/BACKGROUND: The association between socioeconomic status (SES), presentation, and outcome after vascular surgery is largely unknown. This study aimed to determine the influence of SES on post-operative survival and severity of disease at presentation among vascular surgery patients in the Dutch setting of equal access to and provision of care. METHODS: Patients undergoing surgical treatment for peripheral artery disease (PAD), abdominal aortic aneurysm (AAA), or carotid artery stenosis between January 2003 and December 2011 were retrospectively included. The association between SES, quantified by household income, disease severity at presentation, and survival was studied using logistic and Cox regression analysis adjusted for demographics, and medical and behavioral risk factors. RESULTS: A total of 1,178 patients were included. Low income was associated with worse post-operative survival in the PAD cohort (n = 324, hazard ratio 1.05, 95% confidence interval [CI] 1.00-1.10, per 5,000 Euro decrease) and the AAA cohort (n = 440, quadratic relation, p = .01). AAA patients in the lowest income quartile were more likely to present with a ruptured aneurysm (odds ratio [OR] 2.12, 95% CI 1.08-4.17). Lowest income quartile PAD patients presented more frequently with symptoms of critical limb ischemia, although no significant association could be established (OR 2.02, 95% CI 0.96-4.26). CONCLUSIONS: The increased health hazards observed in this study are caused by patient related factors rather than differences in medical care, considering the equality of care provided by the study setting. Although the exact mechanism driving the association between SES and worse outcome remains elusive, consideration of SES as a risk factor in pre-operative decision making and focus on treatment of known SES related behavioral and psychosocial risk factors may improve the outcome of patients with vascular disease.