Urban green spaces have positive effects on both physical and mental wellbeing.However,few studies have focused on the trends and thresholds of the effects of different influences on restorative benefits when viewing ...Urban green spaces have positive effects on both physical and mental wellbeing.However,few studies have focused on the trends and thresholds of the effects of different influences on restorative benefits when viewing scenes differfeaturing plant communities.We measured subjective evaluations and objective physiological data from 44 participants who viewed images of plant communities in the yellow to green hue range to compare differences in restorative benefits among plant communities at different visual distances,as well as quantifying the influencing factors involved.The following results were found:(1)Coniferous and multi-layered plant communities were found to provide greater restorative benefits,and the restorative benefits grew with increasing visual distance.(2)Shape and color characteristics were significantly correlated with restorative benefits,but the relationship is not simply linear.(3)The restorative benefits were found to be greatest when crown proportion was 61.23%,trunk proportion ranged from 4.11%to 13.70%,and the value of color index value ranged from 25.44%to 35.56%;the restorative benefits gradually increased when sky proportion exceeded 12.95%-13.19%,the fractal dimension exceeded 1.62-1.67,and hue index exceeded 91.64°-95.67°;additionally,the restorative benefits decreased when the saturation index increased.This study provides a scientific basis for the construction and improvement of plant landscapes in urban green spaces.展开更多
The development of catalysts with highly efficient oxygen evolution performance and low-Ir loading is key to scaling up the application of proton exchange membrane(PEM)water electrolysis technology.Here,an Ir-skin cat...The development of catalysts with highly efficient oxygen evolution performance and low-Ir loading is key to scaling up the application of proton exchange membrane(PEM)water electrolysis technology.Here,an Ir-skin catalyst(Ir@KM)is realized on a potassium-manganese oxide(K_(0.25)MnO_(x)(KM))using an ion-exchange method.The Ir-skin over the prepared Ir@KM has a low Ir-Ir atomic distance,endowing an energetically favorable oxide path mechanism to allow a low theoretical overpotential of 0.13 V.Ir@KM offers a low overpotential of~280 mV at a current density of 10 mA cm^(-2)and provides a high mass activity of up to 18,500 A at a cell voltage of 1.8 V in PEM,which is 17.6 times higher than that of IrO_(2),demonstrating a significant advantage in reducing the cost of the membrane electrode.The presented Ir-skin concept represents a promising strategy to fabricate low-Ir catalyst with high activity and durability for practical applications of PEM.展开更多
At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, i...At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, incomplete last-kilometer implementation for translating skills into practice, and inadequate incentive mechanisms. As a novel educational form deeply integrating digital information technology with teaching and learning, distance open education provides multi-directional empowerment for enhancing village cadres digital literacy. This is achieved through open learning methods, the application of modern digital technologies, tailored learning programs, and the establishment of "overpass bridges" for translating learning outcomes into practice. Based on this, it is essential to further streamline the pathways for educating and cultivating village cadres, vigorously promote the digitalization of teaching, practice, and support services, develop systematic and localized digital education resources, and actively explore and establish a complementary credit bank system for their digital literacy cultivation.展开更多
Traditional mining in open pit mines often uses explosives,leading to environmental hazards,with flyrock being a critical issue.In detail,excess flying rock beyond the designated explosion area was identified as the p...Traditional mining in open pit mines often uses explosives,leading to environmental hazards,with flyrock being a critical issue.In detail,excess flying rock beyond the designated explosion area was identified as the primary cause of fatal and non-fatal blasting hazards in open pit mining.Therefore,the accurate and reliable prediction of flyrock becomes crucial for effectively managing and mitigating associated problems.This study used the Light Gradient Boosting Machine(LightGBM)model to predict flyrock in a lead-zinc mine,with promising results.To improve its accuracy,multi-verse optimizer(MVO)and ant lion optimizer(ALO)metaheuristic algorithms were introduced.Results showed MVO-LightGBM outperformed conventional LightGBM.Additionally,decision tree(DT),support vector machine(SVM),and classification and regression tree(CART)models were trained and compared with MVO-LightGBM.The MVO-LightGBM model excelled over DT,SVM,and CART.This study highlights MVO-LightGBM's effectiveness and potential for broader applications.Furthermore,a multiple parametric sensitivity analysis(MPSA)algorithm was employed to specify the sensitivity of parameters.MPSA results indicated that the highest and lowest sensitivities are relevant to blasted rock per hole and spacing with theγ=1752.12 andγ=49.52,respectively.展开更多
An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Techniqu...An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared to the original data and traditional SMOTE. The proposed method (NR-Clustering SMOTE) improves accuracy by 15.34% on the Pima dataset and 20.96% on the Haberman dataset compared to SMOTE-LOF. Compared to Radius-SMOTE, this method increases accuracy by 3.16% on the Pima dataset and 13.24% on the Haberman dataset. Meanwhile, compared to RN-SMOTE, the accuracy improvement reaches 15.56% on the Pima dataset and 19.84% on the Haberman dataset. This research result implies that the proposed method experiences consistent performance improvement compared to traditional SMOTE and its latest variants, such as SMOTE-LOF, Radius-SMOTE, and RN-SMOTE, in solving imbalanced health data with class binaries.展开更多
