Effects of edge disorder on the stability of quantum oscillations in two-dimensional coupled systems.

This paper utilizes the theory of quantum diffusion to analyze the electron probability and spreading width of a wavepacket on each layer in a two-dimensional (2D) coupled system with edge disorder, aiming to clarify the effects of edge disorder on the stability of the electron periodic oscillations in 2D coupled systems. Using coupled 2D square lattices with edge disorder as an example, we show that, the electron probability and wavepacket spreading width exhibit periodic oscillations and damped oscillations, respectively, before and after the wavepacket reaches the boundary. Furthermore, these electron oscillations exhibit strong resistance against disorder perturbation with a longer decay time in the regime of large disorder, due to the combined influences of ordered and disordered site energies in the central and edge regions. Finally, we numerically verified the universality of the results through bilayer graphene, demonstrating that this anomalous quantum oscillatory behavior is independent of lattice geometry. Our findings are helpful in designing relevant quantum devices and understanding the influence of edge disorder on the stability of electron periodic oscillations in 2D coupled systems.

TCF-Trans: Temporal Context Fusion Transformer for Anomaly Detection in Time Series.

Anomaly detection tasks involving time-series signal processing have been important research topics for decades. In many real-world anomaly detection applications, no specific distributions fit the data, and the characteristics of anomalies are different. Under these circumstances, the detection algorithm requires excellent learning ability of the data features. Transformers, which apply the self-attention mechanism, have shown outstanding performances in modelling long-range dependencies. Although Transformer based models have good prediction performance, they may be influenced by noise and ignore some unusual details, which are significant for anomaly detection. In this paper, a novel temporal context fusion framework: Temporal Context Fusion Transformer (TCF-Trans), is proposed for anomaly detection tasks with applications to time series. The original feature transmitting structure in the decoder of Informer is replaced with the proposed feature fusion decoder to fully utilise the features extracted from shallow and deep decoder layers. This strategy prevents the decoder from missing unusual anomaly details while maintaining robustness from noises inside the data. Besides, we propose the temporal context fusion module to adaptively fuse the generated auxiliary predictions. Extensive experiments on public and collected transportation datasets validate that the proposed framework is effective for anomaly detection in time series. Additionally, the ablation study and a series of parameter sensitivity experiments show that the proposed method maintains high performance under various experimental settings.

Unreferenced English articles' translation quality-oriented automatic evaluation technology using sparse autoencoder under the background of deep learning.

Currently, both manual and automatic evaluation technology can evaluate the translation quality of unreferenced English articles, playing a particular role in detecting translation results. Still, their deficiency is the lack of a close or noticeable relationship between evaluation time and evaluation theory. Thereupon, to realize the automatic Translation Quality Assessment (TQA) of unreferenced English articles, this paper proposes an automatic TQA model based on Sparse AutoEncoder (SAE) under the background of Deep Learning (DL). Meanwhile, the DL-based information extraction method employs AutoEncoder (AE) in the bilingual words' unsupervised learning stage to reconstruct the translation language vector features. Then, it imports the translation information of unreferenced English articles into Bilingual words and optimizes the extraction effect of language vector features. Meantime, the translation language vector feature is introduced into the automatic DL-based TQA. The experimental findings corroborate that when the number of sentences increases, the number of actual translation errors and the evaluation scores of the proposed model increase, but the Bilingual Evaluation Understudy (BLEU) score is not significantly affected. When the number of sentences increases from 1,000 to 6,000, the BLEU increases from 96 to 98, which shows that the proposed model has good performance. Finally, the proposed model can realize the high-precision TQA of unreferenced English articles.

Multistage Spatio-Temporal Networks for Robust Sketch Recognition.

