N-doped graphene quantum dot-decorated N-TiO2/P-doped porous hollow g-C_(3)N_(4) nanotube composite photocatalysts for antibiotic photodegradation and H2 production

Exclusive responsiveness to ultraviolet light (~3.2 eV) and high photogenerated charge recombination rate are the two primary drawbacks of pure TiO_(2). We combined N-doped graphene quantum dots (N-GQDs), morphology regulation, and heterojunction construction strategies to synthesize N-GQD/N-doped TiO_(2)/P-doped porous hollow g-C_(3)N_(4) nanotube (PCN) composite photocatalysts (denoted as G-TPCN). The optimal sample (G-TPCN doped with 0.1wt% N-GQD, denoted as 0.1% G-TPCN) exhibits significantly enhanced photoabsorption, which is attributed to the change in bandgap caused by elemental doping (P and N), the improved light-harvesting resulting from the tube structure, and the upconversion effect of N-GQDs. In addition, the internal charge separation and transfer capability of0.1% G-TPCN are dramatically boosted, and its carrier concentration is 3.7, 2.3, and 1.9 times that of N-TiO_(2), PCN, and N-TiO_(2)/PCN(TPCN-1), respectively. This phenomenon is attributed to the formation of Z-scheme heterojunction between N-TiO_(2) and PCNs, the excellent electron conduction ability of N-GQDs, and the short transfer distance caused by the porous nanotube structure. Compared with those of N-TiO_(2), PCNs, and TPCN-1, the H2 production activity of 0.1%G-TPCN under visible light is enhanced by 12.4, 2.3, and 1.4times, respectively, and its ciprofloxacin (CIP) degradation rate is increased by 7.9, 5.7, and 2.9 times, respectively. The optimized performance benefits from excellent photoresponsiveness and improved carrier separation and migration efficiencies. Finally, the photocatalytic mechanism of 0.1% G-TPCN and five possible degradation pathways of CIP are proposed. This study clarifies the mechanism of multiple modification strategies to synergistically improve the photocatalytic performance of 0.1% G-TPCN and provides a potential strategy for rationally designing novel photocatalysts for environmental remediation and solar energy conversion.

Rheological behavior of paste in metal mines

Cemented paste backfill(CPB)has been one of the best practical approaches for tailings management and underground goaf treatment.Paste rheology is a science to study the flow and deformation behaviors of paste or filling body under the effects of stress,strain,temperature,and time during the CPB process.The goal of studying paste rheology is to solve the engineering problems existing in four key processes;that is,paste rheology should meet the engineering demands of thickening,mixing,transportation,and backfilling.However,paste rheology is extremely complicated due to its high concentration,materials complexity,and engineering characteristics of non-stratification,nonsegregation,and non-bleeding.The rheological behavior of full tailings in deep thickening,rheological behavior of paste in mixing and pipeline transportation,and rheological behavior of filling body are introduced and discussed:(1)gel point,compressive yield stress,and the hindered settling function are adopted to characterize the rheological properties of full tailings in deep thickening.Combination of Coe-Clevenger theory and Buscall-White theory can also analyze the thickening performance in the whole area of deep cone thickener;(2)yield stress and viscosity are consistent with the evolution trend of the relative structure coefficient of paste in mixing;(3)coupling effect of wall slip and time-temperature dependency has a significant influence on the rheological properties and pipeline transportation;(4)damage variable is introduced to the Burgers model to describe the creep damage of the filling body.However,in-depth and systematic studies were still needed to establish a complete theoretical system of paste rheology in metal mines.

Finite-Time Convergence Disturbance Rejection Control for a Flexible Timoshenko Manipulator

This paper focuses on a new finite-time convergence disturbance rejection control scheme design for a flexible Timoshenko manipulator subject to extraneous disturbances.To suppress the shear deformation and elastic oscillation,position the manipulator in a desired angle,and ensure the finitetime convergence of disturbances,we develop three disturbance observers(DOs)and boundary controllers.Under the derived DOs-based control schemes,the controlled system is guaranteed to be uniformly bounded stable and disturbance estimation errors converge to zero in a finite time.In the end,numerical simulations are established by finite difference methods to demonstrate the effectiveness of the devised scheme by selecting appropriate parameters.

