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The violent vibration of hydraulic pipelines in aircraft may cause faults or even an accident, especially for the large aircraft with the multi-pump system because of different vibration sources and complex pipelines system. Aiming to the vibration analysis and control of the multi-pump system, this paper proposed the clamps' locations optimization to minimize the system impedance at vibration frequencies. Firstly, the models of the flexible clamp and other components in multi-pump system were established, based on which, the system impedance was calculated by using Transfer Matrix Method (TMM); Secondly, the objective function is defined as weighted sum of system impedance at frequencies of different vibration sources. Then, the clamps’ locations were altered to change the system impedance. Moreover, The Chaotic Swarm Particle Optimization (CPSO) algorithm was applied to obtain the optimal clamps’ locations and the minimum value of objective function which decreased by 36.4% compared to the value of original clamps’ locations; Finally, the experiments from vibration and pressure test with original and optimized clamps’ locations verified the effectiveness of the system impedance calculation and clamps’ locations optimization method.

The tensile-tension fatigue behavior of minicomposite SiC/(PyC/SiC)2/SiC at room temperature was studied, and the residual mechanical properties of specimens were tested after 106 pre-fatigue cycles under different levels of stress. The results show that the residual strength first increases owing to the release of stress concentration and then decreases owing to excessive fiber wear. In addition, it is worth noting that the tensile curve of pre-fatigue specimens deflects twice; the first occurrence correlates with matrix crack reopening, and the second occurs when the uniaxial tensile load exceeds the pre-fatigue stress, and the degree of deflection also gradually decreases or almost disappears.

The theoretical Shockley-Queisser limit of photon-electricity conversion in a conventional p-n junction could be potentially overcome by the bulk photovoltaic effect that uniquely occurs in non-centrosymmetric materials. Using strain-gradient engineering, the flexo-photovoltaic effect, that is, the strain-gradient-induced bulk photovoltaic effect, can be activated in centrosymmetric semiconductors, considerably expanding material choices for future sensing and energy applications. Here we report an experimental demonstration of the flexo-photovoltaic effect in an archetypal two-dimensional material, MoS2, by using a strain-gradient engineering approach based on the structural inhomogeneity and phase transition of a hybrid system consisting of MoS2 and VO2. The experimental bulk photovoltaic coefficient in MoS2 is orders of magnitude higher than that in most non-centrosymmetric materials. Our findings unveil the fundamental relation between the flexo-photovoltaic effect and a strain gradient in low-dimensional materials, which could potentially inspire the exploration of new optoelectronic phenomena in strain-gradient-engineered materials.

In this paper, we use an ant colony heuristic method to tackle the integration of data association and state estimation in the presence of cell mitosis, morphological change and uncertainty of measurement. Our approach first models the scouting behavior of an unlabeled ant colony as a chaotic process to generate a set of cell candidates in the current frame, then a labeled ant colony foraging process is modeled to construct an interframe matching between previously estimated cell states and current cell candidates through minimizing the optimal sub-pattern assignment metric for track (OSPA-T). The states of cells in the current frame are finally estimated using labeled ant colonies via a multi-Bernoulli parameter set approximated by individual food pheromone fields and heuristic information within the same region of support, the resulting trail pheromone fields over frames constitutes the cell lineage trees of the tracks. A four-stage track recovery strategy is proposed to monitor the history of all established tracks to reconstruct broken tracks in a computationally economic way. The labeling method used in this work is an improvement on previous techniques. The method has been evaluated on publicly available, challenging cell image sequences, and a satisfied performance improvement is achieved in contrast to the state-of-the-art methods.

The dynamic analysis of cell behavior is fundamental to the evaluation of the correlation between disease and abnormal cell migration. In this study, a self-regulated foraging behavior for cell tracking is proposed under the framework of dual prediction and update of an ant colony and its pheromone field. In the regulated behavior of ant foraging, three strategies are employed: range of foraging, re-sampling, based on the initial distribution of the ant colony; and the stopping criteria of the foraging. The foraging movement of an ant colony is confined to its relevant range determined by the corresponding pheromone field and dynamically varies over iterations. An initial distribution of the ant colonies at each iteration is generated by a Gaussian based re-sampling strategy to regulate an effective search in a centralized manner as a colony. An adaptive stopping criterion of foraging is put forward on the basis of Kullback-Leibler divergence of two approximately Gaussian pheromone fields between two consecutive iterations. The experimental results of the application to cell tracking show that the effectiveness of the algorithm, and demonstrate that it is better than the compared methods.

Polyethylene (PE) membrane has poor wettability and poor thermal stability, which results in insufficient wetting by liquid electrolytes, thermal shrinkage, and no guarantee of safety. In addition, polyethylene terephthalate (PET) nonwoven fabric has inhomogeneous pores and no shutdown function. Therefore, it may cause some problems for independent use, either in the assembly or in usage. In this study, a hybrid separator used in lithium-ion batteries was investigated. The separator was fabricated by laminating a PE membrane and PET nonwoven fabric with or without a ceramic coating on the PET nonwoven. The morphology, wettability, thermal stability, and battery performance were evaluated, and the results showed that the homogeneous distribution of pores can be obtained from the hybrid separators. The wettability properties were also improved in terms of contact angle, liquid electrolyte absorption height, and the decrease in the spreading area. Moreover, with laminated PET nonwoven fabric, the hybrid separators kept the dimensional shape at 180°C for 1 hour of heating, but the PE membrane shrank and became a small wad. The difference between the shutdown and meltdown temperatures ensured that the battery was safe to use. In addition, the evaluation of the battery’s performance indicated that the hybrid separators can be used instead of a PE membrane. This study showed a facile method for the preparation of a hybrid composite separator with improved wettability, thermal stability, and safety for lithium-ion batteries, and it has the potential to be used extensively in the future.

