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This paper presents an innovative cross-coupled differential drive rectifier for dual-band Radio frequency identification (RFID) tags. A self-compensating rectifier with enhanced power-conversion efficiency (PCE) at low and high RF power is proposed. The proposed rectifier utilizes a self-compensating circuit, the extra two cross-couple transistors, to increase the gate voltage of transistors to control the conduction of the rectifying transistors. In order to adapt high frequency (HF) and ultrahigh frequency (UHF) rectification, the matching circuit is designed with parasitic cancellation technology. Moreover, the cascading power management circuits are added to generate a stable output voltage. The multi-standard rectifier is designed and simulated in 0. 1 8 μ m CMOS process. The simulated result shows that the proposed three-stage rectifier achieves a PCE 74% (at 5 0 0 k Ω load) when receiving a 915 MHz signal with average power of − 2 5 dBm. Moreover, the maximum efficiency achieves 56% at HF 13.56 MHz, and the final output voltage can be stabilized at a specific voltage of 1.052 V. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive Particle Swarm Optimization(APSO) global search algorithm and Spiking Neural Network(SNN) surrogate model-based optimization design method for analog integrated circuits performance enhancement. The initial design parameters are calculated by numerical computation. The global design space is extended and explored using APSO in the main loop, with constraint testing ensuring the transistor works in the right conditions. A Spiking Neural Network (SNN) model aids in predicting circuit performance during local searches, in which training data for the local design space is generated through parallel SPICE simulations. The optimization framework is applied to rail-to-rail amplifiers of two topologies. The results show that the proposed method accelerates the optimization process, achieving up to a 35.4x speed enhancement compared to Particle Swarm Optimization(PSO) based on the SPICE simulation. Moreover, Compared with traditional approaches based on multiobjective optimization, the proposed method provides an advantage in performance improvement and is valid for different CMOS processes. [ABSTRACT FROM AUTHOR]

In this work, we study the convergence behavior, as α → 2 , of the invariant probability measures of stochastic Burgers equations driven by two kinds of cylindrical α -stable processes (i.e., cylindrical subordinated Brownian motions and subordinated cylindrical Brownian motions) on torus. We prove that the invariant probability measures of stochastic Burgers equations driven by cylindrical subordinated Brownian motions or subordinated cylindrical Brownian motions converge to the invariant probability measure of stochastic Burgers equations forced by cylindrical Brownian motions in Wasserstein distance. This result shows a connection between stochastic dynamical systems with non-Gaussian noises and stochastic dynamical systems with Gaussian noises. [ABSTRACT FROM AUTHOR]

This paper is intended to establish the connection between stochastic dynamical systems with non-Gaussian noises and stochastic dynamical systems with Gaussian noises, by considering the convergence behavior of invariant probability measures for stochastic real Ginzburg-Landau equation driven by cylindrical α -stable Lévy process, in the limit α → 2. Indeed, we prove that the invariant measure of stochastic real Ginzburg-Landau equation on torus and driven by cylindrical α -stable Lévy processes converges to the invariant measure of stochastic real Ginzburg-Landau equation forced by cylindrical Brownian motions under the Wasserstein distance, as α tends to 2. We state our strategy as below. First, by using an abstract result given by Hairer and Mattingly, we prove that a type of Wasserstein distance is contracting for the dual operator of Markov semigroup associated with the limit equation which forced by Brownian motions. Then, through server priori uniform moment estimates and a convergence result on stochastic convolutions of cylindrical subordinated Brownian motions, we establish a strong convergence result on the solution of stochastic real Ginzburg-Landau equation driven by cylindrical subordinated Brownian motions conditioned on the initial data is distributed as an invariant measure, in the limit α → 2. Finally, by the Monge-Kantorovich duality, we prove that the invariant probability measure of stochastic real Ginzburg-Landau equation driven by cylindrical α -stable Lévy processes converges to the invariant measure of stochastic real Ginzburg-Landau equation forced by Brownian motions under the Wasserstein distance. [ABSTRACT FROM AUTHOR]

Mesh denoising is a critical technology in geometry processing that aims to recover high-fidelity 3D mesh models of objects from noise-corrupted versions. In this work, we propose a learning-based mesh normal denoising scheme, called NormalNet, which employs deep networks to find the correlation between the volumetric representation and denoised face normal. Overall, NormalNet follows the iterative framework of filtering-based mesh denoising. During each iteration, firstly, a local partition normalization strategy is applied to split the local structure around each face into dense voxels, in which both the structure and face normal information can be preserved during this transformation. Benefiting from the thorough information preservation, we can use simple residual networks, which employ the volumetric representation as the input and produce the learned denoised face normal, to achieve satisfactory results. Finally, the vertex positions are updated according to the denoised normals. Besides introducing normalization into mesh denoising, our main contributions include a classification-based training faces selection strategy for balancing the training set and a mismatched-faces rejection strategy for removing the mismatched faces between noisy mesh and ground truth. Compared to state-of-the-art works, NormalNet can effectively remove noise while preserving the original features and avoiding pseudo-features. [ABSTRACT FROM AUTHOR]

The goal of this work is to compare the invariant manifold of the stochastic evolution equation driven by an α-stable process with the invariant manifold of the stochastic evolution equation forced by Brownian motion. First, we show that the solution of the Marcus stochastic evolution equation driven by a type of α-stable process converges to the solution of the related Stratonovich stochastic evolution equation forced by Brownian motion. Then, we study the invariant stable manifold of the stochastic evolution equation driven by an α-stable process. Finally, we prove that the invariant stable manifold of the Marcus stochastic evolution equation driven by an α-stable process converges in probability to the invariant stable manifold of the Stratonovich stochastic evolution equation forced by Brownian motion. The connection between the random dynamical system driven by non-Gaussian noise and the random dynamical system driven by Gaussian noise is established. [ABSTRACT FROM AUTHOR]

