Crystallinity-defect matching relationship of g-C_(3)N_(4): Experimental and theoretical perspectives

Good crystallinity can reduce the charge recombination centers caused by defects,whilst structures with strong polycondensation have high charge mobility,leading to more charge transfer to the material surface for reaction.Much effort has been put into the preparation of a highly efficient g-C_(3)N_(4) with defects to improve its application potential under the premise in high crystallinity.Hence,this review paper emphasizes the importance to balance the defect and crystallinity of g-C_(3)N_(4).In addition,detailed discussion on the relationship between defects and activity of g-C_(3)N_(4) was carried out based on its applications in environmental purification(e.g.,VOCs oxidation,NO_(x) oxidation,H_(2)O_(2) evolution,sterilization,pesticide oxidation)and energy conversion(H_(2) evolution,N_(2) fixation and CO_(2) reduction).Lastly,the challenge in developing more efficient defective g-C_(3)N_(4) photocatalytic materials is summarized.

Research progress on the mechanism of exercise fatigue and the role of probiotics in counteracting it

Exercise fatigue is a physiological phenomenon where the body cannot maintain a specific level after being stimulated by excessive exercise.Its five main theories include“energy depletion”,“accumulation of metabolites”,“homeostasis disorder of the internal environment”,“free radicals”,and“central nervous system protection inhibition”.The imbalance of intestinal flora caused by vigorous exercise can further lead to fatigue.Therefore,maintaining healthy intestinal flora is crucial for athlete health and performance.Recent studies have demonstrated that probiotics can regulate intestinal flora and alleviate exercise fatigue;however,there are no systematic reviews on the anti-fatigue effects of probiotics.Based on the mechanisms of exercise-induced fatigue,this article summarizes the effects and mechanisms by which probiotics combat exercise fatigue,aiming to provide research ideas for the development of probiotics that prevent exercise fatigue.

Analyzing land use characteristics of rural settlements on the urban fringe of Liangjiang New Area, Chongqing, China

The objective of this paper is to analyze land use characteristics of rural settlements in urban fringe so as to provide references for optimizing the regional distribution of rural settlements, consolidating rural settlements, and coordinating urban-rural integrated development. The methods of spatial statistical analysis, buffer analysis, Ripley's K function, kernel density analysis based on GIS(Geographic Information System) were used to analyze the characteristics of scale, spatial differentiation and spatial patterns of the rural settlements in Liangjiang New Area in Chongqing Municipality of China. The fractal dimension formula was also developed to reflect fractal feature of the rural settlements. The results show that, the scale of rural settlements in Liangjang New Area takes on distinct characteristics of spatial differentiation along with changes in elevation, gradient, location, geohazards distribution, and the like. The fractal characteristic of rural settlements has obvious regional variations subject to the 6 factors of location in the Liangjiang New Area. Overall, the worse the terrain conditions are, the larger the fractal dimension values become. The better the locationconditions, the larger the fractal dimension values are. The spatial pattern in the township scale presents three kinds of distribution as being aggregated, uniform and random. In contract, the spatial pattern in the plaque scale displays a banding distribution from a general view with several aggregation zones centering on each town center. From the results, we can see that the characteristics of rural settlements in urban fringe are more complicated. For such kind of rural settlements in special regions, in the rural land consolidation more attention should be paid to improve the rural living environments and public services, as well as to promote the harmonious relationship between the urban and rural areas.

Ecological Restoration Technology and Benefit Assessment of Karst Rocky Desertification Mountains in Xixiu District of Anshun City

Ecological restoration refers to the containment of soil erosion,restoration of water conservation,climate regulation,maintenance of ecological functions of biodiversity,and improvement of ecological environment and landscape pattern based on self-repairing capacity of the nature and combined with appropriate artificial measures. Since the natural restoration process of karst desertification mountain is very long,it needs to be supplemented by artificial vegetation restoration. This paper introduced the ecological restoration technologies implemented in karst rocky desertification mountains in Xixiu District,Anshun City of Guizhou Province,and also introduced the afforestation tending management measures. It assessed the ecological benefits of the ecological restoration project from five aspects: mountain community characteristics,vegetation coverage,species diversity,afforestation survival rate and landscape effect.