Biodiversity has always been valued by ecology,Diversity is generally believed to lead to stability,and biodiversity is an important condition for ecosystems to maintain health.So what factors are related to forest ec...Biodiversity has always been valued by ecology,Diversity is generally believed to lead to stability,and biodiversity is an important condition for ecosystems to maintain health.So what factors are related to forest ecosystem biodiversity,and what kind of forest structure affects and determines the size of biodiversity.This study proposes the concept of contained uniformity based on the theory of uniformity,and uses the convergence of contained uniformity to obtain the judgment model of the forest station pattern type.At the same time,it proposes the concept of forest ecosystem distance diversity,and uses the judgment model of the stand pattern type to derive the mathematical definition of forest ecosystem distance diversity.Combining the ecological characteristics of different stand patterns and measurement indicators of forest ecosystem biodiversity,the connection between forest ecosystem distance diversity and biodiversity is derived,and this is used as an indicator to evaluate forest ecosystem biodiversity.Forest ecosystem distance diversity,as an indicator of biodiversity,can not only conduct early assessment and prediction of the biodiversity of immature forests(forests in the early succession or recovery stage),but also provide a quantitative basis for forest structure optimization.Ultimately realize the sustainable development of forestry production and operation and biodiversity protection.展开更多
The effects of geographic factors on information dissemination among investors have been extensively studied;however,the relationship between the geographical distance and stock price synchronization remains unclear.G...The effects of geographic factors on information dissemination among investors have been extensively studied;however,the relationship between the geographical distance and stock price synchronization remains unclear.Grounded in information asymmetry theory,this study investigates the impact of geographical distance on stock price synchronization in the Chinese stock market.Using the data from the Shanghai and Shenzhen Stock Exchanges,we find that a greater geographical distance between mutual funds and firms considerably increases stock price synchronization,highlighting a strong positive relationship.Additional analysis show that firms in the regions with better external and internal governance,benefit more from reduced information asymmetry,than those in less regulated or transparent regions.These results have key implications for institutional investors and policymakers aiming to enhance information dissemination and market integration in China.展开更多
Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted t...Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted to develop conversion models between the acceleration response spectrum(SA)and the pseudo-acceleration response spectrum(PSA).Our previous studies found that the relationship between SA and PSA is affected by magnitude,distance,and site class.Subsequently,we developed an SA/PSA model incorporating these effects.However,this model is suitable for cases with small and moderate magnitudes and its accuracy is not good enough for cases with large magnitudes.This paper aims to develop an efficient SA/PSA model by considering influences of magnitude,distance,and site class,which can be applied to cases not only with small or moderate magnitudes but also with large ones.For this purpose,regression analyses were conducted using 16,660 horizontal seismic records with a wider range of magnitude.The magnitude of these seismic records varies from 4 to 9 and the distances vary from 10 to 200 km.These ground motions were recorded at 338 stations covering four site classes.By comparing them with existing models,it was found that the proposed model shows better accuracy for cases with any magnitudes,distances,and site classes considered in this study.展开更多
Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamen...Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.展开更多
This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent m...This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent models reflecting low and mid-rise buildings were created.Dynamic analyses were performed by selecting 11 earthquake record pairs compatible with the Turkish Building Earthquake Code(TBEC-2018).Two different cases were considered to determine the minimum required seismic gap distance.In the first case(named as Case-1),the gap distances between neighboring buildings were determined to avoid collisions during each acceleration record.The required distances calculated from the analyses were compared with the minimum seismic gap requirements of the TBEC-2018.The outcomes indicate that theαcoefficient recommended in TBEC-2018 for adjacent buildings with a potential floor-to-column pounding is sufficient for adjacent buildings with a period ratio of 1 to 1.5.The gap distances in the first case were then reduced by an iterative process to determine the distance at which the shear demand equals the shear strength(named as Case-2).The calculated gap distances to prevent shear failure(Case-2)are approximately 6%to 19%lower than the distances determined for avoidance of pounding(Case-1).展开更多
A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which...A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.展开更多
The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational re...The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational restraints on the proteins or their complexes.The rigid connection of the nitroxide spin label to the protein improves the accuracy and precision of distance measurement.We report a new spin labelling approach by formation of thioester bond between nitroxide(NO)spin label,NOAI(NO spin labels activated by acetylimidazole),and a protein thiol,and this spin labeling method has demonstrated high performance in DEER distance measurement on proteins.The results showed that NOAI has shorter connection to the protein ligation site than 2,2,5,5-tetramethyl-pyrroline-1-oxyl methanethiosulfonate(MTSL)and 3-maleimido-proxyl(M-Prox)in the respective protein conjugate and produces narrower distance distributions for the tested proteins including ubiquitin(Ub),immunoglobulin-binding b1 domain of streptococcal protein G(GB1),and second mitochondria-derived activator of caspases(Smac).The NOAI protein conjugate connected by a thioester bond is resistant to reducing reagent and offers highfidelity DEER distance measurements in cell lysates.展开更多