Phase evolution and properties of glass ceramic foams prepared by bottom ash,fly ash and pickling sludge

Municipal solid waste incineration products of bottom ash(BA),fly ash(FA),and pickling sludge(PS),causing severe environ-mental pollution,were transformed into glass ceramic foams with the aid of CaCO3 as a pore-foaming agent during sintering.The effect of the BA/FA mass ratio on the phase composition,pore morphology,pore size distribution,physical properties,and glass structure was investigated,with results showing that with the increase in the BA/FA ratio,the content of the glass phase,Si-O-Si,and Q3Si units decrease gradually.The glass transmission temperature of the mixture was also reduced.When combined,the glass viscosity decreases,causing bubble coalescence and uneven pore distribution.Glass ceramic foams with uniform spherical pores are fabricated.When the content of BA,FA,and PS are 35wt%,45wt%,and 20wt%,respectively,contributing to high performance glass ceramic foams with a bulk density of 1.76 g/cm3,porosity of 56.01%,and compressive strength exceeding 16.23 MPa.This versatile and low-cost approach provides new insight into synergistically recycling solid wastes.

Data-mining and atmospheric corrosion resistance evaluation of Sn-and Sb-additional low alloy steel based on big data technology

Machine-learning and big data are among the latest approaches in corrosion research.The biggest challenge in corrosion research is to accurately predict how materials will degrade in a given environment.Corrosion big data is the application of mathematical methods to huge amounts of data to find correlations and infer probabilities.It is possible to use corrosion big data method to distinguish the influence of the minimal changes of alloying elements and small differences in microstructure on corrosion resistance of low alloy steels.In this research,corrosion big data evaluation methods and machine learning were used to study the effect of Sb and Sn,as well as environmental factors on the corrosion behavior of low alloy steels.Results depict corrosion big data method can accurately identify the influence of various factors on corrosion resistance of low alloy and is an effective and promising way in corrosion research.

Adaptive Memory Event-Triggered Observer-Based Control for Nonlinear Multi-Agent Systems Under DoS Attacks

This paper investigates the event-triggered security consensus problem for nonlinear multi-agent systems(MASs)under denial-of-service(Do S)attacks over an undirected graph.A novel adaptive memory observer-based anti-disturbance control scheme is presented to improve the observer accuracy by adding a buffer for the system output measurements.Meanwhile,this control scheme can also provide more reasonable control signals when Do S attacks occur.To save network resources,an adaptive memory event-triggered mechanism(AMETM)is also proposed and Zeno behavior is excluded.It is worth mentioning that the AMETM's updates do not require global information.Then,the observer and controller gains are obtained by using the linear matrix inequality(LMI)technique.Finally,simulation examples show the effectiveness of the proposed control scheme.

Vibration Control of a High-Rise Building Structure:Theory and Experiment

In this study,an innovative solution is developed for vibration suppression of the high-rise building.The infinite dimensional system model has been presented for describing high-rise building structures which have a large inertial load with the help of the Hamilton’s principle.On the basis of this system model and with the use of the Lyapunov’s direct method,a boundary controller is proposed and the closed-loop system is uniformly bounded in the time domain.Finally,by using the Smart Structure laboratory platform which is produced by Quancer,we conduct a set of experiments and find that the designed method is resultful.

Effects of selective laser melting parameters on surface quality and densification behaviours of pure nickel

The effects of laser power and scanning speed on the forming characteristic of scanning tracks,densification behaviours and surface roughness of pure nickel fabricated with selective laser melting(SLM)were studied.The results indicate that the scanning tracks showed continuous,regular and flat surface with increasing laser power and decreasing scanning speed in a specific range,which could avoid the defects(like holes and balling structures)forming in SLM processing.The optimal process window was identified as the scanning speed of 900 mm/s and the laser power of 255−275 W by comparing the surface qualities and densification behaviours.With the suitable processing parameters,the relative density could achieve 99.16%,the tensile strength was(359.49±2.74)MPa,and the roughnesses of the top and side surfaces were(12.88±2.23)and(14.98±0.69)μm,respectively.

