A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G...A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G,respectively,whereλ_n(G)andλ_1(G)are the largest and smallest eigenvalues of G,andμ_n(G)andμ_2(G)are the largest and second smallest Laplacian eigenvalues of G,respectively.In this paper,we shall present two sufficient conditions involving S_A(G)and S_L(G)for a k-connected graph to possess Hamiltonian s-properties,respectively.We also derive a sufficient condition on the Laplacian eigenratio μ2(G)/μ(G) for a k-connected graph to possess Hamiltonian s-properties.展开更多
This study investigates the international spillover effects of US unconventional monetary policy(UMP)-frequently called large-scale asset purchases or quantitative easing(QE)—on advanced and emerging market economies...This study investigates the international spillover effects of US unconventional monetary policy(UMP)-frequently called large-scale asset purchases or quantitative easing(QE)—on advanced and emerging market economies,using structural vector autoregressive models with high-frequency daily data.Blinder(Federal Reserve Bank of St.Louis Rev 92(6):465–479,2010)argued that the QE measures primarily aim to reduce US interest rate spreads,such as term and risk premiums.Considering this argument and recent empirical evidence,we use two spreads as indicators of US UMP:the mortgage and term spreads.Based on data from 20 emerging and 20 advanced countries,our empirical findings reveal that US unconventional monetary policies significantly affect financial conditions in emerging and advanced countries by altering the risktaking behavior of investors.This result suggests that the risk-taking channel plays an important role in transmitting the effects of these policies to the rest of the world.The extent of these effects depends on the type of QE measures.QE measures such as purchases of private sector securities that lower the US mortgage spread exert stronger and more significant spillover effects on international financial markets than those that reduce the US term spread.Furthermore,the estimated financial spillovers vary substantially across countries and between and within the emerging and advanced countries that we examine in this study.展开更多
The objective of this work was to study the influence of cooking time and cooling rate on functionality and microstructure of processed cheese spreads. When the cooking time was 20 min, the hardness and apparent visco...The objective of this work was to study the influence of cooking time and cooling rate on functionality and microstructure of processed cheese spreads. When the cooking time was 20 min, the hardness and apparent viscosity were increased, and formed a homogenous, dense, and three-dimensional protein network, and a stronger gel was formed at this time. The slow cooling can increase the hardness and apparent viscosity of products, protein wall was thicker, and network was closer, so products can formed a stronger gel structure. The influence of cooking time on the functional properties was more significant than the influence of rapid cooling.展开更多
Australia has experienced significant rises in mortgage costs and sharp declines in housing affordability in the last few decades, particularly since it implemented a new tax system of Goods and Services Tax （GST） i...Australia has experienced significant rises in mortgage costs and sharp declines in housing affordability in the last few decades, particularly since it implemented a new tax system of Goods and Services Tax （GST） in July 2000. Prior research has attempted to examine the influence of the GST on general price levels, but little research effort has been directed to investigate the impact of the GST on mortgage costs. Using proprietary data of major building societies in Australia for 36 months, this paper examines the changes of mortgage yield spreads in the pre-and post-GST periods for building societies. Results suggest that the lenders significantly increased their mortgage charges in the post-GST periods, For example, the increase is found to be, on average, 59.0 basis points which are much higher than that of banks.展开更多
Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were ext...Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were extensively instrumented with strain gauges to measure the distribution of moment during lateral spreading.This allowed us to compute the loading condition,as well as to conduct damage and performance assessments on the piles and pipelines.This paper presents the test results and discussions on the response of single piles and pipelines observed from the full-scale experiments.Based on the test results,it can be concluded that using controlled blasting successfully liquefied the soil,and subsequently induced lateral spreading.The movements of the single pile,as well as the transverse pipelines,were approximately the same as the free field soil movement.Observed moment distribution of the single pile indicated that global translation of the liquefied soil layer provided insignificant force to the pile.In addition,the degree of fixity at the pile tip significantly affected the moment along the pile as well as the pile head displacement.The pile with a higher degree of fixity at the pile tip had smaller pile head displacement but larger maximum moment.展开更多
Bread spread is one of the fundamental foods in human diets. Generally, cheese spread, butter, chocolate spread, and margarine are the most consumed. In the last decade, a new concept alimentary has been integrated, i...Bread spread is one of the fundamental foods in human diets. Generally, cheese spread, butter, chocolate spread, and margarine are the most consumed. In the last decade, a new concept alimentary has been integrated, it was low fat spread or functional spread. This work is an attempt to formulate and optimize new low-fat spreads based on olive oil and honey using a response surface methodology box-benken design. To optimize its stability and its textural properties under the effects of three factors, beeswax content, stirring time, and stirring speed. Results revealed that the best mixture was the formulation that contained 1% beeswax, 79% honey, and 20% olive oil, formulated under 6.39 min of time stirring at 15,428 rpm speed. The beeswax was the major factor showing the highest effect on all the properties of spreads.展开更多
