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We propose a two-step algorithm for almost unsupervised detection of linear structures, in particular, main axes in road networks, as seen in synthetic aperture radar (SAR) images. The first step is local and is used to extract linear features from the speckle radar image, which are treated as roadsegment candidates. We present two local line detectors as well as a method for fusing information from these detectors. In the second global step, we identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects. The influence of the parameters on the road detection is studied and results are presented for various real radar images. Index Terms-Markov random fields (MRF's), road detection, SAR images, statistical properties. NOMENCLATURE Number of looks of the radar image. Amplitude of pixel. Number of pixels in region. Empirical mean of region. Empirical variation coefficient of region. Exact mean-reflected intensity of region. , Exact and empirical contrasts between regions and. Ratio edge detector response between regions and. Ratio line detector (D1) response. Cross-correlation edge detector response between regions and. Cross-correlation line detector (D2) response. Decision threshold for variable. Probability-density function (pdf) of a random variable for value and parameter values. Cumulative distribution function of a random variable for value and parameter values .

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SUMMARYDespite availability of effective antiepileptic drugs (AEDs), many patients with epilepsy continue to experience refractory seizures and adverse events. Achievement of better seizure control and fewer side effects is key to improving quality of life. This review describes the rationale for the discovery and preclinical profile of brivaracetam (BRV), currently under regulatory review as adjunctive therapy for adults with partial-onset seizures. The discovery of BRV was triggered by the novel mechanism of action and atypical properties of levetiracetam (LEV) in preclinical seizure and epilepsy models. LEV is associated with several mechanisms that may contribute to its antiepileptic properties and adverse effect profile. Early findings observed a moderate affinity for a unique brain-specific LEV binding site (LBS) that correlated with anticonvulsant effects in animal models of epilepsy. This provided a promising molecular target and rationale for identifying selective, high-affinity ligands for LBS with potential for improved antiepileptic properties. The later discovery that synaptic vesicle protein 2A (SV2A) was the molecular correlate of LBS confirmed the novelty of the target. A drug discovery program resulted in the identification of anticonvulsants, comprising two distinct families of high-affinity SV2A ligands possessing different pharmacologic properties. Among these, BRV differed significantly from LEV by its selective, high affinity and differential interaction with SV2A as well as a higher lipophilicity, correlating with more potent and complete seizure suppression, as well as a more rapid brain penetration in preclinical models. Initial studies in animal models also revealed BRV had a greater antiepileptogenic potential than LEV. These properties of BRV highlight its promising potential as an AED that might provide broad-spectrum efficacy, associated with a promising tolerability profile and a fast onset of action. BRV represents the first selective SV2A ligand for epilepsy treatment and may add a significant contribution to the existing armamentarium of AEDs.

SUMMARYObjective: Rapid distribution to the brain is a prerequisite for antiepileptic drugs used for treatment of acute seizures. The preclinical studies described here investigated the high-affinity synaptic vesicle glycoprotein 2A (SV2A) antiepileptic drug brivaracetam (BRV) for its rate of brain penetration and its onset of action. BRV was compared with levetiracetam (LEV). Methods: In vitro permeation studies were performed using Caco-2 cells. Plasma and brain levels were measured over time after single oral dosing to audiogenic mice and were correlated with anticonvulsant activity. Tissue distribution was investigated after single dosing to rat (BRV and LEV) and dog (LEV only). Positron emission tomography (PET) displacement studies were performed in rhesus monkeys using the SV2A PET tracer [11 C]UCB-J. The time course of PET tracer displacement was measured following single intravenous (IV) dosing with LEV or BRV. Rodent distribution data and physiologically based pharmacokinetic (PBPK) modeling were used to compute blood-brain barrier permeability (permeability surface area product, PS) values and then predict brain kinetics in man. Results: In rodents, BRV consistently showed a faster entry into the brain than LEV; this correlated with a faster onset of action against seizures in audiogenic susceptible mice. The higher permeability of BRV was also demonstrated in human cells in vitro. PBPK modeling predicted that, following IV dosing to human subjects, BRV might distribute to the brain within a few minutes compared with approximately 1 h for LEV (PS of 0.315 and 0.015 ml/min/g for BRV and LEV, respectively). These data were supported by a nonhuman primate PET study showing faster SV2A occupancy by BRV compared with LEV. Significance: These preclinical data demonstrate that BRV has rapid brain entry and fast brain SV2A occupancy, consistent with the fast onset of action in the audiogenic seizure mice assay. The potential benefit of BRV for treatment of acute seizures remains to be confirmed in clinical studies.

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The purpose of this paper is to show that logic provides a convenient formalism for studying classical database problems. There are two main parts to the paper, devoted respectively to conventional databases and deductive databases. In the first part, we focus on query languages, integrity modeling and maintenance, query optimization, and data dependencies. The second part deals mainly with the representation and manipulation of deduced facts and incomplete information.