Spatiotemporal changes in sunshine duration and its influential factors in Chongqing,China from 1961 to 2020

The surface solar radiation in most parts of the world has undergone a phenomenon known as global dimming and brightening,characterized by an initial decrease followed by an increase.As a result,the sunshine duration(SD)has decreased in the past 60 years.Against the backdrop of global dimming and brightening,SD has decreased to varying degrees in many regions of China.Using the observed data of SD,cloud amount(total cloud amount and low cloud amount,abbreviated as TCA and LCA),precipitation,and relative humidity(RH)from 34 meteorological stations in Chongqing during the period of 1961-2020,along with a digital elevation model(DEM)with a resolution of 90 m,this study analyzed the spatiotemporal variations and influencing factors of SD.The analysis employed methods such as linear regression,Mann-Kendall test,wavelet transformation,and DEM-based possible SD distributed model.The results showed that the annual SD in Chongqing has significantly decreased over the last 60 years,with a decreasing interannual trend rate(ITR)of 40.4 h/10a.Except for no obvious trend in spring,SD decreased significantly in summer,autumn and winter at the ITR of 21.1 h/10a,8.5 h/10a and 7.5 h/10a,respectively.An abrupt decrease in the annual SD was found in 1979.The difference before and after the abrupt decrease was 177.7 h.The difference before and after the abrupt decrease was 177.7 h.The annual SD possessed the oscillation period of 11a.The spatial heterogeneity of the mean annual SD during the last 60 years was obvious.The distribution of SD in Chongqing is high in the northeast and low in the southeast.In addition,about 73%of the total area in Chongqing showed a significant and very significant decreasing trend.The regions with significant changes are mainly concentrated in the regions with altitudes of 200~1000 m.The increasing LCA was the main cause of the decrease of the annual SD in the regions with 200-400 m altitude decreased the most and changed the most.Increasing LCA is the primary cause of the reduction in annual SD,showing a strong negative correlation coefficient of-0.7292.In Chongqing,PM2.5 concentration showed a significant decrease trend in annual,spring,autumn and winter during 2000-2020,but the significant correlation between PM2.5 concentration and SD was only in autumn and reached an extremely significant level.

Comprehensive evaluation and spatial-temporal evolution characteristics of urban resilience in Chengdu-Chongqing Economic Circle

To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.

Professional Career Planning Status Quo Analysis of University Students--Set a Certain University in Chongqing as an Example

This survey sets students in a Chongqing university as examples and on this basis, combining the author＇s perennial professional career planning education experience to analyze and study university students＇ professional career planning status quo in recent years and the deep-seated reasons for the difficulties of career planning, employment and adaptability to explore more effective, more proactive methods for university students＇ career planning education tasks.

Assessing agricultural eco-efficiency in Chongqing,2004-2019

Agricultural eco-efficiency is an important indicator to measure the sustainable development and high-quality development of agriculture.Based on the agricultural input-output data of 37 districts(counties)in Chongqing from 2004 to 2019,this paper uses the static SBM model and the DDF-BML index method to calculate the agricultural eco-efficiency of each district and county in Chongqing and conduct a comparative analysis.The comprehensive analysis of static and dynamic calculation results shows that the agricultural eco-efficiency of Chongqing is low,the agricultural input-output efficiency of various districts and counties is insufficient,and slack variables are common,so the ability of agricultural sustainable development still needs to be improved.The main sources of agricultural eco-efficiency are the progress of agricultural green technology and the efficiency of agricultural green technology.However,as far as the actual situation of Chongqing is concerned,the efficiency of agricultural green technology shows a downward trend,which has an inhibitory effect on the improvement of agricultural eco-efficiency.Therefore,in the process of agricultural ecological development in the future,Chongqing will focus on improving the efficiency of agricultural green technology as a starting point,implement agricultural technology innovation and promotion,improve the level of farmers’science and technology and culture,and achieve"technology to the countryside,demonstration to households,and application to the country."At the same time,it is necessary to further improve the construction of agricultural and rural infrastructure,and promote the"outward migration"of frontier technologies in agricultural production to radiate agricultural development in surrounding districts and counties.

