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
BACKGROUND Colorectal laterally spreading tumors(LSTs)are best treated with endoscopic submucosal dissection or endoscopic mucosal resection.AIM To analyze the clinicopathological and endoscopic profiles of colorectal...BACKGROUND Colorectal laterally spreading tumors(LSTs)are best treated with endoscopic submucosal dissection or endoscopic mucosal resection.AIM To analyze the clinicopathological and endoscopic profiles of colorectal LSTs,determine predictive factors for high-grade dysplasia(HGD)/carcinoma(CA),submucosal invasion,and complications.METHODS We retrospectively assessed the endoscopic and histological characteristics of 375 colorectal LSTs at our hospital between January 2016 and December 2023.We performed univariate and multivariate analysis to identify risk factors associated with HGD/CA,submucosal invasion and complications.RESULTS The numbers of granular(LST-G)and non-granular LST(LST-NG)were 260 and 115,respectively.The rates of low-grade dysplasia and HGD/CA were 60.3%and 39.7%,respectively.Multivariate analysis indicated that a tumor size≥30 mm[odds ratio(OR)=1.934,P=0.032],LST granular nodular mixed type(OR=2.100,P=0.005),and LST non-granular pseudo depressed type(NG-PD)(OR=3.016,P=0.015)were independent risk factors significantly associated with higher odds of HGD/CA.NG-PD(OR=6.506,P=0.001),tumor size(20-29 mm)(OR=2.631,P=0.036)and tumor size≥30 mm(OR=3.449,P=0.016)were associated with increased odds of submucosal invasion.Tumor size≥30 mm(OR=4.888,P=0.003)was a particularly important predictor of complications.A nomogram model demonstrated a satisfactory fit,with an area under the receiver operating characteristic curve of 0.716(95%confidence interval:0.653-0.780),indicating strong predictive performance.CONCLUSION The novel nomogram incorporating tumor size,location,and morphology predicted HGD/CA during endoscopic resection for LSTs.NG-PD lesions larger than 20 mm were more likely to invade the submucosa.Tumor size≥30 mm was an important predictor of complications.展开更多
Information spreading has been investigated for many years,but the mechanism of why the information explosively catches on overnight is still under debate.This explosive spreading phenomenon was usually considered dri...Information spreading has been investigated for many years,but the mechanism of why the information explosively catches on overnight is still under debate.This explosive spreading phenomenon was usually considered driven separately by social reinforcement or higher-order interactions.However,due to the limitations of empirical data and theoretical analysis,how the higher-order network structure affects the explosive information spreading under the role of social reinforcement has not been fully explored.In this work,we propose an information-spreading model by considering the social reinforcement in real and synthetic higher-order networks,describable as hypergraphs.Depending on the average group size(hyperedge cardinality)and node membership(hyperdegree),we observe two different spreading behaviors:(i)The spreading progress is not sensitive to social reinforcement,resulting in the information localized in a small part of nodes;(ii)a strong social reinforcement will promote the large-scale spread of information and induce an explosive transition.Moreover,a large average group size and membership would be beneficial to the appearance of the explosive transition.Further,we display that the heterogeneity of the node membership and group size distributions benefit the information spreading.Finally,we extend the group-based approximate master equations to verify the simulation results.Our findings may help us to comprehend the rapidly information-spreading phenomenon in modern society.展开更多
This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward...This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.展开更多
The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(...The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.展开更多
There are various phenomena of malicious information spreading in the real society, which cause many negative impacts on the society. In order to better control the spreading, it is crucial to reveal the influence of ...There are various phenomena of malicious information spreading in the real society, which cause many negative impacts on the society. In order to better control the spreading, it is crucial to reveal the influence of network structure on network spreading. Motifs, as fundamental structures within a network, play a significant role in spreading. Therefore, it is of interest to investigate the influence of the structural characteristics of basic network motifs on spreading dynamics.Considering the edges of the basic network motifs in an undirected network correspond to different tie ranges, two edge removal strategies are proposed, short ties priority removal strategy and long ties priority removal strategy. The tie range represents the second shortest path length between two connected nodes. The study focuses on analyzing how the proposed strategies impact network spreading and network structure, as well as examining the influence of network structure on network spreading. Our findings indicate that the long ties priority removal strategy is most effective in controlling network spreading, especially in terms of spread range and spread velocity. In terms of network structure, the clustering coefficient and the diameter of network also have an effect on the network spreading, and the triangular structure as an important motif structure effectively inhibits the spreading.展开更多
In recent years,attacks against crowded places such as campuses and theaters have had a frequent and negative impact on the security and stability of society.In such an event,the crowd will be subjected to high psycho...In recent years,attacks against crowded places such as campuses and theaters have had a frequent and negative impact on the security and stability of society.In such an event,the crowd will be subjected to high psychological stress and their emotions will rapidly spread to others.This paper establishes the attack-escape evacuation simulation model(AEES-SFM),based on the social force model,to consider emotion spreading under attack.In this model,(1)the attack-escape driving force is considered for the interaction between an attacker and evacuees and(2)emotion spreading among the evacuees is considered to modify the value of the psychological force.To validate the simulation,several experiments were carried out at a university in China.Comparing the simulation and experimental results,it is found that the simulation results are similar to the experimental results when considering emotion spreading.Therefore,the AEES-SFM is proved to be effective.By comparing the results of the evacuation simulation without emotion spreading,the emotion spreading model reduces the evacuation time and the number of casualties by about 30%,which is closer to the real experimental results.The results are still applicable in the case of a 40-person evacuation.This paper provides theoretical support and practical guidance for campus response to violent attacks.展开更多
