Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autoph...Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autophagy is an important process for maintaining cellular homeostasis,and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors.In contrast to targeting protein activity,intervention with proteinprotein interaction(PPI)can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways.Methods:Here,we employed Naive Bayes,Decision Tree,and k-Nearest Neighbors to elucidate the complex PPI network associated with autophagy in TNBC,aiming to uncover novel therapeutic targets.Meanwhile,the candidate proteins interacting with Beclin 2 were initially screened in MDA-MB-231 cells using Beclin 2 as bait protein by immunoprecipitation-mass spectrometry assay,and the interaction relationship was verified by molecular docking and CO-IP experiments after intersection.Colony formation,cellular immunofluorescence,cell scratch and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)tests were used to predict the clinical therapeutic effects of manipulating candidate PPI.Results:By developing three PPI classification models and analyzing over 13,000 datasets,we identified 3733 previously unknown autophagy-related PPIs.Our network analysis revealed the central role of Beclin 2 in autophagy regulation,uncovering its interactions with 39 newly identified proteins.Notably,the CO-IP studies identified the substantial interaction between Beclin 2 and Ubiquilin 1,which was anticipated by our model and discovered in immunoprecipitation-mass spectrometry assay results.Subsequently,in vitro investigations showed that overexpressing Beclin 2 increased Ubiquilin 1,promoted autophagy-dependent cell death,and inhibited proliferation and metastasis in MDA-MB-231 cells.Conclusions:This study not only enhances our understanding of autophagy regulation in TNBC but also identifies the Beclin 2-Ubiquilin 1 axis as a promising target for precision therapy.These findings open new avenues for drug discovery and offer inspiration for more effective treatments for this aggressive cancer subtype.展开更多
Thermally chargeable supercapacitors(TCSCs)have unique advantages in the collection,conversion,and storage of thermal energy,contributing to the development of new strategies for thermal energy utilization.2D MXene ma...Thermally chargeable supercapacitors(TCSCs)have unique advantages in the collection,conversion,and storage of thermal energy,contributing to the development of new strategies for thermal energy utilization.2D MXene materials are predicted to be highly promising new thermoelectric materials.Here,we report a self-assembled flexible Ti_(3)C_(2)T_(x) MXenebased TCSC device,using prepared Ti_(3)C_(2)T_(x) MXene as the capacitor electrode and a NaClO_(4)/PEO gel as the electrolyte.We also explore the working mechanism of the TCSCs.The fabricated Ti_(3)C_(2)T_(x)-based TCSCs exhibit an excellent Seebeck coefficient of 11.8 mV∙K^(−1) on average and maintain good cycling stability under various temperature differences.Demonstrations of multiple practical applications show that Ti_(3)C_(2)T_(x) MXene-based TCSC devices are excellent candidates for self-powered integrated electronic devices.展开更多
Micro-expressions,fleeting involuntary facial cues lasting under half a second,reveal genuine emotions and are valuable in clinical diagnosis and psychotherapy.Real-time recognition on resource-constrained embedded de...Micro-expressions,fleeting involuntary facial cues lasting under half a second,reveal genuine emotions and are valuable in clinical diagnosis and psychotherapy.Real-time recognition on resource-constrained embedded devices remains challenging,as current methods struggle to balance performance and efficiency.This study introduces a semi-lightweight multifunctional network that enhances real-time deployment and accuracy.Unlike prior simplistic feature fusion techniques,our novel multi-feature fusion strategy leverages temporal,spatial,and differential features to better capture dynamic changes.Enhanced by Residual Network(ResNet)architecture with channel and spatial attention mechanisms,the model improves feature representation while maintaining a lightweight design.Evaluations on SMIC,CASME II,SAMM,and their composite dataset show superior performance in Unweighted F1 Score(UF1)and Unweighted Average Recall(UAR),alongside faster detection speeds compared to existing algorithms.展开更多
