Stability analysis of VBT Echelle spectrograph for precise radial velocity measurements

A fiber-fed Echelle spectrograph at 2.3 m Vainu Bappu Telescope (VBT), Kavalur, has been in operation since 2005. Owing to various technological advancements in precision spectroscopy in recent years, several research avenues have been opened in observational astronomy. These developments have created a demand to improve the Doppler precision of our spectrograph. Currently, the stability of the instrument is compromised by the temperature and pressure fluctuations inside the Echelle room. Further, a better wavelength calibration approach is needed to carefully track and disentangle the instrumental effects from stellar spectra. While planning a possible upgrade with an Iodine absorption gas cell, we measured the raw stability of the spectrograph using a series of calibration frames taken with the ThAr gas discharge lamp. The time series data were analysed with cross-correlation method and the shift in ThAr emission lines was accurately measured across different Echelle orders. In this paper, we present our stability analysis methodology and results for the Kavalur spectrograph. We also identify possible sources of error and discuss our strategy to mitigate them.Comment: 12 pages, 7 figures, Accepted in Journal of Optics (India

Spiders (Araneae) from Agricultural fields near foothill of Satpura Mountain ranges of Amravati District, Maharashtra, India.

This paper deals with the study of spider distribution in agricultural fields adjoining the Satpura Mountain Ranges of the Amravati district. The total collection of spiders comprises 12 families, 37 genera and 76 species. The Araneidae and Thomisidae families were dominant, followed by Saltisidae from the selected agricultural area. Lycosidae and Tetragnathidae were also found in a decreasing number of species due to their specific habitation. The analysis of guild structure revealed six feeding guilds. Orb web weavers and Ambushers constituted the dominant feeding guild representing 33% and 22% of the total collection respectively. Stalkers and ground runners represent 20% and 17% and foliage hunters and sheet web weavers represent 5% and 3% respectively. A new species of genus Sassacus (Beetle like spider), family Saltisidae was found for the first time in the Vidarbha region. The richness of spider diversity is a sign of the overall biodiversity which is a useful indicator of the species richness of the agro-ecosystem.
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WRKY Transcription Factors: Molecular Regulation and Stress Responses in Plants

Plants in their natural habitat have to face multiple stresses simultaneously. Evolutionary adaptation of developmental, physiological and biochemical parameters give advantage over a single window of stress but not multiple. On the other hand transcription factors like WRKY can regulate diverse responses through a complicated network of genes. So molecular orchestration of WRKYs in plant may provide the most anticipated outcome of simultaneous multiple responses. Activation or repression through W-box and W-box like sequences is regulated at transcriptional, translational and domain level. Because of the tight regulation involved in specific recognition and binding of WRKYs to downstream promoters, they have become promising candidate for crop improvement. Epigenetic, retrograde and proteasome mediated regulation enable WRKYs to attain the dynamic cellular homeostatic reprograming. Overexpression of several WRKYs face the paradox of having several beneficial affects but with some unwanted traits. These overexpression-associated undesirable phenotypes need to be identified and removed for proper growth, development and yeild. Taken together, we have highlighted the diverse regulation and multiple stress response of WRKYs in plants along with the future prospects in this field of research

Prediction of storability of organically produced paddy seeds through natural and accelerated ageing techniques

The present study was conducted to know the storage potential of organically produced paddy seeds in the Department of Seed Science and Technology, University of Agricultural Sciences, Raichur. The seed lot were divided into two parts, one part was stored in cloth bag for a period of 12 months under ambient conditions. At thesame time another set of seeds were subjected to accelerated ageing at 42 + 10C temperature and 90 per cent relative humidity (RH) for a period of 0-12 days. Among the ageing methods, artificially aged seeds showed drastic decreases in seed quality as compared to natural ageing. Among the treatments T9 (37.5 % FYM + 37.5 % vermicompost + 25 % neem cake + foliar spray of panchagavya on 30, 60, 90 and 120 DAT) recorded significantly highest seed quality parameters viz., seed germination (97.81 %), seedling length (29.42 cm) and SVI (2878) at initial stage in both the method of aging and at the end of storage period; seed germination (71.23 and 87.33 %), seedling length (19.66 and 27.00 cm) and SVI (1400 and 2358) in accelerated ageing (AA) and natural ageing (NA) respectively, whereas, lowest in control (Inorganic treatment). The seed quality parameters of four days of AA were similar to that of six months of NA. Hence, storability of organically produced paddy seeds were better as compared to inorganic seeds and it can be predicted that four days of AA is equal to six months of NA. The information generated will be useful in retention or disposal of a particular variety or seed lot

Classification of nuclear receptors based on amino acid composition and dipeptide composition