Sketch recognition relies on two types of information, namely, spatial contexts like the local structures in images and temporal contexts like the orders of strokes. Existing methods usually adopt convolutional neural networks (CNNs) to model spatial contexts, and recurrent neural networks (RNNs) for temporal contexts. However, most of them combine spatial and temporal features with late fusion or single-stage transformation, which is prone to losing the informative details in sketches. To tackle this problem, we propose a novel framework that aims at the multi-stage interactions and refinements of spatial and temporal features. Specifically, given a sketch represented by a stroke array, we first generate a temporal-enriched image (TEI), which is a pseudo-color image retaining the temporal order of strokes, to overcome the difficulty of CNNs in leveraging temporal information. We then construct a dual-branch network, in which a CNN branch and a RNN branch are adopted to process the stroke array and the TEI respectively. In the early stages of our network, considering the limited ability of RNNs in capturing spatial structures, we utilize multiple enhancement modules to enhance the stroke features with the TEI features. While in the last stage of our network, we propose a spatio-temporal enhancement module that refines stroke features and TEI features in a joint feature space. Furthermore, a bidirectional temporal-compatible unit that adaptively merges features in opposite temporal orders, is proposed to help RNNs tackle abrupt strokes. Comprehensive experimental results on QuickDraw and TU-Berlin demonstrate that the proposed method is a robust and efficient solution for sketch recognition.

Fast 3D Modeling of Prosthetic Robotic Hands Based on a Multi-Layer Deformable Design.

Current research of designing prosthetic robotic hands mainly focuses on improving their functionality by devising new mechanical structures and actuation systems. Most of existing work relies on a single structure/system (e.g., bone-only or tissue-only) and ignores the fact that the human hand is composed of multiple functional structures (e.g., skin, bones, muscles, and tendons). This may increase the difficulty of the design process and lower the flexibility of the fabricated hand. To tackle this problem, this paper proposes a three-dimensional (3D) printable multi-layer design that models the hand with the layers of skin, tissues, and bones. The proposed design first obtains the 3D surface model of a target hand via 3D scanning, and then generates the 3D bone models from the surface model based on a fast template matching method. To overcome the disadvantage of the rigid bone layer in deformation, the tissue layer is introduced and represented by a concentric tube-based structure, of which the deformability can be explicitly controlled by a parameter. The experimental results show that the proposed design outperforms previous designs remarkably. With the proposed design, prosthetic robotic hands can be produced quickly with low cost and be customizable and deformable.

Joint Feature Optimization and Fusion for Compressed Action Recognition.

Recent methods including CoViAR and DMC-Net provide a new paradigm for action recognition since they are directly targeted at compressed videos (e.g., MPEG4 files). It avoids the cumbersome decoding procedure of traditional methods, and leverages the pre-encoded motion vectors and residuals in compressed videos to complete recognition efficiently. However, motion vectors and residuals are noisy, sparse and highly correlated information, which cannot be effectively exploited by plain and separated networks. To tackle these issues, we propose a joint feature optimization and fusion framework that better utilizes motion vectors and residuals in the following three aspects. (i) We model the feature optimization problem as a reconstruction process that represents features by a set of bases, and propose a joint feature optimization module that extracts bases in the both modalities. (ii) A low-rank non-local attention module, which combines the non-local operation with the low-rank constraint, is proposed to tackle the noise and sparsity problem during the feature reconstruction process. (iii) A lightweight feature fusion module and a self-adaptive knowledge distillation method are introduced, which use motion vectors and residuals to generate predictions similar to those from networks with optical flows. With these proposed components embedded in a baseline network, the proposed network not only achieves the state-of-the-art performance on HMDB-51 and UCF-101, but also maintains its advantage in computational complexity.

Design of a Single-Material Complex Structure Anthropomorphic Robotic Hand.

In the field of robotic hand design, soft body and anthropomorphic design are two trends with a promising future. Designing soft body anthropomorphic robotic hands with human-like grasping ability, but with a simple and reliable structure, is a challenge that still has not been not fully solved. In this paper, we present an anatomically correct robotic hand 3D model that aims to realize the human hand's functionality using a single type of 3D-printable material. Our robotic hand 3D model is combined with bones, ligaments, tendons, pulley systems, and tissue. We also describe the fabrication method to rapidly produce our robotic hand in 3D printing, wherein all parts are made by elastic 50 A (shore durometer) resin. In the experimental section, we show that our robotic hand has a similar motion range to a human hand with substantial grasping strength and compare it with the latest other designs of anthropomorphic robotic hands. Our new design greatly reduces the fabrication cost and assembly time. Compared with other robotic hand designs, we think our robotic hand may induce a new approach to the design and production of robotic hands as well as other related mechanical structures.

