Emission Measures and Emission-measure-weighted Temperatures of Shocked ISM and Ejecta in Supernova Remnants

A goal of supernova remnant (SNR) evolution models is to relate fundamental parameters of a supernova (SN) explosion and progenitor star to the current state of its SNR. The SNR hot plasma is characterized by its observed X-ray spectrum, which yields electron temperature, emission measure and abundances. Depending on their brightness, the properties of the plasmas heated by the SNR forward shock, reverse shock or both can be measured. The current work utilizes models which are spherically symmetric. One dimensional hydrodynamic simulations are carried out for SNR evolution prior to onset of radiative losses. From these, we derive dimensionless emission measures and emission-measure-weighted temperatures, and we present fitting formulae for these quantities as functions of scaled SNR time. These models allow one to infer SNR explosion energy, circumstellar medium density, age, ejecta mass and ejecta density profile from SNR observations. The new results are incorporated into the SNR modelling code SNRPy. The code is demonstrated with application to three historical SNRs: Kepler, Tycho and SN1006.Comment: 50 pages, 10 figures, 5 table

समुद्रातील पिंजऱ्यात करावयाच्या मत्स्यशोतिसाठी स्थळ आणि प्रजाती यांची निवड

Cage culture is an utilisation of existing water bodies with little or no economic costs. The selection of a suitable site for a cage farm is indispensible for their effective function, particularly in relation to proper water quality within the cage and reduced environmental impacts around the cage and for the economic viability of the cage farm. The natural tolerance of species should be studied for assessment of suitable site

Assessing Neuronal Interactions of Cell Assemblies during General Anesthesia

Understanding the way in which groups of cortical neurons change their individual and mutual firing activity during the induction of general anesthesia may improve the safe usage of many anesthetic agents. Assessing neuronal interactions within cell assemblies during anesthesia may be useful for understanding the neural mechanisms of general anesthesia. Here, a point process generalized linear model (PPGLM) was applied to infer the functional connectivity of neuronal ensembles during both baseline and anesthesia, in which neuronal firing rates and network connectivity might change dramatically. A hierarchical Bayesian modeling approach combined with a variational Bayes (VB) algorithm is used for statistical inference. The effectiveness of our approach is evaluated with synthetic spike train data drawn from small and medium-size networks (consisting of up to 200 neurons), which are simulated using biophysical voltage-gated conductance models. We further apply the analysis to experimental spike train data recorded from rats' barrel cortex during both active behavior and isoflurane anesthesia conditions. Our results suggest that that neuronal interactions of both putative excitatory and inhibitory connections are reduced after the induction of isoflurane anesthesia.National Institutes of Health (U.S.) (NIH Grants DP1-OD003646

18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells

Background: One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes. Results: The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. Analysis of qRT-PCR data from virus and mock infected cells using NormFinder and BestKeeper software programmes found that 18S rRNA was the most stable gene in HBECs, PTECs and avian lung cells. Conclusions: Based on the presented data from cell culture models (HBECs, PTECs, chicken and duck lung cells) infected with a range of influenza viruses, we found that 18S rRNA is the most stable reference gene for normalising qRT-PCR data. Expression levels of the other housekeeping genes evaluated in this study (including ACTB and GPADH) were highly affected by influenza virus infection and hence are not reliable as reference genes for RNA normalisation

Seismic fragility assessment of bridges with as-built and retrofitted splice-deficient columns

A significant proportion of existing bridges in high seismic regions were constructed prior to the 1970s. As a result of poor reinforcement detailing, pre-1970s bridge columns are susceptible to lap-splice or shear failure in the plastic region. Given the high economic impact of retrofitting all pre-1970s reinforced concrete (RC) bridges, it is essential to identify the most vulnerable bridges for retrofit prioritisation. Analytical fragility functions are useful for quantifying the seismic vulnerability of existing bridge stock. However, the accuracy of these fragility functions relies on the adequacy of the adopted modelling approach. This paper presents a hinge-type modelling approach for capturing the seismic response of as-built splice-deficient and retrofitted RC bridge columns. Fragility analysis is carried out for typical seat and diaphragm abutment two-span bridges using the proposed hinge-type modelling approach. The results showed that the vulnerability of the bridges depends on the column failure mode and the limit state under consideration. Also, the common notion that the column is the most vulnerable component may not necessarily be true. The study underscored that retrofitting columns without retrofitting other components may not effectively mitigate the damage and associated risk

Influence of system parameters on the hysteresis characteristics of a horizontal Rijke tube

