Geochemistry of K/T boundaries in India and contributions of Deccan volcanism

Three possible Cretaceous/Tertiary (K/T) boundary sections in the Indian subcontinent were studied for their geochemical and fossil characteristics. These include two marine sections of Meghalaya and Zanskar and one continental section of Nagpur. The Um Sohryngkew river section of Meghalaya shows a high iridium, osmium, iron, cobalt, nickel and chromium concentration in a 1.5 cm thick limonitic layer about 30 cm below the planktonic Cretaceous-Palaeocene boundary identified by the characteristic fossils. The Bottaccione and Contessa sections at Gubbio were also analyzed for these elements. The geochemical pattern at the boundary at the Um Sohryngkew river and Gubbio sections are similar but the peak concentrations and the enrichment factors are different. The biological boundary is not as sharp as the geochemical boundary and the extinction appears to be a prolonged process. The Zanskar section shows, in general, similar concentration of the siderophile, lithophile and rare earth elements but no evidence of enrichment of siderophiles has so far been observed. The Takli section is a shallow inter-trappean deposit within the Deccan province, sandwiched between flow 1 and flow 2. The geochemical stratigraphy of the inter-trappeans is presented. The various horizons of ash, clay and marl show concentration of Fe and Co, generally lower than the adjacent basalts. Two horizons of slight enrichment of iridium are found within the ash layers, one near the contact of flow 1 and other near the contact of flow 2, where iridium occurs at 170 and 260 pg/g. These levels are lower by a factor of 30 compared to Ir concentration in the K/T boundary in Meghalaya section. If the enhanced level of some elements in a few horizons of the ash layer are considered as volcanic contribution by some fractionation processes than the only elements for which it occurs are REE, Ir and possibly Cr

Envelope solitons induced by high-order effects of light-plasma interaction

The nonlinear coupling between the light beams and non-resonant ion density perturbations in a plasma is considered, taking into account the relativistic particle mass increase and the light beam ponderomotive force. A pair of equations comprising a nonlinear Schrodinger equation for the light beams and a driven (by the light beam pressure) ion-acoustic wave response is derived. It is shown that the stationary solutions of the nonlinear equations can be represented in the form of a bright and dark/gray soliton for one-dimensional problem. We have also present a numerical analysis which shows that our bright soliton solutions are stable exclusively for the values of the parameters compatible with of our theory.Comment: 9 pages, 5 figure

Rogue seasonality detection in supply chains

Rogue seasonality or unintended cyclic variability in order and other supply chain variables is an endogenous disturbance generated by a company’s internal processes such as inventory and production control systems. The ability to automatically detect, diagnose and discriminate rogue seasonality from exogenous disturbances is of prime importance to decision makers. This paper compares the effectiveness of alternative time series techniques based on Fourier and discrete wavelet transforms, autocorrelation and cross correlation functions and autoregressive model in detecting rogue seasonality. Rogue seasonalities of various intensities were generated using different simulation designs and demand patterns to evaluate each of these techniques. An index for rogue seasonality, based on the clustering profile of the supply chain variables was defined and used in the evaluation. The Fourier transform technique was found to be the most effective for rogue seasonality detection, which was also subsequently validated using data from a steel supply network

Nonlinear dynamics of large amplitude dust acoustic shocks and solitary pulses in dusty plasmas

We present a fully nonlinear theory for dust acoustic (DA) shocks and DA solitary pulses in a strongly coupled dusty plasma, which have been recently observed experimentally by Heinrich et al. [Phys. Rev. Lett. 103, 115002 (2009)], Teng et al. [Phys. Rev. Lett. 103, 245005 (2009)], and Bandyopadhyay et al. [Phys. Rev. Lett. 101, 065006 (2008)]. For this purpose, we use a generalized hydrodynamic model for the strongly coupled dust grains, accounting for arbitrary large amplitude dust number density compressions and potential distributions associated with fully nonlinear nonstationary DA waves. Time-dependent numerical solutions of our nonlinear model compare favorably well with the recent experimental works (mentioned above) that have reported the formation of large amplitude non-stationary DA shocks and DA solitary pulses in low-temperature dusty plasma discharges.Comment: 9 pages, 4 figures. To be published in Physical Review

