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Recently, the virtual machine deployment algorithm uses physical machine less or consumes higher energy in data centers, resulting in declined service quality of cloud data centers or rising operational costs, which leads to a decrease in cloud service provider’s earnings finally. According to this situation, a resource clustering algorithm for cloud data centers is proposed. This algorithm systematically analyzes the cloud data center model and physical machine’s use ratio, establishes the dynamic resource clustering rules through k-means clustering algorithm, and deploys the virtual machines based on clustering results, so as to promote the use ratio of physical machine and bring down energy consumption in cloud data centers. The experimental results indicate that, regarding the compute-intensive virtual machines in cloud data centers, compared to contrast algorithm, the physical machine’s use ratio of this algorithm is improved by 12% on average, and its energy consumption in cloud data center is lowered by 15% on average. Regarding the general-purpose virtual machines in cloud data center, compared to contrast algorithm, the physical machine’s use ratio is improved by 14% on average, and its energy consumption in cloud data centers is lowered by 12% on average. Above results demonstrate that this method shows a good effect in the resource management of cloud data centers, which may provide reference to some extent.

How to improve the efficiency of liquid-phase shear exfoliation (LPSE) for mass production of large-size graphene nanosheets still remains an ongoing challenge. In this work, we have developed a LPSE method using a rotor-stator mixer. It is quite simple and efficient by exfoliation of expanded graphite (EG) in N-methyl-2-pyrrolidone (NMP) with the assistance of organic salts including sodium citrate, potassium citrate and sodium tartrate. The LPSE of EG in NMP can provide improved yields, up to 6 times as high as values from exfoliation of natural flake graphite (NFG). The additive of organic salts in NMP can make a further improvement in graphene yields, 1.5 times higher than that obtained only in NMP. Remarkably, the yields of the as-exfoliated graphene are as high as 10% under optimal conditions, and up to 50% after multiple-cycle exfoliation. Organic salts in LPSE act as analogue grinding aids enhancing the applied shear forces and thus contributing to the improved efficiency of LPSE, but they do not intercalate into the interplanar spaces of graphite. This facile LPSE method should have excellent potential in the large scale production of graphene nanosheets for numerous applications.

Limited by the operation time window and working space, space teleoperation tasks need to be completed within an expected time while ensuring that the end effector meets the physical constraints. Meanwhile, the interaction with unknown environments would cause uncertainty in the closed-loop system, which brings great challenges to the control design. To solve the above problems, the control performance issue for a class of space teleoperation systems subject to multiple constraints and interaction uncertainties is investigated in this article. The force interaction with the human operator/space environment is represented by interval type-2 (IT2) Takagi-Sugeno (T–S) fuzzy systems, where the uncertain equivalent mass and damping parameters can be effectively described and captured by IT2 membership functions. In order to reduce the communication burden and satisfy the constraints of settling time, transient-state performance and operating space, a time-varying threshold event-triggered control scheme together with exponential-type Lyapunov function is developed for the first time. We show that, with the proposed controller, the synchronization tracking errors are guaranteed to converge to a user-defined residual set within preassigned settling time, and never exceed the prescribed range despite unknown control direction and actuator faults, which solves the long-standing constraint issue with more flexibility due to the fact that the related constraints can be arbitrarily specific within the physically available range. Moreover, the convergence set is only dependent on fewer user-defined parameters rather than approximation errors, which provides an effective analysis technique to deal with the difficulty that the convergence accuracy is difficult to calculate quantitatively in the presence of unknown disturbance. Detailed simulation results are provided to show the effectiveness and merit of the proposed control strategy.

With multiple segments and associated universal joints, a segmented hyper-redundant manipulator can perform on-orbital servicing tasks in confined space due to its superior flexibility and dexterity. However, its inverse kinematics resolving and trajectory planning are challenging because of special structure and strict environment constraints. In this paper, we propose an equivalent kinematics modelling and pose-configuration simultaneous planning method to perform given missions with high efficiency. First, a kinematic equivalence arm (KEA) with revolution joints is constructed by rearranging the associated universal joints of each segment. The motion of n associated universal joints in each segment is simplified as that of a serial arm composed of 1 Roll and n coplanar Yaw joints. The endpoint pose (position and orientation) of the KEA is the same as that of each segment; its shape is also easily described as the Roll angle and the normal vector of the configuration plane. Correspondingly, the kinematics of the whole manipulator composed of N segments is modeled as the combined kinematics of N KEAs. Here KEAs is denoted as the kinematic equivalence model of the proposed manipulator. Then, its configuration represented by KEAs' shape parameters and end-effector's pose are planned simultaneously according to the environment constraints. Finally, trajectory tracking and narrow space detection task are simulated and experimented respectively. The results of trajectory tracking show that the computation time of the proposed method is greatly reduced. The simulation and experiment results of narrow space detection verify the proposed method.

Ceramic foams were prepared from ceramic tile polishing waste and fly ash with borax as a fluxing agent at 925 °C. The foaming mechanism of SiC and the effects of borax on the mechanical properties, cellular morphology, and phase composition were investigated. The addition of 18 wt% borax lowered the sintering temperature by 300 °C and accelerated the passive oxidation of SiC, thus promoting the foaming process. The optimum ceramic foam obtained at 925 °C featured a homogenous porous structure, with an average pore diameter, low bulk density, high compressive strength, and high porosity of 1.20 mm, 0.55 g/cm3, 7.8 MPa, and 79.4%, respectively. The excellent mechanical properties make ceramic foams potential candidates for lightweight panels for partition walls and ceiling tiles in building applications.