Quantile estimation with big data is still a challenging problem in statistics. In this paper we introduce a distributed algorithm for estimating high quantiles of heavy-tailed distributions with massive datasets. The key idea of the algorithm is to apply the alternating direction method of multipliers in parameter estimation of the generalized pareto distribution in a distributed structure and compute high quantiles based on parameter estimation by the Peak Over Threshold method. This paper proves that the proposed algorithm converges to a stationary solution when the step size is properly chosen. The numerical study and real data analysis also shows that the algorithm is feasible and efficient for estimating high quantiles of heavy-tailed distribution with massive datasets and there is a clear-cut winner for the extreme quantiles.

Purpose This study aims to propose an improved linear quadratic regulator (LQR) based on the adjusting weight coefficient, which is used to improve the performance of the vehicle direct yaw moment control (DYC) system. Design/methodology/approach After analyzing the responses of the side-slip angle and the yaw rate of the vehicle when driving under different road adhesion coefficients, the genetic algorithm and fuzzy logic theory were applied to design the parameter regulator for an improved LQR. This parameter regulator works according to the changes in the road adhesion coefficient between the tires and the road. Hardware-in-the-loop (HiL) tests with double-lane changes under low and high road surface adhesion coefficients were carried out. Findings The HiL test results demonstrate the proposed controllers’ effectiveness and reasonableness and satisfy the real-time requirement. The effectiveness of the proposed controller was also proven using the vehicle-handling stability objective evaluation method. Originality/value The objective evaluation results reveal better performance using the improved LQR DYC controller than a front wheel steering vehicle, especially in reducing driver fatigue, improving vehicle-handling stability and enhancing driving safety.

Fast, direct electron detectors have significantly improved the spatio-temporal resolution of electron microscopy movies. Preserving both spatial and temporal resolution in extended observations, however, requires storing prohibitively large amounts of data. Here, we describe an efficient and flexible data reduction and compression scheme (ReCoDe) that retains both spatial and temporal resolution by preserving individual electron events. Running ReCoDe on a workstation we demonstrate on-the-fly reduction and compression of raw data streaming off a detector at 3 GB/s, for hours of uninterrupted data collection. The output was 100-fold smaller than the raw data and saved directly onto network-attached storage drives over a 10 GbE connection. We discuss calibration techniques that support electron detection and counting (e.g., estimate electron backscattering rates, false positive rates, and data compressibility), and novel data analysis methods enabled by ReCoDe (e.g., recalibration of data post acquisition, and accurate estimation of coincidence loss)., The use of electron detectors with high spatio-temporal resolution is limited by the large amounts of data generated. Here, the authors describe ReCoDe, a data reduction and compression scheme, that preserves individual electron events, and enable on-the-fly reduction and compression of raw data.

Carbon fiber-reinforced polymer composites (CFRPs) have many features, such as lightweight, high specific strength, and excellent chemical resistance. However, the adhesion at the interface of the CFRPs, which are composed of fiber and resin, is poor. Thus, de-lamination and interfacial peeling occur, and the mechanical properties, such as intrinsic strength and rigidity, decrease. Fiber surface modification by plasma and silane coupling treatments has attracted much attention to improve these properties. In this study, argon and oxygen mixed gas plasma treatment was used as pretreatment to introduce hydroxyl group on the fiber surface. This method was utilized to improve the adhesion between the fiber and resin. A silane coupling treatment was conducted to bond the carbon fiber and epoxy resin by chemical covalent bonding. The effect of silane coupling treatment on the interfacial property of CFRPs was investigated. Elemental analysis of the surface modified carbon fiber was explored through energy dispersive X-ray spectrometry. The functional groups of different carbon fiber surfaces were analyzed through X-ray photoelectron spectroscopy. The wettability of the treated carbon fiber was examined with a contact angle meter. The interlaminar shear strength was determined with a short beam method.

Lactic acid bacteria (LAB) contamination during fuel ethanol fermentation can lead to significant economic loses. To circumvent this, fuel ethanol plants add antibiotics prophylactically, but their overuse has resulted in the emergence of antibiotic-resistant LAB strains. Lignin is a sustainable biopolymer that can be found as a waste product from lignocellulosic biorefineries. Technical lignins and their smaller phenolic subunits have been shown to exhibit broad-spectrum antimicrobial properties, but there is a lack of demonstrations of lignin derivatives with highly selective properties in the literature. Here, corn stover lignin from a biorefinery was oxidatively depolymerized using an environmentally benign organic oxidant, peracetic acid, into a bio-oil that has selective antimicrobial properties against LAB and not yeasts. The resulting bio-oil demonstrated up to 90% inhibition of commercially sampled LAB (including antibiotic-resistant strains) at 4 mg ml−1 with no inhibition against an industrial yeast strain. These antimicrobial properties of the bio-oil are attributed to larger unidentified lignin oligomers, compared to monolignols, that have a membrane damaging mode of action. Using the bio-oil (4 mg ml−1) during simultaneous saccharification and fermentation (SSF) of raw corn starch showed no inhibition of enzymatic activity, and in LAB contaminated fermentations the bio-oil treatments showed an 8% increase in ethanol yields at higher bacterial contamination ratios (l : 100 yeast to LAB, CFU per ml). This study illustrates the efficacy of using lignin bio-oil as an antibiotic replacement during fuel ethanol fermentation and demonstrates the highly selective antimicrobial properties of lignin oligomers, which creates a viable lignin valorization strategy for biorefineries.

