Deposition of F-doped ZnO transparent thin films using ZnF2-doped ZnO target under different sputtering substrate temperatures

Highly transparent and conducting fluorine-doped ZnO (FZO) thin films were deposited onto glass substrates by radio-frequency (RF) magnetron sputtering, using 1.5 wt% zinc fluoride (ZnF2)-doped ZnO as sputtering target. Structural, electrical, and optical properties of the FZO thin films were investigated as a function of substrate temperature ranging from room temperature (RT) to 300°C. The cross-sectional scanning electron microscopy (SEM) observation and X-ray diffraction analyses showed that the FZO thin films were of polycrystalline nature with a preferential growth along (002) plane perpendicular to the surface of the glass substrate. Secondary ion mass spectrometry (SIMS) analyses of the FZO thin films showed that there was incorporation of F atoms in the FZO thin films, even if the substrate temperature was 300°C. Finally, the effect of substrate temperature on the transmittance ratio, optical energy gap, Hall mobility, carrier concentration, and resistivity of the FZO thin films was also investigated

Joint QoS-Aware Scheduling and Precoding for Massive MIMO Systems via Deep Reinforcement Learning

The rapid development of mobile networks proliferates the demands of high data rate, low latency, and high-reliability applications for the fifth-generation (5G) and beyond (B5G) mobile networks. Concurrently, the massive multiple-input-multiple-output (MIMO) technology is essential to realize the vision and requires coordination with resource management functions for high user experiences. Though conventional cross-layer adaptation algorithms have been developed to schedule and allocate network resources, the complexity of resulting rules is high with diverse quality of service (QoS) requirements and B5G features. In this work, we consider a joint user scheduling, antenna allocation, and precoding problem in a massive MIMO system. Instead of directly assigning resources, such as the number of antennas, the allocation process is transformed into a deep reinforcement learning (DRL) based dynamic algorithm selection problem for efficient Markov decision process (MDP) modeling and policy training. Specifically, the proposed utility function integrates QoS requirements and constraints toward a long-term system-wide objective that matches the MDP return. The componentized action structure with action embedding further incorporates the resource management process into the model. Simulations show 7.2% and 12.5% more satisfied users against static algorithm selection and related works under demanding scenarios

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

While representation learning aims to derive interpretable features for describing visual data, representation disentanglement further results in such features so that particular image attributes can be identified and manipulated. However, one cannot easily address this task without observing ground truth annotation for the training data. To address this problem, we propose a novel deep learning model of Cross-Domain Representation Disentangler (CDRD). By observing fully annotated source-domain data and unlabeled target-domain data of interest, our model bridges the information across data domains and transfers the attribute information accordingly. Thus, cross-domain joint feature disentanglement and adaptation can be jointly performed. In the experiments, we provide qualitative results to verify our disentanglement capability. Moreover, we further confirm that our model can be applied for solving classification tasks of unsupervised domain adaptation, and performs favorably against state-of-the-art image disentanglement and translation methods.Comment: CVPR 2018 Spotligh

Random singlets and permutation symmetry in the disordered spin-2 Heisenberg chain: A tensor network renormalization group study

We use a tensor network renormalization group method to study random $S=2$ antiferromagnetic Heisenberg chains with alternating bond strength distributions. In the absence of randomness, bond alternation induces two quantum critical points between the $S=2$ Haldane phase, a partially dimerized phase and a fully dimerized phase, depending on the strength of dimerization. These three phases, called ($\sigma$,$4-\sigma$)=(2,2), (3,1) and (4,0) phases, are valence-bond solid (VBS) states characterized by $\sigma$ valence bonds forming across even links and $4-\sigma$ valence bonds on odd links. Here we study the effects of bond randomness on the ground states of the dimerized spin chain, calculating disorder-averaged twist order parameters and spin correlations. We classify the types of random VBS phases depending on strength of bond randomness $R$ and the dimerization $D$ using the twist order parameter, which has a negative/positive sign for a VBS phase with odd/even $\sigma$. Our results demonstrate the existence of a multicritical point in the intermediate disorder regime with finite dimerization, where (2,2), (3,1) and (4,0) phases meet. This multicritical point is at the junction of three phase boundaries in the $R$-$D$ plane: the (2,2)-(3,1) and (3,1)-(4,0) boundaries that extend to zero randomness, and the (2,2)-(4,0) phase boundary that connects another multicritical point in the undimerized limit. The undimerized multicritical point separates a gapless Haldane phase and an infinite-randomness critical line with the diverging dynamic critical exponent in the large $R$ limit at $D=0$. Furthermore, we identify the (3,1)-(4,0) phase boundary as an infinite-randomness critical line even at small $R$, and find the signature of infinite randomness at the (2,2)-(3,1) phase boundary only in the vicinity of the multicritical point.Comment: 13 pages, 14 figure

