Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disruptin...Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.展开更多
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.展开更多
The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in futu...The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.展开更多
In this article,a novel model-free coordinated optimal regulation design methodology is proposed for the rigidly connected dual permanent magnet synchronous motor(PMSM)system via adaptive dynamic programming(ADP).Firs...In this article,a novel model-free coordinated optimal regulation design methodology is proposed for the rigidly connected dual permanent magnet synchronous motor(PMSM)system via adaptive dynamic programming(ADP).First,we adopt the classical master-slave structure to maintain torque synchronization by virtue of field-oriented control.Then,a reducedorder model of the dual-PMSM system is established through the application of singular perturbation theory(SPT),which is of significance to decrease the learning time and computational complexity in the outer speed loop design.Afterwards,we design a coordinated adaptive optimal regulator in framework of ADP to drive the speed of girth gear asymptotic tracking the reference signal and accommodate the load torque disturbance,which is independent of the knowledge of model parameters of the system.According to SPT,we analyze the suboptimality,closed-loop stability,and robustness properties of the obtained controller under mild conditions.Finally,comprehensive experimental studies are provided to verify that the proposed control strategy can achieve the speed regulation and the torque synchronization,as well as ameliorate the transient response.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is an inflammation-associated tumor with a dismal prognosis.Immunotherapy has become an important treatment strategy for HCC,as immunity is closely related to inflammation in th...BACKGROUND Hepatocellular carcinoma(HCC)is an inflammation-associated tumor with a dismal prognosis.Immunotherapy has become an important treatment strategy for HCC,as immunity is closely related to inflammation in the tumor microenvir-onment.Inflammation regulates the expression of programmed death ligand-1(PD-L1)in the immunosuppressive tumor microenvironment and affects im-munotherapy efficacy.Interleukin-17A(IL-17A)is involved in the remodeling of the tumor microenvironment and plays a protumor or antitumor role in different tumors.We hypothesized that IL-17A participates in tumor progression by affe-cting the level of immune checkpoint molecules in HCC.The upregulation of PD-L1 expression in HCC cells by IL-17A was assessed by reverse transcription PCR,western blotting,and flow cytometry.Mechanistic studies were conducted with gene knockout models and pathway inhibitors.The function of IL-17A in immune evasion was explored through coculture of T cells and HCC cells.The effects of IL-17A on the malignant biological behaviors of HCC cells were evaluated in vitro,and the antitumor effects of an IL-17A inhibitor and its synergistic effects with a PD-L1 inhibitor were studied in vivo.RESULTS IL-17A upregulated PD-L1 expression in HCC cells in a dose-dependent manner,whereas IL-17A receptor knockout or treatment with a small mothers against decapentaplegic 2 inhibitor diminished the PD-L1 expression induced by IL-17A.IL-17A enhanced the survival of HCC cells in the coculture system.IL-17A increased the viability,G2/M ratio,and migration of HCC cells and decreased the apoptotic index.Cyclin D1,VEGF,MMP9,and Bcl-1 expression increased after IL-17A treatment,whereas BAX expression decreased.The combination of IL-17A and PD-L1 inhibitors showed synergistic antitumor efficacy and increased cluster of differentiation 8+T lymphocyte infiltration in an HCC mouse model.CONCLUSION IL-17A upregulates PD-L1 expression via the IL-17A receptor/phosphorylation-small mothers against decapenta-plegic 2 signaling pathway in HCC cells.Blocking IL-17A enhances the therapeutic efficacy of PD-L1 antibodies in HCC in vivo.展开更多
BACKGROUND Breast cancer(BC)continues to occupy a leading position in terms of morbidity and mortality from malignant neoplasms among the female population.One of the promising markers associated with BC progression i...BACKGROUND Breast cancer(BC)continues to occupy a leading position in terms of morbidity and mortality from malignant neoplasms among the female population.One of the promising markers associated with BC progression is programmed death ligand 1(PD-L1).Previously,we investigated PD-L1 expression in BC via a new antibody against programmed cell death protein 1 ligand 1(PDCD1 LG1)and reported that high PDCD1 LG1 expression in tumor cells is an independent factor for a high risk of regional metastasis in patients with BC.However,the prognostic