Digitalization’s Effects on Income Growth and Distribution-Evidence from the CHDES Database

Using the CHDES database,we created the CIDI to comprehensively quantify digital adoption at the individual level and examine digitalization’s impact on individual income.Empirical analysis results indicate that increasing the CIDI by one standard deviation(0.13)improves individual income by 5.93 percentage points,which remains true after a series of endogeneity and robustness tests.In the heterogeneity analysis,we discovered that when digital adoption grows,residents in the countryside and county seats can earn more money through internet business operations and other channels.This helps to decrease the urban-rural income divide,but it has also pushed those digitally skilled into high-paying sectors,widening the income gaps between sectors.In the mechanism analysis,we developed an income function that takes into account the individual level of digitalization to show that digitalization can boost income by increasing working hours or labor participation and adjusting the portfolio of individual material,human,and social capital.In this paper,we have expanded the system for measuring the individual levels of digitalization by offering basic data,research methodology,and policy suggestions for the digital economy’s inclusive development.

Exploring the influences of education,intelligence and income on mental disorders

Background Previous studies have shown that educational attainment(EA),intelligence and income are key factors associated with mental disorders.However,the direct effects of each factor on major mental disorders are unclear.Aims We aimed to evaluate the overall and independent causal effects of the three psychosocial factors on common mental disorders.Methods Using genome-wide association study summary datasets,we performed Mendelian randomisation(MR)and multivariable MR(MVMR)analyses to assess potential associations between the 3 factors(EA,N=766345;household income,N=392422;intelligence,N=146808)and 13 common mental disorders,with sample sizes ranging from 9907 to 807553.Inverse-variance weighting was employed as the main method in the MR analysis.Results Our MR analysis showed that(1)higher EA was a protective factor for eight mental disorders but contributed to anorexia nervosa,obsessive-compulsive disorder(OCD),bipolar disorder(BD)and autism spectrum disorder(ASD);(2)higher intelligence was a protective factor for five mental disorders but a risk factor for OCD and ASD;(3)higher household income protected against 10 mental disorders but confers risk for anorexia nervosa.Our MVMR analysis showed that(1)higher EA was a direct protective factor for attention-deficit/hyperactivity disorder(ADHD)and insomnia but a direct risk factor for schizophrenia,BD and ASD;(2)higher intelligence was a direct protective factor for schizophrenia but a direct risk factor for major depressive disorder(MDD)and ASD;(3)higher income was a direct protective factor for seven mental disorders,including schizophrenia,BD,MDD,ASD,post-traumatic stress disorder,ADHD and anxiety disorder.Conclusions Our study reveals that education,intelligence and income intertwine with each other.For each factor,its independent effects on mental disorders present a more complex picture than its overall effects.

FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Synergetic optimization operation method for distribution network based on SOP and PV

The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.

Coseismic deformation and fault slip distribution of the 2023 M_(W)7.8 and M_(W)7.6 earthquakes in Türkiye

On February 6,2023,a devastating earthquake with a moment magnitude of M_(W)7.8 struck the town of Pazarcik in south-central Türkiye,followed by another powerful earthquake with a moment magnitude of M_(W)7.6 that struck the nearby city of Elbistan 9 h later.To study the characteristics of surface deformation caused by this event and the influence of fault rupture,this study calculated the static coseismic deformation of 56 stations and dynamic displacement waveforms of 15 stations using data from the Turkish national fixed global navigation satellite system(GNSS)network.A maximum static coseismic displacement of 0.38 m for the M_(W)7.8 Kahramanmaras earthquake was observed at station ANTE,36 km from the epicenter,and a maximum dynamic coseismic displacement of 4.4 m for the M_(W)7.6 Elbistan earthquake was observed at station EKZ1,5 km from the epicenter.The rupture-slip distributions of the two earthquakes were inverted using GNSS coseismic deformation as a constraint.The results showed that the Kahramanmaras earthquake rupture segment was distinct and exposed on the ground,resulting in significant rupture slip along the Amanos and Pazarcik fault segments of the East Anatolian Fault.The maximum slip in the Pazarcik fault segment was 10.7 m,and rupture occurred at depths of 0–15 km.In the Cardak fault region,the Elbistan earthquake caused significant ruptures at depths of 0–12 km,with the largest amount of slip reaching 11.6 m.The Coulomb stress change caused by the Kahramanmaras earthquake rupture along the Cardak fault segment was approximately 2 bars,and the area of increased Coulomb stress corresponded to the subsequent rupture region of the M_(W)7.6 earthquake.Thus,it is likely that the M_(W)7.8 earthquake triggered or promoted the M_(W)7.6 earthquake.Based on the cumulative stress impact of the M_(W)7.8 and M_(W)7.6 events,the southwestern segment of the East Anatolian Fault,specifically the Amanos fault segment,experienced a Coulomb rupture stress change exceeding 2 bars,warranting further attention to assess its future seismic hazard risk.

