Structure tensor total variation

This is the final version of the article. Available from Society for Industrial and Applied Mathematics via the DOI in this record.We introduce a novel generic energy functional that we employ to solve inverse imaging problems within a variational framework. The proposed regularization family, termed as structure tensor total variation (STV), penalizes the eigenvalues of the structure tensor and is suitable for both grayscale and vector-valued images. It generalizes several existing variational penalties, including the total variation seminorm and vectorial extensions of it. Meanwhile, thanks to the structure tensor’s ability to capture first-order information around a local neighborhood, the STV functionals can provide more robust measures of image variation. Further, we prove that the STV regularizers are convex while they also satisfy several invariance properties w.r.t. image transformations. These properties qualify them as ideal candidates for imaging applications. In addition, for the discrete version of the STV functionals we derive an equivalent definition that is based on the patch-based Jacobian operator, a novel linear operator which extends the Jacobian matrix. This alternative definition allow us to derive a dual problem formulation. The duality of the problem paves the way for employing robust tools from convex optimization and enables us to design an efficient and parallelizable optimization algorithm. Finally, we present extensive experiments on various inverse imaging problems, where we compare our regularizers with other competing regularization approaches. Our results are shown to be systematically superior, both quantitatively and visually

On Close Relationship between Classical Time-Dependent Harmonic Oscillator and Non-Relativistic Quantum Mechanics in One Dimension

In this paper, I present a mapping between representation of some quantum phenomena in one dimension and behavior of a classical time-dependent harmonic oscillator. For the first time, it is demonstrated that quantum tunneling can be described in terms of classical physics without invoking violations of the energy conservation law at any time instance. A formula is presented that generates a wide class of potential barrier shapes with the desirable reflection (transmission) coefficient and transmission phase shift along with the corresponding exact solutions of the time-independent Schr\"odinger's equation. These results, with support from numerical simulations, strongly suggest that two uncoupled classical harmonic oscillators, which initially have a 90\degree relative phase shift and then are simultaneously disturbed by the same parametric perturbation of a finite duration, manifest behavior which can be mapped to that of a single quantum particle, with classical 'range relations' analogous to the uncertainty relations of quantum physics.Comment: 20 pages, 8 figures, 1 table, final versio

Audio-assisted movie dialogue detection

An audio-assisted system is investigated that detects if a movie scene is a dialogue or not. The system is based on actor indicator functions. That is, functions which define if an actor speaks at a certain time instant. In particular, the crosscorrelation and the magnitude of the corresponding the crosspower spectral density of a pair of indicator functions are input to various classifiers, such as voted perceptrons, radial basis function networks, random trees, and support vector machines for dialogue/non-dialogue detection. To boost classifier efficiency AdaBoost is also exploited. The aforementioned classifiers are trained using ground truth indicator functions determined by human annotators for 41 dialogue and another 20 non-dialogue audio instances. For testing, actual indicator functions are derived by applying audio activity detection and actor clustering to audio recordings. 23 instances are randomly chosen among the aforementioned 41 dialogue instances, 17 of which correspond to dialogue scenes and 6 to non-dialogue ones. Accuracy ranging between 0.739 and 0.826 is reported

Audio-assisted movie dialogue detection

An audio-assisted system is investigated that detects if a movie scene is a dialogue or not. The system is based on actor indicator functions. That is, functions which define if an actor speaks at a certain time instant. In particular, the cross-correlation and the magnitude of the corresponding the cross-power spectral density of a pair of indicator functions are input to various classifiers, such as voted perceptions, radial basis function networks, random trees, and support vector machines for dialogue/non-dialogue detection. To boost classifier efficiency AdaBoost is also exploited. The aforementioned classifiers are trained using ground truth indicator functions determined by human annotators for 41 dialogue and another 20 non-dialogue audio instances. For testing, actual indicator functions are derived by applying audio activity detection and actor clustering to audio recordings. 23 instances are randomly chosen among the aforementioned 41 dialogue instances, 17 of which correspond to dialogue scenes and 6 to non-dialogue ones. Accuracy ranging between 0.739 and 0.826 is reported. © 2008 IEEE