Based on listed companies issuing bonds on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2017, this study analyzes the relationship between significant risk warnings in Chinese companies’ annual reports and ...Based on listed companies issuing bonds on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2017, this study analyzes the relationship between significant risk warnings in Chinese companies’ annual reports and corporate bond credit spreads. The main findings are as follows. First, in the Chinese market, ‘‘substantial warnings of significant risks' can significantly improve corporate bond credit spreads, reflecting the risk-warning effect;second,state-owned property rights weaken this effect, which only pertains to listed companies with poor risk management and low information quality;third, significant risk warnings increase investors’ heterogeneous beliefs, also affecting credit spreads;and fourth, through textual analysis, it is found that the corporate bond credit spread is greater when the disclosed risk factors are more pessimistic and less similar to those of the previous year. The findings of this paper help to enrich the literature on credit spreads and risk disclosure.展开更多
Using hand-collected data on purchases of D&O insurance by Chinese listed firms for the period from 2008 to 2019,we empirically find that D&O insurance negatively associates with credit spreads.The negative re...Using hand-collected data on purchases of D&O insurance by Chinese listed firms for the period from 2008 to 2019,we empirically find that D&O insurance negatively associates with credit spreads.The negative relationship still holds after conducting a series of robustness tests and is not driven by the eyeball effect.We also show that D&O insurance can reduce credit spreads via the channels of internal controls,external monitoring,information asymmetry and default risk.Moreover,the negative effect of D&O insurance on credit spreads is more pronounced for non-state-owned firms,those located in regions with a low level of marketization or that employ rating agencies with a bad reputation.Our study complements the literature on the credit spreads and corporate governance.展开更多
Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives ...Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.展开更多
Health information spreads rapidly,which can effectively control epidemics.However,the swift dissemination of information also has potential negative impacts,which increasingly attracts attention.Message fatigue refer...Health information spreads rapidly,which can effectively control epidemics.However,the swift dissemination of information also has potential negative impacts,which increasingly attracts attention.Message fatigue refers to the psychological response characterized by feelings of boredom and anxiety that occur after receiving an excessive amount of similar information.This phenomenon can alter individual behaviors related to epidemic prevention.Additionally,recent studies indicate that pairwise interactions alone are insufficient to describe complex social transmission processes,and higher-order structures representing group interactions are crucial.To address this,we develop a novel epidemic model that investigates the interactions between information,behavioral responses,and epidemics.Our model incorporates the impact of message fatigue on the entire transmission system.The information layer is modeled using a static simplicial network to capture group interactions,while the disease layer uses a time-varying network based on activity-driven model with attractiveness to represent the self-protection behaviors of susceptible individuals and self-isolation behaviors of infected individuals.We theoretically describe the co-evolution equations using the microscopic Markov chain approach(MMCA)and get the epidemic threshold.Experimental results show that while the negative impact of message fatigue on epidemic transmission is limited,it significantly weakens the group interactions depicted by higher-order structures.Individual behavioral responses strongly inhibit the epidemic.Our simulations using the Monte Carlo(MC)method demonstrate that greater intensity in these responses leads to clustering of susceptible individuals in the disease layer.Finally,we apply the proposed model to real networks to verify its reliability.In summary,our research results enhance the understanding of the information-epidemic coupling dynamics,and we expect to provide valuable guidance for managing future emerging epidemics.展开更多
Objective:To predict the distribution of dengue vector Aedes(Ae.)albopictus and identify high-risk areas for dengue fever transmission.Methods:Data on Ae.albopictus occurrences were collected from electronic databases...Objective:To predict the distribution of dengue vector Aedes(Ae.)albopictus and identify high-risk areas for dengue fever transmission.Methods:Data on Ae.albopictus occurrences were collected from electronic databases.Ensemble models were developed to assess the impacts of climate,vegetation,and human activity on Ae.albopictus.The optimal ensemble model was then used to identify the distribution of suitable areas for Ae.albopictus.Results:After removing duplicate sites and retaining only one location per 100 m×100 m grid,189 Ae.albopictus breeding sites were identified.The optimal ensemble model revealed that Ae.albopictus exhibited higher breeding suitability in Shanghai under specific conditions:a normalized difference vegetation index of 0.1 to 0.6,maximum precipitation in the warmest month ranging from 400 mm to 470 mm,maximum temperature in the warmest month between 30.0℃and 31.0℃,and proximity to waterways within 0.5 km.The most suitable habitats for Ae.albopictus were primarily concentrated in Shanghai’s central urban areas and scattered across the inner suburban districts.Conclusions:The high-risk areas of Ae.albopictus are widely distributed throughout the central urban area and scattered across the inner suburban district of Shanghai,creating conditions conducive to the outbreak of dengue fever.It is essential to enhance targeted control measures for Ae.albopictus in the identified risk areas.展开更多
Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt pro...Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt protective measures.However, whether to disseminate specific information is also a behavioral decision. In light of this understanding, we develop a coupled information–vaccination–epidemic model to depict these co-evolutionary dynamics in a three-layer network. Negative information dissemination and vaccination are treated as separate decision-making processes. We then examine the combined effects of herd and risk motives on information dissemination and vaccination decisions through the lens of game theory. The microscopic Markov chain approach(MMCA) is used to describe the dynamic process and to derive the epidemic threshold. Simulation results indicate that increasing the cost of negative information dissemination and providing timely clarification can effectively control the epidemic. Furthermore, a phenomenon of diminishing marginal utility is observed as the cost of dissemination increases, suggesting that authorities do not need to overinvest in suppressing negative information. Conversely, reducing the cost of vaccination and increasing vaccine efficacy emerge as more effective strategies for outbreak control. In addition, we find that the scale of the epidemic is greater when the herd motive dominates behavioral decision-making. In conclusion, this study provides a new perspective for understanding the complexity of epidemic spreading by starting with the construction of different behavioral decisions.展开更多
Imagine a cold morning in Hanoi,where the steam from a bowl of Vietnamese Pho rises,inviting you in for a warm meal.Pho is more than just a soup;it's a hug in a bowl,full of life and tradition.This tasty dish star...Imagine a cold morning in Hanoi,where the steam from a bowl of Vietnamese Pho rises,inviting you in for a warm meal.Pho is more than just a soup;it's a hug in a bowl,full of life and tradition.This tasty dish started in the north of Vietnam and has spread all over the world.It's made with a tasty broth(肉汤)that takes hours to cook.展开更多
Identifying vital nodes is one of the core issues of network science,and is crucial for epidemic prevention and control,network security maintenance,and biomedical research and development.In this paper,a new vital no...Identifying vital nodes is one of the core issues of network science,and is crucial for epidemic prevention and control,network security maintenance,and biomedical research and development.In this paper,a new vital nodes identification method,named degree and cycle ratio(DC),is proposed by integrating degree centrality(weightα)and cycle ratio(weight 1-α).The results show that the dynamic observations and weightαare nonlinear and non-monotonicity(i.e.,there exists an optimal valueα^(*)forα),and that DC performs better than a single index in most networks.According to the value ofα^(*),networks are classified into degree-dominant networks(α^(*)>0.5)and cycle-dominant networks(α^(*)<0.5).Specifically,in most degree-dominant networks(such as Chengdu-BUS,Chongqing-BUS and Beijing-BUS),degree is dominant in the identification of vital nodes,but the identification effect can be improved by adding cycle structure information to the nodes.In most cycle-dominant networks(such as Email,Wiki and Hamsterster),the cycle ratio is dominant in the identification of vital nodes,but the effect can be notably enhanced by additional node degree information.Finally,interestingly,in Lancichinetti-Fortunato-Radicchi(LFR)synthesis networks,the cycle-dominant network is observed.展开更多
Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model ...Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round simulations.To settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling strategies.Specifically,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC model.In addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational efficiency.The results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC method.Our experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research.展开更多
Botryosphaeria laricina(larch shoot blight)was first identified in 1973 in Jilin Province,China.The disease spread rapidly and caused considerable damage because its pathogenesis was unknown at the time and there were...Botryosphaeria laricina(larch shoot blight)was first identified in 1973 in Jilin Province,China.The disease spread rapidly and caused considerable damage because its pathogenesis was unknown at the time and there were no effective controls or quarantine methods.At present,it shows a spreading trend,but most research can only conduct physiological analyses within a relatively short period,combining individual influencing factors.Nevertheless,methods such as neural network models,ensemble learning algorithms,and Markov models are used in pest and disease prediction and forecasting.However,there may be fitting issues or inherent limitations associated with these methods.This study obtained B.laricina data at the county level from 2003 to 2021.The dataset was augmented using the SMOTE algorithm,and then algorithms such as XGBoost were used to select the significant features from a combined set of 12 features.A new stacking fusion model has been proposed to predict the status of B.laricina.The model is based on random forest,gradient boosted decision tree,CatBoost and logistic regression algorithms.The accuracy,recall,specificity,precision,F_(1) value and AUC of the model reached 90.9%,91.6%,90.4%,88.8%,90.2%and 96.2%.The results provide evidence of the strong performance and stability of the model.B.laricina is mainly found in the northeast and this study indicates that it is spreading northwest.Reasonable means should be used promptly to prevent further damage and spread.展开更多
