Direct electrochemical detection of oligonucleotide hybridization on poly(5-hydroxy-1,4-naphthoquinone- co-5-hydroxy-3-thioacetic acid-1,4-naphthoquinone) film

We describe the construction of a new DNA-modified electrode based on an electroactive film. 5-Hydroxy-1,4-naphthoquinone is coelectrooxidized with 5-hydroxy-3-thioacetic acid-1,4-naphthoquinone to give a copolymer, presenting both electroactive and chemically reactive groups. The carboxylic function acts as a precursor for the covalent grafting of ODN probes while the quinone group acts as the transduction element of hybridization. Electrochemical detection was performed by differential pulse voltammetry in the electroactivity domain of the quinone group (i.e., at very low potentials, 0 to -0.8 V vs SCE). A very clear modification of the redox activity is observed between unmodified and probe-modified films and especially upon addition of target ODN.     

用USB启动Windows XP Embedded

Windows XP Embedded Service Pack 2 Feature Pack 2007（以下简称FP2007）推出了用于嵌入式应用的USB启动功能。现在，用户可以通过一个USB闪存驱动器（UFD）、a．k．a．、U盘和USB密钥等来启动并构建一个Windows XPe的映像。构建这种启动Windows XP Embedded的USB设备的过程中，只要直接使用Target Designer，并准备好需要启动的UFD，就像使用ufdprep．exe（FP2007中包含的一个工具）文件一样简单。     

Design and Fabrication of ZnO-Based FBAR Microwave Devices for Mobile WiMAX Applications

In this letter, we present the design and fabrication of a novel ZnO-based film bulk acoustic wave resonator (FBAR) microwave devices. The novel FBAR devices employ a new-type of Bragg reflector with very thin chromium (Cr) layer formed between SiO₂ and W films. The Cr layer seems to enhance the adhesion between SiO₂ and W layers. The novel FBAR devices show good return losses (S₁₁) and high Q-factors at the frequency range of 2.7-3.0 GHz. This approach will be very helpful for mobile worldwide interoperability for microwave access applications.     

Deflation-based power iteration clustering

Spectral clustering (SC) is currently one of the most popular clustering techniques because of its advantages over conventional approaches such as K-means and hierarchical clustering. However, SC requires the use of computing eigenvectors, making it time consuming. To overcome this limitation, Lin and Cohen proposed the power iteration clustering (PIC) technique (Lin and Cohen in Proceedings of the 27th International Conference on Machine Learning, pp. 655–662, 2010), which is a simple and fast version of SC. Instead of finding the eigenvectors, PIC finds only one pseudo-eigenvector, which is a linear combination of the eigenvectors in linear time. However, in certain critical situations, using only one pseudo-eigenvector is not enough for clustering because of the inter-class collision problem. In this paper, we propose a novel method based on the deflation technique to compute multiple orthogonal pseudo-eigenvectors (orthogonality is used to avoid redundancy). Our method is more accurate than PIC but has the same computational complexity. Experiments on synthetic and real datasets demonstrate the improvement of our approach.     

Urban growth and change analysis using remote sensing and spatial metrics from 1975 to 2003 for Hanoi,Vietnam

Since the beginning of the ‘Doi Moi’ policy in 1986, Hanoi has witnessed significant changes in its urban areas. Landsat and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes were used to identify built-up areas in Hanoi, and spatial metrics were used to characterize urban change patterns from 1975 to 2003. Firstly, a spatial metric called the ‘percentage of like adjacency’ was used to discern urban growth patterns, which were classified into three sub-patterns: expansion growth, infill growth and outlying growth. Secondly, the driving force underlying the urbanization of the city for the 1975–1984, 1984–1992, 1992–2001, 2001–2003 periods was investigated using a spatial metric analysis programme (FRAGSTATS). The expansion of urban areas along major transportation routes in the latter 1980s was identified as the main form of urbanization in Hanoi. This paper shows the potential application of spatial metrics as secondary sources of information for supporting remotely sensed data and their use to characterize urban growth patterns.     

New criteria for exponential stability of nonlinear difference systems with time-varying delay

General nonlinear time-varying difference systems with time-varying delay are considered. Some new explicit criteria for global exponential stability are given. Two examples are given to illustrate the obtained results.     

Estimating aboveground biomass of a mangrove plantation on the Northern coast of Vietnam using machine learning techniques with an integration of ALOS-2 PALSAR-2 and Sentinel-2A data

ABSTRACT

Aboveground biomass (AGB) of mangrove forest plays a crucial role in global carbon cycle by reducing greenhouse gas emissions and mitigating climate change impacts. Monitoring mangrove forests biomass accurately still remains challenging compared to other forest ecosystems. We investigated the usability of machine learning techniques for the estimation of AGB of mangrove plantation at a coastal area of Hai Phong city (Vietnam). The study employed a GIS database and support vector regression (SVR) to build and verify a model of AGB, drawing upon data from a survey in 25 sampling plots and an integration of Advanced Land Observing Satellite-2 Phased Array Type L-band Synthetic Aperture Radar-2 (ALOS-2 PALSAR-2) dual-polarization horizontal transmitting and horizontal receiving (HH) and horizontal transmitting and vertical receiving (HV) and Sentinel-2A multispectral data. The performance of the model was assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), and leave-one-out cross-validation. Usability of the SVR model was assessed by comparing with four state-of-the-art machine learning techniques, i.e. radial basis function neural networks, multi-layer perceptron neural networks, Gaussian process, and random forest. The SVR model shows a satisfactory result (R² = 0.596, RMSE = 0.187, MAE = 0.123) and outperforms the four machine learning models. The SVR model-estimated AGB ranged between 36.22 and 230.14 Mg ha^?1 (average = 87.67 Mg ha^?1). We conclude that an integration of ALOS-2 PALSAR-2 and Sentinel-2A data used with SVR model can improve the AGB accuracy estimation of mangrove plantations in tropical areas.     

Blind separation of instantaneous mixture of sources based on orderstatistics

In this paper, we introduce a novel procedure for separating an instantaneous mixture of sources based on order statistics. The method is derived in a general context of independence component analysis, using a contrast function defined in term of the Kullback-Leibler divergence or of the mutual information. We introduce a discretized form of this contrast permitting its easy estimation through order statistics. We show that the local contrast property is preserved and derive a global contrast, exploiting only the information of the support of the distribution (in case this support is finite). Some simulations are given, illustrating the good performance of the method     

The emergence of coherence over the course of decision making.

Previous research has indicated that decision making is accompanied by an increase in the coherence of assessments of the factors related to the decision alternatives. In the present study, the authors investigated whether this coherence shift is obtained before people commit to a decision, and whether it is obtained in the course of a number of other processing tasks. College students were presented with a complex legal case involving multiple conflicting arguments. Participants rated agreement with the individual arguments in isolation before seeing the case and after processing it under various initial sets, including playing the role of a judge assigned to decide the case. Coherence shifts were observed when participants were instructed to delay making the decision (Experiment 1), to memorize the case (Experiment 2), and to comprehend the case (Experiment 3). The findings support the hypothesis that a coherence-generating mechanism operates in a variety of processing tasks, including decision making. (PsycINFO Database Record (c) 2010 APA, all rights reserved)