The efficacy of Kriging spatial interpolation for filling temporal gaps in daily air temperature data: A case study in northeast China

Quality-controlled and serially complete daily air temperature data are essential to evaluating and modelling the influences of climate change on the permafrost in cold regions. Due to malfunctions and location changes of observing stations, temporal gaps （i.e., missing data） are common in collected datasets. The objective of this study was to assess the efficacy of Kriging spatial interpolation for estimating missing data to fill the temporal gaps in daily air temperature data in northeast China. A cross-validation experiment was conducted. Daily air temperature series from 1960 to 2012 at each station were estimated by using the universal Kriging （UK） and Kriging with an external drift （KED）, as appropriate, as if all the ob-servations at a given station were completely missing. The temporal and spatial variation patterns of estimation uncertainties were also checked. Results showed that Kriging spatial interpolation was generally desirable for estimating missing data in daily air temperature, and in this study KED performed slightly better than UK. At most stations the correlation coefficients （R2） between the observed and estimated daily series were 〉0.98, and root mean square errors （RMSEs） of the estimated daily mean （Tmean）, maximum （Tmax）, and minimum （Tmin） of air temperature were 〈3 ℃. However, the estimation quality was strongly affected by seasonality and had spatial variation. In general, estimation uncertainties were small in summer and large in winter. On average, the RMSE in winter was approximately 1 ℃ higher than that in summer. In addition, estimation uncertainties in mountainous areas with complex terrain were significantly larger than those in plain areas.

A Data-Adaptive Filter of the Tahiti-Darwin Southern Oscillation Index and the Associate Scheme of Filling Data Gaps

The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.

Nano-scale gap filling and mechanism of deposit-etch-deposit process for phase-change material

Ge2Sb2Te5 gap filling is one of the key processes for phase-change random access memory manufacture. Physical vapor deposition is the mainstream method of Ge2Sb2Te5 film deposition due to its advantages of film quality, purity, and accurate composition control. However,the conventional physical vapor deposition process cannot meet the gap- filling requirement with the critical device dimension scaling down to 90 nm or below. In this study, we find that the deposit-etch-deposit process shows better gap-filling capability and scalability than the single-step deposition process, especially at the nano-scale critical dimension. The gap-filling mechanism of the deposit-etch-deposit process was briefly discussed. We also find that re-deposition of phase-change material from via the sidewall to via the bottom by argon ion bombardment during the etch step was a key ingredient for the final good gap filling. We achieve void-free gap filling of phase-change material on the 45-nm via the two-cycle deposit-etch-deposit process. We gain a rather comprehensive insight into the mechanism of deposit-etch-deposit process and propose a potential gap-filling solution for over 45-nm technology nodes for phase-change random access memory.

Gap Filling of Net Ecosystem CO₂Exchange (NEE) above Rain-Fed Maize Using Artificial Neural Networks (ANNs)

The eddy covariance technique is an accurate and direct tool to measure the Net Ecosystem Exchange (NEE) of carbon dioxide. However, sometimes conditions are not amenable to measurements using this technique. Thus, different methods have been developed to allow gap-filling and quality assessment of eddy covariance data sets. In this study first, two different Artificial Neural Networks (ANNs) approaches, the Multi-layer Perceptron (MLP) trained by the Back-Propagation (BP) algorithm, and the Radial Basis Function (RBF), were used to fill missing NEE data measured above rain-fed maize at the University of Nebraska-Lincoln Agricultural Research and Development Center near Mead, Nebraska. The gap-filled data were then compared by different statistical indices to gap-filled data obtained with the technique suggested by Suyker and Verma in 2005 [S&V method], and the ANN approach presented by Papale in 2003. The results showed that the RBF network was able to find better fits for missing values compared to the MLP (BP) network and S&V method. In addition, unlike the S&V method, which depends on different gap-filling procedures over the year;the structure of RBF and MLP (BP) networks was constant. However, data analysis indicated Papale’s approach gave better fits than the RBF and MLP (BP) methods. Thus, based on this work, Papale’s approach is the best method to estimate the missing data;though the applied statistical indices, which were used for model evaluation, show little difference between Papale’s approach and the RBF and MLP (BP).

