Discrete Green's methods and their application to two-dimensional phase unwrapping

A fully self-contained discrete framework with discrete equivalents of Stokes's, Gauss's, and Green's theorems is presented. The formulation is analogous to that of continuous operators, but totally discrete in nature, and the exact relationships derived are shown to hold provided that a set of predefined rules is followed in building discrete contours and domains. The method allows for an analytical rigor that is not guaranteed if one translates the classical continuous formulations onto a discretized approximated framework. We clarify several issues related to the use of discrete operators, which may play a crucial role in specific applications such as the two-dimensional phase-unwrapping problem, chosen as our main application example, and we show that reconstruction on irregular domains and/or in the presence of undersampling and noise is better formulated in the discrete framework than in the continuous domain.     

Off-axis measurements of atmospheric trace gases by use of an airborne ultraviolet-visible spectrometer

An airborne UV-visible spectrometer, the Gas Analyzer Spectrometer Correlating Optical Differences, airborne version (GASCOD/A4pi) was successfully operated during the Airborne Polar Experiment, Geophysica Aircraft in Antarctica airborne campaign from Ushuaia (54 degrees 49' S, 68 degrees 18' W), Argentina in southern spring 1999. The instrument measured scattered solar radiation through three optical windows with a narrow field of view (FOV), one from the zenith, two from the horizontal, as well as actinic fluxes through 2pi FOV radiometric heads. Only a few airborne measurements of scattered solar radiation at different angles from the zenith are available in the literature. With our configuration we attempted to obtain the average line-of-sight concentrations of detectable trace gases. The retrieval method, based on differential optical absorption spectroscopy, is described and results for ozone are shown and compared with measurements from an in situ instrument as the first method of validation.     

An Evolutionary Model of Endogenous Business Cycles

In this paper, we present an evolutionary model of industry dynamics yielding endogenous business cycles with ‘Keynesian’ features. The model describes an economy composed of firms and consumers/workers. Firms belong to two industries. The first one performs R&D and produces heterogeneous machine tools. Firms in the second industry invest in new machines and produce a homogenous consumption good. Consumers sell their labor and fully consume their income. In line with the empirical literature on investment patterns, we assume that the investment decisions by firms are lumpy and constrained by their financial structures. Moreover, drawing from behavioral theories of the firm, we assume boundedly rational expectation formation. Simulation results show that the model is able to deliver self-sustaining patterns of growth characterized by the presence of endogenous business cycles. The model can also replicate the most important stylized facts concerning micro- and macro-economic dynamics. Indeed, we find that investment is more volatile than GDP; consumption is less volatile than GDP; investment, consumption and change in stocks are procyclical and coincident variables; employment is procyclical; unemployment rate is anticyclical; firm size distributions are skewed but depart from log-normality; firm growth distributions are tent-shaped. JEL Classifications: C15, C22, C49, E17, E22, E32.     

A graph-based approach for extracting terminological properties from information sources with heterogeneous formats

The problem of handling both the integration and the cooperation of a large number of information sources characterised by heterogeneous representation formats is a challenging issue. In this context, a central role can be played by the knowledge about the semantic relationships holding between concepts belonging to different information sources (intersource properties). In this paper, we propose a semiautomatic approach for extracting two kinds of intersource properties, namely synonymies and homonymies, from heterogeneous information sources. In order to carry out the extraction task, we introduce both a conceptual model, for representing involved sources, and a metrics, for measuring the strength of the semantic relationships holding among concepts represented within the same source.     

Minority Games, Local Interactions, and Endogenous Networks

We study a local version of the Minority Game, where agents are placed on the nodes of a directed graph. Agents care about being in the minority of the group of agents they are currently linked to and employ myopic best-reply rules to choose their next-period state. We show that, in this benchmark case, the smaller the size of local networks, the larger long-run population-average payoffs. We then explore the collective behavior of the system when agents can: (i) assign weights to each link they hold and modify them over time in response to payoff signals; (ii) delete badly performing links (i.e., opponents) and replace them with randomly chosen ones. Simulations suggest that, when agents are allowed to weigh links but cannot delete/replace them, the system self-organizes into networked clusters that attain very high payoff values. These clustered configurations are not stable and can easily be disrupted, generating huge subsequent payoff drops. If, however, agents can (and are sufficiently willing to) discard badly performing connections, the system quickly converges to stable states where all agents get the highest payoff, independently of the size of the networks initially in place.JEL Classification:s C72, C73.     

Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands

Bio-optical algorithms for remote estimation of chlorophyll-a concentration (Chl) in case-1 waters exploit the upwelling radiation in the blue and green spectral regions. In turbid productive waters other constituents, that vary independently of Chl, absorb and scatter light in these spectral regions. As a consequence, the accurate estimation of Chl in turbid productive waters has so far not been feasible from satellite sensors. The main purpose of this study was to evaluate the extent to which near-infrared (NIR) to red reflectance ratios could be applied to the Sea Wide Field-of-View Sensor (SeaWiFS) and the Moderate Imaging Spectrometer (MODIS) to estimate Chl in productive turbid waters. To achieve this objective, remote-sensing reflectance spectra and relevant water constituents were collected in 251 stations over lakes and reservoirs with a wide variability in optical parameters (i.e. 4 ≤ Chl ≤ 240 mg m^− 3; 18 ≤ Secchi disk depth ≤ 308 cm). SeaWiFS and MODIS NIR and red reflectances were simulated by using the in-situ hyperspectral data. The proposed algorithms predicted Chl with a relative random uncertainty of approximately 28% (average bias between − 1% and − 4%). The effects of reflectance uncertainties on the predicted Chl were also analyzed. It was found that, for realistic ranges of R_rs uncertainties, Chl could be estimated with a precision better than 40% and an accuracy better than ± 35%. These findings imply that, provided that an atmospheric correction scheme specific for the red-NIR spectral region is available, the extensive database of SeaWiFS and MODIS images could be used to quantitatively monitor Chl in turbid productive waters.     

On the design of efficient ATM routing schemes

In this paper we deal with the problem of designing virtual path layouts in ATM networks when the hop-count is given and the load has to be minimized. We first prove a lower bound for networks with arbitrary topology and arbitrary set of connection requests. This result is then applied to derive lower bounds for the following settings: (i) one-to-all (one node has to be connected to all other nodes of the network) in arbitrary networks; (ii) all-to-all (each node has to be connected to all other nodes in the network) in several classes of networks, including planar and k-separable networks and networks of bounded genus. We finally study the all-to-all setting on two-dimensional meshes and we design a virtual path layout for this problem. When the hop-count and the network degree are bounded by constants, our results show that the upper bounds proposed in this paper for the one-to-all problem in arbitrary networks and for the all-to-all problem in two-dimensional mesh networks are asymptotically optimal. Moreover, the general lower bound shows that the algorithm proposed in Gerstel (Ph.D. Thesis, Technion-Haifa, Israel, 1995) for the all-to-all problem in k-separable networks is also asymptotically optimal. The upper bound for mesh networks also shows that the lower bound presented in this paper for the all-to-all problem in planar networks is asymptotically tight.     

Effects of different doses of apomorphine on the glutamate decarboxylase activity of the substantia nigra and the medial basal hypothalamus

The activity of gamma-aminobutyric acid (GABA) synthesizing enzyme glutamic acid decarboxylase (GAD, EC 4.1.1.15) was assayed in the rat substantia nigra (SN) and medial basal hypothalamus (MBH) following systemic injection of different doses of the dopamine receptor agonist apomorphine. In SN, the highest dose of apomorphine (1000 micrograms/kg) causes an increase of the GAD activity whilst an opposite effect is observed with the lowest dose (35 micrograms/kg). Results obtained in SN are in accordance with previous neurochemical and behavioural data suggesting an opposite action of high (500 micrograms/kg) and low doses (100 micrograms/kg) of apomorphine in nigro-striatal system, probably due to the existence of two classes of dopamine receptors, i.e. classical postsynaptic dopamine receptors and presynaptic inhibitory dopamine autoreceptors. In MBH, the evidence for similar effects of low and high doses of apomorphine (the decrease of GAD activity) may suggest that, as already reported, at this level only one class of dopamine receptors is present.     

Application of multi-way models to the time-resolved fluorescence of polycyclic aromatic hydrocarbons mixtures in water

The time-resolved laser-induced fluorescence of a series of polycyclic aromatic compounds (PAHs) and mixtures of these latter in aqueous solution was measured by means of an apparatus equipped with optical fibers, which allows their real time in situ monitoring. The potential of such spectroscopic technique, yielding 4-way fluorescence data arrays, together with the application of multi-way models to the matricized data, was tested for the resolution of complex aqueous mixtures containing low concentrations of PAHs, as typical fluorescent pollutants in aquatic systems. PARAllel FACtors analysis was employed for the qualitative resolution of PAHs mixtures and for calculating the fluorescence lifetimes of single PAHs; n-way partial least squares analysis was applied for evaluating the concentration of the single PAHs in the aqueous mixtures.     

Integrated methodology for forensic oil spill identification

A new integrated methodology for forensic oil spill identification is presented. It consists of GC-MS analysis, chromatographic data processing, variable-outlier detection, multivariate data analysis, estimation of uncertainties, and statistical evaluation. The methodology was tested on four groups of diagnostic ratios composed of petroleum biomarkers and ratios within homologous PAH categories. Principal component analysis (PCA) was employed and enabled the simultaneous analysis of many diagnostic ratios. Weathering was taken into account by considering the sampling uncertainties estimated from replicate spill samples. Statistical evaluation ensured an objective matching of oil spill samples with suspected source oils as well as classification into positive match, probable match, and nonmatch. The data analysis is further refined if two or more source oils are classified as probable match by using weighted least squares fitting of the principal components, local PCA models, and additional information relevant to the spill case. The methodology correctly identified the source of two spill samples (i.e., crude oils from Oseberg East and Oseberg Field Centre) and distinguished them from closely related source oils.