Fiscal multipliers in a two-sector search and matching model

This paper evaluates the effects of policy interventions on sectoral labour markets and the aggregate economy in a business cycle model with search and matching frictions. We extend the canonical model by including capital-skill complementarity in production, labour markets with skilled and unskilled workers and on-the-job-learning (OJL) within and across skill types. We first find that, the model does a good job at matching the cyclical properties of sectoral employment and the wage-skill premium. We next find that vacancy subsidies for skilled and unskilled jobs lead to output multipliers which are greater than unity with OJL and less than unity without OJL. In contrast, the positive output effects from cutting skilled and unskilled income taxes are close to zero. Finally, we find that the sectoral and aggregate effects of vacancy subsidies do not depend on whether they are financed via public debt or distorting taxes.

The antecedents and innovation consequences of organizational search: empirical evidence for Spain

This paper examines the antecedents and innovation consequences of the methods firms adopt in organizing their search strategies. From a theoretical perspective, organizational search is described using a typology that shows how firms implement exploration and exploitation search activities that span their organizational boundaries. This typology includes three models of implementation: ambidextrous, specialized, and diversified implementation. From an empirical perspective, the paper examines the performance consequences when applying these models, and compares their capacity to produce complementarities. Additionally, since firms' choices in matters of organizational search are viewed as endogenous variables, the paper examines the drivers affecting them and identifies the importance of firms' absorptive capacity and diversified technological opportunities in determining these choices. The empirical design of the paper draws on new data for manufacturing firms in Spain, surveyed between 2003 and 2006.

The rational search for natural neolignans

A rational method of search for natural neolignans of desired structures is outlined. This involves consultation of a collection of chemical profiles of plant families. The profiles are assembled considering the biosynthetic class (in the present case lignoids), subclass (neolignans), structural types (neolignan skeleta) and relative frequency of substitutional derivatives belonging to each type (known compounds). The method is of course applicable to ani class of natural products. Its use in the case of neolignans is here selected as an exemple in view of the recently discovered antagonism towards PAF of kadsurenone, a representative of this subclass of phytochemicals. Application of the chemical profiles to phylogenetic studies is illustrated.

Chemical and pharmacological investigation of Solanum species of Brazil: a search for solasodine and other potentially useful therapeutic agents

A systematic search for solasodine, an important staring material for the partial synthesis of steroidal hormones as well as other potentially bioactive constituents of various Solanum species of Brazil has been undertaken. Thus, the fruits of S. paludosum, S. asperum, S. sessiliforum and Solanum sp. were found to contain significant amounts of solasodine. The root bark of S. paludosum which showe durare like activity yelded tomatidenol and another yet unidentified alkaloid responsible for the biological activity. The fruits of S. asperum yelded a new spirosolane alkaloid, solaparnaine. The stem bark of S. pseudo-quina showed convulsive and exitatory activity from which (25S)-isosolafloridine was identified as the active principle. In addition, the latter alkaloid was also found to show antimicrobial activity.

Some variational problems from image processing

"Vegeu el resum a l'inici del document del fitxer adjunt."

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Détectabilité extra-fovéale sur des images anatomiques