Images captured in low lighting environment suffer from both low luminance contrast and noise corruption. However, most existing contrast enhancement algorithms only consider contrast boosting, which tends to reveal or amplify noise that is originally not visible in the dark areas. In this paper, we propose a joint contrast enhancement and denoising algorithm, which is based on structure/texture layer decomposition via minimization of dual forms of graph total variation (GTV). Specifically, the structure layer is expected to be generally smoothing but with sharp edges at the foreground background boundaries, for which we propose a quadratic form of GTV (QGTV) as the prior that promotes signal smoothness along graph structure. For the texture layer, a re-weighted GTV (RGTV) is tailored to noise removal while preserving true image details. We provide theoretical analysis about the filtering behavior of these two priors. Furthermore, a boost factor is derived per patch via optimal contrast-tone mapping to improve the overall brightness level of the patch. Finally, an optimization objective function is formulated, which casts image decomposition, brightness boosting, and noise reduction into a unified optimization framework. We further propose a fast approach to efficiently solve the optimization and provide analysis about the convergency. The experimental results show that the proposed method outperforms the state-of-the-art works in subjective, objective, and statistical quality evaluation. [ABSTRACT FROM AUTHOR]

Gaze mismatch is a common problem in video conferencing, where the viewpoint captured by a camera (usually located above or below a display monitor) is not aligned with the gaze direction of the human subject, who typically looks at his counterpart in the center of the screen. This means that the two parties cannot converse eye-to-eye, hampering the visual communication experience. A recent popular approach to the gaze mismatch problem is to synthesize a gaze-corrected face image as viewed from the screen center via depth-image-based rendering (DIBR), assuming texture and depth maps are both available at the camera-captured viewpoint. Due to self-occlusion, however, there will be missing pixels in the DIBR-synthesized view image that require satisfactory filling. In this paper, we propose to jointly solve the hole-filling problem and the face beautification problem (subtle modifications of facial components and contour to enhance attractiveness of the rendered face) using dual sparsity prior. Specifically, prior to the start of a video conference session, we first train two dictionaries separately offline using two large data sets: one with general face images, and the other with “beautiful” human faces, which means faces with high beauty scores. During the actual conference session, we solve the hole-filling and facial components beautification problems simultaneously by seeking two code vectors—one is sparse in the first dictionary and explains the available DIBR-synthesized pixels, the other is sparse in the second dictionary and matches well with the first vector in terms of feature space distance. This ensures an acceptable level of recognizability of the conference subject, while increasing proximity to “beautiful” facial features to improve attractiveness. Experimental results show naturally rendered human faces with noticeably improved attractiveness. [ABSTRACT FROM AUTHOR]

We employed Fourier transform variable angle infrared spectroscopic ellipsometry (IRSE) in wavelength range of 2–30 μm to investigate a group of silicon wafers, which are implanted with high doses and annealed in high temperature. The IRSE spectra for samples with different implantation doses were analyzed physically. When the semiconductor is heavily doped, it becomes degenerated and the doped impurities cannot ionize completely. For the analysis of the IRSE data, we quantitated the ionization probability as a function of impurity concentration in the optical model to describe the carrier concentration profile, by which the impurity concentration and carrier concentration profiles can be determined simultaneously. [ABSTRACT FROM AUTHOR]

The photocarrier radiometry (PCR) responses of heavily implanted silicon wafers (As+ ion 1×1013–1×1016 cm-2) were reported. The experimental dependence of the PCR amplitude on the implant dose was in good agreement with the theoretical prediction calculated with a three-layer PCR model, in which the implanted silicon wafer was assumed to be consisted of an amorphous, a polycrystalline, and a single-crystalline Si layer. The structural, optical, and transport properties of all layers used in the calculations were determined experimentally with spectroscopic ellipsometry (SE), spectrophotometry, and laterally resolved modulated free-carrier absorption to minimize the uncertainties of the theoretical calculations. The dose dependence of the PCR amplitude showed a nonmonotonicity at high dose implantation, as confirmed by the SE measurements. [ABSTRACT FROM AUTHOR]

Digital microfluidics, with a distinctive manner of droplet actuation via electrowetting on individually addressable electrodes, has made tremendous scientific and technical advances in the last twenty years or so. Its unique advantages in reduced sample consumption, programmability and reconfigurability, ease for intelligent recognition and closed-loop control on compartmentalized liquid samples, and simplicity in integrating with other technologies, offer preciseness and flexibility in discrete biological and chemical sample handling, which bring in promising application opportunities to life science studies. Meeting the growing demands in biological and biochemical applications, this accurate liquid-handling platform now moves into a stage of high-level integration and instrumentation, highlighted by miniaturization and full functionalization. In this paper, we start with a comprehension of mechanisms related to DMF technology from which novel functions of DMF devices were derived, and from a technical perspective, we provide an in-depth review of recent developments in the DMF community on new approaches in DMF chip fabrication, control and automation of DMF manipulation and system integration, instrumentation, and applications. • A thorough understanding of the mechanisms related to the actuation and hydrodynamic paved a strong foundation for solutions on reliable manipulation and interestingly extended functions of DMF chips. • Novelties reported in fabrication and assembly methods of DMF devices allowed for low-cost and reusable but free from cross-contamination chips and highly accessible ways of production. Among these, PCB and flexible substrates, as well as reusable covers, will be attractive in manufacturing DMF chips. • To realize a closed-loop control, real-time detection by impedance or machine vision was proposed, and new schemes and algorithms were realized with close to perfect completion in the literature. Furthermore, for promoting the throughput of DMF systems, the active matrix of switch arrays has been established in reports and will be of great help to developing high-end instruments. • Towards building up functionalized DMF instruments for POC diagnosis, on-chip and system-level integrations were highlighted in this review. [ABSTRACT FROM AUTHOR]

