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Magnesium hydride (MgH2) is a potential material for solid-state hydrogen storage. However, the thermodynamic and kinetic properties are far from practical application in the current stage. In this work, two-dimensional vanadium carbide (V2C) MXene with layer thickness of 50−100 nm was fist synthesized by selectively HF-etching the Al layers from V2AlC MAX phase and then introduced into MgH2 to improve the hydrogen sorption performances of MgH2. The onset hydrogen desorption temperature of MgH2 with V2C addition is significantly reduced from 318 °C for pure MgH2 to 190 °C, with a 128 °C reduction of the onset temperature. The MgH2 + 10 wt% V2C composite can release 6.4 wt% of H2 within 10 min at 300 °C and does not loss any capacity for up to 10 cycles. The activation energy for the hydrogen desorption reaction of MgH2 with V2C addition was calculated to be 112 kJ mol−1 H2 by Arrhenius's equation and 87.6 kJ mol−1 H2 by Kissinger's equation. The hydrogen desorption reaction enthalpy of MgH2 + 10 wt% V2C was estimated by van't Hoff equation to be 73.6 kJ mol−1 H2, which is slightly lower than that of the pure MgH2 (77.9 kJ mol−1 H2). Microstructure studies by XPS, TEM, and SEM showed that V2C acts as an efficient catalyst for the hydrogen desorption reaction of MgH2. The first-principles density functional theory (DFT) calculations demonstrated that the bond length of Mg−H can be reduced from 1.71 A for pure MgH2 to 2.14 A for MgH2 with V2C addition, which contributes to the destabilization of MgH2. This work provides a method to significantly and simultaneously tailor the hydrogen sorption thermodynamics and kinetics of MgH2 by two-dimensional MXene materials.

Hydrogen can serve as a carrier to store renewable energy in large scale. However, hydrogen storage still remains a challenge in the current stage. It is difficult to meet the technical requirements applying the conventional storage of compressed gaseous hydrogen in high-pressure tanks or the solid-state storage of hydrogen in suitable materials. In the present work, a gaseous and solid-state (G-S) hybrid hydrogen storage system with a low working pressure below 5 MPa for a 10 kW hydrogen energy storage experiment platform is developed and validated. A Ti–Mn type hydrogen storage alloy with an effective hydrogen capacity of 1.7 wt% was prepared for the G-S hybrid hydrogen storage system. The G-S hybrid hydrogen storage tank has a high volumetric hydrogen storage density of 40.07 kg H2 m−3 and stores hydrogen under pressure below 5 MPa. It can readily release enough hydrogen at a temperature as low as −15 °C when the FC system is not fully activated and hot water is not available. The energy storage efficiency of this G-S hybrid hydrogen storage system is calculated to be 86.4%–95.9% when it is combined with an FC system. This work provides a method on how to design a G-S hydrogen storage system based on practical demands and demonstrates that the G-S hybrid hydrogen storage is a promising method for stationary hydrogen storage application.

During the refining of Si deoxidized spring steel by low-basicity slag, with the addition of BaCO3 to refining slag, many BaO-containing CaO-SiO2-Al2O3 inclusions existed in steel, which were with approximate chemical compositions to other CaO-SiO2-Al2O3 inclusions. Thermodynamic calculation revealed that (BaO) in slag can be hardly reduced by [Si] in steel, which meant that CaO-SiO2-Al2O3-BaO inclusions in Si-deoxidized spring steel cannot be produced by chemical reactions among slag-steel-inclusion, viz., they were originated from entrapped slag.

This study presents a novel cylindrical vane pump based on the traditional working principle. The efficiency of the cylindrical vane pump was verified by experimental validation and numerical analysis. Numerical analysis, such as kinematics analysis, was performed in Pro/Mechanism and unsteady flow-field analysis was performed using ANSYS FLUENT. The stator surface equations were derived using the geometric theory of the applied spatial triangulation function. A three-dimensional model of the cylindrical vane pump was established with the help of MATLAB and Pro/E. The kinematic analysis helped in developing kinematic equations for cylindrical vane pumps and proved the effectiveness of the structural design. The maximum inaccuracy error of the computational fluid dynamics (CFD) model was 5.7% compared with the experimental results, and the CFD results show that the structure of the pump was reasonable. An experimental test bench was developed, and the results were in excellent agreement with the numerical results of CFD. The experimental results show that the cylindrical vane pump satisfied the three-element design of a positive-displacement pump and the trend of changes in efficiency was the same for all types of efficiency under different operating conditions. Furthermore, the volumetric efficiency presented a nonlinear positive correlation with increased rotational velocity, the mechanical efficiency showed a nonlinear negative correlation, and the total efficiency first increased and then decreased. When the rotational velocity was 1.33[Formula: see text] and the discharge pressure was 0.68[Formula: see text], the total efficiency reached its maximum value.

Hydrogen-atom-transfer (HAT) is an efficient way for direct C H functionalization of inert C H bonds, therefore it has attracted great interests in recent years. So far, various HAT catalysts have been developed. Among them, quinuclidine and its derivatives show different characters toward other HAT catalysts as they tend to abstract electron-rich and hydridic hydrogens in the presence of weak and neutral C H bonds. These features enable direct C H functionalization of compounds with various groups which are unable or difficult by other methods. This review summarizes recent advance of photoinduced reactions with quinuclidine and its derivatives as HAT catalysts and exhibits powerful synthetic potential by using quinuclidine and its derivatives as HAT catalysts.

Full frequency reuse with nonorthogonal multiple access (NOMA) in heterogeneous networks (HetNets) can promisingly satisfy the fast-growing wireless transmission requirements, as the data of different users can be simultaneously delivered over the same frequency band. In HetNets, the transmissions from a micro base station (BS) to its cell-edge users often suffer from strong interference from the macro BS, which severely degrades the communication quality. The macro BS and the micro BS can transmit simultaneously to a common far-user using the distributed Alamouti coding technique to improve the communication robustness. Meanwhile, each BS also transmits data to a near-user using the NOMA protocol. The common far-user adopts the maximal ratio combining (MRC) technique to decode its desired data by treating the data of near users as interference. Each near-user decodes the data of far-user using the MRC technique and cancels it to decode its own data by treating the remaining undesired data as interference. Numerical results show that the Alamouti coding based NOMA transmission can greatly improve the throughput of HetNets.

