Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
A previous paper showed that the real numbers between 0 and 1 could be represented by an infinite tree structure, called the ‘infinity tree’, which contains only a countably infinite number of nodes and arcs. This p...A previous paper showed that the real numbers between 0 and 1 could be represented by an infinite tree structure, called the ‘infinity tree’, which contains only a countably infinite number of nodes and arcs. This paper discusses how a finite-state Turing machine could, in a countably infinite number of state transitions, write all the infinite paths in the infinity tree to a countably infinite tape. Hence it is argued that the real numbers in the interval [0, 1] are countably infinite in a non-Cantorian theory of infinity based on Turing machines using countably infinite space and time. In this theory, Cantor’s Continuum Hypothesis can also be proved. And in this theory, it follows that the power set of the natural numbers P(ℕ) is countably infinite, which contradicts the claim of Cantor’s Theorem for the natural numbers. However, this paper does not claim there is an error in Cantor’s arguments that [0, 1] is uncountably infinite. Rather, this paper considers the situation as a paradox, resulting from different choices about how to represent and count the continuum of real numbers.展开更多
This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We exa...This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We examine the contemporaneous relationships using correlation coefficient analysis,and find apparent differences between the information flow-return volatility relationship and the information flowtrading volume relationship.The empirical evidence contradicts the mixture of distribution hypothesis(MDH)and suggests that the rate of information flow distinctly affects trading volume and volatility.We conducted linear and nonlinear Granger causality tests to explore the sequential information arrival hypothesis(SIAH).The empirical results prove that a lead-lag linear and nonlinear causality exists between the information flow and return volatility of commodity futures,which is consistent with SIAH.In other words,a partial equilibrium exists before reaching the ultimate equilibrium when the new information arrives in the market.Finally,these findings are robust to alternative measurement of return volatility and subperiod analysis.Our findings reject the MDH and support the SIAH in the context of Chinese commodity futures.展开更多
This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerge...This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.展开更多
This paper attempts to form a bridge between a sum of the divisors function and the gamma function, proposing a novel approach that could have significant implications for classical problems in number theory, specific...This paper attempts to form a bridge between a sum of the divisors function and the gamma function, proposing a novel approach that could have significant implications for classical problems in number theory, specifically the Robin inequality and the Riemann hypothesis. The exploration of using invariant properties of these functions to derive insights into twin primes and sequential primes is a potentially innovative concept that deserves careful consideration by the mathematical community.展开更多
Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class at...Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.展开更多
This paper explores the applicability of the generalized wave impedance hypothesis in split Hopkinson pressure bar(SHPB)experiments,particularly under non-ideal conditions.The study investigates the effects of changes...This paper explores the applicability of the generalized wave impedance hypothesis in split Hopkinson pressure bar(SHPB)experiments,particularly under non-ideal conditions.The study investigates the effects of changes in wave impedance ratio and cross-sectional area ratio on the dynamic response of materials at high strain rates.Through theoretical analysis and numerical simulation,the impact of different wave impedance and cross-sectional area ratios on stress wave propagation characteristics is discussed in detail.It is found that when the cross-sections of two bars differ,shear strain occurs at the abrupt cross-section,leading to waveform distortion in the transmitted and reflected waves.The force balance condition does not always align with the momentum conservation theorem,and only when the three waveforms and wavelengths are completely consistent do they align.The research shows that when the wave impedance ratio and cross-sectional area ratio are within a specific range,the generalized wave impedance hypothesis can accurately predict changes in Young’s modulus and density.Additionally,the study extends the exploration to key factors such as wave impedance ratio,wave speed,Young’s modulus,density,and area ratio.展开更多
BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To ...BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.展开更多
In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapi...In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.展开更多
Dilatancy is referred to the phenomenon of volume increase that occurs when a material is deformed.Dilatancy theory originated in geomechanics for the study of the behavior of granular materials.Later it is expanded t...Dilatancy is referred to the phenomenon of volume increase that occurs when a material is deformed.Dilatancy theory originated in geomechanics for the study of the behavior of granular materials.Later it is expanded to the case of more brittle materials like rocks when it is subjected to the load of varying effective stress and starts to crack and deform,then named the dilatancy-diffusion hypothesis.This hypothesis was developed to explain the changes in rock volume and pore pressure that occur prior to and during fault slip,which can influence earthquake dynamics.Dilatancy-fluid diffusion is a significant concept in understanding the seismogenic process and has served as the major theoretical pillar for earthquake prediction by its classic definition.This paper starts with the recount of fundamental laboratory experiments on granular materials and rocks,then conducts review and examination of the history for using the dilatancy-diffusion hypothesis to interpret the‘prediction’of the 1975 Haicheng Earthquake