A method for continuous-range sequence analysis with jensen-shannon divergence

Mutual Information (MI) is a useful Information Theory tool for the recognition of mutual dependence between data sets. Several methods have been developed fore estimation of MI when both data sets are of the discrete type or when both are of the continuous type. However, MI estimation between a discrete range data set and a continuous range data set has not received so much attention. We therefore present here a method for the estimation of MI for this case, based on the kernel density approximation. This calculation may be of interest in diverse contexts. Since MI is closely related to the Jensen Shannon divergence, the method developed here is of particular interest in the problems of sequence segmentation and set comparisons.Fil: Re, Miguel Angel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomia y Física. Sección Física. Grupo de Física de la Atmosfera; ArgentinaFil: Aguirre Varela, Guillermo Gabriel. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomia y Física. Sección Física. Grupo de Física de la Atmosfera; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Física Enrique Gaviola. Universidad Nacional de Córdoba. Instituto de Física Enrique Gaviola; Argentin

Groundwater policy and planning

Groundwater policy defines objectives, ambitions and priorities for managing groundwater resources, for the benefit of society. Planning translates policy into programmes of action. Both are often part of a wider water resource policy and planning framework, but the specific challenges pertaining to groundwater have traditionally received less attention than surface water. The terms ‘policy,’ ‘strategy’ and ‘plans’ are used interchangeably in many countries and contexts

Design and Integration of Electrical Bio-Impedance Sensing in a Bipolar Forceps for Soft Tissue Identification: A Feasibility Study

This paper presents the integration of electrical bio-impedance sensing technology into a bipolar surgical forceps for soft tissue identification during a robotic assisted procedure. The EBI sensing is done by pressing the forceps on the target tissue with a controlled pressing depth and a controlled jaw opening distance. The impact of these 2 parameters are characterized by finite element simulation. Subsequently, an experiment is conducted with 4 types of ex-vivo tissues including liver, kidney, lung and muscle. The experimental results demonstrate that the proposed EBI sensing method can identify these 4 tissue types with an accuracy higher than 92.82%

Quantum control of hybrid nuclear-electronic qubits

Pulsed magnetic resonance is a wide-reaching technology allowing the quantum state of electronic and nuclear spins to be controlled on the timescale of nanoseconds and microseconds respectively. The time required to flip either dilute electronic or nuclear spins is orders of magnitude shorter than their decoherence times, leading to several schemes for quantum information processing with spin qubits. We investigate instead the novel regime where the eigenstates approximate 50:50 superpositions of the electronic and nuclear spin states forming "hybrid nuclear-electronic" qubits. Here we demonstrate quantum control of these states for the first time, using bismuth-doped silicon, in just 32 ns: this is orders of magnitude faster than previous experiments where pure nuclear states were used. The coherence times of our states are five orders of magnitude longer, reaching 4 ms, and are limited by the naturally-occurring 29Si nuclear spin impurities. There is quantitative agreement between our experiments and no-free-parameter analytical theory for the resonance positions, as well as their relative intensities and relative Rabi oscillation frequencies. In experiments where the slow manipulation of some of the qubits is the rate limiting step, quantum computations would benefit from faster operation in the hybrid regime.Comment: 20 pages, 8 figures, new data and simulation

Coordination of opposing sex-specific and core muscle groups regulates male tail posture during Caenorhabditis elegans male mating behavior

