抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Infectious Diseases Society of America.

Memristive devices are electrical resistance switches that can retain a state of internal resistance based on the history of applied voltage and current. These devices can store and process information, and offer several key performance characteristics that exceed conventional integrated circuit technology. An important class of memristive devices are two-terminal resistance switches based on ionic motion, which are built from a simple conductor/insulator/conductor thin-film stack. These devices were originally conceived in the late 1960s and recent progress has led to fast, low-energy, high-endurance devices that can be scaled down to less than 10 nm and stacked in three dimensions. However, the underlying device mechanisms remain unclear, which is a significant barrier to their widespread application. Here, we review recent progress in the development and understanding of memristive devices. We also examine the performance requirements for computing with memristive devices and detail how the outstanding challenges could be met.

Memristive devices for computing

Transparent electronics is today one of the most advanced topics for a wide range of device applications. The key components are wide bandgap semiconductors, where oxides of different origins play an important role, not only as passive component but also as active component, similar to what is observed in conventional semiconductors like silicon. Transparent electronics has gained special attention during the last few years and is today established as one of the most promising technologies for leading the next generation of flat panel display due to its excellent electronic performance. In this paper the recent progress in n- and p-type oxide based thin-film transistors (TFT) is reviewed, with special emphasis on solution-processed and p-type, and the major milestones already achieved with this emerging and very promising technology are summarizeed. After a short introduction where the main advantages of these semiconductors are presented, as well as the industry expectations, the beautiful history of TFTs is revisited, including the main landmarks in the last 80 years, finishing by referring to some papers that have played an important role in shaping transparent electronics. Then, an overview is presented of state of the art n-type TFTs processed by physical vapour deposition methods, and finally one of the most exciting, promising, and low cost but powerful technologies is discussed: solution-processed oxide TFTs. Moreover, a more detailed focus analysis will be given concerning p-type oxide TFTs, mainly centred on two of the most promising semiconductor candidates: copper oxide and tin oxide. The most recent data related to the production of complementary metal oxide semiconductor (CMOS) devices based on n- and p-type oxide TFT is also be presented. The last topic of this review is devoted to some emerging applications, finalizing with the main conclusions. Related work that originated at CENIMAT|I3N during the last six years is included in more detail, which has led to the fabrication of high performance n- and p-type oxide transistors as well as the fabrication of CMOS devices with and on paper.

Oxide Semiconductor Thin‐Film Transistors: A Review of Recent Advances

Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 10(14) synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

In this paper, growth behavior of high density Al2O3 which was prepared by using cyclic chemical vapor deposition (C-CVD) system has been systematically investigated. Tri-Methyl-Aluminum (TMA) and oxygen (02) plasma was used as source precursor and reactant, respectively. Unlike the conventional ALD system that source precursor and reactant was injected alternatively that was separated by inert gas purge step, TMA and 02 was mixed and co-fed into the process chamber simultaneously, followed by purge step. To obtain high density and defects-free Al2O3 layer, source precursor feeding time and the number of deposition cycles dependence on the thickness of C-CVD grown Al2O3 layer were investigated. We found that thickness of Al2O3 layer was increased almost linearly as the number of cycles increased which are typical characteristics of CVD. On the other hand, self-limiting phenomenon was observed in thickness as source feeding time increased which showed saturation of the thickness as source feeding time further increased. Using the optimized C-CVD process conditions, density of 3.298 g/cm3 was obtained in 100 nm thick Al2O3 layer whereas that of ALD Al2O3 was 3.192 g/cm3. The C-CVD grown Al2O3 layer effectively prevents water vapor from diffusing into active layer of organic light emitting diodes, which shows C-CVD grown Al2O3 layer can be applied to water vapor permeation barrier layer in organic light emitting diodes.

Growth Behavior of High Density Al2O3 Layer Prepared by Using Cyclic Chemical Vapor Deposition Technology.