Depth information is being widely used in many real-world applications. However, due to the limitation of depth sensing technology, the captured depth map in practice usually has much lower resolution than that of color image counterpart. In this paper, we propose to combine the internal smoothness prior and external gradient consistency constraint in graph domain for depth super-resolution. On one hand, a new graph Laplacian regularizer is proposed to preserve the inherent piecewise smooth characteristic of depth, which has desirable filtering properties. A specific weight matrix of the respect graph is defined to make full use of information of both depth and the corresponding guidance image. On the other hand, inspired by an observation that the gradient of depth is small except at edge separating regions, we introduce a graph gradient consistency constraint to enforce that the graph gradient of depth is close to the thresholded gradient of guidance. We reinterpret the gradient thresholding model as variational optimization with sparsity constraint. In this way, we remedy the problem of structure discrepancy between depth and guidance. Finally, the internal and external regularizations are casted into a unified optimization framework, which can be efficiently addressed by ADMM. Experimental results demonstrate that our method outperforms the state-of-the-art with respect to both objective and subjective quality evaluations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel depth restoration algorithm from RGB-D data through combining characteristics of local and non-local manifolds, which provide low-dimensional parameterizations of the local and non-local geometry of depth maps. Specifically, on the one hand, a local manifold model is defined to favor local neighboring relationship of pixels in depth, according to which, manifold regularization is introduced to promote smoothing along the manifold structure. On the other hand, the non-local characteristics of the patch-based manifold can be used to build highly data-adaptive orthogonal bases to extract elongated image patterns, accounting for self-similar structures in the manifold. We further define a manifold thresholding operator in 3D adaptive orthogonal spectral bases—eigenvectors of the discrete Laplacian of local and non-local manifolds—to retain only low graph frequencies for depth maps restoration. Finally, we propose a unified alternating direction method of multipliers optimization framework, which elegantly casts the adaptive manifold regularization and thresholding jointly to regularize the inverse problem of depth maps recovery. Experimental results demonstrate that our method achieves superior performance compared with the state-of-the-art works with respect to both objective and subjective quality evaluations. [ABSTRACT FROM AUTHOR]

Highlights • FBG geophone with acceleration limit is designed for weak signal detection. • Environmental tests verify its reliability as oil & gas industry product. • FBG geophone shows higher SNR compared to conventional moving-coil geophone. • Seismic cross-section profiles were obtained by FBG geophone array in field tests. Abstract A fiber Bragg grating (FBG) based geophone is designed for low-frequency signal detection. It has high acceleration response of about 60 dB re pm/g in a low frequency range of 5–60 Hz. However, the basic sensing principle of stretching FBG requires much more delicate and reliable packaging design and technology. Especially the high sensitivity at low frequency challenges the reliability in packaging, transportation and installation of sensor. To guarantee normal operation in field test and practical application, an acceleration amplitude restriction is added in the mechanical design of the FBG geophone. Then a series of environmental and reliability tests have been proceeded with online or offline monitoring of its working performance, including high & low temperature test, vibration test, shock test and tensile test, strictly according to National standard and Oil & Gas Industry Standard. The experimental results indicate that our FBG geophone meet the criterion of oil and gas industry product and is capable of field application. Finally, in the filed blasting tests, the seismic cross-section profile was obtained by use of FBG geophone array which shows the advantage in low frequency signal acquisition compared to conventional move-coil geophone. [ABSTRACT FROM AUTHOR]

Wong–Zakai type approximation for stochastic partial differential equations (abbreviate as PDEs) is well studied. Besides the polygonal approximation, a type of smooth noise approximation is considered. After showing the existence of random attractor for a class of random partial differential equations defined on the entire space ℝ n , when random color noises tend to white noise, the solutions and invariant sets between original stochastic PDEs and random PDEs are compared. Some continuity results of random attractor in random dynamical systems are indicated. [ABSTRACT FROM AUTHOR]

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors—sparsity prior and graph-signal smoothness prior—for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB). [ABSTRACT FROM AUTHOR]

The resonance Raman spectrum of the β-methylallyl (2-methyl-allyl) radical is detected with excitation from 223 nm to 243 nm. The first observation of four fundamentals, the symmetric CH2 rock, the symmetric CCC stretch, the C–CH3 stretch, and the CCC bend, as well as an overtone, the symmetric CH2 twist of the β-methylallyl radical are reported. The assignments of the resonance Raman spectra are based upon the previous force field calculation, and comparisons with molecules having similar characteristic vibrations. Results from the resonance Raman spectra are compared with frequencies obtained by infrared spectroscopy using matrix isolation and our previous work on the allyl radical. © 1996 American Institute of Physics. [ABSTRACT FROM AUTHOR]

Resonance Raman spectra of the allyl-d5 radical have been obtained with excitation between 247 and 223 nm. Analysis of the spectra yields the first observation of fundamental frequencies, ν4, ν5, and ν7 and overtone frequencies 2ν9, 2ν10, and 2ν12. The new vibrational data are combined with previously observed frequencies of allyl-h5 and allyl-d5 radical to produce the force field analysis for the allyl radical. This study suggests reassignment of several previously observed infrared (IR) bands. Experimental frequencies and assignments for allyl-h5 and allyl-d5 are compared with results from ab initio calculations. Force constants obtained in the present work are compared with the force constants of other sp2 hybridization molecules such as benzene, allene, and ethylene. [ABSTRACT FROM AUTHOR]

