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There is a clear clinical need for a bioactive bone graft substitute. Poly(vinyl phosphonic acid‐co‐acrylic acid) (PVPA‐co‐AA) has been identified as a promising candidate for bone regeneration but there is little evidence to show its direct osteogenic effect on progenitor or mature cells. In this study mature osteoblast‐like cells (SaOS‐2) and human bone marrow‐derived mesenchymal stem cells (hBM‐MSCs) were cultured with PVPA‐co‐AA polymers with different VPA:AA ratio and at different concentrations in vitro. We are the first to report the direct osteogenic effect of PVPA‐co‐AA polymer on bone cells and, more importantly, this effect was dependent on VPA:AA ratio and concentration. Under the optimized conditions, PVPA‐co‐AA polymer not only has an osteoconductive effect, enhancing SaOS‐2 cell mineralization, but also has an osteoinductive effect to promote hBM‐MSCs’ osteogenic differentiation. Notably, the same PVPA‐co‐AA polymer at different concentrations could lead to differential osteogenic effects on both SaOS‐2 and hBM‐MSCs in vitro. This study furthers knowledge of the PVPA‐co‐AA polymer in osteogenic studies, which is critical when utilizing the PVPA‐co‐AA polymer for the design of novel bioactive polymeric tissue engineering scaffolds for future clinical applications. © 2017 The Authors Journal of Biomedical Materials Research Part A Published by Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 168–179, 2018.

Based on nonlinear prediction and information theory, spatial heterogeneity of predictability and information flowing channels were obtained over the Northern Hemisphere between 20°N and the North Pole in geopotential height levels. On the whole, the predictability is high in mid-latitude continental and higher levels and low in the tropic and oceans and lower levels. There are two channels in and above 500hpa pressure level. One channel is in the Pacific Ocean, and the other is in the Atlantic Ocean. Though the width of channels may be different in different geopotential height levels, the channels steadily exist in pressure levels. The predictability and teleconnections are paramount issues in atmospheric science. And the teleconnnections may be established by communication channels. So the work is interesting because it reveals the predictability distribution and channel locations in different pressure levels.

A new complex of samarium(III) with malonic acid, Sm(HL)L·4H 2 O (H 2 L = malonic acid), was synthesized and characterized by elemental analysis, molar conductance, thermogravimetric analysis, IR and fluorescence spectra. The structure of the complex was determined by single crystal X-ray diffraction. The samarium ion is coordinated by six carboxylate and three water oxygen atoms which form a distorted monocapped square antiprism. The malonate (L 2− ) and bimalonate (HL − ) have different coordination behaviours. The structure is a three-dimensional samarium-malonate-bimalonate network. The SmO bond lengths are in the range 2.396(6)–2.725(5) A.

This paper reports an effective method to improve the forecasting level of the numerical model through analogue prediction of errors and correction of the results. The analogy of the precipitation model errors and its predictability are studied for the mid-lower reaches of the Yangtze River in summer time in the perspective of analogy, which exists in the error field in the forecasting numerical model. The content of the analogy is also investigated according to the historical data. It is found that the forecasting errors could be improved remarkably by analogue error prediction over the regions researched in summer time. The forecasting error field is decomposed by EOF, and then the geographic distribution and time coefficient evolution of the first three principal components are analyzed. The prediction of the precipitation could be simplified by analogue forecasting of the principal components separately, and it is more targeted to improve the potential forecasting level. On the basis of the analogy of the forecasting error field, its analogue predictability is defined to measure the predictability of the errors. The analogue predictability of the first three principal components is significantly higher than that of the original field. It has potential applications to precipitation predication by forecasting the error field principal components.

In this paper, singular value decomposition (SVD) is used to correct the National Climate Center business model CGCM, thus improving the forecast results. By performing the SVD decomposition using field coupling between the summer rainfall patterns forecasted in 1983-2011 and actual rainfall values, by selecting the mode forecast and 3-7 modals that are best correlated with the live precipitation, and comparing these revised results of the different numbers of modal number, and by selecting the number of modals with the best correction effect in the China region, the revised results are obtained from the model predictions. The 2004-2009 cross hindcast experiments and the return results tested by using the anomaly correlation coefficient and the root mean square error as evaluation criterion show that the best corrections are obtained by taking the first five modals in 2004-2009 as the number of modal revised in the year. The examinations of 2004-2009 mode and actual precipitation data demonstrate the correction effect obtained by the five modals is indeed best. A comparison between the result and the systematic errors shows that the Dhamma revised results are better than the systematic errors. Taking the year of 2010 as the forecast year, using the results of the cross-examination of 27 years 1983-2009 to determine the number of modals, and analyzing the forecast results by the determined number of modals constitute a method that has a potential business value.

