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Solid-state sodium-ion batteries with sodium metal anodes possess high safety and reliability, which are considered as a promising candidate for the next generation of energy storage technology. However, poor electronic and ionic conductivities at the interface between electrodes and solid-state electrolytes restrict its practical application. Herein, we demonstrate a β″-Al2O3 electrolyte with a vertically porous-dense bilayer structure to solve this problem. The carbon-coated vertically porous layer serves as a high mass-loading host for Na3V2(PO4)3 cathode and provides fast electronically and ionically conductive pathways. In addition, the dense layer is produced to prevent sodium dendrite growth and improve mechanical strength of β″-Al2O3 electrolyte. Experimental results show that the cathode loading in vertically porous layer can reach to 8 mg cm−2, and the porous-dense bilayer β″-Al2O3 electrolyte-based battery exhibits a reversible specific capacity of 87 mAh g−1 and a capacity retention of 95.5% over 100 cycles at a current density of 0.1 C, which is superior to that of the traditional dense β″-Al2O3 electrolyte-based battery. This work based on electrolyte structure design represents an efficient strategy for the development of solid-state sodium-ion batteries with high mass-loading cathode.

Two capillary membranes, single-phase Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF) and dual-phase 75 wt% Ce0.85Sm0.15O1.925 - 25 wt% Sm0.6Sr0.4Cr0.3Fe0.7O3-δ (SDC-SSCF), with dense cross section, were successfully prepared through the plastic extrusion method. The dual-phase capillary membrane shows higher strength compared to the BSCF counterpart, while the two capillary membranes exhibit much higher fracture strength than those of hollow fiber membranes. The oxygen permeation fluxes of both membranes increase with the increase of temperature and flow rate of sweep gas at the ambient pressure, and can be greatly improved by applying high pressures to the feed side. The oxygen permeation flux of BSCF capillary membrane is up to 19.5 mL cm−2 min−1 when 0.5 MPa air was applied to the feed side at 900 °C, which is one order of magnitude higher than that of SDC-SSCF capillary membrane. Thus, both capillary membranes have their own advantages and meet applications under different operation conditions.

The evaluation of pore structure is an essential part in the assessment of carbonate reservoirs. The structures (geometry and connectivity) of nm to μm-scale pore networks in outcrop samples of carbonates from Xiaoerbulake Formation in Tarim Basin of China were studied by using optical microscopy, field emission-scanning electron microscopy (FE-SEM), as well as mercury intrusion porosimetry (MIP) with fractal analyses of the data, and spontaneous imbibition tests (distilled water). The results demonstrate that the lithologies are micritic dolomites, fine-to-medium-to-coarse crystalline dolomites, microbial dolomites, and dolarenite. At micro- to nanoscales in size, pore types are dominated by intergranular, intercrystalline, and intragranular (e.g., dissolution) pores. These pore networks have pore-throat diameters from 0.01 to >10 μm. Compared with a nanoscale pore network, the μm-scale pore networks are relatively well connected and serve as the most important permeability pathways. Although the pore volume accounts for most of the total porosity, the permeability of nanoscale pore networks is low. The existence of micro-nano-fractures could improve connectivity, especially for the nanoscale pore networks, by linking the intragranular (dissolution) pores which are mostly in the range of nm-scale.

The lightening system inside the residential or commercial building consumes the highest electrical power. For an energy efficient smart city development, some sustainable and low power consumption methods need to be explored. In this direction, we proposed solar energy based auto-intelligent LED light controlling system that uses wireless sensor network (WSN) with computation and control model for LED on/off and dimming of LED lights inside the building area. The WSN is employed with some sensor devices that sense and gather ambient context information which is transmitted to computation model. LEDs get power supply from photovoltaic solar panel systems that have inbuilt battery banks. Fuzzy rough set is a simplification of a rough set, obtained from the normalization of fuzzy set in a approximation of crisp value. Fuzzy is utilized for analyzing the energy consumed in the system additionally. Performance evaluation of proposed Auto-intelligent LED system is carried out based on the comparative analysis of energy consumption of ac-grid system with solar energy based dc-grid system. Result analysis shows that proposed system saves 78% of energy consumption as compared to the traditional AC power grid system. The proposed DC power grid system presents 3% of voltage drop and maximum power loss of 1.25%. The statistics of battery charger and LED drives are also represented experimentally.

In this paper, the synchronization problem is investigated for a class of time-varying delayed coupling complex dynamical networks subject to incomplete transition rates Markovian switching typologies via pinning control scheme. Compared with most of previous relative networks, a more general network model is discussed and in which the transition rates in Markovian processes are uncertain or completely unknown. The complete knowledge on the transition rates is difficult to precisely acquire on account of the limitations of equipment and environmental impacts. Only a single feedback controller is utilized and, by constructing time dependent Lyapunov–Krasovskii functions, applying an extended Jensen’s integral inequality as well as some inequality techniques, some criteria are obtained for guaranteeing stochastic synchronization of considered networks. Moreover, similar results can be also presented for Markovian jump complex dynamical networks without time-varying delay. The obtained results improve and extend some existing relevant results. In the end, some simulation examples are provided to illustrate the effectiveness of the proposed method.

RDF made of municipal solid waste was pyrolyzed under simulated pyrolytic gas (PG) atmosphere and N2 atmosphere. Besides pyrolysis temperature, the atmosphere also affected the yield of three phase products and thermal conversion. By comparison of the products from two different atmospheres at same pyrolysis temperature, more tar, less char and gas were produced under PG atmosphere than the yields produced under N2 atmosphere; LHV of char produced under PG atmosphere was always lower than the value of char produced under N2 atmosphere, so that the char thermal conversion (CTC) efficiency under PG atmosphere also was lower; O/C and H/C of chars produced PG atmosphere were usually smaller than the data of char produced under N2 atmosphere, which indicated chars produced under PG atmosphere were more similar with coal, and more suitable for co-combustion of coal and char in coal power plant. In additional, highest comprehensive combustion characteristic index S was obtained at 600 °C under PG atmosphere. LHV of gas produced under PG atmosphere was always higher than the gas produced under N2 atmosphere, but gas thermal conversion (GTC) efficiency under PG atmosphere was lower because of less gas yield.