At present, the UAV swarm positioning solution has the problems of poor positioning accuracy and instability. Therefore, it is necessary to design a sliding mode formation controller to realize formation. This study analyzes the self-service control strategy of the UAV swarm and establishes the behavior-based formation control strategy as the main research point of this article. This paper combines the Internet of Things and artificial intelligence algorithms to build an autonomous control model for the UAV swarm and designs the UAV formation control law from the disturbed and undisturbed conditions respectively. With reference to the basic architecture of the Internet of Things, this study imitates ZigBee’s self-organizing network to propose an adaptive networking scheme based on the Internet of Things by using the AP+STA working mode of the Internet of Things module in the node device. The results of the experiment show that the positioning accuracy of the UAV is high, which can meet the needs of cluster flight. Based on the Z-axis coordinates of the UAV, the accuracy of the laser distance measurement and the barometer value is significantly improved, the root mean square error is reduced, and the positioning result is significantly better than the data of direct traditional positioning.

Two-dimensional vanadium carbide (V2C) and titanium carbide (Ti3C2) MXenes were first synthesized by exfoliating V2AlC or Ti3AlC2 and then introduced jointly into magnesium hydride (MgH2) to tailor the hydrogen desorption/absorption performances of MgH2. The as-prepared MgH2-V2C-Ti3C2 composites show much better hydrogen storage performances than pure MgH2. MgH2 with addition of 10 wt % of 2V2C/Ti3C2 initiates hydrogen desorption at around 180 °C; 5.1 wt % of hydrogen was desorbed within 60 min at 225 °C, while 5.8 wt % was desorbed within 2 min at 300 °C. Under 6 MPa H2, the dehydrided MgH2-2V2C/Ti3C2 can start to recover hydrogen at room temperature, and 5.1 wt % of H2 is obtained within 20 s at a constant temperature of 40 °C. The reversible capacity (6.3 wt %) does not decline for up to 10 cycles, which shows excellent cycling stability. The addition of 2V2C/Ti3C2 can remarkably lower the activation energy for the hydrogen desorption reaction of MgH2 by 37% and slightly reduce the hydrogen desorption reaction enthalpy by 2 kJ mol-1 H2. It was demonstrated that the combination of V2C and Ti3C2 promotes the hydrogen-releasing process of MgH2 compared with addition of only V2C or Ti3C2, while Ti3C2 impacts MgH2 more significantly than V2C in the hydrogen absorption process of MgH2 at ambient temperatures. A possible mechanism in the hydrogen release and uptake of the MgH2-V2C-Ti3C2 system was proposed as follows: hydrogen atoms or molecules may preferentially transfer through the MgH2/V2C/Ti3C2 triple-grain boundaries during the desorption process and through the Mg/Ti3C2 interfaces during the absorption process. Microstructure studies indicated that V2C and Ti3C2 mainly act as efficient catalysts for MgH2. This work provides an insight into the hydrogen storage behaviors and mechanisms of MgH2 boosted by a combination of two MXenes.

The formation mechanism of the partially crystallized ultrathin layer at the interface between GaN and SiNx grown by low-pressure chemical vapor deposition was analyzed based on the chemical components of reactants and products detected by high-resolution sputter depth profile analysis by X-ray photoelectron spectroscopy. A reasonable mass action equation for the formation of Si2N2O was proposed from the feasibility analysis of the Gibbs free energy changes of the reaction. The high-energy-activated Ga2O on the surface likely assists in the synthesis of the crystallized components. A well-defined 1ML θ-Ga2O3 transition interface was inserted into Si2N2O/GaN pure interface supercell slabs to edit the unsaturated state of the bonds. Low-density states can be achieved when the effective charges of the unsaturated atoms are adjusted to a certain interval.

We investigate the long-term scheduling and power control scheme for a wirelessly powered cell-free Internet-of-Things (IoT) network which consists of distributed access points (APs) and a large number of sensors. In each time slot, a subset of sensors is scheduled for uplink data transmission or downlink power transfer. Through asymptotic analysis, we obtain closed-form expressions for the harvested energy and the achievable rates that are independent of random pilots. Then, using these expressions, we formulate a long-term scheduling and power control problem to maximize the minimum time-average achievable rate among all sensors while maintaining the battery state of each sensor higher than a predefined minimum level. Using Lyapunov optimization, the transmission mode, the active sensor set, and the power control coefficients for each time slot are jointly determined. Finally, simulation results validate the accuracy of our derived closed-form expressions and reveal that the minimum time-average achievable rate is boosted significantly by the proposed scheme compared with the simple greedy transmission scheme.

Aluminum hydride (AlH3) is a binary metal hydride that contains more than 10.1 wt% of hydrogen and possesses a high volumetric hydrogen density of 148 kg H2 m−3. Pristine AlH3 can readily release hydrogen at a moderate temperature below 200 °C. Such high hydrogen density and low desorption temperature make AlH3 one of most promising hydrogen storage media for mobile application. This review covers the research activity on the structures, synthesis, decomposition thermodynamics and kinetics, regeneration and application validation of AlH3 over the past decades. Finally, the future research directions of AlH3 as a hydrogen storage material will be revealed.

The chain-like carbon nanotubes (CNTs) decorated with CoFeB (CoFeB/CNTs) prepared by oxidation-reduction method is introduced into MgH2 to facilitate its hydrogen storage performance. The addition of CoFeB/CNTs enables MgH2 to start desorbing hydrogen at only 177 °C. Whereas pure MgH2 starts hydrogen desorption at 310 °C. The dehydrogenation apparent activation energy of MgH2 in CoFeB/CNTs doped-MgH2 composite is only 83.2 kJ/mol, and this is about 59.5 kJ/mol lower than that of pure MgH2. In addition, the completely dehydrogenated MgH2−10 wt% CoFeB/CNTs sample can start to absorb hydrogen at only 30 °C. At 150 °C and 5 MPa H2, the MgH2 in CoFeB/CNTs doped-MgH2 composite can absorb 6.2 wt% H2 in 10 min. The cycling kinetics can remain rather stable up to 20 cycles, and the hydrogen storage capacity retention rate is 98.5%. The in situ formation of Co3MgC, Fe, CoFe and B caused by the introduction of CoFeB/CNTs can provide active and nucleation sites for the dehydrogenation/rehydrogenation reactions of MgH2. Moreover, CNTs can provide hydrogen diffusion pathways while also enhancing the thermal conductivity of the sample. All of these can facilitate the dehydrogenation/rehydrogenation performance and cyclic stability of MgH2.

Massive rare earth oxides inevitably form at high La–Ce substitution, causing inadequate liquid-phase-sintering, direct exchange coupling of ferromagnetic grains, obscure core–shell morphology and severe coercivity degradation of multi-main-phase (MMP) Nd–La–Ce–Fe–B sintered magnets. To fully exploit the abundant La–Ce for application, here we designed a facile approach, (Pr, Nd)Hx grain boundary diffusion that combines the joint benefits of forming thick non-ferromagnetic grain boundary layer and PrNd-rich hardening shell, yielding a nearly threefold coercivity of 14.2 kOe with enhanced energy product of 38.5 MGOe for LaCe-40 magnet. These findings suggest a reliable recipe for relieving the main constraints of MMP Nd–La–Ce–Fe–B magnets.

