Bianchi Type-II String Cosmological Models in Normal Gauge for Lyra's Manifold with Constant Deceleration Parameter

The present study deals with a spatially homogeneous and anisotropic Bianchi-II cosmological models representing massive strings in normal gauge for Lyra's manifold by applying the variation law for generalized Hubble's parameter that yields a constant value of deceleration parameter. The variation law for Hubble's parameter generates two types of solutions for the average scale factor, one is of power-law type and other is of the exponential form. Using these two forms, Einstein's modified field equations are solved separately that correspond to expanding singular and non-singular models of the universe respectively. The energy-momentum tensor for such string as formulated by Letelier (1983) is used to construct massive string cosmological models for which we assume that the expansion ($\theta$) in the model is proportional to the component $\sigma^{1}_{~1}$ of the shear tensor $\sigma^{j}_{i}$. This condition leads to $A = (BC)^{m}$, where A, B and C are the metric coefficients and m is proportionality constant. Our models are in accelerating phase which is consistent to the recent observations. It has been found that the displacement vector $\beta$ behaves like cosmological term $\Lambda$ in the normal gauge treatment and the solutions are consistent with recent observations of SNe Ia. It has been found that massive strings dominate in the decelerating universe whereas strings dominate in the accelerating universe. Some physical and geometric behaviour of these models are also discussed.Comment: 24 pages, 10 figure

Biophysical and electrochemical studies of protein-nucleic acid interactions

This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail

Cerebral activations during viewing of food stimuli in adult patients with acquired structural hypothalamic damage: A functional neuroimaging study

BACKGROUND/OBJECTIVES: Obesity is common following hypothalamic damage due to tumours. Homeostatic and non-homeostatic brain centres control appetite and energy balance but their interaction in the presence of hypothalamic damage remains unknown. We hypothesized that abnormal appetite in obese patients with hypothalamic damage results from aberrant brain processing of food stimuli. We sought to establish differences in activation of brain food motivation and reward neurocircuitry in patients with hypothalamic obesity (HO) compared with patients with hypothalamic damage whose weight had remained stable. SUBJECTS/METHODS: In a cross-sectional study at a University Clinical Research Centre, we studied 9 patients with HO, 10 age-matched obese controls, 7 patients who remained weight-stable following hypothalamic insult (HWS) and 10 non-obese controls. Functional magnetic resonance imaging was performed in the fasted state, 1 h and 3 h after a test meal, while subjects were presented with images of high-calorie foods, low-calorie foods and non-food objects. Insulin, glucagon-like peptide-1, Peptide YY and ghrelin were measured throughout the experiment, and appetite ratings were recorded. RESULTS: Mean neural activation in the posterior insula and lingual gyrus (brain areas linked to food motivation and reward value of food) in HWS were significantly lower than in the other three groups (P=0.001). A significant negative correlation was found between insulin levels and posterior insula activation (P=0.002). CONCLUSIONS: Neural pathways associated with food motivation and reward-related behaviour, and the influence of insulin on their activation may be involved in the pathophysiology of HO.International Journal of Obesity advance online publicatio

Current and Future Drug Targets in Weight Management

Obesity will continue to be one of the leading causes of chronic disease unless the ongoing rise in the prevalence of this condition is reversed. Accumulating morbidity figures and a shortage of effective drugs have generated substantial research activity with several molecular targets being investigated. However, pharmacological modulation of body weight is extremely complex, since it is essentially a battle against one of the strongest human instincts and highly efficient mechanisms of energy uptake and storage. This review provides an overview of the different molecular strategies intended to lower body weight or adipose tissue mass. Weight-loss drugs in development include molecules intended to reduce the absorption of lipids from the GI tract, various ways to limit food intake, and compounds that increase energy expenditure or reduce adipose tissue size. A number of new preparations, including combinations of the existing drugs topiramate plus phentermine, bupropion plus naltrexone, and the selective 5-HT2C agonist lorcaserin have recently been filed for approval. Behind these leading candidates are several other potentially promising compounds and combinations currently undergoing phase II and III testing. Some interesting targets further on the horizon are also discussed

Application of nonlinear fatigue damage models in power electronic module wirebond structure under various amplitude loadings

This paper presents mean fatigue lifetime prediction of a wire-bond structure model in power electronic module using a failure physics approach that integrates high fidelity modelling and reduced order modelling. Loading current with variable amplitudes is applied to a finite element model of simplified wirebond structures. The resulting accumulated fatigue damage due to random loads is predicted by using reduced order modelling based on failure physics, a cycle counting algorithm, and various nonlinear fatigue damage models widely used in the literature. The reduced order modelling approach based on failure physics uses prediction data for the electro-thermo-mechanical behaviour of the wire-bond design of a power module obtained through non-linear transient finite element simulations, in particular for the fatigue life-time of the aluminium wire attached to the silicon chip of the wire in the module. The reduced order models that capture the black box function of the accumulated plastic strain are used in predicting the mean fatigue life time of the wire bond structure under random loads. One of the widely used cycle counting algorithms, rainflow counting algorithm, is used to count cycles of the temperature profile at the specific point of the wire bond structure in a power electronic module. The cycle data from the rainflow algorithm mean life time of the wire bond structure are predicted with various cumulative fatigue models. Non-linear cumulative fatigue models such as damage curve approach (DCA), double linear damage rule (DLDR), and double damage curve approach (DDCA), and linear cumulative fatigue damage model such as Palmgren–Miner rule are used to predict the mean fatigue life of the wire bond structure, and the results are compared