Simultaneous realization of electromagnetically induced transparency and electromagnetically induced reflectance in a metasurface.

The analogue of electromagnetically induced transparency (EIT-like) and electromagnetically induced reflectance (EIR-like) effects have been intensively studied and achieved by using metasurfaces. Nevertheless, previous designs could realize only one of them and were unable to support both effects in a metasurface. Here we numerically and experimentally demonstrate a metasurface simultaneously exhibiting EIT-like and EIR-like effects. Qualitative analyses and quantitative calculations based on the electromagnetic multipole decomposition method are performed to reveal their formation mechanisms. Our work offers a simple avenue for simultaneously realizing EIT-like and EIR-like effects in a metasurface, which may find potential applications in sensing, filtering, and slow wave devices.

Application of convolutional neural network on early human embryo segmentation during in vitro fertilization.

Selection of the best quality embryo is the key for a faithful implantation in in vitro fertilization (IVF) practice. However, the process of evaluating numerous images captured by time-lapse imaging (TLI) system is time-consuming and some important features cannot be recognized by naked eyes. Convolutional neural network (CNN) is used in medical imaging yet in IVF. The study aims to apply CNN on day-one human embryo TLI. We first presented CNN algorithm for day-one human embryo segmentation on three distinct features: zona pellucida (ZP), cytoplasm and pronucleus (PN). We tested the CNN performance compared side-by-side with manual labelling by clinical embryologist, then measured the segmented day-one human embryo parameters and compared them with literature reported values. The precisions of segmentation were that cytoplasm over 97%, PN over 84% and ZP around 80%. For the morphometrics data of cytoplasm, ZP and PN, the results were comparable with those reported in literatures, which showed high reproducibility and consistency. The CNN system provides fast and stable analytical outcome to improve work efficiency in IVF setting. To conclude, our CNN system is potential to be applied in practice for day-one human embryo segmentation as a robust tool with high precision, reproducibility and speed.

A Macromolecular Drug for Cancer Therapy via Extracellular Calcification.

Cancer chemotherapy typically relies on drug endocytosis and inhibits tumor cell proliferation via intracellular pathways; however, severe side effects may arise. In this study, we performed a first attempt to develop macromolecular-induced extracellular chemotherapy involving biomineralization by absorbing calcium from the blood through a new type of drug, polysialic acid conjugated with folate (folate-polySia), which selectively induces biogenic mineral formation on tumor cells and results in the pathological calcification of tumors. The macromolecule-initiated extracellular calcification causes cancer cell death mainly by intervening with the glycolysis process in cancer cells. Systemic administration of folate-polySia inhibited cervical and breast tumor growth and dramatically improved survival rates in mice. This study provides an extracellular therapeutic approach for malignant tumor diseases via calcification that is ready for clinical trials and offers new insights into macromolecular anticancer drug discovery.

Optical rotation and electromagnetically induced transparency in a chiral metamaterial with C4 symmetry.

We design and fabricate a double-layered chiral metamaterial with 4-fold rotational symmetry, which simultaneously exhibits optical rotation and electromagnetically induced transparency (EIT) effects. Using analytical equivalent circuit model and Lorentz's coupled oscillator model, we interpret the physical mechanisms and derive material equations. Importantly, we find that magnetic dipole and electric quadrupole play important roles in optical rotation and keeping the symmetry of the material equations. Our work offers a better understanding of optical rotation in chiral metamaterials, and provides a new and simple approach to combine optical rotation and EIT effects into a single metamaterial.

Mechanism and performance analyses of optical beam splitters using all-dielectric oligomer-based metasurfaces.