With time delay under consideration, temperature correlation matrixes are constructed based on the reanalysis of temperature data provided by National Centers for Environmental Prediction/National Center for Atmospheric Research and European Centre for Medium-Range Weather Forecasts. Results indicate that the correlation of global temperature decreases with lag time, and the rate is dependent on time lag. We divide the lag time (1—30 d) into three segments, i.e., 1—7 d, 8—20 d and 21—30 d according to the decrease rate of global average correlation coefficient Cglb. When the lag time is in a specific interval (8—20 d), Cglb is unstable, which may explain the difficulty in long range weather forecast of 10—30 d. The spatial distribution of the global temperature correlation keeps stable for different lag times, while the numerical change shows zonal distribution on the whole, and that the most of Asia and the equatorial central and eastern Pacific show countertrend to other parts of similar latitudes.

Based on the idea of using the historical-analogue information to revise the prediction errors of National Climate Centre numerical business model, for North China, based on analysis data of the CMAP from 1983 to 2009, 40 pieces of climate indices from NOAA, 27 years of the season prediction model results from 1983 to 2009 and 74 pieces of circulation characteristics materials provided by Weather Diagnostic Forecasting Room of National Climate Center, using the method of combining data analysis and numerical simulation of diagnostic tests, taking the advantage of the prediction error of the key information of similar model from the historical data, by identifying key factors, optimizing allocation of the different factors of different forecasting years, we established specific multi-factor dynamic optimal portfolios to revise prediction errors in different periods of the power-statistical model in North China, and constructed early environmental factors similar to field multiple objective criteria, to develop new technology of revising prediction errors from the power-statistical model based on dynamic optimal combination of multi-factor, and improved the prediction effect in the summer precipitation in North China and the forecasting skills. Results of independent sample return of 2005—2009 shows that, the score of similarity revised method has improved significantly compared with the score of systematic revised method. The method has a good prospect for summer precipitation forecast in North China, and is going to be put into operation.

This paper studies the long range correlation of the return intervals of extreme events using the method of percent threshold. In view of return intervals of the extreme events, the long range-correlations of return intervals are studied by simulated time series when the extreme events happened. It is found that the constructed extreme event time series also have the characteristics of long-range correlation if the original time series have one. Meanwhile, the scaling exponents of the two time series are very close, it is very different from the return intervals of stochastic series. The probability density function of time series with long-range correlation has significant difference from the stochastic time series. It was found that there is a group-occurrence phenomenon in the return time series with long-range correlation, so a so-called group occurrence index is defined and computed, the stability of the index is also studied. The results show that the reason of the group occurrence of extreme events series is attributed to the long-range correlation of time series.

Based on the theory of probability distribution of record-breaking events and daily high/low observational temperature data in China form 1960 to 2005, the spatial-temporal characteristics of record-breaking temperature are investigated. We found that the annual mean frequency of record-breaking high temperature is about 2.5 times greater than normal in 1976—2005, while for record-breaking low temperature is 4.5 times less. Record-breaking high temperature is obviously more than normal in Northwest, North China, Northeast and Tibet, while the record-breaking low temperature is obviously less than normal there. As to the relative trend of record-breaking temperature events, the record-breaking high temperature somewhat increases in most parts of China, but the record-breaking low temperature become less and less all over China. For the development trend of strength, the record-breaking high temperature events, have somet enhancement in high latitude areas of China, but the record-breaking low temperature events have no change or only eventually become weakening in this area and also in XinJiang and Tibet. It should to be payed attention that the strength of record-breaking low temperature events becomes obviously enhanced in south China. In studying the relationship of annual frequency of record-breaking high/low temperature events and pacific warm pool index, we found that there are significant correlations between them for most parts of China.

The paper investigates the height and temperature fields reanalysis data of NCEP/NCAR by means of detrended fluctuation analysis method, and gives their scaling exponent distribution of East Asia region. The empirical investigation indicates that both of height field and temperature filed have the property of long range correlation, which matches with the features of space distribution as a whole. As for the grid data of the same layer, the long range correlation varies obviously when the latitude changes. The low-latitude areas near the equator have a bigger scaling exponent and a better long range correlation, whereas the mid-latitude and high latitude areas have a smaller scaling exponent and a worse long range correlation. The average scaling exponent increases with the layer growth of height field data, and the scaling exponent varies obviously when the latitude changes. The scaling exponent of Qinghai-Tibet Plateau is obviously greater than other areas at the same latitude. For the data of temperature, the average scaling exponent first decreases with the layer growth then increases, and the average scaling exponent has a definite latitude trait. All in all, the scaling exponent of height field’s long range correlation is greater than that of temperature field. The investigation for different seasons displays that the long range correlation exists in height field and temperature field as well. And we find that the scaling exponent of winter time is greater than that of other seasons. This may provide a theory for the summer flood season forecast which is based on the winter information.

The occurrence of record breaking temperature events （RBTE） became more and more frequent under the background of global warming. What is the probability that the current temperature record will be broken in the next five years? In this study, answers are provided by given a variety of simple statistical models for temperature, and the relationship between the probability of RBTE of China and the global warming is explored by comparative analysis of the probability of RBTE in the last 50 years. The results show that the frequency of RBTE is influenced by global warming and the autocorrelation. This study quantitatively estimates the relationship between the probability of RBTE and global warming, which can deepen our knowledge about the in-creasing frequency and amplitude of RBTE under the background of global warming.