Evaluation of auditory efferent system function in children with autism

زمینه و هدف: مطالعات مختلف نشان داده اند که سیستم وابران شنیداری در توجه انتخابی نقش دارد و از این رو بررسی این سیستم در کودکان اوتیسمی بسیار ارزشمند است. هدف از این مطالعه بررسی مسیر وابران شنوایی در کودکان مبتلا به اوتیسم در مقایسه با کودکان با رشد هنجار بوده است. روش بررسی: در این مطالعه توصیفی-تحلیلی تعداد 34 کودک 11-5 ساله در قالب دو گروه هنجار (17 نفر) و مبتلا به اوتیسم (17 نفر) مورد بررسی قرار گرفتند. کلیه کودکان در آزمون های ادیومتری تون خالص (Pure-tone audionetry)، ادیومتری گفتاری (Speech audiometery)، تمپانومتری (Tympanometry) و گسیل های صوتی گوشی گذرا (otoacoustic emissions=TEOAE-evoked Transient)دارای نتایج طبیعی بودند. عملکرد سیستم وابران از طریق ثبت پاسخ های TEOAE در دو حالت ارائه نویز دگر طرفی و بدون ارائه نویز بررسی گردید. جهت آنالیز نتایج از از نرم افزار آماری SPSS و آزمون های تی مستقل و تی زوجی استفاده شد. یافته ها: نتایج این پژوهش نشان داد که تفاوت قابل ملاحظه ای بین میانگین میزان مهار در دو گروه وجود دارد (001/0=P). میانگین دامنه TEOAE در حالت بدون نویز دگر طرفی در گروه هنجار (09/4 ± 63/17) و در گروه اوتیسم (78/3 ± 40/17) به دست آمد که از لحاظ آماری نشان دهنده تفاوت معنی داری نبود (83/0=P). نتیجه گیری: یافته های کسب شده در مطالعه حاضر نشان دهنده کاهش فعالیت سیستم وابران شنوایی در کودکان مبتلا به اوتیسم نسبت به کودکان با رشد هنجار بود. با توجه به اینکه آزمون مورد استفاده در این مطالعه، مهار گسیل های صوتی گوشی گذرا (TEOAE suppression) است، می توان نتیجه گرفت این آزمون ابزار بالینی حساس، غیر تهاجمی، عینی و مناسب برای بررسی عملکرد سیستم وابران در کودکان مبتلا به اوتیسم است

A cutoff phenomenon in accelerated stochastic simulations of chemical kinetics via flow averaging (FLAVOR-SSA)

We present a simple algorithm for the simulation of stiff, discrete-space, continuous-time Markov processes. The algorithm is based on the concept of flow averaging for the integration of stiff ordinary and stochastic differential equations and ultimately leads to a straightforward variation of the the well-known stochastic simulation algorithm (SSA). The speedup that can be achieved by the present algorithm [flow averaging integrator SSA (FLAVOR-SSA)] over the classical SSA comes naturally at the expense of its accuracy. The error of the proposed method exhibits a cutoff phenomenon as a function of its speed-up, allowing for optimal tuning. Two numerical examples from chemical kinetics are provided to illustrate the efficiency of the method

From Scattering and Recoiling Spectrometry to Scattering and Recoiling Imaging

A new ion scattering technique, called scattering and recoiling imaging spectrometry (SARIS), is being developed. The SARIS technique uses a large, position sensitive microchannel plate (MCP) and time-of-flight methods to capture images of scattered and recoiled particles from a pulsed ke V ion beam. These images combine the advantage of atomic scale microscopy and spatial averaging simultaneously since they are created from a macroscopic surface area but they are directly related to the atomic arrangement of the surface. This paper de-scribes the basis of the SARIS technique, the instrument which is under development, and the scattering and recoiling imaging code (SARIC) for simulation of the classical ion trajectories. Time-of-flight scattering and recoiling spectrometry (TOF-SARS) data are used to emulate the SARIS images for the case of 4 keV Ne+ scattering from a Pt{111} surface. The observed scattering intensity patterns are characterized by their complex and rich structure. These experimental images are simulated by use of the SARIC program. The abundance of information contained in the images can be used to identify the type of surface being studied and its structure. The extraction of numerical values for the interatomic spacings, relaxations, reconstructions, and adsorbate site positions is accomplished by comparing the experimental and simulated images. Quantitative comparisons are made through the use of a reliability, or R, factor, which is based on the differences between the two images. The SARIS development will move low energy ion scattering into the realm of surface imaging techniques

Introducing the best cell culture method for primary hepatocyte from orangespotted grouper, Epinephelus coioides

Liver is one of the most important organs in vertebrates that have important roles in detoxifying. This organ was used as a target organ in many physiological and toxicological aspects. The main purpose of the present study was developing appropriate methodology for the primary cultivation of hepatic cells from orange-spotted Grouper, Epinephelus coioides, a subtropical fish species of the family Serranidae. In present study, hepatocytes were isolated from five grouper individuals. Initially, the fish wiped with 70% ethanol. Liver were removed and cut into small pieces with scissors and hepatocytes were disconnected using different enzymatic digestion with collagenase (Type 1 and 4) and trypsin and additional nutrient materials in culturing mediums. Then, cells were cultured for 2 weeks in Lebowitz L-15 under 3 methods: 1. using enzymatic digestion by trypsin, 2. using enzymatic digestion by collagenase (type 1 and 4) and 3. Using nutrients and additives was cultured. Finally, effects of different incubation temperature (20, 25, 28, 30 and 32 degree of Celsius) and Bovine serum content (0, 10 and 20% and 20%+ITS) on cell growth were estimated. According to the results, digestion by collagenase type 4, resulted in more cell colonization and growth in comparison with other methods. At the same method, cells showed fibroblastic morphology. In conclusion, the best culture method for primary hepatocyte from orange-spotted Grouper, Epinephelus coioides, was using ITS+20%FBS under 30 degree of Celsius incubation temperature