Rumor Control(RC),aimed at minimizing the spread of rumors in social networks,is of paramount importance,as the spread of rumors can lead to significant economic losses,societal disruptions,and even widespread panic.T...Rumor Control(RC),aimed at minimizing the spread of rumors in social networks,is of paramount importance,as the spread of rumors can lead to significant economic losses,societal disruptions,and even widespread panic.The RC problem has garnered extensive research attention,however,most existing solutions for rumor control face a trade-off between efficiency and effectiveness,which limits their practical application in real-world scenarios.In this light,this paper studies the Truth-spreading-based Rumor Control(TRC)problem,and introduces the Subgraphbased Greedy algorithm Optimized with CELF(SGOC),which employs subgraph techniques and the CELF strategy,as the basic solution for the TRC problem.To improve the performance of SGOC,we carefully design a shortest path length dictionary SPR and an Immune Nodes Set(INS),leading to the Shortest Path-Based Rumor Control(SPRC)algorithm.To further enhance the SPRC algorithm,we develop a pruning method that accelerates the construction process of INS,proposing the Improved Shortest Path-Based Rumor Control(ISPRC)algorithm,which demonstrates superior efficiency compared to both SPRC and SGOC.Extensive experiments conducted on five real-world datasets,demonstrate the effectiveness and efficiency of the proposed algorithms.展开更多
Enhancing the fermentation efficiency of waste in waste warehouses is pivotal for accelerating the pyrolysis process and minimizing harmful gas emissions.This study proposes an integrated approach,combining hot air in...Enhancing the fermentation efficiency of waste in waste warehouses is pivotal for accelerating the pyrolysis process and minimizing harmful gas emissions.This study proposes an integrated approach,combining hot air injection with dual atomizing nozzles,for the thermal treatment of waste piles.Numerical simulations are employed to investigate the influence of various parameters,namely,nozzle height,nozzle tilt angle,inlet air velocity and air temperature,on the droplet diffusion process,spread area,droplet temperature,and droplet size distribution.The results show that reducing the nozzle height increases the temperature of droplets upon their deposition on the waste pile.Specifically,when the nozzle height is lowered to 1.5 m,the temperature of the droplets reaching the waste pile is 1℃higher than when the nozzle height is set at 2 m.Furthermore,an increase in the nozzle tilt angle expands the overlapping heating area.For instance,when the nozzle angle is increased from 15°to 30°,the overlapping spread area expands by 3.21 m2.Additionally,increasing the inlet air velocity enhances the droplet diffusion range.At an air velocity of 2 m/s,the droplet diffusion range grows to 14.4 m,representing a 6.7%increase compared to the nowind condition.While the average droplet diameter decreases to 1.53 mm,the droplet temperature decreases by 1℃.Moreover,the droplet temperature is found to become smaller as the ambient temperature inside the waste warehouse declines.Specifically,a 5℃reduction in the ambient temperature results in a 1℃decrease in the average temperature of the atomized droplets.The study concludes that a nozzle height of 1.5 m and a nozzle tilt angle of 30°effectively meet practical heating requirements.展开更多
The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There i...The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There is a need to evaluate and enhance wildfire prediction methods,focusing on their application during extended periods of intense heat and drought.This study reviews various wildfire modelling approaches,including traditional physical,semi-empirical,numerical,and emerging machine learning(ML)-based models.We critically assess these models’capabilities in predicting fire susceptibility and post-ignition spread,highlighting their strengths and limitations.Our findings indicate that while traditional models provide foundational insights,they often fall short in dynamically estimating parameters and predicting ignition events.Cellular automata models,despite their potential,face challenges in data integration and computational demands.Conversely,ML models demonstrate superior efficiency and accuracy by leveraging diverse datasets,though they encounter interpretability issues.This review recommends hybrid modelling approaches that integrate multiple methods to harness their combined strengths.By incorporating data assimilation techniques with dynamic forecasting models,the predictive capabilities of ML-based predictions can be significantly enhanced.This review underscores the necessity for continued refinement of these models to ensure their reliability in real-world applications,ultimately contributing to more effective wildfire mitigation and management strategies.Future research should focus on improving hybrid models and exploring new data integration methods to advance predictive capabilities.展开更多
基金Supported by NSFC(Nos.12171089,12271235)NSF of Fujian Province(No.2021J02048)。
文摘A graph G possesses Hamiltonian s-properties when G is Hamilton-connected if s=1,Hamiltonian if s=0,and traceable if s=-1.Let S_A(G)=λ_n(G)-λ_1(G)and S_L(G)=μ_n(G)-μ_2(G)be the spread and the Laplacian spread of G,respectively,whereλ_n(G)andλ_1(G)are the largest and smallest eigenvalues of G,andμ_n(G)andμ_2(G)are the largest and second smallest Laplacian eigenvalues of G,respectively.In this paper,we shall present two sufficient conditions involving S_A(G)and S_L(G)for a k-connected graph to possess Hamiltonian s-properties,respectively.We also derive a sufficient condition on the Laplacian eigenratio μ2(G)/μ(G) for a k-connected graph to possess Hamiltonian s-properties.