A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information...A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information is available on the optimized water and nitrogen management for yield formation,especially the grain-filling process,under HLSC mode.A three-year field experiment with four nitrogen rates and three irrigation rates of HLSC was conducted to reveal the response of grain-filling parameters,grain weight percentage of spike weight(GPS),spike moisture content(SMC),and winter wheat yield to water and nitrogen rates.The four nitrogen rates were N1(360 kg ha^(-1) pure N),N2(300 kg ha^(-1) pure N),N3(240 kg ha^(-1) pure N),and N4(180 kg ha^(-1) pure N),respectively,and the three irrigation quotas were W1(120 mm),W2(90 mm),and W3(60 mm),respectively.Results showed that the determinate growth function generally performed well in simulating the temporal dynamics of grain weight(0.989<R^(2)<0.999,where R2 is the determination coefficient).The occurrence time of maximum filling rate(T_(max))and active grain-filling period(AGP)increased with the increase in the water or nitrogen rate,whereas the average grain-filling rate(G_(mean))had a decreasing trend.The final 1,000-grain weight(FTGW)increased and then decreased with the increase in the nitrogen rates and increased with the increase in the irrigation rates.The GPS and SMC had a highly significant quadratic polynomial relationship with grain weight and days after anthesis.Nitrogen,irrigation,and year significantly affected the T_(max),AGP,G_(mean),and FTGW.Particularly,the AGP and FTGW were insignificantly different between high seedbed(HLSC-H)and low seedbed(HLSC-L)across the water and nitrogen levels.Moreover,the moderate water and nitrogen supply was more beneficial for grain yield,as well as for spike number and grain number per hectare.The principal component analysis indicated that combining 240-300 kg N ha^(-1) and 90^(-1)20 mm irrigation quota could improve grain-filling efficiency and yield for the HLSC-cultivated winter wheat.展开更多
To reveal the relationship between a weakening buffer operator and strengthening buffer operator, the traditional integer order buffer operator is extended to one that is fractional order. Fractional order buffer oper...To reveal the relationship between a weakening buffer operator and strengthening buffer operator, the traditional integer order buffer operator is extended to one that is fractional order. Fractional order buffer operator not only can generalize the weakening buffer operator and the strengthening buffer operator, but also results in small adjustments of the buffer effect.The effectiveness of the grey model(GM(1,1)) with the fractional order buffer operator is validated by six cases.展开更多
Solar radiation is an important parameter in the fields of computer modeling,engineering technology and energy development.This paper evaluated the ability of three machine learning models,i.e.,Extreme Gradient Boosti...Solar radiation is an important parameter in the fields of computer modeling,engineering technology and energy development.This paper evaluated the ability of three machine learning models,i.e.,Extreme Gradient Boosting(XGBoost),Support Vector Machine(SVM)and Multivariate Adaptive Regression Splines(MARS),to estimate the daily diffuse solar radiation(Rd).The regular meteorological data of 1966-2015 at five stations in China were taken as the input parameters(including mean average temperature(Ta),theoretical sunshine duration(N),actual sunshine duration(n),daily average air relative humidity(RH),and extra-terrestrial solar radiation(Ra)).And their estimation accuracies were subjected to comparative analysis.The three models were first trained using meteorological data from 1966 to 2000.Then,the 2001-2015 data was used to test the trained machine learning model.The results show that the XGBoost had better accuracy than the other two models in coefficient of determination(R2),root mean square error(RMSE),mean bias error(MBE)and normalized root mean square error(NRMSE).The MARS performed better in the training phase than the testing phase,but became less accurate in the testing phase,with the R2 value falling by 2.7-16.9%on average.By contrast,the R2 values of SVM and XGBoost increased by 2.9-12.2%and 1.9-14.3%,respectively.Despite trailing slightly behind the SVM at the Beijing station,the XGBoost showed good performance at the rest of the stations in the two phases.In the training phase,the accuracy growth is small but observable.In addition,the XGBoost had a slightly lower RMSE than the SVM,a signal of its edge in stability.Therefore,the three machine learning models can estimate the daily Rd based on local inputs and the XGBoost stands out for its excellent performance and stability.展开更多
It is important for regional water resources management to know the agricultural water consumption information several months in advance.Forecasting reference evapotranspiration(ET_(0))in the next few months is import...It is important for regional water resources management to know the agricultural water consumption information several months in advance.Forecasting reference evapotranspiration(ET_(0))in the next few months is important for irrigation and reservoir management.Studies on forecasting of multiple-month ahead ET_(0) using machine learning models have not been reported yet.Besides,machine learning models such as the XGBoost model has multiple parameters that need to be tuned,and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution.This study investigated the performance of the hybrid extreme gradient boosting(XGBoost)model coupled with the Grey Wolf Optimizer(GWO)algorithm for forecasting multi-step ahead ET_(0)(1-3 months ahead),compared with three conventional machine learning models,i.e.,standalone XGBoost,multi-layer perceptron(MLP)and M5 model tree(M5)models in the subtropical zone of China.The results showed that theGWO-XGB model generally performed better than the other three machine learning models in forecasting 1-3 months ahead ET_(0),followed by the XGB,M5 and MLP models with very small differences among the three models.The GWO-XGB model performed best in autumn,while the MLP model performed slightly better than the other three models in summer.It is thus suggested to apply the MLP model for ET_(0) forecasting in summer but use the GWO-XGB model in other seasons.展开更多
