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In this article, the problem of H∞ codesign for nonlinear control systems with unmatched uncertainties and adjustable parameters is investigated. The main purpose is to solve the adjustable parameters and H∞ controller simultaneously so that better robust control performance can be achieved. By introducing a bounded function and defining a special cost function, the problem of solving the Hamilton-Jacobi-Isaacs equation is transformed into an optimization problem with nonlinear inequality constraints. Based on the sum of squares technique, a novel policy iteration algorithm is proposed to solve the problem of the H∞ codesign. Moreover, one modified algorithm for optimizing the robust performance index is given. The convergence and the performance improvement of new iteration policy algorithms are proved. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

This research concerns a novel attitude stabilization structure for a ducted-fan aerial robot to work against modeling error and strong external transient disturbance, and it focuses on two main control targets: modeling error compensation, and the improvement of disturbance resistance along the rolling channel. For the first research objective, we proposed an adaptive nominal controller with the reconfigurable control law design based on the estimation of the modeling error found in the closed-loop. Results of simulations and corresponding flight tests verified that the proposed adaptive control structure is robust against both constant and time-varying modeling error. For the other research objective, a SAC (Stability Augmentation Control) structure was devised based on the CMG (Control Moment Gyroscope) theory in order to provide extra moment which effectively withstands the transient disturbance beyond the CDG (Critical Disturbance Gain). Furthermore, we studied the corresponding controller for the SAC via the SMC (sliding mode control) theory, while the working mechanism and performance of the SAC were verified through a specially devised prototype.

The influence of surface roughness on the interfacial dynamic recrystallization kinetics and mechanical properties of Ti-6Al-3Nb-2Zr-1Mo hot-compression bonding joints was systematically investigated. It is found that for the bonding interface of rough surfaces, elongated fine grains are formed at the bonding interface due to shear deformation of the interfacial area. As the surface roughness increases, the proportion of elongated grains drastically decreases as they further reorient to form equiaxed grains along the bonding interface of rougher surfaces resulting from severe incompatible deformation of the interface area. Meanwhile, high-density geometrically necessary dislocations accumulate around the interfacial recrystallization area to accommodate the incompatible strain and lattice rotation. A rotational dynamic recrystallization mechanism is thereby proposed to rationalize the formation of fine interfacial recrystallization grains during bonding of rough surfaces. In contrast to that of rough surfaces, bonding interface of polished surfaces exists in the form of straight interface grain boundaries without fine grains under the same deformation conditions. While with the increase of deformation strain, small grain nuclei form along the bonding interface, which is associated with discontinuous dynamic recrystallization assisted by strain-induced boundary migration of interface grain boundaries. Moreover, the bonding joints of rough surfaces show lower elongation compared with that of polished surfaces. This is because the formation of heterogeneous fine grains with low Schmid factor along the bonding interface of rough surfaces, leading to worse compatible deformation capability and thereby poor ductility of bonding joints.

PetroChina’s Karamay heavy oil reservoirs mostly comprise Jurassic deposits of braided fluvial facies that have a low porosity, extremely high bitumen viscosity, and strong heterogeneities within the reservoir. Steam-assisted gravity drainage (SAGD) dilation start-up has been proven to be an efficient reservoir geomechanical stimulation method as it shortens the steam circulation time, reduces steam usage, and increases the oil production rates. This method worked well on relatively good-quality oil sand reservoirs. However, for reservoirs with heterogeneous reservoir properties along the SAGD well, field well production data indicated the presence of non-uniform steam chambers in post-dilation SAGD wells. Enhanced dilation methods, such as vertical well assisted SAGD dilation (VW-SAGD-Dilation) are have been used, and field pilot tests have yielded promising results. This reservoir stimulation process utilizes one or more vertical wells beside the SAGD well to initiate the formation of dilation zones that connect to the dilation zone formed during the conventional SAGD dilation start-up. Compared with the normal SAGD dilation start-up, this composite dilation process creates a uniform dilation zone along the SAGD well, thus improving the thermal conformance and well productivity. The vertical well and SAGD well are connected by this composite dilation zone, which enables the combined use of the SAGD process and cyclic steam stimulation process. This paper presents our understanding and numerical case studies of this enhanced dilation strategy. The well production data from the post-dilation wells were positive (uniform steam chamber growth and higher oil rate), which highlights the promising potential of using geomechanical dilation as a reservoir stimulation method to create a large stimulated reservoir volume in heterogeneous super-heavy oil reservoirs.

In 2020, the Regional Comprehensive Economic Partnership (RCEP) initiated by the Association of Southeast Asian Nations (ASEAN) was officially signed; the RCEP is the largest free trade agreement in the world. As both Vietnam and China are important member countries of this agreement, the close trade cooperation that exists between Vietnam and China has important economic and political implications, and its development has been further improved by the Belt and Road Initiative (BRI). The vast majority of this trade is done through intermodal container transport, so efficient multimodal container transport has become necessary to enable cross-border trade. With the rapid development of China’s transportation infrastructure, Chongqing has become an emerging logistics hub in inland China. Hai Phong is the largest port city in Vietnam, and it has extensive multimodal transport infrastructure. In this paper, we scientifically evaluate the competing routes for the multimodal container transport supporting China-Vietnam trade, analyse eight transport routes from Chongqing to Hai Phong, and evaluate these routes with the Delphi and CFPR methods. This study can inform Chinese and Vietnamese trade enterprises in terms of selecting their preferred multimodal transport route strategies and the governmental authorities of both countries in making management decisions.

Acetic acid acidolysis had so far been performed as a green technology to produce high value-added xylo-oligosaccharide from lignocellulosic residues while around 30% inert xylan-constitute is still retained. For improving economic and environmental benefits, a cascade temperature-arising technical strategy was designed and developed for the co-production of xylo-oligosaccharide and enzymatic-hydrolyzed glucose by a continuous two-step acidolysis mode with the recyclable acetic acid catalyst. The combined process was optimized by uniform design experiments and temperature plays the key factor for xylo-oligosaccharide yield and xylose-chemicals degradation. We obtained respectively 63.41% and 61.44% xylo-oligosaccharide yield from corncob and wheat straw during continuous two-step acidolysis with acetic acid recycling operation at 140 °C and 190 °C, which increased by 52.03% and 76.55% than the one-step process. Meanwhile, the corresponding enzymatic hydrolysis yield was increased to 100% and 98.2%. In short, the two-step cascade temperature-rising acidolysis technology can maximize the utilization of hemicellulose and cellulose constitutes and fully explore the value-added utilization of lignocellulosic biomass. The cascade temperature-arising technical strategy does therefore demonstrate something for the more efficient and green utilization of lignocellulosic biomass.