基金Funding was provided by Anadolu University Scientific Research Project Commission(Grant number:1605E282).
文摘This study investigates the international spillover effects of US unconventional monetary policy(UMP)-frequently called large-scale asset purchases or quantitative easing(QE)—on advanced and emerging market economies,using structural vector autoregressive models with high-frequency daily data.Blinder(Federal Reserve Bank of St.Louis Rev 92(6):465–479,2010)argued that the QE measures primarily aim to reduce US interest rate spreads,such as term and risk premiums.Considering this argument and recent empirical evidence,we use two spreads as indicators of US UMP:the mortgage and term spreads.Based on data from 20 emerging and 20 advanced countries,our empirical findings reveal that US unconventional monetary policies significantly affect financial conditions in emerging and advanced countries by altering the risktaking behavior of investors.This result suggests that the risk-taking channel plays an important role in transmitting the effects of these policies to the rest of the world.The extent of these effects depends on the type of QE measures.QE measures such as purchases of private sector securities that lower the US mortgage spread exert stronger and more significant spillover effects on international financial markets than those that reduce the US term spread.Furthermore,the estimated financial spillovers vary substantially across countries and between and within the emerging and advanced countries that we examine in this study.
基金Supported by Tackle Problem Project of Science and Technology Department of Heilongjiang Province (GC05B404)
文摘The objective of this work was to study the influence of cooking time and cooling rate on functionality and microstructure of processed cheese spreads. When the cooking time was 20 min, the hardness and apparent viscosity were increased, and formed a homogenous, dense, and three-dimensional protein network, and a stronger gel was formed at this time. The slow cooling can increase the hardness and apparent viscosity of products, protein wall was thicker, and network was closer, so products can formed a stronger gel structure. The influence of cooking time on the functional properties was more significant than the influence of rapid cooling.
文摘Australia has experienced significant rises in mortgage costs and sharp declines in housing affordability in the last few decades, particularly since it implemented a new tax system of Goods and Services Tax （GST） in July 2000. Prior research has attempted to examine the influence of the GST on general price levels, but little research effort has been directed to investigate the impact of the GST on mortgage costs. Using proprietary data of major building societies in Australia for 36 months, this paper examines the changes of mortgage yield spreads in the pre-and post-GST periods for building societies. Results suggest that the lenders significantly increased their mortgage charges in the post-GST periods, For example, the increase is found to be, on average, 59.0 basis points which are much higher than that of banks.
文摘Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were extensively instrumented with strain gauges to measure the distribution of moment during lateral spreading.This allowed us to compute the loading condition,as well as to conduct damage and performance assessments on the piles and pipelines.This paper presents the test results and discussions on the response of single piles and pipelines observed from the full-scale experiments.Based on the test results,it can be concluded that using controlled blasting successfully liquefied the soil,and subsequently induced lateral spreading.The movements of the single pile,as well as the transverse pipelines,were approximately the same as the free field soil movement.Observed moment distribution of the single pile indicated that global translation of the liquefied soil layer provided insignificant force to the pile.In addition,the degree of fixity at the pile tip significantly affected the moment along the pile as well as the pile head displacement.The pile with a higher degree of fixity at the pile tip had smaller pile head displacement but larger maximum moment.
文摘Bread spread is one of the fundamental foods in human diets. Generally, cheese spread, butter, chocolate spread, and margarine are the most consumed. In the last decade, a new concept alimentary has been integrated, it was low fat spread or functional spread. This work is an attempt to formulate and optimize new low-fat spreads based on olive oil and honey using a response surface methodology box-benken design. To optimize its stability and its textural properties under the effects of three factors, beeswax content, stirring time, and stirring speed. Results revealed that the best mixture was the formulation that contained 1% beeswax, 79% honey, and 20% olive oil, formulated under 6.39 min of time stirring at 15,428 rpm speed. The beeswax was the major factor showing the highest effect on all the properties of spreads.
基金NSFC (71472188, 71672191)Humanities and Social Science Foundation (19YJC630040) for its support
文摘Based on listed companies issuing bonds on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2017, this study analyzes the relationship between significant risk warnings in Chinese companies’ annual reports and corporate bond credit spreads. The main findings are as follows. First, in the Chinese market, ‘‘substantial warnings of significant risks' can significantly improve corporate bond credit spreads, reflecting the risk-warning effect;second,state-owned property rights weaken this effect, which only pertains to listed companies with poor risk management and low information quality;third, significant risk warnings increase investors’ heterogeneous beliefs, also affecting credit spreads;and fourth, through textual analysis, it is found that the corporate bond credit spread is greater when the disclosed risk factors are more pessimistic and less similar to those of the previous year. The findings of this paper help to enrich the literature on credit spreads and risk disclosure.
