BACKGROUND Thrombectomy and anatomical anastomosis(TAA)has long been considered the optimal approach to portal vein thrombosis(PVT)in liver transplantation(LT).However,TAA and the current approach for non-physiologica...BACKGROUND Thrombectomy and anatomical anastomosis(TAA)has long been considered the optimal approach to portal vein thrombosis(PVT)in liver transplantation(LT).However,TAA and the current approach for non-physiological portal reconstructions are associated with a higher rate of complications and mortality in some cases.AIM To describe a new choice for reconstructing the portal vein through a posterior pancreatic tunnel(RPVPPT)to address cases of unresectable PVT.METHODS Between August 2019 and August 2021,245 adult LTs were performed.Forty-five(18.4%)patients were confirmed to have PVT before surgery,among which seven underwent PV reconstruction via the RPVPPT approach.We retrospectively analyzed the surgical procedure and postoperative complications of these seven recipients that underwent PV reconstruction due to PVT.RESULTS During the procedure,PVT was found in all the seven cases with significant adhesion to the vascular wall and could not be dissected.The portal vein proximal to the superior mesenteric vein was damaged in one case when attempting thrombolectomy,resulting in massive bleeding.LT was successfully performed in all patients with a mean duration of 585 min(range 491-756 min)and mean intraoperative blood loss of 800 mL(range 500-3000 mL).Postoperative complications consisted of chylous leakage(n=3),insufficient portal venous flow to the graft(n=1),intra-abdominal hemorrhage(n=1),pulmonary infection(n=1),and perioperative death(n=1).The remaining six patients survived at 12-17 mo follow-up.CONCLUSION The RPVPPT technique might be a safe and effective surgical procedure during LT for complex PVT.However,follow-up studies with large samples are still warranted due to the relatively small number of cases.展开更多
Quantum machine learning(QML)is a rapidly rising research eld that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientic research and improving data processing.How to ef...Quantum machine learning(QML)is a rapidly rising research eld that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientic research and improving data processing.How to efciently control or manipulate the quantum system is a fundamental and vexing problem in quantum computing.It can be described as learning or approximating a unitary operator.Since the success of the hybrid-based quantum machine learning model proposed in recent years,we investigate to apply the techniques from QML to tackle this problem.Based on the Choi–Jamiołkowski isomorphism in quantum computing,we transfer the original problem of learning a unitary operator to a min–max optimization problem which can also be viewed as a quantum generative adversarial network.Besides,we select the spectral norm between the target and generated unitary operators as the regularization term in the loss function.Inspired by the hybrid quantum-classical framework widely used in quantum machine learning,we employ the variational quantum circuit and gradient descent based optimizers to solve the min-max optimization problem.In our numerical experiments,the results imply that our proposed method can successfully approximate the desired unitary operator and dramatically reduce the number of quantum gates of the traditional approach.The average delity between the states that are produced by applying target and generated unitary on random input states is around 0.997.展开更多
An online detection technology must be developed for realizing the real-time control of friction stir welding.In this study,the three-dimensional force exerted on a material during friction stir welding was collected ...An online detection technology must be developed for realizing the real-time control of friction stir welding.In this study,the three-dimensional force exerted on a material during friction stir welding was collected synchronously and the relationship between the forces and welding quality was investigated.The results indicated that the fluctuation period of the traverse force was equal to that of the lateral force during the stable welding stage.The phase difference between two horizontal forces wasπ/2.The values of the horizontal forces increased with welding speed,whereas their amplitudes remained the same.The proposed force model showed that the traverse and lateral forces conformed to an elliptical curve,and this result was consistent with the behavior of the measured data.The variational mode decomposition was used to process the plunge force.The intrinsic mode function that represented the real fluctuation in the plunge force varied at the same frequency as the spindle rotational speed.When tunnel defects occurred,the fluctuation period features were consistent with those obtained during normal welding,whereas the ratio parameter defined in this study increased significantly.展开更多
基金the Third People’s Hospital of Shenzhen Scientific Research Project,No.G2021008 and No.G2022008Shenzhen Key Medical Discipline Construction Fund,No.SZXK079Shenzhen Science and Technology Research and Development Fund,No.JCYJ20190809165813331 and No.JCYJ20210324131809027.
