Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been ...Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CCR wall〈 sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.展开更多
Complex systems from different fields of knowledge often do not allow a mathematical description or modeling, because of their intricate structure composed of numerous interacting components. As an alternative approac...Complex systems from different fields of knowledge often do not allow a mathematical description or modeling, because of their intricate structure composed of numerous interacting components. As an alternative approach, it is possible to study the way in which observables associated with the system fluctuate in time. These time series may provide valuable information about the underlying dynamics. It has been suggested that complex dynamic systems, ranging from ecosystems to financial markets and the climate, produce generic early-warning signals at the "tipping points," where they announce a sudden shift toward a different dynamical regime, such as a population extinction, a systemic market crash, or abrupt shifts in the weather. On the other hand, the framework of Self- Organized Criticality (SOC), suggests that some complex systems, such as life itself, may spontaneously converge toward a critical point. As a particular example, the quasispecies model suggests that RNA viruses self-organize their mutation rate near the error-catastrophe threshold, where robustness and evolvability are balanced in such a way that survival is optimized. In this paper, we study the time series associated to a classical discrete quasispecies model for different mutation rates, and identify early-warning signals for critical mutation rates near the error-catastrophe threshold, such as irregularities in the kurtosis and a significant increase in the autocorrelation range, reminiscent of 1/f noise. In the present context, we find that the early-warning signals, rather than broadcasting the collapse of the system, are the fingerprint of survival optimization.展开更多
The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental challenges.In the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an impo...The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental challenges.In the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and neuroplasticity.The glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic mechanisms.Protein interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive functions.An appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive impairment.Patients with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor expression.This review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive activities.It emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive impairment.This provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.展开更多
The interaction between the gut microbiota and cyclic adenosine monophosphate(cAMP)-protein kinase A(PKA)signaling pathway in the host's central nervous system plays a crucial role in neurological diseases and enh...The interaction between the gut microbiota and cyclic adenosine monophosphate(cAMP)-protein kinase A(PKA)signaling pathway in the host's central nervous system plays a crucial role in neurological diseases and enhances communication along the gut–brain axis.The gut microbiota influences the cAMP-PKA signaling pathway through its metabolites,which activates the vagus nerve and modulates the immune and neuroendocrine systems.Conversely,alterations in the cAMP-PKA signaling pathway can affect the composition of the gut microbiota,creating a dynamic network of microbial-host interactions.This reciprocal regulation affects neurodevelopment,neurotransmitter control,and behavioral traits,thus playing a role in the modulation of neurological diseases.The coordinated activity of the gut microbiota and the cAMP-PKA signaling pathway regulates processes such as amyloid-β protein aggregation,mitochondrial dysfunction,abnormal energy metabolism,microglial activation,oxidative stress,and neurotransmitter release,which collectively influence the onset and progression of neurological diseases.This study explores the complex interplay between the gut microbiota and cAMP-PKA signaling pathway,along with its implications for potential therapeutic interventions in neurological diseases.Recent pharmacological research has shown that restoring the balance between gut flora and cAMP-PKA signaling pathway may improve outcomes in neurodegenerative diseases and emotional disorders.This can be achieved through various methods such as dietary modifications,probiotic supplements,Chinese herbal extracts,combinations of Chinese herbs,and innovative dosage forms.These findings suggest that regulating the gut microbiota and cAMP-PKA signaling pathway may provide valuable evidence for developing novel therapeutic approaches for neurodegenerative diseases.展开更多
Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rode...Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rodents and improves memory and slows cognitive decline in patients with Alzheimer’s disease.However,the molecular pathways for exercise-induced adult hippocampal neurogenesis and improved cognition in Alzheimer’s disease are poorly understood.Recently,regulator of G protein signaling 6(RGS6)was identified as the mediator of voluntary running-induced adult hippocampal neurogenesis in mice.Here,we generated novel RGS6fl/fl;APP_(SWE) mice and used retroviral approaches to examine the impact of RGS6 deletion from dentate gyrus neuronal progenitor cells on voluntary running-induced adult hippocampal neurogenesis and cognition in an amyloid-based Alzheimer’s disease mouse model.We found that voluntary running in APP_(SWE) mice restored their hippocampal cognitive impairments to that of control mice.This cognitive rescue was abolished by RGS6 deletion in dentate gyrus neuronal progenitor cells,which also abolished running-mediated increases in adult hippocampal neurogenesis.Adult hippocampal neurogenesis was reduced in sedentary APP_(SWE) mice versus control mice,with basal adult hippocampal neurogenesis reduced by RGS6 deletion in dentate gyrus neural precursor cells.RGS6 was expressed in neurons within the dentate gyrus of patients with Alzheimer’s disease with significant loss of these RGS6-expressing neurons.Thus,RGS6 mediated voluntary running-induced rescue of impaired cognition and adult hippocampal neurogenesis in APP_(SWE) mice,identifying RGS6 in dentate gyrus neural precursor cells as a possible therapeutic target in Alzheimer’s disease.展开更多
Netrin-1 and its receptors play crucial roles in inducing axonal growth and neuronal migration during neuronal development.Their profound impacts then extend into adulthood to encompass the maintenance of neuronal sur...Netrin-1 and its receptors play crucial roles in inducing axonal growth and neuronal migration during neuronal development.Their profound impacts then extend into adulthood to encompass the maintenance of neuronal survival and synaptic function.Increasing amounts of evidence highlight several key points:(1)Diminished Netrin-1 levels exacerbate pathological progression in animal models of Alzheimer’s disease and Parkinson’s disease,and potentially,similar alterations occur in humans.(2)Genetic mutations of Netrin-1 receptors increase an individuals’susceptibility to neurodegenerative disorders.(3)Therapeutic approaches targeting Netrin-1 and its receptors offer the benefits of enhancing memory and motor function.(4)Netrin-1 and its receptors show genetic and epigenetic alterations in a variety of cancers.These findings provide compelling evidence that Netrin-1 and its receptors are crucial targets in neurodegenerative diseases.Through a comprehensive review of Netrin-1 signaling pathways,our objective is to uncover potential therapeutic avenues for neurodegenerative disorders.展开更多
An imbalance in adenosine-mediated signaling,particularly the increased A_(2A)R-mediated signaling,plays a role in the pathogenesis of Parkinson's disease.Existing therapeutic approaches fail to alter disease prog...An imbalance in adenosine-mediated signaling,particularly the increased A_(2A)R-mediated signaling,plays a role in the pathogenesis of Parkinson's disease.Existing therapeutic approaches fail to alter disease progression,demonstrating the need for novel approaches in PD.Repetitive transcranial magnetic stimulation is a non-invasive approach that has been shown to improve motor and non-motor symptoms of Parkinson's disease.However,the underlying mechanisms of the beneficial effects of repetitive transcranial magnetic stimulation remain unknown.The purpose of this study is to investigate the extent to which the beneficial effects of prolonged intermittent theta burst stimulation in the 6-hydroxydopamine model of experimental parkinsonism are based on modulation of adenosine-mediated signaling.Animals with unilateral 6-hydroxydopamine lesions underwent intermittent theta burst stimulation for 3 weeks and were tested for motor skills using the Rotarod test.Immunoblot,quantitative reverse transcription polymerase chain reaction,immunohistochemistry,and biochemical analysis of components of adenosine-mediated signaling were performed on the synaptosomal fraction of the lesioned caudate putamen.Prolonged intermittent theta burst stimulation improved motor symptoms in 6-hydroxydopamine-lesioned animals.A 6-hydroxydopamine lesion resulted in progressive loss of dopaminergic neurons in the caudate putamen.Treatment with intermittent theta burst stimulation began 7 days after the lesion,coinciding with the onset of motor symptoms.After treatment with prolonged intermittent theta burst stimulation,complete motor recovery was observed.This improvement was accompanied by downregulation of the e N/CD73-A_(2A)R pathway and a return to physiological levels of A_(1)R-adenosine deaminase 1 after 3 weeks of intermittent theta burst stimulation.Our results demonstrated that 6-hydroxydopamine-induced degeneration reduced the expression of A_(1)R and elevated the expression of A_(2A)R.Intermittent theta burst stimulation reversed these effects by restoring the abundances of A_(1)R and A_(2A)R to control levels.The shift in ARs expression likely restored the balance between dopamine-adenosine signaling,ultimately leading to the recovery of motor control.展开更多
By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant ...By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant diseases based on particle swarm and neural network algorithm was established. The test results showed that the construction of early-warning model is effective and feasible, which will provide a via- ble model structure to establish the effective early-warning platform.展开更多