Flexible and Robust Functionalized Boron Nitride/Poly(p‑Phenylene Benzobisoxazole)Nanocomposite Paper with High Thermal Conductivity and Outstanding Electrical Insulation

With the rapid development of 5G information technology,thermal conductivity/dissipation problems of highly integrated electronic devices and electrical equipment are becoming prominent.In this work,“high-temperature solid-phase&diazonium salt decomposition”method is carried out to prepare benzidine-functionalized boron nitride(m-BN).Subsequently,m-BN/poly(pphenylene benzobisoxazole)nanofiber(PNF)nanocomposite paper with nacremimetic layered structures is prepared via sol–gel film transformation approach.The obtained m-BN/PNF nanocomposite paper with 50 wt%m-BN presents excellent thermal conductivity,incredible electrical insulation,outstanding mechanical properties and thermal stability,due to the construction of extensive hydrogen bonds andπ–πinteractions between m-BN and PNF,and stable nacre-mimetic layered structures.Itsλ∥andλ_(⊥)are 9.68 and 0.84 W m^(-1)K^(-1),and the volume resistivity and breakdown strength are as high as 2.3×10^(15)Ωcm and 324.2 kV mm^(-1),respectively.Besides,it also presents extremely high tensile strength of 193.6 MPa and thermal decomposition temperature of 640°C,showing a broad application prospect in high-end thermal management fields such as electronic devices and electrical equipment.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

THE EXISTENCE AND UNIQUENESS OF TIME-PERIODIC SOLUTIONS TO THE NON-ISOTHERMAL MODEL FOR COMPRESSIBLE NEMATIC LIQUID CRYSTALS IN A PERIODIC DOMAIN

In this paper,we are concerned with a three-dimensional non-isothermal model for the compressible nematic liquid crystal flows in a periodic domain.Under some smallness and structural assumptions imposed on the time-periodic force,we establish the existence of the time-periodic solutions to the system by using a regularized approximation scheme and the topological degree theory.We also prove a uniqueness result via energy estimates.

Transformer-Based Cloud Detection Method for High-Resolution Remote Sensing Imagery

Cloud detection from satellite and drone imagery is crucial for applications such as weather forecasting and environmentalmonitoring.Addressing the limitations of conventional convolutional neural networks,we propose an innovative transformer-based method.This method leverages transformers,which are adept at processing data sequences,to enhance cloud detection accuracy.Additionally,we introduce a Cyclic Refinement Architecture that improves the resolution and quality of feature extraction,thereby aiding in the retention of critical details often lost during cloud detection.Our extensive experimental validation shows that our approach significantly outperforms established models,excelling in high-resolution feature extraction and precise cloud segmentation.By integrating Positional Visual Transformers(PVT)with this architecture,our method advances high-resolution feature delineation and segmentation accuracy.Ultimately,our research offers a novel perspective for surmounting traditional challenges in cloud detection and contributes to the advancement of precise and dependable image analysis across various domains.

Recension of boron nitride phase diagram based on high-pressure and high-temperature experiments

Cubic boron nitride and hexagonal boron nitride are the two predominant crystalline structures of boron nitride.They can interconvert under varying pressure and temperature conditions.However,this transformation requires overcoming significant potential barriers in dynamics,which poses great difficulty in determining the c-BN/h-BN phase boundary.This study used high-pressure in situ differential thermal measurements to ascertain the temperature of h-BN/c-BN conversion within the commonly used pressure range(3-6 GPa)for the industrial synthesis of c-BN to constrain the P-T phase boundary of h-BN/c-BN in the pressure-temperature range as much as possible.Based on the analysis of the experimental data,it is determined that the relationship between pressure and temperature conforms to the following equation:P=a+1/bT.Here,P denotes the pressure(GPa)and T is the temperature(K).The coefficients are a=-3.8±0.8 GPa and b=229.8±17.1 GPa/K.These findings call into question existing high-pressure and high-temperature phase diagrams of boron nitride,which seem to overstate the phase boundary temperature between c-BN and h-BN.The BN phase diagram obtained from this study can provide critical temperature and pressure condition guidance for the industrial synthesis of c-BN,thus optimizing synthesis efficiency and product performance.

THE GLOBAL WELL-POSEDNESS OF SOLUTIONS TO COMPRESSIBLE ISENTROPIC TWO-FLUID MAGNETOHYDRODYNAMICS IN A STRIP DOMAIN

In this paper,we consider a model of compressible isentropic two-fluid magneto-hydrodynamics without resistivity in a strip domain in three dimensional space.By exploiting the two-tier energy method developed in[Anal PDE,2013,6:1429–1533],we prove the global well-posedness of the governing model around a uniform magnetic field which is non-parallel to the horizontal boundary.Moreover,we show that the solution converges to the steady state at an almost exponential rate as time goes to infinity.Compared to the work of Tan and Wang[SIAM J Math Anal,2018,50:1432–1470],we need to overcome the difficulties caused by particles.

