Institutional conditions for effective and legitimate industrial policies: the case of Portugal

State intervention in support of specific productive activities aiming to foster structural change (i.e., industrial policy) has been a controversial topic in both academic and political debates. In spite of many years of theoretical and empirical research, such debate has not reached definite conclusions. Recently, the debate on industrial policy has been experiencing a change of focus, falling away from the rationale of such public interventions to focus on the institutional conditions that promote the success of the policies pursued. In this paper we analyse the conditions for effective and legitimate industrial policies, examining four cases of such type of interventions in Portugal. Our analysis emphasises the differences between the various interventions according to two dimensions: the number of (potential) beneficiaries targeted by the policy and the diversity of public agencies in possession of relevant skills for its implementation. These factors help to determine the level of scrutiny to which public policies are subjected, either by private actors or within the State apparatus. Both sources of scrutiny help to minimise the risks of capture of public resources by private interests, and to foster institutional learning processes that promote the effectiveness of policies.FCT

Rheo-NMR velocimetry characterisation of PBLG/m-cresol

NMR spectroscopy was used to characterise the velocity profile in nematic solutions of poly(gamma-benzyl-L-glutamate) (PBLG) in m-cresol during the application of a simple shear-flow at constant shear-rate values. In this study, the rheo-NMR technique was used that allows an insight over the fluid dynamics during the application of a shear flow in the presence of an external magnetic field, in a perpendicular direction to the shear gradient. Using this Magnetic Resonance Imaging (MRI) based technique, the velocity profile developed inside the system is accessed.info:eu-repo/semantics/publishedVersio

Critical fluctuations and random-anisotropy glass transition in nematic elastomers

We carry out a detailed deuterium NMR study of local nematic ordering in polydomain nematic elastomers. This system has a close analogy to the random-anisotropy spin glass. We find that, in spite of the quadrupolar nematic symmetry in 3-dimensions requiring a first-order transition, the order parameter in the quenched ``nematic glass'' emerges via a continuous phase transition. In addition, by a careful analysis of the NMR line shape, we deduce that the local director fluctuations grow in a critical manner around the transition point. This could be the experimental evidence for the Aizenman-Wehr theorem about the quenched impurities changing the order of discontinuous transition

Water quality assessment of Portuguese streams: Regional or national predictive models?

http://www.sciencedirect.com/science/article/B6W87-4TY8WB4-2/2/5bab94f8490387f7a8da832e49003d6

Amphibia, Anura, Hylidae, <i>Sphaenorhynchus botocudo</i> Caramaschi, Almeida and Gasparini, 2009: First state record and first record out of the type locality

This study presents the first record of the recently-described Lime Treefrog Sphaenorhynchus botocudoCaramaschi, Almeida, and Gasparini, 2009 in the state of Bahia, and the first record out of its type locality

Multi-biologic group analysis for an ecosystem response to longitudinal river regulation gradients

This work assesses the effects of river regulation on the diversity of different instream and riparian biological communities along a relieve gradient of disturbance in regulated rivers. Two case studies in Portugal were used, with different river regulation typology (downstream of run-of-river and reservoir dams), where regulated and free-flowing river stretches were surveyed for riparian vegetation, macrophytes, bryophytes, macroalgae, diatoms and macroinvertebrates. The assessment of the regulation effects on biological communities was approached by both biological and functional diversity analysis. Results of this investigation endorse river regulation as a major factor differentiating fluvial biological communities through an artificial environmental filtering that governs species assemblages by accentuating species traits related to river regulation tolerance. Communities' response to regulation gradient seem to be similar and insensitive to river regulation typology. Biological communities respond to this regulation gradient with different sensibilities and rates of response, with riparian vegetation and macroinvertebrates being the most responsive to river regulation and its gradient. Richness appears to be the best indicator for general fluvial ecological quality facing river regulation. Nevertheless, there are high correlations between the biological and functional diversity indices of different biological groups, which denotes biological connections indicative of a cascade of effects leading to an indirect influence of river regulation even on non-responsive facets of communities' biological and functional diversities. These results highlight the necessary holistic perspective of the fluvial system when assessing the effects of river regulation and the proposal of restoration measures.publishe

Prediction of bioactive compounds activity against wood contaminant fungi using artificial neural networks

Biopesticides based on natural endophytic bacteria to control plant diseases are an ecological alternative to the chemical treatments. Bacillus species produce a wide variety of metabolites with biological activity like iturinic lipopeptides. This work addresses the production of biopesticides based on natural endophytic bacteria, isolated from Quercus suber. Artificial Neural Networks were used to maximize the percentage of inhibition triggered by antifungal activity of bioactive compounds produced by Bacillus amyloliquefaciens. The active compounds, produced in liquid cultures, inhibited the growth of fifteen fungi and exhibited a broader spectrum of antifungal activity against surface contaminant fungi, blue stain fungi and phytopathogenic fungi. A 19-7-6-1 neural network was selected to predict the percentage of inhibition produced by antifungal bioactive compounds. A good match among the observed and predicted values was obtained with the R2 values varying between 0.9965 – 0.9971 and 0.9974 – 0.9989 for training and test sets. The 19-7-6-1 neural network was used to establish the dilution rates that maximize the production of antifungal bioactive compounds, namely 0.25 h-1 for surface contaminant fungi, 0.45 h-1 for blue stain fungi and between 0.30 and 0.40 h-1 for phytopathogenic fungi. Artificial neural networks show great potential in the modelling and optimization of these bioprocesses.Les biopesticides à base de bactéries endophytes naturelles pour lutter contre les maladies des plantes constituent une alternative écologique aux traitements chimiques. Les espèces de Bacillus produisent une grande variété de métabolites biologiquement actifs tels que les lipopeptides ituriniques. Cette étude porte sur la production de biopesticides par des bactéries endophytes naturelles isolées du Quercus suber L. Des réseaux neuronaux artificiels ont été utilisés pour maximiser le pourcentage d’inhibition provoquée par l’activité antifongique des composés bioactifs produits par Bacillus amyloliquefaciens. Les composés actifs, produits en culture liquide, ont inhibé la croissance de 15 champignons et avaient un spectre d’activé antifongique plus large contre les contaminants fongiques de surface, les champignons de bleuissement et les champignons phytopathogènes. Un réseau neuronal 19-7-6-1 a été choisi pour prédire le pourcentage d’inhibition produit par les composés bioactifs antifongiques. Une bonne concordance entre les valeurs observées et prédites a été obtenue; les valeurs de R2 variaient de 0,9965 a` 0,9971 et de 0,9974 a` 0,9989 pour les bases d’apprentissage et de test. Le réseau neuronal 19-7-6-1 a été utilisé pour établir les taux de dilution qui maximisent la production des composés bioactifs antifongiques, nommément 0,25 h−1 pour les contaminants fongiques de surface, 0,45 h−1 pour les champignons de bleuissement et entre 0,30 et 0,40 h−1 pour les champignons phytopathogènes. Les réseaux neuronaux artificiels ont un potentiel élevé pour modéliser et optimiser ces processus biologiques