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Abstract

This work reports the effect of Ge, Sb, Sn additives on the thermally activated glass to crystal phase transition in binary Se90In10 alloy. Differential scanning calorimetry (DSC) technique is used for this purpose. Different kinetic parameters of glass/crystal transformation have been calculated. The results are explained using the chemical bond approach for the covalent network of such glasses.

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Abstract  

Different methods have been used by various workers to determine the activation energy of thermal crystallization (E c) in chalcogenide glasses using non-isothermal DSC data. In the present work, the crystallization kinetics of two important binary alloys Se80Te20 and Se80In20 is studied using non-isothermal DSC data. DSC scans of these alloys have been taken at five different heating rates. The values of activation energy of crystallization (E c) have been determined by four different methods, i.e., Kissinger's method, Matusita-Sakka method, Augis-Bennett's method and Ozawa's method, have been used to calculate E c. The results obtained have been compared with each other to see the effect of using different methods in the determination of E c.

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Abstract  

The crystallization kinetics of a-Se80–xTe20Cdx (x=0, 5, 10, 15) and a-Se80–xTe20Gex (x=5, 15, 20) alloys has been studied by an isothermal method. For this purpose, conductivity measurements are done during isothermal annealing at various temperatures between the glass transition and crystallization temperatures. Avrami’s equation is used to calculate the activation energy of crystallization (E c) and order parameter (n). It is shown that Avrami’s theory of isothermal crystallization correctly describes the crystallization kinetics in the present alloys. The composition dependence of E c in these alloys has also been discussed.

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Abstract

Calorimetric measurements have been performed in glassy Se90M10 (M=In, Te, Sb) alloys to study the effect of In, Te and Sb additives on the kinetics of glass transition and crystallization in glassy Se90M10 system. Kinetic parameters of glass transition and crystallization such as the activation energy of glass transition (E g), the activation energy of crystallization (M c), the order parameter (n), the rate constant (K), etc. have been determined using different non-isothermal methods. The composition dependence of the activation energies of glass transition and crystallization processes is also discussed.

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Gene effects were analysed using mean stomatal number and specific leaf weight of 12 populations, consisting of both parents (P 1 and P 2 ), F 1 , F 2 , first backcross generations (BC 1 and BC 2 ), second backcross generations (B 11 , B 12 , B 21 , B 22 ) and backcross selfed generations (B 1 s and B 2 s) of four crosses involving three drought-tolerant and three drought-susceptible cultivars of Triticum aestivum L. to determine the nature of gene action governing stomatal number (SN) and specific leaf weight (SLW) through generation mean analysis in moisture stress (E 1 ) and moisture non-stress (E 2 ) environments. The digenic epistatic model was found to be inadequate for stomatal number and the additive-dominance model was found to be adequate for specific leaf weight in most of the crosses. Additive gene effects were predominant for SLW, while for SN both additive and dominance components of variance were important. Epistatic effects, particularly the additive × dominance (j) type of interaction, were present for both the characters. The duplicate type of epistasis was observed for stomatal number in the cross VL421/HS240 in the moisture stress environment. Significant heterosis was observed for the crosses Hindi 62/HS240 and VL421/HS240 over the standard check (SC) in the moisture stress environment (E 1 ) for both the characters. Genotype-environmental interactions and/or differential gene expression appeared to account for the different results found between environments. Hybridization systems, such as biparental mating and/or diallel selective mating, could be useful for the improvement of these traits, which would help in identifying drought-tolerant progenies.

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Gene effects were analyzed using mean excised-leaf water loss and relative water content of 12 populations viz., both parents (P 1 and P 2 ), F 1 , F 2 , first back cross generations (BC1 and BC2), second back cross generations (B 11 , B 12 , B 21 , B 22 ) and back cross-selfed generations (B 1 s and B 2 s) of four crosses involving three drought tolerant and three drought susceptible cultivars of Triticum aestivum L. to determine nature of gene action governing excised-leaf water loss (ELWL) and relative water content (RWC) through generation mean analysis under rainfed (E1) and irrigated (E2) environments. Both additive-dominance and digenic epistatic model were found to be inadequate in all the crosses for ELWL and in most of the crosses for RWC to explain genetic variation among the generation means. Additive gene effects were predominant for RWC, while for ELWL both additive and dominance component of variance were important. Epistatic effects, particularly dominance × dominance (1) type of interaction was more predominant for RWC, while additive × additive(i) for ELWL. Duplicate type of epistasis was observed in the crosses Hindi 62/HS240 and VL421/HS240 for RWC and in the cross S4/HPW89 for ELWL under both the environments. Complementary type of epistasis was observed only in the cross VL421/PBW175 for ELWL under E1. Hybridization systems, such as biparental mating and/or diallel selective mating could be useful for improvement of these traits which would help in isolating drought tolerant progenies.