In this paper, an extended signal-correction observer (ESCO) is presented for signals correction and estimation, which not only can reject the large measurement error, but also the system uncertainty can be estimated, in spite of the existence of intense stochastic non-Gaussian noise. Multi-input describing function method is proposed to analyze the ESCO robustness in frequency domain. The ESCOs are developed for position/velocity and attitude angle/angular rate integrations, respectively, and they are applied to an aircraft navigation. Based on the ESCO, the position, attitude angle, and the uncertainties in the flight dynamics are estimated. Experiments demonstrate the effectiveness of the proposed method.

This article presents the blade coating analysis of viscous nanofluid passing over a porous substrate using a flexible blade coater. Water-based copper nanoparticles are considered to discuss the blade coating process. The lubrication approximation theory is applied to develop the flow equations. The analytical solution is obtained for velocity, volumetric flow rate, and pressure gradient, while shooting method is applied to obtain the pressure, thickness, and load. Different models for dynamic viscosity have been applied to observe the impact of related parameters on pressure, pressure gradient, and velocity. These results are presented graphically. Interesting engineering quantities such as load, deflection, and thickness are computed numerically and are shown in the tabulated form. It is found that nanoparticle volume fraction increases the pressure gradient, pressure and has minor effects on velocity. For model 1, an increase in the volume fraction reduces the coating thickness, load, and deflection, while model 2 has opposite effects on the mentioned quantities. Also, model 2 has a greater impact on pressure and pressure gradient when compared to model 1.

In order to improve the hydrogen storage performance of MgH2, graphene and CeF3 co-catalyzed MgH2 (hereafter denoted as MgH2+CeF3@Gn) were prepared by wet method ball milling and hydriding, which is a simple and time-saving method. The effect of CeF3@Gn on the hydrogen storage behavior of MgH2 was investigated. The experimental results showed that co-addition of CeF3@Gn greatly decreased the hydrogen desorption/absorption temperature of MgH2, and remarkably improved the dehydriding/hydriding kinetics of MgH2. The onset hydrogen desorption temperature of Mg + CeF3@Gn is 232 °C，which is 86 °C lower than that of as-milled undoped MgH2, and its hydrogen desorption capacity reaches 6.77 wt%, which is 99% of its theoretical capacity (6.84 wt%). At 300 °C and 200 °C the maximum hydrogen desorption rates are 79.5 and 118 times faster than that of the as-milled undoped MgH2. Even at low temperature of 150 °C, the dedydrided sample (Mg + CeF3@Gn) also showed excellent hydrogen absorption kinetics, it can absorb 5.71 wt% hydrogen within 50 s, and its maximum hydrogen absorption rate reached 15.0 wt% H2/min, which is 1765 times faster than that of the undoped Mg. Moreover, no eminent degradation of hydrogen storage capacity occurred after 15 hydrogen desorption/absorption cycles. Mg + CeF3@Gn showed excellent hydrogen de/absorption kinetics because of the MgF2 and CeH2-3 that are formed in situ, and the synergic catalytic effect of these by-products and unique structure of Gn.

The co-combustion characteristics of coal, two types of carbonaceous wastes (HDPE and scrap tire) and their blends were investigated in this study via a non-isothermal thermogravimetric met...

Satellite images with different spatial resolutions are widely used in the observations of floating macroalgae booms in sea surface. In this study, semi-synchronous satellite images with different resolutions (10 m, 16 m, 30 m, 50 m, 100 m, 250 m and 500 m) acquired over the Yellow Sea, are used to quantitatively assess the effects of spatial resolution on the observation of floating macroalgae blooms of Ulva prolifera. Results indicate that the covering area of macroalgae-mixing pixels (MM-CA) detected from high resolution images is smaller than that from low resolution images, however, the area affected by macroalgae blooms (AA) is larger in high resolution images than in low resolution ones. The omission rates in the MM-CA and the AA increase with the decrease of spatial resolution. These results indicate that satellite remote sensing on the basis of low resolution images (especially, 100 m, 250 m, 500 m), would overestimate the covering area of macroalgae while omit the small patches in the affected zones. To reduce the impacts of overestimation and omission, high resolution satellite images are used to show the seasonal changes of macroalgae blooms in 2018 and 2019 in the Yellow Sea.

The behavior of dual-phase (MnO-SiO2-Al2O3) + (SiO2) inclusions in saw wire steels during hot rolling and cold drawing was investigated in detail. It was found that the inclusion matrix (glassy MnO-SiO2-Al2O3 (silicate)) manifested rheological properties and the precipitated SiO2 experienced poor deformation in hot rolling. After multi-pass hot rolling, these two phases gradually became separated from each other. The former was elongated into a thin strip, whereas the shape of the latter was deformed from spherical to ellipsoid. Despite their distinctive deformability during hot rolling, MnO-SiO2-Al2O3 and SiO2 were both crushed into smaller pieces during cold drawing. With the proceeding of drawing, shattered pieces became tiny and their interspaces were enlarged, thus causing a reduction in filament breakage. Based on these findings, inclusions were categorized by their melting points and Young’s moduli. Hence, the effects of inclusions on saw wires fabricated by hot rolling and cold drawing were more quantitatively evaluated, and the obtained results were found to be in good agreement with industrial findings.

A mathematical study of an Oldroyd 4-constant fluid for a blade coating process is studied in this paper. The results for plane as well as exponential coaters are analyzed. Suitable dimensionless variables are used to convert the model governing equations into dimensionless form. Lubrication approximation theory is applied to simplify the dimensionless form of governing partial differential equations. The well-known numerical technique known as the shooting method is used to solve the non-linear boundary value problem. Influence of the involved rheological parameters on the blade coating process is analyzed. From an engineering point of view, load on the blade and pressure are important outcomes of the present study as they ensure the thickness and quality of coating and enhance the life of the substrate. The effects of material parameters on load, thickness, velocity, pressure and pressure gradient are discussed. Obtained results for velocity, pressure gradient and pressure distribution are shown graphically, whereas load and thickness are expressed in a tabulated form.

Mixed chemical wastewaters in industrial parks contain a large number of non-degradable pollutants, and the advanced treatment process after biological treatment is required to meet the strict discharge requirement. In this study, the cost-effective powdered activated coke was used to remove chemical oxygen demand (COD) from the biological effluent in a chemical wastewater treatment plant in pilot-scale experiments. The powdered activated coke showed higher COD removal than different activated carbons, and the adsorption equilibrium was reached within 20 min. When the initial COD values in the biological effluent were in the range of 140–180 mg/L, the final COD in the treated wastewater decreased to below 80 mg/L with the powdered activated coke dose of 0.609 g/L. Moreover, the spent powdered activated coke was regenerated using Fenton oxidation and reused in the adsorption cycles. The spent activated coke was successfully regenerated at 150 mg/L H2O2 and 1.10 mmol/L Fe2+ at pH 4 for 30 min, and the activated coke still maintained 65.6% regeneration efficiency after six adsorption-regeneration cycles. This study demonstrated that activated coke adsorption was an effective and feasible advanced treatment method for the removal of COD from the mixed chemical wastewaters.