Continuum hyper-redundant manipulators (CHRMs) have been widely applied in aerospace, medical or other fields to complete tasks in narrow and multi-obstacles environments with its unique structural advantages. Due to the redundancy, the inverse kinematics of CHRMs is rather complex and the trajectory planning has always been the focal and challenging point in the research of CHRMs. To tackle this issue, the present study proposes an overall configuration planning method of CHRMs based on the improved artificial potential field (APF) method. The method avoids the complicated inverse kinematics and vastly reduces the computational complexity. First, a virtual guiding pipeline (VGP) with no obstacles inside is constructed based on a known target configuration and the minimum safe distance. The movement of the CHRM is restricted to the pipe by the APF method. Then, we propose a method to construct a guided potential field in the VGP to solve the local minimum problem of the traditional artificial potential field method. Further, to address the issue of contradictory forces in the overall configuration planning, the maximum-work planning strategy is proposed. Finally, simulations are conducted and the results demonstrate the high performance of the method in terms of planning efficiency, environmental adaptability.

Recently, a novel method of selective oxidation roasting to extract low valence vanadium (LVV) from vanadium slag was proposed to avoid the toxic V(V)-bearing waste and massive energy consumption in traditional process. In order to investigate the oxidation behavior of LVV in the selective oxidation roasting process, vanadium iron spinel Fe2VO4, the main phase containing vanadium in vanadium slag, was synthesized and its evolution of phase, morphology and bonding structure in the selective oxidation process were investigated systematically in this study. The results showed that the oxidation of Fe(II) prior to V(III) during selective roasting. It was feasible to destroy the structure of spinel by oxidizing Fe(II) selectively, while vanadium still existed in low valence and could be recovered easily, and the maximum recovery of LVV was 97.75%. This study could provide theoretical and technical guidance for extraction of LVV directly from vanadium raw material.

Peri-implant infection is one of the biggest threats to the success of dental implant. Existing coatings on titanium surfaces exhibit rapid decrease in antibacterial efficacy, which is difficult to promisingly prevent peri-implant infection. Herein, we report an N-halamine polymeric coating on titanium surface that simultaneously has long-lasting renewable antibacterial efficacy with good stability and biocompatibility. Our coating is powerfully biocidal against both main pathogenic bacteria of peri-implant infection and complex bacteria from peri-implantitis patients. More importantly, its antibacterial efficacy can persist for a long term (e.g., 12~16 weeks) in vitro, in animal model, and even in human oral cavity, which generally covers the whole formation process of osseointegrated interface. Furthermore, after consumption, it can regain its antibacterial ability by facile rechlorination, highlighting a valuable concept of renewable antibacterial coating in dental implant. These findings indicate an appealing application prospect for prevention and treatment of peri-implant infection., Infection is a major problem for dental implants with current antibacterial coatings losing efficacy quickly. Here, the authors report on the N-halamine polymeric coating of titanium implants to create a long-lasting renewable antibacterial layer and demonstrate application in vivo.

The ablation properties and mechanisms of BN-coated Cf-reinforced SiBCNZr composites under an oxyacetylene combustion torch were investigated. The mass and linear ablation rates of the Cf/SiBCNZr ceramic matrix composites were lower than those of Cf/SiBCN and SiCf/SiBCN composites, reaching 0.0022 mg/s and 0.0136 mm/s, respectively. The ablation resistance of the SiBCN ceramics was enhanced by the addition of Zr, whereas the BN-coated Cf increased the thermal shock resistance of the SiBCNZr ceramics. No macrocracks were found on the ablation surface of the Cf/SiBCNZr specimen. The ablation mechanisms based on different ablation temperatures, phase evolution during ablation, and ablation morphologies in the different ablation regions consisted of oxidation of the carbon fibre and ceramic matrix, emission of various gases, the flow of high-viscosity SiO2, and denudation of Cf under the erosion of the ablation flame.

Based on investigation of rural buildings in china, there are more than 20% of the masonry structures constructed in 1970s. Thus, the old blue bricks (OBB) and old red bricks (ORB), which demolished from the typical brick masonry structures was built in 1970s, was chosen in the test. During demolishing the OBB and ORB, the original mortar was destroyed. Thus, the 1:7.8 cement mortar was chosen instead of original mortars and the 1:5 cement mortar was chosen as the reinforcement mortar. In order to know the performant of the reinforcement methods, there are three-level test plan was put forward in the study. Firstly, the mechanical properties of OBB and ORB and mortars was tested; Secondly, the experiment tested the shear strength of the reinforced and unreinforced masonry specimens along mortar joints; Thirdly, there are four walls (OBB reinforced wall and unreinforced wall, ORB reinforced wall and unreinforced wall) have been made for the pseudo-static tests. This research conducted physical performance tests on masonry bricks, masonry components, and masonry walls of typical masonry structures. Through experiments, the shear capacity of the masonry structure reinforced by high-strength mortar and steel bars can be obtained.

In this study, lignosulfonate is converted to hierarchical carbon materials via templating methods, which are used as supports of molybdenum carbide catalysts for Kraft lignin decomposition to aromatic monomers. The results show that hierarchical carbon materials with micropores, mesopores of about 8 nm, and macropores of about 400 nm are obtained from calcium and sodium lignosulfonates using coupled SiO2+F127 templates with high ash-free carbon yields of about 50 %. The F127 template tends to assemble on SiO2 surface along with radial direction to form ordered meso-/macroporous structure of the carbon materials. The β-Mo2C supported on the hierarchical carbon material exhibits high catalytic performance with aromatic yield of 0.586 g/g Kraft lignin, and the BTX (benzene, toluene, and xylene) components and BTX-derived alcohols donate 21 % and 32 % of the aromatics, respectively. The mesopores benefit the accessibility of lignin fragments to active sites and interconnection between macropores, and the macropores enhance the impregnation of highly-dispersed nano β-Mo2C particles into pore structures. The hierarchical carbon materials from pulping waste lignin shows potential for macromolecular lignin decomposition.

