Secondary Output Research Articles

The impact of topical tranexamic acid on drain duration and seroma volume in axillary lymph node dissection for breast cancer: A randomized controlled trial.

Seroma is the most common complication after breast surgery. Some studies showed that tranexamic acid (TA) can be used in breast surgery to reduce seroma formation and drain volume. We studied the effect of intra-operative and postoperative topical TA on the duration of drain and volume of seroma in patients undergoing axillary lymph node dissection (ALND) for breast cancer. Breast cancer patients planned for ALND were enrolled in the study between July 2020 and July 2021. Patients were randomized into three groups where one group (n=50) received a single intraoperative dose of diluted topical TA, the second group, in addition, received daily postoperative doses till day 5 through the suction drain, and the third group (n=50) did not receive any dose. Chi-square tests and ANOVA were used to analyze the primary outcomes-the total volume of drain fluid and total drain duration, and secondary outcomes-daily drain output till postoperative-day-5, wound infection, and seroma rates. Patients receiving multiple doses of topical TA had a decreasing trend in total drain volume, although this was not statistically significant (1597 vs. 1763 vs. 1773mL: p=0.269). There was no significant change in the duration of the postoperative drain (21.6 vs. 19.2 vs. 19.55days: p=0.54). There was no statistically significant difference in complications between the groups. There is no significant reduction in drain duration, total drain volume, or the rate of complications with the use of single or multiple doses of topical TA.

Machine learning for gap‐filling in greenhouse gas emissions databases

AbstractGreenhouse gas (GHG) emissions datasets are often incomplete due to inconsistent reporting and poor transparency. Filling the gaps in these datasets allows for more accurate targeting of strategies aiming to accelerate the reduction of GHG emissions. This study evaluates the potential of machine learning methods to automate the completion of GHG datasets. We use three datasets of increasing complexity with 18 different gap‐filling methods and provide a guide to which methods are useful in which circumstances. If few dataset features are available, or the gap consists only of a missing time step in a record, then simple interpolation is often the most accurate method and complex models should be avoided. However, if more features are available and the gap involves non‐reporting emitters, then machine learning methods can be more accurate than simple extrapolation. Furthermore, the secondary output of feature importance from complex models allows for data collection prioritization to accelerate the improvement of datasets. Graph‐based methods are particularly scalable due to the ease of updating predictions given new data and incorporating multimodal data sources. This study can serve as a guide to the community upon which to base ever more integrated frameworks for automated detailed GHG emissions estimations, and implementation guidance is available at https://hackmd.io/@luke‐scot/ML‐for‐GHG‐database‐completion and https://doi.org/10.5281/zenodo.10463104. This article met the requirements for a gold‐gold JIE data openness badge described at http://jie.click/badges.

Multi-Omics Analyses of Lettuce (Lactuca sativa) Reveals Primary Metabolism Reorganization Supporting Distinct Features of Secondary Metabolism Induced by Supplementing UV-A Radiation.

UV can serve as an effective light spectrum for regulating plant secondary metabolites, while relevant studies on UV-A are much less extensive than those on UV-B. A comprehensive understanding of the selective effects of UV-A on different secondary metabolites and the specific features of primary metabolism that drive these effects is still lacking. To address this knowledge gap, we conducted a study to analyze the dynamic changes in the metabolome and transcriptome of lettuce leaves irradiated with red plus UV-A light (monochromatic red light as control). Generally, UV-A promoted the synthesis of most phenylpropanoids and terpenoids originating from the shikimate and methylerythritol phosphate (MEP) pathway in plastids but sacrificed the synthesis of terpenoids derived from the mevalonate (MVA) pathway, particularly sesquiterpenes. Increased precursors supply for the shikimate and MEP pathway under UV-A was directly supported by the activation of the Calvin-Benson cycle and phosphoenolpyruvate transport. Whereas, along with phosphoenolpyruvate transport, the TCA cycle was restrained, causing deprivation of the MVA pathway precursor. In addition, UV-A also activated the plastidic oxidative branch of the pentose phosphate pathway, photorespiration, and malate shuttle, to ensure a sufficient supply of nitrogen, circulation homeostasis of the Calvin-Benson cycle, and energy balance, thus indirectly supporting UV-A-induced specific secondary metabolic output. This study provides a comprehensive framework for understanding the flexible primary-secondary metabolism interactions that are able to produce specific metabolites favorable for adaptation to environmental stimuli.