This paper presents a novel distributed reconfiguration strategy to enable the secure and reliable operation of the zonal shipboard power system (SPS). To adapt to the latest distributed control structure, the proposed strategy features two levels of reconfiguration: zonal reconfiguration and global reconfiguration. An extended hybrid model of SPS is first developed to accurately capture the interactions between the discrete events and the continuously evolving system dynamics involved in the reconfiguration process. The concept of zonal and global reconfigurability is then proposed along with the evaluation criteria to examine if the system can be reconfigured to return to steady-state operation. Provided that the SPS is reconfigurable, executable algorithms are proposed to determine the optimal sequence of operation events for both zonal and global reconfiguration. To evaluate the performance of the proposed strategy, four case studies are presented in which a four-zone SPS is faced with multiple random faults and requires reconfiguration. Simulation results demonstrate that the proposed reconfiguration strategy outperformed previous algorithms in examining the reconfigurability of the system and determining the optimal reconfiguration solution.

Defects in strongly correlated materials such as V2O3 play influential roles on their electrical properties. Understanding the defects' structure is of paramount importance. In this project, we investigate defect structures in V2O3 grown via a flux method. We use AFM to see surface features in several large flake-like particles that exhibit characteristics of spiral growth. We also use Bragg coherent diffractive imaging (BCDI) to probe in 3 dimensions a smaller particle without flake-like morphology and note an absence of the pure screw dislocation characteristic of spiral growth. We identified and measured several defects by comparing the observed local displacement of the crystal, measured via BCDI to well-known models of the displacement around defects in the crystal. We identified two partial dislocations in the crystal. We discuss how defects of different types influence the morphology of V2O3 crystals grown via a flux method.

Converting lignin to value-added products at high yields provides an avenue for making ethanol biorefineries more profitable while reducing the carbon footprint of products generally derived from petroleum. In this study, corn stover lignin was depolymerized by catalytic transfer hydrogenolysis (CTH) in supercritical ethanol with a Ru/C catalyst. The lignin-derived bio-oil was then sequentially extracted utilizing hexane, petroleum ether, chloroform, and ethyl acetate as solvents in order of less polar to polar, and the subsequent bio-oils were characterized using GPC, GC/MS, and HSQC NMR. Results show that the monomers in the bio-oil fractions contained primarily alkylated phenols, hydrogenated hydroxycinnamic acid derivatives, syringol and guaiacol-type lignins created from reductive cleavages of ether linkages, which were sequentially extracted into groups depending on the solvent polarity. The antimicrobial properties of the bio-oils were screened against Gram-positive (Bacillus subtilis, Lactobacillus amylovorus, and Staphylococcus epidermidis) and Gram-negative (Escherichia coli) bacteria and yeast (Saccharomyces cerevisiae) by examining microbial growth inhibition. Results show that CTH-derived bio-oils inhibited all tested organisms at concentrations less than 3 mg/mL. Total monomer concentration and the presence of specific monomers (i.e., syringyl propane) showed correlations to antimicrobial activity, likely due to cell death or membrane damage. This study provides insights into using sequential extraction to fractionate lignin-derived compounds and correlations between the properties of the extracted compounds and their antimicrobial activity.

Natural, extracellular membrane vesicles secreted by Gram-negative bacteria, outer membrane vesicles (OMVs), contain numerous pathogen-associated molecular patterns which can activate systemic immune responses. Previous studies have shown that OMVs induce strong IFN-γ- and T cell-mediated anti-tumor effects in mice. However, IFN-γ is known to upregulate immunosuppressive factors in the tumor microenvironment, especially the immune checkpoint programmed death 1 ligand 1 (PD-L1), which may hamper T cell function and limit immunotherapeutic effectiveness. Here, we report the development of genetically engineered OMVs whose surface has been modified by insertion of the ectodomain of programmed death 1 (PD1). This genetic modification does not affect the ability of OMVs to trigger immune activation. More importantly, the engineered OMV-PD1 can bind to PD-L1 on the tumor cell surface and facilitate its internalization and reduction, thereby protecting T cells from the PD1/PD-L1 immune inhibitory axis. Through the combined effects of immune activation and checkpoint suppression, the engineered OMVs drive the accumulation of effector T cells in the tumor, which, in turn, leads to a greater impairment of tumor growth, compared with not only native OMVs but also the commonly used PD-L1 antibody. In conclusion, this work demonstrates the potential of bioengineered OMVs as effective immunotherapeutic agents that can comprehensively regulate the tumor immune microenvironment to effect markedly increased anti-tumor efficacy.

This paper develops a novel co-optimized distribution system management algorithm for the distribution system operator to optimally manage the ever-increasing penetration of networked microgrids that are participating in the transactive distribution market as prosumers. For the first time, we evaluate how the incorporation of joint bidirectional energy and ancillary service exchanges could quantitatively increase the operation economy, flexibility, and reliability for both the microgrids and the distribution grid. We formulate the joint distribution system management problem using a bilevel programming approach, in which the upper level is a distribution system optimal management problem for the distribution system operator and the lower level is a microgrid optimal scheduling problem for each participating microgrid operator. Uncertainties from renewable energy generation and responsive loads within the distribution system are also incorporated in the problem formulation. The bilevel stochastic programming model is then reformulated as a single mixed-integer model to solve. The simulation-based case study supports that the proposed management scheme is capable of enhancing energy independency, system-wide efficiency, operational reliability, and economy of the distribution system in comparison with conventional transactive market management schemes.

Load redistribution (LR) attacks represent a major cyber threat to the power grid that can result in branch overloads and even cascading failures in the transmission network by injecting false data to load bus power injection and line power flow measurements. While the mechanism and defense strategies have been well studied for single-occurrence (i.e., discrete) LR attacks, this paper focuses on a yet unexplored category of LR attacks, namely, the continuous LR (CLR) attack, which continuously injects time-varying false data to one or more bus and branch measurements within the system for a certain period of time. To cope with the potentially ever-changing targeted branches (i.e., the branches under attack) and system vulnerability features caused by CLR attacks, this paper takes a different route from the traditional LR defense and mitigation approaches. We propose a novel correlation chain model to capture the vulnerability correlations among branches under the CLR attack. Then, a dynamic sequential-mining algorithm (DSMA) with top-k structure is proposed based on the specific nature of the CLR attack, to mine the historical SCADA measurement database, extract vulnerable branch sequences, and identify the most suitable branches to defend preventively. Simulation studies are conducted on IEEE RTS-96 system to evaluate the effectiveness of the proposed approach in terms of increasing attack costs for the attackers and reducing the potential impacts of CLR attacks.

