Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Design of Protograph LDPC-Coded MIMO-VLC Systems with Generalized Spatial Modulation

This paper investigates the bit-interleaved coded generalized spatial modulation(BICGSM) with iterative decoding(BICGSM-ID) for multiple-input multiple-output(MIMO) visible light communications(VLC). In the BICGSM-ID scheme, the information bits conveyed by the signal-domain(SiD) symbols and the spatial-domain(SpD) light emitting diode(LED)-index patterns are coded by a protograph low-density parity-check(P-LDPC) code. Specifically, we propose a signal-domain symbol expanding and re-allocating(SSER) method for constructing a type of novel generalized spatial modulation(GSM) constellations, referred to as SSERGSM constellations, so as to boost the performance of the BICGSM-ID MIMO-VLC systems.Moreover, by applying a modified PEXIT(MPEXIT) algorithm, we further design a family of rate-compatible P-LDPC codes, referred to as enhanced accumulate-repeat-accumulate(EARA) codes,which possess both excellent decoding thresholds and linear-minimum-distance-growth property. Both analysis and simulation results illustrate that the proposed SSERGSM constellations and P-LDPC codes can remarkably improve the convergence and decoding performance of MIMO-VLC systems. Therefore, the proposed P-LDPC-coded SSERGSM-mapped BICGSMID configuration is envisioned as a promising transmission solution to satisfy the high-throughput requirement of MIMO-VLC applications.

Identifying Spatial Heterogeneity in the Effects of High-Tech Firm Density on Housing Prices:Evidence from Guangdong-Hong Kong-Macao Greater Bay Area,China

Innovation capitalization is a new concept in innovation geography research.Extant research on a city scale has proven that innovation is an important factor affecting housing prices and verified that innovation has a capitalization effect.However,few studies investigate the spatial heterogeneity of innovation capitalization.Thus,case verification at the urban agglomeration scale is needed.Therefore,this study proposes a theoretical framework for the spatial heterogeneity of innovation capitalization at the urban agglomeration scale.Examining the Guangdong-Hong Kong-Macao Greater Bay Area(GHMGBA),China as a case study,the study investigated the spatial heterogeneity of the influence of high-tech firms,representing innovation,on housing prices.This work verified the spatial heterogeneity of innovation capitalization.The study constructed a data set influencing housing prices,comprising 11 factors in 5 categories(high-tech firms,convenience of living facilities,built environment,the natural environment,and the fundamentals of the districts)for 419 subdistricts in the GHMGBA.On the global scale,the study finds that high-tech firms have a significant and positive influence on housing prices,with the housing price increasing by 0.0156%when high-tech firm density increases by 1%.Furthermore,a semi-geographically weighted regression(SGWR)analysis shows that the influence of high-tech firms on housing prices has spatial heterogeneity.The areas where high-tech firms have a significant and positive influence on housing prices are mainly in the GuangzhouFoshan metropolitan area,western Shenzhen-Dongguan,north-central Zhongshan-Nansha district,and Guangzhou—all areas with densely distributed high-tech firms.These results confirm the spatial heterogeneity of innovation capitalization and the need for further discussion of its scale and spatial limitations.The study offers implications for relevant GHMGBA administrative authorities for spatially differentiated development strategies and housing policies that consider the role of innovation in successful urban development.

Consumer behavior patterns of carbon neutral label using the unified theory of acceptance and use of technology

China has paid considerable attention to developing and implementing a carbon labeling system in response to increasing environmental issues such as global warming.This paper aims to provide a theoretical basis for formulating and implementing a carbon labeling system in China through a study of consumer acceptance behavior and its influencing factors.This paper constructed an extended model of consumers’acceptance behavior of carbon neutral labels based on the theories and methods of Unified Theory of Acceptance and Use of Technology(UTAUT)and analyzed the effects of five factors(carbon label cognition,performance expectancy,effort expectancy,social influence,and facilitating factors)on consumer carbon neutral label acceptance and adoption.The structural equation model analysis revealed that carbon label cognition,performance expectancy,social influence,and facilitating factors significantly,and positively impact consumers’acceptance of carbon neutral labels.Moreover,carbon label cognition,performance expectancy,and facilitating factors significantly,and positively affect consumers’carbon neutral label adoption behavior.Meanwhile,carbon label cognition,and effort expectancy have no significant impact on consumers’willingness to accept carbon neutral labels,which in turn significantly impacts consumers’carbon neutral label adoption behavior.According to the research findings,increasing the promotion of carbon labeling and improving the practical strategies and management recommendations for carbon label design are proposed.