基金supported by the National Natural Science Foundation of China(No.72072012,71672007,71972010 and 71972011)the National Social Science Fund of China(No.18BGL090)
文摘Using hand-collected data on purchases of D&O insurance by Chinese listed firms for the period from 2008 to 2019,we empirically find that D&O insurance negatively associates with credit spreads.The negative relationship still holds after conducting a series of robustness tests and is not driven by the eyeball effect.We also show that D&O insurance can reduce credit spreads via the channels of internal controls,external monitoring,information asymmetry and default risk.Moreover,the negative effect of D&O insurance on credit spreads is more pronounced for non-state-owned firms,those located in regions with a low level of marketization or that employ rating agencies with a bad reputation.Our study complements the literature on the credit spreads and corporate governance.
基金supported by the National Natural Science Foundation of China,Nos.82071426,81873784Clinical Cohort Construction Program of Peking University Third Hospital,No.BYSYDL2019002(all to DF)。
文摘Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.72171136 and 72134004)Humanities and Social Science Research Project,Ministry of Education of China(Grant No.21YJC630157)+1 种基金the Natural Science Foundation of Shandong Province(Grant No.ZR2022MG008)Shandong Provincial Colleges and Universities Youth Innovation Technology of China(Grant No.2022RW066)。
文摘Health information spreads rapidly,which can effectively control epidemics.However,the swift dissemination of information also has potential negative impacts,which increasingly attracts attention.Message fatigue refers to the psychological response characterized by feelings of boredom and anxiety that occur after receiving an excessive amount of similar information.This phenomenon can alter individual behaviors related to epidemic prevention.Additionally,recent studies indicate that pairwise interactions alone are insufficient to describe complex social transmission processes,and higher-order structures representing group interactions are crucial.To address this,we develop a novel epidemic model that investigates the interactions between information,behavioral responses,and epidemics.Our model incorporates the impact of message fatigue on the entire transmission system.The information layer is modeled using a static simplicial network to capture group interactions,while the disease layer uses a time-varying network based on activity-driven model with attractiveness to represent the self-protection behaviors of susceptible individuals and self-isolation behaviors of infected individuals.We theoretically describe the co-evolution equations using the microscopic Markov chain approach(MMCA)and get the epidemic threshold.Experimental results show that while the negative impact of message fatigue on epidemic transmission is limited,it significantly weakens the group interactions depicted by higher-order structures.Individual behavioral responses strongly inhibit the epidemic.Our simulations using the Monte Carlo(MC)method demonstrate that greater intensity in these responses leads to clustering of susceptible individuals in the disease layer.Finally,we apply the proposed model to real networks to verify its reliability.In summary,our research results enhance the understanding of the information-epidemic coupling dynamics,and we expect to provide valuable guidance for managing future emerging epidemics.
基金supported by Three-Year Initiative Plan for Strengthening Public Health System Construction in Shanghai(2023-2025)Key Discipline Project(No.GWVI-11.1-12).
文摘Objective:To predict the distribution of dengue vector Aedes(Ae.)albopictus and identify high-risk areas for dengue fever transmission.Methods:Data on Ae.albopictus occurrences were collected from electronic databases.Ensemble models were developed to assess the impacts of climate,vegetation,and human activity on Ae.albopictus.The optimal ensemble model was then used to identify the distribution of suitable areas for Ae.albopictus.Results:After removing duplicate sites and retaining only one location per 100 m×100 m grid,189 Ae.albopictus breeding sites were identified.The optimal ensemble model revealed that Ae.albopictus exhibited higher breeding suitability in Shanghai under specific conditions:a normalized difference vegetation index of 0.1 to 0.6,maximum precipitation in the warmest month ranging from 400 mm to 470 mm,maximum temperature in the warmest month between 30.0℃and 31.0℃,and proximity to waterways within 0.5 km.The most suitable habitats for Ae.albopictus were primarily concentrated in Shanghai’s central urban areas and scattered across the inner suburban districts.Conclusions:The high-risk areas of Ae.albopictus are widely distributed throughout the central urban area and scattered across the inner suburban district of Shanghai,creating conditions conducive to the outbreak of dengue fever.It is essential to enhance targeted control measures for Ae.albopictus in the identified risk areas.