This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses sig...This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses significant challenges for traditional classifiers due to feature redundancy or being irrelevant.The proposed method addresses these challenges by partitioning the dataset into blocks,calculating the Gower distance within each block,and selecting features based on their average similarity.Technically,the Gower distance normalizes the absolute difference between numerical features,ensuring that each feature contributes equally to the distance calculation.This normalization prevents features with larger scales from overshadowing those with smaller scales.This process facilitates the identification of features that exhibit high harmony and are the most relevant for classification.The proposed feature selection strategy significantly reduces dimensionality,retains the most relevant features,and improves model performance.Experimental results show that the accuracy for the classifiers including k-nearest neighbors(KNN),naive Bayes(NB),decision tree(DT),random forest(RF),support vector machine(SVM),and logistic regression(LR)was increased by 4.38%-7.02%.Besides,the reduction in the feature set size contributes to a considerable decrease in computational complexity and thus faster diagnosis speed.The execution time was averagely reduced by 77.82%for all samples and 76.45%for one sample.These results demonstrate that the proposed feature selection method shows enhanced performance on both prediction accuracy and diagnostic speed,making it a promising tool for real-time clinical decision-making and improving patient care outcomes.展开更多
Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm inv...Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm involves complex dependencies and constraints,making state management and verification work tedious.This paper proposes a derivation and verification method that avoids directly handling dependencies and constraints by proving the equivalence between the edit distance algorithm and existing functional modeling.First,the derivation process of edit distance algorithm mainly includes 1)describing problem specifications,2)inductively deducing recursive relations,3)formally constructing loop invariants using the optimization theory(memorization technology and optimal decision table)and properties(optimal substructure property and subproblems overlapping property)of the edit distance algorithm,4)generating the Minimalistic Imperative Programming Language(IMP)code based on the recursive relations.Second,the problem specification,loop invariants,and generated IMP code are input into Verification Condition Generator(VCG),which automatically generate five verification conditions,and then the correctness of edit distance algorithm is verified in the Isabelle/HOL theorem prover.The method utilizes formal technologies and theorem prover to complete the derivation and verification of the edit distance algorithm,and it can be applied to linear and nonlinear dynamic programming problems.展开更多
Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the spe...Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.展开更多
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar ...This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.展开更多
With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limite...With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.展开更多
This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in ...This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in the Three Gorges Reservoir area,we assessed the local temporal and spatial variations in the frequent earthquakes.Correlation analysis was conducted to investigate the relationship between changes in reservoir water levels and the occurrence of reservoir-induced earthquakes.Additionally,we examined the regularity of earthquake occurrences at the exact location during different periods.Based on the fault mechanics principles,a formula was derived to estimate the length of open and wing-shaped rupture at the hypocenter under the influence of pore or excess pore water pressure.The results reveal that reservoir-induced seismicity demonstrates short-term cycles characterized by alternating"active periods"and"quiet periods,"as well as long-term cycles with the combined periods.The probability of earthquakes occurring within one year at the epicentre is relatively high and decreases after four years.The derived formula can be utilized to estimate the seismic migration distance at the epicentre in the short term.These research findings provide valuable insights for analyzing the regularity of reservoir-induced earthquake activities and understanding the mechanism of seismic source migration.展开更多
This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy ess...This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.展开更多
In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson...In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson–Walker(FLRW)metric.The strong gravitational lensing data is used to construct the dimensionless comoving distance function d(z)and latest type Ia supernovae Pantheon+data is used to estimate luminosity distances at the corresponding redshifts z.Using the distance sum rule along null geodesics of the FLRW metric,the CDDR violation is probed in both flat and non-flat spacetime by considering two parametrizations forη(z),the function generally used to probe the possible deviations from CDDR.The results show that CDDR is compatible with the observations at a very high level of confidence for linear parametrization in a flat Universe.In a non-flat Universe too,CDDR is valid within the 1σconfidence interval with a mild dependence ofηon the curvature density parameterΩK.The results for nonlinear parametrization also show no significant deviation from CDDR.展开更多
基金funded by the National Natural Science Foundation of China(32471953)the Educational Department of Liaoning Province Key Research Project(LJ212410153073).