Application of artificial synapse based on all-inorganic perovskite memristor in neuromorphic computing

Artificial synapse inspired by the biological brain has great potential in the field of neuromorphic computing and artificial intelligence.The memristor is an ideal artificial synaptic device with fast operation and good tolerance.Here,we have prepared a memristor device with Au/CsPbBr_(3)/ITO structure.The memristor device exhibits resistance switching behavior,the high and low resistance states no obvious decline after 400 switching times.The memristor device is stimulated by voltage pulses to simulate biological synaptic plasticity,such as long-term potentiation,long-term depression,pair-pulse facilitation,short-term depression,and short-term potentiation.The transformation from short-term memory to long-term memory is achieved by changing the stimulation frequency.In addition,a convolutional neural network was constructed to train/recognize MNIST handwritten data sets;a distinguished recognition accuracy of~96.7%on the digital image was obtained in 100 epochs,which is more accurate than other memristor-based neural networks.These results show that the memristor device based on CsPbBr3 has immense potential in the neuromorphic computing system.

Study on trifluoromethanesulfonic acid-promoted synthesis of daidzein: Process optimization and reaction mechanism

Daidzein has been widely used in pharmaceuticals,nutraceuticals,cosmetics,feed additives,etc.Its preparation process and related reaction mechanism need to be further investigated.A cost-effective process for synthesizing daidzein was developed in this work.In this article,a two-step synthesis of daidzein(Friedel–Crafts acylation and[5+1]cyclization)was developed via the employment of trifluoromethanesulfonic acid(TfOH)as an effective promoting reagent.The effect of reaction conditions such as solvent,the amount of TfOH,reaction temperature,and reactant ratio on the conversion rate and the yield of the reaction,respectively,was systematically investigated,and daidzein was obtained in 74.0%isolated yield under optimal conditions.Due to the facilitating effect of TfOH,the Friedel–Crafts acylation was completed within 10 min at 90℃ and the[5+1]cyclization was completed within 180 min at 25℃.In addition,a possible reaction mechanism for this process was proposed.The results of the study may provide useful guidance for industrial production of daidzein on a large scale.

THE GLOBAL EXISTENCE AND ANALYTICITY OF A MILD SOLUTION TO THE 3D REGULARIZED MHD EQUATIONS

In this paper,we study the three-dimensional regularized MHD equations with fractional Laplacians in the dissipative and diffusive terms.We establish the global existence of mild solutions to this system with small initial data.In addition,we also obtain the Gevrey class regularity and the temporal decay rate of the solution.

Performance enhancement of a viscoelastic bistable energy harvester using time-delayed feedback control

This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.

Production of linear alkylbenzene over Ce containing Beta zeolites

Ce-encapsulated Beta zeolite was synthesized by a one-pot hydrothermal method with citric acid complexing Ce in the absence of Na species.Additional citric acid can effectively prevent the deposition of Ce species during the hydrothermal synthesis of zeolites,leading to uniform distribution of Ce cluster in the framework of Beta zeolites.Moreover,the sodium-free synthesis system resulted that the Brønsted acid sites were mainly located on the straight channels and external surface of Beta zeolites,improving the utilization of Brønsted acid sites.In addition,Ce encapsulated Beta zeolites showed enhanced activity and robust stability in the alkylation of benzene with 1-dodecene based on the synergistic effect between Ce species and Brønsted acid sites,which pave the way for its practical application in the production of alkylbenzene.

Tailoring the microstructure of Mg-Al-Sn-RE alloy via friction stir processing and the impact on its electrochemical discharge behaviour as the anode for Mg-air battery

Constructing the magnesium alloy with fine grains,low density of dislocations,and weak crystal orientation is of crucial importance to enhance its comprehensive performance as the anode for Mg-air battery.However,this unique microstructure can hardly be achieved with conventional plastic deformation such as rolling or extrusion.Herein,we tailor the microstructure of Mg-Al-Sn-RE alloy by using the friction stir processing,which obviously refines the grains without increasing dislocation density or strengthening crystal orientation.The Mg-air battery with the processed Mg-Al-Sn-RE alloy as the anode exhibits higher discharge voltages and capacities than that employing the untreated anode.Furthermore,the impact of friction stir processing on the electrochemical discharge behaviour of Mg-Al-Sn-RE anode and the corresponding mechanism are also analysed according to microstructure characterization and electrochemical response.