Renovation of Road Landscaping in Old Downtown Areas of Mountainous Cities:A Case Study of Pengshui County,Chongqing Municipality

Current situation of road landscaping in old districts of mountainous cities was analyzed,renovation design principles and basis were proposed. Pengshui County in Chongqing was taken for example to explore renovation design methods,overall concepts and relevant contents of the road landscaping in old districts of mountainous cities,so as to provide references for the renovation design of road landscaping in old districts of modern mountainous cities.

Study on Health of Rural Poor Population and Health Poverty Alleviation Countermeasures in Chongqing

[Objectives]The paper was to understand the health of rural poor population in Chongqing,and to put forward countermeasures for health poverty alleviation.[Methods]The 439 people living in poverty in Qianjiang District and Pengshui County,Chongqing,were investigated on the spot to deeply understand and analyze the health status,current medical insurance status and accuracy of medical system of rural poor population in Chongqing.[Results]The vast majority of poor households had been lifted out of poverty after targeted poverty alleviation.Poverty due to illness was the main cause of family poverty.The prevalence of chronic diseases in poor households was high,and the overall health level showed a downward trend.The countermeasures and suggestions for strengthening the construction of medical insurance system,exploring and perfecting rural medical assistance system,enhancing the service capacity of primary medical and health institutions,and strengthening health education and health management were put forward.[Conclusions]The study provides an empirical evidence for improving the health level of poor rural residents and promoting targeted health poverty alleviation policies.

Application Skills of Business English in International Economic and Trade Negotiations

In international economic and trade negotiations, business English communication skills are extremely important and an important factor affecting the success of negotiations. Based on this, the meaning and characteristics of business English and its role in international trade were elaborated in this study, and the obstacles of business English communication skills in international trade negotiations were deeply studied, then optimization strategies for the current problems were put forward, aiming at providing some theoretical reference for the development of foreign economic and trade in China.

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

Demulsification Behavior, Characteristics, and Performance of Surfactant Stabilized Oil-in-Water Emulsion under Bidirectional Pulsed Electric Field

As a novel electric demulsification method,bidirectional pulsed electric field(BPEF)was employed to demulsify the surfactant stabilized oil-in-water(SSO/W)emulsion for oil/water separation in this work.The demulsification behavior,characteristics,and stages under BPEF were explored.It was discovered that BPEF drove SSO/W emulsion to move and form vortexes,during which the oil droplets aggregated and accumulated to generate an oil droplet layer(ODL).ODL subsequently transformed into a continuous oil layer(COL)leading to the demulsification and separation of SSO/W emulsion.The conversion rate of ODL to COL was defined and used to evaluate the demulsification process and reflect the coalescence ability and transformation efficiency of dispersed oil droplets into COL.Furthermore,the effects of BPEF voltage,frequency,duty cycle,ratio of pulse output time,and surfactant type and content on the demulsification performance were examined.The optimal values of BPEF parameters for demulsification operation were 400 V,25 Hz,50%,and 4:1.O/W emulsion containing anionic surfactant was apt to be demulsified by BPEF,nonionic surfactant took the second place and cationic surfactant was the most difficult.A high surfactant content was not conducive to the BPEF demulsification.This work is anticipated to provide useful guidance for oil/water separation and oil recovery from actual emulsified oily wastewater by BPEF.