A set of molecular parameters describing both the X and A states of CH3S, has been obtained by a joint fitting of the rotationally resolved electronic transitions observed in a free-jet-cooled laser-induced fluorescence study of CH3S and an earlier microwave study of its X state. The present work shows that because of incomplete information, nearly all of the previously reported molecular parameters for CH3S must be significantly revised. The present observations show an unusual electronic structure for the radical, characterized by a short C–S bond distance and peculiar methyl group geometry in the ground state. The C–S bond is observed to lengthen markedly in the excited A state. [ABSTRACT FROM AUTHOR]

This paper deals with the limit distribution for a stochastic differential equation driven by a non-symmetric cylindrical α -stable process. Under suitable conditions, it is proved that the solution of this equation converges weakly to that of a stochastic differential equation driven by a Brownian motion in the Skorohod space as α → 2. Also, the rate of weak convergence, which depends on 2 − α , for the solution towards the solution of the limit equation is obtained. For illustration, the results are applied to a simple one-dimensional stochastic differential equation, which implies the rate of weak convergence is optimal. [ABSTRACT FROM AUTHOR]

Electrical properties of graphene transparent conductive film under visible light irradiation are investigated. The CVD-grown graphene on Polyethylene Terephthalate (PET) and glass substrates for flexible and rigid touch screen display application are chosen for research. The resistances of graphene with and without gold trichloride (AuCl 3 ) doping are measured in vacuum and atmosphere environment under blue light irradiation. Results show that the conductivities of all samples change slowly under light irradiation. The change rate and degree are related to the substrate material, doping, environment and lighting power. Graphene on flexible PET substrate is more stable than that on rigid glass substrate. Doping can improve the electrical conductivity but induce instability under light irradiation. Finally, the main reason resulting in the graphene resistance slowly increasing under blue light irradiation is analyzed. [ABSTRACT FROM AUTHOR]

We use the method of smooth approximation to examine the random attractor for two classes of stochastic partial differential equations (SPDEs). Roughly speaking, we perturb the SPDEs by a Wong-Zakai scheme using smooth colored noise approximation rather than the usual polygonal approximation. After establishing the existence of the random attractor of the perturbed system, we prove that when the colored noise tends to the white noise, the random attractor of the perturbed system with colored noise converges to that of the original SPDEs by invoking some continuity results on attractors in random dynamical systems. [ABSTRACT FROM AUTHOR]

Taking advantage of an extremely high theoretical capacity of 4200 mAh g −1 , silicon has been considered one of the most promising anode materials for lithium ion batteries. Nevertheless, it also has many challenging issues, such as large volume expansion, poor electrical conductivity and the formation of unstable solid electrolyte interphase layers. To address these challenges, much effort has been directed towards developing new strategies, such as designing novel nanosilicon and hybridizing with other functional materials. This paper is dedicated to identifying the current state-of-the-art fabrication methods of nanosilicon, including ball milling, chemical vapor deposition, metal-assisted chemical etching and magnesiothermic reduction, as well as the design principles and the selection criteria for fabricating high performance Si nanostructures. The critical factors determining the electrical conductivity, structural stability and active material content are elucidated as important criteria for designing Si-based composites. The structural evolution and reaction mechanisms of nanosilicon electrodes studied by in situ experiments are discussed, offering new insights into how advanced Si electrodes can be designed. Emerging applications of Si electrodes in other rechargeable batteries, such as Li-S, Li-O 2 and Na-ion batteries are also summarized. The challenges encountered for future development of reliable Si electrodes for real-world applications are proposed. [ABSTRACT FROM AUTHOR]

It is crucial to reveal the dent deformation mechanism of the sandwich pipe (SP) for the dent evaluation of damaged offshore SPs. This study aimed to explore the difference in dent characteristics between sandwich pipes' inner and outer tubes subjected to lateral loads. Quasi-static lateral denting tests are carried out to investigate the denting resistance and the indentation characteristics of SPs with the ends fixed. The finite element method is used to simulate the development of SP dent in the installation, operation, and shutdown stages. The dent depth and dent strain of the inner and outer tubes are examined and compared. Parametric studies are performed to clarify the influence of material properties, geometric configuration, and interlayer friction on the difference in dent characteristics between the inner and outer tubes. The research demonstrates that the relative difference in dent characteristics between the inner tube and the outer tube is closely related to the hollow ratio, thickness-to-radius ratio, material steel grade of the inner tube and the outer tube, and the interaction between the layers. The findings show that the current dent evaluation criteria need to be improved to provide practical dent evaluation for the dented SPs. • The inner tube dent depth ratio is generally lager than the outer tube. • The dent strain of the outer tube is much higher than that of the inner tube. • Geometric parameters are the most crucial factors affecting the dent characteristics. • The current dent evaluation criteria needs to be improved for sandwich pipes. [ABSTRACT FROM AUTHOR]