Integrative biogeography: Validating hypotheses of species distribution

DEAR EDITOR,Biogeography is a scientific field dedicated to the investigation of the origins and distribution patterns of organisms,as well as predicting future alterations in their geographical distributions(Cox&Moore,2005).However,the majority of conclusions drawn within the field of biogeography are hypothetical.Rigorous testing of these biogeographic hypotheses remains a considerable challenge.This paper presents the concept of“integrative biogeography”,which emphasizes the experimental testing of biogeographic hypotheses through studies on geological history,as well as biotic and abiotic factors(Figure 1).

Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.

Hydrocarbon accumulation and orderly distribution of whole petroleum system in marine carbonate rocks of Sichuan Basin,SW China

Based on the situation and progress of marine oil/gas exploration in the Sichuan Basin,SW China,the whole petroleum system is divided for marine carbonate rocks of the basin according to the combinations of hydrocarbon accumulation elements,especially the source rock.The hydrocarbon accumulation characteristics of each whole petroleum system are analyzed,the patterns of integrated conventional and unconventional hydrocarbon accumulation are summarized,and the favorable exploration targets are proposed.Under the control of multiple extensional-convergent tectonic cycles,the marine carbonate rocks of the Sichuan Basin contain three sets of regional source rocks and three sets of regional cap rocks,and can be divided into the Cambrian,Silurian and Permian whole petroleum systems.These whole petroleum systems present mainly independent hydrocarbon accumulation,containing natural gas of affinity individually.Locally,large fault zones run through multiple whole petroleum systems,forming a fault-controlled complex whole petroleum system.The hydrocarbon accumulation sequence of continental shelf facies shale gas accumulation,marginal platform facies-controlled gas reservoirs,and intra-platform fault-and facies-controlled gas reservoirs is common in the whole petroleum system,with a stereoscopic accumulation and orderly distribution pattern.High-quality source rock is fundamental to the formation of large gas fields,and natural gas in a whole petroleum system is generally enriched near and within the source rocks.The development and maintenance of large-scale reservoirs are essential for natural gas enrichment,multiple sources,oil and gas transformation,and dynamic adjustment are the characteristics of marine petroleum accumulation,and good preservation conditions are critical to natural gas accumulation.Large-scale marginal-platform reef-bank facies zones,deep shale gas,and large-scale lithological complexes related to source-connected faults are future marine hydrocarbon exploration targets in the Sichuan Basin.

Influence of Topography on the Distribution and Structure of Woody Plants in the Senegalese Sahel (Sandy Ferlo)

This study describes the floristic composition and structure of a woody stand in the Senegalese Sahel, paying particular attention to the edaphic factors of its floristic composition. A stratified inventory considering the different relief units was adopted. Woody vegetation was surveyed using a dendrometric approach. The results obtained show that the flora is dominated by a few species adapted to drought, such as Balanites aegyptiaca (L.) Del., Calotropis procera Ait. and Boscia senegalensis (Pers.). The distribution of this flora and the structure of the ligneous plants are linked to the topography. In the lowlands, the flora is more diversified and the ligneous plants reach their optimum level of development compared with the higher relief areas. In the lowlands, there are a few woody species which, in the past, were indicative of better climatic conditions. These are Anogeissus leiocarpus (DC.), Commiphora africana (A. Rich.), Feretia apodanthera Del., Loeseneriella africana (A. Smith), Mitragyna inermis (Willd.) and Sclerocarya birrea (A. Rich). It is important that their reintroduction into reforestation projects takes account of their edaphic preference.

