Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

High-efficiency calculation method for watershed rainfall-runoff routing using one-dimensional dynamic wave equations

Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations (HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictor-corrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.     

Identification of Gleissberg Cycles and a Rising Trend in a 315-Year-Long Series of Sunspot Numbers

We show in this short note that the method of singular spectrum analysis (SSA) is able to clearly extract a strong, clean, and clear component from the longest available sunspot (International Sunspot Number, ISN) time series (1700?–?2015) that cannot be an artifact of the method and that can be safely identified as the Gleissberg cycle. This is not a small component, as it accounts for 13% of the total variance of the total original signal. Almost three and a half clear Gleissberg cycles are identified in the sunspot number series. Four extended solar minima (XSM) are determined by SSA, the latest around 2000 (Cycle 23/24 minimum). Several authors have argued in favor of a double-peaked structure for the Gleissberg cycle, with one peak between 55 and 59 years and another between 88 and 97 years. We find no evidence of the former: solar activity contains an important component that has undergone clear oscillations of \(\approx90\) years over the past three centuries, with some small but systematic longer-term evolution of “instantaneous” period and amplitude. Half of the variance of solar activity on these time scales can be satisfactorily reproduced as the sum of a monotonous multi-secular increase, a \(\approx90\)-year Gleissberg cycle, and a double-peaked (\(\approx10.0\) and 11.0 years) Schwabe cycle (the sum amounts to 46% of the total variance of the signal). The Gleissberg-cycle component definitely needs to be addressed when attempting to build dynamo models of solar activity. The first SSA component offers evidence of an increasing long-term trend in sunspot numbers, which is compatible with the existence of the modern grand maximum.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

Expression of putative zinc-finger protein lcn61 gene in lymphocystis disease virus China （LCDV-cn） genome

An open reading frame (lcn61) of lymphocystis disease virus China (LCDV-cn), probably responsible for encoding putative zinc-finger proteins was amplified and inserted into pET24a (+) vector. Then it expressed in E. coli BL21 (DE3), and His-tag fusion protein of high yield was obtained. It was found that the fusion protein existed in E. coli mainly as inclusion bodies. The bioinformatics analysis indicates that LCN61 is C2H2 type zinc-finger protein containing four C2H2 zinc-finger motifs. This work provides a theory for functional research of lcn61 gene. Supported by High Technology Research and Development Program of China (863 Program, No. 2006AA100309)     

Current and thermohaline characteristics of the Arabian Sea during January 1998

Based on a ship survey during January 1998, the characteristics of the flow, the thermohaline properties and the volume transport of the Arabian Sea are discussed. A strong westward flow exists between 10.5?N and 11?N, part of which turns to the south as the Somali current near the coast at about 10?N and the rest turns north. At the passage between the African continent and the So- cotra Island, the northern branch separates into two flows: the left one enters the passage and the right one flows eastward along the southern slope of the island. Off the island the flow separates once more, most of it meandering northeast and a small fraction flow- ing southeast. Volume transport calculation suggests that the tidal transport is one or two orders of magnitude smaller than the total transport in this region and it becomes more important near the coast. The average velocity of the flow in the upper layer (0-150 m) is about 20 cm s-1, with a maximum of 53 cm s-1 appearing east of the Socotra Island, and the subsurface layer (200-800 m) has an aver- age velocity of 8.6 cm s-1; the velocity becomes smaller at greater depths. The depth of the seasonal thermocline is about 100 m, above which there is a layer with well mixed temperature and dissolved oxygen. High-salinity and oxygen-rich water appears near the surface of the northern Arabian Sea; a salinity maximum and oxygen minimum at 100 m depth along 8?N testifies the subduction of surface water from the northern Arabian Sea. Waters from the Red Sea and the Persian Gulf also influence the salinity of the area.     

Preliminary Study on Applicability of Microsatellite DNA Primers from Parasite Protozoa Trypanosoma cruzi in Free-living Protozoa

1　Introduction　Generallyknownasacodominantgeneticmarker ,microsatellitehasbeenwidelyusedinstudiesonpopu lationgenetics,high resolutiongenotyping ,genemap ping ,evolution ,linkageanalysis ,conservationbiology ,behaviouralecology ,relationsbetweenparasite…     

VARIATIONAL ITERATION SOLVING METHOD FOR SEA-AIR OSCILLATOR MODEL OF INTERDECADAL CLIMATE FLUCTUATIONS

1IN T R O D U C T IO NInteractionsbetween the ocean and atmosphere con-tributeto climatefluctuationosver a broad spectrum oftime scales.Studiesof those interactionhsave farfo-cused on El Ni o-SouthernOscillation(ENSO)phe-nomenon thathas a period of3to4yea…     

A search for periodicities from a ULX in the LINER galaxy NGC 4736

We report our findings on a new quasi-periodic oscillation (QPO) and a long period from the ultraluminous X-ray source (ULX) X-2 in nearby galaxy NGC 4736 based on the Chandra and XMM-Newton archival data. To examine the timing properties, power density spectra of the source have been obtained using Fast Fourier Transform. Also the spectral parameters of the source have been calculated by obtaining and fitting the energy spectra. Power density spectrum of this source reveals a QPO peak at \(0.73_{-0.14}^{+0.16}~\mathrm{mHz}\) with an fractional rms variability of 16 % using the Chandra data (in the year 2000-lower state of the source). The XMM-Newton data analysis indicates a peak at \(0.53_{-0.35}^{+0.09}~\mathrm{mHz}\) with a fractional rms variation of 5 % (in the year 2006-higher state of the source). These recovered QPOs overlap within errors and may be the same oscillation. In addition, we detect a long periodicity or a QPO in the Chandra data of about (5.2±2.0)×10^?5 Hz (～5.4 h) over 3 σ confidence level. If this is a QPO, it is the lowest QPO detected from a ULX. The mass of the compact object in ULX X-2 is estimated using the Eddington luminosity and a disk blackbody model in the range (10–80) M _⊙.