Is carbon emission trading policy a panacea? The implications of promoting green total factor productivity

Market‐based environmental regulation is crucial in influencing environmental and socioeconomic development. Carbon emission trading (CET) policy in China has been implemented since 2012 to balance the environment and economy, especially the green total factor productivity (GTFP). Most previous studies have only conducted short‐term investigations on the impact of CET on environmental and socioeconomic development. In this study, we investigated panel data from 30 regions in China during 2003–2019, adopted the Global Malmquist‐Luenberger and Super‐SBM methods to measure GTFP, and employed the propensity score matched difference in difference (PSM‐DID) to investigate the effect of CET policy on the environment, GTFP, and secondary industry output. The results indicate that CET policy has a positive influence on carbon emission reduction, contributes to the improvement of GTFP, and provides economic value. Therefore, we believe that CET policy can effectively help China to achieve a win‐win scenario of environmental protection and economic growth.

The impact of carbon emission trading schemes on China’s economic inequalities between and within urban and rural areas based on the satellite data: a county-level analysis

ABSTRACT Although China’s carbon emission trading schemes (CETS) garnered significant attention in the field of climate mitigation, limited data availability has hindered exploration into the impact of CETS on economic inequality at the county level in China. Given its potential to facilitate industrial upgrading and generate employment opportunities, the adoption of CETS holds promise for reducing economic inequality. To address data limitations, we employed a combination of gridded nighttime light data and land use data to estimate China’s county-level Dagum Gini coefficient and its components. Subsequently, we applied a difference-in-difference-in-difference method to examine how CETS affected economic inequalities between and within urban and rural areas in China. Our findings reveal that: (1) CETS significantly reduced overall economic inequality in counties with a high proportion of secondary industry output; (2) this reduction primarily occurred within urban and rural areas rather than between them. Further heterogeneity analysis demonstrates that while CETS effectively mitigated economic inequality between urban and rural areas in central and western regions, it did not achieve similar outcomes in the eastern region; (3) service industry development and rural GDP per capita served as important channels through which CETS reduced economic inequality within rural areas. Infrastructure development driven by CETS primarily addressed economic inequality within urban areas rather than rural areas.

Analysis of the Coupling Coordination between the Ecosystem Service Value and Urbanization in the Circum-Bohai-Sea Region and Its Obstacle Factors

In light of the tremendous pressure for improving urbanization levels and expanding construction land on ecosystems, regional sustainable development is premised on the coordinated development of the ecological environment and urbanization. This paper focuses on the Circum-Bohai-Sea Region and assesses the ecosystem service value (ESV) and urbanization level using the equivalence factor and entropy-weighted TOPSIS methods. Based on these assessments, it examines the coupling coordination between the ESV and urbanization as well as the obstacles to this coordination, utilizing the coupling coordination degree model, spatial autocorrelation model, and obstacle model. The results revealed several key findings. First, the Circum-Bohai-Sea Region experienced a continuous improvement in the urbanization level from 2005 to 2020, which presented a “center–periphery” spatial pattern. Overall, the ESV exhibited an N-shaped trend, namely, initially increasing, then decreasing, and then rapidly increasing. The ESV per unit of area exhibited a spatial difference, with the boundary of Baoding and Cangzhou as the dividing line. The ESV per unit of area in the northern parts was higher than that in the southern parts. Second, the degree of the coupling coordination between the ESV and urbanization exhibited an inverted U-shaped trend, initially increasing and then slightly decreasing. It also exhibited significant spatial heterogeneity, with the degree of the coupling coordination in the northern parts being higher than that in the southern parts and that in the central parts being higher than those in the eastern and western parts. Additionally, the ESV showed a significant spatially positive correlation with urbanization. H-H clusters were predominantly found in central and southern Liaoning Province, while L-L clusters were primarily located in southern Hebei Province and western Shandong Province. Third, the obstacle factors remained stable during the study period. The top five obstacles in the ESV system were the water resource supply, nutrient cycling maintenance, raw material production, aesthetic landscape, and food production. Moreover, the top five obstacles in the urbanization system were the number of college students per 10,000 people, population density, number of health technical personnel per 10,000 people, per capita road area, and proportion of secondary and tertiary industry output values.