The primary goal of Chinese agricultural development is to guarantee national food security and supply of major agricultural products. Hence, the scientiifc work on agricultural monitoring and early warning as wel as ...The primary goal of Chinese agricultural development is to guarantee national food security and supply of major agricultural products. Hence, the scientiifc work on agricultural monitoring and early warning as wel as agricultural outlook must be strengthened. In this study, we develop the China Agricultural Monitoring and Early-warning System (CAMES) on the basis of a comparative study of domestic and international agricultural outlook models. The system is a dynamic and multi-market partial equilibrium model that integrates biological mechanisms with economic mechanisms. This system, which includes 11 categories of 953 kinds of agricultural products, could dynamical y project agricultural market supply and demand, assess food security, and conduct scenario analysis at different spatial levels, time scale levels, and macro-micro levels. Based on the CAMES, the production, consumption, and trade of the major agricultural products in China over the next decade are projected. The fol owing conclusions are drawn:i) The production of major agricultural products wil continue to grow steadily, mainly because of the increase in yield. i ) The growth of agricultural consumption wil be slightly higher than that of agricultural production. Meanwhile, a high self-sufifciency rate is expected for cereals such as rice, wheat, and maize, with the rate being stable at around 97%. i i) Agricultural trade wil continue to thrive. The growth of soybean and milk im-ports wil slow down, but the growth of traditional agricultural exports such as vegetables and fruits is expected to continue.展开更多
The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,par...The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,particularly of heightened projects in the impoundment period.Herein,a new method for monitoring the safety status of heightened dams is proposed based on the deformation monitoring data of a dam structure,a statistical model,and finite-element numerical simulation.First,a fast optimization inversion method for estimation of dam mechanical parameters was developed,which used the water pressure component extracted from a statistical model,an improved inversion objective function,and a genetic optimization iterative algorithm.Then,a finite element model of a heightened concrete gravity dam was established,and the deformation behavior of the dam with rising water levels in the impoundment period was simulated.Subsequently,mechanical parameters of aged dam parts were calculated using the fast optimization inversion method with simulated deformation and the water pressure deformation component obtained by the statistical model under the same conditions of water pressure change.Finally,a new earlywarning index of dam deformation was constructed by means of the forward-simulated deformation and other components of the statistical model.The early-warning index is useful for forecasting dam deformation under different water levels,especially high water levels.展开更多
The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so t...The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.展开更多
By analyzing the heavy fog data in Chizhou City in recent 50 years(1959-2007),the general rules of meteorological elements variations were found when the heavy fog happened.The meteorological elements included the tem...By analyzing the heavy fog data in Chizhou City in recent 50 years(1959-2007),the general rules of meteorological elements variations were found when the heavy fog happened.The meteorological elements included the temperature,humidity,wind direction,wind speed,air pressure and so on.The conceptual models of high-altitude and ground situation were established when the heavy fog happened in Chizhou City.Based on considering sufficiently the special geographical environment in Chizhou City,we found the key factors which affected the local heavy fog via the relative analyses.By using the statistical forecast methods which included the second-level judgment method and regression method of event probability and so on,the forecast mode equation of heavy fog was established.Moreover,the objective forecast system of heavy fog in Chizhou City was also manufactured.It provided the basis and platform which could be referred for the heavy fog forecast,service and the release of early-warning signal.展开更多
The most common method used to describe earthquake activity is based on the changes in physical parameters of the earth's surface such as displacement of active fault and seismic wave.However,such approach is not suc...The most common method used to describe earthquake activity is based on the changes in physical parameters of the earth's surface such as displacement of active fault and seismic wave.However,such approach is not successful in forecasting the movement behaviors of faults.In the present study,a new mechanical model of fault activity,considering the shear strength on the fault plane and the influence of the resistance force,is established based on the occurrence condition of earthquake.A remote real-time monitoring system is correspondingly developed to obtain the changes in mechanical components within fault.Taking into consideration the local geological conditions and the history of fault activity in Zhangjiakou of China,an active fault exposed in the region of Zhangjiakou is selected to be directly monitored by the real-time monitoring technique.A thorough investigation on local fault structures results in the selection of two suitable sites for monitoring potential active tectonic movements of Zhangjiakou fault.Two monitoring curves of shear strength,recorded during a monitoring period of 6 months,turn out to be steady,which indicates that the potential seismic activities hardly occur in the adjacent region in the near future.This monitoring technique can be used for early-warning prediction of the movement of active fault,and can help to further gain an insight into the interaction between fault activity and relevant mechanisms.展开更多
Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural ...Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and DEA model, whose steps were put forward. On the basis of standard risk early-warning DEA model of natural disasters, weight coefficient of risk early-warning factors was determined with Information Entropy method, which improved standard risk early-warning DEA model with non-Archimedean infinitesimal, and established risk early-warning preference DEA model based on integrated entropy weight and DEA Model. Finally, model was applied into landslide risk early-warning case in earthquake-damaged emergency process on slope engineering, which exemplified the outcome could reflect more risk information than the method of standard DEA model, and reflected the rationality, feasibility, and impersonality, revealing its better ability on comprehensive safety and structure risk.展开更多
The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure ...The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.展开更多
According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destru...According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN) real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system’s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.展开更多
The meteorological early-warning loudspeaker is a specific initiative for the meteorological departments to address the issues concerning issues concerning agriculture,countryside and farmers.Its significance is that ...The meteorological early-warning loudspeaker is a specific initiative for the meteorological departments to address the issues concerning issues concerning agriculture,countryside and farmers.Its significance is that it can promptly deliver the early-warning information concerning some meteorological disasters(such as torrential rains,typhoons,cold wave,hail)to the areas affected,so as to provide reference and protection for agricultural production and effectively reduce the loss of agricultural producers.Up to now,the meteorological early-warning loudspeakers in Benxi have covered the villages.However,due to irregular occurrence of meteorological disasters,the listeners will turn off the information receivers of meteorological early-warning loudspeakers when they fail to receive meteorological information for a long time,so that the users can not promptly know the early-warning information regarding some sudden meteorological disasters.In view of this,the meteorological departments have introduced a series of management measures,such as the daily use of loudspeakers to publish weather forecast information,aimed at improving the online rate and usage rate of meteorological loudspeakers.And the management platform for online rate of meteorological early-warning loudspeakers is an important part of the management system.展开更多
As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their cu...As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their customer resources,it is crucial for banks to accurately predict customers with a tendency to churn.Aiming at the typical binary classification problem like customer churn,this paper establishes an early-warning model for credit card customer churn.That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm(GSA)and an Improved Beetle Antennae Search(IBAS)is proposed to optimize the parameters of the CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.展开更多
A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)paramet...A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.展开更多
Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of techn...Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of technology information automatic retrieval, technology information monitoring, technology threat evaluation, and crisis response and management subsystem, which implements uninterrupted dynamic monitoring, trace and crisis early-warning to the specific technology. Empirical study testifies that the system improves the accuracy, timeliness and reliability of technology early-warning.展开更多
基金Project supported by the Fundamental Research Funds for the Central Universities (Grant No. JUSRP21117)the Program for Innovative Research Team of Jiangnan University (Grant No. 2008CX002)
文摘Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CCR wall〈 sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.
文摘Complex systems from different fields of knowledge often do not allow a mathematical description or modeling, because of their intricate structure composed of numerous interacting components. As an alternative approach, it is possible to study the way in which observables associated with the system fluctuate in time. These time series may provide valuable information about the underlying dynamics. It has been suggested that complex dynamic systems, ranging from ecosystems to financial markets and the climate, produce generic early-warning signals at the "tipping points," where they announce a sudden shift toward a different dynamical regime, such as a population extinction, a systemic market crash, or abrupt shifts in the weather. On the other hand, the framework of Self- Organized Criticality (SOC), suggests that some complex systems, such as life itself, may spontaneously converge toward a critical point. As a particular example, the quasispecies model suggests that RNA viruses self-organize their mutation rate near the error-catastrophe threshold, where robustness and evolvability are balanced in such a way that survival is optimized. In this paper, we study the time series associated to a classical discrete quasispecies model for different mutation rates, and identify early-warning signals for critical mutation rates near the error-catastrophe threshold, such as irregularities in the kurtosis and a significant increase in the autocorrelation range, reminiscent of 1/f noise. In the present context, we find that the early-warning signals, rather than broadcasting the collapse of the system, are the fingerprint of survival optimization.