Object detection based on deep learning typically relies on a large number of training data, which may be very labor-consuming to prepare. In this paper, we attempt to tackle the problem by addressing the One-Shot Object Detection (OSOD) task. Given a novel image denoted as the query image whose category label is not included in the training data, OSOD aims to detect objects of the same class in a complex scene denoted as the target image. The performance of recent OSOD methods is much weaker than general object detection. We find that one of the reasons behind this limited performance is that more false positives (i.e., false detections) are generated. Therefore, we argue that it is important to reduce the number of false positives generated in OSOD task to improve performance. To this end, we present a Focus On Classification One-Shot Object Detection (FOC OSOD) network. Specifically, we design the network from two perspectives: (1) how to obtain the effective similarity feature between the query image and target image; (2) how to classify the similarity feature effectively. To solve the above two challenges, firstly, we propose a Classification Feature Deformation-and-Attention (CFDA) module to obtain the high-quality query feature and target feature, so we can further generate effective similarity feature between them. Secondly, we present a Split Iterative Head (SIH) to improve the ability to classify the similarity feature. Extensive experiments on two public datasets (i.e., PASCAL VOC and COCO) demonstrate that the proposed framework achieves superior performance which outperforms other state-of-the-art methods with a considerable margin.

The traditional pure switched-capacitor equalizer suffers from a large inrush current and low balance speed. An automatic parallel resonant switched-capacitor equalizer (PReSCE) for series-connected battery strings is proposed, which utilizes resonant switched-capacitor to eliminate the inrush current. The parallel ReSC converters not only minimizes output impedance at the low switching frequency, but delivers the excess energy to the low-voltage battery directly from the high-voltage battery in one cycle. Both of the two functions increase the balance speed. All of the switches are controlled by a pair of complementary pulsewidth modulation signals at a fixed operational frequency. Both simulation and experiment are used to verify the theoretical analysis and system feasibility of the proposed circuit. The results show that the PReSCE circuit eliminates the inrush current and increases the balance speed three times than the parallel pure switched-capacitor equalizer.

This study investigates the role of strong seismic motions on the dynamic responses of high CFRDs through elastoplastic analysis. Damage measures (DMs) including vertical and horizontal displacements, plastic shear strain, as well as a face-slab damage index are selected to gauge the deformation, stability of the dam slope and the anti-seepage ability of the face slab, respectively. The selected DMs are key to the safety of high CFRDs. A group of 35 as-recorded ground motions with a wide range of durations are modified to conform to a 5% damped target spectrum are used as input motions for dynamic analysis. A comprehensive understanding of the effects of ground motion duration is obtained through a tri-fold analysis of the ground motion records, the nonlinear dynamic response of CFRDs and the statistics of the results. The definitions of significant duration, bracketed duration and uniform duration, each with consideration to two different thresholds, are selected to characterize strong motion durations. The results suggests that significant duration is the most useful indicator for seismic assessment of high CFRDs and for evaluating the effects of the duration of an earthquake on the integrity of high CFRDs.

So far, many investigations have reported that Zr-based bulk metallic glasses (BMGs) could be precisely and flexibly shaped by electrical discharge machining (EDM). However, EDM induced crystallization and roughness is still a bottleneck. In this research, bench-mode electrochemical surface smoothing (ESS) in the NaCl-ethylene glycol (EG) electrolyte has been proposed to post-process the spark erosion treated Zr-based BMGs in order to solve the abovementioned problems. The utilization of the NaCl-EG electrolyte overcomes the difference in electrochemical dissolution mechanisms of multiple components contained in Zr-based BMGs. Taking a sort of Zr-based BMGs, Vit1 (Zr41.2Ti13.8Cu12.5Ni10.0Be22.5), as an example, voltammetry and chronoamperometry methods have been performed on the BMG surface before and after wire-EDM, respectively, in the NaCl-EG electrolyte to reveal the steady and transient electrochemical behaviors. In order to achieve high-efficiency and high-quality ESS of Zr-based BMGs, a 3D printed setup with lateral flushing has been developed, combined with the micron sized inter-electrode gap (IEG) and the pulse current. The surface morphologies after ESS have been compared to evaluate the effects of the initial surface morphologies, dwell time, and pulse parameters. The surface material properties and mechanical performance before and after ESS have also been investigated by EDS, XRD, XPS, and nanoindentation. The results suggests that the proposed ESS method is capable of quickly eliminating the crystalline layer induced by the thermal shock and reducing roughness caused by the discharge craters, which has been finally validated by fast ESS of two Zr-based BMG molds with ruled surfaces in the NaCl-EG solution.

Semi-solid metal forming processes cover a wide variety of technologies in manufacturing, generally leading to non-dendritic microstructures typified by rosette-like or spherical grains. With the contemporary experimental methods, researchers still cannot completely understand the formation of such microstructures. However, as a process coupled with dendritic growth, deformation and flow, the microstructural evolution during the semi-solid deformation has been scarcely simulated. With the vector-valued phase-field method, two-phase flow model and an innovative design of boundary conditions, the current research numerically compressed a single dendrite into a less dendritic polycrystalline structure. The resulting microstructure was consistent with the metallographic analysis and the simulation enables a clear observation of the whole process: the ripening transformed the highly branched shape into a less dendritic one; the subsequent deformation crushed the dendrite into a stubby structure; eventually, the deformation caused the boundaries inside this structure, dividing the solid into multiple grains. The analysis on the boundaries inside the deformed solid offered further insight into the formation of non-dendritic structures. These boundaries showed a tendency towards melting with increasing misorientation, demonstrating the possibility of the grain boundary wetting, which was considered as the source of the fragmentation when the dendrite undergoes deformation, but is hard to validate in situ even with the cutting-edge X-ray imaging technique.