Background To survive and reproduce, animals must be able to modify their motor behavior in response to changes in the environment. We studied a complex behavior of Caenorhabditis elegans, male mating behavior, which provided a model for understanding motor behaviors at the genetic, molecular as well as circuit level. C. elegans male mating behavior consists of a series of six sub-steps: response to contact, backing, turning, vulva location, spicule insertion, and sperm transfer. The male tail contains most of the sensory structures required for mating, in addition to the copulatory structures, and thus to carry out the steps of mating behavior, the male must keep his tail in contact with the hermaphrodite. However, because the hermaphrodite does not play an active role in mating and continues moving, the male must modify his tail posture to maintain contact. We provide a better understanding of the molecular and neuro-muscular pathways that regulate male tail posture during mating. Results Genetic and laser ablation analysis, in conjunction with behavioral assays were used to determine neurotransmitters, receptors, neurons and muscles required for the regulation of male tail posture. We showed that proper male tail posture is maintained by the coordinated activity of opposing muscle groups that curl the tail ventrally and dorsally. Specifically, acetylcholine regulates both ventral and dorsal curling of the male tail, partially through anthelmintic levamisole-sensitive, nicotinic receptor subunits. Male-specific muscles are required for acetylcholine-driven ventral curling of the male tail but dorsal curling requires the dorsal body wall muscles shared by males and hermaphrodites. Gamma-aminobutyric acid activity is required for both dorsal and ventral acetylcholine-induced curling of the male tail and an inhibitory gamma-aminobutyric acid receptor, UNC-49, prevents over-curling of the male tail during mating, suggesting that cross-inhibition of muscle groups helps maintain proper tail posture. Conclusion Our results demonstrated that coordination of opposing sex-specific and core muscle groups, through the activity of multiple neurotransmitters, is required for regulation of male tail posture during mating. We have provided a simple model for regulation of male tail posture that provides a foundation for studies of how genes, molecular pathways, and neural circuits contribute to sensory regulation of this motor behavior

Heterofucans from the Brown Seaweed Canistrocarpus cervicornis with Anticoagulant and Antioxidant Activities

Fucan is a term used to denominate a family of sulfated polysaccharides rich in sulfated l-fucose. We extracted six fucans from Canistrocarpus cervicornis by proteolytic digestion followed by sequential acetone precipitation. These heterofucans are composed mainly of fucose, glucuronic acid, galactose and sulfate. No polysaccharide was capable of prolonging prothrombin time (PT) at the concentration assayed. However, all polysaccharides prolonged activated partial thromboplastin time (aPTT). Four sulfated polysaccharides (CC-0.3/CC-0.5/CC-0.7/CC-1.0) doubled aPTT with only 0.1 mg/mL of plasma, only 1.25-fold less than Clexane®, a commercial low molecular weight heparin. Heterofucans exhibited total antioxidant capacity, low hydroxyl radical scavenging activity, good superoxide radical scavenging efficiency (except CC-1.0), and excellent ferrous chelating ability (except CC-0.3). These results clearly indicate the beneficial effect of C. cervicornis polysaccharides as anticoagulants and antioxidants. Further purification steps and additional studies on structural features as well as in vivo experiments are needed to test the viability of their use as therapeutic agents