Compact and planar optical beam splitters are highly desirable in various optical and photonic applications. Here, we investigate two kinds of optical beam splitters by using oligomer-based metasurfaces, one is trimer-based metasurface for 3-dB beam splitting, and the other is pentamer-based metasurface for 1:4 beam splitting. Through electromagnetic multipole decomposition and in-depth mechanism analyses, we reveal that the electromagnetic multipolar interactions and the strong near-field coupling between neighboring nanoparticles play critical roles in beam-splitting performance. Our work offers a deeper understanding of electromagnetic coupling effect in oligomer-based metasurfaces, and provides an alternative approach to planar beam splitters.

Dual-band asymmetric optical transmission of both linearly and circularly polarized waves using bilayer coupled complementary chiral metasurface.

It is highly desirable to develop asymmetric transmission (AT) devices for both linearly and circularly polarized light. However, currently existing metamaterial-based AT devices require multi-step micro-nano fabrication processes and usually realize AT responses only for linearly or circularly polarized waves, not simultaneously for both. We here propose a dual-band AT device for both linearly and circularly polarized waves in the near-infrared region by using a bilayer coupled complementary chiral metasurface, which includes a half-gammadion-shape gold (Au) structural layer and its Babinet's complimentary copy. Unlike other multilayer AT devices working at optical frequencies, it takes less micro-nano fabrication steps. Besides, with the help of chirality and the inherent near-field coupling effect between the two complementary Au layers, the maximal AT parameters for linearly and circularly polarized waves can reach up to 0.45 and 0.56, respectively. The underlying mechanisms of dual-band AT responses are also investigated in depth from the perspectives of chirality and coupling effect. Our work offers a new and simple approach to high-performance AT devices, helps to better understand near-filed coupling effect in coupled complementary metasurfaces, and also expands their application fields.

High-performance asymmetric optical transmission based on coupled complementary subwavelength gratings.

Asymmetric transmission (AT) devices are fundamental elements for optical computing and information processing. We here propose an AT device consisting of a pair of coupled complementary subwavelength gratings. Different from previous works, asymmetric dielectric environment is employed for unidirectional excitation of surface plasmon polaritons (SPPs) and thus asymmetric optical transmission, and near-field coupling effect inherent in the coupled complementary structure is exploited to enhance forward transmission and AT behavior, and determine operation bandwidth as well. The influence of asymmetric dielectric environment, effect of vertical and lateral couplings, interactions of electric- and magnetic-dipole moments and the realization of Kerker conditions, are investigated in depth to unearth the AT mechanism and performance. High-performance AT with large forward transmittance of 0.96 and broad bandwidth of 174 nm is achieved at wavelength 1250 nm. Our work helps people to gain a better understanding of near-filed coupling effect in coupled complementary structures, expand their application fields, and it also offers an alternate way to high-performance AT devices.

Narrow-band and high-contrast asymmetric transmission based on metal-metal-metal asymmetric gratings.

A narrow-band and high-contrast asymmetric transmission (AT) device based on metal-metal-metal (M-M-M) asymmetric grating structure is proposed and investigated. Significantly distinct from previous reports, the upper and lower metallic silver (Ag) gratings are connected by a very thin metallic Ag film, without any dielectric spacer layer or subwavelength slit. Under forward incidence, the M-M-M structure supports efficient surface plasmon polaritons (SPPs) excitation and tunneling, more importantly, it promotes direct and thus high-efficiency SPPs decoupling, enabling high forward transmittance. While under backward incidence, the M-M-M structure offers not only high reflection by the Ag film but also a strong near-field coupling effect between the upper and lower gratings, which further suppresses backward transmittance, leading to near-zero backward transmittance. In addition, the M-M-M structure is optimized for narrow-band operation by employing grating groove depth effect and multiple interference effect. Numerical simulation results demonstrate that high-performance AT with high-quality factor (Q≈91), narrow-bandwidth (6.7 nm) and high contrast ratio is achieved, with forward transmittance of 0.72 and backward transmittance of 0.0015 at visible light (610 nm). Our work provides an alternative and simple way to high-performance AT devices.