文摘BACKGROUND Thrombectomy and anatomical anastomosis(TAA)has long been considered the optimal approach to portal vein thrombosis(PVT)in liver transplantation(LT).However,TAA and the current approach for non-physiological portal reconstructions are associated with a higher rate of complications and mortality in some cases.AIM To describe a new choice for reconstructing the portal vein through a posterior pancreatic tunnel(RPVPPT)to address cases of unresectable PVT.METHODS Between August 2019 and August 2021,245 adult LTs were performed.Forty-five(18.4%)patients were confirmed to have PVT before surgery,among which seven underwent PV reconstruction via the RPVPPT approach.We retrospectively analyzed the surgical procedure and postoperative complications of these seven recipients that underwent PV reconstruction due to PVT.RESULTS During the procedure,PVT was found in all the seven cases with significant adhesion to the vascular wall and could not be dissected.The portal vein proximal to the superior mesenteric vein was damaged in one case when attempting thrombolectomy,resulting in massive bleeding.LT was successfully performed in all patients with a mean duration of 585 min(range 491-756 min)and mean intraoperative blood loss of 800 mL(range 500-3000 mL).Postoperative complications consisted of chylous leakage(n=3),insufficient portal venous flow to the graft(n=1),intra-abdominal hemorrhage(n=1),pulmonary infection(n=1),and perioperative death(n=1).The remaining six patients survived at 12-17 mo follow-up.CONCLUSION The RPVPPT technique might be a safe and effective surgical procedure during LT for complex PVT.However,follow-up studies with large samples are still warranted due to the relatively small number of cases.
基金support from the National Key Research and Devel-opment Plan of China under Grant No.2018YFA0306703.
文摘Quantum machine learning(QML)is a rapidly rising research eld that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientic research and improving data processing.How to efciently control or manipulate the quantum system is a fundamental and vexing problem in quantum computing.It can be described as learning or approximating a unitary operator.Since the success of the hybrid-based quantum machine learning model proposed in recent years,we investigate to apply the techniques from QML to tackle this problem.Based on the Choi–Jamiołkowski isomorphism in quantum computing,we transfer the original problem of learning a unitary operator to a min–max optimization problem which can also be viewed as a quantum generative adversarial network.Besides,we select the spectral norm between the target and generated unitary operators as the regularization term in the loss function.Inspired by the hybrid quantum-classical framework widely used in quantum machine learning,we employ the variational quantum circuit and gradient descent based optimizers to solve the min-max optimization problem.In our numerical experiments,the results imply that our proposed method can successfully approximate the desired unitary operator and dramatically reduce the number of quantum gates of the traditional approach.The average delity between the states that are produced by applying target and generated unitary on random input states is around 0.997.
基金supported by the National Natural Science Foundation of China(Grant No.52201048)the China Postdoctoral Science Foundation(Grant No.2020M670651)the National Natural Science Foundation of China(Grant No.52075376).
文摘An online detection technology must be developed for realizing the real-time control of friction stir welding.In this study,the three-dimensional force exerted on a material during friction stir welding was collected synchronously and the relationship between the forces and welding quality was investigated.The results indicated that the fluctuation period of the traverse force was equal to that of the lateral force during the stable welding stage.The phase difference between two horizontal forces wasπ/2.The values of the horizontal forces increased with welding speed,whereas their amplitudes remained the same.The proposed force model showed that the traverse and lateral forces conformed to an elliptical curve,and this result was consistent with the behavior of the measured data.The variational mode decomposition was used to process the plunge force.The intrinsic mode function that represented the real fluctuation in the plunge force varied at the same frequency as the spindle rotational speed.When tunnel defects occurred,the fluctuation period features were consistent with those obtained during normal welding,whereas the ratio parameter defined in this study increased significantly.