Cognitive Granular-Based Path Planning and Tracking for Intelligent Vehicle with Multi-Segment Bezier Curve Stitching

Unmanned vehicles are currently facing many difficulties and challenges in improving safety performance when running in complex urban road traffic environments,such as low intelligence and poor comfort perfor-mance in the driving process.The real-time performance of vehicles and the comfort requirements of passengers in path planning and tracking control of unmanned vehicles have attracted more and more attentions.In this paper,in order to improve the real-time performance of the autonomous vehicle planning module and the comfort requirements of passengers that a local granular-based path planning method and tracking control based on multi-segment Bezier curve splicing and model predictive control theory are pro-posed.Especially,the maximum trajectory curvature satisfying ride comfort is regarded as an important constraint condition,and the corresponding curvature threshold is utilized to calculate the control points of Bezier curve.By using low-order interpolation curve splicing,the planning computation is reduced,and the real-time performance of planning is improved,com-pared with one-segment curve fitting method.Furthermore,the comfort performance of the planned path is reflected intuitively by the curvature information of the path.Finally,the effectiveness of the proposed control method is verified by the co-simulation platform built by MATLAB/Simulink and Carsim.The simulation results show that the path tracking effect of multi-segment Bezier curve fitting is better than that of high-order curve planning in terms of real-time performance and comfort.

Bridging the gap between data mining and medical applications

Artificial Intelligence(AI)is one of the most promising and rapidly evolving fields in modern science.It is increasingly being applied to a wide range of domains,including medicine,where it holds enormous potential for improving patient care,reducing costs,and enhancing clinical decision-making.One area of AI that has shown great promise in the medical domain is data mining,which is the process of extracting useful information and knowledge from large data sets.

Contribution and Modern Public Debt:On the Nature of Patriotic Public Debt in the Late Qing Dynasty and the Early Republic of China

There are different opinions about the first modern domestic debt in China.The theorists judge whether a certain public debt has modernity according to whether it has modern public debt form,ignoring the inconsistency between form and content,institutional provisions and actual implementation.The modern nature of public debt must have both the form and content of modern public debt.Based on the analysis of the issuing background,system design,collection and repayment of patriotic bonds in the late Qing Dynasty and the early Republic of China,it is considered that the part of patriotic bonds subscribed by the Qing royal family is still the nature of donation and return,while the part subscribed by ordinary businessmen and people in the early Republic of China has a modern nature.The dual nature of patriotic bonds is closely related to the social background when the bonds are issued.

An Interpretable Light Attention-Convolution-Gate Recurrent Unit Architecture for the Highly Accurate Modeling of Actual Chemical Dynamic Processes

To equip data-driven dynamic chemical process models with strong interpretability,we develop a light attention–convolution–gate recurrent unit(LACG)architecture with three sub-modules—a basic module,a brand-new light attention module,and a residue module—that are specially designed to learn the general dynamic behavior,transient disturbances,and other input factors of chemical processes,respectively.Combined with a hyperparameter optimization framework,Optuna,the effectiveness of the proposed LACG is tested by distributed control system data-driven modeling experiments on the discharge flowrate of an actual deethanization process.The LACG model provides significant advantages in prediction accuracy and model generalization compared with other models,including the feedforward neural network,convolution neural network,long short-term memory(LSTM),and attention-LSTM.Moreover,compared with the simulation results of a deethanization model built using Aspen Plus Dynamics V12.1,the LACG parameters are demonstrated to be interpretable,and more details on the variable interactions can be observed from the model parameters in comparison with the traditional interpretable model attention-LSTM.This contribution enriches interpretable machine learning knowledge and provides a reliable method with high accuracy for actual chemical process modeling,paving a route to intelligent manufacturing.