The pore structure directly controls the tight reservoir’s physical properties and plays a crucial role in gas charging and accumulation. To characterize the pore structure accurately, it is critic...

This paper aims at exploring the mean-square bounded synchronization of clustered stochastic systems under deception attack which is a ubiquitous phenomenon in cyber-physical network. Actually, when controllers in network send controlling signal to physical plants, controller-to-actuator channel may be injected with wrong signal by malicious hackers intending to destroy the system’s performance. To describe attacker’s behavior, some random variables are introduced to describe whether the cluster’s channel is attacked or not in the controlled moment. Meanwhile, it has been proved that pinning impulsive control is effective to offset both stochastic effect and attack effect, where the nodes with bigger error will be chosen to be pinned in impulsive instants. By applying Gronwall-Bellman inequality and Lyapunov method on stochastic network, several kinds of mean-square bounded synchronization criteria based on pinning impulsive strategy are derived in terms of algebraic conditions and some reasonable assumptions. Finally, some numerical simulations are presented to illustrate the effectiveness of the theoretical results in this paper.

Hypothesis: The anodic dissolution of chalcopyrite (CuFeS2) encounters the problem of surface passivation, which significantly affects the copper extraction efficiency. So far, there is no agreement on the passivation mechanism and composition of passive layer, which could be studied by using in-situ scanning electrochemical microscopy (SECM). Experiments: SECM was applied for the in-situ probing of chalcopyrite dissolution under mild oxidation potentials. The surface hydrophobicity and nanoscale distribution of hydrophobic domains were analyzed by static water contact angle measurement and atomic force microscope (AFM) force mapping, respectively. The surface conductivity was characterized by SECM feedback mode. Findings: The concentrations of released species Fe2+, Cu2+ and soluble copper sulfide species (CuxS) generally increased with the potential of chalcopyrite. In the active region (low potentials), Fe2+ was preferentially released, and the metal-deficient sulfide layer that was rich in copper relative to iron started to form as the passive layer. While the release of Fe2+ and Cu2+ was impeded in the passive region, the detected CuxS became pronounced in this region and the following transpassive region, which suggested that the existence of CuxS was a result of passive layer dissolution. The nanoscale distribution of hydrophobic domains suggested that the formation of hydrophobic passive layer initiated in the active region and this layer almost completely covered the chalcopyrite surface at the beginning of passive region. The surface conductivity of chalcopyrite decreased with potential due to the formation of less conductive metal-deficient sulfide layer and possibly insulating elemental sulfur (in the transpassive region). This work provides a new approach for the in-situ probing of chalcopyrite dissolution and useful insights into its dissolution kinetics and passivation mechanisms, with implications for similar electrochemical processes of other mineral surfaces.

Spectrum trading benefits both secondary users (SUs) and primary users (PUs), while it poses great challenges to maximize PUs’ revenue, since SUs’ demands are uncertain and individual SU's traffic portfolio contains private information. In this paper, we propose a data-driven spectrum trading scheme which maximizes PUs’ revenue and preserves SUs’ demand differential privacy. Briefly, we introduce a novel network architecture consisting of the primary service provider (PSP), the secondary service provider (SSP) and the secondary traffic estimator and database (STED). Under the proposed architecture, PSP aggregates available spectrum from PUs, and sells the spectrum to SSP at fixed wholesale price, directly to SUs at spot price, or both. The PSP has to accurately estimate SUs’ demands. To estimate SUs’ demand, the STED exploits data-driven approach to choose sampled SUs to construct the reference distribution of SUs’ demands, and utilizes reference distribution to estimate the demand distribution of all SUs. Moreover, the STED adds noises to preserve the demand differential privacy of sampled SUs before it answers the demand estimation queries from the PSP. With the estimated SUs’ demand, we formulate the revenue maximization problem into a risk-averse optimization, develop feasible solutions, and verify its effectiveness through both theoretical proof and simulations.

Mussel-inspired chemistry has attracted much research interest in manipulating material properties in surface engineering over the past decade due to its universality and versatility. To address biofouling issues, mussel-inspired molecular interaction strategies have provided promising methods for the design and development of anti-biofouling materials that can either repel proteins and microbes to avoid attachment or kill them in the surrounding environment. This review provides an overview of recent advances in mussel-inspired chemistry and its emerging applications in fabricating anti-biofouling platforms. The molecular interactions and adhesion mechanisms of mussel-inspired chemistry are first introduced. The applications of mussel-inspired chemistry in different anti-biofouling hydrogels, membranes and coatings are then discussed. Various bio-inspired material fabrication processes and surface functionalization strategies are presented, in which materials based on the mussel-inspired chemistry play different roles such as surface modifiers, intermediate layers or adhesive moieties to bind other components for functionalizing materials with anti-biofouling performance. Some remaining challenges are discussed, and future perspectives on mussel-inspired modification of anti-biofouling materials are also provided.

This paper studies leader-following bounded consensus problem for linear multi-agent systems (MASs) with exogenous disturbances under an observer-based dynamic event-triggered scheme. To guarantee performance requirements, and avoid frequent updates of the sensors, and the controllers at the same time, two independent event-triggered schemes with dynamic threshold are proposed in sensor-to-observer (S-O), and controller-to-actuator (C-A) channels, respectively. And a fully distributed observer event-based controller is designed, which only requires the observer information from neighboring followers, and itself for each follower. With the help of the Riccati equation, and inequality techniques, some simple, and convenient sufficient conditions are derived to ensure that the closed loop system converges to a bounded region exponentially. Moreover, the proposed dynamic event-triggered mechanisms in S-O, and C-A channels do not only lessen the transmission load, and controller update, but also exclude the Zeno behavior. Finally, a numerical example is given to verify the correctness, and efficiency of our results.