The load redistribution (LR) attack, as a special type of false data injection attacks, aims to distort the results of the security-constrained economic dispatch (SCED) and drive the system to non-optimal or even unsecure operating conditions by injecting false data to the node power injection and branch power flow measurements. The LR attack represents a great danger to the safe and reliable operation of the current power grid where the physical infrastructure is increasingly intertwined with cyber components. In this paper, we propose a novel pre-overload vulnerability graph (POV-graph) approach to systematically assess, evaluate, and quantify the system vulnerability under an LR attack. The proposed approach is formulated based on the specific overloading mechanism of the LR attack as well as their cascading patterns. A set of case studies are performed on the IEEE 39-bus, 118-bus, and RTS-96 systems to validate the effectiveness of the proposed approach. Simulation results have shown, for the first time that, by revealing the vulnerability correlations among branches, the proposed approach allows the system operator to better utilize the defense resources and focus on strengthening a limited number of vulnerable branches to enhance the system’s overall security against LR attacks.

A novel highly active fluorescence chemical sensor (TBI) for CN- was synthesized based on triphenylamine-benzothiazole as a new fluorophore, and was used for the first time as a fluorophore for detection of CN- . Fluorescence quantum yield of the probe clearly increased when using triphenylamine-benzothiazole as the group. The probe possessed good selectivity towards CN- and had anti-interference ability over common ions. After adding CN- , the UV-visible spectrum of TBI changed clearly and underwent a dramatic colour change from red to colourless, which could be observed clearly by the naked eye. The limit of detection for CN- was calculated to be 2.62 × 10-8 M, which was well below the WHO cut-off point of 1.9 μM. The novel probe displayed fast sensing of CN- . The detection mechanism was a nucleophilic addition reaction between CN- and a carbon atom -C = N- in indole salt. The π-conjugation and intramolecular charge transfer (ICT) transition in the TBI molecule were destroyed by this addition, which resulted in a change of fluorescence before and after the addition of CN- . The mechanism was verified using theoretical calculation, 1 H NMR titration, and mass spectra. In addition, the probe showed low cytotoxicity and could be used for biological imaging in HeLa cells.

Objective Markers of serological autoimmunity such as anti-nuclear antibodies (ANA) are noted in approximately 14.01% of the Chinese population. The vast majority will do not have clinical autoimmune disease. However, the possible influence of antinuclear antibodies in acute aortic syndromes (AAS) has not been elucidated. Methods The study group included 77 patients who underwent AAS. Serum levels of antinuclear (ANA) were tested. Patients detailed data on AAS risk factors and markers of subclinical index (including C-reactive protein, D-dimmer, Glucose, Creatine kinase) were available. Results: Of the 77 patients with AAS, 40 had classic acute aortic dissection 29 variants intramural hematoma (IMH) and 8 penetrating atherosclerotic ulcer (PAU). Among the control group, 12/76 (15.8%) were ANA positive. In marked contrast, among the study subjects 30/77 (39.0%) were ANA positive. There is a higher incidence of ANA positivity among the study group than among the control group (p = 0.001). The presence of ANAs was related to the occurrence of AAS (r = 0.224, p = 0.005). Meanwhile, the positive ANAs were correlated with atherosclerosis (r = 0.167, p = 0.039), the red blood cell count (r = −0.245, p = 0.002) and C-reactive protein (r = 0.181, p = 0.042). Conclusions Our results indicate that ANA positivity is associated with incidence of AAS, especially the incidence of intramural hematoma (IMH), suggesting that mechanisms resulting in ANA production may be involved in the development of AAS.

Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation (FDI) issues for control systems. However, the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems. To avoid these difficulties, a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed. Under this framework, a so-called performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability, accuracy, and rapidity (SAR) respectively. The criteria for quantification, normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given. FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space. A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method.

As a highly abundant renewable carbon source, lignin can be converted to a variety of advanced carbon materials with tailorable properties through slow pyrolysis. In this study, slow pyrolysis of kraft lignin, for the first time, was investigated with a commercial pyrolysis–gas chromatography−mass spectrometry (Py-GC-MS) system through evolved gas analysis-MS (EGA-MS) and heart-cutting-GC-MS (HC-GC-MS) analyses. These analyses allow recovery and examination of the multi-phased gas products generated from thermal decomposition of lignin during slow pyrolysis over long time course thus making it possible to link pyrolysis chemistry and carbon material properties. The overall product distributions, including volatiles and solid product were quantitatively tracked at different heating rates (2, 20, 40 ℃/min) and different temperature regions (100-200, 200-300 and 300-600 ℃). Solid residues were further characterized using a suite of analytical tools, in correlation with the investigation of formation mechanisms of volatiles to reveal the reaction chemistry of lignin during slow pyrolysis, and to determine the morphology, pore structure, and interfacial chemical properties. This study provides critical insights into the slow pyrolysis chemistry of lignin and the properties of the resulting carbon material. These results will facilitate a better design and control of the lignin slow pyrolysis process for synthesizing functional carbon materials.

