EGF-functionalized single-walled carbon nanotubes for targeting delivery of etoposide

To enhance the therapeutic potential of etoposide (ETO), we devised a targeted drug delivery system (TDDS) of epidermal growth factor-chitosan-carboxyl single-walled carbon nanotubes-ETO (EGF/CHI/SWNT-COOHs/ETO) using modified SWNTs (m-SWNTs) as the carrier, EGF-functionalized SWNTs (f-SWNTs) as the targeted moiety and ETO as the drug. After SWNT-COOHs were conjugated with CHI (CHI/SWNT-COOHs/ETO), they displayed high solubility and stable dispersion in aqueous solution. The drug loading capacity was approximately 25-27%. The m-SWNTs and f-SWNTs had only slight cytotoxicity. ETO was released from EGF/CHI/SWNT-COOHs/ETO at low pH and taken up by tumour cells via adenosine triphosphate (ATP)-dependent endocytosis. The cell death induced by EGF/CHI/SWNT-COOHs/ETO was as much as 2.7 times that due to ETO alone. In summary, these results demonstrated that our TDDS had a greater anticancer effect than free ETO in vitro.     

Optimal scan strategy for mega-pixel and kilo-gray-level OLED-on-silicon microdisplay

The digital pixel driving scheme makes the organic light-emitting diode (OLED) microdisplays more immune to the pixel luminance variations and simplifies the circuit architecture and design flow compared to the analog pixel driving scheme. Additionally, it is easily applied in full digital systems. However, the data bottleneck becomes a notable problem as the number of pixels and gray levels grow dramatically. This paper will discuss the digital driving ability to achieve kilogray-levels for megapixel displays. The optimal scan strategy is proposed for creating ultra high gray levels and increasing light efficiency and contrast ratio. Two correction schemes are discussed to improve the gray level linearity. A 1280×1024×3 OLED-on-silicon microdisplay, with 4096 gray levels, is designed based on the optimal scan strategy. The circuit driver is integrated in the silicon backplane chip in the 0.35 μm 3.3 V-6 V dual voltage one polysilicon layer, four metal layers (1P4M) complementary metal-oxide semiconductor (CMOS) process with custom top metal. The design aspects of the optimal scan controller are also discussed. The test results show the gray level linearity of the correction schemes for the optimal scan strategy is acceptable by the human eye.     

Evolutionary algorithm based uniform received power and illumination rendering for indoor visible light communication

In this paper, an evolutionary algorithm based optimization scheme is proposed to realize uniform received power and illumination distribution on the communication floor for fully diffuse indoor visible light communication. Simulation results show that in three distributed lighting configurations, by dynamically modifying the relative optical intensity of transmitters the dynamic range of the received power, referenced against the peak received power, can be reduced to about 40.0% while the uniformity illuminance ratio can be improved up to about 0.70 with the impact to the root mean square delay spread and bandwidth being negligible. Furthermore, the relationship between the field of view of the receivers and the optimization performance is presented as well.     

梳棉滤尘应用间歇吸的实践与体会

我厂105台A186_E~D型梳棉机的滤尘装置由纺织工业部设计院设计,其后吸全部采用了间歇吸落棉技术,为此我们对A186D型梳棉机吸尘系统进行了改造,将该机上、下吸分为两个系统:上吸为常吸,后车肚改为间歇吸,同时增加了盖板花吸点。上吸风量配置为,刺辊盖罩200米~3/时,三角区250米~3/时,盖板花250米~3/     

3-d object retrieval and recognition with hypergraph analysis

View-based 3-D object retrieval and recognition has become popular in practice, e.g., in computer aided design. It is difficult to precisely estimate the distance between two objects represented by multiple views. Thus, current view-based 3-D object retrieval and recognition methods may not perform well. In this paper, we propose a hypergraph analysis approach to address this problem by avoiding the estimation of the distance between objects. In particular, we construct multiple hypergraphs for a set of 3-D objects based on their 2-D views. In these hypergraphs, each vertex is an object, and each edge is a cluster of views. Therefore, an edge connects multiple vertices. We define the weight of each edge based on the similarities between any two views within the cluster. Retrieval and recognition are performed based on the hypergraphs. Therefore, our method can explore the higher order relationship among objects and does not use the distance between objects. We conduct experiments on the National Taiwan University 3-D model dataset and the ETH 3-D object collection. Experimental results demonstrate the effectiveness of the proposed method by comparing with the state-of-the-art methods.     