This letter proposes a novel online active fault diagnosis (AFD) method based on invariant sets for linear time-invariant (LTI) systems with bounded disturbances and noises. In general, the system has the healthy mode and several faulty modes. During system operation, with respect to the healthy and faulty modes, the corresponding healthy and faulty output estimation sets are computed, respectively. Thus, the task of AFD can be converted to separate the healthy and faulty output estimation sets, which can consequently distinguish the current system mode and implement AFD. The existing AFD methods implement the objective by designing an input sequence to separate the healthy and faulty output estimation sets. However, it is difficult to use these methods to simultaneously combine AFD and fault-tolerant control. Thus, we propose a new AFD method in this letter to online design inputs step by step, which has potential to overcome some weakness of the existing AFD methods. Particularly, we implement this AFD objective by online designing inputs at each step to maximize the distances of the healthy and faulty output estimation sets. Moreover, this online input design problem can finally be transformed into the resolution of two mixed integer programming (MIP) problems with a similar structure. At the end, a quadruple-tank benchmark system is used to illustrate the effectiveness of the proposed method by comparing with an existing set-based AFD method.

The dimethyl oxalate (DMO) hydrogenation reaction is the key step of indirect synthesis of C2-C4 oxygenates (e.g., ethanol) from syngas. Copper-based catalysts have been extensively explored for DMO hydrogenation. However, the unstable copper active sites induced by metal-particle growth at high rection temperatures (e.g., > 553 K) is an impediment to the stable performance. Herein, we report a facile co-precipitation method to confine Cu active sites in the layered double hydroxide for the hydrogenation of DMO to ethanol. The effects of Mg/Al molar ratio on the catalytic performance were systematically investigated to get insights into the structure-activity relationship. The results indicate that the CuMgAl-LDH-1.25 catalyst possesses regular lamellar structures, highly dispersed Cu active sites, and moderate acidic sites, which synergistically achieves a stable performance with a DMO conversion of ca. 100 % and ethanol selectivity exceeding 83 % at 553 K, 3 MPa.

In this paper, we have discussed the synthesis of nanoscale silicoboron carbonitride (SiBCN) nanofibers by electrospinning of novel polyborosilazane precursor solutions, which were synthesized from boron trichloride, tris(dichloromethylsilylethyl)borane and hexamethyldisilazane using a one-pot method, followed by pyrolysis at 1000 °C under nitrogen atmosphere. The influence of the processing procedure (solution concentration, feeding rate and spinning voltage) of the electrospum fibers was also investigated. TGA and FT-IR experiments were employed to study the polymer-to-ceramic conversion and SEM was used to characterize the final materials. Combining the precursor derived ceramics route and electrospinning process enables to product SiBCN nanofibers for industrial applications.

CO2 capture by stripping with aqueous amine is a well-understood and widely employed technology. However, there still exist several drawbacks in the practical applications, such as high energy cons...

Simultaneously regulating the physical properties and chemical environment of interlayer is a critical need for enhancing the capacity and stability of layered electrode materials in energy and env...

Multilink cable-driven hyper-redundant manipulators (MCDHMs) have a slender body and flexible movement characteristics, which are very suitable for complex unstructured environments. Since MCDHMs have multiple coupling between active cables, linkage cables, joints, and the end-effector, the mathematical modeling of the segmented linkage MCDHM becomes more complicated, and the uncertainty of its model makes the motion accuracy of the end-effector become low. Traditional calibration methods that rely solely on eye-in-hand or eye-to-hand calibration method to calibrate the MCDHM model will produce relatively large errors. This article proposes a hybrid hand–eye calibration method, which eliminates the errors introduced by inaccurate kinematics models through the fusion modeling of eye-in-hand and eye-to-hand. First, for unstructured application scenarios, the hybrid calibration framework under the condition of large model errors is introduced, and then the multiple kinematics model of the MCDHM is derived. Then, two different types of hybrid hand–eye calibration equations are derived and solved by the recursive iteration method. Furthermore, according to the hand–eye calibration result, the MCDHM kinematic parameters are calibrated by the particle swarm optimization (PSO) method. Finally, in order to demonstrate the feasibility and superiority of the hybrid calibration method, experiments are carried out on the real MCDHM to further verify the proposed method. The experimental results show that the proposed hybrid calibration method has higher calibration accuracy.

Smart contract vulnerabilities have attracted lots of concerns due to the resultant financial losses. Matching-based detection methods extrapolating known vulnerabilities to unknown have proven to be effective in other platforms. However, directly adopting the technique to smart contracts is obstructed by two issues, i.e., diversity of bytecode generation resulting from the rapid evolution of compilers and interference of noise code easily caused by the homogeneous business logics. To address the problems, we propose contract bytecode-oriented normalization and slicing techniques to augment bytecode matching. Specifically, we conduct data- and instruction-level normalizations to uniform the bytecode generated by different compilers, and enforce contract-specific slicing by tracking data- and control-flows with simulated bytecode executions to prune the noise code as far as possible. Based on the above techniques, we design an unsupervised graph embedding algorithm to encode the code graphs into quantitatively comparable vectors. The potentially vulnerable smart contracts can be identified by measuring the similarities between their vectors and known vulnerable ones. Our evaluations have shown the efficiency (0.47 seconds per contract on average), effectiveness (160 verified true positives) and high precision (91.95% for top-ranked). It is worth noting that, we also identify dozens of honeypot contracts, further demonstrating the capability of our method.