significance of PDCD1 LG1 expression in BC stromal cells has not been adequately studied.AIM To study the features of PDCD1 LG1 expression in BC stromal cells and its relationship with BC clinicopathological characteristics.METHODS In a prospective single-center observational study,tumor samples from 148 patients with newly diagnosed BC were examined.The tumor sections were immunohistochemically stained with antibodies against PDCD1 LG1.In the tumor samples,the PDCD1 LG1-positive lymphocyte(PDCD1 LG1+LF)score,presence of nuclear PDCD1 LG1 expression in the LFs,PDCD1 LG1 expression in polymorphic cell infiltrates(PDCD1 LG1+polymorphic cell infiltrates[PCIs]),and cells of the fibroblastic stroma and endothelial cells of the tumor microvessels were assessed.Statistical analyses were performed using Statistica 10.0 software.RESULTS A PDCD1 LG1+LF score≥3 was detected more often at stages N0 and N3 than at N1 and N2(P=0.03).Moderate and pronounced PDCD1 LG1+PCIs and the presence of PDCD1 LG1+fibroblastic stroma were associated with negative estrogen receptor status(P=0.0008 and P=0.03,respectively),human epidermal growth factor receptor 2-positive(HER2+)BC(P<0.00001 and P=0.0005),and luminal B HER2+,non-luminal HER2+and triple-negative BC(P<0.00001 and P=0.004).The risk of metastasis to regional lymph nodes(RLNs)depend on lymphovascular invasion(LVI)and the PDCD1 LG1+LF score.In the absence of LVI and a PDCD1 LG1+LF score<3 or≥3,metastases in RLNs were absent in 66.6%and 93.9%of patients with BC,respectively.In the presence of LVI and a PDCD1 LG1+LF score<3 or≥3,metastases in RLNs were detected in 82.6%and 92.7%of patients with BC,respectively.CONCLUSION The results indicated that the combined assessment of the PDCD1 LG1+LF score and LVI can improve the accuracy of predicting the risk of metastasis to RLNs in patients with BC.展开更多
Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the...Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.展开更多
Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequent...Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.展开更多
Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate...Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.展开更多
BACKGROUND We previously demonstrated that the antibody against programmed cell death protein 1 ligand 1(PDCD1 LG1)is a promising new marker of programmed death-ligand 1(PD-L1)expression that correlates with both brea...BACKGROUND We previously demonstrated that the antibody against programmed cell death protein 1 ligand 1(PDCD1 LG1)is a promising new marker of programmed death-ligand 1(PD-L1)expression that correlates with both breast cancer(BC)clinicopathological characteristics and tumor sensitivity to chemotherapy.However,the concordance of PDCD1 LG1 expression scoring with immunohistochemical(IHC)tests approved for clinical use and with the polymerase chain reaction(PCR)method has not been previously studied.AIM To evaluate the concordance of methods for assessing PD-L1 expression,IHC tests with anti-PD-L1(PDCD1 LG1)and anti-PD-L1(SP142)antibodies and PCR.METHODS This prospective single-center observational cohort study included 148 patients with BC.PD-L1 expression in immune cells was assessed by the IHC method with anti-PD-L1(PDCD1 LG1)and anti-PD-L1(SP142)antibodies and by PCR.The concordance of PD-L1 scores between tests was assessed with positive percentage agreement(PPA)and negative percentage agreement(NPA).The strength of the agreement between the methods was calculated via the Cohen kappa index.P<0.05 was considered statistically significant.RESULTS Regardless of the method used to assess marker expression,PD-L1 expression was significantly more often detected in patients with negative estrogen receptor status,human epidermal growth factor receptor-2-positive(HER2+)status,luminal B HER+BC,nonluminal HER+BC and triple-negative BC.PPA and NPA were 38.3%and 70.4%,respectively,for PD-L1(PDCD1 LG1)and PD-L1(SP142);26.3%and 63.3%,respectively,for PD-L1(PDCD1 LG1)and PD-L1(PCR);and 36.5%and 74.4%,respectively,for PD-L1(SP142)and PD-L1(PCR).Cohen's kappa index for PD-L1(PDCD1 LG1)and PD-L1(SP142)was 0.385(95%CI:0.304–0.466),that for PD-L1(PDCD1 LG1)and PD-L1(PCR)was 0.207(95%CI:0.127–0.287),and that for PD-L1(SP142)and PD-L1(PCR)was 0.389(95%CI:0.309–0.469).CONCLUSION Thus,all three markers of PD-L1 expression are associated with the characteristics of aggressive BC,demonstrating moderate concordance between the tests.展开更多