High Power Fiber Bundle Array Coupled LDA Module

1 Introduction High power laser diode arrays (LDA) have many advan- tages such as small volume, long working life, high slope efficiency and high optical density, so they have many applications in medical treatment, material pro- cessing, and for the pumping source of solid laser and etc. But unfortunately, the LDA can not be easy to use directly in these fields because of their poor beam quality and extremely asymmetric divergent beams (!x≈ 5°～10°and !y≈20°～35°, for example), so it …     

Development of Fiber Lasers and Their Applications

1 Introduction Fiber lasers have been developed for more than forty years since Snitzer!s proposal and the demonstration of Nd- doped fiber in 1961 [1]. But fiber lasers have not been attracted considerable attention until the develop- ment of the low- loss fiber fabrication technology and the high power semiconductor laser technology recently. Actually,it is the application and development of fiber communication technology that has promoted the rapid development of fiber laser. Fiber laser, …     

Novel DTD and VAD assisted voice detection algorithm for VoIP systems

Echo cancellation plays an important role in current Internet protocol(IP) based voice interactive systems. Voice state detection is an essential part in echo cancellation. It mainly comprises two parts: double talk detection(DTD) and voice activity detection(VAD). DTD is used to detect doubletalk and prevent filter divergence in the presence of near-end speech, and VAD is used to determine the near-end voice activity and output silence indicator when near-end is silent. However, DTD straightforwardly proceeded may mistakenly declare double talk under double silent condition, coefficients update under the far-end silence condition may lead to filter divergence, and current VAD algorithms may misjudge the residual echo from the near end to be far-end voice. Therefore, a voice detection algorithm combining DTD and far-end VAD is proposed. DTD is implemented when VAD declares far-end speech, filtering and coefficients update will be halted when VAD declares far-end silence, and the far-end VAD adopted is multi-feature VAD based on short-time energy and correlation. The new algorithm can improve the accuracy of DTD, prevent filter divergence, and exclude the circumstance that far-end signal only contains residual echo from near end. Actual test results show that the voice state decision of the new algorithm is accurate, and the performance of echo cancellation is improved.     

A Solenoid-Type Inductor Fabricated by MEMS Technique

A solenoid-type inductor for high frequency application is realized using a micro-electro-mechanical systems (MEMS) technique.In order to achieve a high inductance value and Q factor,UV-LIGA,dry etching technique,fine polishing and electroplating technique are adopted.The dimensions of the inductor are 1500μm×900μm×70μm,having 41 turns with a coil width of 20μm separated by 20μm spaces and a high aspect ratio of 3.5∶1.The maximum measured inductance of the inductor is 6.17nH with a Q factor of about 6.     

Fuzzy local Gaussian mixture model for brain MR image segmentation

Accurate brain tissue segmentation from magnetic resonance (MR) images is an essential step in quantitative brain image analysis. However, due to the existence of noise and intensity inhomogeneity in brain MR images, many segmentation algorithms suffer from limited accuracy. In this paper, we assume that the local image data within each voxel's neighborhood satisfy the Gaussian mixture model (GMM), and thus propose the fuzzy local GMM (FLGMM) algorithm for automated brain MR image segmentation. This algorithm estimates the segmentation result that maximizes the posterior probability by minimizing an objective energy function, in which a truncated Gaussian kernel function is used to impose the spatial constraint and fuzzy memberships are employed to balance the contribution of each GMM. We compared our algorithm to state-of-the-art segmentation approaches in both synthetic and clinical data. Our results show that the proposed algorithm can largely overcome the difficulties raised by noise, low contrast, and bias field, and substantially improve the accuracy of brain MR image segmentation.