基金supported by the National Natural Science Foundation of China,No.82371444(to YZ)the Natural Science Foundation of Hubei Province,No.2022CFB216(to XC)the Key Research Project of Ministry of Science and Technology of China,No.2022ZD021160(to YZ)。
文摘The hypothalamic-pituitary-adrenal axis regulates the secretion of glucoco rticoids in response to environmental challenges.In the brain,a nuclear receptor transcription fa ctor,the glucocorticoid recepto r,is an important component of the hypothalamicpituitary-a d renal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and neuroplasticity.The glucoco rticoid receptor influences cognitive processes,including glutamate neurotransmission,calcium signaling,and the activation of brain-derived neurotrophic factor-mediated pathways,through a combination of genomic and non-genomic mechanisms.Protein interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor,there by affecting the hypothalamic-pituitary-a d renal axis and stress-related cognitive functions.An appropriate level of glucocorticoid receptor expression can improve cognitive function,while excessive glucocorticoid receptors or long-term exposure to glucoco rticoids may lead to cognitive impairment.Patients with cognitive impairment-associated diseases,such as Alzheimer's disease,aging,depression,Parkinson's disease,Huntington's disease,stroke,and addiction,often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor expression.This review provides a comprehensive overview of the functions of the glucoco rticoid receptor in the hypothalamic-pituitary-a d renal axis and cognitive activities.It emphasizes that appropriate glucocorticoid receptor signaling fa cilitates learning and memory,while its dysregulation can lead to cognitive impairment.This provides clues about how glucocorticoid receptor signaling can be targeted to ove rcome cognitive disability-related disorders.
基金supported by the National Natural Science Foundation of China,No.82003965the Science and Technology Research Project of Sichuan Provincial Administration of Traditional Chinese Medicine,No.2024MS167(to LH)+2 种基金the Xinglin Scholar Program of Chengdu University of Traditional Chinese Medicine,No.QJRC2022033(to LH)the Improvement Plan for the'Xinglin Scholar'Scientific Research Talent Program at Chengdu University of Traditional Chinese Medicine,No.XKTD2023002(to LH)the 2023 National Project of the College Students'Innovation and Entrepreneurship Training Program at Chengdu University of Traditional Chinese Medicine,No.202310633028(to FD)。
文摘The interaction between the gut microbiota and cyclic adenosine monophosphate(cAMP)-protein kinase A(PKA)signaling pathway in the host's central nervous system plays a crucial role in neurological diseases and enhances communication along the gut–brain axis.The gut microbiota influences the cAMP-PKA signaling pathway through its metabolites,which activates the vagus nerve and modulates the immune and neuroendocrine systems.Conversely,alterations in the cAMP-PKA signaling pathway can affect the composition of the gut microbiota,creating a dynamic network of microbial-host interactions.This reciprocal regulation affects neurodevelopment,neurotransmitter control,and behavioral traits,thus playing a role in the modulation of neurological diseases.The coordinated activity of the gut microbiota and the cAMP-PKA signaling pathway regulates processes such as amyloid-β protein aggregation,mitochondrial dysfunction,abnormal energy metabolism,microglial activation,oxidative stress,and neurotransmitter release,which collectively influence the onset and progression of neurological diseases.This study explores the complex interplay between the gut microbiota and cAMP-PKA signaling pathway,along with its implications for potential therapeutic interventions in neurological diseases.Recent pharmacological research has shown that restoring the balance between gut flora and cAMP-PKA signaling pathway may improve outcomes in neurodegenerative diseases and emotional disorders.This can be achieved through various methods such as dietary modifications,probiotic supplements,Chinese herbal extracts,combinations of Chinese herbs,and innovative dosage forms.These findings suggest that regulating the gut microbiota and cAMP-PKA signaling pathway may provide valuable evidence for developing novel therapeutic approaches for neurodegenerative diseases.
基金supported by the National Institutes of Health,Nos.AA025919,AA025919-03S1,and AA025919-05S1(all to RAF).
文摘Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rodents and improves memory and slows cognitive decline in patients with Alzheimer’s disease.However,the molecular pathways for exercise-induced adult hippocampal neurogenesis and improved cognition in Alzheimer’s disease are poorly understood.Recently,regulator of G protein signaling 6(RGS6)was identified as the mediator of voluntary running-induced adult hippocampal neurogenesis in mice.Here,we generated novel RGS6fl/fl;APP_(SWE) mice and used retroviral approaches to examine the impact of RGS6 deletion from dentate gyrus neuronal progenitor cells on voluntary running-induced adult hippocampal neurogenesis and cognition in an amyloid-based Alzheimer’s disease mouse model.We found that voluntary running in APP_(SWE) mice restored their hippocampal cognitive impairments to that of control mice.This cognitive rescue was abolished by RGS6 deletion in dentate gyrus neuronal progenitor cells,which also abolished running-mediated increases in adult hippocampal neurogenesis.Adult hippocampal neurogenesis was reduced in sedentary APP_(SWE) mice versus control mice,with basal adult hippocampal neurogenesis reduced by RGS6 deletion in dentate gyrus neural precursor cells.RGS6 was expressed in neurons within the dentate gyrus of patients with Alzheimer’s disease with significant loss of these RGS6-expressing neurons.Thus,RGS6 mediated voluntary running-induced rescue of impaired cognition and adult hippocampal neurogenesis in APP_(SWE) mice,identifying RGS6 in dentate gyrus neural precursor cells as a possible therapeutic target in Alzheimer’s disease.