BACKGROUND Gastric cancer(GC)is one of the most common malignancies worldwide,and Helicobacter pylori(HP)infection is a well-established risk factor for its development.Programmed death-ligand 1(PD-L1)expression is a ...BACKGROUND Gastric cancer(GC)is one of the most common malignancies worldwide,and Helicobacter pylori(HP)infection is a well-established risk factor for its development.Programmed death-ligand 1(PD-L1)expression is a crucial biomarker for predicting the efficacy of immune checkpoint inhibitors in cancer treatment.While HP infection and PD-L1 expression in GC may be linked,the relationship between them remains unclear,in part because there have been conflicting results reported from various studies.AIM To perform a meta-analysis to assess the relationship between HP and PD-L1 expression in patients with GC.METHODS A systematic literature review was conducted using PubMed,Embase,Cochrane Library,and Web of Science databases.Observational studies that examined the association between HP infection and PD-L1 expression in patients with GC were included.Odds ratios and 95%confidence intervals were calculated to estimate the association.Heterogeneity was assessed using Cochrane’s Q test and I²statistic.A random-effects model was used due to significant heterogeneity across studies.RESULTS Fourteen studies involving a total of 3069 patients with GC were included.The pooled analysis showed a significant association between HP infection and increased PD-L1 expression in GC tissues(odd ratio=1.69,95%confidence interval:1.24-2.29,P<0.001,I^(2)=59%).Sensitivity analyses confirmed the robustness of these findings.Subgroup analyses did not show significant variation based on geographic region,sample size,or method of PD-L1 assessment.Publication bias was minimal,as shown by funnel plots and Egger’s regression test.CONCLUSION HP infection is associated with increased PD-L1 expression in GC,suggesting that HP status may influence the response to programmed cell death protein 1/PD-L1 blockade therapy.展开更多
Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained u...Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).展开更多
Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptabilit...Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.展开更多
BACKGROUND Sleep problems are particularly prevalent in people with depression or anxiety disorder.Although mindfulness has been suggested as an important component in alleviating insomnia,no comprehensive review and ...BACKGROUND Sleep problems are particularly prevalent in people with depression or anxiety disorder.Although mindfulness has been suggested as an important component in alleviating insomnia,no comprehensive review and meta-analysis has been conducted to evaluate the effects of different mindfulness-based intervention(MBI)programs on sleep among people with depression or anxiety disorder.AIM To compare the effects of different MBI programs on sleep among people with depression or anxiety disorder.METHODS Related publications in Embase,Medline,PubMed and PsycINFO databases were systematically searched from January 2010 to June 2020 for randomised controlled trials.Data were synthesized using a random-effects or a fixed-effects model to analyse the effects of various MBI programs on sleep problems among people with depression or anxiety disorder.The fixed-effects model was used when heterogeneity was negligible,and the random-effects model was used when heterogeneity was significant to calculate the standardised mean differences(SMDs)and 95%confidence intervals(CIs).RESULTS We identified 397 articles,of which 10 randomised controlled trials,involving a total of 541 participants,were included in the meta-analysis.Studies of internet mindfulness meditation intervention(IMMI),mindfulness meditation(MM),mindfulness-based cognitive therapy(MBCT),mindfulness-based stress reduction(MBSR)and mindfulness-based touch therapy(MBTT)met the inclusion criteria.The greatest effect sizes are reported in favour of MBTT,with SMDs of-1.138(95%CI:-1.937 to-0.340;P=0.005),followed by-1.003(95%CI:-1.645 to-0.360;P=0.002)for MBCT.SMDs of-0.618(95%CI:-0.980 to-0.257;P=0.001)and-0.551(95%CI:-0.842 to-0.260;P<0.0001)were reported for IMMI and MBSR in the pooling trials,respectively.Significant effects on sleep problem improvement are shown in all reviewed MBI programs,except MM,for which the effect size was shown to be nonsignificant.CONCLUSION All MBI programs(MBTT,MBCT,IMMI and MBSR),except MM,are effective options to improve sleep problems among people with depression or anxiety disorder.展开更多
