Machine learning paradigms for modeling spatial and temporal information in multimedia data mining

Multimedia data mining and knowledge discovery is a fast emerging interdisciplinary applied research area. There is tremendous potential for effective use of multimedia data mining (MDM) through intelligent analysis. Diverse application areas are increasingly relying on multimedia under-standing systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors. The main mission of this special issue is to identify state-of-the-art machine learning paradigms that are particularly powerful and effective for modeling and combining temporal and spatial media cues such as audio, visual, and face information and for accomplishing tasks of multimedia data mining and knowledge discovery. These models should be able to bridge the gap between low-level audiovisual features which require signal processing and high-level semantics. A number of papers have been submitted to the special issue in the areas of imaging, artificial intelligence; and pattern recognition and five contributions have been selected covering state-of-the-art algorithms and advanced related topics. The first contribution by D. Xiang et al. “Evaluation of data quality and drought monitoring capability of FY-3A MERSI data” describes some basic parameters and major technical indicators of the FY-3A, and evaluates data quality and drought monitoring capability of the Medium-Resolution Imager (MERSI) onboard the FY-3A. The second contribution by A. Belatreche et al. “Computing with biologically inspired neural oscillators: application to color image segmentation” investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to gray scale and color image segmentation, an important task in image understanding and object recognition. The major contribution of this paper is the ability to use neural oscillators as a learning scheme for solving real world engineering problems. The third paper by A. Dargazany et al. entitled “Multibandwidth Kernel-based object tracking” explores new methods for object tracking using the mean shift (MS). A bandwidth-handling MS technique is deployed in which the tracker reach the global mode of the density function not requiring a specific staring point. It has been proven via experiments that the Gradual Multibandwidth Mean Shift tracking algorithm can converge faster than the conventional kernel-based object tracking (known as the mean shift). The fourth contribution by S. Alzu’bi et al. entitled “3D medical volume segmentation using hybrid multi-resolution statistical approaches” studies new 3D volume segmentation using multiresolution statistical approaches based on discrete wavelet transform and hidden Markov models. This system commonly reduced the percentage error achieved using the traditional 2D segmentation techniques by several percent. Furthermore, a contribution by G. Cabanes et al. entitled “Unsupervised topographic learning for spatiotemporal data mining” proposes a new unsupervised algorithm, suitable for the analysis of noisy spatiotemporal Radio Frequency Identification (RFID) data. The new unsupervised algorithm depicted in this article is an efficient data mining tool for behavioral studies based on RFID technology. It has the ability to discover and compare stable patterns in a RFID signal, and is appropriate for continuous learning. Finally, we would like to thank all those who helped to make this special issue possible, especially the authors and the reviewers of the articles. Our thanks go to the Hindawi staff and personnel, the journal Manager in bringing about the issue and giving us the opportunity to edit this special issue

Vortex charges in high-temperature superconductors

The vortex charge in high-temperature superconductors was investigated. It was found that the vortex charge was negative when a sufficient strength of antiferromagnetic (AF) order was induced inside the vortex core. The vortex charge at optimal doping was studied as a function of magnetic field. The results showed that the AF order was absent inside the vortex core for small Coulomb repulsion.published_or_final_versio

Ginzburg-Landau equations for layered p-wave superconductors

Based on Gor'kov's theory of weakly coupled superconductors, the Ginzburg-Landau equations for layered p-wave superconductors are derived, the order parameter of which is assumed to belong to a nontrivial two-dimensional representation. This calculation allows us to microscopically determine the expansion coefficients of the Ginzburg-Landau free-energy functional with respect to the order parameter. The main feature of the vortex solution is briefly discussed. It is found that the extreme condition for the nonaxisymmetric singly quantized vortices is not ensured in the weak-coupling limit. If the discrete crystal symmetry is included, the axisymmetric singly quantized vortex is stable. In addition, the upper critical field is also solely determined within the weak-coupling framework.published_or_final_versio

Characterization of carbohydrate fractions and fermentation quality in ensiled alfalfa treated with different additives