Monthly Precipitation Forecasts (MPF) play a critical role in drought monitoring, hydrological forecasting and water resources management. In this study, we applied two advanced Machine Learning Models (MLM) and latest General Circulation Models (GCM) to generate deterministic MPFs with a resolution of 0.5° across China. Then the Bayesian Joint Probability (BJP) modeling approach is employed to calibrate and generate corresponding ensemble MPFs. Raw and post-processing MPFs were put against gridded observations over the period of 1981–2015. The results indicated that: (1) for deterministic evaluation, the forecasting performance of MLMs was more inclined to generate random forecasts around the mean value, while the GCMs could reflect the increasing or decreasing trend of precipitation to some degree; (2) for probabilistic evaluation, the four BJP calibrated ensemble MPFs were unbiased and reliable. Compared to climatology, reliability and sharpness were all significantly improved. However, in terms of overall accuracy metric, the ensemble MPFs generated from MLMs were similar to climatology. In contrast, the ensemble MPFs generated from GCMs achieved better forecasting skill and were not dependent on forecasting regions and months. Moreover, the post-processing method is necessary to achieve not only bias-free but also reliable as well as skillful ensemble MPFs. HIGHLIGHTS Two advanced Machine Learning Models are employed to generate monthly precipitation forecasts with a resolution of 0.5 degree.; The latest seasonal forecasts of ECMWF are evaluated with the same forecasting grid cells and lead time.; The BJP modeling approach is used to calibrate above four raw forecasts.; A comprehensive comparison is achieved for the raw and post-processing forecasts.

A new type of water-soluble coal dust suppressant (later called MA) with excellent performance was prepared by modified starch, styrene, methyl methacrylate, Butyl acrylate (as the main monomers) and acrylic acid (as the functional monomer) via mixed the emulsifiers of Sodium dodecyl sulfate (SDS)/octylphenol polyoxyethylene(10)ether (OP-10) and ammonium persulfate served as initiator. The properties of anti-wind erosion, water retention and coal quality impact were investigated. The MA was characterized by viscosity measurements and scanning electron microscopy. The results show that the spraying of MA has no effect on coal quality, and the water loss rate of MA is slightly lower than that of water, which has certain moisture retention. After spraying MA on the surface of coal sample for 120 hours, the coal sample is swept by six-stage wind (wind speed is 10.8-13.8 m/s), and the erosion rate is only 1.8%. The MA and coal samples are closely bonded to form a dense soft film, which has a excellent dust suppression effect.

The rapid development of hypersonic vehicles has motivated the related research dramatically while the evasion of the hypersonic vehicles becomes one of the challenging issues. Different from the work based on the premise that the pursuers’ information is fully known, in this paper the evasion guidance for air-breathing hypersonic vehicles (AHVs) against unknown pursuer dynamics is studied. The gradient descent is employed for parameter estimation of the unknown dynamics of the pursuer. The energy-optimized evasion guidance algorithm is further developed by taking the acceleration constraint and energy optimization into consideration. Under the proposed algorithm, the system can deal with the unknown pursuer dynamics effectively and provide more practical guidance for the evasion process. The simulation results show that the proposed method can enable the AHV to achieve successful evasion.

Welding properties of three alloys with different Cu contents (0.1, 0.4 and 0.9 wt.%) is studied by means of melt inert-gas welding (MIG). The results showed that, with the increase of Cu content from 0.1 wt.% to 0.9 wt.%, the strength and elongation increased obviously. When the Cu content was 0.9 wt.%, the strength and elongation reached 375MPa and 15%, respectively, which is a better match for bearing structure part of vehicles application. Besides, the adding of Cu element provided an increase limit for welding joint strength. Due to abundant coarse phases in fusion zone (FZ) and welding zone (WZ), the strength slightly increased and the failure fracture was different compared with that of 0.1Cu and 0.4Cu alloy. Present result was meaningful and valuable for pushing aluminum application automobile structural parts and other engineering components.

The main target of this paper is to design a density-based clustering algorithm using the weighted grid and information entropy based on MapReduce, noted as DBWGIE-MR, to deal with the problems of unreasonable division of data gridding, low accuracy of clustering results and low efficiency of parallelization in big data clustering algorithm based on density. This algorithm is implemented in three stages: data partitioning, local clustering, and global clustering. For each stage, we propose several strategies to improve the algorithm. In the first stage, based on the spatial distribution of data points, we propose an adaptive division strategy (ADG) to divide the grid adaptively. In the second stage, we design a weighted grid construction strategy (NE) which can strengthen the relevance between grids to improve the accuracy of clustering. Meanwhile, based on the weighted grid and information entropy, we design a density calculation strategy (WGIE) to calculate the density of the grid. And last, to improve the parallel efficiency, core clusters computing algorithm based on MapReduce (COMCORE-MR) are proposed to parallel compute the core clusters of the clustering algorithm. In the third stage, based on disjoint-set, we propose a core cluster merging algorithm (MECORE) to speed-up ratio the convergence of merged local clusters. Furthermore, based on MapReduce, a core clusters parallel merging algorithm (MECORE-MR) is proposed to get the clustering algorithm results faster, which improves the core clusters merging efficiency of the density-based clustering algorithm. We conduct the experiments on four synthetic clusters. Compared with H-DBSCAN, DBSCAN-MR and MR-VDBSCAN, the experimental results show that the DBWGIE-MR algorithm has higher stability and accuracy, and it takes less time in parallel clustering.

Many uncertainties exist in pile-stabilized slopes which make their design substantially complicated. In this paper, a first-order reliability method (FORM) based on a support vector machine (SVM) and uniform design (UD) is proposed to investigate the reliability of a pile-stabilized slope. A deterministic model considering soil-pile interaction and using a strength reduction method based on the displacement criterion is employed to calculate the factor of safety and the corresponding pile-bending moment. The uncertainties involved in both the soil and the stabilizing pile are taken into consideration in the proposed method. Two typical failure modes, namely the insufficient factor of safety of a pile-stabilized slope and the insufficient flexural bearing capacity of stabilizing piles, are investigated from a probabilistic viewpoint. The proposed method is illustrated with an artificial homogeneous slope and a real slope engineering case. The influence of stabilizing pile installation locations on the reliability results were studied. The sensitivity of random variability was also investigated. The results of the proposed method show high accuracy while having a smaller computational time requirement when compared with the polynomial response surface method. The case study of a real highway slope shows the feasibility of the proposed method applied to practical engineering problems.