Given the prevalence of joint photographic experts group (JPEG) compressed images, optimizing image reconstruction from the compressed format remains an important problem. Instead of simply reconstructing a pixel block from the centers of indexed discrete cosine transform (DCT) coefficient quantization bins (hard decoding), soft decoding reconstructs a block by selecting appropriate coefficient values within the indexed bins with the help of signal priors. The challenge thus lies in how to define suitable priors and apply them effectively. In this paper, we combine three image priors—Laplacian prior for DCT coefficients, sparsity prior, and graph-signal smoothness prior for image patches—to construct an efficient JPEG soft decoding algorithm. Specifically, we first use the Laplacian prior to compute a minimum mean square error initial solution for each code block. Next, we show that while the sparsity prior can reduce block artifacts, limiting the size of the overcomplete dictionary (to lower computation) would lead to poor recovery of high DCT frequencies. To alleviate this problem, we design a new graph-signal smoothness prior (desired signal has mainly low graph frequencies) based on the left eigenvectors of the random walk graph Laplacian matrix (LERaG). Compared with the previous graph-signal smoothness priors, LERaG has desirable image filtering properties with low computation overhead. We demonstrate how LERaG can facilitate recovery of high DCT frequencies of a piecewise smooth signal via an interpretation of low graph frequency components as relaxed solutions to normalized cut in spectral clustering. Finally, we construct a soft decoding algorithm using the three signal priors with appropriate prior weights. Experimental results show that our proposal outperforms the state-of-the-art soft decoding algorithms in both objective and subjective evaluations noticeably. [ABSTRACT FROM AUTHOR]

Hierarchical-structured copper sulfide nanoneedles were grown on multi-walled carbon nanotube backbone (denoted as CuS@CNT) as electrodes for supercapacitors via a facile template-based hydrothermal conversion approach and further by simply impregnating sulfur into CuS@CNT (S@CuS@CNT) as electrodes for Li-S batteries. The electrochemical measurements showed that the resultant CuS@CNT composite electrodes deliver outstanding electrochemical performance with a specific capacitance up to 566.4 F g and cyclic stability of 94.5 % of its initial capacitance after 5000 cycles at a current density of 1 A g. A synergistic effect arising from the unique hierarchical structure was responsible for the electrode performance, including a large surface area of 49.3 m g and active CuS ultrafine nanoneedles firmly bonded to the highly conductive carbon nanotube (CNT) backbone. When used as an electrode material for Li-S batteries, the S@CuS@CNT (S content 59 wt%) exhibited satisfying electrochemical performance. The S@CuS@CNT electrode showed that coulombic efficiency was close to 100 % and capacity maintained more than 500 mA h g with progressive cycling up to more than 100 cycles even at a high current density. This strategy of stabilizing S with a small amount of copper sulfide nanoneedles can be a very promising method to prepare free-standing cathode material for high-performance Li-S batteries. The fabrication strategy presented here is low cost, facile, and scalable, which can be considered as a promising material for large-scale energy storage device. In particular, the use of CNT as backbone for the growth of active materials presents many potential merits owing to its lightweight, biodegradable, and stretchable characteristics. [ABSTRACT FROM AUTHOR]

Digital microfluidics (DMF), facilitating independent manipulation of microliter samples, provides an ideal platform for immunoassay detection; however, suffering limited multiplexity. To address the need, herein we described a digital microfluidics (DMF) platform that realizes spatial barcoding on the Teflon-coated indium tin oxide (ITO) glass side to fulfill highly multiplexed immunoassay (10+) with low-volume samples (∼4 μL) in parallel, representing the highest multiplexing recorded to date for DMF-actuated immunoassay. Planar-based spatial immobilization of multiple capture antibodies was realized on a Teflon-coated ITO glass side, which was then used as the top plate of the DMF device. Droplets containing analytes, secondary antibodies, and fluorescent signaling reporters with low volume, which were electrically manipulated by our DMF control system, were shuttled sequentially along the working electrodes to complete the immuno-reaction. Evaluation of platform performance with recombinant proteins showed excellent sensitivity and reproducibility. To test the feasibility of our platform in analyzing multiplex biomarkers of the immune response, we used lipopolysaccharide-stimulated macrophages as a model system for protein secretion dynamics studies. As a result, temporal profiling of pro-inflammatory cytokine secretion dynamics was obtained. The spatial barcoding strategy presented here is easy-to-operate to enable a more comprehensive evaluation of protein abundance from biological samples, paving the way for new opportunities to realize multiplexity-associated applications with the DMF platform. [ABSTRACT FROM AUTHOR]

A facile co-precipitation and annealing method for the growth of porous CoMn 2 O 4 microspheres is presented. Serving as a supercapacitor electrode, the CoMn 2 O 4 microsphere possesses a remarkable specific capacitance (788 F g −1 at the current density of 1 A g −1 ), which hold great promise for use as electrochemical energy storage. [ABSTRACT FROM AUTHOR]

Dynamic compact thermal model plays important roles in predicting the junction temperature and characterizing the transient thermal behavior of an electronic device. In this paper, analytical dynamic compact thermal model for high power LEDs is established based on the three-directional heat flow paths under junction-to-ambient definition. Comparative results with finite element method model indicate that the presented model is accurate and efficient. It is further reduced by analyzing the influence of different components of the LED package. Good agreement with experimental results confirms that the reduced analytical model can predict the junction temperature and characterize the thermal behavior effectively. [ABSTRACT FROM AUTHOR]

The performance and reliability of the high-power light-emitting diodes (HP LEDs) are closely related to the quality of the die attach adhesive (DAA) layer, because voids or delaminations in the layer may cause higher junction temperature, and even result in the break of the chip. In this paper, a dynamic compact thermal model is constructed for an independent HP LED without being attached on a cold plate. The time-constant spectrum method based on the thermal model is applied to characterize the transient thermal behavior of the DAA layer and other layers along the heat flow path. Thermal transient experiments are carried on HP LED samples with different DAA dosages. The theoretical and experimental results demonstrate that the time-constant spectrum for LEDs tested without cold plate can reflect the thermal characteristics of the DAA layer as well as that with cold plate. Differences in the HP LED samples with different DAA layers can be obviously distinguished in the time-constant spectrums as well. Compared with the traditional testing method with cold plate, direct test in air for HP LEDs has the advantages of easy operation, time saving, and no pollution to samples. [ABSTRACT FROM AUTHOR]