Analyzing scattered wave to recognize object is of fundamental significance in wave physics. Recently-emerged deep learning technique achieved great success in interpreting wave field such as in ultrasound non-destructive testing and disease diagnosis, but conventionally need time-consuming computer postprocessing or bulky-sized diffractive elements. Here we theoretically propose and experimentally demonstrate a purely-passive and small-footprint meta-neural-network for real-time recognizing complicated objects by analyzing acoustic scattering. We prove meta-neural-network mimics a standard neural network despite its compactness, thanks to unique capability of its metamaterial unit-cells (dubbed meta-neurons) to produce deep-subwavelength phase shift as training parameters. The resulting device exhibits the “intelligence” to perform desired tasks with potential to overcome the current limitations, showcased by two distinctive examples of handwritten digit recognition and discerning misaligned orbital-angular-momentum vortices. Our mechanism opens the route to new metamaterial-based deep-learning paradigms and enable conceptual devices automatically analyzing signals, with far-reaching implications for acoustics and related fields., The authors present a passive meta-neural-network for real-time recognition of objects by analysis of acoustic scattering. It consists of unit cells termed meta-neurons, mimicking an analogous neural network for classical waves, and is shown to recognise handwritten digits and misaligned orbital-angular-momentum vortices.

Graphite felt (GF) was modified by the hydrothermal treatment with aqueous ammonia to improve the efficiency of electro-Fenton (EF) process. The surface morphology, structure, and electrochemical p...

The continuous advancement of cloud computing technology has driven the vigorous development of cloud data centers. This manifests itself not only in increasing numbers, but also in rapid expansion scale. At the same time, the problems of high energy consumption, high cost and high carbon emissions began to stand out. These factors have become a bottleneck restricting the further development of cloud computing technology. As a result of the application of virtualization technology, mature cloud service providers use virtual machines instead of physical machines to provide users with computing, storage and other services. Therefore, the scheduling algorithm of cloud tasks and virtual machines has been widely studied by academia as a core problem. However, most of the current cloud data center resource management algorithms take CPU utilization as the main consideration, and increase the CPU utilization through virtual machine integration to reduce the energy consumption of cloud data centers. However, these algorithms will cause waste and low utilization of other resources in the cloud data center due to excessive consideration of CPU utilization. This paper systematically analyzes the mapping relationship between cloud tasks, virtual machines and physical machines. At the same time, the performance of cloud tasks, virtual machines, and physical machines is modeled in the cloud data center. By comprehensively considering the CPU and memory characteristics of cloud tasks, the memory priority cloud task mapping rule is established. Based on the rule, the memory-aware resource management algorithm for low-energy cloud data centers (MALE) is proposed. The algorithm maps cloud tasks and deploys virtual machines according to the memory requirements of the cloud tasks, thereby achieving the goal of simultaneously reducing the total fee of cloud users and the energy consumption of cloud data centers. Finally, the algorithm is compared with the other three algorithms. The experimental simulation results show that the effect of the proposed algorithm in this paper is significantly better than the comparison algorithm for the total fee of cloud users and the energy consumption of the cloud data center.

In this paper, an adaptive output-feedback control strategy is presented for a class of teleoperation systems with system uncertainties, external disturbances, and state constraints. An exponential-type Barrier Lyapunov Function (EBLF) based velocity reconstruction scheme is firstly developed, ensuring that the observation errors converge within finite time while never exceeding the prescribed range. Then, a novel constrained sliding mode controller is presented in the framework of output-feedback control. We show that, under the developed control scheme, the chattering-free finite-time convergence of the synchronization errors can be guaranteed, and the constraint requirement on full states is satisfied. During the sliding motion, the system behaves as a desirable full-order dynamics rather than a conventional reduced-order dynamics. Simulation results further validate the effectiveness of the proposed method.

Cable-Constrained Synchronous Rotating Mechanism (CCSRM) has an important application prospect in the field of cable-driven robots, which can greatly reduce the number of driving motors while ensuring the light and slender body. However, there are obvious cable friction effect and elastic deformation in CCSRM. These nonlinear characteristics have a significant impact on synchronous motion performance. In this letter, a model of CCSRM considering cable friction is proposed, which integrates the effects of cable pretension, elastic deformation, and friction between cable and pulley on system characteristics. The distribution law of cable tension under the influence of friction force and the phenomenon of motion hysteresis caused in reverse rotation are emphatically discussed. Then, an improved LuGre friction model is proposed to solve the problem of line contact friction between cables and pulleys. Further a dynamic model of CCSRM is established to simulate the motion characteristics of the whole process, including the discontinuous friction phenomenon in reverse rotation. Finally, an experimental prototype of two-axis synchronous rotating system is built, and the friction coefficient is identified. The experimental results show that the dynamic model can well simulate the motion characteristics of CCSRM.

This paper characterises and analyses the minimum detectable fault (MDF) (named generalised MDF here) for multiple multiplicative actuator faults based on set-separation constraints of healthy and ...

In this study, a route for simultaneous mineralization of CO2 and production of titanium dioxide and ammonium alum, and microporous silicon dioxide from titanium-bearing blast furnace slag (TBBF slag) was proposed, which is comprised of (NH4)2SO4 roasting, acid leaching, ammonium alum crystallization, silicic acid flocculation and Ti hydrolysis. The effects of relevant process parameters were systematically investigated. The results showed that under the optimal roasting and leaching conditions about 85% of titanium and 84.6% of aluminum could be extracted while only 30% of silicon entered the leachate. 84% of Al3+ was crystallized from the leachate in the form of ammonium aluminum sulfate dodecahydrate with a purity up to 99.5 wt%. About 85% of the soluble silicic acid was flocculated with the aid of secondary alcohol polyoxyethylene ether 9 (AEO-9) to yield a microporous SiO2 material (97.4 wt%) from the crystallized mother liquor. The Al- and Si-depleted solution was then hydrolyzed to generate a titanium dioxide (99.1 wt%) with uniform particle size distribution. It was figured out that approximately 146 kg TiO2 could be produced from 1000 kg of TBBF slag. Therefore, the improved process is a promising method for industrial application.

