Hysteresis suppression improvement of polycrystalline silicon thin-film transistors by two-step hydrogenation

The effect of two-step hydrogenation, consisting of plasma hydrogenation and annealing in hydrogen, on the hysteresis phenomenon of metal-induced unilaterally crystallized silicon thin-film transistors (MIUC-Si TFTs) was investigated. The large hysteresis level of the conventional MIUC-Si TFTs caused a wide variation of the drain current with the previous gate voltage. As the plasma exposure time increased, the plasma hydrogenation commonly used for stability in poly-Si TFTs was found to increase the hysteresis level of MIUC-Si TFTs after a minimum point. This is because plasma-induced damages correlated with unique defects of MIUC-Si such as metal-related weak bonds, are accompanied by passivation. The following annealing repaired the damages. Consequently the hysteresis level was lower, which resulted in a narrower variation of the drain current.     

Cotton fabric coated with nano TiO2-acrylate copolymer for photocatalytic self-cleaning by in-situ suspension polymerization

Two kinds of nano TiO₂-polyacrylate hybrid dispersions, TBM-w and TBM-e were synthesized by in-situ suspension polymerization and solution polymerization respectively, in order to fix the nano TiO₂ on fabrics. The photocatalytic self-cleaning fabrics have received much attention in recent years for its water-saving and environment-protection advantages. However, the fixation of the photocatalyst on fabrics is still a key problem that inhibits industrialization of these eco-friendly fabrics. The cotton fabric was treated by the two hybrid dispersions. The photocatalytic self-cleaning property was characterized. Infrared spectroscopy, burning loss test and thermogravimetry showed that some copolymer chains entangled with the nano TiO₂. Transmission electron microscope illustrated that there was a polymeric layer on the surface of nano TiO₂. The average diameter of TBM-w was smaller than that of TBM-e based on size analysis. The photocatalytic decoloration of the grape syrup indicated that the fabric with TiO₂-polymer hybrid had excellent self-cleaning property.     

Unsupervised MRI segmentation of brain tissues using a local linear model and level set

Real-world magnetic resonance imaging of the brain is affected by intensity nonuniformity (INU) phenomena which makes it difficult to fully automate the segmentation process. This difficult task is accomplished in this work by using a new method with two original features: (1) each brain tissue class is locally modeled using a local linear region representative, which allows us to account for the INU in an implicit way and to more accurately position the region's boundaries; and (2) the region models are embedded in the level set framework, so that the spatial coherence of the segmentation can be controlled in a natural way. Our new method has been tested on the ground-truthed Internet Brain Segmentation Repository (IBSR) database and gave promising results, with Tanimoto indexes ranging from 0.61 to 0.79 for the classification of the white matter and from 0.72 to 0.84 for the gray matter. To our knowledge, this is the first time a region-based level set model has been used to perform the segmentation of real-world MRI brain scans with convincing results.     

A joint shape evolution approach to medical image segmentation using expectation-maximization algorithm

This study proposes an expectation–maximization (EM)-based curve evolution algorithm for segmentation of magnetic resonance brain images. In the proposed algorithm, the evolution curve is constrained not only by a shape-based statistical model but also by a hidden variable model from image observation. The hidden variable model herein is defined by the local voxel labeling, which is unknown and estimated by the expected likelihood function derived from the image data and prior anatomical knowledge. In the M-step, the shapes of the structures are estimated jointly by encoding the hidden variable model and the statistical prior model obtained from the training stage. In the E-step, the expected observation likelihood and the prior distribution of the hidden variables are estimated. In experiments, the proposed automatic segmentation algorithm is applied to multiple gray nuclei structures such as caudate, putamens and thalamus of three-dimensional magnetic resonance imaging in volunteers and patients. As for the robustness and accuracy of the segmentation algorithm, the results of the proposed EM-joint shape-based algorithm outperformed those obtained using the statistical shape model-based techniques in the same framework and a current state-of-the-art region competition level set method.     