This study investigated the combustion characteristics and kinetics of sewage sludge (SS), wheat straw (WS) and their blends using thermogravimetric analysis, under air condition. Combustion characteristic parameters of SS blended with 5%–50% WS was enhanced, especially revealed by an increase in comprehensive combustion index. A significant synergetic interaction was found in high temperature region through experiments. When proportion of WS was 50%, the synergetic interaction was strongest. And the catalytic effect of alkali metal oxides in WS ash on the combustion of SS residues at high temperature region had a strong effect on synergetic interaction. Metal oxides circulated in different oxide forms to transport oxygen to carbon surface, leading to catalytic effect. Activation energy was evaluated by two isoconversional method: Flynn-Wall-Ozawa and Vyazovkin method. The lowest average activation energies of the blends were obtained at 50% wheat straw blending ratio (89.29 kJ/mol by FWO and 87.48 kJ/mol by V, respectively). The thermodynamic parameters (Gibbs free energy, Entropy and Enthalpy) were also obtained. And two master plots methods were utilized to determine the appropriate fit kinetic model of combustion which can be described by Avarami-Erofeve (A2).

Natural gas leakage from gas pipelines usually leads to human intoxication. Further, it may even cause fires and/or explosion accidents or make an indirect chemical contribution to climate change in the long term because of its high global-warming potential. As a clean, potential, and effective method for controlling/mitigating the risk of natural gas leakage, water mist is tested to suppress gas jet leakage from a lab-scale pipe in this study. Based on actual natural gas leakages in pipelines or practical emergency management measures, both tilted and non-tilted gas jet cases were considered to evaluate the performance of gas jet suppression by water mist. A series of small-scale experiments has been conducted to deepen the understanding of the dynamical behavior and mechanisms of the gas jet–water mist interaction by visualizing the two-phase flow via planar particle image velocimetry. The results indicate that different shapes of leakage nozzles with a similar effective diameter are highly consistent regarding the interacting flow field characteristics. In addition, guidelines for optimizing a water mist system for leakage gas suppression/control are presented based on gas–spray momentum ratio and dimensionless gas jet suppression height analyses. Owing to the lack of applications on natural gas leakage with water mist, this study is valuable toward optimizing water mist systems for leakage gas suppression/control of such applications.

Currently, it is reported that approximately 1000 occupational injuries, especially the front-line miners occurring the coal industry of China in 2015. Previous researches have indicated that miners’ unsafe behavior is the predominant reason of safety accidents and listed numerous factors which influence their behavior. Owing to the complexities of the relationship among these influencing factors in the coal industry, the improvement of coal mine safety level is still facing enormous challenges. With an aim towards exploring and sorting the influencing factors for increasing safety behavior or reducing unsafe behavior, a cross-sectional survey which lasted three months was conducted on 1590 front-line coal miners from seven mining areas in Shandong province, China. Principal component analysis (PCA), binary logistic regression (BLR) and Poisson regression (PR) were selected as analytical techniques. In order to eliminate the correlation and collinearity among independent variables, PCA was used firstly. Then, as the core method, BLR was introduced to estimate relationships between different components and coal miners’ unsafe behavior. In addition, we also concluded that coal miners who are younger and less experienced are more likely to behave safely through the results of PR. On the basis of the above results, we highlighted the useful measures, such as strengthening the safety education and training of miners, building safety climate and grasping the rationality of management system, which might motivate miners’ safety behavior. Findings from this research are beneficial not only to the establishment of more targeted unsafe behavior prevention measures, but also to the improvement of the safety management level in coal mines.

In this work we present a physics-based semi-empirical large-signal model for GaN MIS-HEMTs, which introduces the non-segmented, smooth continuous equations to describe the static and dynamic characteristics of GaN MIS-HEMTs in different working regions. The unique physical effect of threshold voltage drift was considered for MIS-HEMTs in the current model, in addition to effects of the channel length modulation and the temperature drift. In addition, a current-controlled current source was used in the dynamic model to characterize the nonlinear capacitance including the gate-drain capacitance CGD, gate-source capacitance CGS and drain-source capacitance CDS at different operating voltages. The model is in excellent agreement with the experimental data for both drain current and capacitances over a typical range of applied voltages and temperatures.

Forward osmosis (FO) is an emerging technology for wastewater treatment and reclamation. However, membrane fouling remains a strong hindrance to FO application. We proposed a novel approach for alleviating FO membrane fouling via in situ removing Ca 2+ binding with organic foulants using the EDTA-based adsorption layer. Results suggested that the EDTA-based adsorption layer can effectively remove the Ca 2+ binding with sodium alginate, and its adsorption capacity correspondingly increased as a function of Ca 2+ concentration in the feed solution. Owing to the effective extraction of Ca 2+ from the fouling layer by the EDTA-based adsorption layer, water flux of FO membrane was significantly enhanced, and fouling layer became easily removed by physical flushing, suggesting a remarkable alleviation of FO membrane fouling. Mitigation of FO membrane fouling by the EDTA-based adsorption layer was attributed to the fact that the fouling layer structure became more porous and looser after in situ removing Ca 2+ from the alginate-Ca 2+ gel networks. This study demonstrated a novel fouling control strategy via in situ removing Ca 2+ binding with the organic foulants, providing a new avenue for FO membrane fouling management.

We consider a cooperative relaying system with source (S) and relay (R) capable of harvesting wireless energy. A power beacon is placed between S and R to transfer wireless power to charge their batteries. Both the time-switching and the power-splitting methods are adopted to facilitate the energy harvesting (EH) at S and R. With the assumption that the predefined energy signal can be canceled by the receivers, we proposed to simultaneously transfer power and signal to strive for more opportunities of EH to greatly boost the amount of harvested energy at S and R. Using the harvested energy, S and R can cooperatively transmit data to the destination according to the decode-and-forward or the amplify-and-forward protocol. We analyze the average amount of harvested energy at S and R, and properly set their transmit powers to make the average amount of consumed energy equal the average amount of harvested energy. The system throughput of the proposed EH-based relaying schemes are analyzed. Extensive numerical results are provided to compare our proposed schemes and reveal the impacts of key system parameters.

