3,232 research outputs found
Sequences of regressions and their independences
Ordered sequences of univariate or multivariate regressions provide
statistical models for analysing data from randomized, possibly sequential
interventions, from cohort or multi-wave panel studies, but also from
cross-sectional or retrospective studies. Conditional independences are
captured by what we name regression graphs, provided the generated distribution
shares some properties with a joint Gaussian distribution. Regression graphs
extend purely directed, acyclic graphs by two types of undirected graph, one
type for components of joint responses and the other for components of the
context vector variable. We review the special features and the history of
regression graphs, derive criteria to read all implied independences of a
regression graph and prove criteria for Markov equivalence that is to judge
whether two different graphs imply the same set of independence statements.
Knowledge of Markov equivalence provides alternative interpretations of a given
sequence of regressions, is essential for machine learning strategies and
permits to use the simple graphical criteria of regression graphs on graphs for
which the corresponding criteria are in general more complex. Under the known
conditions that a Markov equivalent directed acyclic graph exists for any given
regression graph, we give a polynomial time algorithm to find one such graph.Comment: 43 pages with 17 figures The manuscript is to appear as an invited
discussion paper in the journal TES
Tetraquarks as Diquark Antidiquark Bound Systems
In this paper, we study four-body systems consisting of diquark antidiquark,
and we analyze diquark-antidiquark in the framework of a two body (pseudo
point) problem. We solve Lippman Schwinger equation numerically for charm
diquark antidiquark systems and find the eigenvalues to calculate the binding
energies and masses of heavy tetraquarks with hidden charms. Our results are in
good agreement with theoretical and experimental data
A Novel User Pairing Scheme for Functional Decode-and-Forward Multi-way Relay Network
In this paper, we consider a functional decode and forward (FDF) multi-way
relay network (MWRN) where a common user facilitates each user in the network
to obtain messages from all other users. We propose a novel user pairing
scheme, which is based on the principle of selecting a common user with the
best average channel gain. This allows the user with the best channel
conditions to contribute to the overall system performance. Assuming lattice
code based transmissions, we derive upper bounds on the average common rate and
the average sum rate with the proposed pairing scheme. Considering M-ary
quadrature amplitude modulation with square constellation as a special case of
lattice code transmission, we derive asymptotic average symbol error rate (SER)
of the MWRN. We show that in terms of the achievable rates, the proposed
pairing scheme outperforms the existing pairing schemes under a wide range of
channel scenarios. The proposed pairing scheme also has lower average SER
compared to existing schemes. We show that overall, the MWRN performance with
the proposed pairing scheme is more robust, compared to existing pairing
schemes, especially under worst case channel conditions when majority of users
have poor average channel gains.Comment: 30 pages, 6 figures, submitted for journal publicatio
The effect of spatial learning on the number of astrocytes in rat dentate gyrus
In this study, we evaluated the effect of spatial learning on the number of astrocytes in the rat dentate gyrus with Morris water maze. Fifteen male albino Wistar rats were divided into three groups as control, reference memory and working memory groups. Each group was consisted of 5 rats. After spatial learning, the brains were histologically examined; the slides were stained with phosphotungstic acid hematoxylin (PTAH) staining to show the astrocytes. We found significant difference in the number of astrocytes in dentate gyrus between control and reference memory groups, and between control and working memory groups as well. When compared two learning groups there was a significant difference in the number of astrocytes between them, being higher in the working memory group. We concluded that the number of astrocytes increased due to spatial learning and this increase can be affected to the period of learning. Our studies of spatial learning and effect of learning techniques (reference and working memory) showed that the technique that has longer period of learning has more effect on the number of astrocytes
The similarity of astrocytes number in dentate gyrus and CA3 subfield of rats hippocampus
The dentate gyrus is a part of hippocampal formation that it contains granule cells, which project to the pyramidal cells and interneurons of the CA3 subfield of the hippocampus. Astrocytes play a more active role in neuronal activity, including regulating ion flux currents, energy production, neurotransmitter release and synaptogenesis. Astrocytes are the only cells in the brain that contain the energy molecule glycogen. The close relationship between dentate gyrus and CA3 area can cause the similarity of the number of astrocytes in these areas. In this study 5 male albino wistar rats were used. Rats were housed in large plastic cage in animal house and were maintained under standard conditions, after histological processing, The 7 μm slides of the brains were stained with PTAH staining for showing the astrocytes. This staining is specialized for astrocytes. We showed that the number of astrocytes in different (ant., mid., post) parts of dentate gyrus and CA3 of hippocampus is the same. For example, the anterior parts of two area have the most number of astrocytes and the middle parts of two area have the least number of astrocytes. We concluded that dentate gyrus and CA3 area of hippocampus have the same group of astrocytes. © 2007 Asian Network For Scientific Information
The effect of spatial learning on the number of astrocytes in the CA3 subfield of the rat hippocampus
Introduction: Astrocytes play an important role in the hippocampus, probably in memory and learning. The aim of this study was to evaluate the number of astrocytes in the CA3 subfield of the rat hippocampus after spatial learning using the Morris water maze with reference and working memory methods. Methods: 45 male albino wistar rats were divided into three groups, with 15 rats in the control group and 15 rats in each of the other two groups. The two study groups of rats underwent spatial learning using the Morris water maze, with one group trained using the reference memory and the other, the working memory technique, respectively. After histological processing, the slides of the brains were stained with the phosphotanguestic acid haematoxylin staining method for detection of the astrocytes. Results: There was a significant difference in the number of astrocytes in the CA3 area between the control and reference memory groups. The difference between control and working memory groups was significant as well. Additionally, when comparing the two learning groups, we also found significant differences between them. Conclusion: The number of astrocytes increased due to spatial learning
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