Deep learning approaches to recover the plasma current density profile from the safety factor based on Grad–Shafranov solutions across multiple tokamaks

Many magnetohydrodynamic stability analyses require generation of a set of equilibria with a fixed safety factor q-profile while varying other plasma parameters.A neural network(NN)-based approach is investigated that facilitates such a process.Both multilayer perceptron(MLP)-based NN and convolutional neural network(CNN)models are trained to map the q-profile to the plasma current density J-profile,and vice versa,while satisfying the Grad–Shafranov radial force balance constraint.When the initial target models are trained,using a database of semianalytically constructed numerical equilibria,an initial CNN with one convolutional layer is found to perform better than an initial MLP model.In particular,a trained initial CNN model can also predict the q-or J-profile for experimental tokamak equilibria.The performance of both initial target models is further improved by fine-tuning the training database,i.e.by adding realistic experimental equilibria with Gaussian noise.The fine-tuned target models,referred to as fine-tuned MLP and fine-tuned CNN,well reproduce the target q-or J-profile across multiple tokamak devices.As an important application,these NN-based equilibrium profile convertors can be utilized to provide a good initial guess for iterative equilibrium solvers,where the desired input quantity is the safety factor instead of the plasma current density.

Some convergence theorems of fuzzy concave integral on fuzzyσ-algebra

In this paper,we consider the extension of the concave integral from classical crispσ-algebra to fuzzyσ-algebra of fuzzy sets.Firstly,the concept of fuzzy concave integral on a fuzzy set is introduced.Secondly,some important properties of such integral are discussed.Finally,various kinds of convergence theorems of a sequence of fuzzy concave integrals are proved.

Defective Nickel-Iron Layered Double Hydroxide for Enhanced Photocatalytic NO Oxidation with Significant Alleviation of NO2 Production

Photocatalysis offers a sustainable means for the oxidative removal of low concentrations of NOx(NO,NO2,N2O,N2O5,etc.)from the atmosphere.Layered double hydroxides(LDHs)are promising candidate photocatalysts owing to their unique layered and tunable chemical structures and abundant surface hydroxide(OH)moieties,which are hydroxyl radical(OH)precursors.However,the practical applications of LDHs are limited by their poor charge-separation ability and insufficient active sites.Herein,we developed a facile N_(2)H_(4)-driven etching approach to introduce dual Ni^(2+)and OHvacancies(Niv and OHv,respectively)into NiFe-LDH nanosheets(hereafter referred to as NiFe-LDH-et)to facilitate improved charge-carrier separation and active Lewis acidic site(Fe^(3+)and Ni^(2+)exposed at OHv)formation.In contrast to inert pristine LDH,NiFe-LDH-et actively removed NO under visible-light illumination.Specifically,Ni_(76)Fe_(24)-LDH-et etched with 1.50 mmol·L^(-1)N_(2)H_(4)solution removed 32.8%of the NO in continuously flowing air(NO feed concentration:500 parts per billion(ppb))under visible-light illumination,thereby outperforming most reported catalysts.Experimental and theoretical data revealed that the dual vacancies promoted the production of reactive oxygen species(O_(2)·^(-)andOH)and the adsorption of NO on the LDH.In situ spectroscopy demonstrated that NO was preferentially adsorbed at Lewis acidic sites,particularly exposed Fe^(3+)sites,converted into NO+,and subsequently oxidized to NO3without the notable formation of the more toxic intermediate NO2,thereby alleviating risks associated with its production and emission.

Exploring the Dynamics of Industrial Convergence Among RCEP Member Countries: An Empirical Study

The evolving dynamics of industrial convergence among the member countries of the Regional Comprehensive Economic Partnership(RCEP)framework have emerged as a significant subject that merits in-depth consideration and analysis.This study initially employs multi-regional input-output(MRIO)data and the social network analysis(SNA)method to delineate the levels and variation trends of this industrial convergence across the RCEP member countries.It then delves into the positive effects of this convergence phenomenon on the trade and investment fields of the member countries.The research findings indicate:(a)In 2006 and 2015,before the implementation of the RCEP,the RCEP member countries displayed a relatively close industrial convergence.The convergence levels exhibited a general upward trend on both the supply and the demand sides,but there were significant disparities in the levels of industrial convergence among the member countries.Furthermore,while the convergence in the three economic sectors showed an increasing trend,the development was uneven across the board.(b)Since the implementation of the RCEP,the trade ties among the member countries within the region have strengthened significantly,and the interplay between the countries’industrial and supply chains has been characterized by high-quality collaboration and demonstrated remarkable resilience.In addition,the convergence in the investment fields of the RCEP member countries and their respective industries has unleashed a wave of positive synergies.These findings offer valuable insights that can serve as a robust foundation for formulating effective policies to advance the growth and prosperity of the RCEP region.