The distribution of metallic elements in a submerged membrane bioreactor (MBR) was revealed at different temperatures using inductively coupled plasma-optical emission spectrometry (ICP-OES), and the role of extracellular polymeric substances (EPS) was probed by integrating scanning electron microscopy (SEM) with confocal laser scanning microscopy (CLSM) over long-term operation. More metallic elements in the influent were captured by suspended sludge and built up in the fouling layer at lower temperature. The concentration of metallic elements in the effluent was 5.60mg/L at 10°C operational temperature, far lower than that in the influent (51.35mg/L). The total contents of metallic elements in suspended sludge and the membrane fouling layer increased to 40.20 and 52.19mg/g at 10°C compared to 35.14 and 32.45mg/g at 30°C, and were dominated by the organically bound fraction. The EPS contents in suspended sludge and membrane fouling layer sharply increased to 37.88 and 101.51mg/g at 10°C, compared to 16.87 and 30.03mg/g at 30°C. The increase in EPS content at lower temperature was responsible for the deposition of more metallic ions. The strong bridging between EPS and metallic elements at lower temperature enhanced the compactness of the fouling layer and further decreased membrane flux. This was helpful for understanding the mechanism of membrane fouling at different operational temperatures and the role of EPS, and also of significance for the design of cleaning strategies for fouled membranes after long-term operation.

This study aimed at understanding the effects of co-flow condition on lift-off characteristics of the propane jet flame. A co-flow burner system was used to provide free jet condition, air co-flow condition and vitiated co-flow condition. In vitiated co-flow, methane was the co-flow fuel, and the co-flow equivalence ratios of methane/air mixtures changed from 0.5 to 0.7. On the basis of the results, the flame issuing into air-co-flow showed a higher lift-off height compared to the flame not issuing into a co-flow (i.e. free jet condition), with a faster increment rate simultaneously. In the vitiated co-flow condition, a conversion of lift-off height changing tendency was observed with the increment of flow rate and equivalence ratio of the co-flow. As the cases remained the same equivalence ratio, the cases with lower co-flow rates showed higher lift-off heights in the early combustion period. The lift-off height increased with the equivalence ratio in the cases with low co-flow rate, however, it decreased at high co-flow rate. It could be observed in the captured images that the ignition process was accelerated with the increment of equivalence ratio and co-flow rate.

A recommender system is an important tool to help users obtain content and overcome information overload. It can predict users’ interests and offer recommendations by analyzing their history behaviors. However, traditional recommender systems focus primarily on static user behavior analysis. Recently, with the promotion of the Netflix recommendation prize and the open dataset with location and time information, many researchers have focused on the dynamic characteristics of the recommender system (including the changes in the dynamic model of user interest), and begun to offer recommendations based on these dynamic features. Intuitively, these dynamic user features provide us with an effective method to learn user interests deeply. Based on the observations above, we present a dynamic fusion model by integrating geographical location, user preferences, and the time factor based on the Gibbs sampling process to provide better recommendations. To evaluate the performance of our proposed method, we conducted experiments on real-world datasets. The experimental results indicate that our proposed dynamic recommender system with fused time and location factors not only performs well in traditional scenarios, but also in sparsity situations where users appear at the first time.

The ignition characteristics and combustion processes of coal gangue pellets in O2/CO2 atmosphere were studied in a drop tube furnace with oxygen concentration range from 21% to 100%, the experimen...

Anaerobic osmotic membrane bioreactor (AnOMBR) has shown great promise for wastewater treatment and energy recovery. One of the major obstacles limiting the performance of the AnOMBR is the low water flux of forward osmosis (FO) membrane. Here, impacts of draw solution (DS) concentration on the performance of the AnOMBR were investigated for enhancing the water flux of FO membrane via controlling the driving force. The results indicated that the flux variations of FO membrane in the AnOMBR included two stages of a rapid and a mild flux declines at all DS concentration conditions. In addition, the FO membrane fouling correlated well with the flux variations for all DS concentration levels, i.e., a severe fouling in Stage 1 and a slight fouling in Stage 2. When the driving force or DS concentration exceeded a critical value, a worse FO membrane performance especially a severer flux decline in Stage 1 was observed. It could be attributed to an aggravated membrane fouling in Stage 1 owing to an increased initial flux with the rise of the driving force, implying that a critical initial flux exists in the AnOMBR except for a critical driving force. Inspired by the critical initial flux and the significant role of the membrane fouling in Stage 1, this study provides a novel method to enhance flux performance of FO membrane via controlling the driving force in a two-stage pattern. It utilizes a low driving force in Sage 1 to form a thin and loose fouling layer on the FO membrane surface and then a high driving force in Sage 2 to alleviate the flux drop. Compared with the stable driving force, the two-stage pattern obtained a better flux performance owing to a mitigation of membrane fouling with thinner layer thickness and less deposited foulants.

To deal with the inherent data sparsity and cold-start problem, many recommender systems try to exploit the textual information for improving prediction accuracy. Due to the significant progress of deep learning techniques, neural network-based content modeling methods have been investigated in recent studies. However, most of these existing methods often assume that users are independent and identically distributed (i.i.d), and the social influence is not considered. However, in the real world, we always turn to our friends for recommendations, and the closer the friendship between the friends, the greater the social impact is. These methods only exploit the reviews from an item perspective and rarely consider the user’s reviews to capture the user’s interests, but in reality, users often express their preferences by posting different reviews to different items. Based on the above-mentioned observations, we propose a social-enhanced content-aware recommendation method by fusing the social network, item’s reviews, and user’s reviews in a unified framework. Specifically, to better model the item’s reviews, we first introduce the convolutional matrix factorization (ConvMF) as our basic recommendation framework, which utilizes convolutional neural network (CNN) to capture the deeper understanding of the content context. Then, to consider the user’s social influence, we integrate the user’s social network into ConvMF by a shared user latent factor, which can bridge the user’s social interests and user’s general preferences in the same latent space. To model the user’s reviews, similar to ConvMF, we exploit another CNN to learn a deeper understanding of the user’s posted contents. Finally, we conduct experiments on the real-world dataset Yelp to demonstrate the effectiveness of our method. The experimental results indicate that our proposed method can effectively model the social and the review information and outperforms other related methods in terms of root mean squared error (RMSE) and mean absolute error (MAE).

The catalytic efficiency of CeO2 carriers and the catalytic properties of palladium (Pd) nanocrystals loaded on different morphology CeO2 carrier were studied for lean methane (CH4) combustion. The catalytic activity of simple CeO2 carriers was ranked in the order of rod-CeO2(r-CeO2) > cube-CeO2(c-CeO2) > octahedral-CeO2(o-CeO2). After the Pd species was loaded on CeO2, 90% of CH4 was converted at 348 °C catalyzed by Pd/octahedral-CeO2 (Pd/o-CeO2) with (1 1 1) crystal faces, which had much higher catalytic activity comparing with Pd loaded on c-CeO2 with (1 0 0) crystal faces and r-CeO2 with (1 1 0) and (1 0 0) crystal faces. The results of XRD, HRTEM, EDS, H2-TPR, XPS and elemental mapping showed that the Pd species in the form of Pd0 and PdO were highly dispersed on surface of all CeO2 carriers. Most importantly, quasi In-situ XPS results convinced that Ce3+/Ce4+ ion pairs played an important role in the catalytic combustion of low-concentration methane by adsorbing or releasing oxygen. Compared with r-CeO2 and c-CeO2, the concentration of Ce3+ on the surface of o-CeO2 carrier was greatly increased when the Pd species were present, which indirectly reflected that the concentration of oxygen vacancies on the carrier surface also increased. Consequently, the high catalytic activity of Pd/o-CeO2 is not only related to the high dispersion of Pd0 and PdO species on the surface of the catalyst, but also closely related to the synergistic interaction between Pd species and (1 1 1) specific faces of o-CeO2 exposing.