A hierarchically normalized physics-informed neural network for solving differential equations: Application for solid mechanics problems

Physics-informed neural networks (PINNs) usually confront significant difficulties to accurately solve partial differential equations (PDEs) due to many pathologies caused by gradient failures during training process. In this paper, a gradient disease regarding the ill-conditioned loss function of the PINN methodology is intensively investigated in both theoretical and experimental aspects. Particularly, the regular PINN approaches can obtain good predictions for trivial problems but may fail to learn solutions when their PDE coefficients and/or physical domain sizes vary. Besides, the influences of neural network structure to the PINN training quality are inferred from the theoretical analyses and also confirmed by relating experiments, in which using large-width multi-layer perceptrons (MLPs) is proved to be beneficial in stabilizing PINN training process. To overcome the abovementioned restrictions, a novel PINN methodology using hierarchically normalized technique (hnPINN) motivated from the developed theory is devised. The key idea of the proposed hnPINN is, on the one hand, to transform the original PDE system into one of two proposed dimensionless forms to alleviate the negative effects of PDE coefficients and domain size; on the other hand, to use secondary output scalers to flexibly calibrate the gradient flow for training effectively and improving the solution preciseness. The determination of the secondary output scaler is formulated by a heuristic framework inspired from theoretical analyses on the hnPINN gradient flow. The obtained results from some typical PDEs and common problems in solid mechanics strongly confirm the high effectiveness of the hnPINN in terms of solution accuracy, superior convergence and performance stability in comparison to those of the vanilla PINN and the non-dimensionalized PINN (ndPINN). As a preprocessing procedure, the hnPINN method is independent on network architectures and also greatly potential to combine with other state-of-the-art PINN models for effectively solving challenged issues in practice.

Error state prediction method for electronic voltage transformer based on empirical mode decomposition and auto-regressive moving average

Electronic voltage transformers have been used in the power system in conjunction with the development of power grid intelligence due to their good insulation structure, economy, volume, and other advantages. However, in its long-term operation, the phenomena of error overshooting and unstable operation will inevitably occur, and the existing periodic off-line testing methods require a high calibration cycle, which is difficult to achieve. To solve these problems, an error state prediction method based on empirical mode decomposition and autoregressive moving average model is proposed. Firstly, according to the physical correlation between the secondary output signal and the error, the output signal is quantified as a statistic Q by the method of principal component analysis, and then the statistic is used as the prediction object to establish a prediction model for predicting the operating state of the electronic voltage transformer. The simulation results show that the model can accurately predict the trend of the transformer error, which meets the prediction requirements.