文摘Urban green spaces have positive effects on both physical and mental wellbeing.However,few studies have focused on the trends and thresholds of the effects of different influences on restorative benefits when viewing scenes differfeaturing plant communities.We measured subjective evaluations and objective physiological data from 44 participants who viewed images of plant communities in the yellow to green hue range to compare differences in restorative benefits among plant communities at different visual distances,as well as quantifying the influencing factors involved.The following results were found:(1)Coniferous and multi-layered plant communities were found to provide greater restorative benefits,and the restorative benefits grew with increasing visual distance.(2)Shape and color characteristics were significantly correlated with restorative benefits,but the relationship is not simply linear.(3)The restorative benefits were found to be greatest when crown proportion was 61.23%,trunk proportion ranged from 4.11%to 13.70%,and the value of color index value ranged from 25.44%to 35.56%;the restorative benefits gradually increased when sky proportion exceeded 12.95%-13.19%,the fractal dimension exceeded 1.62-1.67,and hue index exceeded 91.64°-95.67°;additionally,the restorative benefits decreased when the saturation index increased.This study provides a scientific basis for the construction and improvement of plant landscapes in urban green spaces.
基金supported by the Hainan Province Science and Technology Special Fund(ZDYF2023GXJS165)the National Natural Science Foundation of China(52164028,22109035,52274297)+2 种基金the Foundation of State Key Laboratory of Marine Resource Utilization in South China Sea(Hainan University,MRUKF2021029)the Start-up Research Foundation of Hainan University(KYQD(ZR)-20008,20084,21170)the Specific Research Fund of the Innovation Platform for Academicians of Hainan Province。
文摘The development of catalysts with highly efficient oxygen evolution performance and low-Ir loading is key to scaling up the application of proton exchange membrane(PEM)water electrolysis technology.Here,an Ir-skin catalyst(Ir@KM)is realized on a potassium-manganese oxide(K_(0.25)MnO_(x)(KM))using an ion-exchange method.The Ir-skin over the prepared Ir@KM has a low Ir-Ir atomic distance,endowing an energetically favorable oxide path mechanism to allow a low theoretical overpotential of 0.13 V.Ir@KM offers a low overpotential of~280 mV at a current density of 10 mA cm^(-2)and provides a high mass activity of up to 18,500 A at a cell voltage of 1.8 V in PEM,which is 17.6 times higher than that of IrO_(2),demonstrating a significant advantage in reducing the cost of the membrane electrode.The presented Ir-skin concept represents a promising strategy to fabricate low-Ir catalyst with high activity and durability for practical applications of PEM.
基金Supported by Science Research Fund Project of Yunnan Provincial Department of Education-Research on the Pathways for Distance Open Education to Empower the Enhancement of Digital Literacy and Skills of Rural"Leading Geese"in Ethnic Areas(2023J0792)The Ideological and Political Education Reform Project of Yunnan Province in 2022-Exploration and Practice of Integrating Ideological and Political Education into the Training Mode of"Leading Goose"Talents for Rural Revitalization in the Course of Agricultural and Forestry Economics and Management in Open Education.
文摘At present, enhancing the digital literacy of village cadres faces practical constraints such as governance capability gaps induced by the second-level digital divide, the absence of a systematic cultivation system, incomplete last-kilometer implementation for translating skills into practice, and inadequate incentive mechanisms. As a novel educational form deeply integrating digital information technology with teaching and learning, distance open education provides multi-directional empowerment for enhancing village cadres digital literacy. This is achieved through open learning methods, the application of modern digital technologies, tailored learning programs, and the establishment of "overpass bridges" for translating learning outcomes into practice. Based on this, it is essential to further streamline the pathways for educating and cultivating village cadres, vigorously promote the digitalization of teaching, practice, and support services, develop systematic and localized digital education resources, and actively explore and establish a complementary credit bank system for their digital literacy cultivation.
基金funded by the Key Laboratory of Geological Safety of Coastal Urban Underground Space,Ministry of Natural Resources of China(Grant No.BHKF2022Y02)Natural Science Foundation of Guangdong Province,China(Grant No.2024A1515011162)Natural Science Foundation of Shandong Province,China(Grant No.ZR2024QE021).