Separation and recovery of high-purity Si powder from kerf-loss Si slurry waste is a critical challenge for the photovoltaic industry. A green surfactant poly (propylene glycol) bis (2-aminopropyl ether) (PEA) was employed as a collector to facilitate the separation of Si and SiC from kerf-loss Si waste during flotation process. Single flotation tests of Si and SiC were conducted using 5 × 10−6 mol/L PEA, respectively. The separation efficiencies of Si and SiC in conjunction with PEA adsorption mechanism were investigated. It was found that the maximum recoveries rate of SiC and Si were 90.59% (pH 9.00) and 80.93% (pH 1.96), respectively. Furthermore, the maximum Si grade was determined as 92.31% at pH 8.95 for the sinking part of the mixture generating excellent floatability and selectivity. Zeta potential measurements, FT-IR spectra, and XPS analyses demonstrated that PEA was present on the surface of Si and SiC through electrostatic and hydrogen-bond interactions. The adsorption mechanism was explained based on the results. This research provides an efficient and environmentally friendly route for the separation and recovery of high purity silicon from kerf-loss Si waste.

Ultrasonic vibration–assisted EDM (UEDM) has excellent performance on difficult-to-machine materials processing such as titanium alloy, stellite, and nickel-based alloy, and it was hard to describe the material removal process and surface generation mechanism due to the complex physiochemical reactions during UEDM. In the present study, the material removal mechanism is fundamentally studied based on heat transfer theory. The model of microscopic removal volume of single pulse in UEDM is established according to the characteristics of EDM removal mechanism and the interference of ultrasonic vibration energy. The micro-surface topography generating process is described and the influence of ultrasonic vibration on the machined surface is analyzed. Both simulation calculation and experiment validation are executed in order to verify the accuracy of the theoretical derivation. As the experimental results have shown, the surface-generating process is matching well with the theoretical deduction; the carbon deposit area is reduced and the surface roughness is decreased due to the ultrasonic vibration interference. The machined surface quality can be modified by adjusting the matching performance of ultrasonic vibration energy and EDM energy.

The scoring processes of home and away team in basketball games are modeled by two dependent inverse Gaussian processes with a team-specific parameter that measures the team strength. A common late...

In order to clarify the distribution and variation of silt and fluid mud in the Waiganmen shallow section of the 50000-ton intake channel of the Xiangshan Port, and to understand the influence of the channel excavation on the surrounding flow conditions and the strength of the backsilting, especially the impact of typhoon on the sudden silting of the channel, so as to demonstrate the feasibility and stability of the channel excavation. The fluid mud, hydraulic, sediment and topographic measurements were carried out in the study area, and the thickness of the fluid mud layers, tidal current, sediment and topographic data were obtained. Dual-frequency sounder, gamma-ray densitometer and SILAS navigational fluid mud measurement system were used to monitor the fluid mud, and the results were compared and verified. The adaptability and accuracy of the three methods were analyzed. The SILAS navigational continuous density measurement system and gamma-ray fixed-point fluid mud measurement are used to detect the density, thickness and variation of the fluid mud accurately. Based on the hydrological observation data, the process of erosion and deposition in excavation channel and its influence mechanism are analyzed, and the distribution characteristics and evolution law of siltation in engineering area are given in the form of empirical formula. The research shows that the super typhoon can produce large siltation, which results in sudden siltation of the channel. The tidal current is the main dynamic factor of the change of erosion and siltation of the excavation trench. Under the influence of reciprocating tidal current and excavation topography, the trial excavation trench is silted on the whole. There is fluid mud in the monitoring area of the trench, and the distribution of fluid mud is different in space. The thickness of the fluid mud at the bottom of the trench is generally larger than that outside the trench and the slope of the trench, and the siltation of the trench tends to be slow. The research results can provide scientific evaluation for channel excavation and maintenance, and support for the implementation of the project.

This paper presents an in-play prediction model based on the gamma process for the scoring processes of the National Basketball Association matches. The model is team-specific, i.e., it takes account of the relative strengths of the two teams playing in a match. The dependence between the home and away scoring processes is characterized by a common latent variable. A Bayesian dynamic forecasting procedure for future games is developed, which utilizes the in-match information to update the scale parameter of the model as the match progresses. An evaluation against baseline models is provided in an empirical study. Our proposed model can predict the final score and total points, while the baseline models are unable to make such predictions. Furthermore, our model can produce positive returns on the point spread betting market and the over-under betting market.

The temperature-induced variation in operating force of flow control valves may result in performance degradation or even jam faults of fuel metering unit (FMU), which significantly affects the safety of aircrafts. In this work, an analytical modeling approach of temperature-sensitive operating-force of servo valve is proposed to investigate the temperature characteristics in varying temperature conditions. Considering the temperature effects, a new extended model of flow force is built and an analytical model of valve friction is also derived theoretically based on the dynamic clearance induced by thermal effects. The extremum condition of friction is obtained to analyze the characteristic-temperature points where jam faults occur easily. The numerical results show that flow force increases firstly and then decreases as temperature increases under a constant valve opening. The maximum friction of flow servo valve can be uniquely determined when the structural parameters and ambient temperature are given. The worst situation just happens at the characteristic-temperature points, which are linearly related to the axial temperature gradients of valve spool. Such evaluations may give an explanation for the temperature-induced jam faults of vulnerable valves and provide a reference for designers to determine a suitable working-temperature range of valves in practice.

A combined experimental and numerical investigation is carried out to study the performance of a vertical-axis eccentric-disc variable-pitch turbine (VEVT). A scheme of eccentric disc pitch control mechanism based on double-block mechanism is proposed. The eccentric control mechanism and the deflection angle control mechanism in the pitch control structure are designed and optimized according to the functional requirements of the turbine, and the three-dimensional model of the turbine is established. Kinematics analysis of the eccentric disc pitch control mechanism is carried out. Kinematics parameters and kinematics equations which can characterize its motion characteristics are derived. Kinematics analysis and simulation are carried out, and the motion law of the corresponding mechanical system is obtained. By analyzing the force and motion of blade of VEVT, the expressions of the important parameters such as deflection angle, attack angle and energy utilization coefficient are obtained. The lateral induced velocity coefficient is acquired by momentum theorem, the hydrodynamic parameters such as energy utilization coefficient are derived, and the hydrodynamic characteristics of VEVT are also obtained. The experimental results show that the turbine has good energy capture capability at different inflow velocities of different sizes and directions, which verifies that VEVT has good self-startup performance and high energy capture efficiency.