Preparation of Nitrogen-doped TiO2 Nanoparticle Catalyst and Its Catalytic Activity under Visible Light

N-doped TiO2 nanoparticle photocatalysts were prepared through a sol-gel procedure using NH4C1 as the nitrogen source and followed by calcination at certain temperature. Systematic studies for the preparation parameters and their impact on the structure and photocatalytic activity under ultraviolet （UV） and visible light irra-diation were carried out. Multiple techniques （XRD, TEM, DRIF, DSC, and XPS） were commanded to characterize the crystal structures and chemical binding of N-doped TiO2. Its photocatalytic activity was examined by the deg- radation of organic compounds. The catalytic activity of the prepared N-doped TiO2 nanoparticles under visible light （λ〉400nm） irradiation is evidenced by the decomposition of 4-chlorophenol, showing that nitrogen atoms in the N-doped TiO2 nanoparticle catalyst are responsible for the visible light catalytic activity. The N-doped TiO2 nanoparticle catalyst prepared with this modified route exhibits higher catalytic activity under UV irradiation in contrast to TiO2 without N-doping. It is suggested that the doped nitrogen here is located at the interstitial site of TiO2 lattice.

New chaotical image encryption algorithm based on Fisher–Yatess scrambling and DNA coding

Based on the Fisher–Yatess scrambling and DNA coding technology, a chaotical image encryption method is proposed. First, the SHA-3 algorithm is used to calculate the hash value of the initial password, which is used as the initial value of the chaotic system. Second, the chaotic sequence and Fisher–Yatess scrambling are used to scramble the plaintext,and a sorting scrambling algorithm is used for secondary scrambling. Then, the chaotic sequence and DNA coding rules are used to change the plaintext pixel values, which makes the ciphertext more random and resistant to attacks, and thus ensures that the encrypted ciphertext is more secure. Finally, we add plaintext statistics for pixel-level diffusion to ensure plaintext sensitivity. The experimental results and security analysis show that the new algorithm has a good encryption effect and speed, and can also resist common attacks.

Improving the denitration performance and K-poisoning resistance of the V_2O_5-WO_3/TiO_2 catalyst by Ce^(4+) and Zr^(4+) co-doping

A series of V2O5‐WO3/TiO2‐ZrO2,V2O5‐WO3/TiO2‐CeO2,and V2O5‐WO3/TiO2‐CeO2‐ZrO2 catalysts were synthesized to improve the selective catalytic reduction(SCR)performance and the K‐poisoning resistance of a V2O5‐WO3/TiO2 catalyst.The physicochemical properties were investigated by using XRD,BET,NH3‐TPD,H2‐TPR,and XPS,and the catalytic performance and K‐poisoning resistance were evaluated via a NH3‐SCR model reaction.Ce^4+and Zr^4+co‐doping were found to enhance the conversion of NOx,and exhibit the best K‐poisoning resistance owing to the largest BET‐specific surface area,pore volume,and total acid site concentration,as well as the minimal effects on the surface acidity and redox ability from K poisoning.The V2O5‐WO3/TiO2‐CeO2‐ZrO2 catalyst also presents outstanding H2O+SO2 tolerance.Finally,the in situ DRIFTS reveals that the NH3‐SCR reaction over the V2O5‐WO3/TiO2‐CeO2‐ZrO2 catalyst follows an L‐H mechanism,and that K poisoning does not change the reaction mechanism.