The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the wid...The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features,their treatment usually lacks spatiotemporal variation.Here,we propose a stochastic individual dynamical(SID)model to mimic the random and heterogeneous nature of epidemic propagation.The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual.Using this model,we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak.The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective,enabling a quantitative assessment of different interventions.Seemingly,this model is also applicable to studying stochastic processes at the “meter scale”,e.g.,human society’s collective dynamics.展开更多
Background: We present a compelling case fitting the phenomenon of cortical spreading depression detected by intraoperative neurophysiological monitoring (IONM) following an intraoperative seizure during a craniotomy ...Background: We present a compelling case fitting the phenomenon of cortical spreading depression detected by intraoperative neurophysiological monitoring (IONM) following an intraoperative seizure during a craniotomy for revascularization. Cortical spreading depression (CSD, also called cortical spreading depolarization) is a pathophysiological phenomenon whereby a wave of depolarization is thought to propagate across the cerebral cortex, creating a brief period of relative neuronal inactivity. The relationship between CSD and seizures is unclear, although some literature has made a correlation between seizures and a cortical environment conducive to CSD. Methods: Intraoperative somatosensory evoked potentials (SSEPs) and electroencephalography (EEG) were monitored continuously during the craniotomy procedure utilizing standard montages. Electrophysiological data from pre-ictal, ictal, and post-ictal periods were recorded. Results: During the procedure, intraoperative EEG captured a generalized seizure followed by a stepwise decrease in somatosensory evoked potential cortical amplitudes, compelling for the phenomenon of CSD. The subsequent partial recovery of neuronal function was also captured electrophysiologically. Discussion: While CSD is considered controversial in some aspects, intraoperative neurophysiological monitoring allowed for the unique analysis of a case demonstrating a CSD-like phenomenon. To our knowledge, this is the first published example of this phenomenon in which intraoperative neurophysiological monitoring captured a seizure, along with a stepwise subsequent reduction in SSEP cortical amplitudes not explained by other variables.展开更多
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BACKGROUND Colorectal laterally spreading tumors(LSTs)are best treated with endoscopic submucosal dissection or endoscopic mucosal resection.AIM To analyze the clinicopathological and endoscopic profiles of colorectal LSTs,determine predictive factors for high-grade dysplasia(HGD)/carcinoma(CA),submucosal invasion,and complications.METHODS We retrospectively assessed the endoscopic and histological characteristics of 375 colorectal LSTs at our hospital between January 2016 and December 2023.We performed univariate and multivariate analysis to identify risk factors associated with HGD/CA,submucosal invasion and complications.RESULTS The numbers of granular(LST-G)and non-granular LST(LST-NG)were 260 and 115,respectively.The rates of low-grade dysplasia and HGD/CA were 60.3%and 39.7%,respectively.Multivariate analysis indicated that a tumor size≥30 mm[odds ratio(OR)=1.934,P=0.032],LST granular nodular mixed type(OR=2.100,P=0.005),and LST non-granular pseudo depressed type(NG-PD)(OR=3.016,P=0.015)were independent risk factors significantly associated with higher odds of HGD/CA.NG-PD(OR=6.506,P=0.001),tumor size(20-29 mm)(OR=2.631,P=0.036)and tumor size≥30 mm(OR=3.449,P=0.016)were associated with increased odds of submucosal invasion.Tumor size≥30 mm(OR=4.888,P=0.003)was a particularly important predictor of complications.A nomogram model demonstrated a satisfactory fit,with an area under the receiver operating characteristic curve of 0.716(95%confidence interval:0.653-0.780),indicating strong predictive performance.CONCLUSION The novel nomogram incorporating tumor size,location,and morphology predicted HGD/CA during endoscopic resection for LSTs.NG-PD lesions larger than 20 mm were more likely to invade the submucosa.Tumor size≥30 mm was an important predictor of complications.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12305043 and 12165016)the Natural Science Foundation of Jiangsu Province(Grant No.BK20220511)+1 种基金the Project of Undergraduate Scientific Research(Grant No.22A684)the support from the Jiangsu Specially-Appointed Professor Program。
文摘Information spreading has been investigated for many years,but the mechanism of why the information explosively catches on overnight is still under debate.This explosive spreading phenomenon was usually considered driven separately by social reinforcement or higher-order interactions.However,due to the limitations of empirical data and theoretical analysis,how the higher-order network structure affects the explosive information spreading under the role of social reinforcement has not been fully explored.In this work,we propose an information-spreading model by considering the social reinforcement in real and synthetic higher-order networks,describable as hypergraphs.Depending on the average group size(hyperedge cardinality)and node membership(hyperdegree),we observe two different spreading behaviors:(i)The spreading progress is not sensitive to social reinforcement,resulting in the information localized in a small part of nodes;(ii)a strong social reinforcement will promote the large-scale spread of information and induce an explosive transition.Moreover,a large average group size and membership would be beneficial to the appearance of the explosive transition.Further,we display that the heterogeneity of the node membership and group size distributions benefit the information spreading.Finally,we extend the group-based approximate master equations to verify the simulation results.Our findings may help us to comprehend the rapidly information-spreading phenomenon in modern society.