One-Pot Three-Component Synthesis of Enamine-Functionalized 1,2,3-Triazoles via Cu-Catalytic Azide-Alkyne Click (CuAAC) and Cu-Catalyzed Vinyl Nitrene Transfer Sequence.

A number of enamine-functionalized 1,2,3-triazole derivatives have been prepared via the Cu-catalyzed three-component reaction of terminal alkyne, azide, and 2H-azirine. The reaction proceeds through insertion of vinyl nitrene into the C-Cu bond of the triazolyl-Cu species, providing an efficient and step- and atom-economic approach to the enamine-bearing polysubstituted 1,2,3-triazoles. The resulting triazoles were easily transformed to trisubstituted pyrazoles in the presence of a Rh catalyst.

[Determination of arsenic, antimony, mercury and selenium in different parts of Acanthopanax senticosus harms by atomic fluorescence spectrometry].

A method for the determination of arsenic, antimony, mercury and selenium in different parts (root, stem, leaf and fruit) of acanthopanax senticosus harms using hydride generation atomic fluorescence spectrometry with microwave digestion was developed. Under the optimized experimental conditions, the concentration of arsenic, antimony, mercury and selenium showed a linear relationship with the fluorescence intensity. The detection limit of arsenic was 0.068 ng x mL(-1), and the RSD was 1.05%. The detection limit of antimony was 0.155 ng x mL(-1), and the RSD was 1.32%. The detection limit of mercury was 0.014 ng x mL(-1), and the RSD was 2.03%. The detection limit of selenium was 0.052 ng x mL(-1), and the RSD was 2.34%. The method was checked in terms of accuracy and precision using the standard reference substance of hair (GBW07601), and proved to be sensitive and rapid with satisfactory results. The content of arsenic, mercury and selenium is high in the leaf, and that of antimony is higher in the root than in other parts.

[Determination of trace mercury in different sorts of Chinese herbs by atomic fluorescence spectrometry with microwave digestion].

A method for the determination of trace mercury in different sorts of Chinese herbs using hydride generation atomic fluorescence spectrometry under different microwave digestion conditions was developed. Under the optimized experimental conditions, the linear equation was I(F) = 809.1 x -3.327 5, the correlation coefficient was 0.999 998,and the linear range for mercury was 0-80 ng x mL(-1). The detection limit of mercury was 0.014 ng x mL(-1) (n = 11) and the relative standard deviation was 2.03%. The recoveries for these samples were 96.8%-102.80% (n = 6) while the detection limit of the method was 1.17 ng x g(-1). The method's accuracy and precision for different sorts of Chinese herbs using the standard reference standard substance of rice (GBW08508), poplar leaf (GBW07601), and mytilus edulis (GBW08571) was checked, and the results were found to be basically consistent with the reference values. This method has been proved to be sensitive, simple and rapid with satisfactory results.

Bandpass filters based on phase-shifted photonic crystal waveguide gratings.

In this paper, a bandpass transmission filter realized in phase-shifted waveguide gratings based on photonic crystals (PCs) is proposed. Phase-shift regions each composed of one period of photonic crystal (PC) waveguide are incorporated into PC waveguide gratings. The magnitudes of the phase-shifts are modified by involving small changes in the size of the border rods in the phase-shift regions. Using standard coupled-mode theory and finite-difference time-domain (FDTD) method, we show that by properly choosing the magnitudes of phase-shifts and the lengths of waveguide gratings, a flat-top and sharp roll-off response with a narrow bandwidth is theoretically and numerically achieved by the designed filter. A further analysis shows that the center frequency of the transmission band can be changed by altering the magnitude of the phase-shift and the response performance exhibits relaxed sensitivity to the phase-shift variation. As a specific application, we theoretically demonstrate a third-order Chebyshev bandpass filter based on compound phase-shifted PC waveguide gratings. The filter performance is suitable for dense wavelength-division-multiplexed (DWDM) optical communication systems with a channel spacing of 100-GHz.