Effects of Hydrogen Plasma on the Electrical Properties of F-Doped ZnO Thin Films and p-i-n -Si:H Thin Film Solar Cells

1.5 wt% zinc fluoride (ZnF2) was mixed with zinc oxide powder to form the F-doped ZnO (FZO) composition. At first, the FZO thin films were deposited at room temperature and 5×10-3 Torr in pure Ar under different deposition power. Hall measurements of the as-deposited FZO thin films were investigated, and then the electrical properties were used to find the deposition power causing the FZO thin films with minimum resistance. The FZO thin films with minimum resistance were further treated by H2 plasma and then found their variations in the electrical properties by Hall measurements. Hydrochloric (HCl) acid solutions with different concentrations (0.1%, 0.2%, and 0.5%) were used to etch the surfaces of the FZO thin films. Finally, the as-deposited, HCl-etched as-deposited, and HCl-etched H2-plasma-treated FZO thin films were used as transparent electrodes to fabricate the p-i-n α-Si:H thin film solar cells and their characteristics were compared in this study. We would show that using H2-plasma-treated and HCl-etched FZO thin films as transparent electrodes would improve the efficiency of the fabricated thin film solar cells

iGEMDOCK: a graphical environment of enhancing GEMDOCK using pharmacological interactions and post-screening analysis

<p>Abstract</p> <p>Background</p> <p>Pharmacological interactions are useful for understanding ligand binding mechanisms of a therapeutic target. These interactions are often inferred from a set of active compounds that were acquired experimentally. Moreover, most docking programs loosely coupled the stages (binding-site and ligand preparations, virtual screening, and post-screening analysis) of structure-based virtual screening (VS). An integrated VS environment, which provides the friendly interface to seamlessly combine these VS stages and to identify the pharmacological interactions directly from screening compounds, is valuable for drug discovery.</p> <p>Results</p> <p>We developed an easy-to-use graphic environment, <it>i</it>GEMDOCK, integrating VS stages (from preparations to post-screening analysis). For post-screening analysis, <it>i</it>GEMDOCK provides biological insights by deriving the pharmacological interactions from screening compounds without relying on the experimental data of active compounds. The pharmacological interactions represent conserved interacting residues, which often form binding pockets with specific physico-chemical properties, to play the essential functions of a target protein. Our experimental results show that the pharmacological interactions derived by <it>i</it>GEMDOCK are often hot spots involving in the biological functions. In addition, <it>i</it>GEMDOCK provides the visualizations of the protein-compound interaction profiles and the hierarchical clustering dendrogram of the compounds for post-screening analysis.</p> <p>Conclusions</p> <p>We have developed <it>i</it>GEMDOCK to facilitate steps from preparations of target proteins and ligand libraries toward post-screening analysis. <it>i</it>GEMDOCK is especially useful for post-screening analysis and inferring pharmacological interactions from screening compounds. We believe that <it>i</it>GEMDOCK is useful for understanding the ligand binding mechanisms and discovering lead compounds. <it>i</it>GEMDOCK is available at <url>http://gemdock.life.nctu.edu.tw/dock/igemdock.php</url>.</p

DNA Binding and Degradation by the HNH Protein ColE7

The bacterial toxin ColE7 bears an HNH motif which has been identified in hundreds of prokaryotic and eukaryotic endonucleases, involved in DNA homing, restriction, repair, or chromosome degradation. The crystal structure of the nuclease domain of ColE7 in complex with a duplex DNA has been determined at 2.5 Å resolution. The HNH motif is bound at the minor groove primarily to DNA phosphate groups at and beyond the 3′ side of the scissile phosphate, with little interaction with ribose groups and bases. This result provides a structural basis for sugar- and sequence-independent DNA recognition and the inhibition mechanism by inhibitor Im7, which blocks the substrate binding site but not the active site. Structural comparison shows that two families of endonucleases bind and bend DNA in a similar way to that of the HNH ColE7, indicating that endonucleases containing a “ββα-metal” fold of active site possess a universal mode for protein-DNA interactions

BETTER POSTURAL CONTROL DURING ACCURATE SHOOTING IN ELITE FEMALE BASKETBALL PLAYERS

The purpose of this study was to evaluate the differences of postural control (PC) during accurate and inaccurate shooting in elite female basketball players. 21 female professional basketball players recruited as subjects. The PC was evaluated by the Accusway as sway radius, velocity, radial and 95% area of the center of pressure (COP) during standard penalty line shooting. The results showed that the COP sway area during accurate shooting was significantly smaller than during inaccurate shooting (74.0 ± 37.9 vs. 110.6 ± 49.1, p < .05). Moreover, no significant differences were found between situations in the COP radius and velocity. This study found that during the accurate shooting, elite female basketball player had better PC which demonstrated that significant smaller COP sway area than inaccurate shooting