In this paper, an effective low bit-rate video coding scheme is developed to realize state-of-the-art video coding efficiency with lower encoder complexity, while supporting standard compliance and error resilience. Such an architecture is particularly attractive for application scenarios involving resource-deficient wireless video communications. At the encoder, in order to increase resilience to channel error, multiple descriptions of a video sequence are generated in the spatio-temporal domain by temporal multiplexing and spatial adaptive downsampling. The resulting side descriptions are interleaved with each other in temporal domain, while still with conventional square sample grids in spatial domain. As such, each side description can be compressed without any change to existing video coding standards. At the decoder, each side description is first decompressed, and then reconstructed to the original resolution with the help of the other side description. In this procedure, the decoder recovers the original video sequence in a constrained least squares regression process, in which 2D or 3D piecewise autoregressive model is adaptively chosen according to different predictive modes. In this way, the spatial and temporal correlation is sufficiently explored to achieve superior quality. Experimental results demonstrate that the proposed video coding scheme outperforms H.264/AVC and other state-of-the-art methods in rate–distortion performance at low bit-rates and achieves superior visual quality at medium bit rates as well, while with lower encoding computational complexity. [ABSTRACT FROM AUTHOR]

A new method based on Bayesian deconvolution is proposed for multiexponential transient signal analysis. The multiexponential signal is initially converted to a convolution model using logarithmic and differential transformation after which the Bayesian iteration is used to deconvolve the data. The numerical simulation is applied on four different multiexponential signals with different levels of noise. Thermal transient experiment data of the high power light emitting diodes are also analyzed using the proposed method. Simulation and experimental results indicate that the present method performs efficiently in accurately estimating the decay rates except at low SNR case. [ABSTRACT FROM AUTHOR]

Multi-focus image fusion (MFF) is an effective way to eliminate the out-of-focus blur generated in the imaging process. The difficulties in distinguishing different blur levels and the lack of real supervised data make multi-focus image fusion remain a challenging task after decades of research. According to deep image prior (DIP) (Ulyanov et al., 2018), a neural network itself can capture the low-level statistics of a single image and is successfully used as a prior for solving many inverse problems without the need for handmade priors or priors learned from large-scale datasets. Motivated by this idea, we propose a novel multi-focus image fusion framework named ZMFF comprised of a deep image prior network to model the deep prior of the fused image and a deep mask prior network to model the deep prior of the focus map corresponding to each source image. Without the labor-intensive training pair collection, our method achieves zero-shot learning and avoids the domain shifting problem due to the inconsistency between the manually degraded multi-focus images and the real ones. As far as we know, it is the first unsupervised and untrained deep model for the MFF task. Extensive experiments on both synthetic and real-world datasets demonstrate the promising performance, generalization and flexibility of our approach. Source code is available at https://github.com/junjun-jiang/ZMFF. • It proposes the first zero-shot methods for multi-focus image fusion. • It successfully mines the deep priors of clear fused image and the corresponding focus maps. • It could avoid the labor-intensive data collection and domain shifting while achieving competitive results. [ABSTRACT FROM AUTHOR]

Digital microfluidics is a plausible platform for manipulation of discrete droplets, which are driven by electrowetting and dielectrophoretic forces. Increasing the sustainability of DMF chips while reducing their fabrication cost would be attractive to research on droplet-based micro-actuators. Here, we report a new robust composite layer, with which a broad range of its operation voltage of DMF chips was demonstrated, covering from 30 V, which was 25 V below the theoretical value predicted with scaling model that derived from d / ɛ , to at least 350 V with a minimum dispensing voltage at 100 V. Also, a lifetime of at least 5000 continuous cycles at 110 volts was achieved. Deposition of such a composite layer was solely accomplished with a low-cost spincoater, instead of expensive vapour deposition instruments. And the materials we used were cheap as well. The electromechanical force, which was expressed in separate terms of electrowetting force and dielectrophoretic force on a droplet, in six chips with different values of d / ɛ were calculated and compared. The result from our calculation showed that, differently from low- d / ɛ DMF chips, there was considerable electrowetting factor among the electromechanical force in the high- d / ɛ DMF chips and it may be the cause that the initial apparent actuation voltage was much lower than theoretical threshold actuation voltage. [ABSTRACT FROM AUTHOR]

Exp Ther Med 20:Article no. 261, 2020; DOI: 10.3892/etm.2020.9391 Following the publication of the above article, the authors have realized that they inadvertently included data derived from the same original source for the invasion and migration assay Vector control experiments shown for the HCT116 cells in Fig. (D) Quantification of the effect of lncRNA-ATB overexpression on HCT116 cell migration and invasion assay. [Extracted from the article]

In this paper, we propose a novel image interpolation algorithm via graph-based Bayesian label propagation. The basic idea is to first create a graph with known and unknown pixels as vertices and with edge weights encoding the similarity between vertices, then the problem of interpolation converts to how to effectively propagate the label information from known points to unknown ones. This process can be posed as a Bayesian inference, in which we try to combine the principles of local adaptation and global consistency to obtain accurate and robust estimation. Specially, our algorithm first constructs a set of local interpolation models, which predict the intensity labels of all image samples, and a loss term will be minimized to keep the predicted labels of the available low-resolution (LR) samples sufficiently close to the original ones. Then, all of the losses evaluated in local neighborhoods are accumulated together to measure the global consistency on all samples. Moreover, a graph-Laplacian-based manifold regularization term is incorporated to penalize the global smoothness of intensity labels, such smoothing can alleviate the insufficient training of the local models and make them more robust. Finally, we construct a unified objective function to combine together the global loss of the locally linear regression, square error of prediction bias on the available LR samples, and the manifold regularization term. It can be solved with a closed-form solution as a convex optimization problem. Experimental results demonstrate that the proposed method achieves competitive performance with the state-of-the-art image interpolation algorithms. [ABSTRACT FROM AUTHOR]

