Low-temperature synthesis of CuO-interlaced nanodiscs for lithium ion battery electrodes

In this study, we report the high-yield synthesis of 2-dimensional cupric oxide (CuO) nanodiscs through dehydrogenation of 1-dimensional Cu(OH)2 nanowires at 60°C. Most of the nanodiscs had a diameter of approximately 500 nm and a thickness of approximately 50 nm. After further prolonged reaction times, secondary irregular nanodiscs gradually grew vertically into regular nanodiscs. These CuO nanostructures were characterized using X-ray diffraction, transmission electron microscopy, and Brunauer-Emmett-Teller measurements. The possible growth mechanism of the interlaced disc CuO nanostructures is systematically discussed. The electrochemical performances of the CuO nanodisc electrodes were evaluated in detail using cyclic voltammetry and galvanostatic cycling. Furthermore, we demonstrate that the incorporation of multiwalled carbon nanotubes enables the enhanced reversible capacities and capacity retention of CuO nanodisc electrodes on cycling by offering more efficient electron transport paths.     

Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization

Detecting and localizing image manipulation are necessary to counter malicious use of image editing techniques. Accordingly, it is essential to distinguish between authentic and tampered regions by analyzing intrinsic statistics in an image. We focus on JPEG compression artifacts left during image acquisition and editing. We propose a convolutional neural network that uses discrete cosine transform (DCT) coefficients, where compression artifacts remain, to localize image manipulation. Standard CNNs cannot learn the distribution of DCT coefficients because the convolution throws away the spatial coordinates, which are essential for DCT coefficients. We illustrate how to design and train a neural network that can learn the distribution of DCT coefficients. Furthermore, we introduce Compression Artifact Tracing Network that jointly uses image acquisition artifacts and compression artifacts. It significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.

     

Mitochondrial Peroxiredoxin III is a Potential Target for Cancer Therapy

Mitochondria are involved either directly or indirectly in oncogenesis and the alteration of metabolism in cancer cells. Cancer cells contain large numbers of abnormal mitochondria and produce large amounts of reactive oxygen species (ROS). Oxidative stress is caused by an imbalance between the production of ROS and the antioxidant capacity of the cell. Several cancer therapies, such as chemotherapeutic drugs and radiation, disrupt mitochondrial homeostasis and release cytochrome c, leading to apoptosome formation, which activates the intrinsic pathway. This is modulated by the extent of mitochondrial oxidative stress. The peroxiredoxin (Prx) system is a cellular defense system against oxidative stress, and mitochondria in cancer cells are known to contain high levels of Prx III. Here, we review accumulating evidence suggesting that mitochondrial oxidative stress is involved in cancer, and discuss the role of the mitochondrial Prx III antioxidant system as a potential target for cancer therapy. We hope that this review will provide the basis for new strategic approaches in the development of effective cancer treatments.     

A new damage quantification approach for shear-wall buildings using ambient vibration data

This paper presents a new approach to estimate damage severity for shear-wall buildings using diagonal terms of a modal flexibility matrix estimated from dynamic properties. This study aims to provide a fundamental concept for quantifying the damage of realistic buildings by investigating an idealized shear-wall building. Numerical studies were performed on a 5-story shear-wall building model to validate the applicability of the presented approach, using two damage patterns. With the numerical simulations, the proposed approach accurately determined the damage ratio of the specimens. Experiments were also conducted on a 5-story shear-wall building model for which the system parameters were almost the same as those in numerical simulations. The estimated damage-quantification results from the experimental validations demonstrated that the performance of the presented method for shear-wall buildings was both suitable and accurate.     

The characteristics of biodiesel and oxygenated additives in a compression ignition engine

In this study, experiments on the simultaneous reduction of smoke and NOx emissions of indirect-injection (IDI) diesel engines were conducted using a biodiesel fuel (BDF) and ethylene glycol mono-n-butyl ether (EGBE), which is an oxygenated fuel of mono-ethers, as a pre-processing method and by applying cooled EGR. A four-cylinder, water-cooled IDI diesel engine was used, while the engine performance and emission characteristics were considered using diesel fuel, BDF 100%, and a mixed fuel BDF and EGBE (maximum EGBE mixing ratio in mixed fuel: 20 vol-%). Results showed the BDF and the BDF and EGBE mix had significantly better smoke reduction effects than the diesel fuel. In particular, the use of the BDF and EGBE mix and the simultaneous application of 10% cooled EGR were confirmed to have reduced both smoke and NOx emissions.     