Waste activated sludge (WAS) treatment has gained growing interests for its increasingly capacity and high process cost. Sludge thickening is generally the first process of the WAS treatment. However, traditional sludge thickening approach was restrained by large footprint, low thickening efficiency, and tendency of releasing phosphorus. Here, we reported a novel microfiltration (MF) membrane assisting forward osmosis (FO) process (MF-FO) for sludge thickening. The MF-FO reactor achieved a sludge thickening of the mixed liquor suspended solids (MLSS) concentration from approximately 7 to 50 g/L after 10-day operation. More importantly, the effluent quality after FO filtration was superior with total organic carbon (TOC), ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N) and total phosphorus (TP) of 1.94 ± 0.46, 0.02 ± 0.07, 4.55 ± 1.59 and 0.24 ± 0.26 mg/L, respectively. Additionally, the integration of MF membrane successfully controlled the salinity of the MF-FO reactor in a low range of 1.6-3.1 mS/cm, which mitigated the flux decline of FO membrane and thus prolonged the operating time. In this case, the flux decline of FO membrane in the MF-FO reactor was mainly due to the membrane fouling. Furthermore, the fouling layer on the FO membrane surface was a gel layer mainly composed of biofoulants and organic foulants when the MLSS concentration was less than 30 g/L, while it turned to a cake layer when the MLSS concentration exceeded 30 g/L. Results reported here demonstrated that the MF-FO reactor is a promising WAS thickening technology for its excellent thickening performance and high effluent quality of FO membrane.

Two-dimensional metal-organic frameworks (2D-MOFs) and their derivatives are promising for catalysis, energy storage, gas separation, etc. due to their unique microstructure and physicochemical properties. Many efforts have been devoted to fabricating 2D-MOFs with challenges remaining in yield and fine control of their thickness and lateral size. Here a versatile strategy has been used involving epitaxial, anisotropic, and confined growth of CoNi-MOF-71 nanosheet arrays, giving rise to excellent quantity and controllability of the 2D-MOFs. Electromagnetic (EM) wave absorption performance has been investigated for the resultant 2D Co/Ni/C derivatives. Compared with the bulk counterpart, significantly increased surface area, conductivity, and shape anisotropy for the 2D derivatives result in enhanced interfacial polarization, conductive loss, and magnetic resonance. As such, optimum EM wave absorption of minimum reflection loss RLmin = -49.8 dB and an ultrawide effective adsorption bandwidth EAB = 7.6 GHz can be achieved at a thickness of 2.6 mm. This work not only sheds light on the performance enhancement for 2D absorbers via synergistic effects of multiple attenuation mechanisms but also provides an effective fabrication route of ultrathin MOFs with high yield and uniform size for extended applications in catalysis, electrochemistry, and optoelectronics fields.

Purpose. The stress shielding effect caused due to the mechanical mismatch between the solid titanium and the surrounding bone tissue warrants the utilization of a mechanically and biologically compatible material such as the titanium-hydroxyapatite (Ti-HA) functionally graded material (FGM) for dental implants. This study is aimed at fabricating a Ti-HA FGM with superior mechanical and biological properties for dental implantation. Materials and Methods. We fabricated a Ti-HA FGM with different Ti volume fractions (VFs) using HA and Ti powders. Ti-HA was characterized by studying its mechanical properties. Cytotoxicity was examined using a Cell Counting Kit-8 assay and an LDH cell cytotoxicity assay. Scanning electron microscopy was performed on an XL30 environmental scanning electron microscope (ESEM). Alkaline phosphatase (ALP) and transforming growth factor (TGF-β1) expressions were quantitatively monitored using enzyme-linked immunosorbent assay (ELISA) kits. The expressions of TGF-β receptors and ALP genes were measured using real-time polymerase chain reaction. The Ti-HA FGM dental implants were placed in beagle dogs. Microcomputed tomography (CT) and hard tissue slices were performed to evaluate the bone-implant contact (BIC) and bone volume over total volume (BV/TV). Results. The density and mechanical properties of the Ti-HA exhibited various graded distributions corresponding to VF. Based on the results of the Cell Counting Kit-8 (CCK-8) and lactate dehydrogenase (LDH) assays, the difference in cytotoxicity between the two groups was statistically nonsignificant ( P = 0.11 ). The ALP and TGF-β1 levels were slightly upregulated. The transcript levels of ALP and TGF-βRI were higher in the Ti-HA groups than in the Ti group at 7 days, whereas the transcript levels of TGF-βRII exhibited no obvious increase. The BIC did not exhibit significant differences between the Ti and Ti-HA FGM groups ( P = 0.0504 ). BV/TV showed the Ti-HA FGM group had better osteogenesis ( P = 0.04 ). Conclusion. Ti-HA FGM contributes to the osteogenesis of dental implants in vivo and in vitro.

Anaerobic membrane bioreactors (AnMBRs) have aroused growing interest in wastewater treatment and energy recovery. However, serious membrane fouling remains a critical hindrance to AnMBRs. Here, a novel membrane fouling mitigation via optimizing initial water flux is proposed, and its feasibility was evaluated by comparing the membrane performance in AnMBRs between constant flux and varying flux modes. Results indicated that, compared with the constant flux mode, varying flux mode significantly prolonged the membrane operating time by mitigating membrane fouling. Through the analyses of fouled membranes under two operating modes, the mechanism of membrane fouling mitigation was revealed as follows: A low water flux was applied in stage 1 which slowed down the interaction between foulants and membrane surface, especially reduced the deposition of proteins on the membrane surface and formed a thin and loose fouling layer. Correspondingly, the interaction between foulants was weakened in the following stage 2 with a high water flux and, subsequently, the foulants absorbed on the membrane surface was further reduced. In addition, flux operating mode had no impact on the contaminant removal in an AnMBR. This study provides a new way of improving membrane performance in AnMBRs via a varying flux operating mode.