Fermions and Loops on Graphs. II. Monomer-Dimer Model as Series of Determinants

We continue the discussion of the fermion models on graphs that started in the first paper of the series. Here we introduce a Graphical Gauge Model (GGM) and show that : (a) it can be stated as an average/sum of a determinant defined on the graph over $\mathbb{Z}_{2}$ (binary) gauge field; (b) it is equivalent to the Monomer-Dimer (MD) model on the graph; (c) the partition function of the model allows an explicit expression in terms of a series over disjoint directed cycles, where each term is a product of local contributions along the cycle and the determinant of a matrix defined on the remainder of the graph (excluding the cycle). We also establish a relation between the MD model on the graph and the determinant series, discussed in the first paper, however, considered using simple non-Belief-Propagation choice of the gauge. We conclude with a discussion of possible analytic and algorithmic consequences of these results, as well as related questions and challenges.Comment: 11 pages, 2 figures; misprints correcte

Spectral density of random graphs with topological constraints

The spectral density of random graphs with topological constraints is analysed using the replica method. We consider graph ensembles featuring generalised degree-degree correlations, as well as those with a community structure. In each case an exact solution is found for the spectral density in the form of consistency equations depending on the statistical properties of the graph ensemble in question. We highlight the effect of these topological constraints on the resulting spectral density.Comment: 24 pages, 6 figure

The number of matchings in random graphs

We study matchings on sparse random graphs by means of the cavity method. We first show how the method reproduces several known results about maximum and perfect matchings in regular and Erdos-Renyi random graphs. Our main new result is the computation of the entropy, i.e. the leading order of the logarithm of the number of solutions, of matchings with a given size. We derive both an algorithm to compute this entropy for an arbitrary graph with a girth that diverges in the large size limit, and an analytic result for the entropy in regular and Erdos-Renyi random graph ensembles.Comment: 17 pages, 6 figures, to be published in Journal of Statistical Mechanic

Exactness of Belief Propagation for Some Graphical Models with Loops

It is well known that an arbitrary graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by an iterative Belief Propagation (BP) algorithm convergent to unique minimum of the so-called Bethe free energy functional. For a general graphical model on a loopy graph the functional may show multiple minima, the iterative BP algorithm may converge to one of the minima or may not converge at all, and the global minimum of the Bethe free energy functional is not guaranteed to correspond to the optimal Maximum-Likelihood (ML) solution in the zero-temperature limit. However, there are exceptions to this general rule, discussed in \cite{05KW} and \cite{08BSS} in two different contexts, where zero-temperature version of the BP algorithm finds ML solution for special models on graphs with loops. These two models share a key feature: their ML solutions can be found by an efficient Linear Programming (LP) algorithm with a Totally-Uni-Modular (TUM) matrix of constraints. Generalizing the two models we consider a class of graphical models reducible in the zero temperature limit to LP with TUM constraints. Assuming that a gedanken algorithm, g-BP, funding the global minimum of the Bethe free energy is available we show that in the limit of zero temperature g-BP outputs the ML solution. Our consideration is based on equivalence established between gapless Linear Programming (LP) relaxation of the graphical model in the $T\to 0$ limit and respective LP version of the Bethe-Free energy minimization.Comment: 12 pages, 1 figure, submitted to JSTA

Threshold Saturation in Spatially Coupled Constraint Satisfaction Problems

We consider chains of random constraint satisfaction models that are spatially coupled across a finite window along the chain direction. We investigate their phase diagram at zero temperature using the survey propagation formalism and the interpolation method. We prove that the SAT-UNSAT phase transition threshold of an infinite chain is identical to the one of the individual standard model, and is therefore not affected by spatial coupling. We compute the survey propagation complexity using population dynamics as well as large degree approximations, and determine the survey propagation threshold. We find that a clustering phase survives coupling. However, as one increases the range of the coupling window, the survey propagation threshold increases and saturates towards the phase transition threshold. We also briefly discuss other aspects of the problem. Namely, the condensation threshold is not affected by coupling, but the dynamic threshold displays saturation towards the condensation one. All these features may provide a new avenue for obtaining better provable algorithmic lower bounds on phase transition thresholds of the individual standard model

Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices

Compressed sensing is a signal processing method that acquires data directly in a compressed form. This allows one to make less measurements than what was considered necessary to record a signal, enabling faster or more precise measurement protocols in a wide range of applications. Using an interdisciplinary approach, we have recently proposed in [arXiv:1109.4424] a strategy that allows compressed sensing to be performed at acquisition rates approaching to the theoretical optimal limits. In this paper, we give a more thorough presentation of our approach, and introduce many new results. We present the probabilistic approach to reconstruction and discuss its optimality and robustness. We detail the derivation of the message passing algorithm for reconstruction and expectation max- imization learning of signal-model parameters. We further develop the asymptotic analysis of the corresponding phase diagrams with and without measurement noise, for different distribution of signals, and discuss the best possible reconstruction performances regardless of the algorithm. We also present new efficient seeding matrices, test them on synthetic data and analyze their performance asymptotically.Comment: 42 pages, 37 figures, 3 appendixe