文摘Traditional mining in open pit mines often uses explosives,leading to environmental hazards,with flyrock being a critical issue.In detail,excess flying rock beyond the designated explosion area was identified as the primary cause of fatal and non-fatal blasting hazards in open pit mining.Therefore,the accurate and reliable prediction of flyrock becomes crucial for effectively managing and mitigating associated problems.This study used the Light Gradient Boosting Machine(LightGBM)model to predict flyrock in a lead-zinc mine,with promising results.To improve its accuracy,multi-verse optimizer(MVO)and ant lion optimizer(ALO)metaheuristic algorithms were introduced.Results showed MVO-LightGBM outperformed conventional LightGBM.Additionally,decision tree(DT),support vector machine(SVM),and classification and regression tree(CART)models were trained and compared with MVO-LightGBM.The MVO-LightGBM model excelled over DT,SVM,and CART.This study highlights MVO-LightGBM's effectiveness and potential for broader applications.Furthermore,a multiple parametric sensitivity analysis(MPSA)algorithm was employed to specify the sensitivity of parameters.MPSA results indicated that the highest and lowest sensitivities are relevant to blasted rock per hole and spacing with theγ=1752.12 andγ=49.52,respectively.
基金funded by Universitas Negeri Malang,contract number 4.4.841/UN32.14.1/LT/2024.
文摘An imbalanced dataset often challenges machine learning, particularly classification methods. Underrepresented minority classes can result in biased and inaccurate models. The Synthetic Minority Over-Sampling Technique (SMOTE) was developed to address the problem of imbalanced data. Over time, several weaknesses of the SMOTE method have been identified in generating synthetic minority class data, such as overlapping, noise, and small disjuncts. However, these studies generally focus on only one of SMOTE’s weaknesses: noise or overlapping. Therefore, this study addresses both issues simultaneously by tackling noise and overlapping in SMOTE-generated data. This study proposes a combined approach of filtering, clustering, and distance modification to reduce noise and overlapping produced by SMOTE. Filtering removes minority class data (noise) located in majority class regions, with the k-nn method applied for filtering. The use of Noise Reduction (NR), which removes data that is considered noise before applying SMOTE, has a positive impact in overcoming data imbalance. Clustering establishes decision boundaries by partitioning data into clusters, allowing SMOTE with modified distance metrics to generate minority class data within each cluster. This SMOTE clustering and distance modification approach aims to minimize overlap in synthetic minority data that could introduce noise. The proposed method is called “NR-Clustering SMOTE,” which has several stages in balancing data: (1) filtering by removing minority classes close to majority classes (data noise) using the k-nn method;(2) clustering data using K-means aims to establish decision boundaries by partitioning data into several clusters;(3) applying SMOTE oversampling with Manhattan distance within each cluster. Test results indicate that the proposed NR-Clustering SMOTE method achieves the best performance across all evaluation metrics for classification methods such as Random Forest, SVM, and Naїve Bayes, compared to the original data and traditional SMOTE. The proposed method (NR-Clustering SMOTE) improves accuracy by 15.34% on the Pima dataset and 20.96% on the Haberman dataset compared to SMOTE-LOF. Compared to Radius-SMOTE, this method increases accuracy by 3.16% on the Pima dataset and 13.24% on the Haberman dataset. Meanwhile, compared to RN-SMOTE, the accuracy improvement reaches 15.56% on the Pima dataset and 19.84% on the Haberman dataset. This research result implies that the proposed method experiences consistent performance improvement compared to traditional SMOTE and its latest variants, such as SMOTE-LOF, Radius-SMOTE, and RN-SMOTE, in solving imbalanced health data with class binaries.
基金funded by Research on Intelligent Control System of Variable Fertilization of Deep Application Liquid Fertilizer(GXKS2022GKY003)the Key Laboratory of Smart Agriculture Technology,Guangxi Science and Technology Normal University(GXKSKYPT2024008)+1 种基金Key Laboratory of Detection Technology for Sugarcane and Peanut Leaf Spot Disease,Guangxi Science and Technology Normal University(GXKSKYPT2025008)Research on the Application of Uniformity Theory and 3D Virtual Forest Phase in Harbin Normal University’s Science and Technology Innovation Climbing Program Funding Project(XKB202415)。
文摘Biodiversity has always been valued by ecology,Diversity is generally believed to lead to stability,and biodiversity is an important condition for ecosystems to maintain health.So what factors are related to forest ecosystem biodiversity,and what kind of forest structure affects and determines the size of biodiversity.This study proposes the concept of contained uniformity based on the theory of uniformity,and uses the convergence of contained uniformity to obtain the judgment model of the forest station pattern type.At the same time,it proposes the concept of forest ecosystem distance diversity,and uses the judgment model of the stand pattern type to derive the mathematical definition of forest ecosystem distance diversity.Combining the ecological characteristics of different stand patterns and measurement indicators of forest ecosystem biodiversity,the connection between forest ecosystem distance diversity and biodiversity is derived,and this is used as an indicator to evaluate forest ecosystem biodiversity.Forest ecosystem distance diversity,as an indicator of biodiversity,can not only conduct early assessment and prediction of the biodiversity of immature forests(forests in the early succession or recovery stage),but also provide a quantitative basis for forest structure optimization.Ultimately realize the sustainable development of forestry production and operation and biodiversity protection.