This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the b...This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the body of the dam can develop during the first impoundment of the reservoir. Although there is vast experience worldwide in CFRD design and construction, few accurate experimental relationships are available to predict the settlement in CFRD. The goal is to advance the development of intelligent methods to estimate the subsidence of dams at the design stage. Due to dam zonifieation and uncertainties in material properties, these methods appear to be the appropriate choice. In this study, the crest settlement behavior of CFRDs is analyzed based on compiled data of 24 CFRDs constructed during recent years around the world, along with the utilization of gene ex- pression programming （GEP） and adaptive neuro-fuzzy inference system （ANFIS） methods. In addition, dam height （H）, shape factor （St）, and time （t, time after first operation） are also assessed, being considered major factors in predicting the settlement behavior. From the relationships proposed, the values ofR2 for both equations of GEP （with and without constant） were 0.9603 and 0.9734, and for the three approaches of ANFIS （grid partitioning （GP）, subtractive clustering method （SCM）, and fuzzy c-means clustering （FCM）） were 0.9693, 0.8657, and 0.8848, respectively. The obtained results indicate that the overall behavior evaluated by this approach is consistent with the measured data of other CFRDs.展开更多
Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells c...Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.展开更多
This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-vary...This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.展开更多
A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking prob...A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.展开更多
BACKGROUND Irreversible electroporation(IRE)is a novel local tumor ablation approach with the potential to activate the host’s immune system.However,this approach is insufficient to prevent cancer progression,and com...BACKGROUND Irreversible electroporation(IRE)is a novel local tumor ablation approach with the potential to activate the host’s immune system.However,this approach is insufficient to prevent cancer progression,and complementary approaches are required for effective immunotherapy.AIM To assess the immunomodulatory effects and mechanism of IRE combined antiprogrammed cell death protein 1(PD-1)treatment in subcutaneous pancreatic cancer models.METHODS C57BL-6 tumor-bearing mice were randomly divided into four groups:Control group;IRE group;anti-PD-1 group;and IRE+anti-PD-1 group.Tumor-infiltrating T,B,and natural killer cell levels and plasma concentrations of T helper type 1 cytokines(interleukin-2,interferon-γ,and tumor necrosis factor-α)were evaluated.Real-time PCR was used to determine the expression of CD8(marker of CD8+T cells)in tumor tissues of the mice of all groups at different points of time.The growth curves of tumors were drawn.RESULTS The results demonstrated that the IRE+anti-PD-1 group exhibited significantly higher percentages of T lymphocyte infiltration,including CD4+and CD8+T cells compared with the control group.Additionally,the IRE+anti-PD-1 group showed increased infiltration of natural killer and B cells,elevated cytokine levels,and higher CD8 mRNA expression.Tumor volume was significantly reduced in the IRE+anti-PD-1 group,indicating a more pronounced therapeutic effect.CONCLUSION The combination of IRE and anti-PD-1 therapy promotes CD8+T cell immunity responses,leading to a more effective reduction in tumor volume and improved therapeutic outcomes,which provides a new direction for ablation and immunotherapy of pancreatic cancer.展开更多
基金financially supported by Ministerio de Ciencia e Innovación projects SAF2017-82736-C2-1-R to MTMFin Universidad Autónoma de Madrid and by Fundación Universidad Francisco de Vitoria to JS+2 种基金a predoctoral scholarship from Fundación Universidad Francisco de Vitoriafinancial support from a 6-month contract from Universidad Autónoma de Madrida 3-month contract from the School of Medicine of Universidad Francisco de Vitoria。
文摘Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
基金Project(2022YFC2904502)supported by the National Key Research and Development Program of ChinaProject(62273357)supported by the National Natural Science Foundation of China。
文摘The electricity-hydrogen integrated energy system(EH-IES)enables synergistic operation of electricity,heat,and hydrogen subsystems,supporting renewable energy integration and efficient multi-energy utilization in future low carbon societies.However,uncertainties from renewable energy and load variability threaten system safety and economy.Conventional chance-constrained programming(CCP)ensures reliable operation by limiting risk.However,increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks.To address this,this paper proposes a risk-adjustable chance-constrained goal programming(RACCGP)model,integrating CCP and goal programming to balance risk and cost based on system risk assessment.An intelligent nonlinear goal programming method based on the state transition algorithm(STA)is developed,along with an improved discretized step transformation,to handle model nonlinearity and enhance computational efficiency.Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP,and the solution method outperforms average sample sampling in efficiency and solution quality.