Modeling of microstructure evolution of AZ80 magnesium alloy during hot working process using a unified internal state variable method

In this paper, a unified internal state variable(ISV) model for predicting microstructure evolution during hot working process of AZ80 magnesium alloy was developed. A novel aspect of the proposed model is that the interactive effects of material hardening, recovery and dynamic recrystallization(DRX) on the characteristic deformation behavior were considered by incorporating the evolution laws of viscoplastic flow, dislocation activities, DRX nucleation and boundary migration in a coupled manner. The model parameters were calibrated based on the experimental data analysis and genetic algorithm(GA) based objective optimization. The predicted flow stress, DRX fraction and average grain size match well with experimental results. The proposed model was embedded in the finite element(FE) software DEFORM-3 D via user defined subroutine to simulate the hot compression and equal channel angular extrusion(ECAE) processes. The heterogeneous microstructure distributions at different deformation zones and the dislocation density evolution with competitive deformation mechanisms were captured.This study can provide a theoretical solution for the hot working problems of magnesium alloy.

Influencing factors and mechanism of high-temperature oxidation of high-entropy alloys: A review

High-temperature oxidation is a common failure in high-temperature environments,which widely occur in aircraft engines and aerospace thrusters;as a result,the development of anti-high-temperature oxidation materials has been pursued.Ni-based alloys are a common high-temperature material;however,they are too expensive.High-entropy alloys are alternatives for the anti-oxidation property at high temperatures because of their special structure and properties.The recent achievements of high-temperature oxidation are reviewed in this paper.The high-temperature oxidation environment,temperature,phase structure,alloy elements,and preparation methods of high-entropy alloys are summarized.The reason why high-entropy alloys have anti-oxidation ability at high temperatures is illuminated.Current research,material selection,and application prospects of high-temperature oxidation are introduced.

The essential roles of sugar metabolism for pollen development and male fertility in plants

Sugar metabolism plays an essential role in plant male reproduction. Defects in sugar metabolism during anther and pollen development often result in genic male sterility(GMS). In this review, we summarize the recent progresses of the sugar metabolism-related GMS genes and their roles during plant anther and pollen development, including callose wall and primexine formation, intine development, pollen maturation and starch accumulation, anther dehiscence, and pollen germination and tube growth. We predict 112 putative sugar metabolic GMS genes in maize based on bioinformatics and RNA-seq analyses, and most of them have peak expression patterns during middle or late anther developmental stages.Finally, we outline the potential applications of sugar metabolic GMS genes in crop hybrid breeding and seed production. This review will deepen our understanding on sugar metabolic pathways in controlling pollen development and male fertility in plants.

Effects of the electric field at the edge of a substrate to deposit a φ100 mm uniform diamond film in a 2.45 GHz MPCVD system

In this study,uniform diamond films with a diameter of 100 mm were deposited in a 15 kW/2.45 GHz ellipsoidal microwave plasma chemical vapour deposition system.A phenomenological model previously developed by our group was used to simulate the distribution of the electric strength and electron density of plasma.Results indicate that the electric field in the cavity includes multiple modes,i.e.TM_(02) and TM_(03).When the gas pressure exceeds 10 kPa,the electron density of plasma increases and plasma volume decreases.A T-shaped substrate was developed to achieve uniform temperature,and the substrate was suspended in air fromφ70 to 100 mm,thus eliminating vertical heat dissipation.An edge electric field was added to the system after the introduction of the T-shaped substrate.Moreover,the plasma volume in this case was greater than that in the central electric field but smaller than that in the periphery electric field of the TM_(02) mode.This indicates that the electric field above and below the edge benefits the plasma volume rather than the periphery electric field of the TM_(02) mode.The quality,uniformity and surface morphology of the deposited diamond films were primarily investigated to maintain substrate temperature uniformity.When employing the improved substrate,the thickness unevenness of theφ100 mm diamond film decreased from 22%to 7%.

Carbon materials:The burgeoning promise in electronics

Current electronic technology based on silicon is approaching its physical and scientific limits. Carbon-based devices have numer- ous advantages for next generation electronics (e.g., fast speed, low power consumption and simple process), that when combined with the unique nature of the versatile allotropes of carbon elements, are creating an electronics revolution. Carbon electronics are greatly advancing with new preparations and sophisticated designs. In this perspective, representatives with various dimensions, e.g., carbon nanotubes, graphene, bulk diamond, and their extraordinary performance, are reviewed. The associated state-of-the-art devices and composite hybrid all-carbon structures are also emphasized to reveal their potential in the electronics field. Advances in commercial production have improved the cost effi-ciency, material quality, and device design, accelerating the promise of carbon materials.