and other events.The Haicheng Earthquake is the first significant event to be interpreted with the dilatancy-diffusion hypothesis in the world.As one pivotal figure in the development of the dilatancy-diffusion hypothesis for earthquake prediction Professor Amos Nur of Stanford University worked tirelessly to attract societal attention to this important scientific and humanistic issue.As a deterministic physical model the dilatancy-diffusion hypothesis intrinsically bears the deficit to interpret the stochastic seismogenic process.With the emergence of deep learning and its successful applications to many science and technology fields,we may see a possibility to overcome the shortcoming of the current state of the theory with the addition of empirical statistics to push the operational earthquake forecasting approach with the addition of the physicallyinformed neural networks which adopt the dilatancy-diffusion hypothesis as one of its embedded physical relations,to uplift the seismic risk reduction to a new level for saving lives and reducing the losses.展开更多
Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose...Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.展开更多
Aiming at gradually developing and perfecting the task-based teaching method, the essay, with enlightment from the Krashen＇s Input Hypothesis, discusses some issues about input, output, activities and teacher＇s role...Aiming at gradually developing and perfecting the task-based teaching method, the essay, with enlightment from the Krashen＇s Input Hypothesis, discusses some issues about input, output, activities and teacher＇s role in this method.展开更多
Aim To study the rules governing pressure distribution of traveling charge under the condition of Lagrange hypothesis. Methods\ The study is based on the laws of conservation of momentum and energy. Results\ The gas ...Aim To study the rules governing pressure distribution of traveling charge under the condition of Lagrange hypothesis. Methods\ The study is based on the laws of conservation of momentum and energy. Results\ The gas flow velocity distribution formula at the back of a projectile and the momentum equation of a traveling charge are deduced, and rules governing their pressure distribution under the Lagrange hypothesis conditions are established. The pressure distribution of a traveling charge is compared with that of a conventional charge. Conclusion\ The pressure distribution in the bore of a traveling charge can be accurately predicted. A parabolic pressure distribution type is revealed.展开更多
A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an i...A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.展开更多
“Sapir-Whorf hypothesis"holds that human thoughts are shaped by their native languages,and speakers of different languages think differently relevantly.The hypothesis is controversial partly because it seems to ...“Sapir-Whorf hypothesis"holds that human thoughts are shaped by their native languages,and speakers of different languages think differently relevantly.The hypothesis is controversial partly because it seems to deny the possibility of a general principle for human cognition,and partly because some findings taken to support it have not reliably replicated.The author argued that considering this hypothesis through the lens of probabilistic inference has the potential to figure out both issues,at least with respect to certain prominent findings in the two languages—Chinese and English.After exploring on the inner relationship among language,thought and culture with the comparison between English and Chinese based on a series of examples including“numbers,Wuhan dialect and some different understandings of idioms”,the author made an inference that language can somewhat affect human thought under the different culture contexts.Besides,it also provides some reference for educators to take in-depth studies on the relationship among language,thought and culture,which is vitally significant for ESL educators and learners.展开更多
Sapir-Whorf hypothesis has its implication in translation studies. Each language is a peculiar whole. It is a product, even an expression, of the spiritual personality and the cultural particularity. Translation is a ...Sapir-Whorf hypothesis has its implication in translation studies. Each language is a peculiar whole. It is a product, even an expression, of the spiritual personality and the cultural particularity. Translation is a kind of interlingual and intercultural communication. It involves not only the transference from one language into another, but a whole set of extra-linguistic criteria. In translating we are always crossing a greater or lesser barrier or divide.展开更多
The researches on Critical Period Hypothesis(CPH) aims to explain the importance of the age factor in the process of learning a second language.In this essay,a critical review of the theoretical issues and empirical r...The researches on Critical Period Hypothesis(CPH) aims to explain the importance of the age factor in the process of learning a second language.In this essay,a critical review of the theoretical issues and empirical research on the CPH will spread out.Meanwhile,the discussion of implication and limitation of the CPH research will be concerned as well.展开更多
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
文摘A previous paper showed that the real numbers between 0 and 1 could be represented by an infinite tree structure, called the ‘infinity tree’, which contains only a countably infinite number of nodes and arcs. This paper discusses how a finite-state Turing machine could, in a countably infinite number of state transitions, write all the infinite paths in the infinity tree to a countably infinite tape. Hence it is argued that the real numbers in the interval [0, 1] are countably infinite in a non-Cantorian theory of infinity based on Turing machines using countably infinite space and time. In this theory, Cantor’s Continuum Hypothesis can also be proved. And in this theory, it follows that the power set of the natural numbers P(ℕ) is countably infinite, which contradicts the claim of Cantor’s Theorem for the natural numbers. However, this paper does not claim there is an error in Cantor’s arguments that [0, 1] is uncountably infinite. Rather, this paper considers the situation as a paradox, resulting from different choices about how to represent and count the continuum of real numbers.