It is experimentally observed that the photocarrier radiometry (PCR) signals of silicon wafers are greatly enhanced by ion implantation and thermal annealing. A two-layer theoretical model is employed to analyze the experimental observation in detail. Theoretical simulations indicate that the increased optical-to-electronic quantum efficiency of the implanted layer could be the main photoluminescence mechanism contributing to the PCR signal enhancement. The decreased surface recombination velocity induced by surface electric field and the change of electronic transport properties of the implanted layer also contribute to the signal enhancement. [ABSTRACT FROM AUTHOR]

The dissociation of H2 and its isotopologues through excitation to the singlet ungerade continua is one of the major channels for the production of slow hydrogen atoms at high temperature (T > 10 000 K) and electron energy >25 eV. State-specific photodissociation cross sections and oscillator strengths for molecular deuterium from the X 1&Sgr;g+ (vi, Ji) levels to the continuum levels of the B 1&Sgr;u+, C 1&Pgr;, B" ¯B 1&Sgr;+u, D' 1&Pgr;u and 5pq 1&Sgr;+u 1&Sgr;+u states have been calculated. The corresponding (vi, Ji) state-specific electron impact dissociation cross sections have been obtained for the first time over a wide energy range using calculated continuum oscillator strengths along with previously published excitation functions of the Lyman and Werner bands. Estimated cross sections to the higher (n ⩾ 5) npσ 1&Sgr;+u and npπ 1&Pgr;u continua are also provided. Both photon and electron impact excitation cross sections show strong dependences on the initial (vi, Ji) quantum numbers. Thermally averaged electron impact cross sections of all singlet ungerade states increase monotonically with temperature. While excitation to the B 1&Sgr;+u continuum is the dominant dissociation channel at room temperature, the C 1&Pgr;u and B 1&Sgr;+u continua become more important at high temperature (>5000 K). The large increase of the C 1&Pgr;u and B 1&Sgr;+u cross sections with (vi, Ji) is primarily responsible for making the continuum dissociation from a minor break-up channel at room temperature into a major one at high temperature. The electron dissociation cross section of D2 via the singlet ungerade continua is smaller than its H2 counterpart, although this difference decreases with temperature. This work, along with the previous calculations of H2 by Liu et al (2009, 2012), provides the complete electron impact dissociation cross sections of H2 and D2 through the singlet ungerade continua. Thermally averaged electron dissociation cross sections are provided at various temperatures for applications in plasma physics. [ABSTRACT FROM AUTHOR]

State-to-state [X1Σ+g (vj) → X 2Σ+g (vj )] and quasi state-specific [X 1Σ+g (vj, Ji) → X 2Σ+g (vj )] photon and electron-impact ionization cross sections of hydrogen and deuterium molecules have been obtained with a combined analysis of experimental measurement and theoretical calculations. Rotation state ionization transitions are considered using the p-partial wave approximation. Previously calculated photoionization transition moments are refined and extended to ∼300 eV using accurate experimental photoionization cross sections. The transition moments are used to obtain the photoionization cross sections and oscillator strengths for the H2 and D2 X 1Σ+g (vj, Ji) →H+2 and D+2 X 2Σ+g (vj, Jj ) transitions. The calculated ionization oscillator strengths, together with excitation functions derived from electron-impact ionization measurements of H2, enable accurate determination of electron-impact ionization cross sections for both H2 and D2 transitions to (vj, Jj) levels of the X2Σ+g state at energies ranging from threshold to the non-relativistic limit. The autoionizing singlet-ungerade states contribute at least 0.6-1% of the total e+H2 →+2 cross section. The e+D2 →D+2 and e+H2 →H+2 cross sections are very similar above the threshold energy region. The D2 cross section is ∼1.6% larger than the H2 cross section. Thermally averaged nondissociative ionization cross sections of H2 and D2 at temperatures appropriate for plasma and planetary applications have been tabulated. [ABSTRACT FROM AUTHOR]

The linear regression model is a very attractive tool to design effective image interpolation schemes. Some regression-based image interpolation algorithms have been proposed in the literature, in which the objective functions are optimized by ordinary least squares (OLS). However, it is shown that interpolation with OLS may have some undesirable properties from a robustness point of view: even small amounts of outliers can dramatically affect the estimates. To address these issues, in this paper we propose a novel image interpolation algorithm based on regularized local linear regression (RLLR). Starting with the linear regression model where we replace the OLS error norm with the moving least squares (MLS) error norm leads to a robust estimator of local image structure. To keep the solution stable and avoid overfitting, we incorporate the \ell_2-norm as the estimator complexity penalty. Moreover, motivated by recent progress on manifold-based semi-supervised learning, we explicitly consider the intrinsic manifold structure by making use of both measured and unmeasured data points. Specifically, our framework incorporates the geometric structure of the marginal probability distribution induced by unmeasured samples as an additional local smoothness preserving constraint. The optimal model parameters can be obtained with a closed-form solution by solving a convex optimization problem. Experimental results on benchmark test images demonstrate that the proposed method achieves very competitive performance with the state-of-the-art interpolation algorithms, especially in image edge structure preservation. [ABSTRACT FROM AUTHOR]

