New insights about the evaluation of human sperm quality: the aromatase example.

Male contribution to the couple's infertility is at first evaluated by the routine examination of semen parameters upon optical microscopy providing valuable information for a rational initial diagnosis and for a clinical management of infertility. But the different forms of infertility defined according to the WHO criteria especially teratozoospermia are not always related to the chromatin structure or to the fertilization capacity. New investigations at the molecular level (transcript and protein) could be developed in order to understand the nature of sperm malformation responsible of human infertility and thus to evaluate the sperm quality. The profile analysis of spermatozoal transcripts could be considered as a fingerprint of the past spermatogenic events. The selection of representative transcripts of normal spermatozoa remains complex because a differential expression (increased, decreased or not modified levels) of specific transcripts has been revealed between immotile and motile sperm fractions issued from normozoospermic donors. Microarrays tests or real-time quantitative PCR could be helpful for the identification of factors involved in the male infertility. Differences in the expression of specific transcripts have been reported between normal and abnormal semen samples. With the aromatase example, we have noted a negative strong correlation between the amount of transcript and the percentage of abnormal forms especially in presence of head defects. Immunocytochemical procedures using fluorescent probes associated with either confocal microscopy or flow cytometry can be also helpful to proceed with further investigations about the localization of proteins in the compartmentalized spermatozoa or the acrosome reaction. The dual location of aromatase both in the equatorial segment, the mid-piece and the tail could explain the double role of this enzyme in acrosome reaction and motility

Review of EEG and ERP studies of extraversion personality for baseline and cognitive tasks

According to psychological studies, the most fundamental personality is the extraversion personality. Most studies looking at differences between extroverts and introverts are pen and paper based studies. However, in a few studies, electrophysiological signals were involved. In this paper, we reviewed studies examining extraversion personality using electroencephalography (EEG) and event-related potentials (ERP). It was found that some of the EEG studies claimed that extroverts and introverts can be differentiated using baseline EEG, while some others claimed otherwise. Conflicting findings were also observed in the ERP studies; higher/lower P300 amplitude in extroverts compared to that of introverts in visual stimuli tasks. These various findings are probably due to differences in their experimental protocols, sample size, or age of subjects. Other possible reasons include no consideration given on the main feature of extraversion and the studies only focused on EEG power spectral analysis. We are thus suggesting for future investigations to involve the main feature such as sociability and/or to incorporate more EEG features in the analysis to produce more robust and reliable results. This review constitutes a guidance for research on brain-related conditions of extroverts and introverts and shall be useful in many areas

A new class of coherent states with Meixner-Pollaczek polynomials for the Gol'dman-Krivchenkov Hamiltonian

A class of generalized coherent states with a new type of the identity resolution are constructed by replacing the labeling parameter zn/n! of the canonical coherent states by Meixner-Pollaczek polynomials with specific parameters. The constructed coherent states belong to the state Hilbert space of the Gol'dman-Krivchenkov Hamiltonian.Comment: 10 pages, Submitte

Penile hair coil strangulation of the child

AbstractWe report the case of a child with a delayed presentation of penile strangulation with a coil of hair that resulted in a complete transection of the urethra. Hair coil strangulation of the penis is uncommon. It is also known as penile Tourniquet syndrome. It has been reported with circumcised and uncircumcised penises and it can lead to serious complications like the amputation of the penis. Prompt diagnosis and treatment are necessary to prevent complications

Robust Dropping Criteria for F-norm Minimization Based Sparse Approximate Inverse Preconditioning