Neural stem cell-derived exosomes promote mitochondrial biogenesis and restore abnormal protein distribution in a mouse model of Alzheimer's disease

Mitochondrial dysfunction is a hallmark of Alzheimer’s disease.We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of AP P/PS1 mice.Because Alzheimer’s disease affects the entire brain,further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole.Here,we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing,immunostaining,and lightsheet imaging to clarify their spatial distribution.Additionally,to clarify whether the sirtuin 1(SIRT1)-related pathway plays a regulatory role in neural stem cell-de rived exosomes interfering with mitochondrial functional changes,we generated a novel nervous system-SIRT1 conditional knoc kout AP P/PS1mouse model.Our findings demonstrate that neural stem cell-de rived exosomes significantly increase SIRT1 levels,enhance the production of mitochondrial biogenesis-related fa ctors,and inhibit astrocyte activation,but do not suppress amyloid-βproduction.Thus,neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer’s disease that activates the SIRT1-PGC1αsignaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis.In addition,we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer’s disease,and that neural stem cell-derived exosome treatment can reverse this effect,indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Diversity of Orchids in Terms of Their Distribution, Uses and Conservation in Annapurna Conservation Area of Nepal

The Annapurna Conservation Area (ACA), the first conservation area and the largest protected area (PA) in Nepal, is incredibly rich in biodiversity. Notwithstanding this, orchids in the ACA have not been explored enough yet thus making the need for ambitious research to be carried out. Previous study only included 81 species of orchids within ACA. This study aims to update the record of species and genera richness in the ACA. In total 198 species of orchids, belonging to 67 genera (40% and 62% of the total recorded orchid species and genera in Nepal) has been recorded in ACA. This represents an increase of 144% in species and 56% in genera over the previous data. Out of the 198 species, 99 were epiphytes, 6 were holomycotrophic and 93 were terrestrial. Among the 67 genera, Bulbophyllum (17) species were dominant, followed by Dendrobium (16), Herminium (10), Coelogyne, Plantanthera (9 each), Eria, Habenaria, Oberonia (8 each), Calanthe (7), and Liparis (6). Fifty-six species were found to be ornamentally significant and 85 species medicinally significant.

Boosting Adversarial Training with Learnable Distribution

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments.

Cost of Medical Treatment for Primary Open-Angle Glaucoma in Relation to Patients’ Income and Its Impact on the Prognosis of the Disease, in Bouaké University Hospital

Introduction: Medical treatment for POAG is continuous and lifelong treatment. The aim of this study was to evaluate the relationship between the cost of this treatment and patients’ income and the impact of this relationship on treatment compliance. Materials and Methods: Prospective cross-sectional study with a descriptive aim covering sociodemographic data, average incomes, and direct and indirect costs of treatment of 57 patients followed for POAG during the period from January 1, 2012, to December 31, 2016 (5 years). Results: The patients were aged 25 to 77 years (mean = 54.4 years) with a male predominance (sex ratio = 1.5). Retirees were the most represented (26.32%), followed by workers in the informal sector (14.04%) and housewives (12.28%). Patients who had an annual income less than or equal to 900,000 CFA francs (€1370.83) per year represented 56.14% and those who did not have health coverage represented 57.89%. The treatment was monotherapy (64.91%), dual therapy (31.58%) or triple therapy (3.05%) and the average ratio of “annual cost of treatment to annual income” was 0.56 with for maximum 2.23 and 0.02 as minimum. Patients who considered the cost of treatment unbearable for their income represented 78.95%. Conclusion: Prevention of blindness due to glaucoma requires early detection but also the establishment of health coverage mechanisms to improve compliance with medical treatment. In addition, consideration should be given to the development of glaucoma surgery in our country, the indication of which could be the first intention in certain patients, considering for those patients, the geographical and financial accessibility of medical treatment. .

Effect of distribution of fines on evolution of cooperation in spatial public goods game

In the realm of public goods game,punishment,as a potent tool,stands out for fostering cooperation.While it effectively addresses the first-order free-rider problem,the associated costs can be substantial.Punishers incur expenses in imposing sanctions,while defectors face fines.Unfortunately,these monetary elements seemingly vanish into thin air,representing a loss to the system itself.However,by virtue of the redistribution of fines to cooperators and punishers,not only can we mitigate this loss,but the rewards for these cooperative individuals can be enhanced.Based upon this premise,this paper introduces a fine distribution mechanism to the traditional pool punishment model.Under identical parameter settings,by conducting a comparative experiment with the conventional punishment model,the paper aims to investigate the impact of fine distribution on the evolution of cooperation in spatial public goods game.The experimental results clearly demonstrate that,in instances where the punishment cost is prohibitively high,the cooperative strategies of the traditional pool punishment model may completely collapse.However,the model enriched with fine distribution manages to sustain a considerable number of cooperative strategies,thus highlighting its effectiveness in promoting and preserving cooperation,even in the face of substantial punishment cost.