This paper builds an integrated optimization model for the laminated plate to suppress the structural frequency response in a given frequency band, where the objective is to minimize the dynamic compliance of the structure excited by an external sinusoidal mechanical load with given amplitude and frequency range. The dynamic response analysis of the laminated structure is performed via a finite element model based on the first-order shear deformation theory. Therein, the Heaviside penalization of the discrete material optimization method and the solid isotropic material with penalization scheme are separately employed to optimize the fiber orientation and the layout of the damping material. Meanwhile, mode reduction method and a decoupled sensitivity analysis are incorporated for efficient frequency and sensitivity analysis to reduce the heavy computational burden from many frequency steps in each iteration, a large number of freedom degrees and plenty of design variables as well as maintain high accuracy. And the method of moving asymptotes is used to solve the optimization problem. And three numerical examples including the efficiency and accuracy demonstration, single load and multi-load case with separate and integrated optimization are presented to verify the validity and advantage of the proposed model.

Vertical retaining wall is usually built at the water intake in front of the pump station and is widely used in the protection of intake and voidance structures of nuclear power plants (NPPs). It has great practical significance for disaster prevention to gauge the plastic failure of vertical retaining wall accurately. In this paper, a generalized plastic model is introduced to obtain the residual deformation of vertical retaining wall during earthquake and the numerical simulation results based on plastic model reflect the plastic failure mode of the vertical retaining wall, which is consistent with the shaking table test results. In addition, the seismic excitation has great uncertainty, and in order to reflect the uncertainty, a set of fully nonstationary stochastic seismic loading samples are generated with spectral representation random function method. As a recently developed dynamic reliability methodology, the probability density evolution method (PDEM) is incorporated to the generalized plastic model to perform stochastic seismic response analysis of a vertical retaining wall. Plentiful probabilistic results of vertical retaining wall, such as evolution of probability density functions (PDF) and second-order statistics are acquired in this study. Finally, the dynamic reliability of vertical retaining wall under two earthquake levels are obtained based on the dip angle, which can more directly reflect the failure probability and degree of vertical retaining wall. The results of this study indicate that the geotechnical structures can show a more objective failure mode under earthquakes based on the plastic model, and it is more reliable to evaluate the safety of structures from the perspective of probability combined with PDEM.

In this study, flowback-assisted minifrac tests were conducted in low-permeability shale and salt formations to measure the in situ stress. An injection/flowback testing protocol was implemented in each test to achieve accuracy and efficiency. Accurate and efficient injection/flowback testing is very important, given the impermeable nature of these formations and the need to complete each test as quickly as possible. Each flowback cycle yields a distinct and repeatable fracture closure signature, simplifying the interpretation of the fracture closure pressure. The objective of this paper is to share our field experience and to present a numerical analysis of the flowback test pressure responses, fracture closure behaviors, and fracture closure diagnostic methods. Examples from open-hole and cased-hole minifrac tests are used to demonstrate site operation procedures. Then, two numerical models are presented for simulating the fracture closure behavior during a flowback test. Field evidence is provided to demonstrate that the fracture closure pressures from the flowback tests are identical to those from tests without flowback. The fracture closure diagnostic methods for flowback tests are discussed, and it is found that the G-function diagnostic method yields a distinct fracture closure signal during the flowback tests. This study is intended to provide additional insights regarding flowback tests by sharing our successes, experience, and knowledge, thereby benefiting the industry.

Reinforcement learning (RL) is gradually being implemented in the hybrid electric vehicle (HEV) supervisory control. Even though RL exhibits significant fuel consumption saving, the long learning time makes it hardly applicable in real-world vehicles. This study aims to reduce the learning iterations of Q-learning in HEV application utilizing warm-start methods. Different from previous studies, which initiated Q-learning with zero or random Q values, this study initiates the Q-learning with different supervisory controls, and the detailed analysis is given. The results show that the proposed warm-start Q-learning requires 68.8% fewer iterations than cold-start Q-learning and improves 10%–16% MPG compared with equivalent consumption minimization strategy control. The results of this study can be used to facilitate the deployment of RL in vehicle applications.

Lithium-sulfur (Li-S) batteries have great potential in next-generation energy storage due to its high theoretical specific capacity and energy density. However, there are several challenges to the practical application of Li-S batteries including the growth of lithium dendrites and the shuttle effect of polysulfide. Introducing interlayeres (freestanding or coated on the separator) is an effective approach to reduce these obstacles and improve the electrochemical performance of Li-S batteries. In this review, we briefly summarize the interlayer materials and structures modified on both cathodic and anodic sides including (i) carbon-based materials, (ii) polymers, (iii) inorganic metal compounds, (iv) metal–organic frameworks, as well as (v) the novel separators in recent years. We also systematically address the fabrication processes, assembling methods, and functions of interlayers for enhancing the performance of Li-S batteries. Furthermore, the prospects and outlooks of the future development of advanced interlayers and separators are also presented.

Non-dendritic microstructures are generally obtained in metals after semi-solid deformation (deformation during solidification); however, dendritic growth is preferred without deformation. The fragmentation of dendrites is recognized as an essential contributing factor to non-dendritic microstructures. However, the underlying mechanism of fragmentation needs to be clarified in depth. It is infamously hard for researchers to carry out a direct observation of this process. Moreover, a comprehensive numerical survey of this process is not trivial. The present research reported a new method to model dendritic growth during semi-solid deformation. The motion and deformation of the solid coupled with liquid flow in the melt were treated as the two-phase flow because plastic materials could be formulated as non-Newtonian fluids. The vector-valued phase-field formulation and the self-constructed Navier–Stokes solver made it possible to simulate the growth, motion, deformation, fragmentation and agglomeration of two dendrites coupled with liquid flow in the melt. Computational results suggest that fragmentation can occur when the grain boundary is wet and penetrated by the melt, giving new supporting evidence to a previously proposed mechanism for the fragmentation of dendrites.