In this paper, we investigate the quasi-synchronization issue of an array of Diffusion Effects Neural Networks (DENNs) with time-varying coupling strength. Two kinds of quasi-synchronization scenarios are discussed. One is self-synchronization and the other is tracking-synchronization. In order to lower the communication loads and reduce the control resource consumption, we propose a new control scheme called intermittent control of reginal division to make the synchronization error within a bounded scope. In this novel control scheme, the non-negative real region is divided into three subregions in advance and an auxiliary Lyapunov function is imported to decide the work time and the rest time by its relationship with three subregions. Moreover, by using rigorous mathematic analysis, we obtain sufficient conditions for the two kinds of quasi-synchronization modes of DENNs under the as-proposed control scheme. Nonidentical term in the network is viewed as external disturbance about to be compensated by the controller. The result shows that the upper bound of synchronization error will be progressively regulated by the parameters in chosen divided region. Several numerical examples are also presented to verify the validity of our theory.

Waste sorting is being gradually implemented as a key measure for circular and sustainable development in China, food waste will be separately collected and separated from municipal solid waste (MSW), thus the plastic content in food waste also will be reduced. In this study, supercritical water gasification (SCWG) of food waste with different contents of plastic (0–3.5 wt%) was experimentally investigated to simulate the influence of waste sorting on the food waste treatment. The results showed that lower plastic content in food waste favored higher gas yield and gasification efficiencies. The highest H2 yield and total gas yield were 3.11 mol/kg and 8.41 mol/kg in the plastic-free case, respectively. When the plastic content decreased from 3.5 wt% to 0 wt%, the cold gas efficiency (CGE), carbon conversion efficiency (CE) and hydrogen gasification efficiency (HE) increased by 125.97%, 173.48% and 94.09%, respectively. However, lower plastic content negatively affected the quality of produced syngas through decreasing H2 mole fraction and LHV. The solid residues from SCWG of food waste with lower plastic content had higher ratio of fixed carbon to volatile matter (FC/VM). Based on the analysis of pyrolysis properties and combustion behavior, decreasing the plastic content in food waste helped to improve the thermal stability of solid residues. Moreover, lower plastic content resulted in a decrease of total organic carbon (TOC) concentration in liquid effluent, which is favorable for further treatment of liquid effluent.

Hydraulic fracturing is widely used in the exploitation of unconventional reservoirs, such as shale gas and tight gas. However, a full understanding of the activation of natural fractures, prediction of fracture growth, distribution of proppant, and network fracture system effectiveness remain unresolved. The onset of fracturing in the media requires energy and this is due to the buildup of pressure within the rock due to continuous injection of fluid. In other words, when the energy associated with the injection fluid reaches the fracture strength of the rock, the fracture initiates and propagates into the formation. Here, we use gelatin in hydraulic fracturing laboratory tests and compare the results to a modified radial hydraulic fracturing theory. The mechanics of the gelatin, procedures to make a testing gelatin block, and procedures to conduct the test are described. The results show that the fracture evolving behaviours from experiments are well matched by the theory. The results are then scaled up to understand fracture growth behaviour in a tight rock reservoir.

Improved power and cycle performances are eagerly required in intermediate-temperature sodium–metal halide (Na–MH) batteries. The existence of the low conductivity NiCl2 layer and the growth of the...

Purpose In the information commons (IC) space of library, it is very important to recognize the emotional state of users for better playing the role of IC. In view of this point, this paper aims to discuss the human expression of user emotion. Design/methodology/approach An emotional state recognition method based on body posture change under video monitoring is proposed. In this method, two parameters are proposed to represent the emotional state of users. Finally, the distribution of users’ overall emotional state is recognized. Findings It is found that the change of human posture reflects the emotional state of users to a certain extent. The spatial frequency of the user’s average body position change and per capita body position change can reflect the spatial distribution of individual and body position change, respectively. Originality/value The method in this paper can effectively overcome the inaccuracy of manual identification of video monitoring images, especially in the case of a large number of users and effectively help the construction of university library IC space and provide a basis for the setting of environmental parameters.

Two-dimensional (2D) CuInP2X6 (X = S or Se) materials have emerged as promising candidates for various technological applications due to their lamellar structures and ferroelectric properties. However, 2D CuInP2Se6 material has not been well explored yet for the difficulty in acquiring ultrathin flakes. Here, we prepare, for the first time, CuInP2Se6 crystals by the chemical vapor deposition method and its 2D flakes, and demonstrate that the thinnest CuInP2Se6 flakes of 4 nm are achieved. X-ray diffraction and atomic-resolution scanning transmission electron microscopy analyses reveal their single crystal phase and the corresponding atomic structure of bulk CuInP2Se6 with good crystallization. Raman results further exhibit obvious thickness dependence of Raman peak position and intensity for the CuInP2Se6 flake. First-principles calculations validate the ferroelectric property of CuInP2Se6 monolayer. Importantly, we find that the antiferroelectric (AFE) state is slightly stable than the ferroelectric (FE) state in bulk form, yet these two states are far more stable than the paraelectric (PE) state, resulting in the coexistence of AFE and FE states in this material.

The conversion of selenium oxyanions to elemental selenium (Se0) of low solubility and bioavailability is an effective industrial approach for selenium management in wastewater treatment. The gener...