The anterolateral thigh flap (ALTF) is a versatile fasciocutaneous or myocutaneous flap, which can be harvested incorporating several skin islands and muscle components. The perforator of the ALTF is usually derived from the descending or transverse branch of the lateral circumflex femoral artery, and these vessels are based mainly on musculocutaneous perforators traversing the vastus lateralis muscle, and also based on the septocutaneous vessels running in between the rectus femoris and vastus lateralis muscle. Despite its usefulness for the oral cavity reconstruction, anatomic variations of these nutrient vessels, such as three main branches of ALTF and its relations with sartorius, vastus lateralis, tensor fasciae latae and rectus femoris muscle, have been reconstructive surgeons to be hesitated for the selection of ALTF. For the better understanding of ALTF as a routine reconstructive procedure in oral and maxillofacial surgery, various anatomical findings must be learned and memorized by young doctors in the course of the special curriculum periods for the Korean national board of oral and maxillofacial surgery. This review article will discuss the vascular anatomy and relavant anatomical variations of ALTF with Korean language.

Anatomical Review of Anterolateral Thigh Flap for the Oral and Maxillofacial Reconstruction

In this paper, an inversely tapered coupler with Bragg reflectors is reported for the first time. With appropriately positioned reflecting structures, our fiber-to-chip coupler can transmit the light from an optical fiber into a waveguide in PIC (photonic IC) more efficiently. A numerical simulation evaluated the coupling efficiency of the coupler with the reflector. The optimized parameters which maximize the coupling efficiency of the coupler are also investigated. The simulation result shows that the reflector with appropriate parameters enhances the efficiency up to 7dB.

Design of a high efficient fiber-to-chip coupler with reflectors

A synapse device array based on the gated Schottky diodes (GSDs) is fabricated. This GSD operates in reverse mode, so the synapse current is considerably low, helping to implement a low-power hardware-based neural networks (HNNs). The reverse Schottky diode current, which represents the synaptic weight, is modulated by applying program or erase pulses. In this GSD, the reverse diode current is used as the synapse current, but the forward diode current is cut off. This is an important feature to prevent the sneak path problem in the crossbar array. A synapse array consisting of fabricated 200 GSDs shows a variation (σ/μ) of 0.34, 0.22, and 0.14 for three different synaptic weight states. By using this GSD array, we perform the vector-by-matrix multiplication, and evaluate the inference accuracy of MNIST. As a baseline accuracy for MNIST classification, a convolutional neural network similar to Lenet-5 is designed and gives an accuracy of 99.53%. Normalization method is applied to the weights trained in the network to map the weights into the conductance range of synapse device. The adaptive weight quantization is then applied to the normalized weights. We verify that the HNN using GSDs works well in comparison to the baseline network even in the presence of non-ideal characteristics of synapse devices.

Investigation of Neural Networks Using Synapse Arrays Based on Gated Schottky Diodes

Dielektrische Mehrfachschicht mit – einer Kompositschicht (101) aus einem Oxid von zwei oder mehr verschiedenen Elementen in einer nicht-laminaren Struktur und – einer Einzelschicht (102) aus einem Oxid eines einzelnen Elements auf wenigstens einer Oberflache der Kompositschicht, dadurch gekennzeichnet, dass – die Kompositschicht aus einem Oxid gebildet ist, das durch M1 x M2 y O z ausgedruckt wird, wobei M1 Aluminium ist und M2 aus der Gruppe ausgewahlt ist, die aus Hafnium (Hf), Zirkonium (Zr), Lanthan (La), Tantal (Ta), Chrom (Cr), Molybdan (Mo), Wolfram (W), Titan (Ti), Yttrium (Y) und Mangan (Mn) besteht, und – die Einzelschicht aus einem Oxid gebildet ist, das aus der Gruppe ausgewahlt ist, die aus Oxiden von Aluminium (Al), Hafnium (Hf), Zirkonium (Zr), Lanthan (La), Tantal (Ta), Strontium (Sr), Barium (Ba), Blei (Pb), Chrom (Cr), Molybdan (Mo), Wolfram (W), Titan (Ti), Yttrium (Y) und Mangan (Mn) besteht.

Jong-Ho Lee

Papers

Growth Behavior of High Density Al2O3 Layer Prepared by Using Cyclic Chemical Vapor Deposition Technology.

Anatomical Review of Anterolateral Thigh Flap for the Oral and Maxillofacial Reconstruction

Design of a high efficient fiber-to-chip coupler with reflectors

Investigation of Neural Networks Using Synapse Arrays Based on Gated Schottky Diodes

Dielektrische Mehrfachschicht, mikroelektronisches Bauelement, Kondensator und Herstellungsverfahren