The influence of system parameters such as heater power, heater location and mass flow rate on the hysteresis characteristics of a horizontal Rijke tube is presented in this paper. It is observed that a hysteresis zone is present for all the mass flow rates considered in the present study. A power law relation is established between the non-dimensional hysteresis width and the Strouhal number, defined as the ratio between convective time scale and acoustic time scale. The transition to instability in a horizontal Rijke tube is found to be subcritical in all the experiments performed in this study. When heater location is chosen as the control parameter, period-2 oscillations are found for specific values of mass flow rate and heater power

Discrete- and Continuous-Time Probabilistic Models and Algorithms for Inferring Neuronal UP and DOWN States

UP and DOWN states, the periodic fluctuations between increased and decreased spiking activity of a neuronal population, are a fundamental feature of cortical circuits. Understanding UP-DOWN state dynamics is important for understanding how these circuits represent and transmit information in the brain. To date, limited work has been done on characterizing the stochastic properties of UP-DOWN state dynamics. We present a set of Markov and semi-Markov discrete- and continuous-time probability models for estimating UP and DOWN states from multiunit neural spiking activity. We model multiunit neural spiking activity as a stochastic point process, modulated by the hidden (UP and DOWN) states and the ensemble spiking history. We estimate jointly the hidden states and the model parameters by maximum likelihood using an expectation-maximization (EM) algorithm and a Monte Carlo EM algorithm that uses reversible-jump Markov chain Monte Carlo sampling in the E-step. We apply our models and algorithms in the analysis of both simulated multiunit spiking activity and actual multi- unit spiking activity recorded from primary somatosensory cortex in a behaving rat during slow-wave sleep. Our approach provides a statistical characterization of UP-DOWN state dynamics that can serve as a basis for verifying and refining mechanistic descriptions of this process.National Institutes of Health (U.S.) (Grant R01-DA015644)National Institutes of Health (U.S.) (Director Pioneer Award DP1- OD003646)National Institutes of Health (U.S.) (NIH/NHLBI grant R01-HL084502)National Institutes of Health (U.S.) (NIH institutional NRSA grant T32 HL07901

Comparative efficacy of behavioral despair models in depicting antidepressant-like effect of tramadol

Background: Experimental evaluation of antidepressants (ADs) in diverse animal models is the need of time. There is a constant search for newer models with ease and rapid screening of AD activity. As earlier studies highlight AD effect of tramadol in animal models, the study was undertaken to compare antidepressant-like effect of tramadol in two models of behavioural despair in mice.Methods: Tramadol was administered intraperitoneally (i.p.) at two different doses of 20 and 40 mg/kg, once daily for 7 days to Swiss albino mice. The immobility period of control and drug-treated mice was recorded in tail suspension test (TST) and forced swim test (FST). The antidepressant (AD) effect of tramadol was compared with control (NS) and reference drug imipramine (10 mg/kg, p.o.), administered orally (p.o.) for seven successive days.Results: Tramadol in tail suspension test (TST) produced significant antidepressant effect at 20 and 40 mg/kg doses, as depicted by reduction in immobility period of drug-treated mice compared to control group. The efficacy of tramadol at dose of 40 mg/kg was comparable to that of imipramine treated group (p0.05).Conclusion: The results of the present study depict antidepressant-like activity of tramadol in both the models of depression TST and FST. But TST in mice seems to be more efficacious in appraising the antidepressant like effect of tramadol

Experimental investigation on the susceptibility of minimal networks to a change in topology and number of oscillators

Understanding the global dynamical behaviour of a network of coupled oscillators has been a topic of immense research in many fields of science and engineering. Various factors govern the resulting dynamical behaviour of such networks, including the number of oscillators and their coupling schemes. Although these factors are seldom significant in large populations, a small change in them can drastically affect the global behaviour in small populations. In this paper, we perform an experimental investigation on the effect of these factors on the coupled behaviour of a minimal network of candle-flame oscillators. We observe that strongly coupled oscillators exhibit the global behaviour of in-phase synchrony and amplitude death, irrespective of the number and the topology of oscillators. However, when they are weakly coupled, their global behaviour exhibits the intermittent occurrence of multiple stable states in time. In addition to states of clustering, chimera, and weak chimera, we report the experimental discovery of partial amplitude death in a network of candle-flame oscillators. We also show that closed-loop networks tend to hold global synchronization for longer duration as compared to open-loop networks. We believe that our results would find application in real-life problems such as power grids, neuronal networks, and seizure dynamics.Comment: 10 pages, 8 figures, not submitted anywher