Observation of T-2 Toxin and HT-2 Toxin Glucosides from Fusarium sporotrichioides by Liquid Chromatography Coupled to Tandem Mass Spectrometry (LC-MS/MS)

The trichothecenes produced by solid and liquid cultures of Fusarium sporotrichioides were evaluated with high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Along with the expected T-2 toxin HT-2 toxin and neosolaniol, two additional compounds were detected, which had ions 162 m/z higher than those in the mass spectra of T-2 toxin or HT-2 toxin. Fragmentation behavior of these two compounds was similar to that of T-2 toxin and HT-2 toxin. Based on LC-MS/MS behavior, it is proposed that the two compounds are T-2 toxin 3-O-glucoside and HT-2 toxin 3-O-glucoside. Production of the two glucosides was measured in kernels from wheat and oat inoculated with F. sporotrichiodes, as well as in cultures grown in liquid media and on cracked corn or rice. Production of glucosides in wheat and oats suggest that they may also be present in naturally contaminated cereals

Proteomic Analysis of Protein Expression and Oxidative Modification in R6/2 Transgenic Mice A Model of Huntington Disease

Huntington disease (HD) is a hereditary neurodegenerative disorder characterized by motor, psychiatric, and cognitive symptoms. The genetic defect responsible for the onset of the disease, expansion of CAG repeats in exon 1 of the gene that codes for huntingtin on chromosome 4, has been unambiguously identified. On the other hand, the mechanisms by which the mutation causes the disease are not completely understood yet. However, defects in energy metabolism of affected cells may cause oxidative damage, which has been proposed as one of the underlying molecular mechanisms that participate in the etiology of the disease. In our effort to investigate the extent of oxidative damage occurring at the protein level, we used a parallel proteomic approach to identify proteins potentially involved in processes upstream or downstream of the disease-causing huntingtin in a well established HD mouse model (R6/2 transgenic mice). We have demonstrated that the expression levels of dihydrolipoamide S-succinyltransferase and aspartate aminotransferase increase consistently over the course of disease (10-week-old mice). In contrast, pyruvate dehydrogenase expression levels were found to be decreased in 10-week-old HD transgenic mice compared with young (4-week-old) mice. Our experimental approach also led to the identification of oxidatively modified proteins. Six proteins were found to be significantly oxidized in old R6/2 transgenic mice compared with either young transgenic mice or non-transgenic mice. These proteins are alpha-enolase, gamma-enolase (neuron-specific enolase), aconitase, the voltage-dependent anion channel 1, heat shock protein 90, and creatine kinase. Because oxidative damage has proved to play an important role in the pathogenesis and the progression of Huntington disease, our results for the first time identify specific oxidatively modified proteins that potentially contribute to the pathogenesis of Huntington disease

Estrogen protects against the synergistic toxicity by HIV proteins, methamphetamine and cocaine

BACKGROUND: Human immunodeficiency virus (HIV) infection continues to increase at alarming rates in drug abusers, especially in women. Drugs of abuse can cause long-lasting damage to the brain and HIV infection frequently leads to a dementing illness.To determine how these drugs interact with HIV to cause CNS damage, we used an in vitro human neuronal culture characterized for the presence of dopaminergic receptors, transporters and estrogen receptors. We determined the combined effects of dopaminergic drugs, methamphetamine, or cocaine with neurotoxic HIV proteins, gp120 and Tat. RESULTS: Acute exposure to these substances resulted in synergistic neurotoxic responses as measured by changes in mitochondrial membrane potential and neuronal cell death. Neurotoxicity occurred in a sub-population of neurons. Importantly, the presence of 17beta-estradiol prevented these synergistic neurotoxicities and the neuroprotective effects were partly mediated by estrogen receptors. CONCLUSION: Our observations suggest that methamphetamine and cocaine may affect the course of HIV dementia, and additionally suggest that estrogens modify the HIV-drug interactions