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Abstract  

Traditional Indian medicinal herbs, used for strengthening the body immune system, are rich source of many essential nutrient elements in bioavailable form. Instrumental neutron activation analysis (INAA) employing short (5 minutes) and long (14 hours and 3 days) reactor irradiation followed by high resolution gamma-ray spectrometry has been used for the determination of Al, Au, Ba, Br, Ca, Ce, Cl, Co, Cr, Cu, Eu, Fe, K, La, Mg, Mn, Na, P, Rb, Sb, Sc, Sm, Th, V and Zn in 15 medicinal herbs commonly used in Indian household for treatment of various ailments. viz. C. rhombifolia (Amaltas), W. somnifera (Ashwagandha), P. corylifolia (Bakuchi), T. cordifolia (Guduchi), M. fragrans (Jaiphal), N. jatamansi (Jatamansi), A. paniculata (Kalmegh), H. anticlysentrica (Kutaj), T. chebula (Laghu Haritaki), S. racemosa (Lodhra), A. indica (Neem), V. negundo (Nirgundi), H. indicus (Sariva), A. calamus (Vach) and E. ribes (Vidang). Several of herbs are enriched in Ca, Co, Cu, Mg, P, Fe, Mn and Zn, which play a vital role in biochemical and enzymatic processes. Jatamansi, often used as antibacterial, antipyretic and heart tonic is specially enriched in Co, Cr, Cu, Na, Mn, Fe, Rb and Zn. Also Guduchi and Laghu Haritaki are enriched in Ca and Mg, respectively. An attempt has been made to correlate elemental contents with the therapeutic importance of various herbs. Also our results for the participation in an Intercomparison Study of renewal of Pine Needles (SRM-1575a) from NIST, USA are presented.

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Abstract  

Brahmi (Bacopa monnieri) leaves, known as nervine tonic in Ayurveda, and its aqueous (BA), methanolic (BM) and aqueous–methanolic (BAM) extracts were analyzed for 7 minor (Al, Fe, Na, K, Ca, P, Cl) and 18 trace (As, Au, Ba, Br, Co, Cr, Cu, Hf, Hg, La, Mn, Rb, Se, Sm, Sr, Th, V, Zn) elements by INAA. BAM extract showed maximum contents of Na, K, Cl and significant amounts of Mn, Co, Zn. It was also found as effective scavenger of DPPH radicals with 33.5% total phenolic content, highest γ-ray radioprotective effect and higher anti lipid peroxidation activity.

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In order to study the inheritance pattern of morpho-physiological traits in bread wheat, a 10×10 diallel cross, excluding reciprocals was made and grown in a randomized complete block design (RCBD) with three replications. Observations were recorded on Days to 75% flowering (DF), Days to maturity (DM), Duration of reproductive phase (DRP), Plant height (cm) (PH), Effective tiller/plant (TLS), No. of spikelets per spike (SLS), No. of grains per spike (GS), Grain weight per spike (g) (GW), Spike length (cm) (SL), Biological yield per plant (g) (BY), Harvest index (%) (HI), 1000-Grain weight (g) (TGW), Spike density (SD), Canopy temperature depression (°C) (CTD), Chlorophyll intensity (%) (CI), Chlorophyll fluorescence (Fv/Fm) (CF), Protein content (%) (PC), Grain yield per plant (g) (GY). Highly significant differences were observed among the genotypes for all traits. The resulted 45 F1s and their F2s used for study the nature of gene for grain yield and its contributing traits in bread wheat. The result indicated that considerable gene action and average degree of dominance respond to achieving significant result for grain yield and its component traits. In both the generations F1s and F2s, grain yield per plant (g) was governed by non-additive gene action based on combining ability analysis, (σ2 g/σ2 s)0.5 [GCA and SCA variance ratio] and (H1/D)0.5 [Degree of dominance] were exhibited over dominance type average degree of dominance for grain yield and its component traits in both generations. Genetic analyses of the traits confirm the involvement of both additive and non-additive gene effects in governing the inheritance.

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Abstract  

A nondestructive NAA method based on the reaction 31P(n,γ)32P (T 1/2 = 14.23 d) has been developed where the product nucleus, a pure β-emitter with end point energy 1.71 MeV is measured by using an end window G.M. counter and an Al filter of 27 mg·cm−2. 32P was identified by measuring E β using Feather’s analysis and its half-life was found to be 15.3±0.2 days in standard reference materials (SRMs) and samples. For most reference materials (RMs) from NIST (USA) and IAEA (Vienna), our values agree within ±5% of the certified values. A variety of biological samples have also been analyzed and our values are in the range; medicinal herbs (n = 43), 0.29–5.23 mg/g; bhasmas (n = 19), 0.09–51.4 mg/g; vegetables (n = 8), 1.85–5.73 mg/g; lentils (n = 6), 2.1–5.5 mg/g; flours (n = 6), 1.3–3.3 mg/g; vegetarian diet (n = 5), 2.41–2.90 mg/g; fish (n = 43), 3.61–36.8 mg/g; human and animal milk (n = 6), 1.24–7.95 mg/g; commercial milk powders (n = 14), 2.76–11.9 mg/g; water from various sources (n = 14), 1–417 µg/l; human and animal blood (n = 9), 1.00–15.0 mg/g; cancerous and healthy breast tissue (n = 60), 1.00–8.63 mg/g; human hair (n = 43), 0.12–5.81 mg/g, where n is the number of samples analyzed. The method is simple, fast, and nondestructive and provides data within ±5% error limit with a detection limit of 0.1 mg/g.

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