Long-term storage of aerobic granular sludge (AGS) may lead to granule inactivation and disintegration. Granule recovery in both structure and activity is important for scale-up and stability of AGS, but information about the structure recovery of stored AGS is limited. In addition, whether short-term exogenous N-acyl-homoserine lactones (AHLs) regulations could accelerate the granule recovery and sustain positive effects on AGS is unknown. Herein, the recovery of 33-month stored AGS was performed in three reactors for 38 days (phase I) at different exogenous AHLs concentrations (0, 50 and 500 nM of AHL-mixtures in R0, R1 and R2, respectively) and for an extended 45 days without exogenous AHLs (phase II). Results demonstrated successful recovery of disintegrated AGS in all reactors, although it was relatively time-consuming in R0. The treatment performance was similar among the reactors and steady-state removal of COD (90%) and NH4+-N (94%) could be recovered within 7 and 21 days, respectively. However, exogenous AHLs regulation (especially in R1) obviously accelerated bioactivity recovery of heterotrophs and nitrifiers and improved granule characteristics, including biomass, density, hydrophobicity and extracellular polymeric substance (EPS). During phase II, sustainable positive effects remained in R1, but granule characteristics deteriorated in R2. The abundance of functional genera Thauera, Nitrosomonas and Candidatus_Nitrotoga, contributed to the rapid recovery and helped maintain the structure and activity of AGS. The predictive functional profiling of bacterial communities also demonstrated sustainably higher activities of metabolism, growth and signal sensing under exogenous AHLs regulation at an appropriate content.

Research in the field of tribo-mechatronics has been gaining popularity in recent decades. The objective of the current research is to improve static/dynamics characteristics of hydrostatic bearings. Hydrostatic bearings always work in harsh environmental conditions that effect their performance, and which may even result in their failure. The current research proposes a mathematical model-based system for hydrostatic bearings that helps to improve its static/dynamic characteristics under varying conditions of performance-influencing variables such as temperature, spindle speed, external load, and clearance gap. To achieve these objectives, the capillary restrictors are replaced with servo valves, and a mathematical model is developed along with robust control design systems. The control system consists of feedforward and feedback control techniques that have not been applied before for hydrostatic bearings in the published literature. The feedforward control tries to remove a disturbance before it enters the system while feedback control achieves the objective of disturbance rejection and improves steady-state characteristics. The feedforward control is a trajectory-based controller and the feedback controller is a sliding mode controller with a PID sliding surface. The particle swarm optimization algorithm is used to tune the 6-dimensional vector of the tuning parameters with multi-objective performance criteria. Numerical investigations have been carried out to check the performance of the proposed system under varying conditions of viscosity, clearance gap, external load and the spindle speed. The comparison of our results with the published literature shows the effectiveness of the proposed system.

In the game between coal miners and supervisors, the behavior choices of the game parties will be affected by cognitive factors. The analysis of the behavior choices of coal miners and supervisors under the influence of cognitive factors is helpful for the design of violation behavior control strategies. Firstly, a description method of subjective cognition based on the mathematical method of quantum theory is designed. Secondly, taking the subjective cognition of coal miners and supervisors as a random variable, a behavior evolution model with random variables is constructed. Thirdly, the impact of subjective cognition on the behavior choices of coal miners and supervisors is analyzed. Finally, the violation behavior control strategy is designed. It is found that when the violation probability decreases to a certain extent, the probability of supervision will change from the increase to decrease. When the probability of supervision decreases to a certain extent, the violation probability will change from the decrease to increase. Fluctuations in cognitive state can affect the change process of violation probability and supervision probability. The behavior control strategy designed according to the behavior evolution model can control the violation behavior in the situation of cognitive state fluctuation.

UAV needs sensor to fly in an environment with obstacles. However, UAV may not be able to move forward when it encounters a large obstacle, or UAV will be in a dangerous state when the sensor fails briefly which disturbed by the environment factors. In order to solve these problems, the following methods are proposed in this paper. Aiming at the first problem, this paper proposes an improved APF method for path planning, and verified by simulation experiments that this method can find the optimal path. Aiming at the second problem, this paper proposes a solution to expand the range of obstacles and dynamically change the distance in the APF repulsion function. It is verified that the UAV can fly safely within the short time of the sensor problem by simulation experiments. In conclusion, this paper has an important reference value for the application of UAV online dynamic path planning in engineering.

The minimum ignition temperature of dust suspension (MIT) and the hot surface ignition temperature of the dust layer (LIT) are essential safety parameters for the process industry. However, the knowledge of the ignition behavior when solid mixtures of flammable fuels and phosphorous-free inhibitors are considered is still scarce and further experimental and theoretical analyses are requested. In this work, the ignition temperature of phosphorous-free inhibitors (coal fly ash and calcium carbonate) mixed with lycopodium dust have been studied in terms of LIT analysis (hot plate thickness: 5 mm, 12.5 mm and 15 mm), and by the Godbert-Greenwald test for the MIT. Both coal fly ash and calcium carbonate have been tested at different concentrations and particle sizes. Results show that the effects of the inhibitor can be counter-productive when layer ignition temperature is considered even if the minimum ignition temperature of the dust suspension shows a positive effect from the safety point of view. This behavior has been analyzed in the terms of thermal conductivity and diffusivity of the mixture, by using Maxwell's equation for two-phase solid mixtures. Standard empirical correlations for the ignition temperature of solid mixtures have been also tested, showing their weakness in reproducing mixture behavior.

We consider a wirelessly powered Internet of Things (IoT) based on cell-free massive MIMO with energy harvesting. In such a system, during the downlink phase, the sensors harvest radio-frequency (RF) energy emitted by the distributed access points (APs). During the uplink phase, sensors transmit data to the APs using the harvested energy. We assume that single antenna sensors send uplink pilots in order to allow APs to detect active users and estimate their channel coefficients. We assume that each AP is equipped with N$\geq$1 antennas and uses the linear minimum mean square error (LMMSE) channel estimation. Through an asymptotic analysis, we derive closedform approximations for the variance of the LMMSE channel coefficient estimates, the amount of harvested energy, and the achievable rates for the uplink data transmission. We next use these expressions to jointly optimize the charging duration and uplink and downlink power control coefficients to minimize the total transmit energy consumptions of APs and sensors, which is crucially important for IoT sensors. Simulation results verify the accuracy of the obtained expressions, and shows that significant gains in energy efficiency can be achieved by the proposed optimization algorithms.