International audience; Optimal robust state estimation (SE) and fault detection (FD) methods of discrete-time linear parameter varying (LPV) systems with measurement error-affected scheduling variables are proposed under the boundedness assumption of system uncertainties. By using the weighted Frobenius norm of the generator matrix of SE zonotope to characterize the set size, the optimal observer gain can be computed by a Zonotopic Kalman Filter (ZKF) procedure for the purpose of observation. Meanwhile, by minimizing the influence of system uncertainties while maximizing that of faults on SE to enhance the sensitivity of FD, the optimal FD criterion is characterized based on an on-line fractional programming problem, which can be equivalently transformed into a parametric quadratic programming (pQP) problem. The pQP problem can be efficiently solved by searching the root of its nonlinear characteristic equation using secant method. In general, as long as sensors with sufficiently high precision are equipped to measure the scheduling variables, the bounds of measurement errors of scheduling variables can be less conservative than those direct bounds of scheduling variables, which can reduce the conservatism of FD or SE in this way. At the end of this paper, a case study based on a practical circuit model is used to illustrate the effectiveness of the proposed method. Copyright

Herein, an orbitron-like three-dimensional (3D) DNA clip-based nanomachine was proposed for ultrasensitive fluorescent bioassay of microRNA, which was constructed by mechanically interlocking double-DNA-ring with two single-stranded DNAs, performing an orbitron-like 3D structure with double freely rotated DNA rings as the open state. In the presence of target microRNA, the proposed orbitron-like 3D DNA clip can alter its structure from open to closed state in identification of the target microRNA, generating the closure between the previously modified fluorescent dyes and the quenchers to perform a "signal off" fluorescent signal correlated with the concentration of target microRNA. Compared with the normal DNA nanomachines, such as DNA tweezers constructed by self-assembly of three single-stranded DNAs which regulated the open and closed states on the basis of linear conformational changes, the proposed 3D DNA clip-based nanomachine with high mechanical rigidity realized the conformational changes in 3D space with the assistance of target microRNA, which could effectively increase the adjustable distance range and reduce the background signal. Furthermore, the 3D DNA clip-based nanomachine was applied in the fluorescent detection of microRNA-21 with favorable performances for the sensitive detection of microRNA in cells, providing a new avenue for early clinical diagnoses of disease.

Kiln phosphoric acid (KPA) technology could produce P2O5 with high purity and has been applied in thermal phosphoric acid industry; however the formation of fouling in the high-temperature rotary kiln restricts the stable and long-term operation. In this paper, the reaction of phosphate ores with gaseous P2O5 was investigated in a high-temperature reactor, and the CaO–SiO2–P2O5 ternary phase diagram was analyzed to understand the fouling formation mechanism. The results showed that the low-melting-point products, such as Ca(PO3)2 and Ca2P2O7, are responsible for the fouling in the KPA process. In addition, a small amount of impurities, e.g., aluminum and iron, could facilitate the generation of the low-melting-point products and cause serious fouling. Based on the high-temperature SiO2–P2O5 and CaO–SiO2–P2O5 phase diagram analysis, the control of Si/Ca molar ratio (e.g., Si/Ca = 2.0) was found to avoid fouling formation in the kiln. These results could provide the operation parameters of reaction temperature and feeds composition to suppress the fouling in the kiln reactor for the phosphoric acid production in industry.

In this article, we present an adaptive prescribed-time control method for a class of nonlinear telerobotic systems with actuator faults and position error constraints. Extended from prescribed-time stability , practically prescribed-time stability (PPTS) is proposed for the first time aiming at stability analysis and control synthesis of nonlinear systems with disturbance and uncertainty. We show that, under the control scheme in the framework of PPTS, the system states are guaranteed to converge to a user-defined set (physically realizable) within user-defined settling time (physically realizable). Based on PPTS, an adaptive fault-tolerant controller is developed by integrating a novel exponential-type barrier Lyapunov function. Rigorous stability analysis based on back-stepping approach proves that, under the proposed control strategy, synchronization errors converge to a user-defined residual-set within predefined settling time and never exceed the prescribed range. Universal performance indexes, including the settling time, residual-set, accuracy, and overshoot, can be user-defined and only dependent on fewer user-defined parameters. Simulation results illustrate the effectiveness of the developed control scheme.

Software-defined networking (SDN) is an emerging networking technology, which has attracted wide attention from academia and industry, playing a key role in enabling techniques of the 5th generation wireless systems (5G). The fundamental characteristic of SDN is that it decouples the control plane from the data plane, which can provide flexibility and programmability for 5G. Unfortunately, the separation of the two planes becomes a potential attack surface as well, which enables adversaries to fingerprint and attack the SDNs. Existing work showed the possibility of fingerprinting an SDN with time-based features. However, they are coarse-grained. This paper proposes a fine-grained fingerprinting approach that reveals the much more severe threats to SDN security and explores the mitigation strategies. By analyzing network packets, the approach can dig out sensitive and control-related information, i.e., match fields of SDN flow rules. The match fields of flow rules can be used to infer the type of an SDN controller and the security policy of an SDN network. With sensitive configuration information, adversaries can launch more targeted and destructive attacks against an SDN. We implement our approach in both simulated and physical environments with different kinds of SDN controllers to verify the effectiveness of our concept. Experimental results demonstrate the feasibility to obtain fine-grained and highly sensitive information in SDN, and hence reveal the high risk of information disclosure in SDN and severe threats of attacks against SDN. To mitigate the fine-grained fingerprinting threat we have revealed, we explore a lightweight countermeasure trying to hide the sensitive time-based features of SDN networks. Implementation and evaluation demonstrate that our countermeasure can play a role in mitigating the risk of SDN control information leakage with only minor overheads.