基金supported by the Natural Science Basic Research Program of Shanxi(Grant No.2024JC-YBMS-025)the Innovation Capability Support Program of Shanxi(Grant No.2024RS-CXTD-88)。
文摘This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.
文摘The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 62373197 and 62203229)the Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (Grant No. KYCX24_1211)。
文摘There are various phenomena of malicious information spreading in the real society, which cause many negative impacts on the society. In order to better control the spreading, it is crucial to reveal the influence of network structure on network spreading. Motifs, as fundamental structures within a network, play a significant role in spreading. Therefore, it is of interest to investigate the influence of the structural characteristics of basic network motifs on spreading dynamics.Considering the edges of the basic network motifs in an undirected network correspond to different tie ranges, two edge removal strategies are proposed, short ties priority removal strategy and long ties priority removal strategy. The tie range represents the second shortest path length between two connected nodes. The study focuses on analyzing how the proposed strategies impact network spreading and network structure, as well as examining the influence of network structure on network spreading. Our findings indicate that the long ties priority removal strategy is most effective in controlling network spreading, especially in terms of spread range and spread velocity. In terms of network structure, the clustering coefficient and the diameter of network also have an effect on the network spreading, and the triangular structure as an important motif structure effectively inhibits the spreading.
基金Project supported by the National Natural Science Foundation of China(Grant No.72274208)。
文摘In recent years,attacks against crowded places such as campuses and theaters have had a frequent and negative impact on the security and stability of society.In such an event,the crowd will be subjected to high psychological stress and their emotions will rapidly spread to others.This paper establishes the attack-escape evacuation simulation model(AEES-SFM),based on the social force model,to consider emotion spreading under attack.In this model,(1)the attack-escape driving force is considered for the interaction between an attacker and evacuees and(2)emotion spreading among the evacuees is considered to modify the value of the psychological force.To validate the simulation,several experiments were carried out at a university in China.Comparing the simulation and experimental results,it is found that the simulation results are similar to the experimental results when considering emotion spreading.Therefore,the AEES-SFM is proved to be effective.By comparing the results of the evacuation simulation without emotion spreading,the emotion spreading model reduces the evacuation time and the number of casualties by about 30%,which is closer to the real experimental results.The results are still applicable in the case of a 40-person evacuation.This paper provides theoretical support and practical guidance for campus response to violent attacks.
基金supported by the National Natural Science Foundation of China(Grant No.22273034)the Frontiers Science Center for Critical Earth Material Cycling of Nanjing University。
文摘The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features,their treatment usually lacks spatiotemporal variation.Here,we propose a stochastic individual dynamical(SID)model to mimic the random and heterogeneous nature of epidemic propagation.The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual.Using this model,we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak.The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective,enabling a quantitative assessment of different interventions.Seemingly,this model is also applicable to studying stochastic processes at the “meter scale”,e.g.,human society’s collective dynamics.
文摘Background: We present a compelling case fitting the phenomenon of cortical spreading depression detected by intraoperative neurophysiological monitoring (IONM) following an intraoperative seizure during a craniotomy for revascularization. Cortical spreading depression (CSD, also called cortical spreading depolarization) is a pathophysiological phenomenon whereby a wave of depolarization is thought to propagate across the cerebral cortex, creating a brief period of relative neuronal inactivity. The relationship between CSD and seizures is unclear, although some literature has made a correlation between seizures and a cortical environment conducive to CSD. Methods: Intraoperative somatosensory evoked potentials (SSEPs) and electroencephalography (EEG) were monitored continuously during the craniotomy procedure utilizing standard montages. Electrophysiological data from pre-ictal, ictal, and post-ictal periods were recorded. Results: During the procedure, intraoperative EEG captured a generalized seizure followed by a stepwise decrease in somatosensory evoked potential cortical amplitudes, compelling for the phenomenon of CSD. The subsequent partial recovery of neuronal function was also captured electrophysiologically. Discussion: While CSD is considered controversial in some aspects, intraoperative neurophysiological monitoring allowed for the unique analysis of a case demonstrating a CSD-like phenomenon. To our knowledge, this is the first published example of this phenomenon in which intraoperative neurophysiological monitoring captured a seizure, along with a stepwise subsequent reduction in SSEP cortical amplitudes not explained by other variables.
