Psychophysiological Characteristics of Children with Dyslexia

Dyslexia is a specific learning disorder that involves difficulty reading due to decoding problems for letters and words. Statistics shows that 5-10% of the general population has dyslexia. The aetiology of reading disorder supposes some biological causes and morphological markers useful in the classification and early identification of the problem.The aim of this article is to find appropriate parameters, which will be useful for early diagnosis and finding the right modalities for treatment.Our findings about QEEG characteristics are not conclusive. However, slowing of brain activity in dyslexic children appeared to be confirmed. These findings lead to the possible hypothesis of delay in neurological development of these children. Significant theta/beta ratio suggest possible comorbidity with ADHD.Further research with more children included is proposed

Modeling ring current ion and electron dynamics and plasma instabilities during a high‐speed stream driven storm

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94593/1/jgra21840.pd

Religious discrimination and common mental disorders in England: a nationally representative population-based study

PURPOSE: Although the impact of discrimination on mental health has been increasingly discussed, the effect of religious discrimination has not been examined systematically. We studied the prevalence of perceived religious discrimination and its association with common mental disorders in a nationally representative population-based sample in England. METHODS: We used data from the Adult Psychiatric Morbidity Survey 2007 that represents all adults age 16 years and over living in private households in England. Common mental disorders were ascertained using the Revised Clinical Interview Schedule. Experience of discrimination was assessed by a computer-assisted self-report questionnaire and potential paranoid traits by the Psychosis Screening Questionnaire. RESULTS: From the total of 7318 participants, 3873 (52.4 %) reported adhering to religion. 108 subjects (1.5 %) reported being unfairly treated in the past 12 months due to their religion. Non-Christian religious groups were more likely to report perceived religious discrimination compared to Christians (OR 11.44; 95 % CI 7.36–17.79). People who experienced religious discrimination had increased prevalence of all common mental disorders. There was a two-fold increase in the risk of common mental disorders among people who reported experience of religious discrimination independent of their ethnicity, skin colour or suspected paranoid traits. CONCLUSIONS: The impact of perceived religious discrimination on mental health should be given more consideration in treatment and future preventative policies

Parametric Optimization Of Magneto-Rheological Fluid Damper Using Particle Swarm Optimization

This paper presents a parametric modeling of a magneto-rheological (MR) damper using a Particle Swarm Optimization (PSO) method. The objective of this paper is to optimize the parameter values of the MR fluid damper behavior using the Bouc-Wen model. The parametric identification was imposed beforehand in replicating the behavior of the MR fluid damper. The algebraic function from a number of hysteresis models was steered by comparing selected models: Bingham, Bouc-Wen and BoucWen by Kwok. A simulation method was operated in investigating these models by employing MATLAB reliant from the model intricacy. The experimental data was presented in terms of the time histories of the displacement, the velocity and the force parameters, measured for both constant and variable current settings and at a selected frequency applied to the damper. The model parameters were determined using a set of experimental measurements corresponding to different current constant values. It has been shown that the MR damper model’s response via the proposed approach is in good agreement with the MR damper test rig counterpar

Application and testing of the L neural network with the self-consistent magnetic field model of RAM-SCB

Abstract We expanded our previous work on L neural networks that used empirical magnetic field models as the underlying models by applying and extending our technique to drift shells calculated from a physics-based magnetic field model. While empirical magnetic field models represent an average, statistical magnetospheric state, the RAM-SCB model, a first-principles magnetically self-consistent code, computes magnetic fields based on fundamental equations of plasma physics. Unlike the previous L neural networks that include McIlwain L and mirror point magnetic field as part of the inputs, the new L neural network only requires solar wind conditions and the Dst index, allowing for an easier preparation of input parameters. This new neural network is compared against those previously trained networks and validated by the tracing method in the International Radiation Belt Environment Modeling (IRBEM) library. The accuracy of all L neural networks with different underlying magnetic field models is evaluated by applying the electron phase space density (PSD)-matching technique derived from the Liouville\u27s theorem to the Van Allen Probes observations. Results indicate that the uncertainty in the predicted L is statistically (75%) below 0.7 with a median value mostly below 0.2 and the median absolute deviation around 0.15, regardless of the underlying magnetic field model. We found that such an uncertainty in the calculated L value can shift the peak location of electron phase space density (PSD) profile by 0.2 RE radially but with its shape nearly preserved. Key Points L* neural network based on RAM-SCB model is developed L* calculation accuracy is estimated by PSD matching using RBSP data L* uncertainty causes a radial shift in the electron phase space density profile

The effects of dynamic ionospheric outflow on the ring current

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94583/1/jgra20739.pd

Monitoring the effect of therapy on a patient with a neuroendocrine tumor of the pancreas with PET/CT, 68Ga-DOTATATE - case report

Neuroendocrine tumors (NET) are a rare diagnosis, often without symptoms or mimicking other different symptoms. Тhey are a heterogeneous group of tumors derived from neuroendocrine cells, most commonly of the gastrointestinal tract, but may originate also from other organs including the pancreas, lungs, ovaries, thyroid, pituitary, and adrenal glands (3). Due to the difficult diagnosis, NET‘s are detected at a late stage in their development, often already locally advanced or metastasized. PET/CT with 68Gallium DOTATATE proved to be an effective imaging method not only for the primary diagnosis of NET and subsequent therapeutic behavior, but also for evaluating the effect of the treatment. (1) We present a case of a positive PET/CT scan, performed with Ga-68 DOTATATE in the topical location of the tail of the pancreas after therapy with Sandostain lar

What’s sex got to do with it? A family-based investigation of growing up heterosexual during the twentieth century

This paper explores findings from a cross-generational study of the making of heterosexual relationships in East Yorkshire, which has interviewed women and men within extended families. Using a feminist perspective, it examines the relationship between heterosexuality and adulthood, focussing on sexual attraction, courtship, first kisses, first love and first sex, as mediated within family relationships, and at different historical moments. In this way, the contemporary experiences of young people growing up are compared and contrasted with those of mid-lifers and older adults who formed heterosexual relationships within the context of the changing social and sexual mores of the 1960s/1970s, and the upheavals of World War Two

Immune Cell Infiltrate in Chronic-Active Antibody-Mediated Rejection

Background: Little is known about immune cell infiltrate type in the kidney allograft of patients with chronic-active antibody-mediated rejection (c-aABMR). Methods: In this study, multiplex immunofluorescent staining was performed on 20 cases of biopsy-proven c-aABMR. T-cell subsets (CD3, CD8, Foxp3, and granzyme B), macrophages (CD68 and CD163), B cells (CD20), and natural killer cells