In this paper, we studied a non-autonomous predator-prey system where the prey dispersal in a two-patch environment. With the help of a continuation theorem based on coincidence degree theory, we establish sufficient ...In this paper, we studied a non-autonomous predator-prey system where the prey dispersal in a two-patch environment. With the help of a continuation theorem based on coincidence degree theory, we establish sufficient conditions for the existence of positive periodic solutions. Finally, we give numerical analysis to show the effectiveness of our theoretical results.展开更多
Cancer reprogramming is an important facilitator of cancer development and survival,with tumor cells exhibiting a preference for aerobic glycolysis beyond oxidative phosphorylation,even under sufficient oxygen supply ...Cancer reprogramming is an important facilitator of cancer development and survival,with tumor cells exhibiting a preference for aerobic glycolysis beyond oxidative phosphorylation,even under sufficient oxygen supply condition.This metabolic alteration,known as the Warburg effect,serves as a significant indicator of malignant tumor transformation.The Warburg effect primarily impacts cancer occurrence by influencing the aerobic glycolysis pathway in cancer cells.Key enzymes involved in this process include glucose transporters(GLUTs),HKs,PFKs,LDHs,and PKM2.Moreover,the expression of transcriptional regulatory factors and proteins,such as FOXM1,p53,NF-κB,HIF1a,and c-Myc,can also influence cancer progression.Furthermore,lncRNAs,miRNAs,and circular RNAs play a vital role in directly regulating the Warburg effect.Additionally,gene mutations,tumor microenvironment remodeling,and immune system interactions are closely associated with the Warburg effect.Notably,the development of drugs targeting the Warburg effect has exhibited promising potential in tumor treatment.This comprehensive review presents novel directions and approaches for the early diagnosis and treatment of cancer patients by conducting in-depth research and summarizing the bright prospects of targeting the Warburg effect in cancer.展开更多
This study investigates how the events of deception attacks are distributed during the fusion of multi-sensor nonlinear systems.First,a deception attack with limited energy(DALE)is introduced under the framework of di...This study investigates how the events of deception attacks are distributed during the fusion of multi-sensor nonlinear systems.First,a deception attack with limited energy(DALE)is introduced under the framework of distributed extended Kalman consensus filtering(DEKCF).Next,a hypothesis testing-based mechanism to detect the abnormal data generated by DALE,in the presence of the error term caused by the linearization of the nonlinear system,is established.Once the DALE is detected,a new rectification strategy can be triggered to recalibrate the abnormal data,restoring it to its normal state.Then,an attack-resilient DEKCF(AR-DEKCF)algorithm is proposed,and its fusion estimation errors are demonstrated to satisfy the mean square exponential boundedness performance,under appropriate conditions.Finally,the effectiveness of the AR-DEKCF algorithm is confirmed through simulations involving multi-unmanned aerial vehicle(multi-UAV)tracking problems.展开更多
Detailed routing has become much challenging in modern circuit designs due to the extreme scaling of chip size and the complicated design rules.In this paper,we give an effective algorithm for detailed routing conside...Detailed routing has become much challenging in modern circuit designs due to the extreme scaling of chip size and the complicated design rules.In this paper,we give an effective algorithm for detailed routing considering advanced technology nodes.First,we present a valid pin-access candidates generation technology for handling complex pin shapes.Then,we propose a tree-based nets components selection algorithm to decide connecting order for multiple nets components.Finally,combined with global routing results and advanced technology nodes,an initial routing results optimization algorithm is presented to achieve the final detailed routing results.Experimental results on industry benchmarks show that,our proposed algorithm not only achieves 100%routability on real industrial cases in a reasonable runtime,but also optimizes total wirelength,total vias and other advanced technology nodes simultaneously.展开更多
基金the National Natural Science Foundation of China(Nos.22307009,82374155,82073997,82104376)the Sichuan Science and Technology Program(Nos.2023NSFSC1108,2024NSFTD0023)+1 种基金the Postdoctoral Research Project of Sichuan Provincethe Xinglin Scholar Research Promotion Project of Chengdu University of TCM.