Dropping tolerance criteria play a central role in Sparse Approximate Inverse preconditioning. Such criteria have received, however, little attention and have been treated heuristically in the following manner: If the size of an entry is below some empirically small positive quantity, then it is set to zero. The meaning of "small" is vague and has not been considered rigorously. It has not been clear how dropping tolerances affect the quality and effectiveness of a preconditioner $M$. In this paper, we focus on the adaptive Power Sparse Approximate Inverse algorithm and establish a mathematical theory on robust selection criteria for dropping tolerances. Using the theory, we derive an adaptive dropping criterion that is used to drop entries of small magnitude dynamically during the setup process of $M$. The proposed criterion enables us to make $M$ both as sparse as possible as well as to be of comparable quality to the potentially denser matrix which is obtained without dropping. As a byproduct, the theory applies to static F-norm minimization based preconditioning procedures, and a similar dropping criterion is given that can be used to sparsify a matrix after it has been computed by a static sparse approximate inverse procedure. In contrast to the adaptive procedure, dropping in the static procedure does not reduce the setup time of the matrix but makes the application of the sparser $M$ for Krylov iterations cheaper. Numerical experiments reported confirm the theory and illustrate the robustness and effectiveness of the dropping criteria.Comment: 27 pages, 2 figure

On composite systems of dilute and dense couplings

Composite systems, where couplings are of two types, a combination of strong dilute and weak dense couplings of Ising spins, are examined through the replica method. The dilute and dense parts are considered to have independent canonical disordered or uniform bond distributions; mixing the models by variation of a parameter $\gamma$ alongside inverse temperature $\beta$ we analyse the respective thermodynamic solutions. We describe the variation in high temperature transitions as mixing occurs; in the vicinity of these transitions we exactly analyse the competing effects of the dense and sparse models. By using the replica symmetric ansatz and population dynamics we described the low temperature behaviour of mixed systems.Comment: 35 pages, 9 figures, submitted to JPhys

Survey propagation for the cascading Sourlas code

We investigate how insights from statistical physics, namely survey propagation, can improve decoding of a particular class of sparse error correcting codes. We show that a recently proposed algorithm, time averaged belief propagation, is in fact intimately linked to a specific survey propagation for which Parisi's replica symmetry breaking parameter is set to zero, and that the latter is always superior to belief propagation in the high connectivity limit. We briefly look at further improvements available by going to the second level of replica symmetry breaking.Comment: 14 pages, 5 figure

Multiscale Computations on Neural Networks: From the Individual Neuron Interactions to the Macroscopic-Level Analysis

We show how the Equation-Free approach for multi-scale computations can be exploited to systematically study the dynamics of neural interactions on a random regular connected graph under a pairwise representation perspective. Using an individual-based microscopic simulator as a black box coarse-grained timestepper and with the aid of simulated annealing we compute the coarse-grained equilibrium bifurcation diagram and analyze the stability of the stationary states sidestepping the necessity of obtaining explicit closures at the macroscopic level. We also exploit the scheme to perform a rare-events analysis by estimating an effective Fokker-Planck describing the evolving probability density function of the corresponding coarse-grained observables

Training a perceptron in a discrete weight space

On-line and batch learning of a perceptron in a discrete weight space, where each weight can take $2 L+1$ different values, are examined analytically and numerically. The learning algorithm is based on the training of the continuous perceptron and prediction following the clipped weights. The learning is described by a new set of order parameters, composed of the overlaps between the teacher and the continuous/clipped students. Different scenarios are examined among them on-line learning with discrete/continuous transfer functions and off-line Hebb learning. The generalization error of the clipped weights decays asymptotically as $exp(-K \alpha^2)$/$exp(-e^{|\lambda| \alpha})$ in the case of on-line learning with binary/continuous activation functions, respectively, where $\alpha$ is the number of examples divided by N, the size of the input vector and $K$ is a positive constant that decays linearly with 1/L. For finite $N$ and $L$, a perfect agreement between the discrete student and the teacher is obtained for $\alpha \propto \sqrt{L \ln(NL)}$. A crossover to the generalization error $\propto 1/\alpha$, characterized continuous weights with binary output, is obtained for synaptic depth $L > O(\sqrt{N})$.Comment: 10 pages, 5 figs., submitted to PR