O paradoxo da cidade monitorada : vigilância limitada e espaços públicos fragilizados a partir do estudo do sistema das câmeras do município de Vila Velha - ES

A dissertação aborda a fragilização dos espaços públicos num contexto de utilização de câmeras de vigilância, temática que será problematizada a partir da vigilância exercida pelas câmeras do município de Vila Velha – ES. Partimos da hipótese de que vivemos cercados por objetos técnicos que continuamente produzem informações sobre os sujeitos sociais e os seus espaços como forma de controle. As câmeras representam o exemplo mais conhecido desses objetos, embora sejam apresentadas pelos discursos das administrações públicas como ferramentas de auxílio à segurança. Utilizando como metodologia a observação participante para acompanhamento do trabalho realizado “por trás” das câmeras, concluímos que uma série de fatores desmistificam esses discursos: as câmeras que não são monitoradas, a ausência de manutenção dos equipamentos do sistema, os baixos salários e as condições trabalhistas daqueles que operam as câmeras, a ausência de articulação com os demais setores da prefeitura, a falta de credibilidade das câmeras com a polícia, etc. Por outro lado, ao fazermos um trabalho “na frente” das câmeras, observando o cotidiano de três áreas vigiadas nos bairros Praia da Costa, Glória e Riviera da Barra, bem como entrevistando transeuntes, moradores e comerciantes, concluímos que a maneira surpreendentemente indiferente com que as pessoas lidam com a vigilância é alimentada quando descobrimos que elas não oferecem a segurança pretendida. Se as câmeras não auxiliam a segurança pública, a sua utilização tem um efeito perverso na fragilização dos espaços públicos de Vila Velha, considerando que a vigilância representa ameaças potenciais e reais às condições que o pressupõem: a pluralidade e a liberdade, pois as câmeras atualizam um estado de vigilância permanente alimentando o estigma sobre determinados grupos sociais, que, por sua vez, são os alvos favoritos da vigilância, o que permite às câmeras, ainda, a potencial função de controle socioespacial direto (função admitida inclusive pelos cidadãos entrevistados) sobre os espaços vigiados; e a individualidade dos cidadãos, que é acintosamente violada. As câmeras, portanto, ao pretenderem garantir qualidade de vida à população (oferecendo segurança), produzem o efeito exatamente inverso

Electric vehicle scenario simulator tool for smart grid operators

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operator´s planning and operations but can be used by other entities for related studies. The paper describes the parameters supported by the current version of the Electric Vehicle Scenario Simulator (EVeSSi) tool and its current algorithm. EVeSSi enables the definition of electric vehicles scenarios on distribution networks using a built-in movement engine. The scenarios created with EVeSSi can be used by external tools (e.g., power flow) for specific analysis, for instance grid impacts. Two scenarios are briefly presented for illustration of the simulator capabilities.

Chemical and biological studies from an Azorean macroalga: Ulva rigida

3rd Portuguese Meeting on Medicinal Chemistry and 1st Portuguese-Spanish-Brazilian Meeting on Medicinal Chemistry, Aveiro, 28-30 Novembro 2012.

The invisible factors that can make the difference. Language management and knowledge transfer in multinational sites

The knowledge-based society we live in has stressed the importance of human capital and brought talent to the top of most wanted skills, especially to companies who want to succeed in turbulent environments worldwide. In fact, streams, sequences of decisions and resource commitments characterize the day-to-day of multinational companies (MNCs). Such decision-making activities encompass major strategic moves like internationalization and new market entries or diversification and acquisitions. In most companies, these strategic decisions are extensively discussed and debated and are generally framed, formulated, and articulated in specialized language often developed by the best minds in the company. Yet the language used in such deliberations, in detailing and enacting the implementation strategy is usually taken for granted and receives little if any explicit attention (Brannen & Doz, 2012) an can still be a “forgotten factor” (Marschan et al. 1997). Literature on language management and international business refers to lack of awareness of business managers of the impact that language can have not only in communication effectiveness but especially in knowledge transfer and knowledge management in business environments. In the context of MNCs, management is, for many different reasons, more complex and demanding than that of a national company, mainly because of diversity factors inherent to internationalization, namely geographical and cultural spaces, i.e, varied mindsets. Moreover, the way of functioning, and managing language, of the MNC depends on its vision, its values and its internationalization model, i.e on in the way the MNE adapts to and controls the new markets, which can vary essentially from a more ethnocentric to a more pluricentric focus. Regardless of the internationalization model followed by the MNC, communication between different business units is essential to achieve unity in diversity and business sustainability. For the business flow and prosperity, inter-subsidiary, intra-company and company-client (customers, suppliers, governments, municipalities, etc..) communication must work in various directions and levels of the organization. If not well managed, this diversity can be a barrier to global coordination and create turbulent environments, even if a good technological support is available (Feely et al., 2002: 4). According to Marchan-Piekkari (1999) the tongue can be both (i) a barrier, (ii) a facilitator and (iii) a source of power. Moreover, the lack of preparation for the barriers of linguistic diversity can lead to various costs, including negotiations’ failure and failure on internationalization.. On the other hand, communication and language fluency is not just a message transfer procedure, but above all a knowledge transfer process, which requires extra-linguistic skills (persuasion, assertiveness …) in order to promote credibility of both parties. For this reason, MNCs need a common code to communicate and trade information inside and outside the company, which will require one or more strategies, in order to overcome possible barriers and organization distortions.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