In the search for chemically stable two-dimensional (2D) materials with high in-plane mobility, proper bandgap, and compatibility with vapor-based fabrication, van der Waals semiconductor SiP has become a potential candidate as a robust variation of black phosphorous. While bulk SiP crystals were synthesized in the 1970s, the vapor-based synthesis of SiP nanostructures or thin films is still absent. We here report the first chemical vapor growth of SiP nanostructures on SiO2/Si substrate. SiP islands with lateral size up to 20 µm and showing well-defined Raman signals were grown on SiO2/Si substrate or on SiP-containing concentric rings. The presence of SiP phase is confirmed by XRD. The formation of rings and islands is explained by a multiple coffee ring growth model where a dynamic fluctuation of droplet growth front induces the topography of concentric ring surfaces. This new growth method might shed light on the controlled growth of group IV-III high-mobility 2D semiconductors.

The traditional network reliability research generally focuses on the topological connectivity among given nodes based on graph theory. Without considering the relationship between network failures...

In this study, silk fibroin (SF)/sodium alginate (SA) porous materials (PMs) with different blend ratios were generated using 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) as crosslinking agent by a simple freeze-dried method. Degradation experiment of SF/SA PMs have been systematically investigated up to 18 days in Collagenase IA solution at 37 °C, Phosphate buffer saline (PBS) solution without enzyme was used as a control. The results showed SF/SA 50/50 PMs exhibited a lowest rate of weight loss, about 68% of the weight retained within 18 d in Collagenase IA solution. SEM images indicated Collagenase IA can degrade fibroin leading to collapse of the pure SF PMs, while SF/SA 50/50 PMs still possessed integrity of pore structure during enzyme degradation with increasing exposure time. The crystalline structure of the SF in the SF/SA PMs changed to silk II after degradation for 18 d. Furthermore, the results of the in vivo degradation by subcutaneous implantation in rats showed that all PMs can be degraded at different levels, and exhibited good subcutaneous histocompatibility to the host animals. The degradability was strongly correlated to the blend ratios in a series of SF/SA composite PMs, and insights gained in this study can serve as a guide to match desired degradation behavior with specific applications for the SF/SA composite PMs.

With the influx of flexible electronics as well as the emergence or prediction of unique phenomena in two dimensional forms of materials, epitaxy at weakly-coupled interfaces is gaining momentum as...

Industrial hemp has gained resurgent interest recently for applications in various sectors. This study evaluated 11 different industrial hemp [6 fiber-only and 5 dual-purpose (fiber and grain)] cul...

This paper presents a two-stage microgrid scheduling strategy in which the frequency control reserve (FCR) is incorporated to ensure economic, reliable, and stable microgrid operation in a joint energy and ancillary service market environment. In addition, to using such reserve to limit frequency excursions caused by uncertainties of active loads and renewable generation, this paper is focused on determining the optimal provision of reserve for microgrid operation mode switching to assure sufficient reserve is available and readily deployable at the disposal of the microgrid operator. The scheduling problem is formulated as a two-stage chance-constrained programming (CCP) model where the power balance chance constraints are used to determine the trade-off between operational economy and stability risk exposure. The chance-constrained formulation is then approximated as a deterministic mixed-integer linear programming (MILP) model for solution. Two sets of policy studies are performed through simulation to evaluate the effectiveness of the proposed strategy in enhancing the operational performance of a microgrid through optimal scheduling.

We investigate in-hand regrasping by pushing an object against an external constraint and allowing sliding at the fingertips. Each fingertip is modeled as attached to a multidimensional spring mounted to a position-controlled anchor. Spring compliance maps contact forces to spring compressions, ensuring the fingers remain in contact, and sliding “compliance” governs the relationship between sliding motions and tangential contact forces. A spring-sliding compliant regrasp is achieved by controlling the finger anchor motions. We derive the fingertip sliding mechanics for multifingered sliding regrasps and analyze robust regrasping conditions in the presence of finger contact wrench uncertainties. The results are verified in simulation and experiment with a two-fingered sliding regrasp designed to maximize robustness of the operation.

Accurate depth estimation from images is a fundamental problem in computer vision. In this paper, we propose an unsupervised learning based method to predict high-quality depth map from multiple images. A novel multi-view constrained DenseDepthNet is designed for this task. Our DenseDepthNet can effectively leverage both the low-level and high-level features of input images and generate appealing results, especially with sharp details. We employ the public datasets KITTI and Cityscapes for training in an end-to-end unsupervised fashion. A novel depth consistency loss based on multi-view geometry constraint is also applied to the corresponding points across pairwise images, which helps to improve the quality of predicted depth maps significantly. We conduct comprehensive evaluations on our DenseDepthNet and our depth consistency loss function. Experiments validate that our method outperforms the state-of-the-art unsupervised methods and produce comparable results with supervised methods.

The reconfigurability of the electrical heterostructure featured with external variables, such as temperature, voltage, and strain, enabled electronic/optical phase transition in functional layers has great potential for future photonics, computing, and adaptive circuits. VO2 has been regarded as an archetypal phase transition building block with superior metal-insulator transition characteristics. However, the reconfigurable VO2-based heterostructure and the associated devices are rare due to the fundamental challenge in integrating high-quality VO2 in technologically important substrates. In this report, for the first time, we show the remote epitaxy of VO2 and the demonstration of a vertical diode device in a graphene/epitaxial VO2/single-crystalline BN/graphite structure with VO2 as a reconfigurable phase-change material and hexagonal boron nitride (h-BN) as an insulating layer. By diffraction and electrical transport studies, we show that the remote epitaxial VO2 films exhibit higher structural and electrical quality than direct epitaxial ones. By high-resolution transmission electron microscopy and Cs-corrected scanning transmission electron microscopy, we show that a graphene buffered substrate leads to a less strained VO2 film than the bare substrate. In the reconfigurable diode, we find that the Fermi level change and spectral weight shift along with the metal-insulator transition of VO2 could modify the transport characteristics. The work suggests the feasibility of developing a single-crystalline VO2-based reconfigurable heterostructure with arbitrary substrates and sheds light on designing novel adaptive photonics and electrical devices and circuits.

