This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigat...This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigate the influence of the radius ratio(R/B),anisotropic ratio(re),interface roughness factor(α),and inclination angle(β).Specifically,the results reveal that increasingβsignificantly enhances Nc,especially as soil behavior approaches isotropy.Higherαimproves resistance at steeper inclinations by mobilizing greater interface shear.Nc increases with re,reflecting enhanced strength under isotropic conditions.To enhance predictive accuracy and generalization,a hybrid machine learning model was developed by integrating Extreme Gradient Boosting(XGBoost)with Genetic Algorithm(GA)and Mutation-Based Genetic Algorithm(MGA)for hyperparameter tuning.Among the models,MGA-XGBoost outperformed GA-XGBoost,achieving higher predictive accuracy(R^(2)=0.996 training,0.993 testing).Furthermore,SHAP analysis consistently identified anisotropic ratio(re)as the most influential factor in predicting uplift capacity,followed by interface roughness factor(α),inclination angle(β),and radius ratio(R/B).The proposed framework serves as a scalable decision-support tool adaptable to various soil types and foundation geometries,offering a more efficient and data-driven approach to uplift-resistant design in anisotropic cohesive soils.展开更多
Intrahepatic cholangiocarcinoma(ICC),a rare but rising global malignancy originating from the bile ducts,poses significant challenges in terms of effective treatment and patient outcomes.While surgical excision remain...Intrahepatic cholangiocarcinoma(ICC),a rare but rising global malignancy originating from the bile ducts,poses significant challenges in terms of effective treatment and patient outcomes.While surgical excision remains the curative option,its limited efficacy necessitates more therapeutic strategies,including systemic therapies.The management of ICC involves a multidisciplinary approach,with treatment decisions guided by patient-specific and tumor-specific factors.Gemcitabine-cisplatin(GEMCIS)chemotherapy has been a standard first-line therapy,but recent advancements in immunotherapy,particularly the introduction of durvalumab,have provided new hope.Additionally,gene mutation-based therapies,targeting fibroblast growth factor receptors(FGFRs),isocitrate dehydrogenase-1(IDH1),human epidermal growth factor receptor-2(HER2),and B-RAF proto-oncogene(BRAF),offer promising prospects for personalized treatment.High-throughput genomic profiling technologies have facilitated the identification of actionable targets and the development of innovative therapeutic approaches.This review summarizes the mutation-based therapies in ICC,including FDA-approved targeted drugs and ongoing clinical trials,highlighting the evolving landscape of ICC treatment.展开更多
文摘This study evaluates the undrained uplift capacity of open-caisson anchors embedded in anisotropic clay using Finite Element Limit Analysis(FELA)and a hybrid machine learning framework.The FELA simulations inves-tigate the influence of the radius ratio(R/B),anisotropic ratio(re),interface roughness factor(α),and inclination angle(β).Specifically,the results reveal that increasingβsignificantly enhances Nc,especially as soil behavior approaches isotropy.Higherαimproves resistance at steeper inclinations by mobilizing greater interface shear.Nc increases with re,reflecting enhanced strength under isotropic conditions.To enhance predictive accuracy and generalization,a hybrid machine learning model was developed by integrating Extreme Gradient Boosting(XGBoost)with Genetic Algorithm(GA)and Mutation-Based Genetic Algorithm(MGA)for hyperparameter tuning.Among the models,MGA-XGBoost outperformed GA-XGBoost,achieving higher predictive accuracy(R^(2)=0.996 training,0.993 testing).Furthermore,SHAP analysis consistently identified anisotropic ratio(re)as the most influential factor in predicting uplift capacity,followed by interface roughness factor(α),inclination angle(β),and radius ratio(R/B).The proposed framework serves as a scalable decision-support tool adaptable to various soil types and foundation geometries,offering a more efficient and data-driven approach to uplift-resistant design in anisotropic cohesive soils.
基金supported by the National Natural Science Foundation of China(No.82173260,No.81972708,No.82072681,No.82003082,No.81773069,No.81830102,No.81772578)the National Key R&D Program of China(No.2019YFC1315800,2019YFC1315802,2018YFA0109400)Shanghai Technical Standard Program(21DZ2201100).
文摘Intrahepatic cholangiocarcinoma(ICC),a rare but rising global malignancy originating from the bile ducts,poses significant challenges in terms of effective treatment and patient outcomes.While surgical excision remains the curative option,its limited efficacy necessitates more therapeutic strategies,including systemic therapies.The management of ICC involves a multidisciplinary approach,with treatment decisions guided by patient-specific and tumor-specific factors.Gemcitabine-cisplatin(GEMCIS)chemotherapy has been a standard first-line therapy,but recent advancements in immunotherapy,particularly the introduction of durvalumab,have provided new hope.Additionally,gene mutation-based therapies,targeting fibroblast growth factor receptors(FGFRs),isocitrate dehydrogenase-1(IDH1),human epidermal growth factor receptor-2(HER2),and B-RAF proto-oncogene(BRAF),offer promising prospects for personalized treatment.High-throughput genomic profiling technologies have facilitated the identification of actionable targets and the development of innovative therapeutic approaches.This review summarizes the mutation-based therapies in ICC,including FDA-approved targeted drugs and ongoing clinical trials,highlighting the evolving landscape of ICC treatment.