Multiple carbide reinforced metal matrix composite coating has been a promising material with superior abrasion resistance properties. Currently the improvement of the wear resistance of metal matrix composite coating mainly depends on the introduction of reinforcing phase at the expense of the inherent excellent ductility of metal matrix. Here, a new window to enhancing the wear resistance by adjusting the configuration of reinforcing phase space without sacrificing the inherent toughness of the matrix is introduced. Multiple (Ti,Nb)C/Ni-based hardfacing alloy coating prepared by plasma transferred arc technology has been investigated in this paper. Results showed that with the change of Ti/Nb atoms ratio, Cr-rich carbide has an obvious refinement behavior, which changes from a thick slat shape to a short bar with a smaller length-diameter ratio. It is observed that the microcracks are generated from coarse Cr-rich carbide under the action of applied stress and expand rapidly. Nevertheless, with the refinement evolution of Cr-rich carbide shape, only tiny micro-cracks exist in Cr-rich carbide. When Ti:Nb = 7:3, the improvement of wear resistance of the coating was mainly attributed to the reasonable spatial configuration distribution of the enhanced phase. When Ti:Nb = 3:7 and 0:10, the improvement of wear resistance of coating was mainly attributed to the improvement of microhardness brought by the increase of carbide precipitation content. By designing the internal correlation between the spatial configuration behavior of reinforcing phase and dry sliding wear test, the positive correlation between wear resistance and microhardness of materials was broken, which may provide a design window for improving wear resistance while maintaining good toughness of matrix.

For numerous applications, it is essential to reliably link a public key with its owner. The current solution is to employ the well-known Public Key Infrastructure (PKI), represented by a trusted certificate authority (CA), to fulfill this assignment by signing the certificate for the public key after validating its owner. However, due to the centralized architecture, it raises the single-point failure problem with unpredictable threats. In this paper, we present a distributed certificate scheme, referred to as Cecoin which is inspired by the well-known Bitcoin by employing its irreversible unforgeability and public verifiability. In Cecoin, the certificates can be treated as currencies and recorded on block chain, which removes the single point failure problem. The miners can verify the validity of certificates following a set of rules to ensure ownership consistency, and allow an identity to bind multiple public-key certificates. For efficient retrieval and verification of certificates, and quick operations, we incorporate the modified Merkle Patricia tree and employ it to implement a distributed Certificate Library. To allow the owner to transfer the possession of identity, we design an online fair exchange protocol without a trusted third party. Security and efficiency analyses show that our Cecoin provides strong security with desirable efficiency.

With many degrees of freedom (DOFs), a hyper-redundant manipulator has superior dexterity and flexible manipulation ability. However, its inverse kinematics and configuration planning are very challenging. With the increase in the number of DOFs, the corresponding computation load or training set will be much larger for traditional methods (such as the generalized inverse method and the artificial neural network method). In this paper, a segmented geometry method is proposed for a spatial hyper-redundant manipulator to solve the above problems. Similar to the human arm, the hyper-redundant manipulator is segmented into three sections from geometry, i.e., shoulder, elbow, and wrist. Then, its kinematics can be solved separately according to the segmentation, which reduces the complexity of the solution and simplifies the computation of the inverse kinematics. Furthermore, the configuration is parameterized by several parameters, i.e., the arm-angle, space arc parameters, and desired direction vector. The shoulder has proximal four DOFs, which is redundant for positioning the elbow and avoiding the joint limit. The arm-angle parameter is defined to solve the redundancy. The wrist consists of the distal two DOFs, and its joints are determined to match the desired direction vector of the end-effector. All the other joints (except for the joints belonging to shoulder and wrist) compose the elbow. These joint angles are solved by using space arc-based method. The configuration planning for avoiding joint limit, obstacles, and inspecting narrow pipeline are detailed for practical applications. Finally, circular trajectory tracking and pipeline inspection are, respectively, simulated and experimented on a 20-DOFs hyper-redundant manipulator. The results show that the proposed method can give solutions of the three-dimensional-pose-determining problem and the configuration-planning problem. The computation of the inverse kinematics is simplified for real-time control. It can also be applied to other spatial hyper-redundant manipulators with similar serial configurations.

Phase-change solvents exhibit the promising potential to reduce the regeneration energy for CO2 capture. In this paper, 3-dimethylaminopropylamine (DMAPA) with intramolecular primary and tertiary a...

Hydraulic fracturing is essential for efficient developments of low-permeability reservoirs. For these fractured production wells, serious water channeling frequently occurs because of the fracture...

A series of highly efficient, environmentally friendly, and low-cost FeaSbTiOx catalysts were prepared by a simple thermal hydrolysis method for the NH3-selective catalytic reduction (SCR) reaction...

Amine-based carbon dioxide (CO2) capture is still limited by high desorption energy consumption. Fixing CO2 into carbonate is a safer and more permanent method. In this work, calcium oxide (CaO) is introduced to perform chemical desorption instead of thermal desorption on 1,8-diazabicyclo [5.4.0] undec-7-ene (DBU) aqueous solution after CO2 absorption. The X-ray diffraction (XRD) patterns of solid products show the formation of calcite calcium carbonate (CaCO3), which prove the feasibility of this method. The effects of reaction temperature, reaction time and Ca2+/CO32− molar ratios on the related reactions in CO2 absorption–mineralization process and CaCO3 precipitation are discussed, and purer CaCO3 is obtained by ultrasonic treatment. The CaCO3 content can be increased to 95.8% and the CO2 desorption ratio can achieve 80% by 30 min ultrasonic dispersion treatment under the conditions (40 °C, 180 min, Ca2+/CO32− molar ratio = 1.0). After five cycles, DBU aqueous solution shows stable CO2 absorption and mineralization ability. Fourier transform infrared spectroscopy (FT-IR) spectra of the reaction process also indicate the regeneration of the solvent. Compared with thermal desorption, this process is exothermic, almost without no additional heat.

