994 resultados para Reestruturação industrial


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This study critically evaluates industrial relations (IR) in South-Eastern Europe and points towards future practical and research-oriented opportunities in the region. A survey of organizational policies and practices has been used to explore the state of IR in both private and public organizations in this region. Specifically, the data, collected in 2009–2010 (including the latest changes due to the economic crisis), cover 840 different organizations located in Slovenia, Serbia, Bulgaria, Greece and Cyprus. We discuss the development of ‘regional-specific’ IR policies, the ‘importing’ of varieties of capitalism models, the diffusion of the European Union social model and the role of foreign MNCs in changing IR in the region.

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Pseudomonas corrugata was first described as the causal agent of a tomato disease called 'pith necrosis' yet it is considered as a biological resource in various fields such as biocontrol of plant diseases and production of industrially promising microbial biopolymers (mcl-PHA). Here we report the first draft genome sequence of this species.

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This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects.

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This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects.

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Episodic explosive volcanic eruptions are a natural part of the climate system but are often omitted from atmosphere-ocean general circulation model (AOGCM) preindustrial spin-up and control experiments. This omission imposes a negative bias on ocean heat uptake in simulations of the historical period. In models of a range of complexity, we find that global-mean sea level rise due to thermal expansion during the last ∼ 150 years is consequently underestimated by 5–30 mm, which is a substantial proportion of the model mean of 50 mm in Coupled Model Intercomparison Project Phase 3 AOGCMs with anthropogenic forcing only, and is therefore important in accounting for 20th century sea level rise. We test and recommend a procedure for removing the bias.

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As new buildings are constructed in response to changes in technology or user requirements, the value of the existing stock will decline in relative terms. This is termed economic depreciation and it may be influenced by the age and quality of buildings, amount and timing of expenditure, and wider market and economic conditions. This study tests why individual assets experience different depreciation rates, applying panel regression techniques to 375 UK office and industrial assets. Results suggest that rental value depreciation rates reduce as buildings get older, while a composite measure of age and quality provides more explanation of depreciation than age alone. Furthermore, economic and local real estate market conditions are significant in explaining how depreciation rates change over time.

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Cistus is a plant genus traditionally used in folk medicine as remedy for several microbial disorders and infections. The abundance of Cistus spp. in the Iberian Peninsula together with their ability to renew after wildfire contribute to their profitability as suppliers of functional ingredients. The aim of this study was to provide a comprehensive characterization of the volatile profile of different Cistus plants grown in Spain:Cistus ladanifer L., Cistus albidus L., Cistus salviifolius L., and Cistus clusii Dunal (the latter has not been studied before). A system combining headspace solid-phase microextraction and gas chromatography coupled to mass spectrometry (HS-SPME-GC–MS) was implemented; thereby, the volatile compounds were extracted and analyzed in a fast, reliable and environment-friendly way. A total of 111 volatile compounds were identified, 28 of which were reported in Cistus for the first time. The most abundant components of the samples (mono and sesquiterpenes) have been previously reported as potent antimicrobial agents. Therefore, this work reveals the potential use of the Cistus spp. studied as natural sources of antimicrobial compounds for industrial production of cosmeceuticals, among other applications.

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We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.

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Pseudomonas corrugata was first described as the causal agent of a tomato disease called ‘pith necrosis’ yet it is considered as a biological resource in various fields such as biocontrol of plant diseases and production of industrially promising microbial biopolymers (mcl-PHA). Here we report the first draft genome sequence of this species.

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In the present study, the main focus was the characterization and application of the by-product lignin isolated through an industrial organosolv acid hydrolysis process from sugarcane bagasse, aiming at the production of bioethanol. The sugarcane lignin was characterized and used to prepare phenolic-type resins. The analysis confirmed that the industrial sugarcane lignin is of HGS type, with a high proportion of the less substituted aromatic ring p-hydroxyphenyl units, which favors further reaction with formaldehyde. The lignin-formaldehyde resins were used to produce biobased composites reinforced with different proportions of randomly distributed sisal fibers. The presence of lignin moieties in both the fiber and matrix increases their mutual affinity, as confirmed by SEM images, which showed good adhesion at the biocomposite fiber/matrix interface. This in turn allowed good load transference from the matrix to the fiber, leading to biobased composites with good impact strength (near 500 J m(-1) for a 40 wt% sisal fiber-reinforced composite). The study demonstrates that sugarcane bagasse lignin obtained from a bioethanol plant can be used without excessive purification in the preparation of lignocellulosic fiber-reinforced biobased composites displaying high mechanical properties. Biotechnol. Bioeng. 2010;107: 612-621. (C) 2010 Wiley Periodicals, Inc.

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Leaf fibers are fibers that run lengthwise through the leaves of most monocotyledonous plants such as pineapple, banana, etc. Pineapple (Ananas comosus) and Banana (Musa indica) are emerging fiber having a very large potential to be used for composite materials. Over 150,000 ha of pineapple and over 100,000 ha of banana plantations are available in Brazil for the fruit production and enormous amount of agricultural waste is produced. This residual waste represents one of the single largest sources of cellulose fibers available at almost no cost. The potential consumers for this fiber are pulp and paper, chemical feedstock, textiles and composites for the automotive, furniture and civil construction industry.