Copper (Cu), one of the heavy metals, is far beyond the carrying capacity of the environment with Cu mining, industrial wastewater discharging and the use of Cu-containing pesticides. Intaking excess Cu can cause toxic effects on liver, kidney, heart, but few studies report Cu toxicity on brain tissue. It is noteworthy that most toxicity tests are based on rodent models, but large mammals chosen as animal models has no reported. To explore the relationship of the Cu toxicity and mitochondria-mediated apoptosis on hypothalamus in pigs, the content of Cu, histomorphology, mitochondrial related indicators, apoptosis, and AMPK-mTOR signaling pathway were detected. Results showed that Cu could accumulate in hypothalamus and lead to mitochondrial dysfunction, evidenced by the decrease of ATP production, activities of respiratory chain complex I-IV, and mitochondrial respiratory function in Cu-treated groups. Additionally, the genes and proteins expression of Bax, Caspase-3, Cytc in treatment group were higher than control group. Furthermore, the protein level of p-AMPK was enhanced significantly and p-mTOR was declined, which manifested that AMPK-mTOR signaling pathway was activated in Cu-treated groups. In conclusion, this study illuminated that the accumulation of Cu could cause mitochondrial dysfunction, induce mitochondria-mediated apoptosis and activate AMPK-mTOR pathway in hypothalamus.

Many published models can be used to analyse the sealing performance of rotary lip seal. The surfaces are normally assumed to be periodic variation. However, the quasi-randomness of surface height distribution should be considered, especially the non-Gaussian distribution. Hence, a mixed elastohydrodynamic lubrication model with non-Gaussian surfaces is proposed and used to analyse the effects of sealed fluid pressure on the seal performance in this paper. Based on digital filter and Johnson’s translator system, a rough surface simulation method is introduced to simulate non-Gaussian rough surface. Based on this method the mixed lubrication model with non-Gaussian surfaces is built. The proposed model is verified by comparing the simulation results to experimental observations. Furthermore, it is hardly to find the research focused on the effects of sealed pressure. Hence, the effects of sealed fluid pressure on the seal performance is focused.

Highlighted by the discovery of high-temperature superconductivity, strongly correlated oxides with highly distorted perovskite structures serve as intriguing model systems for pursuing emerging materials physics and testing technological concepts. While 3d correlated oxides with a distorted perovskite structure are not uncommon, their 4d counterparts are unfortunately rare. In this work, we report the tuning of the electrical and optical properties of a quasi-2D perovskite niobate CsBiNb2O7 via hydrogenation. It is observed that hydrogenation induces drastic changes of lattice dynamics, optical transmission, and conductance. It is suggested that changing the orbital occupancy of Nb d orbitals could trigger the on-site Coulomb interaction in the NbO6 octahedron. The observed hydrogen doping-induced electrical plasticity is implemented for simulating neural synaptic activity. Our finding sheds light on the role of hydrogen in 4d transition metal oxides and suggests a new avenue for the design and development of novel electronic phases.

Ocean sound speed is an essential foundation for marine scientific research and marine engineering applications. In this article, a model based on a comprehensive optimal back propagation artificial neural network model is developed. The Levenberg–Marquardt algorithm is used to optimize the model, and the momentum term, normalization, and early termination method were used to predict the high precision marine sound speed profile. The sound speed profile was described by five indicators: date, time, latitude, longitude, and depth. The model used data from the CTD observation dataset of scientific investigation over the South China Sea (2009–2012) (108°–120° E, 6°–8° N), which includes comprehensive scientific investigation data from four voyages. The feasibility of modeling the sound speed field in the South China Sea is investigated. The proposed model uses the momentum term, normalization, and early termination in a traditional BP artificial neural network structure and mitigates issues with overtraining and difficulty when determining the BP neural network parameters. With the LM algorithm, a fast-modeling method for the sound field effectively achieves the precision requirement for sound speed prediction. Through the prediction and verification of the data from 2009 to 2012, the newly proposed optimized BP network model is shown to dramatically reduce the training time and improve precision compared to the traditional network model. Results showed that the root mean squared error decreased from 1.7903 m/s to 0.95732 m/s, and the training time decreased from 612.43 s to 4.231 s. Finally, the sound ray tracing simulations confirm that the model meets the accuracy requirements of acoustic sounding and verify the model’s feasibility for the real-time prediction of the vertical sound speed in saltwater bodies.

Understanding the domain structure of two-dimensional materials is of paramount importance for the design of next generation microelectronic devices. Here, the authors employ a Dion--Jacobson layered oxide as a model system to study the ferroelectric domain structure with atomic scale analysis. They reveal the existence of a unit-cell-thick ferroelectric domain size as well as both 180\ifmmode^\circ\else\textdegree\fi{} and 90\ifmmode^\circ\else\textdegree\fi{} domain walls in a free-standing ferroelectric oxide. This may suggest ways to achieve unit-cell-thick domain structures and shed light on promising material solutions for emerging nonvolatile high-density memories and synaptic devices.