We have investigated the influence of rapid thermal annealing (RTA) on the surface defects of CdZnTe (CZT) crystals by using low-temperature photoluminescence (PL) measurements. In the low-temperature PL spectrum for the as-grown CZT crystals, the donor–acceptor pair (DAP) recombination peak is dominant. Overlapping of the free-exciton (FE) and the neutral donor bound exciton (D0,X) luminescence peaks leads to broadening of the (D0,X) peak. In the low-temperature PL spectra for CZT crystals annealed at 523 K and 623 K for 5 min, the A-center peak is dominant. The deterioration of the intensity and FWHM of the (D0,X) peak indicates worsening of the crystal quality under the two RTA conditions. In the low-temperature PL spectra for CZT crystals annealed at 723 K, 773 K and 873 K for 5 min, an FE peak gradually becomes evident as the annealing temperature increases. The full-width half-maximum (FWHM) of the (D0,X) peak decreases from 7.95 meV before annealing to 2.85 meV after annealing at 873 K. The neutral acceptor bound exciton (A0,X) peak intensity increases with the annealing temperature increasing. The peak intensity ratio I(D0,X)/I(DAP) increases from ∼ 0.24 before annealing to ∼ 1.62 after annealing at 873 K. The A-center peak intensity decreases with the increase in annealing temperature. These phenomena demonstrate better surface structure and higher crystal quality under the three RTA conditions, especially for the annealing at 873 K. RTA treatment can be an effective way to improve the surface properties of CZT crystals by modifying the technical parameters.

In this study, the mean square consensus problem for stochastic multi-agent systems with nonlinear protocols is concerned. In particular, the topological structure of the system is characterised by...

This study aimed to investigate quantitative inversion of salt ions. Now, most research on hyperspectral characters in salinized soils focus on quantitative inversion of salt content, but few on ions. Original hyperspectral data were collected and calculated average as reflectance (R), the logarithm of the reciprocal of R (Log(1/R)) and continual removed reflectance (Rcr) were also used. Correlations between salt content and ions were calculated, three ions were chosen as characteristic. SVR and PLSR methods were used to derive inversion models. Results showed both methods provided accurate measurement. For modeling precision, no matter which hyperspectral characters based on, inversion models derived with SVR were more accurate than PLSR. For test precision, inversion models derived with SVR were also more accurate. Inversion model of Cl- based on R was the most accurate, followed by that based on Rcr, while the inversion model of K+ based on Rcr was the most accurate. All the inversion models of Na+ based on R, Log(1/R) and Rcr had good test precision. In conclusion, the accuracy of the quantitative inversion model with SVR was higher than PLSR, the best hyperspectral characters for inversion models were chosen, making a useful diagnostic tool for soil salinity.

Although small water clusters (SWCs) are important in many research fields, efficient methods of preparing SWCs are still rarely reported, which is mainly due to the lack of related materials and understanding of the molecular interaction mechanisms. In this study, a series of functional molecules were added in water to obtain small water cluster systems. The decreasing rate of the half-peak width in a sodium dodecyl sulfate (SDS)–water system reaches ≈20% at 0.05 mM from 17O nuclear magnetic resonance (NMR) results. Based on density functional theory (DFT) and molecular dynamics (MD) simulation calculation, it can be concluded that functional molecules with stronger negative electrostatic potential (ESP) and higher hydrophilicity have a stronger ability to destroy big water clusters. Notably, the concentrations of our selected molecule systems are one to two magnitudes lower than that of previous reports. This study provides a promising way to optimize aqueous systems in various fields such as oilfield development, protein stability, and metal anti-corrosion.

Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)—which is closely related to forest productivity, the forest carbon cycle, and, in particular, carbon sinks in forest ecosystems—is calculated and applied as an indicator. Among the existing studies considering AGB estimation, linear or nonlinear regression models are the most frequently used; however, these methods do not take the influence of spatial heterogeneity into consideration. A geographically weighted regression (GWR) model, as a spatial local model, can solve this problem to a certain extent. Based on Landsat 8 OLI images, we use the Random Forest (RF) method to screen six variables, including TM457, TM543, B7, NDWI, NDVI, and W7B6VAR. Then, we build the GWR model to estimate the bamboo forest AGB, and the results are compared with those of the cokriging (COK) and orthogonal least squares (OLS) models. The results show the following: (1) The GWR model had high precision and strong prediction ability. The prediction accuracy (R2) of the GWR model was 0.74, 9%, and 16% higher than the COK and OLS models, respectively, while the error (RMSE) was 7% and 12% lower than the errors of the COK and OLS models, respectively. (2) The bamboo forest AGB estimated by the GWR model in Zhejiang Province had a relatively dense spatial distribution in the northwestern, southwestern, and northeastern areas. This is in line with the actual bamboo forest AGB distribution in Zhejiang Province, indicating the potential practical value of our study. (3) The optimal bandwidth of the GWR model was 156 m. By calculating the variable parameters at different positions in the bandwidth, close attention is given to the local variation law in the estimation of the results in order to reduce the model error.

High-precision profile reconstruction is a key issue in the profile detection and visualization of aero-engine blades. A method based on adaptive step size bat algorithm (ASSBA) for blade profile reconstruction and an adaptive mesh model for visualization analysis of the key machining errors are proposed. Firstly, the original bat algorithm (BA) is improved to introduce the global stage and local search stage. Then, combined with the node layer characteristics of the blade measurement data, the ASSBA is used to fit the optimal surface. Further, the adaptive mesh is planned on the blade profile to extract various evaluation parameters. Finally, the algorithm analysis and verification are carried out based on a certain type of blade. The results show this reconstruction method can get the fitted surface more quickly and accurately than other iterative methods. Simultaneously, the visualization method and corresponding software system can intuitively visualize the blade profile error, the twist deformation error, the swept deformation error, the bending deformation error and the cross-section line profile error.