TWO-CHANNEL BALLISTIC TRANSFORMER GRAVIMETER

The two-channel ballistic transformer gravimeter for measuring the doubled value of the acceleration of gravity contains a gravimeter that uses a fixed glass tube made of a dielectric material, a magnetized test body in the form of a layer, a computer and an inductance winding, which is characterized by the fact that the fixed tube is made of a dielectric material, the inductance winding acts as a primary excitation winding connected to the power source, which additionally contains two identical sections of the secondary output winding, connected in series-opposite, to create two measurement channels, an electromagnet consisting of an armature made of magnetic material, an additional winding connected through a switch to an additional power source. To provide free vertical movement in two opposite directions along the OZ axis of the magnetized test body, it is proposed to use the proposed electromagnet consisting of an armature made of a soft magnetic material, an additional winding connected through a switch to an additional power source. The winding of the electromagnet is connected to the power source by a switch to create an electromagnetic flux of attraction to the test body, which, thanks to this, will rise to the uppermost position. At the next moment, the electromagnet switch is turned off, and the test body falls down under the action of the acceleration of gravity. The doubled output signal of the acceleration of gravity, which is removed from the secondary winding, is free from the effects of interference: external electromagnetic flows, inertial vertical acceleration, instrumental errors caused by changes in temperature, humidity, vibrations, pressure, the moment of dry friction forces, non-identity of the parameters of two identical sections of the secondary output winding and other factors - is submitted to the computer. The output of the computer is proportional to twice the acceleration of gravity value. Increased accuracy and reliability of measurements of the doubled value of the acceleration of gravity and increased efficiency of the search for minerals have been ensured

Analysis of Extreme Random Uncertainty in Energy and Environment Systems for Coal-Dependent City by a Copula-Based Interval Cost–Benefit Stochastic Approach

Extreme random events will interfere with the inversion analysis of energy and environment systems (EES) and make the planning schemes unreliable. A Copula-based interval cost–benefit stochastic programming (CICS) is proposed to deal with extreme random uncertainties. Taking Yulin city as an example, there are nine constraint-violation scenarios and six coal-reduction scenarios are designed. The results disclose that (i) both system cost and pollutant emission would decrease as the industrial energy supply constraint-violation level increases; (ii) when the primary and secondary energy output increases by 9% and 13%, respectively, and industrial coal supply decreases by 40%, the coal-dependent index of the system would be the lowest, and the corresponding system profitability could reach [29.3, 53.0] %; (iii) compared with the traditional chance-constrained programming, Copula-based stochastic programming can reflect more uncertain information and achieve a higher marginal net present value rate. Overall, the CICS-EES model offers a novel approach to gain insight into the tradeoff between system reliability and profitability.

Dynamic variation and driving mechanisms of land use change from 1980 to 2020 in the lower reaches of the Yangtze River, China

To systematically explore land use/cover change (LUCC) trends and driving mechanisms at the large watershed scale under the background of climate change and rapid urbanization. Taking the lower reaches of the Yangtze River (LRYR) as the research object, based on the land use remote sensing monitoring data from 1980 to 2020, the spatial and temporal evolution characteristics of LUCC in LRYR were analyzed by adopting the methods of land use dynamics degree (LUDD) and hotspot analysis and used geospatial detectors to quantitatively assess the intensity of the role of the land use change drivers in the LRYR. The results show that: 1) The land-use types in LRYR were dominated by arable land and woodland, accounting for more than 70% of the total area. During the study period, the construction land area increased by 11,835 km2, and became the third largest land-use type in LRYR after 2010 and formed a typical urban contiguous zone along the route from Nanjing to Shanghai. 2) The land use degree comprehensive index (LUDCI) in LRYR at each stage is 270.91, 270.88, 272.22, 272.72, 274.00, 275.57, 276.93 and 280.37, respectively. LUCC in LRYR has become more dramatic, and there is significant spatial heterogeneity. Shanghai has always been a hot area of LUCC and Huangshan and Chizhou are cold spots of LUCC. 3) The driving mechanism of LUCC in LRYR can be divided into three stages. In these three stages, secondary industry output value, precipitation, and elevation are always important factors affecting LUCC. The interaction between driving factors is significant. The strongest interaction is the output value of the secondary industry ∩ precipitation, the interaction reaches above 0.6. The research results are of great significance for promoting the sustainable development of land use in this region.