Hand pose understanding is essential to applications such as human computer interaction and augmented reality. Recently, deep learning based methods achieve great progress in this problem. However, the lack of high-quality and large-scale dataset prevents the further improvement of hand pose related tasks such as 2D/3D hand pose from color and depth from color. In this paper, we develop a large-scale and high-quality synthetic dataset, PBRHand. The dataset contains millions of photo-realistic rendered hand images and various ground truths including pose, semantic segmentation, and depth. Based on the dataset, we firstly investigate the effect of rendering methods and used databases on the performance of three hand pose related tasks: 2D/3D hand pose from color, depth from color and 3D hand pose from depth. This study provides insights that photo-realistic rendering dataset is worthy of synthesizing and shows that our new dataset can improve the performance of the state-of-the-art on these tasks. This synthetic data also enables us to explore multi-task learning, while it is expensive to have all the ground truth available on real data. Evaluations show that our approach can achieve state-of-the-art or competitive performance on several public datasets.

When the data are stored in a distributed manner, direct application of traditional hypothesis testing procedures is often prohibitive due to communication costs and privacy concerns. This paper mainly develops and investigates a distributed two-node Kolmogorov–Smirnov hypothesis testing scheme, implemented by the divide-and-conquer strategy. In addition, this paper also provides a distributed fraud detection and a distribution-based classification for multi-node machines based on the proposed hypothesis testing scheme. The distributed fraud detection is to detect which node stores fraud data in multi-node machines and the distribution-based classification is to determine whether the multi-node distributions differ and classify different distributions. These methods can improve the accuracy of statistical inference in a distributed storage architecture. Furthermore, this paper verifies the feasibility of the proposed methods by simulation and real example studies.

Lignin is a crucial component of plant matter; however, it is also largely responsible for the recalcitrance of lignocellulosic biomass when subjected to pretreatment processes. Lignin is generated...

Biomass deconstruction and lignin depolymerization was performed using three different deep eutectic solvents. Various temperature (110°, 130°, and 150 °C) and time (1, 5, 10, 15 min) conditions were tested in a 2450 MHz microwave reactor. Oxalic acid (130 °C, 15 min) and formic acid DES (150 °C, 15 min) gave the highest lignin yield. Microwave heating reduced the processing time significantly. NMR characterization shows that microwave heating promotes selective bond cleavage during lignin depolymerization and has a narrow molecular weight distribution compared to conventional heating techniques. Molecular dynamic simulations showed that certain lignin bonds are stretched under the electric field imparted during microwave irradiation, increasing its probability of breaking.

Crystallographic dislocation has been well-known to be one of the major causes responsible for the unfavorable carrier dynamics in conventional semiconductor devices. Halide perovskite has exhibited promising applications in optoelectronic devices. However, how dislocation impacts its carrier dynamics in the ‘defects-tolerant’ halide perovskite is largely unknown. Here, via a remote epitaxy approach using polar substrates coated with graphene, we synthesize epitaxial halide perovskite with controlled dislocation density. First-principle calculations and molecular-dynamics simulations reveal weak film-substrate interaction and low density dislocation mechanism in remote epitaxy, respectively. High-resolution transmission electron microscopy, high-resolution atomic force microscopy and Cs-corrected scanning transmission electron microscopy unveil the lattice/atomic and dislocation structure of the remote epitaxial film. The controlling of dislocation density enables the unveiling of the dislocation-carrier dynamic relation in halide perovskite. The study provides an avenue to develop free-standing halide perovskite film with low dislocation density and improved carried dynamics., Crystallographic dislocation has proven harmful to the carrier dynamics in conventional semiconductors but it is unexplored in metal halide perovskites. Here Jiang et al. grow remote epitaxial perovskite films on graphene with density-controlled dislocations and confirm their negative impact.

A new wave database has been built over the period of 1979–2017, which can provide wave parameters with high spatial (1 km along Chinese coast) and temporal (1 h) resolutions. Buoy data and satellite altimeter data are used to evaluate the accuracy of the wave hindcasts. Wave climate analysis is the next stage in which the yearly/seasonal maximum, 100-year return period and mean wave characteristics are analyzed. The maximum of the significant wave height (SWH) in summer and autumn are larger than those in the other seasons, while the seasonal mean values in autumn and winter are larger. Severe wave events analysis reveals the maximum values of the 99th percentile SWH (approximate 6 m) are located around Taiwan Island. The average durations for the events during typhoons are 20–30 h with SWH 2–3 m above the 99th percentile SWH. In contrast, the durations are 10–15 h with intensities less than 1 m in winter. For long-term trends, the 99th percentile SWH increases in most part of the Chinese seas, of 0.5–3 cm per year. The changes in times and durations over the past 39 years are not obvious, but the intensity increases approximate 6 cm per year along typhoon tracks.

The anaerobic ammonium oxidation (anammox) process has the advantages of a high nitrogen removal rate, low operational cost, and small footprint and has been successfully implemented to treat high-content ammonium wastewater. However, very little is known about the toxicity of the heavy metal element Ni(II) to the anammox process. In this study, the short- and long-term effects of Ni(II) on the anammox process in an upflow anaerobic sludge blanket (UASB) reactor were revealed. The results of the short-term batch test showed that the half maximal inhibitory concentration (IC50) of Ni(II) on anammox biomass was 14.6 mg L-1. A continuous-flow experiment was performed for 150 days of operation, and the results illustrated that after domestication, the achieved nitrogen removal efficiency was up to 93±0.03% at 10 mg L-1 Ni(II). The settling velocity, specific anammox activity and EPS content decreased as the Ni(II) concentration increased. Nevertheless, the content of heme c increased as the Ni(II) increased. These results indicate that short-term exposure to Ni(II) has an adverse impact on anammox process, but the anammox system could tolerate 10 mg L-1 Ni(II) stress after acclimation during continuous-flow operation for 150 days. High-throughput sequencing results indicated that the presence of Ni(II) had an impact on the microbial community composition in the anammox reactor, especially Candidatus Kuenenia. At Ni(II) concentrations of 0-10 mg L-1, the relative abundance of Candidatus Kuenenia decreased from 36.23% to 28.46%.