基金supported by the National Natural Science Foundation of China(72141304,72201190).
文摘The effects of geographic factors on information dissemination among investors have been extensively studied;however,the relationship between the geographical distance and stock price synchronization remains unclear.Grounded in information asymmetry theory,this study investigates the impact of geographical distance on stock price synchronization in the Chinese stock market.Using the data from the Shanghai and Shenzhen Stock Exchanges,we find that a greater geographical distance between mutual funds and firms considerably increases stock price synchronization,highlighting a strong positive relationship.Additional analysis show that firms in the regions with better external and internal governance,benefit more from reduced information asymmetry,than those in less regulated or transparent regions.These results have key implications for institutional investors and policymakers aiming to enhance information dissemination and market integration in China.
基金National Natural Science Foundation of China under Grant No.52278135。
文摘Both acceleration and pseudo-acceleration response spectra play important roles in structural seismic design.However,only one of them is generally provided in most seismic codes.Therefore,many studies have attempted to develop conversion models between the acceleration response spectrum(SA)and the pseudo-acceleration response spectrum(PSA).Our previous studies found that the relationship between SA and PSA is affected by magnitude,distance,and site class.Subsequently,we developed an SA/PSA model incorporating these effects.However,this model is suitable for cases with small and moderate magnitudes and its accuracy is not good enough for cases with large magnitudes.This paper aims to develop an efficient SA/PSA model by considering influences of magnitude,distance,and site class,which can be applied to cases not only with small or moderate magnitudes but also with large ones.For this purpose,regression analyses were conducted using 16,660 horizontal seismic records with a wider range of magnitude.The magnitude of these seismic records varies from 4 to 9 and the distances vary from 10 to 200 km.These ground motions were recorded at 338 stations covering four site classes.By comparing them with existing models,it was found that the proposed model shows better accuracy for cases with any magnitudes,distances,and site classes considered in this study.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC2204601)the National Natural Science Foundation of China(Grant Nos.11925503 and 12275093)+1 种基金the Natural Science Foundation of Hubei Province(Grant No.2021CFB019)the State Key Laboratory of Applied Optics(Grant No.SKLAO2022001A10).
文摘Laser frequency combs,which are composed of a series of equally spaced coherent frequency components,have triggered revolutionary progress in precision spectroscopy and optical metrology.Length/distance is of fundamental importance in both science and technology.We describe a ranging scheme based on chirped pulse interferometry.In contrast to the traditional spectral interferometry,the local oscillator is strongly chirped which is able to meet the measurement pulses at arbitrary distances,and therefore,the dead zones can be removed.The distances can be precisely determined via two measurement steps based on the time-of-flight method and synthetic wavelength interferometry,respectively.To overcome the speed limitation of the optical spectrum analyzer,the spectrograms are stretched and detected by a fast photodetector and oscilloscope and consequently mapped into the time domain in real time.The experimental results indicate that the measurement uncertainty can be well within±2μm,compared with the reference distance meter.The Allan deviation can reach 0.4μm at 4 ns averaging time and 25 nm at 1μs and can achieve 2 nm at 100μs averaging time.We also measured a spinning disk with grooves of different depths to verify the measurement speed,and the results show that the grooves with about 150 m∕s line speed can be clearly captured.Our method provides a unique combination of non-dead zones,ultrafast measurement speed,high precision and accuracy,large ambiguity range,and only one single comb source.This system could offer a powerful solution for field measurements in practical applications in the future.
文摘This study aims to investigate the minimum required seismic gap distance based on the avoidance of shear failure for reinforced concrete(RC)buildings with potential floor-to-column pounding.Twenty different adjacent models reflecting low and mid-rise buildings were created.Dynamic analyses were performed by selecting 11 earthquake record pairs compatible with the Turkish Building Earthquake Code(TBEC-2018).Two different cases were considered to determine the minimum required seismic gap distance.In the first case(named as Case-1),the gap distances between neighboring buildings were determined to avoid collisions during each acceleration record.The required distances calculated from the analyses were compared with the minimum seismic gap requirements of the TBEC-2018.The outcomes indicate that theαcoefficient recommended in TBEC-2018 for adjacent buildings with a potential floor-to-column pounding is sufficient for adjacent buildings with a period ratio of 1 to 1.5.The gap distances in the first case were then reduced by an iterative process to determine the distance at which the shear demand equals the shear strength(named as Case-2).The calculated gap distances to prevent shear failure(Case-2)are approximately 6%to 19%lower than the distances determined for avoidance of pounding(Case-1).