The test bench for simulation impact of core saturation on the current transformer on coordination of inverse relay protection

When the measurement-type Current Transformer (CT) is used for protection schemes, this condition causes problems related to the operation of the protection relay. This performance can provide the right output to be captured by the relay when using the CT type of protection system, and measurement CT will be appropriately used as a measurement instrument. When the primary current is greater, the denser the flux flowing in the iron core, and when a certain primary current value is reached, the iron core is unable to accommodate the flux that must be flowed. As a result, the value Es is unable to rise again, so the error ratio begins to rise, and the secondary current output is distorted. This research aims to design a tool that can display the distortion that occurs in the secondary current, and this research will evaluate its impact on the characteristics of the inverse-type overcurrent relay. The research method is R&D (Research & Development) by configuring a prototype analog test table so that saturation occurs on the CT connected to the protection relay. The results of the research Simulation of protection coordination failure due to core saturation can be shown, and the design of core saturation test equipment can be demonstrated. The root cause of core failure can be traced from the disconnection time deviation that occurs at the protection relay. The design of core saturation test equipment can be implemented to display protection failures due to core saturation and show the correlation between the voltage excitation curve and relay disconnection time. Testing CT ratio 30/5 with a burden of 1.5 VA, the operating limit is 183.3% of the primary rated rating, meaning that for CT with a primary rated current of 30 amperes, testing up to 60 amperes shows the results have not occurred core saturation.

Proposing of a two-stage system known as the PV/T-ST system combining thermoelectric conversion technology for round-the-clock electrical output

In this study, a two-stage system known as the PV/T-ST system with a series photovoltaic/thermal (PV/T) module and a solar thermal (ST) collector combining thermoelectric conversion technology is proposed. In the daytime, the PV/T module generates power and captures low-temperature heat simultaneously. The ST module achieves secondary heating of water and secondary thermal-electric output by the thermoelectric generators (TEG). In the nighttime, the water heated by day continues to circulate, providing heat for TEG, thus achieving round-the-clock electrical output. Theoretical research reveals that the system’s total electrical power reaches its maximum value at 11:57, measuring 97.43 W. The maximum heat gain amounts to 380.67 W. During the night, TEG operates continuously and experiences a gradual decline in electrical output, with an average electrical efficiency of 0.43%.

IoT Based Electrical Devices Surveillance Control

Analogue electronics devices are losing ground to digital electronics components in today’s technologically evolved society. Another aspect of our increasingly digital society is the home device control system. A lot of people are chatting it up over the cellular phone network. These phone networks rely on WIFI modules as their foundation. A shorthand way to say “global system of mobile communication” is WIFI. In addition to being widely employed in industry, it is also used in several electronics projects undertaken by engineering students. It is possible to operate equipment from afar using WIFI-based projects. For instance, what if you wanted to be able to operate any equipment from afar using only your cell phone? Would it be possible? Sure, I can help you with that. Wi-Fi modules and cell phones make it easy to power on and off various gadgets. The home devices control system was developed to enable the control of home equipment from a mobile phone by using the aforementioned ideas. This document makes use of a regulated 5V, 1A power source. When controlling voltage, a 7805 three-terminal regulator is ideal. When a 230/12V step-down transformer’s secondary AC output needs rectifying, a bridge-type full wave rectifier is the way to go.

Electromagnetic converter of reactive power and monitoring of high-voltage induction motors

In this paper, the control and monitoring of reactive power in an over-voltage induction motor are elucidated through a comparative analysis of theoretical and practical research findings. These results are based on structural principles, research models, and the static, dynamic, metrological, and technical characteristics of three-phase electromagnetic current converters, evaluated against established criteria. The effectiveness of employing current converters with straightforward design, high sensitivity, speed, and reliability, along with simple switching elements that transform the primary input stator current into a secondary voltage output signal, is emphasized. Utilizing a graph model, the static characteristics of the stator current to secondary voltage converter, essential for regulating and monitoring the reactive power of an asynchronous motor, are delineated, and a research algorithm is developed.