A filter mesh was prepared by a facile biomimetic mineralization method with excellent superhydrophilic and underwater superoleophobic properties for the gravity-driven oil-water separations. It sh...

Dual-arm space robot is a promising autonomous system to remove the increasing space debris actively. Due to its limited on-orbit energy, dual-arm space robot should approach and capture the target with minimum time and base disturbance. In this paper, the multi-objective configuration optimization is proposed for maximizing manipulability and minimizing base disturbance of dual-arm space robot during the pre-contact phase. Based on virtual base modelling and coordinated planning, the free-floating dual-arm space robots can be controlled to track and approach the target satellite. In addition, in the null-space of tracking motion, the configuration optimization of dual-arm space robot can be realized by arm-angle adjustment of 7 DOF redundant manipulator. Therefore, the expressions of arm angle and arm-angle Jacobian are first derived. Then the arm-angle trajectory is parameterized by adopting 5th order polynomial interpolation. The optimal arm-angle trajectory can be obtained by Multiple Objective Particle Swarm Optimization (MOPSO), in which the objective function of configuration optimization is set to the vector consisted of base disturbance and manipulability. Therefore, in the null space of dual-arm space robot approaching the tumbling target satellite, the configuration optimization is realized through following the optimal arm-angle trajectory. Finally, several single-objective and multi-objective optimization simulations are carried out to verify the proposed method.

SUMMARYA dual-arm space robot has large potentials in on-orbit servicing. However, there exist multiple dynamic coupling effects between the two arms, each arm, and the base, bringing great challenges to the trajectory planning and dynamic control of the dual-arm space robotic system. In this paper, we propose a dynamic coupling modeling and analysis method for a dual-arm space robot. Firstly, according to the conservation principle of the linear and angular momentum, the dynamic coupling between the base and each manipulator is deduced. The dynamic coupling factor is then defined to evaluate the dynamic coupling degree. Secondly, the dynamic coupling equations between the two arms, each arm, and the base are deduced, respectively. The dynamic coupling factor is suitable not only for single-arm space robots but also for multi-arm space robot systems. Finally, the multiple coupling effects of the dual-arm space robotic system are analyzed in detail through typical cases. Simulation results verified the proposed method.

Dynamic taint analysis (DTA), as a mainstream information flow tracking technique, has been widely used in mobile security. On the Android platform, the existing DTA approaches are typically implemented by instrumenting the Dalvik virtual machine (DVM) interpreter or the Android emulator with taint enforcement code. The most prominent problem of the interpreter-based approaches is that they cannot work in the new Android RunTime (ART) environment introduced since the 5.0 release. For the emulator-based approaches, the most prominent problem is that they cannot be deployed on real devices. In addition, almost all the existing Android DTA approaches only concern the explicit information flow caused by data dependence, while completely ignore the impact of implicit information flow caused by control dependence. These problems limit their adoption in the latest Android system and make them ineffective in detecting the state-of-the-art malware whose privacy-breaching behaviors are inactivated in the analyzed environment (e.g., the emulator) or conducted via implicit information flow. In this paper, we present TaintMan, an ART-compatible DTA framework that can be deployed on unmodified and non-rooted Android devices. In TaintMan, the taint enforcement code is statically instrumented into both the target application and the system class libraries to track data flow and common control flow. A specially designed execution environment reconstruction technique, named reference hijacking, is proposed to force the target application to reference the instrumented system class libraries. By enforcing on-demand instrumentation and on-demand tracking, the performance overhead is significantly reduced. We have developed TaintMan and deployed it on two popular stock smartphones (HTC One S equipped with Android-4.0 and Motorola MOTO G equipped with Android-5.0). The evaluation with malware samples and real-world applications shows that TaintMan can effectively detect privacy leakage behaviors with an acceptable performance overhead.

It is quite difficult to imitate the motion of human arms using non-humanoid robots due to their dissimilar embodiments (degree-of-freedom, body morphology, and constraints). However, in most cases of the robotic imitation, the human operator and the robot would not share the same kinematic configuration. This paper addresses the motion imitation problem between the human arm and an industrial robot, where a commonly-used UR5 robot is considered. The motion of the human arm is obtained by an inertial motion capture system, and then the captured motion is reproduced using the UR5 embodiment. A virtual-joint-based approach is proposed to facilitate the fast and intuitive kinematics mapping between the human arm and the UR5 robot, leading to a robotic imitation system that can imitate the tip location and configuration of the human arm simultaneously. The proposed approach is verified experimentally on a real UR5 robot and compared with classic Cartesian-space-based mapping approach and joint-space-based approach.

Gas–liquid mass transfer of rotating disk reactor was studied in CO2 absorption using 1,8-diazabicyclo-[5.4.0]-undec-7-ene (DBU)-glycerol solution as solvent. Effects of the rotating disk structure and various operation parameters on the CO2 absorption rate and CO2 removal efficiency were investigated. The rotating disk with optimal holes is conducive to mass transfer of CO2 and the formation of thin liquid film at the opening increases the gas–liquid contact area. With the increase of rotating speed, the liquid flow pattern on the rotating disk surface changes from thin film flow to separated streams and creates extra liquid lines attached to the rim of the disk, which leads to a very complicated change on the CO2 absorption rate and CO2 removal efficiency. The overall gas-phase mass transfer coefficient increases 138% as the rotating speed increasing from 250 to 1400 r·min−1. Increasing temperature from 298 to 338 K can enhance the CO2 absorption rate due to lowering the viscosity of the solvent. The rate-determined step for the absorption is focused on the gas side. The rotating disk reactor can effectively enhance the absorption of CO2 with viscous DBU-glycerol solvents.