基金supported by the National Natural Science Foundation of China(62073327,62403467,62373090,62273350,62521001)the Natural Science Foundation of Jiangsu Province(BK20241635)+2 种基金the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(CPSF)(GZB20240827)Jiangsu Funding Program for Excellent Postdoctoral Talent(2024ZB604)the China Postdoctoral Science Foundation(2024M763545,2025T054ZGMK).
文摘In this article,a novel model-free coordinated optimal regulation design methodology is proposed for the rigidly connected dual permanent magnet synchronous motor(PMSM)system via adaptive dynamic programming(ADP).First,we adopt the classical master-slave structure to maintain torque synchronization by virtue of field-oriented control.Then,a reducedorder model of the dual-PMSM system is established through the application of singular perturbation theory(SPT),which is of significance to decrease the learning time and computational complexity in the outer speed loop design.Afterwards,we design a coordinated adaptive optimal regulator in framework of ADP to drive the speed of girth gear asymptotic tracking the reference signal and accommodate the load torque disturbance,which is independent of the knowledge of model parameters of the system.According to SPT,we analyze the suboptimality,closed-loop stability,and robustness properties of the obtained controller under mild conditions.Finally,comprehensive experimental studies are provided to verify that the proposed control strategy can achieve the speed regulation and the torque synchronization,as well as ameliorate the transient response.
基金Supported by the Natural Science Foundation of Gansu Province,No.21JR7RA373 and No.24JRRA295.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is an inflammation-associated tumor with a dismal prognosis.Immunotherapy has become an important treatment strategy for HCC,as immunity is closely related to inflammation in the tumor microenvir-onment.Inflammation regulates the expression of programmed death ligand-1(PD-L1)in the immunosuppressive tumor microenvironment and affects im-munotherapy efficacy.Interleukin-17A(IL-17A)is involved in the remodeling of the tumor microenvironment and plays a protumor or antitumor role in different tumors.We hypothesized that IL-17A participates in tumor progression by affe-cting the level of immune checkpoint molecules in HCC.The upregulation of PD-L1 expression in HCC cells by IL-17A was assessed by reverse transcription PCR,western blotting,and flow cytometry.Mechanistic studies were conducted with gene knockout models and pathway inhibitors.The function of IL-17A in immune evasion was explored through coculture of T cells and HCC cells.The effects of IL-17A on the malignant biological behaviors of HCC cells were evaluated in vitro,and the antitumor effects of an IL-17A inhibitor and its synergistic effects with a PD-L1 inhibitor were studied in vivo.RESULTS IL-17A upregulated PD-L1 expression in HCC cells in a dose-dependent manner,whereas IL-17A receptor knockout or treatment with a small mothers against decapentaplegic 2 inhibitor diminished the PD-L1 expression induced by IL-17A.IL-17A enhanced the survival of HCC cells in the coculture system.IL-17A increased the viability,G2/M ratio,and migration of HCC cells and decreased the apoptotic index.Cyclin D1,VEGF,MMP9,and Bcl-1 expression increased after IL-17A treatment,whereas BAX expression decreased.The combination of IL-17A and PD-L1 inhibitors showed synergistic antitumor efficacy and increased cluster of differentiation 8+T lymphocyte infiltration in an HCC mouse model.CONCLUSION IL-17A upregulates PD-L1 expression via the IL-17A receptor/phosphorylation-small mothers against decapenta-plegic 2 signaling pathway in HCC cells.Blocking IL-17A enhances the therapeutic efficacy of PD-L1 antibodies in HCC in vivo.
基金Supported by Russian Science Foundation,No.23-25-00183.