Fouling is a critical issue faced by the chemical and oil industries in various operation processes, which has negative impact on the operational efficiency and generates significant economic losses, technical and environmental challenges. Investigating the interaction mechanisms between foulants (e.g., fine solids, asphaltenes) and different substrates is of both fundamental and practical importance in understanding the fouling mechanisms in chemical/petroleum engineering processes and developing antifouling strategies. In this work, atomic force microscope (AFM) colloidal probe technique was employed to directly quantify the interactions between silica or asphaltenes and selected substrates (i.e., carbon steel L80 and L80 with electroless nickel-phosphorus (EN) coating) in aqueous solutions. The effects of salinity, pH and presence of divalent ions (e.g., Ca2+) on the surface interactions were investigated. The obtained force profiles showed that the interactions between silica or asphaltenes and L80 surface were more attractive than that between silica or asphaltenes and EN coating, in NaCl solutions. Bulk fouling tests in silica and asphaltenes-coated silica suspensions revealed that significant fouling of silica and asphaltenes were found on L80 substrates, while EN coating exhibited excellent antifouling performance. Our results provide useful insights into the fundamental understanding of the fouling mechanism of fine solids and asphaltenes, and the development of novel effective antifouling coatings in chemical and oil industries.

Antifouling coatings have attracted much attention in applications of industrial equipment and systems. The accumulation of foulants on downhole equipment used in the steam-assisted gravity drainag...

The inhibitory effect of carboxymethyl pachyman (CMP) mixed with lotus seedpod oligomeric procyanidins (LSPC) in certain ratios against E. coli 10899 was determined. Added low concentration of LSPC could improve the antibacterial activity of CMP, and a significant synergistic effect could be observed between them, especially when the concentration of CMP was below its critical concentration (1.35 mg/mL). Then, the interaction between CMP and LSPC was characterized after mixing; the changes in spectral characteristics, thermal properties, crystallinity pattern, molecular weight, chain morphology and microrheological behaviour explained the influence of interaction on the structure of CMP and LSPC. The smaller molecular size, electrostatic interaction and stronger hydrophobic interaction might play important roles in improving the antibacterial activity of mixture. The dissociation constant (Kd) was determined to be 0.102±0.0008 mg/mL using MicroScale Thermophoresis (MST), and the micromorphology was observed by SEM. Therefore, this mixture might be an effective natural bacteriostat.

Microstructured optical fiber based distributed pressure sensor is proposed and demonstrated for high resolution manometry (HRM), which adopts the hybrid wavelength and frequency division multiplexing architecture, and hyperelastic packaging. The microstructure acting as a sensing element is composed of two identical and closely spaced ultrashort fiber Bragg gratings with the reflectivity of only 1%. In theory, 243 microstructures can be multiplexed along one single fiber with an interval of 10 mm beneficial from the compact structure, hybrid encoding feature, and low insertion loss. Homogeneous elastic packaging is explored to protect the fiber and greatly enhance the lateral pressure sensitivity of the sensor. Moreover, a mechanical model is established through the finite element method to analyze the sensitizing effect of the packaging. A prototype system is built and experimentally demonstrated the distributed pressure measurement with the spatial resolution of 10 mm and the pressure sensitivity up to 2.2 Nm/mPa. Due to the advantage of high spatial resolution, high multiplexing capacity, and high pressure sensitivity, the proposed sensor is suitable for HRM in medical application.

The synchronization for reaction-diffusion neural networks with time-varying and distributed delays is concerned in the letter. A mixed pinning impulsive controller is introduced for realizing the synchronization of the neural networks. The novel control method combines the advantages of pinning control as well as two types of impulsive effects (i.e. synchronizing and desynchronizing impulses) such that the control cost is reduced tremendously in practical applications. By applying the generalized comparison principle and average mixed impulsive interval approach, some sufficient criteria are constructed so that response system can be synchronized with corresponding drive system. Finally, two numerical examples are presented to verify the correctness of the obtained results.

A novel Ce-doped magnetic biochar was successfully synthesized by chemical co-precipitation (Ce/FeCP-BC) and solvothermal methods (Ce/FeST-BC) for efficient Sb(V) adsorption. The Ce/FeCP-BC exhibited a high adsorption capacity of 25.0 mg/g, which was two times and one order of magnitude higher than that of Ce/FeST-BC and un-doped BC, respectively. The excellent adsorption performance of Ce/FeCP-BC maintained over a wide pH range or in the presence of coexisting anions. The adsorption results indicated that co-precipitation method was superior to solvothermal method and Ce oxide was the main contribution to Sb(V) adsorption enhancement. The combined results of TEM, XRD, FTIR and XPS revealed that Ce atom was successfully doped into the Fe3O4 structure and abundant hydroxyl groups were formed on the surface of Ce/FeCP-BC. The magnetic performance decreased after Ce doping, but Ce/FeCP-BC still showed good separation potential. Based on the results of batch experiments and physiochemical analyses, the underlying mechanisms controlling Sb(V) adsorption on Ce/FeCP-BC involved the inner-sphere surface complexation, hydrogen bonding, electrostatic attraction and ligand exchange. Among them, the ligand exchange and the formation of Ce–O–Sb complex were the main contributions to the significant Sb(V) adsorption increment on Ce/FeCP-BC. All the results implied that Ce/FeCP-BC could be used as a promising adsorbent for antimonate decontamination.

To improve the biochar’s adsorption performance towards phosphate as well as to endow the biochar with magnetic property, novel rare earth element doped magnetic biochars, Ce/Fe3O4-BC and La/Fe3O4-BC, were prepared by separately co-precipitating cerium (Ce) and lanthanum (La) with FeCl3, FeCl2 and biochar. For comparison, Fe3O4-BC without doping Ce or La was also synthesized. The characterization results indicated that Ce and La ions were successfully doped into the magnetite. The La/Fe3O4-BC had higher magnetic saturation and point of zero charge than Ce/Fe3O4-BC. A series of batch experiment results demonstrated that the phosphate adsorption capacity of biochar has been greatly improved after Ce or La doping, especially La. The phosphate adsorption capacity of La/Fe3O4-BC was 20.5 mg/g at pH 6.5, which was 1.6 and 2.9 times than that of Ce/Fe3O4-BC and Fe3O4-BC, respectively. The adsorption kinetics and isotherms of phosphate onto La/Fe3O4-BC and Ce/Fe3O4-BC were best fitted by the pseudo-second order and Freundich model, respectively, indicating that the adsorption process was a multilayer process and controlled by chemical reaction. The combined results of batch experiments and physiochemical analyses revealed that the possible mechanisms were the formation of inner-sphere complex at neutral conditions and electrostatic attraction between positively charged adsorption sites and phosphate under acid conditions. The enhanced phosphate adsorption performance and endowed magnetic property indicated La/Fe3O4-BC could be used as a promising adsorbent in phosphate removal.

