Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

炉壁集束碳氧枪在电炉中的应用

介绍了鄂钢电炉厂70t consteel 电炉使用炉壁集束碳氧枪后对经济指标的改善,以及在生产实践中的冶金效果.     

A Real-World Application of Lane-Guidance Technologies—Automated Snowblower

This paper describes the development process and the initial field test results of an automated snowblower, focusing on one of the more difficult snow removal operations: blowing snow off the freeway alongside a guardrail without the snowblower touching the guardrail. The development process includes transforming this highway winter maintenance operation into a control problem, modeling a snowblower, designing control algorithms, devising a human-machine interface, and equipping a 20-ton snowblower with sensors and an actuator. Specific challenges include modeling the low-speed tire-induced oscillation, designing high-gain automatic control on front wheels while keeping rear steering under driver control, and implementing such a system under practical limitations. A new dynamic deflection tire model is incorporated into a bicycle model to account for the additional lateral dynamics. A low-order controller was first generated based on the understanding of the specific control problem and, then, refined and tuned iteratively using linear-matrix-inequality optimization. The initial winter field tests were successfully conducted with embedded magnetic markers along the guardrails installed on the shoulders of Interstate-80 in the Sierra Mountain region close to Donner Summit, CA, during the winter of 2005.     

β-hydroxyacyl-coa-dehydrogenase (HADH) activity of unfrozen and frozen—thawed frog (Rana esculenta) legs

The β-hydroxyacyl-CoA-dehydrogenase (HADH) activity of unfrozen and thawed frog legs was investigated. The enzyme was extracted by either immersing frog legs in phosphate buffer 0.1 M, pH 6.0 at 25°C for 15 min or pressing them between trichinoscopy glasses. The enzyme activity was assayed using acetoacetyl-CoA as substrate and measured spectrophotometrically at 340 nm. It was possible by both extraction methods to distinguish between thawed and unfrozen samples although when the juice was obtained by pressing the HADH activity of the dilution was ～ 1.5 times higher than that obtained by immersion. The HADH activity was significantly higher (P≤0·001) in frozen-thawed frogs than in unfrozen legs because during freezing there is a release of HADH. No significative differences were found in the HADH activity in samples frozen in the temperature range -10 to -196°C. HADH activity was not affected by the storage time in crushed ice up to 6 days.     

Rapid determination of chlorophylls in vegetable oils by laser-based fluorometry

The presence of chlorophylls in vegetable oils is considered undesirable due to their adverse effects on oxidative deterioration, bleachability and hydrogenation. The usual methods for determination of chlorophylls in vegetable oils are absorption spectrophotometry, fluorometry and liquid chromatography using fluorescence detectors. This paper outlines a fluorometric method using a laser as the excitation source. The chlorophylls in crude palm oil, rapeseed oil, soya bean oil and olive oil were determined directly by laser-based fluorometry using (a) a helium-neon laser (632-8 nm, 5 mW) as the excitation source and an optical-multichannel analyser (OMA) with an intensified diode array as the detector, and (b) a helium-neon laser and a photomultiplier tube as the detector. The method is especially suitable for the detection of chlorophylls in crude palm oil since no pre-extraction step is required. The levels of chlorophylls measured in vegetable oils using the laser technique was also compared against values obtained by conventional spectrophotometric methods. The simplicity and rapid quantification of laser based fluorometry suggest that this technique can be readily applied to the detection or a wide variety of fluorescing species in vegetable oils.     

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theorectically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

Enhancement of oxide break-up by implantation of fluorine inpoly-Si emitter contacted p+-n shallow junctionformation

In this study, it is demonstrated that the incorporation of fluorine can enhance poly-Si/Si interfacial oxide break-up in the poly-Si emitter contacted p⁺-n shallow junction formation. The annealing temperature for breaking up the poly-Si/Si interfacial oxide has been found to be as low as 900°C. As a result, the junction depth of the BF₂-implanted device is much larger than that of the boron-implanted device     

Using artificial intelligence to model heavy plate mill rolling

This research summary discusses the application of neural networks, evolutionary strategies, and other artificial intelligence techniques in the modeling and optimization of the models used for temperature, rolling force, and torque calculation in heavy plate milling.