Anomalous lateral diffusion in a viscous membrane surrounded by viscoelastic media

We investigate the lateral dynamics in a purely viscous lipid membrane surrounded by viscoelastic media such as polymeric solutions. We first obtain the generalized frequency-dependent mobility tensor and focus on the case when the solvent is sandwiched by hard walls. Due to the viscoelasticity of the solvent, the mean square displacement of a disk embedded in the membrane exhibits an anomalous diffusion. An useful relation which connects the mean square displacement and the solvent modulus is provided. We also calculate the cross-correlation of the particle displacements which can be applied for two-particle tracking experiments.Comment: 6 pages, 2 figure

Czochralski crystal growth: Modeling study

The modeling study of Czochralski (Cz) crystal growth is reported. The approach was to relate in a quantitative manner, using models based on first priniciples, crystal quality to operating conditions and geometric variables. The finite element method is used for all calculations

A Novel Skeleton Extraction Algorithm for 3d Wireless Sensor Networks

Wireless sensor network design is critical and resource allocation is a major problem which remains to be solved satisfactorily. The discrete nature of sensor networks renders the existing skeleton extraction algorithms inapplicable. 3D topologies of sensor networks for practical scenarios are considered in this paper and the research carried out in the field of skeleton extraction for three dimensional wireless sensor networks. A skeleton extraction algorithm applicable to complex 3D spaces of sensor networks is introduced in this paper and is represented in the form of a graph. The skeletal links are identified on the basis of a novel energy utilization function computed for the transmissions carried out through the network. The frequency based weight assignment function is introduced to identify the root node of the skeleton graph. Topological clustering is used to construct the layered topological sets to preserve the nature of the topology in the skeleton graph. The skeleton graph is constructed with the help of the layered topological sets and the experimental results prove the robustness of the skeleton extraction algorithm introduced. Provisioning of additional resources to skeletal nodes enhances the sensor network performance by 20% as proved by the results presented in this paper

Estimation of Radioprotective Effects of Garcinia Indica Methanol Extract in Swiss Albino Mice

The radio protective effectiveness of methanol extract of Garcinia indica against whole body gamma radiation was premeditated in Swiss albino mice. The oral administration of Garcinia indica extract at 800 mg / kg body weight / day for 15 consecutive days before whole body exposure to radiation was found to be effective with the LD50/30 values of 7.21 and 8.83 Gy for irradiation alone and Garcinia indica andirradiation group, respectively, giving a dose reduction factor of 1.42. This effect of Garcinia indica as the modulation of the radiation-induced decrease of reduced glutathione and the radiation-induced increase in lipid per oxidation assessed in the liver and the bloo

Examining the Drivers of Stock Prices of Private Sector Banks in India

Indian private sector banking stocks have been rebounding from a massive selloff. Private sector banks which have traditionally maintained their asset quality and profitability when compared to their public-sector counterparts, have recently seen their asset quality erode. Given that private sector banks play an influential role in the Indian economy, it would be helpful to understand the key drivers of private bank stock prices. This paper studied the influence of some key micro and macro determinants on the stock prices of all listed private sector banks in India over the 12 years from 2008-2019. Panel regression models were fit to study the relationship between the variables. Liquidity, profitability, growth, inflation and exchange rate indicators proved to be important influencers of the stock prices of private sector banks in India. The study provides evidence for the Fisher effect suggesting that private bank stocks can provide good inflation adjusted returns over time. Stakeholders of these banks can focus on these determinants which will contribute to shareholder value over time. Keywords: Indian Private Banks, Stock Market capitalization, Liquidity, Exchange rates, GDP, Panel regression DOI: 10.7176/EJBM/13-11-04 Publication date:June 30th 202

Software Metrics Evaluation Based on Entropy

Software engineering activities in the Industry has come a long way with various improve- ments brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the expectation for high quality products demand the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this paper the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. We have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness

A Search for Sub-Millisecond Pulsars

We have conducted a search of 19 southern Galactic globular clusters for sub-millisecond pulsars at 660 MHz with the Parkes 64-m radio telescope. To minimize dispersion smearing we used the CPSR baseband recorder, which samples the 20 MHz observing band at the Nyquist rate. By possessing a complete description of the signal we could synthesize an optimal filterbank in software, and in the case of globular clusters of known dispersion measure, much of the dispersion could be removed using coherent techniques. This allowed for very high time resolution (25.6 us in most cases), making our searches in general sensitive to sub-millisecond pulsars with flux densities greater than about 3 mJy at 50 cm. No new pulsars were discovered, placing important constraints on the proportion of pulsars with very short spin periods in these clusters.Comment: 8 pages, 3 figures, to appear in Ap

Earth Science Data Analysis in the Era of Big Data

Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment. To illustrate the effects of combining a Big Data technology with an effective means of collaboration, we relate the (fictitious) experience of an early-career Earth science researcher a few years beyond the present, interlaced and contrasted with reminiscences of its recent past (i.e., the present)

Investigation of complete and incomplete fusion in 7^{7}Li+124^{124}Sn reaction around Coulomb barrier energies

The complete and incomplete fusion cross sections for $^{7}$Li+$^{124}$Sn reaction were measured using online and offline characteristic $\gamma$-ray detection techniques. The complete fusion (CF) cross sections at energies above the Coulomb barrier were found to be suppressed by $\sim$ 26 \% compared to the coupled channel calculations. This suppression observed in complete fusion cross sections is found to be commensurate with the measured total incomplete fusion (ICF) cross sections. There is a distinct feature observed in the ICF cross sections, i.e., $\textit{t}$-capture is found to be dominant than $\alpha$-capture at all the measured energies. A simultaneous explanation of complete, incomplete and total fusion (TF) data was also obtained from the calculations based on Continuum Discretized Coupled Channel method with short range imaginary potentials. The cross section ratios of CF/TF and ICF/TF obtained from the data as well as the calculations showed the dominance of ICF at below barrier energies and CF at above barrier energies.Comment: 9 pages, 8 figure

Fractal Dimensions in Perceptual Color Space: A Comparison Study Using Jackson Pollock's Art

The fractal dimensions of color-specific paint patterns in various Jackson Pollock paintings are calculated using a filtering process which models perceptual response to color differences (\Lab color space). The advantage of the \Lab space filtering method over traditional RGB spaces is that the former is a perceptually-uniform (metric) space, leading to a more consistent definition of ``perceptually different'' colors. It is determined that the RGB filtering method underestimates the perceived fractal dimension of lighter colored patterns but not of darker ones, if the same selection criteria is applied to each. Implications of the findings to Fechner's 'Principle of the Aesthetic Middle' and Berlyne's work on perception of complexity are discussed.Comment: 21 pp LaTeX; two postscript figure