The widespread adoption of mobile devices with global positioning system enables location-based games (LBGs) to use real world maps, while locations and objectives in LBGs can make the progression, achievements, and virtual rewards feel more palpable and entertaining. However, allowing location sharing in LBGs gives dishonest parties opportunities to learn users’ trajectories, which compromises the users’ privacy. In this paper, we propose a novel scheme jointly maximizing LBG players’ virtual rewards while preserving their trajectory privacy. Briefly, we first introduce a quantitative machine learning-based approach to model trajectory inference attacks via tensor voting. Then, to thwart this attack, we propose a tensor voting-based $k$ -anonymous obfuscation strategy. Considering the trajectory privacy concerns and power constraint of hand-held mobile devices, we mathematically formulate the LBG players’ virtual reward maximization optimization into the mixed integer problem and develop the feasible solutions. Simulation results and analysis show that the proposed scheme can effectively preserve LBG players’ trajectory privacy against tensor voting based inference attacks while maximizing LBG players’ virtual rewards.

In this paper, the exponential leader-following consensus problem is investigated for networked multi-agent systems. In order to further reduce the usage of the communication resources, event-triggered delayed impulsive control strategy is put forward, which successfully combines the delayed impulsive control and event-triggered mechanism, and the delayed impulsive controller is implemented only at event-triggered instants. By constructing the novel Lyapunov based event-triggered strategy and impulsive control theory, some easy-to-check conditions are derived such that the error system is exponentially stable. Furthermore, it is shown that the Zeno behavior can be eliminated from the event-triggering rules. Numerical simulation is proposed to illustrate the effectiveness of the theoretical results.

Abutment pressure distribution is different when a longwall panel is passing through the abandoned gate roads in a damaged coal seam. According to the geological condition of panel E13103 in Cuijiazhai Coal Mine in China, theoretical analysis and finite element numerical simulation were used to determine the front pressure distribution characteristics when the longwall face is 70, 50, 30, 20, 10, and 5 m from the abandoned roadways. The research results show that the influence range of abutment pressure is 40 to 45 m outby the face, and the peak value of front abutment pressure is related to the distance between the face and abandoned roadways. When the distance between the longwall face and abandoned roadways is reduced from 50 to 10 m, the front abutment pressure peak value kept increasing. When the distance is 10 m, it has reached the maximum. The peak value is located in 5 to 6 m outby the faceline. When the distance between the longwall face and abandoned roadways is reduced from10 to5 m, the front abutment pressure sharply decreases, the intact coal yields and is even in plastic state. The peak value transfers to the other side of the abandoned roadways. The research results provide a theoretical basis for determining the advance support distance of two roadways in the panel and the reinforcement for face stability when the longwall face is passing through the abandoned roadways. Keywords: Abandoned roadways, Abutment pressure, Theoretical calculation, Numerical simulation

Cu2Se is considered as a potential thermoelectric material due to its excellent electrical properties and relatively high ZT values. However, the temperature-dependent phase transition and expensive experimental preparation approach hamper its practical application. In this work, a series of Cu2Se1-xIx (x = 0, 0.02, 0.03, 0.04, 0.05) alloys were prepared by using the cheap and facile hydrothermal method in combination with vacuum hot pressing. The crystal structures of synthesized Cu2Se1-xIx (x ≤ 0.04) are identical to the cubic β-Cu2Se. By doping with iodine, the thermoelectric figure of merit of Cu2Se could be greatly improved up to 1.1 at 773 K and the phase transition temperature was reduced to 380 K. Our results suggest a promising route to optimize the performance of Cu2Se-based materials for high performance thermoelectric applications.

Smart homes (SHs) aim at forming an energy optimized environment that can efficiently regulate the use of various Internet of Things (IoT) devices in its network. Real-time electricity pricing models along with SHs provide users an opportunity to reduce their electricity expenditure by responding to the pricing that varies with different times of the day, resulting in reducing the expenditure at both customers’ and utility provider’s end. However, responding to such prices and effectively scheduling the appliances under such complex dynamics is a challenging optimization problem to be solved by the provider or by third party services. As communication in SH-IoT environment is extremely sensitive and private, reporting of such usage information to the provider to solve the optimization has a potential risk that the provider or third party services may track users’ energy consumption profile which compromises users’ privacy. To address these issues, we developed a homomorphic encryption-based alternating direction method of multipliers approach to solve the cost-aware appliance scheduling optimization in a distributed manner and schedule home appliances without leaking users’ privacy. Through extensive simulation study considering real-world datasets, we show that the proposed secure appliance scheduling for flexible and efficient energy consumption scheme, namely SAFE, effectively lowers electricity cost while preserving users’ privacy.