A Single-Stage Isolated Battery Charger Using Nonbridged Positive Cuk Converter Configuration

This article presents a nonbridged isolated positive Cuk (NB-IPCuk) converter-based single-stage battery charging system (SSBCS). The architecture of the suggested charger ensures the intrinsic advantage of power quality improvement in discontinuous current conduction (DCC) mode at the supply mains. The suggested NB-IPCuk converter scheme has fewer components than other bridgeless/nonbridged Cuk converter schemes. This is because the NB-IPCuk converter is a partial integration of two Cuk converters. The usage of the Cuk converter garnishes the system with input and output inductances, which lessens supply current harmonic distortion and, thus supply terminal low pass filter requirement is eradicated. The advantages of the NB-IPCuk converter are the eradication of one inductor and multiple diodes (two back-feeding diodes), which are generally used in NB converter configurations. In place of two separate inductors, the NB-IPCuk converter uses a single secondary side output inductor. The usage of BL configuration of NB-IPCuk converter eradicates the bridge rectifier (BR) stage, and thus, the BR-associated losses also got eradicated. The NB-IPCuk converter also garnishes the system with electrical isolation which adds to the safety standards of the system. DCC mode operation of the NB-IPCuk converter is used in the present work. DCC mode requires lesser sensors in comparison to continuous current conduction mode. The abovementioned benefits of the NB-IPCuk converter make the SSBCS system cheaper, compact, and more efficient. The detailed stability analysis (Bode diagram and pole-zero map) and mathematics for the NB-IPCuk converter are also included in the paper. The prototype and MATLAB/Simulink model of NB-IPCuk converter-based SSBCS system with DCC mode control has been built, and results of both prototype and MATLAB/Simulink are deployed to verify SSBCS system’s performance during dynamic and steady-state conditions.

Simulation of the influence of parameters of disturbing vibration accelerations on the operation of a new two-channel transformer gravimeter

A new two-channel transformer gravimeter of an automated aviation gravimetric system was considered, the accuracy of which is higher than gravimeters known today. Its design was described. The influence of the parameters of disturbing vibrational accelerations on the operation of a new two-channel transformer gravimeter was simulated. The influence of frequencies and amplitudes of perturbing accelerations for the most unfavorable resonant cases on the operation of a two-channel transformer gravimeter was studied using a computer. After all, today there are no scientific, theoretical and practical works devoted to researching the possibility and expediency of using a two-channel transformer gravimeter as an AGS gravimeter. The transformer gravimeter contains a sensitive element consisting of a magnetic circuit, a movable armature, a primary excitation winding and a secondary output winding having two identical sections. Two sections of the secondary winding are connected in series-opposite, and the movable armature is connected to the motor, which, with a certain period, lowers the armature down and lifts it up along the magnetic circuit, and the motor is controlled by a switching device connected to the control voltage source, and the output signal from the secondary output winding is fed to the input of the output signal calculator, where an output signal is generated that is proportional to twice the value of the gravitational acceleration. A transformer gravimeter is a means of measuring the vertical component of the gravitational acceleration vector from an aircraft and can be used in the field of geodesy, geophysics, in particular, in the formation of reference gravimetric grids in hard-to-reach areas of the globe, as well as in aircraft and rocket building. The transformer gravimeter is part of the aviation gravimetric system placed on the aircraft.

Influence of Natural and Social Economic Factors on Landscape Pattern Indices—The Case of the Yellow River Basin in Henan Province