Stabilisation of BGK modes by relativistic effects

Context. We examine plasma thermalisation processes in the foreshock region of astrophysical shocks within a fully kinetic and self-consistent treatment. We concentrate on proton beam driven electrostatic processes, which are thought to play a key role in the beam relaxation and the particle acceleration. Our results have implications for the effectiveness of electron surfing acceleration and the creation of the required energetic seed population for first order Fermi acceleration at the shock front. Aims. We investigate the acceleration of electrons via their interaction with electrostatic waves, driven by the relativistic Buneman instability, in a system dominated by counter-propagating proton beams. Methods. We adopt a kinetic Vlasov-Poisson description of the plasma on a fixed Eulerian grid and observe the growth and saturation of electrostatic waves for a range of proton beam velocities, from 0.15c to 0.9c. Results. We can report a reduced stability of the electrostatic wave (ESW) with increasing non-relativistic beam velocities and an improved wave stability for increasing relativistic beam velocities, both in accordance with previous findings. At the highest beam speeds, we find the system to be stable again for a period of ≈160 plasma periods. Furthermore, the high phase space resolution of the Eulerian Vlasov approach reveals processes that could not be seen previously with PIC simulations. We observe a, to our knowledge, previously unreported secondary electron acceleration mechanism at low beam speeds. We believe that it is the result of parametric couplings to produce high phase velocity ESW’s which then trap electrons, accelerating them to higher energies. This allows electrons in our simulation study to achieve the injection energy required for Fermi acceleration, for beam speeds as low as 0.15c in unmagnetised plasma

Nonlinear propagation of light in Dirac matter

The nonlinear interaction between intense laser light and a quantum plasma is modeled by a collective Dirac equation coupled with the Maxwell equations. The model is used to study the nonlinear propagation of relativistically intense laser light in a quantum plasma including the electron spin-1/2 effect. The relativistic effects due to the high-intensity laser light lead, in general, to a downshift of the laser frequency, similar to a classical plasma where the relativistic mass increase leads to self-induced transparency of laser light and other associated effects. The electron spin-1/2 effects lead to a frequency up- or downshift of the electromagnetic (EM) wave, depending on the spin state of the plasma and the polarization of the EM wave. For laboratory solid density plasmas, the spin-1/2 effects on the propagation of light are small, but they may be significant in super-dense plasma in the core of white dwarf stars. We also discuss extensions of the model to include kinetic effects of a distribution of the electrons on the nonlinear propagation of EM waves in a quantum plasma.Comment: 9 pages, 2 figure

Nonlinear structures: explosive, soliton and shock in a quantum electron-positron-ion magnetoplasma

Theoretical and numerical studies are performed for the nonlinear structures (explosive, solitons and shock) in quantum electron-positron-ion magnetoplasmas. For this purpose, the reductive perturbation method is employed to the quantum hydrodynamical equations and the Poisson equation, obtaining extended quantum Zakharov-Kuznetsov equation. The latter has been solved using the generalized expansion method to obtain a set of analytical solutions, which reflect the possibility of the propagation of various nonlinear structures. The relevance of the present investigation to the white dwarfs is highlighted.Comment: 7 figure

Transition Metal Complexes of 6-Methyl-2-Amino Benzothiazole -Part III

Complexes of the type ML/sub2/X/sub2/ and ML/sub4/X/sub2/ (where M=Cu(II),Ni(II), Co(II), Mn(II), Zin(II), Hg(II) and Cd(II); L=6-methyl-2-aminobenzothiazole;X=-I, -NCS and -OAC have been isolated and characterised on the basis of analytical, magnetic moment, molar conductance, electronic and i.r.spectal data. The antifungal screening of Cu(II) and Hg(II) complexes is also reported

Breast cancer data analysis for survivability studies and prediction

© 2017 Elsevier B.V. Background Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. Objective The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties. Methods Unsupervised data mining methods viz. the self-organising map (SOM) and density-based spatial clustering of applications with noise (DBSCAN) is used to create patient cohort clusters. These clusters, with associated patterns, were used to train multilayer perceptron (MLP) model for improved patient survivability analysis. A large dataset available from SEER program is used in this study to identify patterns associated with the survivability of breast cancer patients. Information gain was computed for the purpose of variable selection. All of these methods are data-driven and require little (if any) input from users or experts. Results SOM consolidated patients into cohorts of patients with similar properties. From this, DBSCAN identified and extracted nine cohorts (clusters). It is found that patients in each of the nine clusters have different survivability time. The separation of patients into clusters improved the overall survival prediction accuracy based on MLP and revealed intricate conditions that affect the accuracy of a prediction. Conclusions A new, entirely data driven approach based on unsupervised learning methods improves understanding and helps identify patterns associated with the survivability of patient. The results of the analysis can be used to segment the historical patient data into clusters or subsets, which share common variable values and survivability. The survivability prediction accuracy of a MLP is improved by using identified patient cohorts as opposed to using raw historical data. Analysis of variable values in each cohort provide better insights into survivability of a particular subgroup of breast cancer patients

Can apparent superluminal neutrino speeds be explained as a quantum weak measurement?

Probably not.Comment: 10 pages, 1 figur