Dynamics of Land Use/Land Cover Considering Ecosystem Services for a Dense-Population Watershed Based on a Hybrid Dual-Subject Agent and Cellular Automaton Modeling Approach

Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

Efficient Polytelluride Anchoring for Ultralong-Life Potassium Storage: Combined Physical Barrier and Chemisorption in Nanogrid-in-Nanofiber

Metal tellurides(MTes) are highly attractive as promising anodes for high-performance potassium-ion batteries. The capacity attenuation of most reported MTe anodes is attributed to their poor electrical conductivity and large volume variation. The evolution mechanisms, dissolution properties, and corresponding manipulation strategies of intermediates(K-polytellurides, K-pTe_(x)) are rarely mentioned. Herein,we propose a novel structural engineering strategy to confine ultrafine CoTe_(2) nanodots in hierarchical nanogrid-in-nanofiber carbon substrates(CoTe_(2)@NC@NSPCNFs) for smooth immobilization of K-pTe_(x) and highly reversible conversion of CoTe_(2) by manipulating the intense electrochemical reaction process. Various in situ/ex situ techniques and density functional theory calculations have been performed to clarify the formation, transformation, and dissolution of K-pTe_(x)(K_(5)Te_(3) and K_(2)Te), as well as verifying the robust physical barrier and the strong chemisorption of K_(5)Te_(3) and K_(2)Te on S, N co-doped dual-type carbon substrates. Additionally, the hierarchical nanogrid-in-nanofiber nanostructure increases the chemical anchoring sites for K-pTe_(x), provides sufficient volume buffer space, and constructs highly interconnected conductive microcircuits, further propelling the battery reaction to new heights(3500 cycles at 2.0 A g^(-1)). Furthermore, the full cells further demonstrate the potential for practical applications. This work provides new insights into manipulating K-pTe_(x) in the design of ultralong-cycling MTe anodes for advanced PIBs.

Policy Network-Based Dual-Agent Deep Reinforcement Learning for Multi-Resource Task Offloading in Multi-Access Edge Cloud Networks

The Multi-access Edge Cloud(MEC) networks extend cloud computing services and capabilities to the edge of the networks. By bringing computation and storage capabilities closer to end-users and connected devices, MEC networks can support a wide range of applications. MEC networks can also leverage various types of resources, including computation resources, network resources, radio resources,and location-based resources, to provide multidimensional resources for intelligent applications in 5/6G.However, tasks generated by users often consist of multiple subtasks that require different types of resources. It is a challenging problem to offload multiresource task requests to the edge cloud aiming at maximizing benefits due to the heterogeneity of resources provided by devices. To address this issue,we mathematically model the task requests with multiple subtasks. Then, the problem of task offloading of multi-resource task requests is proved to be NP-hard. Furthermore, we propose a novel Dual-Agent Deep Reinforcement Learning algorithm with Node First and Link features(NF_L_DA_DRL) based on the policy network, to optimize the benefits generated by offloading multi-resource task requests in MEC networks. Finally, simulation results show that the proposed algorithm can effectively improve the benefit of task offloading with higher resource utilization compared with baseline algorithms.

Promoted catalytic property of Cu/SSZ-13 by introducing a minority of Mn for NO removal from diesel engine exhaust

The Cu-exchanged SSZ-13 with the small-pore chabazite framework is considered as a highly efficient catalyst for selective catalytic reduction of NO with NH_(3)(NH_(3)-SCR).In order to further improve the catalytic property,a series of Mn ion-assisted Cu/SSZ-13 powder catalysts were prepared by co-exchange method and stepwise exchange method.It is found that the NH_(3)-SCR activity,N_(2) selectivity,hydrothermal stability and sulfur resistance of Cu/SSZ-13 are promoted by introducing a minority of Mn(0.15%to 0.23%(mass))through co-exchange method.Characterization results reveal that the Cu,Mn co-exchange enables the higher amounts of Cu^(2+)active sites,the abundant medium strong and strong acid,the optimized ratio of Lewis acid to Brønsted acid etc.,which are required for a good NH_(3)-SCR catalytic property over broad temperature range and under harsh working environment.Moreover,a monolithic catalyst was prepared by impregnating a cordierite ceramic support into the coating slurry containing the optimized CuMn/SSZ-13 powder.The diesel engine bench tests show that Cu,Mn co-exchange gives the monolith catalyst a better catalytic property than commercial catalysts.This work provides an important guidance for the rational design of secondary-ion-assisted zeolites applied in NH_(3)-SCR.