Using Damour-Ruffini method, Hawking radiation from the apparent horizon of a Vaidya black hole is calculated. The thermodynamics can be built successfully on the apparent horizon. In the meantime, when a time-dependent perturbation is given to the apparent horizon, the first law of thermodynamics can also be constructed successfully at a new supersurface near the apparent horizon. The expressions of the characteristic position and temperature are consistent with the previous results. It is concluded that the thermodynamics should be constructed on the apparent horizon exactly while the event horizon thermodynamics is just one of the perturbations near the apparent horizon. These conclusions can be regarded as providing some new evidences for our previous viewpoint. [ABSTRACT FROM AUTHOR]

Abstract: Dynamical systems driven by Gaussian noises have been considered extensively in modeling, simulation and theory. However, complex systems in engineering and science are often subject to non-Gaussian fluctuations or uncertainties. A coupled dynamical system under non-Gaussian Lévy noise is considered. After discussing cocycle property, stationary orbits and random attractors, a synchronization phenomenon is shown to occur, when the drift terms of the coupled system satisfy certain dissipativity conditions. The synchronization result implies that coupled dynamical systems share a dynamical feature in certain asymptotic sense. [ABSTRACT FROM AUTHOR]

Based on the black hole tunneling mechanism in which the ingoing particles should be absorbed absolutely, Hamilton-Jacobi method is modified to investigate Hawking radiation from a Schwarzschild black hole once again. The results are independent on the coordinates and the standard Hawking temperature is obtained without the factor of 2 problem. Moreover, it is also pointed out that the modified Hamilton-Jacobi method can be applied to investigate Hawking radiation from the general horizons in dynamical spacetimes. [ABSTRACT FROM AUTHOR]

Abstract: Uniform, vertically aligned multiwalled carbon nanotube arrays (VACNTs) were grown on glassy carbon-like thin films by thermal chemical vapour deposition (CVD). Thin (5nm) aluminum and iron catalyst layers were pre-deposited by evaporation on the carbon substrates and VACNTs were grown at 750°C by water-assisted CVD using ethylene as the carbon source. The aluminum layer was shown to be essential for aligned nanotube growth. VACNT arrays adhered strongly to the carbon film with low contact resistance between the VACNTs and the substrate. The VACNT arrays grown directly on the planar conducting carbon substrate have attractive properties for use as electrodes. Excellent voltammetric characteristics are demonstrated after insulating the arrays with a dielectric material. [Copyright &y& Elsevier]

Using the Damour–Ruffini method, Hawking radiation from a four-dimensional charged rotating black string in asymptotically anti-de Sitter space–time is investigated. When energy, angular momentum, charge conservations, and the particles’ back-reaction to the space–time are taken into account, the exact emission spectrum near the horizon is calculated. The horizon is not spherical, but can be toroidal and cylindrical. Our results indicate that the spectrum is not purely thermal, which may be consistent with an underlying unitary theory. Moreover, it is a possible mechanism to explain the information loss paradox. [ABSTRACT FROM AUTHOR]

Abstract: A prototype device was made to scale up a method for the wet purification of multiwalled carbon nanotubes (MWCNTs). The device consists of a fluid-flow chamber, which facilitates the flow of MWCNT suspensions across a large array of interdigitated electrodes (IDEs). A radio-frequency voltage provides the electric field for dielectrophoresis. Electric parameters of the array were monitored during the running of the process and were observed to reflect the increase of conductance caused by accumulation of MWCNTs. SEM and Raman spectroscopy showed a decrease in the D-band to G-band ratio for the material accumulated on the array. [Copyright &y& Elsevier]

CVD-grown multi-walled carbon nanotubes (CNTs) in suspension were aligned and collected by an AC electric field developed within an inter-digitated electrode structure. The increases of conductance and capacitance were observed and monitored by dielectric spectroscopy and attributed to the accumulations of CNTs. Comparisons of the capacitance and conductance changes of aligned CNTs in different solvents were made. Among these, CNTs in distilled water showed the greatest increases in both conductance and capacitance. As the field is switched on or off, the conductance and capacitance of the CNTs show substantial reversible changes superimposed on the underlying increasing trend. [Copyright &y& Elsevier]

High spatial resolution and high spectral resolution images (HR-HSIs) are widely applied in geosciences, medical diagnosis, and beyond. However, how to get images with both high spatial resolution and high spectral resolution is still a problem to be solved. In this paper, we present a deep spatial-spectral feature interaction network (SSFIN) for reconstructing an HR-HSI from a low-resolution multispectral image (LR-MSI), e.g., RGB image. In particular, we introduce two auxiliary tasks, i.e., spatial super-resolution (SR) and spectral SR to help the network recover the HR-HSI better. Since higher spatial resolution can provide more detailed information about image texture and structure, and richer spectrum can provide more attribute information, we propose a spatial-spectral feature interaction block (SSFIB) to make the spatial SR task and the spectral SR task benefit each other. Therefore, we can make full use of the rich spatial and spectral information extracted from the spatial SR task and spectral SR task, respectively. Moreover, we use a weight decay strategy (for the spatial and spectral SR tasks) to train the SSFIN, so that the model can gradually shift attention from the auxiliary tasks to the primary task. Both quantitative and visual results on three widely used HSI datasets demonstrate that the proposed method achieves a considerable gain compared to other state-of-the-art methods. Source code is available at https://github.com/junjun-jiang/SSFIN. [ABSTRACT FROM AUTHOR]