Contexte¦- Les métastases hépatiques hypovasculaires sont parfois difficile à détecter car très polymorphiques et fréquemment irrégulières. Leurs contrastes sur CT scan hépatique sont souvent faibles.¦- Lors d'un diagnostic, le radiologue ne fixe pas sa vision fovéale sur chaque pixel de l'image. Les expériences de psychophysique avec eye-tracker montrent en effet que le radiologue se concentre sur quelques points spécifiques de l'image appelés fixations. Dans ce travail, nous nous intéresserons aux capacités de détection de l'oeil lorsque l'observateur effectue une saccade entre deux points de fixation. Plus particulièrement, nous nous intéresserons à caractériser les capacités de l'oeil à détecter les signaux se trouvant en dehors de sa vision fovéale, dans ce qu'on appelle, la vision périphérique.¦Objectifs¦- Caractériser l'effet de l'excentricité de la vision sur la détectabilité des contrastes dans le cas de métastases hépatiques hypovasculaires.¦- Récolter des données expérimentales en vue de créer un modèle mathématique qui permettra, à terme, de qualifier le système d'imagerie.¦- → objectifs du TM en soit :¦o prendre en main l'eyetracker¦o traduire une problématique médicale en une expérience scientifique reproductible, quantifiable et qualifiable.¦Méthode¦Nous effectuons une expérience 2AFC (2 Alternative Forced-Choice experiment) afin d'estimer la détectabilité du signal. Pour cela, nous forcerons l'observateur à maintenir son point de fixation à un endroit défini et vérifié par l'eye-tracker. La position del'excentricité du signal tumoral généré sur une coupe de CT hépatique sera le paramètre varié. L'observateur se verra présenté tour à tour deux coupes de CT hépatique, l'une comportant le signal tumoral standardisé et l'autre ne comportant pas le signal. L'observateur devra déterminer quelle image contient la pathologie avec la plus grande probabilité.¦- Cette expérience est un modèle simplifié de la réalité. En effet, le radiologue ne fixe pas un seul point lors de sa recherche mais effectue un "scanpath". Une seconde expérience, dite en free search sera effectuée dans la mesure du temps à disposition. Lors de cette expérience, le signal standardisé sera connu de l'observateur et il n'y aura plus de point de fixation forcée. L'eyetracker suivra le scanpath effectué par l'oeil de l'observateur lors de la recherche du signal sur une coupe de CT scan hépatique. L'intérêt de cette expérience réside dans l'observation de la corrélation entre les saccades et la découverte du signal. Elle permet aussi de vérifier les résultats obtenus lors de la première expérience.¦Résultats escomptés¦- Exp1 : Quantifier l'importance de l'excentricité en radiologie et aider à améliorer la performance de recherche.¦- Exp 2 : tester la validité des résultats obtenus par la première expérience.¦Plus value escomptée¦- Récolte de données pour créer un modèle mathématique capable de déterminer la qualité de l'image radiologique.¦- Possibilité d'extension à la recherche dans les trois dimensions du CT scan hépatique.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

L'image de la Suisse à l'étranger

L'image qu'un pays a dans le monde est importante à plusieurs titres. Elle peut soutenir la commercialisation de biens et de services exportés, elle revêt un caractère tout particulier dans le cadre des promotions touristique et économique et elle peut aussi être de nature à contribuer aux relations qu'un pays entretient avec d'autres pays aux niveaux politique, économique ou culturel. L'image de la Suisse a fait l'objet d'études dans de nombreux pays, dont les Etats-Unis, l'Allemagne et la Chine, auprès d'échantillons représentatifs de la population ainsi qu'auprès de groupes de leaders d'opinion et cet ouvrage présente de manière synthétique les principaux résultats de ces études. Après une description de l'image globale de la Suisse auprès des personnes interrogées et une analyse des associations faites à l'évocation de la Suisse, une partie importante est consacrée aux dimensions qui caractérisent l'image du pays en différenciant notamment entre les dimensions liées à la Suisse en tant qu'espace socioculturel et les dimensions liées aux aspects économiques. Pour terminer, un dernier chapitre analyse l'impact de faits ayant marqué l'actualité helvétique, comme le grounding de Swissair, sur l'image de la Suisse dans les pays étudiés.

Using a NPWE model observer to assess suitable image quality for a digital mammography quality assurance programme.

A method of objectively determining imaging performance for a mammography quality assurance programme for digital systems was developed. The method is based on the assessment of the visibility of a spherical microcalcification of 0.2 mm using a quasi-ideal observer model. It requires the assessment of the spatial resolution (modulation transfer function) and the noise power spectra of the systems. The contrast is measured using a 0.2-mm thick Al sheet and Polymethylmethacrylate (PMMA) blocks. The minimal image quality was defined as that giving a target contrast-to-noise ratio (CNR) of 5.4. Several evaluations of this objective method for evaluating image quality in mammography quality assurance programmes have been considered on computed radiography (CR) and digital radiography (DR) mammography systems. The measurement gives a threshold CNR necessary to reach the minimum standard image quality required with regards to the visibility of a 0.2-mm microcalcification. This method may replace the CDMAM image evaluation and simplify the threshold contrast visibility test used in mammography quality.