基金supported by the National Natural Science Foundation of China(Youth Science Fund Project),No.81901292(to GC)the National Key Research and Development Program of China,No.2021YFC2502100(to GC)the National Natural Science Foundation of China,No.82071183(to ZZ).
文摘Netrin-1 and its receptors play crucial roles in inducing axonal growth and neuronal migration during neuronal development.Their profound impacts then extend into adulthood to encompass the maintenance of neuronal survival and synaptic function.Increasing amounts of evidence highlight several key points:(1)Diminished Netrin-1 levels exacerbate pathological progression in animal models of Alzheimer’s disease and Parkinson’s disease,and potentially,similar alterations occur in humans.(2)Genetic mutations of Netrin-1 receptors increase an individuals’susceptibility to neurodegenerative disorders.(3)Therapeutic approaches targeting Netrin-1 and its receptors offer the benefits of enhancing memory and motor function.(4)Netrin-1 and its receptors show genetic and epigenetic alterations in a variety of cancers.These findings provide compelling evidence that Netrin-1 and its receptors are crucial targets in neurodegenerative diseases.Through a comprehensive review of Netrin-1 signaling pathways,our objective is to uncover potential therapeutic avenues for neurodegenerative disorders.
基金supported by a grant from Ministry of Science,Technological Development and Innovation,Serbia,No.451-03-68/2022-14/200178(to NN)University of Defence,No.MFVMA/02/22-24(to MN)。
文摘An imbalance in adenosine-mediated signaling,particularly the increased A_(2A)R-mediated signaling,plays a role in the pathogenesis of Parkinson's disease.Existing therapeutic approaches fail to alter disease progression,demonstrating the need for novel approaches in PD.Repetitive transcranial magnetic stimulation is a non-invasive approach that has been shown to improve motor and non-motor symptoms of Parkinson's disease.However,the underlying mechanisms of the beneficial effects of repetitive transcranial magnetic stimulation remain unknown.The purpose of this study is to investigate the extent to which the beneficial effects of prolonged intermittent theta burst stimulation in the 6-hydroxydopamine model of experimental parkinsonism are based on modulation of adenosine-mediated signaling.Animals with unilateral 6-hydroxydopamine lesions underwent intermittent theta burst stimulation for 3 weeks and were tested for motor skills using the Rotarod test.Immunoblot,quantitative reverse transcription polymerase chain reaction,immunohistochemistry,and biochemical analysis of components of adenosine-mediated signaling were performed on the synaptosomal fraction of the lesioned caudate putamen.Prolonged intermittent theta burst stimulation improved motor symptoms in 6-hydroxydopamine-lesioned animals.A 6-hydroxydopamine lesion resulted in progressive loss of dopaminergic neurons in the caudate putamen.Treatment with intermittent theta burst stimulation began 7 days after the lesion,coinciding with the onset of motor symptoms.After treatment with prolonged intermittent theta burst stimulation,complete motor recovery was observed.This improvement was accompanied by downregulation of the e N/CD73-A_(2A)R pathway and a return to physiological levels of A_(1)R-adenosine deaminase 1 after 3 weeks of intermittent theta burst stimulation.Our results demonstrated that 6-hydroxydopamine-induced degeneration reduced the expression of A_(1)R and elevated the expression of A_(2A)R.Intermittent theta burst stimulation reversed these effects by restoring the abundances of A_(1)R and A_(2A)R to control levels.The shift in ARs expression likely restored the balance between dopamine-adenosine signaling,ultimately leading to the recovery of motor control.
基金Supported by a Grant from the Science and Technology Project ofYunnan Province(2006NG02)~~
文摘By studying principles and methods related to early-warning model of plant diseases and using PSO method, parameter optimization was conducted to backward propagation neural network, and a pre-warning model for plant diseases based on particle swarm and neural network algorithm was established. The test results showed that the construction of early-warning model is effective and feasible, which will provide a via- ble model structure to establish the effective early-warning platform.