基金supported by the National Social Science Fund of China(24CGL027)the National Natural Science Foundation of China(72101009,72141304,72201122)National Key Research and Development Program of China(2022YFC3303304).
文摘This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses.We examine the contemporaneous relationships using correlation coefficient analysis,and find apparent differences between the information flow-return volatility relationship and the information flowtrading volume relationship.The empirical evidence contradicts the mixture of distribution hypothesis(MDH)and suggests that the rate of information flow distinctly affects trading volume and volatility.We conducted linear and nonlinear Granger causality tests to explore the sequential information arrival hypothesis(SIAH).The empirical results prove that a lead-lag linear and nonlinear causality exists between the information flow and return volatility of commodity futures,which is consistent with SIAH.In other words,a partial equilibrium exists before reaching the ultimate equilibrium when the new information arrives in the market.Finally,these findings are robust to alternative measurement of return volatility and subperiod analysis.Our findings reject the MDH and support the SIAH in the context of Chinese commodity futures.
基金supported by MHRD as researcher C.K.Neog received the MHRD Institute GATE scholarship from Govt.of India.
文摘This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.
文摘This paper attempts to form a bridge between a sum of the divisors function and the gamma function, proposing a novel approach that could have significant implications for classical problems in number theory, specifically the Robin inequality and the Riemann hypothesis. The exploration of using invariant properties of these functions to derive insights into twin primes and sequential primes is a potentially innovative concept that deserves careful consideration by the mathematical community.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)—Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156334)in part by Liaoning Province Nature Fund Project(2024-BSLH-214).
文摘Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2341244,12172179,11772160,and 12202207)China Postdoctoral Science Foundation(Grant No.2022M711623)+3 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20220968)Open Funds for Key Laboratory of Impact and Safety Engineering(Ningbo University)Ministry of Education(Grant No.CJ202201)Open Funds for Shock and Vibration of Engineering Materials and Structures Key Laboratory of Sichuan Province(Grant No.22kfgk03).
文摘This paper explores the applicability of the generalized wave impedance hypothesis in split Hopkinson pressure bar(SHPB)experiments,particularly under non-ideal conditions.The study investigates the effects of changes in wave impedance ratio and cross-sectional area ratio on the dynamic response of materials at high strain rates.Through theoretical analysis and numerical simulation,the impact of different wave impedance and cross-sectional area ratios on stress wave propagation characteristics is discussed in detail.It is found that when the cross-sections of two bars differ,shear strain occurs at the abrupt cross-section,leading to waveform distortion in the transmitted and reflected waves.The force balance condition does not always align with the momentum conservation theorem,and only when the three waveforms and wavelengths are completely consistent do they align.The research shows that when the wave impedance ratio and cross-sectional area ratio are within a specific range,the generalized wave impedance hypothesis can accurately predict changes in Young’s modulus and density.Additionally,the study extends the exploration to key factors such as wave impedance ratio,wave speed,Young’s modulus,density,and area ratio.
基金Supported by Talent Scientific Research Start-up Foundation of Wannan Medical College,No.WYRCQD2023045.
文摘BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.
基金supported by the Basic Scientific Research Business Fund Project of Higher Education Institutions in Heilongjiang Province(145409601)the First Batch of Experimental Teaching and Teaching Laboratory Construction Research Projects in Heilongjiang Province(SJGZ20240038).
文摘In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.
基金sponsored by the National Research Foundation of Korea(RS-2023-00220913).