The traditional balance circuit is employed to balance the retired battery string. It will occupy some space for the extra switches, inductors, or/and capacitors of the energy storage system. This letter is trying to share the inductor of the dc–dc converter with the balance system by utilizing the current ripple on the inductor of the multiwinding transformer. The balance circuit does not require additional switches and control logic. The results of dynamic charging conditions show that the circuit is appropriate for balancing the battery string, and the system efficiency with the proposed approach reaches 94.1% at rated 28-W input power. The balance system only increases one diode and one inductor for each cell, which reduces the cost by 60% and 66% separately compared with the traditional resistance equalizer and transformer-based equalizer.

Optimum interpolation (OI) analysis is performed on the sea surface temperature (SST) products retrieved from the Fengyun-3C (FY-3C) visible and infrared radiometer (VIRR). The oriented elliptic co...

To evaluate the efficacy and safety of Yangyin Yiqi Huoxue Granule (养阴益气活血颗粒, YYHG) in the treatment of ischemic stroke (IS) patients with qi-yin deficiency and blood stasis syndrome (QYDBSS), and to explore its effective dosage. The total of 288 patients were randomly assigned to the YYHG high-dose, YYHG low-dose, positive control (administered Xiaoshuantong Granule, XSTG, 消栓通颗粒), or placebo control (administered inert granule) groups (72 cases per group) by software-drived competitive block randomization. The trial was conducted for a 28-day period, with a 180-day follow-up period. The primary outcome was the comprehensive curative evaluation, and secondary outcomes were the National Institute of Health Stroke Scale (NIHSS) score, Barthel activities of daily living (ADL) index score, the quality of life index (QLI) score, and the Chinese medicine syndrome (CMS) score. All analyses were done on an intention-to-treat basis. The clinical safety was also assessed. The total of 288 participants were recruited between June 1, 2008 and September 30, 2009, and 287 patients received intervention; the treatment groups were well balanced at baseline. The comprehensive cure rates of YYHG high-dose, low-dose, positive and placebo control groups were 63.38%, 31.94%, 36.11% and 6.14%, respectively; there was a statistical difference between the two groups (P

This article investigates the composite learning fuzzy control for a class of stochastic nonlinear strict-feedback systems subject to dynamics uncertainty. The fuzzy logic system is built to model the unknown system nonlinearity. The highlight is that different from previous studies using only tracking error for fuzzy weight updating, the accuracy of fuzzy learning is emphasized in this study. The serial-parallel estimation model with fuzzy approximation and gain compensation is constructed to acquire the prediction error such that the composite fuzzy updating law is designed with more accurate feedback information. The stochastic stability analysis ensures the uniformly ultimate boundedness of the system signals in mean square. Through the simulation tests on a numerical example with different stochastic disturbances and one-link manipulator dynamics, it is proved that the proposed composite learning scheme can solve the system uncertainty effectively and make the closed-loop system track the reference command with satisfactory accuracy.

Sodium-ion batteries (SIBs) have attracted significant attentions as promising alternatives to lithium-ion batteries for large-scale energy storage applications. Here carbon materials are considered as the most competitive anodes for SIBs based on their low-cost, abundant availability and excellent structural stability. Pitch, with high carbon content and low cost, is an ideal raw precursor to prepare carbon materials for large-scale applications. Nevertheless, the microstructures of pitch-based carbon are highly ordered with smaller interlayer distances, which are unfavorable for Na ion storage. Many efforts have been made to improve the sodium storage performance of pitch-based carbon materials. This review summarizes the recent progress about the application of pitch-based carbons for SIBs anodes in the context of carbon's morphology and structure regulation strategies, including morphology adjustment, heteroatoms doping, fabricating heterostructures, and the increase of the degree of disorder. Besides, the advantages, present challenges, and possible solutions to current issues in pitch-based carbon anode are discussed, with the highlight of future research directions. This review will provide a deep insight into the development of low-cost and high-performance pitch-based carbon anode for SIBs.

The growing energy concern all over the world has recognized hydrogen energy as the most promising renewable energy sources. Recently, electrocatalytic hydrogen evolution reaction (HER) by water splitting has been extensively studied with a focus on developing efficient electrocatalysts that can afford HER at overpotential with minimum power consumption. The two-dimensional transition metal carbides and nitride, also known as MXenes, are becoming the rising star in developing efficient electrocatalysts for HER, owing to their integrated chemical and electronic properties, e.g., metallic conductivity, variety of redox-active transition metals, high hydrophilicity, and tunable surface functionalities. In this review, the recent progress about the fundamental understanding and materials engineering of MXenes-based electrocatalysts is summarized in concern with two aspects: i) the regulation of the intrinsic properties of MXenes, which include the composition, surface functionality, and defects; and ii) MXenes-based composites for HER process. In the end, we summarize the present challenges concerning the efficiency of MXenes-based HER electrocatalysts and propose the directions of future research efforts.

In view of the multi-scale changes and the influence of light and angle in the image matching process, it is quite difficult to realize intelligent image registration by using convolutional neural network. The existing image matching algorithm has the following problems in the application process: the existing shallow feature extraction model has lost a lot of effective feature information and low recognition accuracy. Meanwhile, the image registration method based on deep learning is not robust and accurate enough. Therefore, an image registration method based on additive edge cosine loss was proposed in this paper. In the twin network architecture, cosine loss was used to convert Euclidean space into angular space, which eliminated the influence of characteristic intensity and improved the accuracy of registration. The matching cost was directly calculated by the included angle of two vectors in the embedded space, where the size of the angle edge could be quantitatively adjusted through parameter $$m$$ . We further derived a specific $$m$$ to quantitatively adjust the loss. In addition, anti-rotation attention mechanism was added to the network to enhance the ability of feature information extraction and adjust the position information of feature vectors to reduce the mismatching caused by image rotation.

The evolution of heterogeneous microstructure and mechanical properties of a 12Cr–10Ni–Mo–Ti maraging steel was investigated at different aging temperatures. As the aging temperature increases, more reversed austenite forms with the recovery of martensite matrix. When aging temperature is up to 560 °C, more lath-like reversed austenite coalesces together and leads to the formation of martensite and austenite dual-phase microstructure. Fine η-Ni3(Ti, Al) particles initially precipitate at 440 °C and grow up with increased aging temperature. Notably, it was found that η-precipitates can be encompassed in reversed austenite at 500 °C. Thermodynamic calculations further verify the austenite reversion, and nanoprecipitation can occur independently of each other though there is competition of Ni element. However, it leads to the coarsening and dissolution of η-precipitates as the aging temperature further increases. The desirable heterogeneous microstructure of the aged martensite matrix, soft reversed austenite and stable η-precipitates at 500 °C contributes to a high yield strength (~ 1 GPa, 25 °C; ~ 1.4 GPa, -196 °C) and a reasonable cryogenic impact toughness (~ 60 J, − 196 °C), which is mainly ascribed to the precipitation strengthening of η-precipitates, transformation-induced plasticity (TRIP) toughening effect from the lath-like reversed austenite and the increased misorientation toward high-angle grain boundary.