基金supported by the National Natural Science Foundation of China (71303238)the National Science and Technology Support Plan Projects (2012BAH20B04)the compilation group of the China Agricultural Outlook Report (2015–2024)
文摘The primary goal of Chinese agricultural development is to guarantee national food security and supply of major agricultural products. Hence, the scientiifc work on agricultural monitoring and early warning as wel as agricultural outlook must be strengthened. In this study, we develop the China Agricultural Monitoring and Early-warning System (CAMES) on the basis of a comparative study of domestic and international agricultural outlook models. The system is a dynamic and multi-market partial equilibrium model that integrates biological mechanisms with economic mechanisms. This system, which includes 11 categories of 953 kinds of agricultural products, could dynamical y project agricultural market supply and demand, assess food security, and conduct scenario analysis at different spatial levels, time scale levels, and macro-micro levels. Based on the CAMES, the production, consumption, and trade of the major agricultural products in China over the next decade are projected. The fol owing conclusions are drawn:i) The production of major agricultural products wil continue to grow steadily, mainly because of the increase in yield. i ) The growth of agricultural consumption wil be slightly higher than that of agricultural production. Meanwhile, a high self-sufifciency rate is expected for cereals such as rice, wheat, and maize, with the rate being stable at around 97%. i i) Agricultural trade wil continue to thrive. The growth of soybean and milk im-ports wil slow down, but the growth of traditional agricultural exports such as vegetables and fruits is expected to continue.
基金This work was supported by the National Key Research and Development Program of China(Grant No.2018YFC0407104)the National Natural Science Foundation of China(Grants No.52079049 and 51739003)+1 种基金the Central University Basic Research Project(Grant No.B200202160)the Water Science Project of Xinjiang(Grant No.YF 2020-05).
文摘The mechanical parameters of materials in a dam body and dam foundation tend to change when dams are reinforced in aging processes.It is important to use an early-warning index to reflect the safety status of dams,particularly of heightened projects in the impoundment period.Herein,a new method for monitoring the safety status of heightened dams is proposed based on the deformation monitoring data of a dam structure,a statistical model,and finite-element numerical simulation.First,a fast optimization inversion method for estimation of dam mechanical parameters was developed,which used the water pressure component extracted from a statistical model,an improved inversion objective function,and a genetic optimization iterative algorithm.Then,a finite element model of a heightened concrete gravity dam was established,and the deformation behavior of the dam with rising water levels in the impoundment period was simulated.Subsequently,mechanical parameters of aged dam parts were calculated using the fast optimization inversion method with simulated deformation and the water pressure deformation component obtained by the statistical model under the same conditions of water pressure change.Finally,a new earlywarning index of dam deformation was constructed by means of the forward-simulated deformation and other components of the statistical model.The early-warning index is useful for forecasting dam deformation under different water levels,especially high water levels.
基金Project 70533050 supported by the National Natural Science Foundation of China
文摘The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.
文摘By analyzing the heavy fog data in Chizhou City in recent 50 years(1959-2007),the general rules of meteorological elements variations were found when the heavy fog happened.The meteorological elements included the temperature,humidity,wind direction,wind speed,air pressure and so on.The conceptual models of high-altitude and ground situation were established when the heavy fog happened in Chizhou City.Based on considering sufficiently the special geographical environment in Chizhou City,we found the key factors which affected the local heavy fog via the relative analyses.By using the statistical forecast methods which included the second-level judgment method and regression method of event probability and so on,the forecast mode equation of heavy fog was established.Moreover,the objective forecast system of heavy fog in Chizhou City was also manufactured.It provided the basis and platform which could be referred for the heavy fog forecast,service and the release of early-warning signal.
文摘The most common method used to describe earthquake activity is based on the changes in physical parameters of the earth's surface such as displacement of active fault and seismic wave.However,such approach is not successful in forecasting the movement behaviors of faults.In the present study,a new mechanical model of fault activity,considering the shear strength on the fault plane and the influence of the resistance force,is established based on the occurrence condition of earthquake.A remote real-time monitoring system is correspondingly developed to obtain the changes in mechanical components within fault.Taking into consideration the local geological conditions and the history of fault activity in Zhangjiakou of China,an active fault exposed in the region of Zhangjiakou is selected to be directly monitored by the real-time monitoring technique.A thorough investigation on local fault structures results in the selection of two suitable sites for monitoring potential active tectonic movements of Zhangjiakou fault.Two monitoring curves of shear strength,recorded during a monitoring period of 6 months,turn out to be steady,which indicates that the potential seismic activities hardly occur in the adjacent region in the near future.This monitoring technique can be used for early-warning prediction of the movement of active fault,and can help to further gain an insight into the interaction between fault activity and relevant mechanisms.