文摘Dilatancy is referred to the phenomenon of volume increase that occurs when a material is deformed.Dilatancy theory originated in geomechanics for the study of the behavior of granular materials.Later it is expanded to the case of more brittle materials like rocks when it is subjected to the load of varying effective stress and starts to crack and deform,then named the dilatancy-diffusion hypothesis.This hypothesis was developed to explain the changes in rock volume and pore pressure that occur prior to and during fault slip,which can influence earthquake dynamics.Dilatancy-fluid diffusion is a significant concept in understanding the seismogenic process and has served as the major theoretical pillar for earthquake prediction by its classic definition.This paper starts with the recount of fundamental laboratory experiments on granular materials and rocks,then conducts review and examination of the history for using the dilatancy-diffusion hypothesis to interpret the‘prediction’of the 1975 Haicheng Earthquake and other events.The Haicheng Earthquake is the first significant event to be interpreted with the dilatancy-diffusion hypothesis in the world.As one pivotal figure in the development of the dilatancy-diffusion hypothesis for earthquake prediction Professor Amos Nur of Stanford University worked tirelessly to attract societal attention to this important scientific and humanistic issue.As a deterministic physical model the dilatancy-diffusion hypothesis intrinsically bears the deficit to interpret the stochastic seismogenic process.With the emergence of deep learning and its successful applications to many science and technology fields,we may see a possibility to overcome the shortcoming of the current state of the theory with the addition of empirical statistics to push the operational earthquake forecasting approach with the addition of the physicallyinformed neural networks which adopt the dilatancy-diffusion hypothesis as one of its embedded physical relations,to uplift the seismic risk reduction to a new level for saving lives and reducing the losses.
基金Supported by the National Natural Science Foundation of China(Grant No.40674063)National Hi-tech Research and Development Program of China(863Program)(Grant No.2006AA09Z311)
文摘Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.
文摘Aiming at gradually developing and perfecting the task-based teaching method, the essay, with enlightment from the Krashen＇s Input Hypothesis, discusses some issues about input, output, activities and teacher＇s role in this method.
文摘Aim To study the rules governing pressure distribution of traveling charge under the condition of Lagrange hypothesis. Methods\ The study is based on the laws of conservation of momentum and energy. Results\ The gas flow velocity distribution formula at the back of a projectile and the momentum equation of a traveling charge are deduced, and rules governing their pressure distribution under the Lagrange hypothesis conditions are established. The pressure distribution of a traveling charge is compared with that of a conventional charge. Conclusion\ The pressure distribution in the bore of a traveling charge can be accurately predicted. A parabolic pressure distribution type is revealed.
基金国家自然科学基金面上项目“基于高压人群身心健康的工作环境绿色空间体系研究”(编号51978364)国家自然科学基金青年科学基金项目“北京地区城市森林疗养空间特征识别及健康效益定量评价”(编号51908310)Tsinghua-Toyota Joint Research Institute Cross discipline Program共同资助。
文摘A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.
文摘“Sapir-Whorf hypothesis"holds that human thoughts are shaped by their native languages,and speakers of different languages think differently relevantly.The hypothesis is controversial partly because it seems to deny the possibility of a general principle for human cognition,and partly because some findings taken to support it have not reliably replicated.The author argued that considering this hypothesis through the lens of probabilistic inference has the potential to figure out both issues,at least with respect to certain prominent findings in the two languages—Chinese and English.After exploring on the inner relationship among language,thought and culture with the comparison between English and Chinese based on a series of examples including“numbers,Wuhan dialect and some different understandings of idioms”,the author made an inference that language can somewhat affect human thought under the different culture contexts.Besides,it also provides some reference for educators to take in-depth studies on the relationship among language,thought and culture,which is vitally significant for ESL educators and learners.
文摘Sapir-Whorf hypothesis has its implication in translation studies. Each language is a peculiar whole. It is a product, even an expression, of the spiritual personality and the cultural particularity. Translation is a kind of interlingual and intercultural communication. It involves not only the transference from one language into another, but a whole set of extra-linguistic criteria. In translating we are always crossing a greater or lesser barrier or divide.
文摘The researches on Critical Period Hypothesis(CPH) aims to explain the importance of the age factor in the process of learning a second language.In this essay,a critical review of the theoretical issues and empirical research on the CPH will spread out.Meanwhile,the discussion of implication and limitation of the CPH research will be concerned as well.