Antagonism effect of residual S triggers the dual-path mechanism for water oxidation

Transition metal chalcogenides(TMCs)are recognized as pre-catalysts,and their(oxy)hydroxides derived from electrochemical reconstruction are the active species in the water oxidation.However,understanding the role of the residual chalcogen in the reconstructed layer is lacking in detail,and the corresponding catalytic mechanism remains controversial.Here,taking Cu_(1-x)Co_(x)S as a platform,we explore the regulating effect and existence form of the residual S doped into the reconstructive layer for oxygen evolution reaction(OER),where a dual-path OER mechanism is proposed.First-principles calculations and operando~(18)O isotopic labeling experiments jointly reveal that the residual S in the reconstructive layer of Cu_(1-x)Co_(x)S can wisely balance the adsorbate evolution mechanism(AEM)and lattice oxygen oxidation mechanism(LOM)by activating lattice oxygen and optimizing the adsorption/desorption behaviors at metal active sites,rather than change the reaction mechanism from AEM to LOM.Following such a dual-path OER mechanism,Cu_(0.4)Co_(0.6)S-derived Cu_(0.4)Co_(0.6)OSH not only overcomes the restriction of linear scaling relationship in AEM,but also avoids the structural collapse caused by lattice oxygen migration in LOM,so as to greatly reduce the OER potential and improved stability.

A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.

MSADCN:Multi-Scale Attentional Densely Connected Network for Automated Bone Age Assessment

Bone age assessment(BAA)helps doctors determine how a child’s bones grow and develop in clinical medicine.Traditional BAA methods rely on clinician expertise,leading to time-consuming predictions and inaccurate results.Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations.This operation is costly and subjective.To address these problems,we propose a multi-scale attentional densely connected network(MSADCN)in this paper.MSADCN constructs a multi-scale dense connectivity mechanism,which can avoid overfitting,obtain the local features effectively and prevent gradient vanishing even in limited training data.First,MSADCN designs multi-scale structures in the densely connected network to extract fine-grained features at different scales.Then,coordinate attention is embedded to focus on critical features and automatically locate the regions of interest(ROI)without additional annotation.In addition,to improve the model’s generalization,transfer learning is applied to train the proposed MSADCN on the public dataset IMDB-WIKI,and the obtained pre-trained weights are loaded onto the Radiological Society of North America(RSNA)dataset.Finally,label distribution learning(LDL)and expectation regression techniques are introduced into our model to exploit the correlation between hand bone images of different ages,which can obtain stable age estimates.Extensive experiments confirm that our model can converge more efficiently and obtain a mean absolute error(MAE)of 4.64 months,outperforming some state-of-the-art BAA methods.

Precise Determination of the Bottom-Quark On-Shell Mass Using Its Four-Loop Relation to the■-Scheme Running Mass

We explore the properties of the bottom-quark on-shell mass(Mb)by using its relation to the■mass■.At present,this■-on-shell relation has been known up to four-loop QCD corrections,which however still has a~2%scale uncertainty by taking the renormalization scale as■and varying it within the usual range of■.

Thermal conductivity of iron under the Earth’s inner core pressure

The thermal conductivity ofε-iron at high pressure and high temperature is a key parameter to constrain the dynamics and thermal evolution of the Earth’s core.In this work,we use first-principles calculations to study the Hugoniot sound velocity and the thermal transport properties ofε-iron.The total thermal conductivity considering lattice vibration is 200 W/mK at the Earth’s inner core conditions.The suppressed anharmonic interactions can significantly enhance the lattice thermal conductivity under high pressure,and the contribution of the lattice thermal conductivity should not be ignored under the Earth’s core conditions.

The Mediating Effect of Digital Transformation on the Link Between Executive Overconfidence and Corporate Green Innovation

Green technological innovation is crucial for the manufacturing industry’s green transformation and sustainable development.This study examines the impact of executive overconfidence on corporate green innovation,focusing on the internal drivers of corporate innovation and using a sample of Shanghai and Shenzhen A-share listed manufacturing companies from 2013 to 2020.We further examine the mediating role of digital transformation and the moderating role of external attention.The findings indicate that executive overconfidence promotes corporate green technological innovation.Overconfident executives enhance green innovation by accelerating digital transformation.Moreover,external attention from analysts and media positively moderates the relationship between executive overconfidence and corporate green innovation.Heterogeneity analysis reveals that the positive impact of executive overconfidence on green innovation is more significant in non-state-owned enterprises,high-tech firms,and enterprises with lower pollution levels.