The Yellow River Basin holds significance as a vital ecological shield and economic hub within China. Adapting land utilization practices and optimizing landscape patterns are of paramount significance in preserving the ecological equilibrium of the Yellow River Basin while fostering high-quality economic development. In this study, we selected the Yellow River Basin in Henan Province as our research area. We use a land use transition matrix and FRAGSTATS 4.2 software to analyze changes in land use and landscape patterns within the study area from 1990 to 2020. Furthermore, Geographical Detector is employed to explore the impact of different natural and social economic factors that have influenced the progress of the landscape surface pattern in the study area. Finally, to identify the zonal aggregation effects of primary components in connection with landscaping feature indices at the city dimension, we use bivariate local spatial autocorrelation. The results are as follows: (1) In terms of land use change characteristics, the area of cultivated land, grassland, shrubs, and bare land shows a decreasing tendency, the area of construction land and forest land shows an increasing tendency, and the water area fluctuates and changes. Most of the cultivated land is shifted to construction land, followed by forest land, construction land, and cultivated land mainly transferred from grassland. (2) At the level of type in terms of shifting landscape patterns, cultivated land, forest land, water, and construction land have a more complex landscape shape, reduced fragmentation, and better natural connectivity. At the overall level, the overall landscape pattern indices are relatively stable, with more patch types and a more balanced distribution. (3) The findings regarding influencing factors reveal that the primary industry output value, population, secondary industry output value, and temperature are the principal driving forces behind the progress of the landscape surface pattern. The main drivers have changed over time in different regions. As indicated by the findings from bivariate local spatial autocorrelation analysis, at the city scale, the leading cause of landscape fragmentation in Luoyang is the primary industry output value, while in Xinxiang, landscape fragmentation is primarily driven by the secondary industry output value and temperature. In this study, we introduce the bivariate local spatial autocorrelation method to analyze the clustering effects of key influencing factors and landscape patterns at the city scale. This is crucial for the harmonized growth of land use planning and the urban economy in the Yellow River Basin.

Estimation and Convergence Analysis of Traffic Structure Efficiency Based on an Undesirable Epsilon-Based Measure Model

To improve transportation efficiency, this paper analyzes the factors of transportation structure from the two levels of transportation—input and system output. An epsilon-based measure model of non-expected output is introduced, and the environmental benefits of transportation are considered. This model is used to analyze the regional transportation efficiency of 30 provinces and cities in China. Tobit regression and geographically weighted regression are applied to analyze the causes and spatial variation of differences in the efficiency of the transportation structure, and corresponding structural adjustment strategies are proposed. The results show that the regression coefficients of the share of secondary industry output in GDP, population density, and social fixed asset investment exert the most significant effects on transportation structure efficiency. The spatial distribution of sub-variable coefficients shows that spatial heterogeneity exists in the degree of influence of various socio-economic factors on the transportation structure efficiency in different regions.

Study on Urban Spatial Expansion and Its Scale Benefit in the Yellow River Basin

Based on nighttime light data from 2000, 2005, 2010, 2015 and 2020, the urban built-up area of 90 prefecture-level cities in the Yellow River Basin was extracted, and the urban spatial expansion characteristics of 90 prefecture-level cities were explored from the two elements of expansion speed and expansion intensity. The entropy method was used to calculate the comprehensive level of economic-, social- and ecological-scale benefits of 90 prefecture-level cities. The gray correlation degree was used to measure the correlation between urban spatial expansion and scale benefits, and the geographical detector was used to identify the driving factors of urban spatial expansion. The results show the following: (1) The urban spatial expansion characteristics of 90 prefecture-level cities in the Yellow River Basin are clearly different. From 2000 to 2020, the urban spatial area increased to 2.94 times the original, and the expansion speed and intensity increased but fluctuated significantly. (2) The comprehensive level of economic-, social- and ecological-scale benefits of 90 prefecture-level cities in the Yellow River Basin has gradually improved. (3) There is a high correlation between urban spatial expansion and economic-, social- and ecological-scale benefits in 90 prefecture-level cities in the Yellow River Basin, but there are obvious regional differences in the eastern, central and western prefecture-level cities. (4) The urban spatial expansion of the Yellow River Basin is the result of the joint action of natural factors, the economic development level, industrial structure, government regulation ability, population size and opening level. Among them, per capita GDP, population density and the proportion of secondary and tertiary industry output value to the total output value are the most important driving factors.