Thermal effect in absorbing composite is concerned gradually due to electromagnetic environment tends to high power, high frequency and wide bandwidth. Microstructure characteristics and some basic material properties of carbonyl iron powder/silicone rubber (CIP/SR) are obtained by experiments method. Complex permittivity and permeability of CIP/SR composite as an absorbing material is measured by the vector network analyzer. CIP/SR composite with 78 wt% particles filling exhibits excellent absorption performance in C and X band. A numerical model coupled with electromagnetic wave, heat transfer and mechanics theory is presented to study the thermal effect and mechanical damage of absorbing composite under microwave radiation. Microwave heating and attenuation mechanism of CIP/SR composite are discussed. Electric field, temperature, stress and deformation in CIP/SR composite are quantitatively characterized. The results indicate temperature distribution relates to electric polarization and hysteresis loss. Temperature of CIP/SR composite increases by 36 °C as microwave radiation lasts 2 s at 9.37 GHz. Thermal expansion and stress concentration will be aggravated as frequency increases.

We report on the fabrication of circular cladding waveguides with cross-section diameters of 60−120 μm in Pr:YAG crystal by applying femtosecond laser inscription. The fabricated waveguides present 2D guidance on the cross-section and fairly low propagation losses. Multiple high-order guiding modes are observed in waveguides with different diameters. Corresponding simulation results reveal the origin of a specific kind of guiding modes. Confocal micro-Raman (μ-Raman) experiments demonstrate the modification effects in femtosecond laser affected areas and ascertain the refractive index induced guiding mechanism. In addition, luminescence emission properties of Pr3+ ions at waveguide volume are well preserved during the femtosecond laser inscription process, which may result in a potential high-power visible waveguide laser.

Luminescent conjugated network polymer is one of the most promising chemo-sensors owing to their good chemical/optical stability and multiple functionalization. Herein, three conjugated network polymers were prepared by using aggregation-induced emission active 1,1,2,2-tetrakis(4-formyl-(1,1′-biphenyl))-ethane (TFBE) unit as monomer and hydrazine as linker. Through regulating the synthetical condition, the polymeric network can form either uniform two-dimensional azine-linked nanosheets (A-NS), conjugated microporous polymers (A-CMP) or covalent organic frameworks (A-COF). All of these polymers exhibited good stability and high fluorescence quantum efficiency with the quantum yield of 6.31% for A-NS, 5.26% for A-CMP, and 5.80% for A-COF, as well as fast and selective fluorescence quenching response to 2,4,6-trinitrophenol (TNP). And the best TNP sensing performance with the Stern-Volmer constants (Ksv) values up to 8 × 105 L/mol and a detection limit of 0.09 μmol/L was obtained for A-NS. The study explores various strategies to construct conjugated polymers with different nanoarchitectures based on the same building block for sensitive detection of explosives.

Fe–10Cr–10Ni cryogenic maraging steel is one of the key candidate materials applied in harsh cryogenic condition due to its high strength and good cryogenic toughness. In this study, the effect of aging temperature on its microstructure and mechanical properties was systematically studied based on austenite reversion and nano-precipitation. It shows that a desirable combination of high strength (834 MPa, 25 °C) and excellent cryogenic impact toughness (164 J, −196 °C) can be obtained by aging treatment at 500 °C. Multi-scale characterizations were conducted to reveal the microstructure characteristics of the steel. It was found that obvious film-like reversed austenite nucleate and grow at the high-angle grain boundaries of martensite matrix in the steel aged at 500 °C, whereas the higher aging temperature resulted in a larger content of blocky reversed austenite in martensite blocks. Austenite reversion mechanism was proposed based on the double-spherical-cap model and diffusion kinetics of Ni element. Besides, it was found that the precipitation sites of Ti-rich particles are not only distributed in matrix but also located at the dislocations, and they were identified as the clusters of Ni3Ti precipitates. Finally, the origin of the above cryogenic toughness includes the transformation-induced plasticity (TRIP) effect from the soft film-like austenite, higher density of high angle grain boundaries of martensite and fine nanoscale precipitates. Moreover, the precipitation strengthening from the clusters of Ni3Ti precipitates contributes to the high strength of the steel aged at 500 °C.

This study proposes a material microstructure topology optimization model for a piezoelectric composite beam subject to initial disturbance. The optimization model is built through the Solid Isotropic Material with Penalization interpolation subject to the material volume fraction on the microlevel. And the objective function is to minimize the time integral about local structural response. By introducing the Lyapunov second equation, this time integral is simplified and does not need any numerical integration technique. It can also be used to measure the global vibration response instead of short time gap. Besides, different objectives such as a regional structural response can also be obtained by only changing the weight matrix form. And the sensitivity of the objective function with respect to the design variables are also deduced by solving the Lyapunov equation. A bidirectional evolutionary structural optimization algorithm is used to acquire the optimal results. Four numerical examples including multiphase material microstructure topology optimization verify the developed method that can effectively suppress local structural vibration level and obtain lighter structure.

In this study, we present a novel mixed reality navigation system to facilitate brachytherapy, which is an effective method for curing cancer. The accuracy of needle positioning is a vital problem in brachytherapy that can influence the treatment effect. The purpose of the developed system is to help doctors more quickly and easily position the needles and improve seed accuracy in brachytherapy surgery. Based on mixed reality and a multi-information fusion method, a successful fusion of medical images and a preoperative plan for real patients was achieved, allowing doctors to gain an intuitive understanding of the tumor. Image recognition and pose estimation were used to track the needle punctures in real time and perform registration processes. After global registration using an iterative closest-point algorithm with a pattern tracker, medical images and volume renderings of organs, needles and seeds were aligned with the patient. Based on a phantom experiment, the average needle location error was 0.961 mm, and the angle error was 1.861°. The accuracy of needle insertion was 1.586 mm, and the angle error was 2.429°. This research presents the design and validation of a surgical navigation system for thoracoabdominal brachytherapy based on mixed reality. The proposed system was validated through both phantom and animal experiments. The results indicated that the proposed system achieves clinically acceptable accuracy and can aid doctors in performing surgery based on a visualized plan.