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.

Reflections on the legal framework for relations between cooperatives and subsidiaries.

In the light of Portuguese legal system, cooperative enterprises may include an enterprise carried out by a subsidiary, provided they conform to certain requirements. The aim of this paper is to reflect on the issue of the legal framework of the relationship between the cooperative and the subsidiary. There are several problems to be addressed in this paper: (i) How to qualify such a relationship since corresponding to mere investments made by the cooperative? Should it be classified as non-member cooperative transactions or as extraordinary activities? (ii) How to qualify such a relationship when related to the development of preparatory or complementary activities for the economic activity developed between the cooperative and its members? May we speak, in this situation, of a concept of “indirect mutuality”, as provided in other legal systems? (iii) How should we classify and what is the regime of the economic results from the activity developed by the subsidiary? We will conclude, advocating: (i) That the cooperative enterprise may include an enterprise carried out by a subsidiary if this is deemed necessary to satisfy the interests of the members; (ii) The inadmissibility of the concept of “indirect mutuality”; (iii) The inadequacy of qualifying the legal relationship between the cooperative partner (iv) The application, to the economic results coming from the activity developed by the subsidiary, of the regime provided for in the Portuguese Cooperative Code to the results from non-member cooperative transactions; (v) The economic results coming from the activity developed by the subsidiary cannot be appropriated by individual co-operators members, and so should be allocated to indivisible reserves.

Portal cd4+ and cd8+ t lymphocyte correlate to intensity of interface hepatitis in chronic hepatitis C

BACKGROUND: The pathogenesis of chronic hepatitis C is still a matter of debate. CD4+ and CD8+ T lymphocytes (TL) are typically observed within the portal and periportal spaces of affected livers, but their functional role in hepatitis C progression has not been fully elucidated. METHODS: CD4+ and CD8+ TL were quantified by immunohistochemistry in portal and periportal spaces of 39 liver biopsies from patients with chronic hepatitis C. They were associated to demographic data, histological parameters, laboratory findings of patients and hepatitis C genotypes. RESULTS: There was high numbers of CD4+ and CD8+ TL from which the density of CD4+ T was higher than CD8+ TL in portal and periportal spaces. CD4+ and CD8+ TL were directly correlated to intensity of interface hepatitis. CD8+ TL correlated to serum enzyme levels. CONCLUSION: The high numbers of CD4+ and CD8+ TL in portal and periportal spaces and their correlation to interface hepatitis suggest that hepatitis C evolution depends on the action of intrahepatic T lymphocytes, lending support to the notion of an immune-mediated mechanism in the pathogenesis of chronic hepatitis C.

Neurotoxic activity and ultrastructural changes in muscles caused by the brown widow spider Latrodectus geometricus venom