Leakage Proof,Flame-Retardant,and Electromagnetic Shield Wood Morphology Genetic Composite Phase Change Materials for Solar Thermal Energy Harvesting

Phase change materials(PCMs)offer a promising solution to address the challenges posed by intermittency and fluctuations in solar thermal utilization.However,for organic solid-liquid PCMs,issues such as leakage,low thermal conductivity,lack of efficient solar-thermal media,and flamma-bility have constrained their broad applications.Herein,we present an innova-tive class of versatile composite phase change materials(CPCMs)developed through a facile and environmentally friendly synthesis approach,leveraging the inherent anisotropy and unidirectional porosity of wood aerogel(nanowood)to support polyethylene glycol(PEG).The wood modification process involves the incorporation of phytic acid(PA)and MXene hybrid structure through an evaporation-induced assembly method,which could impart non-leaking PEG filling while concurrently facilitating thermal conduction,light absorption,and flame-retardant.Consequently,the as-prepared wood-based CPCMs showcase enhanced thermal conductivity(0.82 W m^(-1)K^(-1),about 4.6 times than PEG)as well as high latent heat of 135.5 kJ kg^(-1)(91.5%encapsula-tion)with thermal durability and stability throughout at least 200 heating and cooling cycles,featuring dramatic solar-thermal conversion efficiency up to 98.58%.In addition,with the synergistic effect of phytic acid and MXene,the flame-retardant performance of the CPCMs has been significantly enhanced,showing a self-extinguishing behavior.Moreover,the excellent electromagnetic shielding of 44.45 dB was endowed to the CPCMs,relieving contemporary health hazards associated with electromagnetic waves.Overall,we capitalize on the exquisite wood cell structure with unidirectional transport inherent in the development of multifunctional CPCMs,showcasing the operational principle through a proof-of-concept prototype system.

Shape-influenced non-reciprocal transport of magnetic skyrmions in nanoscale channel

Skyrmions, with their vortex-like structures and inherent topological protection, play a pivotal role in developing innovative low-power memory and logic devices. The efficient generation and control of skyrmions in geometrically confined systems are crucial for the development of skyrmion-based spintronic devices. In this study, we focus on investigating the non-reciprocal transport behavior of skyrmions and their interactions with boundaries of various shapes. The shape of the notch structure in the nanotrack significantly affects the dynamic behavior of magnetic skyrmions. Through micromagnetic simulation, the non-reciprocal transport properties of skyrmions in nanowires with different notch structures are investigated in this work.

Exploring the Roles of Single Atom in Hydrogen Peroxide Photosynthesis

This comprehensive review provides a deep exploration of the unique roles of single atom catalysts(SACs)in photocatalytic hydrogen peroxide(H_(2)O_(2))production.SACs offer multiple benefits over traditional catalysts such as improved efficiency,selectivity,and flexibility due to their distinct electronic structure and unique properties.The review discusses the critical elements in the design of SACs,including the choice of metal atom,host material,and coordination environment,and how these elements impact the catalytic activity.The role of single atoms in photocatalytic H_(2)O_(2)production is also analysed,focusing on enhancing light absorption and charge generation,improving the migration and separation of charge carriers,and lowering the energy barrier of adsorption and activation of reactants.Despite these advantages,several challenges,including H_(2)O_(2)decomposition,stability of SACs,unclear mechanism,and low selectivity,need to be overcome.Looking towards the future,the review suggests promising research directions such as direct utilization of H_(2)O_(2),high-throughput synthesis and screening,the creation of dual active sites,and employing density functional theory for investigating the mechanisms of SACs in H_(2)O_(2)photosynthesis.This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H_(2)O_(2)production.

Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

Synthesis strategies of hard carbon anodes for sodium-ion batteries

Sodium-ion battery(SIB)is an ideal candidate for large-scale energy storage due to high abundant sodium sources,relatively high energy density,and potentially low costs.Hard carbons,as one of the most promising anodes,could deliver high plateau capacities at low potentials,which boosts the energy densities of SIBs.Their slope capacities have been demonstrated from the defect adsorption of sodium ions,while the plateau capacity depends highly on intercalation and pore filling.Nevertheless,the specific structures of sodium ions stored in hard carbons have not been clarified,namely active sites of adsorption,intercalation,and pore-filling mechanisms.Therefore,delicate synthesis methods are required to prepare hard carbons with controllable specific structures,along with elucidating the precise active sites for enhancing the Na-ion storage performance.To offer databases for future designs,we summarized the synthesis strategies of hard carbon anodes for constructing active sites of plateau capacities.Synthesis methods were highlighted with corresponding influences on the meticulous structures of hard carbons and Na-ion storage behaviors.Last but not least,perspectives were proposed for developing hard carbon anodes from the points of research and practical applications.