Quantum states for perfectly secure secret sharing

In this work, we investigate what kinds of quantum states are feasible to perform perfectly secure secret sharing, and present its necessary and sufficient conditions. We also show that the states are bipartite distillable for all bipartite splits, and hence the states could be distillable into the Greenberger-Horne-Zeilinger state. We finally exhibit a class of secret-sharing states, which have an arbitrarily small amount of bipartite distillable entanglement for a certain split.Comment: 4 page

Vacuum ultraviolet photoabsorption spectra of nitrile ices for their identification on Pluto

Icy bodies, such as Pluto, are known to harbor simple and complex molecules. The recent New Horizons flyby of Pluto has revealed a complex surface composed of bright and dark ice surfaces, indicating a rich chemistry based on nitrogen (N2), methane (CH4), and carbon monoxide (CO). Nitrile (CN) containing molecules such as acetonitrile (CH3CN), propionitrile (CH3CH2CN), butyronitrile (CH3CH2CH2CN), and isobutyronitrile ((CH3)2CHCN) are some of the nitrile molecules that are known to be synthesized by radiative processing of such simple ices. Through the provision of a spectral atlas for such compounds we propose that such nitriles may be identified from the ALICE payload on board New Horizons</i

Feature extraction based on bio-inspired model for robust emotion recognition

Emotional state identification is an important issue to achieve more natural speech interactive systems. Ideally, these systems should also be able to work in real environments in which generally exist some kind of noise. Several bio-inspired representations have been applied to artificial systems for speech processing under noise conditions. In this work, an auditory signal representation is used to obtain a novel bio-inspired set of features for emotional speech signals. These characteristics, together with other spectral and prosodic features, are used for emotion recognition under noise conditions. Neural models were trained as classifiers and results were compared to the well-known mel-frequency cepstral coefficients. Results show that using the proposed representations, it is possible to significantly improve the robustness of an emotion recognition system. The results were also validated in a speaker independent scheme and with two emotional speech corpora.Fil: Albornoz, Enrique Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

Disposition of Federally Owned Surpluses

PDZ domains are scaffolding modules in protein-protein interactions that mediate numerous physiological functions by interacting canonically with the C-terminus or non-canonically with an internal motif of protein ligands. A conserved carboxylate-binding site in the PDZ domain facilitates binding via backbone hydrogen bonds; however, little is known about the role of these hydrogen bonds due to experimental challenges with backbone mutations. Here we address this interaction by generating semisynthetic PDZ domains containing backbone amide-to-ester mutations and evaluating the importance of individual hydrogen bonds for ligand binding. We observe substantial and differential effects upon amide-to-ester mutation in PDZ2 of postsynaptic density protein 95 and other PDZ domains, suggesting that hydrogen bonding at the carboxylate-binding site contributes to both affinity and selectivity. In particular, the hydrogen-bonding pattern is surprisingly different between the non-canonical and canonical interaction. Our data provide a detailed understanding of the role of hydrogen bonds in protein-protein interactions

A PBIL for load balancing in network coding based multicasting

One of the most important issues in multicast is how to achieve a balanced traffic load within a communications network. This paper formulates a load balancing optimization problem in the context of multicast with network coding and proposes a modified population based incremental learning (PBIL) algorithm for tackling it. A novel probability vector update scheme is developed to enhance the global exploration of the stochastic search by introducing extra flexibility when guiding the search towards promising areas in the search space. Experimental results demonstrate that the proposed PBIL outperforms a number of the state-of-the-art evolutionary algorithms in terms of the quality of the best solution obtained

An expression signature of the angiogenic response in gastrointestinal neuroendocrine tumours: correlation with tumour phenotype and survival outcomes.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are heterogeneous with respect to biological behaviour and prognosis. As angiogenesis is a renowned pathogenic hallmark as well as a therapeutic target, we aimed to investigate the prognostic and clinico-pathological role of tissue markers of hypoxia and angiogenesis in GEP-NETs. METHODS: Tissue microarray (TMA) blocks were constructed with 86 tumours diagnosed from 1988 to 2010. Tissue microarray sections were immunostained for hypoxia inducible factor 1α (Hif-1α), vascular endothelial growth factor-A (VEGF-A), carbonic anhydrase IX (Ca-IX) and somatostatin receptors (SSTR) 1–5, Ki-67 and CD31. Biomarker expression was correlated with clinico-pathological variables and tested for survival prediction using Kaplan–Meier and Cox regression methods. RESULTS: Eighty-six consecutive cases were included: 51% male, median age 51 (range 16–82), 68% presenting with a pancreatic primary, 95% well differentiated, 51% metastatic. Higher grading (P=0.03), advanced stage (P<0.001), high Hif-1α and low SSTR-2 expression (P=0.03) predicted for shorter overall survival (OS) on univariate analyses. Stage, SSTR-2 and Hif-1α expression were confirmed as multivariate predictors of OS. Median OS for patients with SSTR-2+/Hif-1α-tumours was not reached after median follow up of 8.8 years, whereas SSTR-2-/Hif-1α+ GEP-NETs had a median survival of only 4.2 years (P=0.006). CONCLUSION: We have identified a coherent expression signature by immunohistochemistry that can be used for patient stratification and to optimise treatment decisions in GEP-NETs independently from stage and grading. Tumours with preserved SSTR-2 and low Hif-1α expression have an indolent phenotype and may be offered less aggressive management and less stringent follow up