This experiment was carried out to evaluate the effects of adding fast-sile (FS), previous fermented juice (PFJ), sucrose (S) or fast-sile + sucrose (FS + S) on the fermentation characteristics and carbohydrates fractions of alfalfa silages by the Cornell net carbohydrates and proteins systems (CNCPS). Silages quality were well preserved determined by pH, lactic acid (LA), acetic acid (AA), propionic acid (PA), butyric acid (BA) and (NH3-N, % of TN). Except for the silage with no addition of (CK), all other silages were well preserved. FS + S addition showed the lowest pH and contents of AA, PA, BA, and the highest contents of LA. The contents of WSC (Water soluble carbohydrate) in all alfalfa silages decreased with the extension of ensiling time, especially in the former 15 days and decreased sharply in the first 2 days. The content of sucrose in all alfalfa silages in the residual mono and disaccharides was highest, and the content of fructose was the least. The contents of all these sugars decreased sharply in the first 2 days. The content of hemicellulose decreased during ensiling, while no obvious change on content of cellulose. The content of ADL (acid detergent lignin) in alfalfa silages increased during ensiling. The content of starch in silages reduced rapidly in the former days, and then had not obvious change.Key words: Carbohydrate fractions, alfalfa silage, additives, water soluble carbohydrate (WSC)

T-Bet and Eomes Regulate the Balance between the Effector/Central Memory T Cells versus Memory Stem Like T Cells

Memory T cells are composed of effector, central, and memory stem cells. Previous studies have implicated that both T-bet and Eomes are involved in the generation of effector and central memory CD8 T cells. The exact role of these transcription factors in shaping the memory T cell pool is not well understood, particularly with memory stem T cells. Here, we demonstrate that both T-bet or Eomes are required for elimination of established tumors by adoptively transferred CD8 T cells. We also examined the role of T-bet and Eomes in the generation of tumor-specific memory T cell subsets upon adoptive transfer. We showed that combined T-bet and Eomes deficiency resulted in a severe reduction in the number of effector/central memory T cells but an increase in the percentage of CD62LhighCD44low Sca-1+ T cells which were similar to the phenotype of memory stem T cells. Despite preserving large numbers of phenotypic memory stem T cells, the lack of both of T-bet and Eomes resulted in a profound defect in antitumor memory responses, suggesting T-bet and Eomes are crucial for the antitumor function of these memory T cells. Our study establishes that T-bet and Eomes cooperate to promote the phenotype of effector/central memory CD8 T cell versus that of memory stem like T cells. © 2013 Li et al

Quasiparticle resonant states induced by a unitary impurity in a d-wave superconductor

Journals published by the American Physical Society can be found at http://journals.aps.org/The quasiparticle resonant states around a single nonmagnetic impurity with unitary scattering in a d-wave superconductor is studied by solving the Bogoliubov-de Gennes equations based on a t-J model. Both the spatial variation of the order parameter and the local density of states (LDOS) around the impurity have been investigated. We find that (i) a particle-hole symmetric system has a single symmetric zero-energy peak in the LDOS regardless of the size of the superconducting coherence length xi(0); (ii) for the particle-hole asymmetric case, an asymmetric splitting of the zero-energy peak is intrinsic to a system with a small value of k(F)xi(0)

Identification of Lactoferricin B Intracellular Targets Using an Escherichia coli Proteome Chip

Lactoferricin B (LfcinB) is a well-known antimicrobial peptide. Several studies have indicated that it can inhibit bacteria by affecting intracellular activities, but the intracellular targets of this antimicrobial peptide have not been identified. Therefore, we used E. coli proteome chips to identify the intracellular target proteins of LfcinB in a high-throughput manner. We probed LfcinB with E. coli proteome chips and further conducted normalization and Gene Ontology (GO) analyses. The results of the GO analyses showed that the identified proteins were associated with metabolic processes. Moreover, we validated the interactions between LfcinB and chip assay-identified proteins with fluorescence polarization (FP) assays. Sixteen proteins were identified, and an E. coli interaction database (EcID) analysis revealed that the majority of the proteins that interact with these 16 proteins affected the tricarboxylic acid (TCA) cycle. Knockout assays were conducted to further validate the FP assay results. These results showed that phosphoenolpyruvate carboxylase was a target of LfcinB, indicating that one of its mechanisms of action may be associated with pyruvate metabolism. Thus, we used pyruvate assays to conduct an in vivo validation of the relationship between LfcinB and pyruvate level in E. coli. These results showed that E. coli exposed to LfcinB had abnormal pyruvate amounts, indicating that LfcinB caused an accumulation of pyruvate. In conclusion, this study successfully revealed the intracellular targets of LfcinB using an E. coli proteome chip approach

Zika Virus Infection in Dexamethasone-immunosuppressed Mice Demonstrating Disseminated Infection with Multi-organ Involvement Including Orchitis Effectively Treated by Recombinant Type I Interferons

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