A novel La-doped magnetic biochar was synthesized by a co-precipitation method for efficient Sb(V) removal. In contrast to pristine biochar and un-doped magnetic biochar, the Sb(V) adsorption capacity in La-doped magnetic biochar was greatly improved, increasing from 2.22 mg/g and 4.85 mg/g to 18.92 mg/g at pH of 7.0, respectively. The enhanced Sb(V) adsorption remained over a wide pH range (2–10), despite the existence of Cl−, SO42−, NO3−, HCO3−, or H2PO4−. These competing anions had little interference with Sb(V) sorption except HCO3− and H2PO4−. The combined results of TEM, XRD, FTIR and XPS further confirmed that La atom was successfully doped into the Fe3O4 structure. The point of zero charge of the biochar increased accordingly with a number of hydroxyl groups (i.e. La OH) formed on the surface. Although the magnetic performance decreased after La doping, La-doped magnetic biochar still showed high separation potential. The comparison of FTIR and XPS analyses before and after Sb(V) adsorption revealed that the formation of inner-sphere La O Sb complex was the dominant contribution for Sb(V) sorption enhancement. Meanwhile, other mechanisms such as hydrogen bonding, electrostatic attraction and ligand exchange were also involved. All the results suggested that La-doped magnetic biochars could serve as promising adsorbents for Sb(V) pollution minimization.

This paper presents an uncertainty analysis of subjective thermal comfort measurement, which was overlooked in some subjective thermal comfort studies. Three chamber experiments were conducted to collect the data and to analyze how the uncertainty of subjective measurement is influenced by the survey instrument and the experiment protocol. Four widely-utilized subjective indicators were examined: thermal sensation, humidity sensation, draught sensation and thermal satisfaction. It was found that the Standard Uncertainty, defined as the Standard Error of the Mean, of subjective thermal comfort measurement would decrease with the increasing number of person-votes (number of subjects times votes per subject). When the person-votes were above 40, the Standard Uncertainty of subjective measurement was within 3% of the total scale length, confirming the precision and reliability of subjective thermal comfort measurement. It was found the measurement of thermal sensation/satisfaction and humidity sensation had similar uncertainty level, while the measurement of draught sensation had higher uncertainty. Discrete multiple-points scales (Likert) are recommended for subjective thermal comfort measurement since continuous scales enlarge intra-individual differences.

The threats faced by cyber-physical systems (CPSs) in critical infrastructure have motivated research into a multitude of attack detection mechanisms, including anomaly detectors based on neural network models. The effectiveness of anomaly detectors can be assessed by subjecting them to test suites of attacks, but less consideration has been given to adversarial attackers that craft noise specifically designed to deceive them. While successfully applied in domains such as images and audio, adversarial attacks are much harder to implement in CPSs due to the presence of other built-in defence mechanisms such as rule checkers(or invariant checkers). In this work, we present an adversarial attack that simultaneously evades the anomaly detectors and rule checkers of a CPS. Inspired by existing gradient-based approaches, our adversarial attack crafts noise over the sensor and actuator values, then uses a genetic algorithm to optimise the latter, ensuring that the neural network and the rule checking system are both deceived.We implemented our approach for two real-world critical infrastructure testbeds, successfully reducing the classification accuracy of their detectors by over 50% on average, while simultaneously avoiding detection by rule checkers. Finally, we explore whether these attacks can be mitigated by training the detectors on adversarial samples., Accepted by the International Journal of Critical Infrastructure Protection (IJCIP)

Aiming at the shortcomings of general CNN wellbore fault identification models that require a large number of samples and low recognition accuracy, this paper proposes a wellbore fault diagnosis model based on the combination of ResNet34 and transfer learning. Migrate the ResNet34 pre-training model to the image data set of four kinds of wellbore faults for training, extract the features of the wellbore fault images, use the feature values as the input of the fully connected neural network classifier, and then classify and identify the data set, which improves the accuracy and training speed of this model. The experimental data in this paper uses the wellbore fault images of an oil field in Shandong obtained by the VideoLog visualization logging platform. The experimental results show that the recognition accuracy of ResNet is 99.2%, which is 8.9% higher than that of MobileNet, indicating ResNet34 has high accuracy in wellbore fault identification.

A critical issue is how to obtain the accurate ranging value in the context of non-line-of-sight (NLOS) for Ultra Wide Band (UWB). The multiple distance relationship based on the relative position relationship of the UWB devices is proposed to process the NLOS error in this paper. Firstly, zero-crossing analysis and bilateral filtering (BLF) are combined to smooth the measurement error. Then, the sequences of the multiple distances relationship for the ranging data are calculated, and the thresholds of the NLOS error detection process are determined. Finally, the NLOS error is detected and processed by the the multiple distances relationship in two different ways of extracting data, and the two results are added according to the corresponding weights. The actual measurement results demonstrated that the method can effectively suppress the NLOS error under three different situations. The approach presented in this paper can be used as an effective processing means for the UWB ranging.

Functionalized oligonucleotides (ONs) are widely applied as target binding molecules for biosensing and regulators for gene expression. Numerous efforts have been focused on developing facile methods for preparing these useful ONs carrying diverse modifications. Herein, we present a general method for postsynthetic modification of ONs via oxidative amination of 4-thio-2'-deoxyuridine (4SdU). 4SdU-containing ON can be derived by both alkyl and aromatic amines. Using this approach, ONs are successfully attached with alkyne/azide, biotin and dansylamide moieties, and these as-prepared ONs possess the expected biorthogonal reactivity, streptavidin affinity and fluorescent property, respectively. Furthermore, we also directly install fluorophores to the ON nucleobase based on oxidative amination of 4SdU, and these fluorophores exhibit distinct luminescence behaviors before and after conjugation. We believe our method will be a versatile strategy for constructing various functionalized ONs used in a wide range of nucleic acid applications.

Blockchain-based crowdsourcing systems can mitigate some known limitations of the centralized crowdsourcing platform, such as single point of failure and Sybil attacks. However, blockchain-based crowdsourcing systems still endure the issues of privacy and security. Participants’ sensitive information (e.g., identity, address, and expertise) have the risk of privacy disclosure. Sensitive crowdsourcing tasks such as location-based data collection and labeling images including faces also need privacy-preserving. Moreover, current work fails to balance the anonymity and public auditing of workers. In this paper, we present a secure blockchain-based crowdsourcing framework with fine-grained worker selection, named PrivCrowd which exploits a functional encryption scheme to protect the data privacy of tasks and to select workers by matching the attributes. In PrivCrowd, requesters and workers can achieve both exchange and evaluation fairness by calling smart contracts. Solutions collection also can be done in a secure, sound, and noninteractive way. Experiment results show the feasibility, usability, and efficiency of PrivCrowd.

