INTRPERITONEAL INJECTION OF GABA B RECEPTOR ANTAGONIST (CGP 35348) FOLLOWING NEONATAL BRAIN DAMAGE AFFECTS THE BLOOD CHEMISTRY IN ALBINO MICE

ABSTRACT Aim of this study was to demonstrate the effect of GABA B receptor antagonists (CGP 35348) on hematological and serum biochemical profile of albino mouse injected for 12 days following neonatal hypoxic ischemic insult. Blood samples from 35 albino mice [CGP35348 treated (N = 19) and saline treated (N= 16)] were collected from direct cardiac puncture and various hematological [blood glucose, packed cell volume (PCV), total WBC count, total RBC count] and selected serum biochemical parameters (cholesterol, AST, ALT, HDL, LDL total protein, triglycerides) were determined. Glucose (P < 0.001), TRBC (P < 0.001), MCV (P < 0.001), TWBC (P = 0.02) and PCV (P = 0.005) concentrations were significantly lower in CGP35348 treated as compared to saline treated albino mice. Gender based data analysis revealed that CGP 35348 had more drastic effects in blood chemistry of female than male albino mice as glucose (P = 0.002) and TRBC (P = 0.007) were the only significantly different parameters when compared between GABAB receptor antagonist and saline treated male albino mice while glucose (P = 0.01), TRBC (P = 0.01), TWBC (P = 0.01), PCV (P = 0.01) and MCV (P = 0.047) concentrations were significantly lower in CGP 35348 treated female albino mice than their respective control group indicating gender specific effect of hypoxic ischemic brain damage and CGP 35348 in albino mice

Self-interrupted synthesis of sterically hindered aliphatic polyamide dendrimers

Hydrolytically and enzymatically stable nanoscale synthetic constructs, with well-defined structures that exhibit antimicrobial activity, offer exciting possibilities for diverse applications in the emerging field of nanomedicine. Herein, we demonstrate that it is the core conformation, rather than periodicity, that ultimately controls the synthesis of sterically hindered aliphatic polyamide dendrimers. The latter self-interrupt at a predictable low generation number due to backfolding of their peripheral groups, which in turn leads to well-defined nanoarchitectures

Effect of temperature anisotropy on various modes and instabilities for a magnetized non-relativistic bi-Maxwellian plasma

Using kinetic theory for homogeneous collisionless magnetized plasmas, we present an extended review of the plasma waves and instabilities and discuss the anisotropic response of generalized relativistic dielectric tensor and Onsager symmetry properties for arbitrary distribution functions. In general, we observe that for such plasmas only those electromagnetic modes whose magnetic field perturbations are perpendicular to the ambient magneticeld, i.e.,B1 \perp B0, are effected by the anisotropy. However, in oblique propagation all modes do show such anisotropic effects. Considering the non-relativistic bi-Maxwellian distribution and studying the relevant components of the general dielectric tensor under appropriate conditions, we derive the dispersion relations for various modes and instabilities. We show that only the electromagnetic R- and L- waves, those derived from them and the O-mode are affected by thermal anisotropies, since they satisfy the required condition B1\perpB0. By contrast, the perpendicularly propagating X-mode and the modes derived from it (the pure transverse X-mode and Bernstein mode) show no such effect. In general, we note that the thermal anisotropy modifies the parallel propagating modes via the parallel acoustic effect, while it modifies the perpendicular propagating modes via the Larmor-radius effect. In oblique propagation for kinetic Alfven waves, the thermal anisotropy affects the kinetic regime more than it affects the inertial regime. The generalized fast mode exhibits two distinct acoustic effects, one in the direction parallel to the ambient magnetic field and the other in the direction perpendicular to it. In the fast-mode instability, the magneto-sonic wave causes suppression of the firehose instability. We discuss all these propagation characteristics and present graphic illustrations

Dynamics of MOOC Discussion Forums

In this integrated study of dynamics in MOOCs discussion forums, we analyze the interplay of temporal patterns, discussion content, and the social structure emerging from the communication using mixed methods. A special focus is on the yet under-explored aspect of time dynamics and influence of the course structure on forum participation. Our analyses show dependencies between the course structure (video opening time and assignment deadlines) and the overall forum activity whereas such a clear link could only be partially observed considering the discussion content. For analyzing the social dimension we apply role modeling techniques from social network analysis. While the types of user roles based on connection patterns are relatively stable over time, the high fluctuation of active contributors lead to frequent changes from active to passive roles during the course. However, while most users do not create many social connections they can play an important role in the content dimension triggering discussions on the course subject. Finally, we show that forum activity level can be predicted one week in advance based on the course structure, forum activity history and attributes of the communication network which enables identification of periods when increased tutor supports in the forum is necessary

Tunnelling Methods and Hawking's radiation: achievements and prospects

The aim of this work is to review the tunnelling method as an alternative description of the quantum radiation from black holes and cosmological horizons. The method is first formulated and discussed for the case of stationary black holes, then a foundation is provided in terms of analytic continuation throughout complex space-time. The two principal implementations of the tunnelling approach, which are the null geodesic method and the Hamilton-Jacobi method, are shown to be equivalent in the stationary case. The Hamilton-Jacobi method is then extended to cover spherically symmetric dynamical black holes, cosmological horizons and naked singularities. Prospects and achievements are discussed in the conclusions.Comment: Topical Review commissioned and accepted for publication by "Classical and Quantum Gravity". 101 pages; 6 figure

An Anatomy Massive Open Online Course as a Continuing Professional Development Tool for Healthcare Professionals