文摘Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autophagy is an important process for maintaining cellular homeostasis,and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors.In contrast to targeting protein activity,intervention with proteinprotein interaction(PPI)can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways.Methods:Here,we employed Naive Bayes,Decision Tree,and k-Nearest Neighbors to elucidate the complex PPI network associated with autophagy in TNBC,aiming to uncover novel therapeutic targets.Meanwhile,the candidate proteins interacting with Beclin 2 were initially screened in MDA-MB-231 cells using Beclin 2 as bait protein by immunoprecipitation-mass spectrometry assay,and the interaction relationship was verified by molecular docking and CO-IP experiments after intersection.Colony formation,cellular immunofluorescence,cell scratch and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)tests were used to predict the clinical therapeutic effects of manipulating candidate PPI.Results:By developing three PPI classification models and analyzing over 13,000 datasets,we identified 3733 previously unknown autophagy-related PPIs.Our network analysis revealed the central role of Beclin 2 in autophagy regulation,uncovering its interactions with 39 newly identified proteins.Notably,the CO-IP studies identified the substantial interaction between Beclin 2 and Ubiquilin 1,which was anticipated by our model and discovered in immunoprecipitation-mass spectrometry assay results.Subsequently,in vitro investigations showed that overexpressing Beclin 2 increased Ubiquilin 1,promoted autophagy-dependent cell death,and inhibited proliferation and metastasis in MDA-MB-231 cells.Conclusions:This study not only enhances our understanding of autophagy regulation in TNBC but also identifies the Beclin 2-Ubiquilin 1 axis as a promising target for precision therapy.These findings open new avenues for drug discovery and offer inspiration for more effective treatments for this aggressive cancer subtype.
基金supported by National Natural Science Foundation of China(62474019)Beijing Natural Science Foundation(L223006).
文摘Thermally chargeable supercapacitors(TCSCs)have unique advantages in the collection,conversion,and storage of thermal energy,contributing to the development of new strategies for thermal energy utilization.2D MXene materials are predicted to be highly promising new thermoelectric materials.Here,we report a self-assembled flexible Ti_(3)C_(2)T_(x) MXenebased TCSC device,using prepared Ti_(3)C_(2)T_(x) MXene as the capacitor electrode and a NaClO_(4)/PEO gel as the electrolyte.We also explore the working mechanism of the TCSCs.The fabricated Ti_(3)C_(2)T_(x)-based TCSCs exhibit an excellent Seebeck coefficient of 11.8 mV∙K^(−1) on average and maintain good cycling stability under various temperature differences.Demonstrations of multiple practical applications show that Ti_(3)C_(2)T_(x) MXene-based TCSC devices are excellent candidates for self-powered integrated electronic devices.
文摘Micro-expressions,fleeting involuntary facial cues lasting under half a second,reveal genuine emotions and are valuable in clinical diagnosis and psychotherapy.Real-time recognition on resource-constrained embedded devices remains challenging,as current methods struggle to balance performance and efficiency.This study introduces a semi-lightweight multifunctional network that enhances real-time deployment and accuracy.Unlike prior simplistic feature fusion techniques,our novel multi-feature fusion strategy leverages temporal,spatial,and differential features to better capture dynamic changes.Enhanced by Residual Network(ResNet)architecture with channel and spatial attention mechanisms,the model improves feature representation while maintaining a lightweight design.Evaluations on SMIC,CASME II,SAMM,and their composite dataset show superior performance in Unweighted F1 Score(UF1)and Unweighted Average Recall(UAR),alongside faster detection speeds compared to existing algorithms.