Sapo Fills the Gaps of 200 W 1064 nm Diode Pumping Modules in China

Wuhan Sapo Laser Industry Ltd．has recently introduced HipoweTM series 1064 nm high power doide laser pumping modules,which not only fill the gaps in Chinese market and end the history of importing this kind products from abroad,but also have great influence on Chinese laser industry and medical laser market．

The In-orbit Application of 25Nms Gyroscope Fills the Gap in Domestic Market

After the successful launch of Yaogan 14, the 25Nms control moment gyroscope onboard the Yaogan 14 satellite successfully finished the attitude maneuver commands to the satellite and operates in a normal state. The successful maiden use of the 25Nms gyroscope fills the gap in the field of small control moment gyroscopes in

Effects of different gap filling methods and land surface energy balance closure on annual net ecosystem exchange in a semiarid area of China

Based on eddy covariance measurements over two kinds of land surfaces(a degraded grassland and a maize cropland)in a semiarid area of China in 2005 and 2008,the effects of different gap filling methods,energy balance closure and friction velocity threshold(u*)on annual net ecosystem exchange(NEE)were analyzed.Six gap filling methods,including mean diurnal variation(MDV),marginal distribution sampling(MDS),and nonlinear regressions method,were investigated by generating secondary datasets with four different artificial gap lengths(ranging in length from single half-hours to 12 consecutive days).The MDS generally showed a good overall performance especially for long gaps,with an annual sum bias error less than 5 g C m-2 yr-1.There was a large positive annual sum bias error for nonlinear regressions,indicating an overestimate on net ecosystem respiration.The offset in the annual sum NEE for four nonlinear regressions was from 8.0 to 30.8 g C m-2 yr-1.As soil water content was a limiting factor in the semiarid area,the nonlinear regressions considering both soil temperature and soil water content as controlling variables had a better performance than others.The performance of MDV was better in daytime than in nighttime,with an annual sum bias error falling between-2.6 and-13.4 g C m-2 yr-1.Overall,the accuracy of the gap filling method was dependent on the type of the land surface,gap length,and the time of day when the data gap occurred.The energy balance ratio for the two ecosystems was nearly 80%.Turbulent intensity had a large impact on energy balance ratio.Low energy balance ratio was observed under low friction velocity during the night.When there was a large fetch distance in a wind direction,a low energy balance ratio was caused by mismatch of the footprints between the available energy and turbulent fluxes.The effect of energy balance correction on CO2 flux was evaluated by assuming the imbalance caused by the underestimation of sensible heat flux and latent heat flux.The results showed an average increase of 10 g C m-2 yr-1 for annual NEE in both ecosystems with an energy balance correction.On the other hand,the u*threshold also have a large impact on annual sum NEE.Net carbon emission increased 37.5 g C m-2 yr-1 as u*threshold increased from 0.1 to 0.2 m s-1,indicating a large impact of imposing u*threshold on net ecosystem carbon exchange.

GSA and BIGD:Filling the Gap of Bioinformatics Resource and Service in China

In the 2017 first issue of this Journal - Genomes, Proteomes and Bioinformatics - a special database article entitled ＂GSA： Gen- ome Sequence Archive＂ is published. This article provides a brief introduction to the platform developed by the authors from the BIG Data Center （BIGD） of Beijing Institute of Genomics （BIG）, Chinese Academy of Sciences （CAS）. The aim of the GSA project is to collect, integrate, and archive raw sequence data submitted by domestic and international users. It is one of the major activities being carried on by a team of around 50 young bioinformaticians at BIGD. In addition to the GSA system, they are also working on several bioinformatics service-orientated projects as described in one of their recent publications .

Tunable Photonic Band Gaps In Photonic Crystal Fibers Filled With a Cholesteric Liquid Crystal

A photonic crystal fiber has been filled with a cholesteric liquid crystal. A temperature sensitive photonic band gap effect was observed, which was especially pronounced around the liquid crystal phase transition temperature.

Filling the Income Gap

Income distribution has become one of the people’s main concerns in China where more than 30 years of reform and opening up have also resulted in an ever-expanding wealth gap. But narrowing down