We propose a spurious region guided refinement approach for robustness verification of deep neural networks. Our method starts with applying the DeepPoly abstract domain to analyze the network. If the robustness property cannot be verified, the result is inconclusive. Due to the over-approximation, the computed region in the abstraction may be spurious in the sense that it does not contain any true counterexample. Our goal is to identify such spurious regions and use them to guide the abstraction refinement. The core idea is to make use of the obtained constraints of the abstraction to infer new bounds for the neurons. This is achieved by linear programming techniques. With the new bounds, we iteratively apply DeepPoly, aiming to eliminate spurious regions. We have implemented our approach in a prototypical tool DeepSRGR. Experimental results show that a large amount of regions can be identified as spurious, and as a result, the precision of DeepPoly can be significantly improved. As a side contribution, we show that our approach can be applied to verify quantitative robustness properties.

Fungal contamination in drinking water source has become a problem worth studying, as waterborne fungi may cause deterioration of water quality and outbreak of diseases. Various disinfection methods have been explored to control fungal spores in drinking water, such as chlor(am)ination, ozonation, chlorine dioxide treatment, but these methods are not appropriate for remote areas, owing to the difficulties in preparation, carriage and storage. In this study, a powdery disinfectant of 1-bromo-3-chloro-5,5-dimethylhydantoin (BCDMH), which facilitated transportation and preservation, was firstly chosen to inactivate opportunistic pathogens of Aspergillus niger (A. niger) and Penicillium polonicum (P. polonicum). The results revealed that the inactivation kinetics of fungal spores by BCDMH fitted to Chick-Watson model well, with the inactivation rate constant of 0.011 and 0.034 L mg−1 min−1 for A. niger and P. polonicum, respectively. Acidic condition and high temperature promoted the inactivation by BCDMH. Compared with chlorine, BCDMH showed relative weaker ability on inactivation of fungal spores. However, it was demonstrated that the inactivation efficiency of BCDMH was obviously enhanced by adding halide ions, with 11 or 36 folds for A. niger and 4 or 15 folds for P. polonicum by adding 40 μM Br− or I−. The inactivation mechanisms were detected by flow cytometry and scanning electron microscope. Fungal spores lost their culturability firstly, then membrane integrity was damaged. Meanwhile, the esterase activity and intracellular reactive oxygen species level changed, and finally intracellular adenosine triphosphate released.

Public AI-as-a-Service (AIaaS) is a promising next-generation computing paradigm that attracts resource-limited mobile users to outsource their machine learning tasks. However, the time delay between cloud/edge servers and end users makes it hard for real-time mobile artificial intelligence applications. In this paper, we propose a real-time mobile facial expression tracking framework combining AIaaS and mobile local auxiliary computing, including facial expression tracking and the corresponding task offloading. Mobile facial expression tracking estimates the facial expression of the current frame with the help of sparse optical flow and neural network. Task offloading utilizes neural network to dynamically estimate the moment of task offloading. According to the experimental results in a real-world environment, the proposed framework successfully fulfills the mobile real-time facial expression tracking requirements with high accuracy. Moreover, compared to its benchmark, it effectively reduces the power consumption of mobile devices and the potential service cost for AIaaS.

The effect of Mn impregnation on the NH3-SCR (selective catalytic reduction of NOx by NH3) activity of in situ synthesized Cu-SSZ-13 was investigated in this work. It was found that Mn addition could efficiently improve the low-temperature activity of Cu-SSZ-13. The optimal amount of Mn was 5 wt.%, and NOx conversion was improved by more than 20% over a temperature range of 120 &deg, C to 150 &deg, C. SEM (scanning electron microscopy), XRD (X-ray diffraction), N2 adsorption-desorption, H2-TPR (temperature programmed reduction of H2), NH3-TPD (temperature programmed desorption of NH3) and in situ DRIFTS (diffuse reflectance infrared Fourier transform spectroscopy) experiments were conducted to investigate the changes in the zeolite structure, active sites, acid sites and reaction mechanism. The impregnated MnOx species caused a decline in the crystallinity of Cu-SSZ-13 but markedly improved the redox ability. Nitrate and nitrite species were observed in the Mn-modified Cu-SSZ-13, and the formation of these species was thought to cause the observed increase in low-temperature NH3-SCR activity. The results show that the addition of Mn is a promising method for promoting the low-temperature catalytic activity of Cu-SSZ-13.

Electrochemical techniques are very useful tools for characterizing the surface properties of natural minerals involved in electrochemical reactions. This work reviews the recent advances in electrochemical characterizations of minerals by employing various electrochemical techniques, i.e., open circuit potential, chronoamperometry, potential sweep voltammetry, electrochemical impedance spectroscopy, and electrochemical scanning probe techniques. The fundamental working principles of these electrochemical techniques and their applications for mineral surface characterizations in various research areas, including mineral flotation, mineral leaching, electrocatalysis, energy storage materials and environmental issues, are highlighted. Valuable information such as the redox condition of substrate surface, the current response of substrate with time under polarization, the identification of redox reaction and its kinetics on substrate surface, the structure of substrate/electrolyte interface, and the local electrochemical response on substrate surface at micro-/nano-scale can be obtained by open circuit potential, chronoamperometry, potential sweep voltammetry, electrochemical impedance spectroscopy, and scanning electrochemical microscopy, respectively. Some remaining challenges and future perspectives are discussed. These recent advances in electrochemical techniques can be readily applied to characterize the surface properties and interfacial interactions of a wide variety of material systems and in different engineering processes.