New prioritized value iteration for Markov decision processes

The problem of solving large Markov decision processes accurately and quickly is challenging. Since the computational effort incurred is considerable, current research focuses on finding superior acceleration techniques. For instance, the convergence properties of current solution methods depend, to a great extent, on the order of backup operations. On one hand, algorithms such as topological sorting are able to find good orderings but their overhead is usually high. On the other hand, shortest path methods, such as Dijkstra's algorithm which is based on priority queues, have been applied successfully to the solution of deterministic shortest-path Markov decision processes. Here, we propose an improved value iteration algorithm based on Dijkstra's algorithm for solving shortest path Markov decision processes. The experimental results on a stochastic shortest-path problem show the feasibility of our approach. © Springer Science+Business Media B.V. 2011.García Hernández, MDG.; Ruiz Pinales, J.; Onaindia De La Rivaherrera, E.; Aviña Cervantes, JG.; Ledesma Orozco, S.; Alvarado Mendez, E.; Reyes Ballesteros, A. (2012). New prioritized value iteration for Markov decision processes. Artificial Intelligence Review. 37(2):157-167. doi:10.1007/s10462-011-9224-zS157167372Agrawal S, Roth D (2002) Learning a sparse representation for object detection. In: Proceedings of the 7th European conference on computer vision. Copenhagen, Denmark, pp 1–15Bellman RE (1954) The theory of dynamic programming. Bull Amer Math Soc 60: 503–516Bellman RE (1957) Dynamic programming. Princeton University Press, New JerseyBertsekas DP (1995) Dynamic programming and optimal control. Athena Scientific, MassachusettsBhuma K, Goldsmith J (2003) Bidirectional LAO* algorithm. 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Cumbria, UKBoutilier C, Dean T, Hanks S (1999) Decision-theoretic planning: structural assumptions and computational leverage. J Artif Intell Res 11: 1–94Chang I, Soo H (2007) Simulation-based algorithms for Markov decision processes Communications and control engineering. Springer, LondonDai P, Goldsmith J (2007a) Faster dynamic programming for Markov decision processes. Technical report. Doctoral consortium, department of computer science and engineering. University of WashingtonDai P, Goldsmith J (2007b) Topological value iteration algorithm for Markov decision processes. In: Proceedings of the 20th international joint conference on artificial intelligence. Hyderabad, India, pp 1860–1865Dai P, Hansen EA (2007c) Prioritizing bellman backups without a priority queue. In: Proceedings of the 17th international conference on automated planning and scheduling, association for the advancement of artificial intelligence. Rhode Island, USA, pp 113–119Dibangoye JS, Chaib-draa B, Mouaddib A (2008) A Novel prioritization technique for solving Markov decision processes. In: Proceedings of the 21st international FLAIRS (The Florida Artificial Intelligence Research Society) conference, association for the advancement of artificial intelligence. Florida, USAFerguson D, Stentz A (2004) Focused propagation of MDPs for path planning. In: Proceedings of the 16th IEEE international conference on tools with artificial intelligence. pp 310–317Hansen EA, Zilberstein S (2001) LAO: a heuristic search algorithm that finds solutions with loops. Artif Intell 129: 35–62Hinderer K, Waldmann KH (2003) The critical discount factor for finite Markovian decision processes with an absorbing set. Math Methods Oper Res 57: 1–19Li L (2009) A unifying framework for computational reinforcement learning theory. PhD Thesis. The state university of New Jersey, New Brunswick. 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Comprehensive establishment and characterization of orthoxenograft mouse models of malignant peripheral nerve sheath tumors for personalized medicine

Malignant peripheral nerve sheath tumors (MPNSTs) are soft-tissue sarcomas that can arise either sporadically or in association with neurofibromatosis type 1 (NF1). These aggressive malignancies confer poor survival, with no effective therapy available. We present the generation and characterization of five distinct MPNST orthoxenograft models for preclinical testing and personalized medicine. Four of the models are patient-derived tumor xenografts (PDTX), two independent MPNSTs from the same NF1 patient and two from different sporadic patients. The fifth model is an orthoxenograft derived from an NF1-related MPNST cell line. All MPNST orthoxenografts were generated by tumor implantation, or cell line injection, next to the sciatic nerve of nude mice, and were perpetuated by 7-10 mouse-to-mouse passages. The models reliably recapitulate the histopathological properties of their parental primary tumors. They also mimic distal dissemination properties in mice. Human stroma was rapidly lost after MPNST engraftment and replaced by murine stroma, which facilitated genomic tumor characterization. Compatible with an origin in a catastrophic event and subsequent genome stabilization, MPNST contained highly altered genomes that remained remarkably stable in orthoxenograft establishment and along passages. Mutational frequency and type of somatic point mutations were highly variable among the different MPNSTs modeled, but very consistent when comparing primary tumors with matched orthoxenografts generated. Unsupervised cluster analysis and principal component analysis (PCA) using an MPNST expression signature of ~1,000 genes grouped together all primary tumor-orthoxenograft pairs. Our work points to differences in the engraftment process of primary tumors compared with the engraftment of established cell lines. Following standardization and extensive characterization and validation, the orthoxenograft models were used for initial preclinical drug testing. Sorafenib (a BRAF inhibitor), in combination with doxorubicin or rapamycin, was found to be the most effective treatment for reducing MPNST growth. The development of genomically well-characterized preclinical models for MPNST allowed the evaluation of novel therapeutic strategies for personalized medicine