基金supported by the National Key Research and Development Program of China(2023YFD1900802)the China Agriculture Research System of MOF and MARA(CARS-03-19)+2 种基金the National Natural Science Foundation of China(51879267)the Central Public-interest Scientific Institution Basal Research Fund,China(IFI2023-13)the Agricultural Science and Technology Innovation Program(ASTIP),Chinese Academy of Agricultural Sciences。
文摘A high-efficiency mode of high-low seedbed cultivation(HLSC)has been listed as the main agricultural technology to increase land utilization ratio and grain yield in Shandong Province,China.However,limited information is available on the optimized water and nitrogen management for yield formation,especially the grain-filling process,under HLSC mode.A three-year field experiment with four nitrogen rates and three irrigation rates of HLSC was conducted to reveal the response of grain-filling parameters,grain weight percentage of spike weight(GPS),spike moisture content(SMC),and winter wheat yield to water and nitrogen rates.The four nitrogen rates were N1(360 kg ha^(-1) pure N),N2(300 kg ha^(-1) pure N),N3(240 kg ha^(-1) pure N),and N4(180 kg ha^(-1) pure N),respectively,and the three irrigation quotas were W1(120 mm),W2(90 mm),and W3(60 mm),respectively.Results showed that the determinate growth function generally performed well in simulating the temporal dynamics of grain weight(0.989<R^(2)<0.999,where R2 is the determination coefficient).The occurrence time of maximum filling rate(T_(max))and active grain-filling period(AGP)increased with the increase in the water or nitrogen rate,whereas the average grain-filling rate(G_(mean))had a decreasing trend.The final 1,000-grain weight(FTGW)increased and then decreased with the increase in the nitrogen rates and increased with the increase in the irrigation rates.The GPS and SMC had a highly significant quadratic polynomial relationship with grain weight and days after anthesis.Nitrogen,irrigation,and year significantly affected the T_(max),AGP,G_(mean),and FTGW.Particularly,the AGP and FTGW were insignificantly different between high seedbed(HLSC-H)and low seedbed(HLSC-L)across the water and nitrogen levels.Moreover,the moderate water and nitrogen supply was more beneficial for grain yield,as well as for spike number and grain number per hectare.The principal component analysis indicated that combining 240-300 kg N ha^(-1) and 90^(-1)20 mm irrigation quota could improve grain-filling efficiency and yield for the HLSC-cultivated winter wheat.
基金supported by the National Natural Science Foundation of China(71401051)China Postdoctoral Science Foundation(2018M630562)+1 种基金the Leverhulme Trust International Network(IN-2014-020)the Cultural and Artistic Scientific Research Project of Hebei Province(HBWY2014-Y-C031)
文摘To reveal the relationship between a weakening buffer operator and strengthening buffer operator, the traditional integer order buffer operator is extended to one that is fractional order. Fractional order buffer operator not only can generalize the weakening buffer operator and the strengthening buffer operator, but also results in small adjustments of the buffer effect.The effectiveness of the grey model(GM(1,1)) with the fractional order buffer operator is validated by six cases.
基金supported by National Natural Science Foundation of China(51769010,51979133,51469010 and 51109102).
文摘Solar radiation is an important parameter in the fields of computer modeling,engineering technology and energy development.This paper evaluated the ability of three machine learning models,i.e.,Extreme Gradient Boosting(XGBoost),Support Vector Machine(SVM)and Multivariate Adaptive Regression Splines(MARS),to estimate the daily diffuse solar radiation(Rd).The regular meteorological data of 1966-2015 at five stations in China were taken as the input parameters(including mean average temperature(Ta),theoretical sunshine duration(N),actual sunshine duration(n),daily average air relative humidity(RH),and extra-terrestrial solar radiation(Ra)).And their estimation accuracies were subjected to comparative analysis.The three models were first trained using meteorological data from 1966 to 2000.Then,the 2001-2015 data was used to test the trained machine learning model.The results show that the XGBoost had better accuracy than the other two models in coefficient of determination(R2),root mean square error(RMSE),mean bias error(MBE)and normalized root mean square error(NRMSE).The MARS performed better in the training phase than the testing phase,but became less accurate in the testing phase,with the R2 value falling by 2.7-16.9%on average.By contrast,the R2 values of SVM and XGBoost increased by 2.9-12.2%and 1.9-14.3%,respectively.Despite trailing slightly behind the SVM at the Beijing station,the XGBoost showed good performance at the rest of the stations in the two phases.In the training phase,the accuracy growth is small but observable.In addition,the XGBoost had a slightly lower RMSE than the SVM,a signal of its edge in stability.Therefore,the three machine learning models can estimate the daily Rd based on local inputs and the XGBoost stands out for its excellent performance and stability.
基金This study was jointly supported by the National Natural Science Foundation of China(Nos.51879196,51790533,51709143)Jiangxi Natural Science Foundation of China(No.20181BAB206045).
