Room-temperature high on/off ratio in suspended graphene nanoribbon field-effect transistors

We have fabricated suspended few-layer (1-3 layers) graphene nanoribbon field-effect transistors from unzipped multi-wall carbon nanotubes. Electrical transport measurements show that current annealing effectively removes the impurities on the suspended graphene nanoribbons, uncovering the intrinsic ambipolar transfer characteristic of graphene. Further increasing the annealing current creates a narrow constriction in the ribbon, leading to the formation of a large bandgap and subsequent high on/off ratio (which can exceed 10(4)). Such fabricated devices are thermally and mechanically stable: repeated thermal cycling has little effect on their electrical properties. This work shows for the first time that ambipolar field-effect characteristics and high on/off ratios at room temperature can be achieved in relatively wide graphene nanoribbons (15-50 nm) by controlled current annealing.     

An effective structured approach to finding optimal partitions of networks

The problem considered is to partition an edge-valued, node-weighted, finite, connected, simple graph (called a network) into disjoint subgraphs, each of which has a total node weight that does not exceed a weight constraint, and so that the total value of edges interconnecting the subgraphs is minimized. This paper presents a new approach which is effective in solving the problem, and fast enough to be practical in finding optimal partitions of large networks. It uses the concept of “divide and conquer” to partition the problem into several subproblems, which can be efficiently solved one after the other by using depth-first search and branch-and-bound principle. The operations required under the algorithms are additions, comparisons, and logical operations on binary vectors.     

Enzymatic production of fructose 1,6-diphosphate using crude cell extract of Bacillus stearothermophilus

The enzymatic production of fructose 1,6-diphosphate (FDP) from glucose was performed in a batch reactor and a semibatch reactor using the crude cell extract of Bacillus stearothermophilus which contains all four enzymes required for the synthesis. The experimental results of the yield and the time courses of FDP production obtained using various enzyme concentrations were in good agreement with the theoretical predictions calculated based on the differential equations including the rate equations of the four enzymes, which were determined using the purified enzymes of B. stearothermophilus.     

Experimental verifications of a joint transform correlator using compressed reference images

Single-target and multiple-target detections by using a joint transform correlator (JTC) with compressed reference images are experimentally verified. Two high-contrast images with different spatial-frequency content are used as test scenes. Although an effect of the additive noise on detection performance of the proposed correlator is more severe than that of the compression, the experimental results confirm the feasibility of implementing the JTC with compressed reference images.     

OREX-J: towards a universal software framework for the experimental analysis of optimization algorithms

The Operations Research EXperiment Framework for Java (OREX-J) is an object-oriented software framework that helps users to design, implement and conduct computational experiments for the analysis of optimization algorithms. As it was designed in a generic way using object-oriented programming and design patterns, it is not limited to a specific class of optimization problems and algorithms. The purpose of the framework is to reduce the amount of manual labor required for conducting and evaluating computational experiments: OREX-J provides a generic, extensible data model for storing detailed data on an experimental design and its results. Those data can include algorithm parameters, test instance generator settings, the instances themselves, run-times, algorithm logs, solution properties, etc. All data are automatically saved in a relational database (MySQL, http://www.mysql.com/) by means of the object-relational mapping library Hibernate (http://www.hibernate.org/). This simplifies the task of analyzing computational results, as even complex analyses can be performed using comparatively simple Structured Query Language (SQL) queries. Also, OREX-J simplifies the comparison of algorithms developed by different researchers: Instead of integrating other researchers’ algorithms into proprietary test beds, researchers could use OREX-J as a common experiment framework. This paper describes the architecture and features of OREX-J and exemplifies its usage in a case study. OREX-J has already been used for experiments in three different areas: Algorithms and reformulations for mixed-integer programming models for dynamic lot-sizing with substitutions, a simulation-based optimization approach for a stochastic multi-location inventory control model, and an optimization model for software supplier selection and product portfolio planning.     

Use of Raman microscopy and band-target entropy minimization technique to differentiate physical mixture from chemical mixture in mixed metal oxides

Raman microscopy has been applied to characterize physical and chemical mixtures of mixed metal oxides. The obtained Raman mapping data were first subjected to singular value decomposition to obtain the right singular vectors, and the right singular vectors were then subjected to band-target entropy minimization (BTEM) to recover the pure component spectra of the observed species present in the sample. Subsequently, these resolved pure component spectral information was used to differentiate the physical and chemical mixtures. In addition, BTEM is also able to recover the pure component spectra of both unstable compound and its degradation product due to laser irradiation. In current study, the physical mixture of Mn₂O₃ and Co₃O₄, and the chemical mixture of CoMn₂O₄ spinel oxide were investigated.     

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.     

Application of kernel principal component analysis for single-lead-ECG-derived respiration

Recent studies show that principal component analysis (PCA) of heartbeats is a well-performing method to derive a respiratory signal from ECGs. In this study, an improved ECG-derived respiration (EDR) algorithm based on kernel PCA (kPCA) is presented. KPCA can be seen as a generalization of PCA where nonlinearities in the data are taken into account by nonlinear mapping of the data, using a kernel function, into a higher dimensional space in which PCA is carried out. The comparison of several kernels suggests that a radial basis function (RBF) kernel performs the best when deriving EDR signals. Further improvement is carried out by tuning the parameter σ(2) that represents the variance of the RBF kernel. The performance of kPCA is assessed by comparing the EDR signals to a reference respiratory signal, using the correlation and the magnitude squared coherence coefficients. When comparing the coefficients of the tuned EDR signals using kPCA to EDR signals obtained using PCA and the algorithm based on the R peak amplitude, statistically significant differences are found in the correlation and coherence coefficients (both p<0.0001), showing that kPCA outperforms PCA and R peak amplitude in the extraction of a respiratory signal from single-lead ECGs.     

Scheduling bursts in time-domain wavelength interleaved networks

A time-domain wavelength interleaved network (TWIN) (Widjaja, I. et al., IEEE Commun. Mag., vol.41, 2003) is an optical network with an ultrafast tunable laser and a fixed receiver at each node. We consider the problem of scheduling bursts of data in a TWIN. Due to the high data rates employed on the optical links, the burst transmissions typically last for very short times compared with the round trip propagation times between source-destination pairs. A good schedule should ensure that: 1) there are no transmit/receive conflicts; 2) propagation delays are observed; 3) throughput is maximized (schedule length is minimized). We formulate the scheduling problem with periodic demand as a generalization of the well-known crossbar switch scheduling. We prove that even in the presence of propagation delays, there exist a class of computationally viable scheduling algorithms which asymptotically achieve the maximum throughput obtainable without propagation delays. We also show that any schedule can be rearranged to achieve a factor-two approximation of the maximum throughput even without asymptotic limits. However, the delay/throughput performance of these schedules is limited in practice. We consequently propose a scheduling algorithm that exhibits near optimal (on average within /spl sim/7% of optimum) delay/throughput performance in realistic network examples.