Transformation power or development pressure:economic growth targets and urban carbon productivity

Maintaining moderate economic growth targets(EGTs)is the key for local governments to effectively implement the“carbon peak and carbon neutrality”goals under the refreshed development pattern.Utilizing panel data of 276 prefecture-level cities in China's Mainland from 2010 to 2020,and employing methods such as intermediary and threshold models,this study empirically analyzes the internal mechanism of EGT’s impact on urban carbon productivity(UCP).Our findings demonstrate that:①The overall EGT during the analyzed period is not conducive to improving UCP.This conclusion remains valid after a series of robustness tests.This effect is more pronounced in the central region and resource-based cities than in the east-west region and non resource-based cities.②EGT not only directly suppresses UCP but also exerts indirect negative impacts on UCP from three aspects:delaying the digital economy(DE),constraining financial expansion(FE),and hindering green technology innovation(GTI).This negative indirect effect is similar to or even surpasses the direct effect,suggesting that the internal relationship between EGT and“dual-carbon”goals should be re-evaluated from a new compound perspective.③EGT not only has a simple linear impact on UCP but also significantly exhibits a dynamic evolution pattern in inverted“U”shape.That is,as EGT continuously upgrades,a nonlinear impact on UCP emerges in the form of“promoting first,suppressing later”.This indicates that surpassing the“degree”limit for EGT will be detrimental to the improvement of UCP.This study broadens the scope of carbon productivity analysis by introducing a new perspective centered on EGT.The insights gleaned from this research offer valuable guidance for local governments to effectively manage economic growth expectations and promote the synchronized achievement of dual-carbon objectives.

Exploring social-ecological system resilience in South China Karst:Quantification,interaction and policy implication

China’s Grain to Green Program(GTGP),which is one of the largest payments for ecosystem services(PES)in the world,has made significant ecological improvements to the environment.However,current understanding of its outcomes on the social-ecological system(SES)remains limited.Therefore,taking the South China Karst as an example,a SES resilience evaluation index system was constructed followed by an exploratory spatial analysis,root mean square error,and Self-Organizing Feature Map to clarify the spatiotemporal changes and relationship of SES resilience,achieve the zoning of SES resilience and provide restoration measures.The results showed an upward trend in social resilience from 2000 to 2020,especially its subsystem of social development.Regional ecological resilience was stable,owing to a slightly declined ecosystem services and increased landscape pattern.Spatially,nearly half of the counties exhibited a distribution mismatch in SES resilience.There was an obvious inverted U-shaped relationship of SES resilience,indicating a clear threshold effect,and the constraint relation-ship of SES resilience eased over time,demonstrating the effectiveness of the ecological restoration program.GTGP played a positive role in reducing regional SES trade-off,but this positive effect was limited,reflecting the limitations of overemphasizing the conversion from farmland to forest and grassland.Regional SES resilience can be divided into four clusters,which were the key optimization zone for social system,the SES resilience safety zone,the key restoration zone for SES resilience,and the key optimization zone for ecological system.Adaptive adjustments for the GTGP in these zones should be taken to achieve maximum SES benefits in the future.

Spatial diversion and coordination of flood water for an urban flood control project in Suzhou, China

Suzhou City,located in the Yangtze River Delta in China,is prone to flooding due to a complex combination of natural factors,including its monsoon climate,low elevation,and tidally influenced position,as well as intensive human activities.The Large Encirclement Flood Control Project(LEFCP)was launched to cope with serious floods in the urban area.This project changed the spatiotemporal pattern of flood processes and caused spatial diversion of floods from the urban area to the outskirts of the city.Therefore,this study developed a distributed flood simulation model in order to understand this transition of flood processes.The results revealed that the LEFCP effectively protected the urban areas from floods,but the present scheduling schemes resulted in the spatial diversion of floods to the outskirts of the city.With rainstorm frequencies of 10.0%to 0.5%,the water level differences between two representative water level stations(Miduqiao(MDQ)and Fengqiao(FQ))located inside and outside the LEFCP area,ranged from 0.75 m to 0.24 m and from 1.80 m to 1.58 m,respectively.In addition,the flood safety margin at MDQ and the duration with the water level exceeding the warning water level at FQ ranged from 0.95 m to 0.43 m and from 4 h to 22 h,respectively.Rational scheduling schemes for the hydraulic facilities of the LEFCP in extreme precipitation cases were developed ac-cording to food simulations under seven scheduling scenarios.This helps to regulate the spatial flood diversion caused by the LEFCP during extreme precipitation.

The Impact of the Digital Economy on Rural Residents’Working Hours:Mechanisms and Empirical Evidence

The rapid development of the digital economy has provided a new impetus for rural residents to extend their working hours.Based on the data collected by the China Labor-force Dynamics Survey(CLDS)in 2014,2016,and 2018,this paper measured the development level of the digital economy in China from the perspectives of internet development and digital financial inclusion,and tested the mechanisms of how the digital economy affected rural residents’working hours.The results showed that the digital economy extended rural residents’working hours by expanding information channels and enhancing human capital,and this mechanism was affected by heterogeneity in rural residents’educational background,age,and social capital.Building on these findings,this paper holds that to increase rural residents’income by extending their working hours and achieving common prosperity for all,it is necessary to expand the opportunities for rural residents to participate in skills training and promote their accumulation of human capital.