Printed circuit board (PCB) can provide assembly support and electrical connection for components in electronic systems. The machining of micro-holes in PCB is a necessary process and key step for its application in electronic components. Therefore, micro-holes are the key structures of PCB. At present, high-speed drilling based on micro-bit is the key supporting technology for machining PCB micro-holes. However, when the copper foil layer in PCB is machined by this technology, the micro-holes are prone to defects such as hole mouth burr and hole nail head, which could seriously affect the performance of PCB. Focusing on the above problems, this paper proposed to use micro electro-discharge machining (micro-EDM) for assisted machining of PCB micro-holes. With this method, the copper foil layer in PCB was machined by micro-EDM, so as to remove hole mouth burr and hole nail head. The paper detailedly studied the influence of micro-EDM voltage, pulse width and pulse interval on hole mouth burr and hole nail head. Finally, under the effects of 10,000 rpm rotational speed, 40 V voltage, 80 ns pulse width and 160 ns pulse interval, the micro-bit with diameter of 200 μm was used to carry out micro-EDM-assisted machining of the copper foil in PCB. From the machining results, it can be found that the hole mouth burr and the hole nail head were basically eliminated and PCB micro-holes with good quality were obtained by the proposed method.

Strict industry demands necessitate better penetration classification in gas tungsten arc welding of aluminum alloys. An innovative classification method, namely time–frequency spectrogram based convolutional neural network (TF-CNN), has been developed in this article. The logarithmic time–frequency spectrograms are used to interpret the raw arc sound data in the time–frequency domain and served as the input of an optimized convolutional neural network (CNN) model for welding quality classification. The leaky rectified linear unit activation function and root mean square prop optimizer are utilized to improve the property of CNN. Effective arc sound features are extracted automatically by the CNN model. The proposed method is experimentally verified to recognize four penetration states with an average accuracy of 98.2%, which significantly outperforms the four typical comparison models. The generation mechanism and characteristics of arc sound are discussed as the adaptive feature extraction of TF-CNN. These studies expand the application scope of CNN to intelligent welding and achieve notable effects.

Excellent crystallinity and uniform composition distribution of the Cu2ZnSn(S,Se)4 (CZTSSe) absorber are indispensable factors for the fabrication of photovoltaic device with excellent performance. Here, a facile and effective method is developed to improve the composition uniformity of CZTSSe absorber. It is inspiring that by replacing the acetates with chlorides as the solutes in the precursor solution, the issue of the composition non-uniformity especially for the distribution of Cu and Sn, which is ascribed to the rich-carbon in the acetate-based CZTSSe absorber, is able to be avoided. Due to less organic residues and composition uniformity, the grain size and the crystallinity of absorber could be significantly enhanced, and the photovoltaic performance of chloride-based CZTSSe solar cell is improved remarkably. Furthermore, substituting CuCl2 with CuCl as the copper source in the precursor solution is able to obtain a stable solution, and the quality of CZTSSe absorber is further improved. As a consequence, 8.48% efficient CZTSSe solar cell has been yield.

In this communication, we report the scanning manipulation on radiation beams with an active metamaterial (MTM) antenna using p-i-n diode switches. Thanks to the MTM antenna possessing periodical configuration with isolated units, p-i-n diodes in each unit are capable of being actuated individually with OFF/ON-states (coding sequences 0/1), equivalently tuning the phase constant $\beta $ of each cell either in state $\beta _{0}$ or state $\beta _{1}$ . Therefore, for MTM array with a certain number of units, we can obtain plenty of tunable states presented via digitally coding sequence combinations, thereby manipulating beam scanning in a fixed frequency band. Especially, for the first time, we propose the digitally modulated array factor (DMAF) method for the MTM array: introducing unit-cell dispersion curves of both 0/1 states to the array factor, thus, map the digitally coding sequences linearly to the scanning beams at a fixed frequency, resulting in scanning functionalities. Experiments are implemented with applying micro-control-unit (MCU) to the active MTM antenna for driving p-i-n diodes, and measurements demonstrate beam scanning continuously from −30° to +30° at fixed frequencies around 5 GHz, validating the proposed method.

Micro-milling is a flexible and promising fabrication process. Based on the analysis of the surface formation process in micro-end milling, the theoretical surface model was established to investigate the influence of seven identified factors, i.e., minimum cut thickness (MCT), elastic recovery, plastic side flow, radial and axial runout, tool wear (corner radius and unbalanced wear coefficient), and vibration on the frequency spectrum characteristics. The increase of MCT coefficient and plastic side flow height could increase the amplitude of the sft and 2sft frequency, while the scenario for the elastic recovery coefficient witnessed a reverse trend. The amplitude of the 0.5sft frequency decreased with the increase of the radial runout offset, while the amplitude of sft frequency increased as the radial runout offset increased; the scenario for the influence of the radial runout angle was opposite. The increase of the axial runout offset could lead to the increase of the amplitude of both 0.5sft and sft frequency. The increase of corner radius could lead to a slight reduction of the amplitude of the 0.5sft and sft frequency. The occurrence of the vibration with high frequency leaded to a low spatial frequency. The corresponding tool wear experiment was conducted, and the frequency-spectrum characteristics of the micro-milled surface were compared with the simulated results to validate the established profile models. The paper successfully correlated the relative importance of the identified individual factors to the corresponding frequency spectrum characteristics, and it had potential applications in predicting and controlling the spatial content of machined surfaces.

Fluorescent photoswitches are highly attractive, because they hold great promises for photonic devices and imaging. However, a limited number of reversible switches with a response to light have been achieved in the solid state. Here, we report reversible dual fluorescent photoswitching characteristics in the solid state of spiropyran (SP)-functionalized tetraphenylethene (TPE) derivatives. These photoswitches exhibit two distinct and selectively addressable states, a cyan fluorescence and a red fluorescence, which can be conveyed into each other in a reversible feature upon irradiation with alternating UV and visible light. Detailed spectroscopic and theoretical studies suggest that the nonplanar molecular conformation of TPE moieties leads to large free volumes, which facilitates the reversible photoisomerization of SP. The excellent reversibility and high-contrast fluorescence of solid-state photoswitches enable great applications in multimodality anticounterfeiting and optical writing and erasing fluorescent devices.