Brown widow spider (Latrodectus geometricus) venom (BrWSV) produces few local lesions and intense systemic reactions such as cramps, harsh muscle pains, nausea, vomiting and hypertension. Approximately 16 protein bands under reducing conditions and ~ 14 bands under non-reducing conditions on a 12.5% sodium dodecyl sulfate-polyacrylamide gel electrophoresis were observed. Neurotoxic clinical manifestations were confirmed in vivo, while proteolytic activity was demonstrated on gelatine film. Severe ultrastructural damages in mice skeletal muscles were observed at 3, 6, 12 and 24 h postinjection with at total of 45 µg of venom protein. Infiltration of eosinophils and ruptures of the cellular membranes were observed in the muscles along with swelling of the nuclear cover and interruption of the collagen periodicity. Altered mitochondrias and autophage vacuoles, nuclear indentation and mitochondria without cristae, slight increment of intermyofibrillar and subsarcolemic spaces and myelinic figures formation were also observed. In the capillary, endothelial membrane unfolding into the lumen was noticed; along with myelinic figures compatible with a toxic myopathy. Swollen sarcotubular systems with lysis of membrane, intense mitochondria autophagia and areas without pinocytic vesicles were observed. Swollen mitochondria surrounded by necrotic areas, myofibrillar disorganization and big vacuolas of the sarcotubular system, degenerated mitochondrium with formation of myelinic figure was seen. Glycogenosomes with small particulate, muscle type glycogen was noticed. Autophagic vacuole (autophagolysosomes) and necrotic areas were also noticed. These damages may be due to interactive effects of the multifactorial action of venom components. However, Latrodectus geometricus venom molecules may also be utilized as neuro therapeutic tools, as they affect neuronal activities with high affinity and selectivity. To our knowledge, the present study is the first ultrastructural report in the literature of muscle injuries and neurological and proteolytic activities caused by BrWSV.

Rational approximations of sectional category and Poincaré duality

Félix, Halperin, and Lemaire have shown that the rational module category Mcat and the rational Toomer invariant coincide for simply connected Poincaré duality complexes. We establish an analogue of this result for the sectional category of a fibration.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

On finite unions and finite products with the D-property

We show that the product of a subparacompact C-scattered space and a Lindelöf D-space is D. In addition, we show that every regular locally D-space which is the union of a finite collection of subparacompact spaces and metacompact spaces has the D-property. Also, we extend this result from the class of locally D-spaces to the wider class of D-scattered spaces. All the results are shown in a direct way.

Generalized descriptive set theory and classification theory

Descriptive set theory is mainly concerned with studying subsets of the space of all countable binary sequences. In this paper we study the generalization where countable is replaced by uncountable. We explore properties of generalized Baire and Cantor spaces, equivalence relations and their Borel reducibility. The study shows that the descriptive set theory looks very different in this generalized setting compared to the classical, countable case. We also draw the connection between the stability theoretic complexity of first-order theories and the descriptive set theoretic complexity of their isomorphism relations. Our results suggest that Borel reducibility on uncountable structures is a model theoretically natural way to compare the complexity of isomorphism relations.

Flow cytometry as a tool to identify Mycobacterium tuberculosis interaction with the immune system and drug susceptibility

Flow cytometric analysis is a useful and widely employed tool to identify immunological alterations caused by different microorganisms, including Mycobacterium tuberculosis. However, this tool can be used for several others analysis. We will discuss some applications for flow cytometry to the study of M. tuberculosis, mainly on cell surface antigens, mycobacterial secreted proteins, their interaction with the immune system using inflammatory cells recovered from peripheral blood, alveolar and pleura spaces and the influence of M. tuberculosis on apoptosis, and finally the rapid determination of drug susceptibility. All of these examples highlight the usefulness of flow cytometry in the study of M. tuber-culosis infection.

Influence of inter-electrode distance, contraction type, and muscle on the relationship between the sEMG power spectrum and contraction force.

INTRODUCTION: Spectral frequencies of the surface electromyogram (sEMG) increase with contraction force, but debate still exists on whether this increase is affected by various methodological and anatomical factors. This study aimed to investigate the influence of inter-electrode distance (IED) and contraction modality (step-wise vs. ramp) on the changes in spectral frequencies with increasing contraction strength for the vastus lateralis (VL) and vastus medialis (VM) muscles. METHODS: Twenty healthy male volunteers were assessed for isometric sEMG activity of the VM and VL, with the knee at 90° flexion. Subjects performed isometric ramp contractions in knee extension (6-s duration) with the force gradually increasing from 0 to 80 % MVC. Also, subjects performed 4-s step-wise isometric contractions at 10, 20, 30, 40, 50, 60, 70, and 80 % MVC. Interference sEMG signals were recorded simultaneously at different IEDs: 10, 20, 30, and 50 mm. The mean (F mean) and median (F median) frequencies and root mean square (RMS) of sEMG signals were calculated. RESULTS: For all IEDs, contraction modalities, and muscles tested, spectral frequencies increased significantly with increasing level of force up to 50-60 % MVC force. Spectral indexes increased systematically as IED was decreased. The sensitivity of spectral frequencies to changes in contraction force was independent of IED. The behaviour of spectral indexes with increasing contraction force was similar for step-wise and ramp contractions. CONCLUSIONS: In the VL and VM muscles, it is highly unlikely that a particular inter-electrode distance or contraction modality could have prevented the observation of the full extent of the increase in spectral frequencies with increasing force level.