A strategy to release attached bacteria from surface-grafted bactericidal poly((trimethylamino)ethyl methacrylate chloride) (pTMAEMA) brushes has been proposed. The pTMAEMA brushes were fabricated via the surface-initiated atom transfer radical polymerization for contact killing of bacteria, including Escherichia coli, Staphylococcus epidermidis and Stenotrophomonas maltophilia. The bacteria-conditioning surfaces, afterward, were washed with electrolyte solutions containing anions with different lipophilic characteristic, charge density, polarity and adsorbility to quaternary ammonium groups in polymers. Because of the special ion-pairing interactions, the interfacial properties, including wettability and ζ-potential, can be manipulated in a controlled manner. Therefore, the counterion-assisted modulation of pTMAEMA brushes facilitates the bacterial release and regeneration of antimicrobial polymer films. The physicochemical properties of polymer brushes and their interactions with counterions were characterized using an ellipsometer, contact angle goniometer, X-ray photoelectron spectroscopy and an electrokinetic analyzer. The repetitive killing and releasing actions of pTMAEMA through unlocking and locking counterions were demonstrated, showing the robust effectiveness of the pTMAEMA-based nanoactuator in controlling the physical action by the chemical stimuli. The real-world implementation of the nanoactuator was demonstrated with a surgical scalpel by repelling killed bacteria and retaining reusability.

The tongue diagnosis is an important diagnostic method in Traditional Chinese Medicine (TCM). Human tongue is one of the im­portant organs which contain the information of health status. Image segmentation has always been a fundamental problem and complex task in the field of image processing and computer vision. Its goal is to change the representation of an image into something that is more meaningful and easier to analyze. In other words, it is used to partition a given image into several parts in each of which the intensity is homogeneous. In order to achieve an automatic tongue diagnostic system, an effective segmentation me­thod for detecting the edge of tongue is very important. We mainly compare the Chan Vese Method and Canny algorithm for edge segmentation. The segmentation using Canny algorithm may produce many false edges after cutting; thus, it is not suitable for use. But, for our two steps Chan Vese method can automatically select the best edge information. Therefore, it may be useful in clinical automated tongue diagnosis system. Experiments show the results of these techniques.

Brain Magnetic Resonance Imaging (MRI) has become a widely used modality because it produces multispectral image sequences that provide information of free water, proteinaceous fluid, soft tissue and other tissues with a variety of contrast. The abundance fractions of tissue signatures provided by multispectral images can be very useful for medical diagnosis compared to other modalities. Multiple Sclerosis (MS) is thought to be a disease in which the patient immune system damages the isolating layer of myelin around the nerve fibers. This nerve damage is visible in Magnetic Resonance (MR) scans of the brain. Manual segmentation is extremely time-consuming and tedious. Therefore, fully automated MS detection methods are being developed which can classify large amounts of MR data, and do not suffer from inter observer variability. In this paper we use standard fuzzy c-means algorithm (FCM) for multi-spectral images to segment patient MRI data. Geodesic Active Contours of Caselles level set is another method we implement to do the brain image segmentation jobs. And then we implement anther modified Fuzzy C-Means algorithm, where we call Bias-Corrected FCM as BCFCM, for bias field estimation for the same thing. Experimental results show the success of all these intelligent techniques for brain medical image segmentation.

This work describes the application of a cell-centered unstructured finite volume method with finite-rate chemistry model to hypersonic flows. The complex internal viscous flow in the HyShot-II Scramjet model is studied. Two dimensional CFD analyses considering air dissociation are presented on the complete geometry of the HyShot-II scramjet and separately on the combustion chamber at fuel-off conditions as a precursor to the future studies of three dimensional simulations, fuel-on combustion flows and designs of different scramjet models. The simulated pressure distribution in the combustor chamber at free stream flow of Mach 7.4 and altitude of 27 km is compared with the experimental results of a full-scale model of the HyShot II vehicle presented by Schramm et al 1 conducted at the High Enthalpy Shock Tunnel (HEG), German Aerospace Center (DLR). Good agreement is observed between the wind tunnel test and CFD results.

The present study is aimed to investigate the effects of wavy roughness on electro-osmotic (EO) flow over a wavy plate. The waviness of the plate is modeled by the product of two cosinoidal functions, and the roughness (ε) is defined to be the ratio of the wavy amplitude to the Debye length. The effects are examined with respect to the roughness ε and different wave numbers (α and β) of the plate waviness. The analysis of the EO flow over the wavy plate is carried out for the applied electric potential, the potential for the electric double layer, as well as the EO flow velocity and pressure field under the Debye-Hückel approximation by using a boundary perturbation method. It is found that the velocity component along the direction of the applied electric field is modified by a second-order term of the roughness, though the same velocity component near the wavy wall exhibits periodic behaviors in phase with the plate waviness. The mean flow rate deficit (ε2μ2) due to the surface roughness presents a sophisticated dependence on the longitudinal wave number (α) and transverse wave number (β) of the plate waviness, yet the flow deficit is linear in α for small α at β = 0, and shows a long wavelength limit singularity at β = 0 for α ≠ 0.