基金Project supported by the National Natural Science Foundation of China (Grant No. 72174121)the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and the Soft Science Research Project of Shanghai (Grant No. 22692112600)。
文摘Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt protective measures.However, whether to disseminate specific information is also a behavioral decision. In light of this understanding, we develop a coupled information–vaccination–epidemic model to depict these co-evolutionary dynamics in a three-layer network. Negative information dissemination and vaccination are treated as separate decision-making processes. We then examine the combined effects of herd and risk motives on information dissemination and vaccination decisions through the lens of game theory. The microscopic Markov chain approach(MMCA) is used to describe the dynamic process and to derive the epidemic threshold. Simulation results indicate that increasing the cost of negative information dissemination and providing timely clarification can effectively control the epidemic. Furthermore, a phenomenon of diminishing marginal utility is observed as the cost of dissemination increases, suggesting that authorities do not need to overinvest in suppressing negative information. Conversely, reducing the cost of vaccination and increasing vaccine efficacy emerge as more effective strategies for outbreak control. In addition, we find that the scale of the epidemic is greater when the herd motive dominates behavioral decision-making. In conclusion, this study provides a new perspective for understanding the complexity of epidemic spreading by starting with the construction of different behavioral decisions.
文摘Imagine a cold morning in Hanoi,where the steam from a bowl of Vietnamese Pho rises,inviting you in for a warm meal.Pho is more than just a soup;it's a hug in a bowl,full of life and tradition.This tasty dish started in the north of Vietnam and has spread all over the world.It's made with a tasty broth(肉汤)that takes hours to cook.
基金Project supported by Yunnan Fundamental Research Projects(Grant No.202401AT070359)。
文摘Identifying vital nodes is one of the core issues of network science,and is crucial for epidemic prevention and control,network security maintenance,and biomedical research and development.In this paper,a new vital nodes identification method,named degree and cycle ratio(DC),is proposed by integrating degree centrality(weightα)and cycle ratio(weight 1-α).The results show that the dynamic observations and weightαare nonlinear and non-monotonicity(i.e.,there exists an optimal valueα^(*)forα),and that DC performs better than a single index in most networks.According to the value ofα^(*),networks are classified into degree-dominant networks(α^(*)>0.5)and cycle-dominant networks(α^(*)<0.5).Specifically,in most degree-dominant networks(such as Chengdu-BUS,Chongqing-BUS and Beijing-BUS),degree is dominant in the identification of vital nodes,but the identification effect can be improved by adding cycle structure information to the nodes.In most cycle-dominant networks(such as Email,Wiki and Hamsterster),the cycle ratio is dominant in the identification of vital nodes,but the effect can be notably enhanced by additional node degree information.Finally,interestingly,in Lancichinetti-Fortunato-Radicchi(LFR)synthesis networks,the cycle-dominant network is observed.
基金support from the National Natural Science Foundation of China(Grant No.T2293771)the STI 2030-Major Projects(Grant No.2022ZD0211400)the Sichuan Province Outstanding Young Scientists Foundation(Grant No.2023NSFSC1919)。
文摘Independent cascade(IC)models,by simulating how one node can activate another,are important tools for studying the dynamics of information spreading in complex networks.However,traditional algorithms for the IC model implementation face significant efficiency bottlenecks when dealing with large-scale networks and multi-round simulations.To settle this problem,this study introduces a GPU-based parallel independent cascade(GPIC)algorithm,featuring an optimized representation of the network data structure and parallel task scheduling strategies.Specifically,for this GPIC algorithm,we propose a network data structure tailored for GPU processing,thereby enhancing the computational efficiency and the scalability of the IC model.In addition,we design a parallel framework that utilizes the full potential of GPU's parallel processing capabilities,thereby augmenting the computational efficiency.The results from our simulation experiments demonstrate that GPIC not only preserves accuracy but also significantly boosts efficiency,achieving a speedup factor of 129 when compared to the baseline IC method.Our experiments also reveal that when using GPIC for the independent cascade simulation,100-200 simulation rounds are sufficient for higher-cost studies,while high precision studies benefit from 500 rounds to ensure reliable results,providing empirical guidance for applying this new algorithm to practical research.
基金supported by the National Key R&D Program of China(Grant No.2021YFD1400300).
文摘Botryosphaeria laricina(larch shoot blight)was first identified in 1973 in Jilin Province,China.The disease spread rapidly and caused considerable damage because its pathogenesis was unknown at the time and there were no effective controls or quarantine methods.At present,it shows a spreading trend,but most research can only conduct physiological analyses within a relatively short period,combining individual influencing factors.Nevertheless,methods such as neural network models,ensemble learning algorithms,and Markov models are used in pest and disease prediction and forecasting.However,there may be fitting issues or inherent limitations associated with these methods.This study obtained B.laricina data at the county level from 2003 to 2021.The dataset was augmented using the SMOTE algorithm,and then algorithms such as XGBoost were used to select the significant features from a combined set of 12 features.A new stacking fusion model has been proposed to predict the status of B.laricina.The model is based on random forest,gradient boosted decision tree,CatBoost and logistic regression algorithms.The accuracy,recall,specificity,precision,F_(1) value and AUC of the model reached 90.9%,91.6%,90.4%,88.8%,90.2%and 96.2%.The results provide evidence of the strong performance and stability of the model.B.laricina is mainly found in the northeast and this study indicates that it is spreading northwest.Reasonable means should be used promptly to prevent further damage and spread.