Influence of Transportation Accessibility on Urban-rural Income Disparity and Its Spatial Heterogeneity

Transportation accessibility has been treated as an important means of reducing the urban-rural income disparity.However,only a few studies have examined the effects of different types of transportation accessibility on urban-rural income disparity and their spatial heterogeneity.Based on data from 285 prefecture-level(and above)Chinese cities in 2000,2005,2010,2015,and 2020,this study uses spatial econometric models to examine how highway accessibility and railway accessibility influence the urban-rural income disparity and to identify their spatial heterogeneity.The result reveals that highway accessibility and railway accessibility have‘coreperiphery’ring-like circle structures.The urban-rural income disparity exhibits strong spatial clustering effects.Both highway accessibility and railway accessibility are negatively associated with urban-rural income disparity,and the former having a greater effect size.Moreover,there is a substitution effect between highway accessibility and railway accessibility in the whole sample.Furthermore,these associations differ in geographic regions.In the central region,highway accessibility is more important in reducing the urban-rural income disparity,but its effect is weakened with the increase of railway accessibility.In the western region,railway accessibility has a larger effect on narrowing the urban-rural income disparity,and this effect is strengthened by the increase of highway accessibility.We conclude that improving transportation accessibility is conducive to reducing the urban-rural income disparity but its effect is spatial heterogenetic.Highways and railways should be developed in a coordinated manner to promote an integrated transport network system.

Simulation of Haloxylon Ammodendron Stand Basic Diameter Structure Based on Fuzzy Distribution Function

Based on the investigation data of 12 Haloxylon ammodendron plots in the south edge of Gurbantunggut Desert, Fuzzy distribution was introduced into the study of Haloxylon ammodendron base diameter structure fitting according to the consistency between the characteristics of Fuzzy distribution function and the distribution series of cumulative percentage of stand base diameter, and the fitting precision and effect of Fuzzy distribution function were discussed. The root mean square error RMSE and determination coefficient R2 values showed that Fuzzy-Γ1, Fuzzy-Γ2, Fuzzy-Γ3, Fuzzy-Γ4 had good fitting performance, among which Fuzzy-Γ1 had relatively high fitting precision, and its parameters were closely related to stand age and density, Fuzzy-Γ2 distribution function was the second, and Fuzzy-Γ4 distribution function had the worst fitting effect. By introducing a parameter c from the similarity of four distribution function formulas, a generalized Fuzzy distribution function Fuzzy-Γ5 is obtained. This function shows the highest fitting accuracy. Most of the values of parameter c are near 1 or 2, which shows that the diameter distribution is mainly approximate to Fuzzy-Γ1 and Fuzzy-Γ2.

Approximating the Radial Distribution Function of the Electron in a Hydrogen Atom by a Normal Distribution Suggests That Magnetic Confinement Fusion Would Be Less Energy Efficient than Inertial Confinement Fusion

Since the position of the electron in a hydrogen atom cannot be determined, the region in which it resides is said to be determined stochastically and forms an electron cloud. The probability density function of the single electron in 1s orbit is expressed as φ2, a function of distance from the nucleus. However, the probability of existence of the electron is expressed as a radial distribution function at an arbitrary distance from the nucleus, so it is estimated as the probability of the entire spherical shape of that radius. In this study, it has been found that the electron existence probability approximates the radial distribution function by assuming that the probability of existence of the electron being in the vicinity of the nucleus follows a normal distribution for arbitrary x-, y-, and z-axis directions. This implies that the probability of existence of the electron, which has been known only from the distance information, would follow a normal distribution independently in the three directions. When the electrons’ motion is extremely restricted in a certain direction by the magnetic field of both tokamak and helical fusion reactors, the probability of existence of the electron increases with proximity to the nucleus, and as a result, it is less likely to be liberated from the nucleus. Therefore, more and more energy is required to free the nucleus from the electron in order to generate plasma.

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Security analysis of satellite-to-ground reference-frame-independent quantum key distribution with beam wandering

The reference-frame-independent(RFI)quantum key distribution(QKD)is suitable for satellite-based links by removing the active alignment on the reference frames.However,how the beam wandering influences the performance of RFI-QKD remains a pending issue in satellite-to-ground links.In this paper,based on the mathematical model for characterizing beam wandering,we present the security analysis for satellite-to-ground RFI-QKD and analytically derive formulas for calculating the secret key rate with beam wandering.Our simulation results show that the performance of RFI-QKD is better than the Bennett–Brassard 1984(BB84)QKD with beam wandering in asymptotic case.Furthermore,the degree of influences of beam wandering is specifically presented for satellite-to-ground RFI-QKD when statistical fluctuations are taken into account.Our work can provide theoretical support for the realization of RFI-QKD using satellite-to-ground links and have implications for the construction of large-scale satellite-based quantum networks.