Effect of distribution of stickers along backbone on temperature-dependent structural properties in associative polymer solutions

Effect of distribution of stickers along the backbone on structural properties in associating polymer solutions is studied using self-consistent field lattice model. Only two inhomogeneous morphologies, i.e., microfluctuation homogenous (MFH) and micelle morphologies, are observed. If the system is cooled, the solvent content within the aggregates decreases. When the spacing of stickers along the backbone is increased the temperature-dependent range of aggregation in MFH morphology and half-width of specific heat peak for homogenous solutions-MFH transition increase, and the symmetry of the peak decreases. However, with increasing spacing of stickers, the above three corresponding quantities related to micelles behave differently. It is demonstrated that the broad nature of the observed transitions can be ascribed to the structural changes which accompany the replacement of solvents in aggregates by polymer, which is consistent with the experimental conclusion. It is found that different effect of spacing of stickers on the two transitions can be interpreted in terms of intrachain and interchain associations.Comment: 10 pages, 4 figures. arXiv admin note: text overlap with arXiv:1202.459

Birthrates and delay times of Type Ia supernovae

Type Ia supernovae (SNe Ia) play an important role in diverse areas of astrophysics, from the chemical evolution of galaxies to observational cosmology. However, the nature of the progenitors of SNe Ia is still unclear. In this paper, according to a detailed binary population synthesis study, we obtained SN Ia birthrates and delay times from different progenitor models, and compared them with observations. We find that the Galactic SN Ia birthrate from the double-degenerate (DD) model is close to those inferred from observations, while the birthrate from the single-degenerate (SD) model accounts for only about 1/2-2/3 of the observations. If a single starburst is assumed, the distribution of the delay times of SNe Ia from the SD model is a weak bimodality, where the WD + He channel contributes to the SNe Ia with delay times shorter than 100Myr, and the WD + MS and WD + RG channels to those with age longer than 1Gyr.Comment: 11 pages, 2 figures, accepted by Science in China Series G (Dec.30, 2009

Efecto del estrés producido por la mezcla de sales en la concentración de aldehído malónico, proteínas y enzimas antioxidantes de Leymus chinensis de tres colores foliares diferentes

The mixed salt stress is common in nature. Salt stressalways affects plant growth. Different plant species have different adaptive capacity to salty soil. Leymus chinensis is an herbaceous plant with different leaf colors. However, little research was conducted to explore the different tolerance mechanisms to salt stress among the three different leaf colour genotypes of Leymus chinensis (grey green, transitional color, yellow green). Pot experiments for Leymus chinensis in three leaf colors were conducted under mixed salt treatments in 2010. Malondialdehyde (MDA) and protein concentrations, and the activity of various antioxidant enzymes [i.e., superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), glutathione reductase (GR), dehydroascorbate reductase (DHAR) and monodehydroascorbate reductase (MDHAR)] were determined and compared among the three leaf color genotypes of Leymus chinensis. The concentrations of MDA and protein, and the activity of antioxidant enzymes showed an increasing trend with increasing pHs in almost all three leaf colors, and all of them became highest when salt stress and pH values were also highest. Moreover, antioxidant enzymes were the highest in the grey-green leaf color, and the lowest in the yellow green leaf color after exposure to the same pH treatment. The results suggested that all three leaf colors of Leymus chinensis were tolerant to salt stress, and the salt-tolerance declined according to the order of grey green > transitional color > yellow green of Leymus chinensis. This study can give us a better understanding of the intra-species adaptation to mixed salt soils.El estrés causado por mezcla de sales en el suelo es común en la naturaleza. El estrés salino siempre afecta el crecimiento de las plantas. Plantas de especies diferentes difieren en su capacidad de adaptación al estrés por sales en el suelo. Leymus chinensis es una planta herbácea con diferentes colores foliares. Sin embargo, se han conducido pocos estudios tendientes a determinar los diferentes mecanismos de tolerancia al estrés salino entre los tres genotipos de color foliar diferente de L. chinensis (grisáceo verdoso, color intermedio, amarillo verdoso). En 2010, se condujeron experimentos en macetas usando genotipos de L. chinensis de tres colores diferentes de hoja expuestos o no a tratamientos conteniendo una mezcla de sales. Las concentraciones de aldehído malónico (MDA) y proteínas, y la actividad de varias enzimas antioxidantes [es decir, la superóxido dismutasa (SOD), catalasa (CAT), ascórbico peroxidasa (APX), glutatión reductasa (GR), dehidroascórbico reductasa (DHAR) y monodehidroascórbico reductasa (MDHAR)] se determinaron y compararon entre los tres genotipos de color foliar diferente de L. chinensis. Las concentraciones de MDA y proteínas, y la actividad de enzimas antioxidantes mostraron una tendencia a incrementarse a mayores pHs en casi todos los colores foliares, y las tendencias en los tres colores foliares alcanzaron su punto máximo cuando el estrés salino y los valores de pH fueron máximos. Más aún, las concentraciones de las enzimas antioxidantes fueron las más altas en el color grisáceo verdoso, intermedias en el color intermedio, y las más bajas en el color amarillo verdoso después de la exposición al mismo tratamiento de pH. Los resultados sugirieron que los genotipos de los tres colores foliares de L. chinensis fueros tolerantes al estrés salino, y la tolerancia a la sal declinó de acuerdo al orden grisáceo verdoso > color intermedio > amarillo verdoso de L. chinensis. Este estudio puede proveer un mejor entendimiento de la adaptación intraespecífica de L. chinensis a suelos salinos.Fil: Zhou, C.. Chinese Academy of Science; China. Liaoning University; ChinaFil: Busso, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; ArgentinaFil: Yang, Y. G.. Liaoning University; ChinaFil: Zhang, Z.. Shenyang University; ChinaFil: Wang, Z. W.. Chinese Academy of Science; ChinaFil: Yang, Y. F.. Northeast Normal University; ChinaFil: Han, X. G.. Chinese Academy of Science; Chin

Mitigation of coupled model biases induced by dynamical core misfitting through parameter optimization: simulation with a simple pycnocline prediction model

Imperfect dynamical core is an important source of model biases that adversely impact on the model simulation and predictability of a coupled system. With a simple pycnocline prediction model, in this study, we show the mitigation of model biases through parameter optimization when the assimilation model consists of a "biased" time-differencing. Here, the "biased" time-differencing is defined by a different time-differencing scheme from the "truth" model that is used to produce "observations", which generates different mean values, climatology and variability of the assimilation model from the "truth" model. A series of assimilation experiments is performed to explore the impact of parameter optimization on model bias mitigation and climate estimation, as well as the role of different media parameter estimations. While the stochastic "physics" implemented by perturbing parameters can enhance the ensemble spread significantly and improve the representation of the model ensemble, signal-enhanced parameter estimation is able to mitigate the model biases on mean values and climatology, thus further improving the accuracy of estimated climate states, especially for the low-frequency signals. In addition, in a multiple timescale coupled system, parameters pertinent to low-frequency components have more impact on climate signals. Results also suggest that deep ocean observations may be indispensable for improving the accuracy of climate estimation, especially for low-frequency signals