基金Supported by the National Natural Science Foundation of China(Grant No.12071260)。
文摘A graph whose edges are labeled either as positive or negative is called a signed graph.Hameed et al.introduced signed distance and distance compatibility in 2021,initially to characterize balanced signed graphs which have nice spectral properties.This article mainly studies the conjecture proposed by Shijin et al.on the distance compatibility of the direct product of signed graphs,and provides necessary and sufficient conditions for the distance compatibility of the direct product of signed graphs.Some further questions regarding distance compatibility are also posed.
基金supported by National Natural Science Foundation of China(22161142018,21991081,22177056,and 22174074)the Ministry of Science and Technology of China(2021YFA1600304).
文摘The distance distributions between two site-specifically anchored spin labels in a protein,measured by pulsed electron-electron double resonance(PELDOR or DEER),provide rich sources of structural and conformational restraints on the proteins or their complexes.The rigid connection of the nitroxide spin label to the protein improves the accuracy and precision of distance measurement.We report a new spin labelling approach by formation of thioester bond between nitroxide(NO)spin label,NOAI(NO spin labels activated by acetylimidazole),and a protein thiol,and this spin labeling method has demonstrated high performance in DEER distance measurement on proteins.The results showed that NOAI has shorter connection to the protein ligation site than 2,2,5,5-tetramethyl-pyrroline-1-oxyl methanethiosulfonate(MTSL)and 3-maleimido-proxyl(M-Prox)in the respective protein conjugate and produces narrower distance distributions for the tested proteins including ubiquitin(Ub),immunoglobulin-binding b1 domain of streptococcal protein G(GB1),and second mitochondria-derived activator of caspases(Smac).The NOAI protein conjugate connected by a thioester bond is resistant to reducing reagent and offers highfidelity DEER distance measurements in cell lysates.
文摘This study presents an efficient feature selection method based on the Gower distance to enhance the accuracy and efficiency of standard classifiers on high-dimensional medical datasets.High-dimensional data poses significant challenges for traditional classifiers due to feature redundancy or being irrelevant.The proposed method addresses these challenges by partitioning the dataset into blocks,calculating the Gower distance within each block,and selecting features based on their average similarity.Technically,the Gower distance normalizes the absolute difference between numerical features,ensuring that each feature contributes equally to the distance calculation.This normalization prevents features with larger scales from overshadowing those with smaller scales.This process facilitates the identification of features that exhibit high harmony and are the most relevant for classification.The proposed feature selection strategy significantly reduces dimensionality,retains the most relevant features,and improves model performance.Experimental results show that the accuracy for the classifiers including k-nearest neighbors(KNN),naive Bayes(NB),decision tree(DT),random forest(RF),support vector machine(SVM),and logistic regression(LR)was increased by 4.38%-7.02%.Besides,the reduction in the feature set size contributes to a considerable decrease in computational complexity and thus faster diagnosis speed.The execution time was averagely reduced by 77.82%for all samples and 76.45%for one sample.These results demonstrate that the proposed feature selection method shows enhanced performance on both prediction accuracy and diagnostic speed,making it a promising tool for real-time clinical decision-making and improving patient care outcomes.
基金Supported by the National Natural Science Foundation of China(62462036,62462037)Key Project of Jiangxi Provincial Natural Science Foundation(20242BAB26017)Academic and Major Disciplines in Jiangxi Province Technical Leader Training Project(20232BCJ22013)。
文摘Edit distance is an algorithm to measure the difference between two strings,usually represented as the minimum number of editing operations required to transform one string into another.The edit distance algorithm involves complex dependencies and constraints,making state management and verification work tedious.This paper proposes a derivation and verification method that avoids directly handling dependencies and constraints by proving the equivalence between the edit distance algorithm and existing functional modeling.First,the derivation process of edit distance algorithm mainly includes 1)describing problem specifications,2)inductively deducing recursive relations,3)formally constructing loop invariants using the optimization theory(memorization technology and optimal decision table)and properties(optimal substructure property and subproblems overlapping property)of the edit distance algorithm,4)generating the Minimalistic Imperative Programming Language(IMP)code based on the recursive relations.Second,the problem specification,loop invariants,and generated IMP code are input into Verification Condition Generator(VCG),which automatically generate five verification conditions,and then the correctness of edit distance algorithm is verified in the Isabelle/HOL theorem prover.The method utilizes formal technologies and theorem prover to complete the derivation and verification of the edit distance algorithm,and it can be applied to linear and nonlinear dynamic programming problems.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1177117812171198)+2 种基金the Science and Technology Development Program of Jilin Province(Grant No.20210101467JC)the Technology Program of Jilin Educational Department During the“14th Five-Year”Plan Period(Grant No.JJKH20241239KJ)the Fundamental Research Funds for the Central Universities.