Massive open online courses (MOOCs) remain a novel and under-evaluated learning tool within anatomical and medical education. This study aimed to provide valuable information by using an anatomy MOOC to investigate the demographic profile, patterns of engagement and self-perceived benefits to healthcare professionals. A 21-item survey aimed at healthcare professionals was embedded into the Exploring Anatomy: The Human Abdomen MOOC, in April 2016. The course attracted 2711 individual learners with 94 of these completing the survey, and 79 of those confirming they worked full- or part-time as healthcare professionals. Variations in use across healthcare profession (allied healthcare professional, nurse or doctor) were explored using a Fisher’s exact test to calculate significance across demographic, motivation and engagement items; one-way ANOVA was used to compare self-perceived benefits. Survey data revealed that 53.2% were allied healthcare professionals, 35.4% nurses and 11.4% doctors. Across all professions, the main motivation for enrolling was to learn new things in relation to their clinical practice, with a majority following the prescribed course pathway and utilising core, and clinically relevant, material. The main benefits were in relation to improving anatomy knowledge, which enabled better support for patients. This exploratory study assessing engagement and self-perceived benefits of an anatomy MOOC has shown a high level of ordered involvement, with some indicators suggesting possible benefits to patients by enhancing the subject knowledge of those enrolled. It is suggested that this type of learning tool should be further explored as an approach to continuing professional, and interprofessional, education

Computationally Inexpensive 1D-CNN for the Prediction of Noisy Data of NOx Emissions From 500 MW Coal-Fired Power Plant

Coal-fired power plants have been used to meet the energy requirements in countries where coal reserves are abundant and are the key source of NOx emissions. Owing to the serious environmental and health concerns associated with NOx emissions, much work has been carried out to reduce NOx emissions. Sophisticated artificial intelligence (AI) techniques have been employed during the past few decades, such as least-squares support vector machine (LSSVM), artificial neural networks (ANN), long short-term memory (LSTM), and gated recurrent unit (GRU), to develop the NOx prediction model. Several studies have investigated deep neural networks (DNN) models for accurate NOx emission prediction. However, there is a need to investigate a DNN-based NOx prediction model that is accurate and computationally inexpensive. Recently, a new AI technique, convolutional neural network (CNN), has been introduced and proven superior for image class prediction accuracy. According to the best of the author’s knowledge, not much work has been done on the utilization of CNN on NOx emissions from coal-fired power plants. Therefore, this study investigated the prediction performance and computational time of one-dimensional CNN (1D-CNN) on NOx emissions data from a 500 MW coal-fired power plant. The variations of hyperparameters of LSTM, GRU, and 1D-CNN were investigated, and the performance metrics such as RMSE and computational time were recorded to obtain optimal hyperparameters. The obtained optimal values of hyperparameters of LSTM, GRU, and 1D-CNN were then employed for models’ development, and consequently, the models were tested on test data. The 1D-CNN NOx emission model improved the training efficiency in terms of RMSE by 70.6% and 60.1% compared to LSTM and GRU, respectively. Furthermore, the testing efficiency for 1D-CNN improved by 10.2% and 15.7% compared to LSTM and GRU, respectively. Moreover, 1D-CNN (26 s) reduced the training time by 83.8% and 50% compared to LSTM (160 s) and GRU (52 s), respectively. Results reveal that 1D-CNN is more accurate, more stable, and computationally inexpensive compared to LSTM and GRU on NOx emission data from the 500 MW power plant

Communication patterns in massively open online courses

Despite the hype and speculation about the role massively open online courses (MOOCs) may play in higher education, empirical research that explores the realities of interacting and learning in MOOCs is in its infancy. MOOCs have evolved from previous incarnations of online learning but are distinguished in their global reach and semi-synchronicity. Thus, it is important to understand the ways that learners from around the world interact in these settings. In this paper, we ask three questions: (1) What are the demographic characteristics of students that participate in MOOC discussion forums? (2) What are the discussion patterns that characterize their interactions? And (3) How does participation in discussion forums relate to students' final scores? Analysis of nearly 87,000 individuals from one MOOC reveals three key trends. First, forum participants tend to be young adults from the Western world. Secondly, these participants assemble and disperse as crowds, not communities, of learners. Finally, those that engage explicitly in the discussion forums are often higher-performing than those that do not, although the vast majority of forum participants receive "failing" marks. These findings have implications for the design and implementation of future MOOCs, and how they are conceptualised as part of higher education. © 2014 Elsevier Inc

Vote me up if you like my ideas! Experiences of learning in a MOOC

Higher education is described as being in a time of crisis. In the US, tuition costs have been escalating beyond the cost of inflation for some years, students are building up significant debt, whilst completion rates are in decline. The higher education system is creaking under the strain of additional scrutiny from government, funders, parents and students, yet is struggling to re-invent itself to reduce costs whilst improving quality and increasing flexibility for learners. In a Europe facing the financial downturn, universities struggle to retain their public service ethos when budgets are under huge pressure. Elsewhere in the world, many countries plan dramatic expansion to their higher education systems to fuel their growing economies, but they are being held up by lack of infrastructure and the increased intellectual capital that is needed. Higher education is becoming a global, Internet-based business. But few universities are equipped to fully embrace the potential that this offers. Few faculty were even aware of these seismic shifts until the recent publicity around Massive Open Online Courses (MOOCs) which provide access to free online courses by a wide range of universities and opened to students with any academic background. They are attracting millions of students from across the globe. To what extent though is the MOOC really revolutionary and disruptive, or is it being used cynically by the most elite institutions to further increase their brand power and assert their superiority, whilst the middle tier of institutions lose student numbers and academic credibility? Do MOOCs hold the potential to support the developing world in its academic ambitions, or are they just another example of neo-colonialism? And what about online learning more broadly – are we giving enough attention to the quiet revolution of blended learning that has been taken place over many years, and what that means for higher education