文摘It is important for regional water resources management to know the agricultural water consumption information several months in advance.Forecasting reference evapotranspiration(ET_(0))in the next few months is important for irrigation and reservoir management.Studies on forecasting of multiple-month ahead ET_(0) using machine learning models have not been reported yet.Besides,machine learning models such as the XGBoost model has multiple parameters that need to be tuned,and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution.This study investigated the performance of the hybrid extreme gradient boosting(XGBoost)model coupled with the Grey Wolf Optimizer(GWO)algorithm for forecasting multi-step ahead ET_(0)(1-3 months ahead),compared with three conventional machine learning models,i.e.,standalone XGBoost,multi-layer perceptron(MLP)and M5 model tree(M5)models in the subtropical zone of China.The results showed that theGWO-XGB model generally performed better than the other three machine learning models in forecasting 1-3 months ahead ET_(0),followed by the XGB,M5 and MLP models with very small differences among the three models.The GWO-XGB model performed best in autumn,while the MLP model performed slightly better than the other three models in summer.It is thus suggested to apply the MLP model for ET_(0) forecasting in summer but use the GWO-XGB model in other seasons.
文摘In this paper, we studied a non-autonomous predator-prey system where the prey dispersal in a two-patch environment. With the help of a continuation theorem based on coincidence degree theory, we establish sufficient conditions for the existence of positive periodic solutions. Finally, we give numerical analysis to show the effectiveness of our theoretical results.
基金supported in part by National Natural Science Foundation of China(Grant No.82172649,82003580,and 82173666)Shenzhen science and technology research and development funds(Grant No.JCYJ20210324094612035,China)。
文摘Cancer reprogramming is an important facilitator of cancer development and survival,with tumor cells exhibiting a preference for aerobic glycolysis beyond oxidative phosphorylation,even under sufficient oxygen supply condition.This metabolic alteration,known as the Warburg effect,serves as a significant indicator of malignant tumor transformation.The Warburg effect primarily impacts cancer occurrence by influencing the aerobic glycolysis pathway in cancer cells.Key enzymes involved in this process include glucose transporters(GLUTs),HKs,PFKs,LDHs,and PKM2.Moreover,the expression of transcriptional regulatory factors and proteins,such as FOXM1,p53,NF-κB,HIF1a,and c-Myc,can also influence cancer progression.Furthermore,lncRNAs,miRNAs,and circular RNAs play a vital role in directly regulating the Warburg effect.Additionally,gene mutations,tumor microenvironment remodeling,and immune system interactions are closely associated with the Warburg effect.Notably,the development of drugs targeting the Warburg effect has exhibited promising potential in tumor treatment.This comprehensive review presents novel directions and approaches for the early diagnosis and treatment of cancer patients by conducting in-depth research and summarizing the bright prospects of targeting the Warburg effect in cancer.
基金supported by the National Natural Science Foundation of China(Nos.62103283 and 12371308)。
文摘This study investigates how the events of deception attacks are distributed during the fusion of multi-sensor nonlinear systems.First,a deception attack with limited energy(DALE)is introduced under the framework of distributed extended Kalman consensus filtering(DEKCF).Next,a hypothesis testing-based mechanism to detect the abnormal data generated by DALE,in the presence of the error term caused by the linearization of the nonlinear system,is established.Once the DALE is detected,a new rectification strategy can be triggered to recalibrate the abnormal data,restoring it to its normal state.Then,an attack-resilient DEKCF(AR-DEKCF)algorithm is proposed,and its fusion estimation errors are demonstrated to satisfy the mean square exponential boundedness performance,under appropriate conditions.Finally,the effectiveness of the AR-DEKCF algorithm is confirmed through simulations involving multi-unmanned aerial vehicle(multi-UAV)tracking problems.
文摘Detailed routing has become much challenging in modern circuit designs due to the extreme scaling of chip size and the complicated design rules.In this paper,we give an effective algorithm for detailed routing considering advanced technology nodes.First,we present a valid pin-access candidates generation technology for handling complex pin shapes.Then,we propose a tree-based nets components selection algorithm to decide connecting order for multiple nets components.Finally,combined with global routing results and advanced technology nodes,an initial routing results optimization algorithm is presented to achieve the final detailed routing results.Experimental results on industry benchmarks show that,our proposed algorithm not only achieves 100%routability on real industrial cases in a reasonable runtime,but also optimizes total wirelength,total vias and other advanced technology nodes simultaneously.