1D/2D carbon nanotube/graphene nanosheet composite anodes fabricated using electrophoretic assembly

This study examines the direct assembly of hybrid graphene nanosheets (GNSs) and multiwalled carbon nanotubes (MWCNTs) onto Ni current collectors in the presence of an electric field. The dissociation of Ni nitrate salt, which provides ions to charge the GNSs and MWCNTs positively, facilitates the homogeneous dispersion of each powder and assists in electrophoretic deposition. Direct assembly by this electrophoretic deposition results in the effective packing of GNS/MWCNT composites without any appreciable agglomeration, which is desirable for achieving high electrochemical performance of the composite electrodes in Li-ion batteries. Hence, GNS/MWCNT composite electrodes exhibit higher specific capacity compared to electrodes made of pure GNSs or MWCNTs owing to better realization of electrolyte permeability and Li-ion transfer.     

A CT saturation detection algorithm

This paper proposes an algorithm for detecting current transformer (CT) saturation by analyzing a secondary current. The current has points of inflection where saturation begins and ends. Then, discontinuity in the first difference of the current arises at the next instants of points of inflection, where the second and third differences of the current may have large values enough to detect saturation. In this paper, the third difference is used because it is more effective than the second difference in terms of saturation detection. However, an anti-aliasing low-pass filter softens the current and, thus, reduces the values of the third difference at those instants. This paper includes the effect of a low-pass filter on the proposed algorithm. The sampling rate of 64 samples/cycle (s/c) is studied by varying a remanent flux and the cutoff frequency of the filter. The test results clearly indicate that the proposed algorithm successfully detects the interval of saturation even with a remanent flux and the softening effect. However, special attention should be paid to the decision of the threshold value when a cutoff frequency is much lower than half the sampling frequency. This paper concludes by implementing the algorithm into a TMS320C6701 digital signal processor and the results are satisfactory.     

Preliminary tests for the application of an optical measurement system for the development of a kiln-drying schedule

The drying defects of refractory species are known to begin occurring in the early stages of kiln drying. Therefore, monitoring the strain distribution in wood at these early stages of drying is expected to be helpful for the reduction of possible defect development. In this study, the strain distribution of red oak specimens was progressively monitored on the tangential surface of the wood using an optical measurement system based on the digital image correlation (DIC) principle. The specimens were kiln-dried with three different initial conditions. The strain distribution maps obtained at various moisture contents clearly illustrated the progress of the strain development in the wood. In addition, strain velocities and strain ratios were calculated from the data extracted from the strain distribution maps. These parameters could be used for developing or modifying a kiln-drying schedule of a refractory species.     

A SIFT features based blind watermarking for DIBR 3D images

Depth image based rendering (DIBR) is a promising technique for extending viewpoints with a monoscopic center image and its associated per-pixel depth map. With its numerous advantages including low-cost bandwidth, 2D-to-3D compatibility and adjustment of depth condition, DIBR has received much attention in the 3D research community. In the case of a DIBR-based broadcasting system, a malicious adversary can illegally distribute both a center view and synthesized virtual views as 2D and 3D content, respectively. To deal with the issue of copyright protection for DIBR 3D Images, we propose a scale invariant feature transform (SIFT) features based blind watermarking algorithm. To design the proposed method robust against synchronization attacks from DIBR operation, we exploited the parameters of the SIFT features: the location, scale and orientation. Because the DIBR operation is a type of translation transform, the proposed method uses high similarity between the SIFT parameters extracted from a synthesized virtual view and center view images. To enhance the capacity and security, we propose an orientation of keypoints based watermark pattern selection method. In addition, we use the spread spectrum technique for watermark embedding and perceptual masking taking into consideration the imperceptibility. Finally, the effectiveness of the presented method was experimentally verified by comparing with other previous schemes. The experimental results show that the proposed method is robust against synchronization attacks from DIBR operation. Furthermore, the proposed method is robust against signal distortions and typical attacks from geometric distortions such as translation and cropping.     

Conceptual foundations of a landmark personality scale based on a destination personality scale: Text mining of online reviews

Landmarks play an important role in representing tourist destinations because they symbolize a destination’s image and personality. Despite the significance of landmarks to the perception of a destination’s image and personality, a personality scale based on landmarks has not been developed. To this end, the purpose of this study is to propose a conceptual foundation of a landscape personality scale based on a destination personality scale using online travel reviews, which are regarded as more valid sources for understanding actual tourist perceptions than simple answers to survey questionnaires. The results of this study imply that the words that describe specific landmarks may differ from those that portray the entire destination and suggest that the words tourists actually use in real situations to characterize tourism resources can be distinguished from hypothetical words of a destination personality scale. Finally, the theoretical and practical implications of the research and directions for future studies are discussed.