文摘Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and DEA model, whose steps were put forward. On the basis of standard risk early-warning DEA model of natural disasters, weight coefficient of risk early-warning factors was determined with Information Entropy method, which improved standard risk early-warning DEA model with non-Archimedean infinitesimal, and established risk early-warning preference DEA model based on integrated entropy weight and DEA Model. Finally, model was applied into landslide risk early-warning case in earthquake-damaged emergency process on slope engineering, which exemplified the outcome could reflect more risk information than the method of standard DEA model, and reflected the rationality, feasibility, and impersonality, revealing its better ability on comprehensive safety and structure risk.
文摘The period economic fluctuation is vital for an enterprise to exist and further develop, it directly affect the enterprise financial health. So, it is significant to build up financial early-warning index and measure the warning condition that the enterprise faces and take the effective measures to eliminate. We criticize Altman’sZ calculating model and build up some new indexes for enterprise financial early-warning condition measuring and making sound decision.
基金Fund by the Ministry of Science and Technology, No.2002BA516A17 Foundation of Chinese Academy of Forestry Science, No.200114
文摘According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN) real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system’s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.
文摘The meteorological early-warning loudspeaker is a specific initiative for the meteorological departments to address the issues concerning issues concerning agriculture,countryside and farmers.Its significance is that it can promptly deliver the early-warning information concerning some meteorological disasters(such as torrential rains,typhoons,cold wave,hail)to the areas affected,so as to provide reference and protection for agricultural production and effectively reduce the loss of agricultural producers.Up to now,the meteorological early-warning loudspeakers in Benxi have covered the villages.However,due to irregular occurrence of meteorological disasters,the listeners will turn off the information receivers of meteorological early-warning loudspeakers when they fail to receive meteorological information for a long time,so that the users can not promptly know the early-warning information regarding some sudden meteorological disasters.In view of this,the meteorological departments have introduced a series of management measures,such as the daily use of loudspeakers to publish weather forecast information,aimed at improving the online rate and usage rate of meteorological loudspeakers.And the management platform for online rate of meteorological early-warning loudspeakers is an important part of the management system.
基金This work is supported by the National Natural Science Foundation of China(Nos.72071150,71871174).
文摘As the banking industry gradually steps into the digital era of Bank 4.0,business competition is becoming increasingly fierce,and banks are also facing the problem of massive customer churn.To better maintain their customer resources,it is crucial for banks to accurately predict customers with a tendency to churn.Aiming at the typical binary classification problem like customer churn,this paper establishes an early-warning model for credit card customer churn.That is a dual search algorithm named GSAIBAS by incorporating Golden Sine Algorithm(GSA)and an Improved Beetle Antennae Search(IBAS)is proposed to optimize the parameters of the CatBoost algorithm,which forms the GSAIBAS-CatBoost model.Especially,considering that the BAS algorithm has simple parameters and is easy to fall into local optimum,the Sigmoid nonlinear convergence factor and the lane flight equation are introduced to adjust the fixed step size of beetle.Then this improved BAS algorithm with variable step size is fused with the GSA to form a GSAIBAS algorithm which can achieve dual optimization.Moreover,an empirical analysis is made according to the data set of credit card customers from Analyttica official platform.The empirical results show that the values of Area Under Curve(AUC)and recall of the proposedmodel in this paper reach 96.15%and 95.56%,respectively,which are significantly better than the other 9 common machine learning models.Compared with several existing optimization algorithms,GSAIBAS algorithm has higher precision in the parameter optimization for CatBoost.Combined with two other customer churn data sets on Kaggle data platform,it is further verified that the model proposed in this paper is also valid and feasible.
基金This work was supported by the National Key R&D Program of China(Nos.2023YFA1606403 and 2023YFE0101600)the National Natural Science Foundation of China(Nos.12027809,11961141003,U1967201,11875073 and 11875074).
文摘A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.
基金Sponsored by Excellent Young Scholars Research Fund of Beijing Institute of Technology (c2007Y0820)Program for New Century Excellent Talents in University (NCET)"985" Philosophy and Social Science Innovation Base of the Ministry of Education(107008200400024)
文摘Relying on the advanced information technologies, such as information monitoring, data mining, natural language processing etc., the dynamic technology early-warning system is constructed. The system consists of technology information automatic retrieval, technology information monitoring, technology threat evaluation, and crisis response and management subsystem, which implements uninterrupted dynamic monitoring, trace and crisis early-warning to the specific technology. Empirical study testifies that the system improves the accuracy, timeliness and reliability of technology early-warning.