基金partially supported by Research Programs of Henan Science and Technology Department(252102210022,232102210054)Henan Province Key Research and Development Project(231111212000)+2 种基金Henan Center for Out-standingOverseas Scientists(GZS2022011)Henan Province Collaborative Innovation Center of Aeronautics and Astronautics Electronic Information TechnologyHenan International Joint Laboratory of Aerospace Intelligent Technology and Systems.
文摘Rumor Control(RC),aimed at minimizing the spread of rumors in social networks,is of paramount importance,as the spread of rumors can lead to significant economic losses,societal disruptions,and even widespread panic.The RC problem has garnered extensive research attention,however,most existing solutions for rumor control face a trade-off between efficiency and effectiveness,which limits their practical application in real-world scenarios.In this light,this paper studies the Truth-spreading-based Rumor Control(TRC)problem,and introduces the Subgraphbased Greedy algorithm Optimized with CELF(SGOC),which employs subgraph techniques and the CELF strategy,as the basic solution for the TRC problem.To improve the performance of SGOC,we carefully design a shortest path length dictionary SPR and an Immune Nodes Set(INS),leading to the Shortest Path-Based Rumor Control(SPRC)algorithm.To further enhance the SPRC algorithm,we develop a pruning method that accelerates the construction process of INS,proposing the Improved Shortest Path-Based Rumor Control(ISPRC)algorithm,which demonstrates superior efficiency compared to both SPRC and SGOC.Extensive experiments conducted on five real-world datasets,demonstrate the effectiveness and efficiency of the proposed algorithms.
文摘Enhancing the fermentation efficiency of waste in waste warehouses is pivotal for accelerating the pyrolysis process and minimizing harmful gas emissions.This study proposes an integrated approach,combining hot air injection with dual atomizing nozzles,for the thermal treatment of waste piles.Numerical simulations are employed to investigate the influence of various parameters,namely,nozzle height,nozzle tilt angle,inlet air velocity and air temperature,on the droplet diffusion process,spread area,droplet temperature,and droplet size distribution.The results show that reducing the nozzle height increases the temperature of droplets upon their deposition on the waste pile.Specifically,when the nozzle height is lowered to 1.5 m,the temperature of the droplets reaching the waste pile is 1℃higher than when the nozzle height is set at 2 m.Furthermore,an increase in the nozzle tilt angle expands the overlapping heating area.For instance,when the nozzle angle is increased from 15°to 30°,the overlapping spread area expands by 3.21 m2.Additionally,increasing the inlet air velocity enhances the droplet diffusion range.At an air velocity of 2 m/s,the droplet diffusion range grows to 14.4 m,representing a 6.7%increase compared to the nowind condition.While the average droplet diameter decreases to 1.53 mm,the droplet temperature decreases by 1℃.Moreover,the droplet temperature is found to become smaller as the ambient temperature inside the waste warehouse declines.Specifically,a 5℃reduction in the ambient temperature results in a 1℃decrease in the average temperature of the atomized droplets.The study concludes that a nozzle height of 1.5 m and a nozzle tilt angle of 30°effectively meet practical heating requirements.
基金funding enabled and organized by CAUL and its Member Institutions.
文摘The significant threat of wildfires to forest ecology and biodiversity,particularly in tropical and subtropical regions,underscores the necessity for advanced predictive models amidst shifting climate patterns.There is a need to evaluate and enhance wildfire prediction methods,focusing on their application during extended periods of intense heat and drought.This study reviews various wildfire modelling approaches,including traditional physical,semi-empirical,numerical,and emerging machine learning(ML)-based models.We critically assess these models’capabilities in predicting fire susceptibility and post-ignition spread,highlighting their strengths and limitations.Our findings indicate that while traditional models provide foundational insights,they often fall short in dynamically estimating parameters and predicting ignition events.Cellular automata models,despite their potential,face challenges in data integration and computational demands.Conversely,ML models demonstrate superior efficiency and accuracy by leveraging diverse datasets,though they encounter interpretability issues.This review recommends hybrid modelling approaches that integrate multiple methods to harness their combined strengths.By incorporating data assimilation techniques with dynamic forecasting models,the predictive capabilities of ML-based predictions can be significantly enhanced.This review underscores the necessity for continued refinement of these models to ensure their reliability in real-world applications,ultimately contributing to more effective wildfire mitigation and management strategies.Future research should focus on improving hybrid models and exploring new data integration methods to advance predictive capabilities.