Nuclear receptors are key transcription factors that regulate crucial gene networks responsible for cell growth, differentiation, and homeostasis. Nuclear receptors form a superfamily of phylogenetically related proteins and control functions associated with major diseases (e.g. diabetes, osteoporosis, and cancer). In this study, a novel method has been developed for classifying the subfamilies of nuclear receptors. The classification was achieved on the basis of amino acid and dipeptide composition from a sequence of receptors using support vector machines. The training and testing was done on a non-redundant data set of 282 proteins obtained from the NucleaRDB data base (1). The performance of all classifiers was evaluated using a 5-fold cross validation test. In the 5-fold cross-validation, the data set was randomly partitioned into five equal sets and evaluated five times on each distinct set while keeping the remaining four sets for training. It was found that different subfamilies of nuclear receptors were quite closely correlated in terms of amino acid composition as well as dipeptide composition. The overall accuracy of amino acid composition-based and dipeptide compositionbased classifiers were 82.6 and 97.5%, respectively. Therefore, our results prove that different subfamilies of nuclear receptors are predictable with considerable accuracy using amino acid or dipeptide composition. Furthermore, based on above approach, an online web service, NRpred, was developed, which is available at www.imtech.res.in/raghava/nrpred

An analysis of ultraviolet spectra of Extreme Helium Stars and new clues to their origins

Abundances of about 18 elements including the heavy elements Y and Zr are determined from Hubble Space Telescope Space Telescope Imaging Spectrograph ultraviolet spectra of seven extreme helium stars (EHes): LSE 78, BD+10 2179, V1920 Cyg, HD 124448, PV Tel, LS IV -1 2, and FQ Aqr. New optical spectra of the three stars -- BD+10 2179, V1920 Cyg, and HD 124448 were analysed. The abundance analyses is done using LTE line formation and LTE model atmospheres especially constructed for these EHe stars. The stellar parameters derived from an EHe's UV spectrum are in satisfactory agreement with those derived from its optical spectrum. Adopted abundances for the seven EHes are from a combination of the UV and optical analyses. Published results for an additional ten EHes provide abundances obtained in a nearly uniform manner for a total of 17 EHes, the largest sample on record. The initial metallicity of an EHe is indicated by the abundance of elements from Al to Ni; Fe is adopted to be the representative of initial metallicity. Iron abundances range from approximately solar to about one-hundredth of solar. Clues to EHe evolution are contained within the H, He, C, N, O, Y, and Zr abundances. Two novel results are (i) the O abundance for some stars is close to the predicted initial abundance yet the N abundance indicates almost complete conversion of initial C, N, and O to N by the CNO-cycles; (ii) three of the seven stars with UV spectra show a strong enhancement of Y and Zr attributable to an s-process. The observed compositions are discussed in light of expectations from accretion of a He white dwarf by a CO white dwarf.Comment: 126 pages, 15 figures, 20 Tables, accepted for publication in the Ap

Prediction of neurotoxins based on their function and source

We have developed a method NTXpred for predicting neurotoxins and classifying them based on their function and origin. The dataset used in this study consists of 582 non-redundant, experimentally annotated neurotoxins obtained from Swiss-Prot. A number of modules have been developed for predicting neurotoxins using residue composition based on feed-forwarded neural network (FNN), recurrent neural network (RNN), support vector machine (SVM) and achieved maximum accuracy of 84.19%, 92.75%, 97.72% respectively. In addition, SVM modules have been developed for classifying neurotoxins based on their source (e.g., eubacteria, cnidarians, molluscs, arthropods have been and chordate) using amino acid composition and dipeptide composition and achieved maximum overall accuracy of 78.94% and 88.07% respectively. The overall accuracy increased to 92.10%, when the evolutionary information obtained from PSI-BLAST was combined with SVM module of source classification. We have also developed SVM modules for classifying neurotoxins based on functions using amino acid, dipeptide composition and achieved overall accuracy of 83.11%, 91.10% respectively. The overall accuracy of function classification improved to 95.11%, when PSI-BLAST output was combined with SVM module. All the modules developed in this study were evaluated using five-fold cross-validation technique. The NTXpred is available at www.imtech.res.in/raghava/ntxpred/ and mirror site at http://bioinformatics.uams.edu/mirror/ntxpred

BTXpred: prediction of bacterial toxins

This paper describes a method developed for predicting bacterial toxins from their amino acid sequences. All the modules, developed in this study, were trained and tested on a non-redundant dataset of 150 bacterial toxins that included 77 exotoxins and 73 endotoxins. Firstly, support vector machines (SVM) based modules were developed for predicting the bacterial toxins using amino acids and dipeptides composition and achieved an accuracy of 96.07% and 92.50%, respectively. Secondly, SVM based modules were developed for discriminating entotoxins and exotoxins, using amino acids and dipeptides composition and achieved an accuracy of 95.71% and 92.86%, respectively. In addition, modules have been developed for classifying the exotoxins (e.g. activate adenylate cyclase, activate guanylate cyclase, neurotoxins) using hidden Markov models (HMM), PSI-BLAST and a combination of the two and achieved overall accuracy of 95.75%, 97.87% and 100%, respectively. Based on the above study, a web server called 'BTXpred' has been developed, which is available at http://www.imtech.res.in/raghava/btxpred/. Supplementary information is available at http://www.imtech.res.in/raghava/btxpred/supplementary.html