Anaerobic osmotic membrane bioreactor (AnOMBR) holds promise for simultaneous wastewater purification and biogas production, allowing for an energy and carbon-neutral treatment facility. In a typical AnOMBR, reverse osmosis (RO) is employed for re-concentrating draw solution for continuous operation and cost saving. We compared membrane fouling behaviors between AnOMBR-RO hybrid system and AnOMBR without RO unit. We concluded that the porous support layer was susceptible to both inorganic scaling and biofouling in the closed-loop AnOMBR-RO system. We also explored two cleaning approaches to mitigate inorganic scaling and biofouling. Specifically, ethylenediaminetetraacetic acid (EDTA) was introduced into draw solution for minimizing inorganic scaling, but biofouling was deteriorated as EDTA provided extra nutrients for bacterial proliferation and biofouling. On the other hand, chemical cleaning of membrane support layer was performed using NaClO solution for biofouling control, but such cleaning efficacy attenuated after several cleaning cycles, because inorganic minerals accumulated and grew within membrane porous layer which could not be flushed by NaClO cleaning. Our finding highlighted the complexity and courter intuitive perspective to membrane fouling and cleaning in AnOMBR-RO hybrid system for inorganic scaling and biofouling management.

Objective In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform classification using support vector machine (SVM) algorithm for neonatal sleep and wake states using Fluke® facial video frames. Using pre-trained CNNs as a feature extractor would hugely reduce the effort of collecting new neonatal data for training a neural network which could be computationally expensive. The features are extracted after fully connected layers (FCL’s), where we compare several pre-trained CNNs, e.g., VGG16, VGG19, InceptionV3, GoogLeNet, ResNet, and AlexNet. Results From around 2-h Fluke® video recording of seven neonates, we achieved a modest classification performance with an accuracy, sensitivity, and specificity of 65.3%, 69.8%, 61.0%, respectively with AlexNet using Fluke® (RGB) video frames. This indicates that using a pre-trained model as a feature extractor could not fully suffice for highly reliable sleep and wake classification in neonates. Therefore, in future work a dedicated neural network trained on neonatal data or a transfer learning approach is required.

Objective Electrical status epilepticus during sleep (ESES), as electroencephalographic disturbances, is characterized by strong activation of epileptiform activity in the electroencephalogram during sleep. Quantitative descriptors of such epileptiform activity can support the diagnose and the prognosis of children with ESES. To quantify the epileptiform activity of ESES, a knowledge-based approach to mimic the clinical decision-making process is proposed. Approach Firstly, a morphological operations-based scheme is designed to quickly locate the positive peaks/negative pits and roughly estimate the onset/offset of spike and slow-wave abnormalities. Then, to provide the accurate duration of ESES patterns, a set of rules for further adjusting these onsets/offsets are proposed by merging medical knowledge with a generalized threshold obtained from statistics. As such, the quantification is accomplished by evaluating the obtained spike and slow-wave abnormalities and their various durations. Main results The effectiveness and feasibility of the proposed method were evaluated on a clinical dataset that collected at Children's Hospital of Fudan University, Shanghai, China. We demonstrate that the proposed method can recognize different types of spike and slow-wave abnormalities. The sensitivity, precision, and false positive rate achieved 91.96%, 97.09%, and 1.88 min-1, respectively. The estimation error for the spike-wave index was 2.32%. Comparison results showed that our method outperforms the state-of-the-art. Significance The quantification of spike and slow-waves provides information about ESES activity. The detection of variations types of spike and slow-waves improves the performance in the quantification of ESES. Experimental results suggest that the proposed method has great potential in automatic ESES quantification and can help improve the diagnosis and researches of epileptic encephalopathy with ESES.

As students&rsquo, behaviors are important factors that can reflect their learning styles andliving habits on campus, extracting useful features of them plays a helpful role in understanding thestudents&rsquo, learning process, which is an important step towards personalized education. Recently,the task of predicting students&rsquo, performance from their campus behaviors has aroused the researchers&rsquo, attention. However, existing studies mainly focus on extracting statistical features manually fromthe pre-stored data, resulting in hysteresis in predicting students&rsquo, achievement and finding out theirproblems. Furthermore, due to the limited representation capability of these manually extractedfeatures, they can only understand the students&rsquo, behaviors shallowly. To make the prediction processtimely and automatically, we treat the performance prediction task as a short-term sequence predictionproblem, and propose a two-stage classification framework, i.e., Sequence-based PerformanceClassifier (SPC), which consists of a sequence encoder and a classic data mining classifier. Morespecifically, to deeply discover the sequential features from students&rsquo, campus behaviors, we firstintroduce an attention-based Hybrid Recurrent Neural Network (HRNN) to encode their recentbehaviors by giving a higher weight to the ones that are related to the students&rsquo, last action. Then,to conduct student performance prediction, we further involve these learned features to the classicSupport Vector Machine (SVM) algorithm and finally achieve our SPC model. We conduct extensiveexperiments in the real-world student card dataset. The experimental results demonstrate thesuperiority of our proposed method in terms of Accuracy and Recall.

The non-contact detection of buried ferromagnetic pipeline is a long-standing problem in the field of inspection of outside pipelines, and the extraction of magnetic anomaly signal is a prerequisite for accurate detection. Pipeline defects can cause the fluctuation of magnetic signals, which are easily submerged in wide-band background noise without external excitation sources. Previously, Variational Mode Decomposition (VMD) was used to separate modal components, however, VMD is based on narrow-band signal processing algorithm and the calculation is complex. In this article, a method of pipeline defect signal based on Variational Specific Mode Extraction (VSME) is employed to extract the signal of a specific central frequency by signal modal decomposition, i.e., the specific mode is weak magnetic anomaly signal of pipeline defects. VSME is based on the fact that a wide-band signal can be converted into a narrow-band signal by demodulation method. Furthermore, the problem of wide-band signal decomposition is expressed as an optimal demodulation problem, which can be solved by alternating direction method of multipliers. The proposed algorithm is verified by artificially synthesized signals, and its performance is better than that of VMD. The results showed that the VSME method can extract the magnetic anomaly signal of pipeline damage using experimental data, while obtaining a better accuracy.

The use of heterogeneous catalysts to improve the Electro-Fenton (EF) process has attracted significant attention. However, complex redox reactions and multiple mass transfer steps during the EF process result in limited current efficiency with only a low rate of generation of hydroxyl radicals (·OH). Herein, we establish a three-electron oxygen reduction reaction (ORR) process coupling adsorbed H2O2 (H2O2ad) generation with an in situ EF-like reaction on TiO2 during cathodic electrolysis. Anatase TiO2 was composited with graphite, enabling the electrochemical reduction of Ti4+ to Ti3+. H2O2ad was formed during the ORR, electrocatalyzed by TiO2, then the H2O2ad was reduced in situ to ·OH without desorption. The generation and decomposition of Ti-OH during the electrochemical reduction were directly observed by in situ Raman spectroscopy. This result was further confirmed by density functional theory (DFT) calculations. Based on this three-electron ORR mechanism, the ·OH yield reached 2.69 μg cm−2 min−1 and the current efficiency approached 92.8% at a current density of −0.80 mA cm−2 within 2 h during ORR on the TiO2/graphite (TiO2/C) cathode. Keywords: TiO2, Oxygen reduction reaction, Electrocatalysis, Hydroxyl radicals