Tightened1D/3Dcarbonheterostructure infiltratingphase change materials for solar-thermoelectric energy harvesting:Faster and better

Extensive use of thermal energy in daily life is ideal for reducing carbon emissions to achieve carbon neutrality;however,the effective collection of thermal energy is a major hurdle.Thermoelectric(TE)conversion technology based on the Seebeck effect and thermal energy storage technology based on phase change materials(PCMs)represent smart,feasible,and research-worthy approaches to overcome this hurdle.However,the integration of multiple thermal energy sources freely existing in the environment for storage and output of thermal and electrical energy simultaneously still remains a huge challenge.Herein,three-dimensional(3D)nanostructured metal-organic frameworks(MOFs)are in situ nucleated and grown onto carbon nanotubes(CNTs)via coordination bonding.After calcination,the prepared core-shell structural CNTs@MOFs are transformed into tightened 1D/3D carbon heterostructure loading Co nanoparticles for efficient solar-thermoelectric energy harvesting.Surprisingly,the corresponding composite PCMs show a record-breaking solar-thermal conversion efficiency of 98.1%due to the tightened carbon heterostructure and the local surface plasmon resonance effect of Co nanoparticles.Moreover,our designed all-in-one composite PCMs are also capable of creating an electrical potential of 0.5 mV based on the Seebeck effect without a TE generator.This promising approach can store thermal and electrical energy simultaneously,providing a new direction in the design of advanced all-in-one multifunctional PCMs for thermal energy storage and utilization.

A Task-Resource Joint Management Model with Intelligent Control for Mission-Aware Dispersed Computing

Dispersed computing can link all devices with computing capabilities on a global scale to form a fully decentralized network,which can make full use of idle computing resources.Realizing the overall resource allocation of the dispersed computing system is a significant challenge.In detail,by jointly managing the task requests of external users and the resource allocation of the internal system to achieve dynamic balance,the efficient and stable operation of the system can be guaranteed.In this paper,we first propose a task-resource joint management model,which quantifies the dynamic transformation relationship between the resources consumed by task requests and the resources occupied by the system in dispersed computing.Secondly,to avoid downtime caused by an overload of resources,we introduce intelligent control into the task-resource joint management model.The existence and stability of the positive periodic solution of the model can be obtained by theoretical analysis,which means that the stable operation of dispersed computing can be guaranteed through the intelligent feedback control strategy.Additionally,to improve the system utilization,the task-resource joint management model with bi-directional intelligent control is further explored.Setting control thresholds for the two resources not only reverse restrains the system resource overload,but also carries out positive incentive control when a large number of idle resources appear.The existence and stability of the positive periodic solution of the model are proved theoretically,that is,the model effectively avoids the two extreme cases and ensure the efficient and stable operation of the system.Finally,numerical simulation verifies the correctness and validity of the theoretical results.

A pilot allocation method for multi-cell multi-user massive MIMO system

Pilot contamination can spoil the accuracy of channel estimation and then has become one of the key problems influencing the performance of massive multiple input multiple output(MIMO)systems.This paper proposes a method based on cell classification and users grouping to mitigate the pilot contamination in multi-cell massive MIMO systems and improve the spectral efficiency.The pilots of the terminals are allocated onebit orthogonal identifier to diminish the cell categories by the operation of exclusive OR(XOR).At the same time,the users are divided into edge user groups and central user groups according to the large-scale fading coefficients by the clustering algorithm,and different pilot sequences are assigned to different groups.The simulation results show that the proposed method can effectively improve the spectral efficiency of multi-cell massive MIMO systems.