Microemulsion and reverse microemulsion exhibited important applications in many fields. Bola-surfactant as a specific type of surfactants has a certain impact on the formation and stability of the...

Organic mechanochromic materials(also known as piezochromic materials), whose color or emission changes under mechanical force, have attracted great interest owing to their potential applications in pressure sensors, rewritable materials, optical storage, and security ink. Organic mechanochromic materials with aggregation-induced emission(AIE) features have better development prospects and research value owing to their excellent optical properties. To date, mechanochromism has mostly been realized by means of mechanical grinding. Nevertheless, the magnitude of the grinding force is usually uncontrollable and its direction is anisotropic, making it awkward to study the mechanism of mechanochromic materials. On the contrary, hydrostatic pressure, whose magnitude and direction are controllable, is a more valid and governable method to investigate the mechanism of mechanochromic materials, which can help us to construct a meaningful structure-property relationship and understand the latent origin of the mechanochromism. Furthermore, it is conducive to developing other mechanochromic material systems with desired chemical and physical properties. In this review, we focus on the recent progress in the mechanism of organic mechanochromic materials with AIE features under hydrostatic pressure. Four types of mechanisms are included: intermolecular interaction change, intramolecular conformation change, transformation from locally excited state to intramolecular charge-transfer state, and intra- and inter-molecular effects induced by hydrostatic pressure, respectively.

Materials that can produce large controllable strains are widely used in shape memory devices, actuators and sensors. Great efforts have been made to improve the strain outputs of various material systems. Among them, ferroelastic transitions underpin giant reversible strains in electrically-driven ferro/piezoelectrics and thermally- or magneticallydriven shape memory alloys. However, large-strain ferroelastic switching in conventional ferroelectrics is very challenging while magnetic and thermal controls are not desirable for applications. Here, we demonstrate an unprecedentedly large shear strain up to 21.5 % in a hybrid ferroelectric, C6H5N(CH3)3CdCl3. The strain response is about two orders of magnitude higher than those of top-performing conventional ferroelectric polymers and oxides. It is achieved via inorganic bond switching and facilitated by the structural confinement of the large organic moieties, which prevents the undesired 180-degree polarization switching. Furthermore, Br substitution can effectively soften the bonds and result in giant shear piezoelectric coefficient (d35 ~ 4800 pm/V) in Br-rich end of the solid solution, C6H5N(CH3)3CdBr3xCl3(1-x). The superior electromechanical properties of the compounds promise their potential in lightweight and high energy density devices, and the strategy described here should inspire the development of next-generation piezoelectrics and electroactive materials based on hybrid ferroelectrics., 32 pages, 14 figures, 5 tables

In the present work, uniaxial tension tests have been conducted to study the mechanical response of a commercial Al4.5wt%Mg alloy (AA5182). The measurements range from the strain rate of 10-4 to 100 s-1 at room temperature. Digital image correlation (DIC) is also utilized to characterize the heterogeneous deformation of PLC localization. An extremely high camera frame rate (1000Hz) is applied to accurately measure the critical strain of instabilities, especially for tests at high strain rates (>10-1 s-1). The objective of this work has been to evaluate currently existing constitutive and physically based models to see to which extent they can match the experimental findings related to dynamic strain aging, i.e. stress-strain curves, work hardening behavior and critical strain behavior.

The model highly parallel graphics processor systems rely on high-bandwidth DRAM I/O interfaces for large volume of data access at the cost of a lot of energy consumption. In order to reduce the energy consumption of data transmission, modern DRAM uses an asymmetric pseudo-drain I/O interface, which increases the ratio of the termination energy to the transmission energy of logic value 1 in data transactions. This paper proposes the X + B Dynamic Bus Encoding Mechanism, which dynamically selects the encoding mechanism to reduce the number of logical values 1 within different data elements, thereby reducing the data transmission energy consumption of the modern DRAM data bus. The simulation evaluation shows the X + B Dynamic Bus Encoding Mechanism reduces the number of logical values 1 by 38.6%, which saves 31.4% of transmission energy consumption compared to the current bus coding technology.

2D MXene nanosheets with metallic conductivity and high pseudo-capacitance are promising electrode materials for supercapacitors. Especially, MXene films can be directly used as electrodes for flexible supercapacitors. However, they suffer from sluggish ion transport due to self-restacking, causing limited electrochemical performance. Herein, a flexible 3D porous MXene film is fabricated by incorporating graphene oxide (GO) into MXene film followed by self-propagating reduction. The self-propagating process is facile and effective, which can be accomplished in 1.25 s and result in 3D porous framework by releasing substantial gas instantaneously. As the 3D porous structure provides massive ion-accessible active sites and promotes fast ion transport, the MXene-rGO films exhibit superior capacitance and rate performance. With the rGO content of 20%, the MXene-rGO-20 film delivers a high capacitance of 329.9 F g−1 at 5 mV s−1 in 3 M H2SO4 electrolyte and remains 260.1 F g−1 at 1,000 mV s−1 as well as good flexibility. Furthermore, the initial capacitance is retained above 90% after 40,000 cycles at 100 A g−1, revealing good cycle stability. This work not only provides a high-performance flexible electrode for supercapacitors, but also proposes an efficient and time-saving strategy for constructing 3D structure from 2D materials.

18650 Lithium-ion batteries are wildly used as power sources for portable electronics because of the standardized format and economical manufacturing cost. However, commercial 18650 cells come in various designs due to the implementation of different protection devices. The current interrupt device and top vent are mandatory protection devices for all commercial 18650 Li-ion batteries. In contrast, the positive temperature coefficient thermistor, bottom vent, and protection circuit are optional protection devices that can be non-installed, installed separately, or combined in commercial 18650 batteries. Four representative commercial 18650 Li-ion batteries were disassembled and compared in terms of the similarities and differences of the protection devices. This paper overviews the working mechanism, advantages, and drawbacks of each protection device. Recommendations on battery selection and potential future trends are then provided.