Lipid Peroxidation After Intracortical Injection of Ferric Chloride Increases the Incidence of Seizures in Young Rats

Clinical studies have shown that the incidence of early posttraumatic seizures ishigher in children than in adults and it has been proposed that iron-induced lipidperoxidation has an important role in the development of epileptogenic foci. In this study,we examined some of the hypothesized reasons for the difference in the incidence ofearly posttraumatic seizures between young and adult rats. Twelve young and twelveadult rats were randomized into 4 groups. Group 1 and 2 were control groups, eachcomprising of 6 young rats and 6 adult rats respectively and were given intracorticalinjections of normal saline. Group 3 and 4 were injury groups, again comprising 6 youngrats and 6 adult rats respectively and were given intracortical injections of FeCl3. All ratswere observed for 6 hours post injection for the occurrence of seizures and were thenkilled. The injected hemispheres were extirpated and tested for malondialdehyde (MDA)level and superoxide dismutase (SOD) activity as indices of oxidative damage. Resultsshowed that seizures were observed only in Group 3. Increased MDA level and decreasedSOD activity were observed in Group 3 (ANOVA, p<0.001). Increased MDA levels anddecreased SOD activity were significantly higher in rats with seizures (Group 3) than inthose without seizures (independent t-test, p<0.001). We conclude was that differentlevels of lipid peroxidation induced by intracortical ferric chloride injection may accountfor the different seizure incidence between young and adult rat

A constructive method for decomposing real representations

A constructive method for decomposing finite dimensional representations of semisimple real Lie algebras is developed. The method is illustrated by an example. We also discuss an implementation of the algorithm in the language of the computer algebra system {\sf GAP}4.Comment: Final version; to appear in "Journal of Symbolic Computation

Viability problem with perturbation in Hilbert space

This paper deals with the existence result of viable solutions of the differential inclusion $$\dot{x}(t) \in f(t,x(t)) + F(x(t))$$ $$x(t) \in K \quad \text{on } [0,T],$$ where $K$ is a locally compact subset in separable Hilbert space $H,$ $(f(s,\cdot))_s$ is an equicontinuous family of measurable functions with respect to $s$ and $F$ is an upper semi-continuous set-valued mapping with compact values contained in the Clarke subdifferential $\partial_{c} V(x)$ of an uniformly regular function $V.

Spin coherence times of point defects in two-dimensional materials from first principles

The spin coherence times of 69 triplet defect centers in 45 different 2D host materials are calculated using the cluster correlation expansion (CCE) method with parameters of the spin Hamiltonian obtained from density functional theory (DFT). Several of the triplets are found to exhibit extraordinarily large spin coherence times making them interesting for quantum information processing. The dependence of the spin coherence time on various factors, including the hyperfine coupling strength, the dipole-dipole coupling, and the nuclear g-factors, are systematically investigated. The analysis shows that the spin coherence time is insensitive to the atomistic details of the defect center and rather is dictated by the nuclear spin properties of the host material. Symbolic regression is then used to derive a simple expression for spin coherence time, which is validated on a test set of 55 doublet defects unseen by the regression model. The simple expression permits order-of-magnitude estimates of the spin coherence time without expensive first principles calculations

Reforming education in Pakistan – tracing global links

This paper is about tracing global links in national education reforms in Pakistan. The paper tries to describe globalization and its general effects on national policies. It particularly highlights the effects of globalization on education reforms, which are: competitiveness-driven, finance-driven and equity-driven. In light of these global education reform patterns the paper explores the major educational reforms being pursued in Pakistan since 1990s. The paper argues that globalization has seriously challenged the national reform policies, which are now becoming more and more globally driven. Rather than out rightly rejecting all global policies, engaging critically with them is the stance of the authors

Single-photon emitters in hexagonal boron nitride: a review of progress.

This report summarizes progress made in understanding properties such as zero-phonon-line energies, emission and absorption polarizations, electron-phonon couplings, strain tuning and hyperfine coupling of single photon emitters in hexagonal boron nitride. The primary aims of this research are to discover the chemical nature of the emitting centres and to facilitate deployment in device applications. Critical analyses of the experimental literature and data interpretation, as well as theoretical approaches used to predict properties, are made. In particular, computational and theoretical limitations and challenges are discussed, with a range of suggestions made to overcome these limitations, striving to achieve realistic predictions concerning the nature of emitting centers. A symbiotic relationship is required in which calculations focus on properties that can easily be measured, whilst experiments deliver results in a form facilitating mass-produced calculations

Intuitionistic Fuzzy Broad Learning System: Enhancing Robustness Against Noise and Outliers

In the realm of data classification, broad learning system (BLS) has proven to be a potent tool that utilizes a layer-by-layer feed-forward neural network. It consists of feature learning and enhancement segments, working together to extract intricate features from input data. The traditional BLS treats all samples as equally significant, which makes it less robust and less effective for real-world datasets with noises and outliers. To address this issue, we propose the fuzzy BLS (F-BLS) model, which assigns a fuzzy membership value to each training point to reduce the influence of noises and outliers. In assigning the membership value, the F-BLS model solely considers the distance from samples to the class center in the original feature space without incorporating the extent of non-belongingness to a class. We further propose a novel BLS based on intuitionistic fuzzy theory (IF-BLS). The proposed IF-BLS utilizes intuitionistic fuzzy numbers based on fuzzy membership and non-membership values to assign scores to training points in the high-dimensional feature space by using a kernel function. We evaluate the performance of proposed F-BLS and IF-BLS models on 44 UCI benchmark datasets across diverse domains. Furthermore, Gaussian noise is added to some UCI datasets to assess the robustness of the proposed F-BLS and IF-BLS models. Experimental results demonstrate superior generalization performance of the proposed F-BLS and IF-BLS models compared to baseline models, both with and without Gaussian noise. Additionally, we implement the proposed F-BLS and IF-BLS models on the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset, and promising results showcase the models effectiveness in real-world applications. The proposed methods offer a promising solution to enhance the BLS frameworks ability to handle noise and outliers