A Continuous Authentication Protocol Without Trust Authority for Zero Trust Architecture

Zero-trust security is a novel concept to cope with intricate access,which can not be handled by the conventional perimeter-based architecture anymore.The device-to-device continuous authentication protocol is one of the most crucial cornerstones,especially in the IoT scenario.In the zero-trust architecture,trust does not rely on any position,person or device.However,to the best of our knowledge,almost all existing device-to-device continuous authentication relies on a trust authority or a node to generate secret keys or secret values.This is betrayed by the principle of zero-trust architecture.In this paper,we employ the blockchain to eliminate the trusted node.One node is chosen to produce the public parameter and secret keys for two entities through the practical Byzantine fault tolerance consensus mechanism.Additionally,the devices are categorized into three folds:trusted device,suspected device and untrusted device.Only the first two can participate in authentication,and they have different lengths of security parameters and intervals to reach a better balance between security and efficiency.Then we prove the security of the initial authentication part in the eCK model and give an informal analysis of the continuous authentication part.Finally,we implement the proposed protocol on simulated devices.The result illustrates that our scheme is highly efficient,and the continuous authentication only costs around 0.1ms.

A Novel Named Entity Recognition Scheme for Steel E-Commerce Platforms Using a Lite BERT

In the era of big data,E-commerce plays an increasingly important role,and steel E-commerce certainly occupies a positive position.However,it is very difficult to choose satisfactory steel raw materials from diverse steel commodities online on steel E-commerce platforms in the purchase of staffs.In order to improve the efficiency of purchasers searching for commodities on the steel E-commerce platforms,we propose a novel deep learning-based loss function for named entity recognition(NER).Considering the impacts of small sample and imbalanced data,in our NER scheme,the focal loss,the label smoothing,and the cross entropy are incorporated into a lite bidirectional encoder representations from transformers(BERT)model to avoid the over-fitting.Moreover,through the analysis of different classic annotation techniques used to tag data,an ideal one is chosen for the training model in our proposed scheme.Experiments are conducted on Chinese steel E-commerce datasets.The experimental results show that the training time of a lite BERT(ALBERT)-based method is much shorter than that of BERT-based models,while achieving the similar computational performance in terms of metrics precision,recall,and F1 with BERT-based models.Meanwhile,our proposed approach performs much better than that of combining Word2Vec,bidirectional long short-term memory(Bi-LSTM),and conditional random field(CRF)models,in consideration of training time and F1.

ZmMs33 promotes anther elongation via modulating cell elongation regulators,metabolic homeostasis,and cell wall remodeling in maize

Plant cell elongation depends on well-defined gene regulations,adequate nutrients,and timely cell wall modifications.Anther size is positively correlated with the number and viability of pollen grains,while little is known about molecular mechanisms underlying anther cell elongation.Here,we found that properly activated cell elongation regulators at transcriptional levels in loss-of-function ZmMs33 mutant(ms33-6038)anthers failed to promote maize anther elongation.ZmMs33 deficiency disrupted metabolic homeostasis mainly by inhibiting both photosynthesis in anther endothecium and lipid accumulation in anther tapetum.Importantly,ms33-6038 anthers displayed ectopic,premature and excessive secondary cell wall thickening in anther middle layer,which constrained cell elongation structurally and blocked nutrient flows across different anther wall layers.The metabolic disorder was only found in ms33-6038 mutant rather than several representative male-sterility lines at transcriptional and post-translational levels.Collectively,the disordered metabolisms and blocked nutrient flows defeated the activated cell elongation regulators,and finally inhibited anther elongation and growth with a unique‘‘idling effect”in ms33-6038 mutant.

Improved encoding structure and decoding algorithms for spinal codes

To improve the error correction performance, an innovative encoding structure with tail-biting for spinal codes is designed. Furthermore, an adaptive forward stack decoding(A-FSD) algorithm with lower complexity for spinal codes is proposed. In the A-FSD algorithm, a flexible threshold parameter is set by a variable channel state to narrow the scale of nodes accessed. On this basis, a new decoding method of AFSD with early termination(AFSD-ET) is further proposed. The AFSD-ET decoder not only has the ability of dynamically modifying the number of stored nodes, but also adopts the early termination criterion to curtail complexity. The complexity and related parameters are verified through a series of simulations. The simulation results show that the proposed spinal codes with tail-biting and the AFSD-ET decoding algorithms can reduce the complexity and improve the decoding rate without sacrificing correct decoding performance.