This paper proposes a mixed active/passive robust fault detection and isolation (FDI) method for discrete-time linear paramter varying (LPV) systems based on set-theoretic unknown input observers (SUIO) and invariant sets. The robustness against system uncertainties in FDI of LPV systems can be guaranteed by actively decoupling or passively bounding their effect on residual signal. Furthermore, the quadratic H∞ stability condition of the LPV-form state-estimation-error dynamics is established based on a group of linear matrix inequalities (LMIs). Under the precondition of stability, a family of residual sets are constructed to establish set-separation guaranteed fault isolation (FI) conditions using invariant sets off-line. As long as the occurred faults satisfy the guaranteed FI conditions, they can be isolated from each other. At the end, a numerical example is used to illustrate the effectiveness of the proposed method.

Noncooperative target pose (position and attitude) measurement is very important for on-orbital servicing tasks, such as malfunctioned spacecraft capturing and repairing, space debris removal, and so on. Traditional stereovision-based methods require the two cameras to observe the same object and form a common observation area, limiting system flexibility, and measurement distance. In this paper, a virtual stereovision (VSV) modeling and pose measurement method are proposed for a dual-arm space robotic system. Each arm only carries one camera to observe different objects. The geometry features (i.e., the triangle, quadrilateral, or circular features) are independently extracted from the images of each camera. The two separate cameras are mapped to a stereo measurement range and the, respectively, identified features are converted into an equivalent “virtual common feature.” Then, a “VSV measurement system” is constructed. The rocket nozzle and the triangular support of the satellite are considered as different objects to be observed by the two cameras of a dual-arm space robot. The pose of the nozzles and the triangular brackets is further achieved based on the VSV information. Finally, we developed an experimental system, which is composed of a satellite mockup, two monocular cameras, and high precision laser tracker (used to evaluate the vision measure accuracy). The experimental results verified the proposed method. The average position error of the method is less than 6.1367 mm, and the average attitude error is less than 2.415°.

Metasurface based positional modulation design has been introduced recently, where a given modulation pattern can only be received at certain desired positions by the proposed method. However, the magnitude of weight coefficient of each element on metasurface varies from one other, representing an attenuation of the amplitude of incoming signal in different degrees. In this paper, a constant reflection attenuation constraint for incoming signals is proposed for the first time, and the proposed method can be extended with a post-processing process to the ideal case where there is no reflection attenuation.

The interface/interphase is modeled by distributed springs, and the degree of interface damage is characterized by the flexibility coefficient of the springs. Considering different degrees of damage at different interfaces, a general dispersion equation by the transfer matrix method was obtained. For the purpose of application, the transmission coefficient of finite-period phononic crystals is also derived. Additionally, the band structures and the transmission coefficients are calculated for different degrees of damage to confirm the interface effect on band gaps. A numerical simulation of the transmission coefficient is performed using the commercial FEM software Comsol Multiphysics. The numerical results obtained agree well with the analytical solution. Finally, based on a monotonic decreasing relationship between the degree of interface damage and the central frequency of band gaps and a monotonic relationship between the degree of interface damage and the amplitude of transmission coefficients, a new method how to evaluate the degree of interface damage theoretically is proposed.

This paper proposes a novel robust fault detection (FD) approach and designs a set-theoretic unknown input observer (SUIO) for linear parameter-varying (LPV) systems with both state and output equations scheduled by inexact scheduling variables. First, for such LPV systems, we propose a novel robust FD method by combing the set theory with the unknown input observer, which considers the bounds of measurement errors of scheduling variables to generate FD-oriented sets. In general, as long as sensors with sufficiently high precision are equipped to measure the scheduling variables, the bounds of measurement errors of scheduling variables can be less conservative than those direct bounds of scheduling variables, which can reduce robust FD conservatism in this way. Second, we give the unknown input decoupling condition of SUIO for such LPV systems and propose an SUIO design method under this condition for robust state estimation (SE). Besides, stability conditions for the proposed methods are established via matrix inequalities. At the end of this paper, a case study is used to illustrate the effectiveness of the proposed methods.

In a multiarm space robotic system, one or more manipulators can be used to stabilize the base through counteracting the disturbance caused by other manipulators performing on-orbital tasks. However, singularities are inevitably present in the traditional methods based on differential kinematics solutions. In this paper, we propose a singularity-free trajectory planning method to simultaneously keep the attitude and centroid position of the base stabilized in inertial space; the balance arms are also designed. First, we derive the coupling motion equations of a free-floating multiarm space robotic system. Then, the singularity problems are theoretically analyzed, and the theoretical basis for singularity-free trajectory planning is established. Second, we decompose the six degrees of freedom pose (attitude and position) stabilization problem into two 3DOF subproblems related to attitude and position balancing. We then design two robotic arms: 1) a position balance arm and 2) an attitude balance arm, to maintain the base centroid position and attitude, respectively. Third, we plan the coordinated trajectories of the two balance arms according to holonomic and nonholonomic constraints. As long as the desired motion is not beyond its balance ability, the reasonable joint variables can always be determined without encountering a singularity problem. Finally, the proposed methods are verified using simulations of typical on-orbital missions, including joint trajectory tracking and target capturing.

In this study, ordered mesoporous carbon materials are prepared to support β-Mo2C catalysts for conversion of Kraft lignin into aromatic monomers. Carbon supports with different porous structures are compared to discuss the critical role of ordered mesopores. The results show a volcano evolution of aromatic monomer yields with the increase in Mo contents over β-Mo2C supported on ordered mesoporous carbon, and a high aromatic yield of 0.576 g/g Kraft lignin is achieved at 280 °C for 3 h for only 10% Mo mass content. Dispersion of β-Mo2C and confinement of ordered mesopores contribute to the highest aromatic yield per unit Mo. The highly dispersed β-Mo2C on the surface of ordered mesoporous carbon exhibits the advances of confined environment and accessibility of lignin fragments to active β-Mo2C, resulting high activity of β-Mo2C for Kraft lignin decomposition.