γ-Active Constraints in Convex Semi-Infinite Programming

In this article, we extend the definition of γ-active constraints for linear semi-infinite programming to a definition applicable to convex semi-infinite programming, by two approaches. The first approach entails the use of the subdifferentials of the convex constraints at a point, while the second approach is based on the linearization of the convex inequality system by means of the convex conjugates of the defining functions. By both these methods, we manage to extend the results on γ-active constraints from the linear case to the convex case.     

Multiplex bioanalytical methods for food and environmental monitoring

Recent advances in miniaturization of analytical systems and newly emerging technologies offer platforms with greater automation and multiplexing capabilities than traditional biological binding assays. Multiplexed bioanalytical techniques provide control agencies and food industries with new possibilities for improved, more efficient monitoring of food and environmental contaminants. This review deals with recent developments in planar-array and suspension-array technologies, and their applications in detecting pathogens, food allergens and adulterants, toxins, antibiotics and environmental contaminants.     

Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems

Successful modeling and/or design of engineering systems often requires one to address the impact of multiple "design variables" on the prescribed outcome.There are often multiple,competing objectives based on which we assess the outcome of optimization.Since accurate,high fidelity models are typically time consuming and computationally expensive,comprehensive evaluations can be conducted only if an efficient framework is available.Furthermore,informed decisions of the model/hardware’s overall performance rely on an adequate understanding of the global,not local,sensitivity of the individual design variables on the objectives.The surrogate-based approach,which involves approximating the objectives as continuous functions of design variables from limited data,offers a rational framework to reduce the number of important input variables,i.e.,the dimension of a design or modeling space.In this paper,we review the fundamental issues that arise in surrogate-based analysis and optimization,highlighting concepts,methods,techniques,as well as modeling implications for mechanics problems.To aid the discussions of the issues involved,we summarize recent efforts in investigating cryogenic cavitating flows,active flow control based on dielectric barrier discharge concepts,and lithium(Li)-ion batteries.It is also stressed that many multi-scale mechanics problems can naturally benefit from the surrogate approach for "scale bridging."     

Active TLCGD control of plane asymmetric buildings under earthquake excitation

The sealed,tuned liquid column gas damper (TLCGD) with gas-spring effect extends the frequency range of application and efficiently increases the modal structural damping.Active tuned liquid column gas damper (ATLCGD) is developed for the vibration control of plane asymmetric buildings subjected to earthquake excitation,improving the performance of the passive control scheme.The active behaviour is obtained by adjusting the pressure at the end of the liquid column using a pressurised reservoir.The classical linear quadratic regulator (LQR) design is presented as a straightforward approach to optimal control.Numerical simulations indicate a significant vibration reduction of plane asymmetric buildings by active control within the strong motion of the dynamic response.     

Redox behaviour of thermally activated platinum electrodes with particular reference to operation at elevated temperature

The present work is a continuation of an earlier investigation of the effect of severe thermal pretreatment on the redox properties of platinum electrodes in aqueous media. The most interesting observation was that raising the solution temperature to ca. 75 °C resulted in a dramatic anodic response in the positive sweep at ca. 0.25 V (RHE). Such behaviour was noted earlier at room temperature but only when the thermally pretreated sample was further activated by cathodic polarization. This transition at 0.25 V was partially reversed on the negative sweep, but the cathodic process involved was subject to severe inhibition. There is independent evidence for similar behaviour for gold in aqueous acid solution. The relevance of the present results to the operation of fuel cell anodes is outlined. Received: 2 December 1999 / Accepted: 24 February 2000     

Palladium-catalyzed stereoselective synthesis of 3-(aminomethylene)-oxindoles

An efficient palladium-catalyzed protocol for the stereoselective synthesis of 3-(aminoarylmethylene)-oxindoles has been developed. In this approach, Ugi-4-component reaction adducts were used as starting materials for carbopalladative cyclization-Buchwald reaction sequences.