文摘Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.
基金supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
文摘This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
基金National Natural Science Foundation of China, grant number 52177074.
文摘With the evolution of DC distribution networks from traditional radial topologies to more complex multi-branch structures,the number of measurement points supporting synchronous communication remains relatively limited.This poses challenges for conventional fault distance estimation methods,which are often tailored to simple topologies and are thus difficult to apply to large-scale,multi-node DC networks.To address this,a fault distance estimation method based on sparse measurement of high-frequency electrical quantities is proposed in this paper.First,a preliminary fault line identification model based on compressed sensing is constructed to effectively narrow the fault search range and improve localization efficiency.Then,leveraging the high-frequency impedance characteristics and the voltage-current relationship of electrical quantities,a fault distance estimation approach based on high-frequency measurements from both ends of a line is designed.This enables accurate distance estimation even when the measurement devices are not directly placed at both ends of the faulted line,overcoming the dependence on specific sensor placement inherent in traditional methods.Finally,to further enhance accuracy,an optimization model based on minimizing the high-frequency voltage error at the fault point is introduced to reduce estimation error.Simulation results demonstrate that the proposed method achieves a fault distance estimation error of less than 1%under normal conditions,and maintains good performance even under adverse scenarios.
基金supported by the Open Research Fund of Key Laboratory of Geological Hazards on Three Gorges Reservoir Area of China Three Gorges University,the Ministry of Education(2020KDZ12)the National Natural Science Foundation Joint Funded Project of China(U2034203),the National Natural Science Foundation Joint Funded Project of China(U22A20600)+2 种基金the Hubei Key Laboratory of Disaster Prevention and Mitigation of China Three Gorges University(2022KJZ08)Natural Science Research Program of Yichang City in 2023(A23-2-047)Scientific Research Program of Hubei Provincial Department of Education in 2022(B2022567)。
文摘This paper aims to elucidate the seismic characteristics of the Three Gorges Reservoir area after impoundment and investigate the seismic source migration.Based on the seismic data analysis from the Badong segment in the Three Gorges Reservoir area,we assessed the local temporal and spatial variations in the frequent earthquakes.Correlation analysis was conducted to investigate the relationship between changes in reservoir water levels and the occurrence of reservoir-induced earthquakes.Additionally,we examined the regularity of earthquake occurrences at the exact location during different periods.Based on the fault mechanics principles,a formula was derived to estimate the length of open and wing-shaped rupture at the hypocenter under the influence of pore or excess pore water pressure.The results reveal that reservoir-induced seismicity demonstrates short-term cycles characterized by alternating"active periods"and"quiet periods,"as well as long-term cycles with the combined periods.The probability of earthquakes occurring within one year at the epicentre is relatively high and decreases after four years.The derived formula can be utilized to estimate the seismic migration distance at the epicentre in the short term.These research findings provide valuable insights for analyzing the regularity of reservoir-induced earthquake activities and understanding the mechanism of seismic source migration.
文摘This study introduces a novel distance measure(DM)for(p,q,r)-spherical fuzzy sets((p,q,to improve decision-making in complex and uncertain environments.Many existing distance measures eitherr)-SFSs)fail to satisfy essential axiomatic properties or produce unintuitive outcomes.To address these limitations,we propose a new three-dimensional divergence-based DM that ensures mathematical consistency,enhances the discrimination of information,and adheres to the axiomatic framework of distance theory.Building on this foundation,we construct a multi-criteria decision-making(MCDM)model that utilizes the proposed DM to evaluate and rank alternatives effectively.The applicability and robustness of the model are validated through a practical case study,demonstrating that it leads to more rational,consistent,and reliable decision outcomes compared to existing approaches.
文摘In this paper,cosmic distance duality relation(CDDR)is probed without considering any background cosmological model.The only a priori assumption is that the Universe is described by the Friedmann–Lema?tre–Robertson–Walker(FLRW)metric.The strong gravitational lensing data is used to construct the dimensionless comoving distance function d(z)and latest type Ia supernovae Pantheon+data is used to estimate luminosity distances at the corresponding redshifts z.Using the distance sum rule along null geodesics of the FLRW metric,the CDDR violation is probed in both flat and non-flat spacetime by considering two parametrizations forη(z),the function generally used to probe the possible deviations from CDDR.The results show that CDDR is compatible with the observations at a very high level of confidence for linear parametrization in a flat Universe.In a non-flat Universe too,CDDR is valid within the 1σconfidence interval with a mild dependence ofηon the curvature density parameterΩK.The results for nonlinear parametrization also show no significant deviation from CDDR.