文摘BACKGROUND Breast cancer(BC)continues to occupy a leading position in terms of morbidity and mortality from malignant neoplasms among the female population.One of the promising markers associated with BC progression is programmed death ligand 1(PD-L1).Previously,we investigated PD-L1 expression in BC via a new antibody against programmed cell death protein 1 ligand 1(PDCD1 LG1)and reported that high PDCD1 LG1 expression in tumor cells is an independent factor for a high risk of regional metastasis in patients with BC.However,the prognostic significance of PDCD1 LG1 expression in BC stromal cells has not been adequately studied.AIM To study the features of PDCD1 LG1 expression in BC stromal cells and its relationship with BC clinicopathological characteristics.METHODS In a prospective single-center observational study,tumor samples from 148 patients with newly diagnosed BC were examined.The tumor sections were immunohistochemically stained with antibodies against PDCD1 LG1.In the tumor samples,the PDCD1 LG1-positive lymphocyte(PDCD1 LG1+LF)score,presence of nuclear PDCD1 LG1 expression in the LFs,PDCD1 LG1 expression in polymorphic cell infiltrates(PDCD1 LG1+polymorphic cell infiltrates[PCIs]),and cells of the fibroblastic stroma and endothelial cells of the tumor microvessels were assessed.Statistical analyses were performed using Statistica 10.0 software.RESULTS A PDCD1 LG1+LF score≥3 was detected more often at stages N0 and N3 than at N1 and N2(P=0.03).Moderate and pronounced PDCD1 LG1+PCIs and the presence of PDCD1 LG1+fibroblastic stroma were associated with negative estrogen receptor status(P=0.0008 and P=0.03,respectively),human epidermal growth factor receptor 2-positive(HER2+)BC(P<0.00001 and P=0.0005),and luminal B HER2+,non-luminal HER2+and triple-negative BC(P<0.00001 and P=0.004).The risk of metastasis to regional lymph nodes(RLNs)depend on lymphovascular invasion(LVI)and the PDCD1 LG1+LF score.In the absence of LVI and a PDCD1 LG1+LF score<3 or≥3,metastases in RLNs were absent in 66.6%and 93.9%of patients with BC,respectively.In the presence of LVI and a PDCD1 LG1+LF score<3 or≥3,metastases in RLNs were detected in 82.6%and 92.7%of patients with BC,respectively.CONCLUSION The results indicated that the combined assessment of the PDCD1 LG1+LF score and LVI can improve the accuracy of predicting the risk of metastasis to RLNs in patients with BC.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z2443)State Key Laboratory for Man ufacturing Systems Engineering of Xi’an Jiaotong University of China
文摘Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.
基金supported by the National Natural Science Foundation of China(No.62203256)。
文摘Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A^(*)Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time.
基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDB0740000National Key Research and Development Program of China,No.2022YFB3904200,No.2022YFF0711601+1 种基金Key Project of Innovation LREIS,No.PI009National Natural Science Foundation of China,No.42471503。
文摘Deep-time Earth research plays a pivotal role in deciphering the rates,patterns,and mechanisms of Earth's evolutionary processes throughout geological history,providing essential scientific foundations for climate prediction,natural resource exploration,and sustainable planetary stewardship.To advance Deep-time Earth research in the era of big data and artificial intelligence,the International Union of Geological Sciences initiated the“Deeptime Digital Earth International Big Science Program”(DDE)in 2019.At the core of this ambitious program lies the development of geoscience knowledge graphs,serving as a transformative knowledge infrastructure that enables the integration,sharing,mining,and analysis of heterogeneous geoscience big data.The DDE knowledge graph initiative has made significant strides in three critical dimensions:(1)establishing a unified knowledge structure across geoscience disciplines that ensures consistent representation of geological entities and their interrelationships through standardized ontologies and semantic frameworks;(2)developing a robust and scalable software infrastructure capable of supporting both expert-driven and machine-assisted knowledge engineering for large-scale graph construction and management;(3)implementing a comprehensive three-tiered architecture encompassing basic,discipline-specific,and application-oriented knowledge graphs,spanning approximately 20 geoscience disciplines.Through its open knowledge framework and international collaborative network,this initiative has fostered multinational research collaborations,establishing a robust foundation for next-generation geoscience research while propelling the discipline toward FAIR(Findable,Accessible,Interoperable,Reusable)data practices in deep-time Earth systems research.
基金Supported by Russian Science Foundation,No.23-25-00183.
文摘BACKGROUND We previously demonstrated that the antibody against programmed cell death protein 1 ligand 1(PDCD1 LG1)is a promising new marker of programmed death-ligand 1(PD-L1)expression that correlates with both breast cancer(BC)clinicopathological characteristics and tumor sensitivity to chemotherapy.However,the concordance of PDCD1 LG1 expression scoring with immunohistochemical(IHC)tests approved for clinical use and with the polymerase chain reaction(PCR)method has not been previously studied.AIM To evaluate the concordance of methods for assessing PD-L1 expression,IHC tests with anti-PD-L1(PDCD1 LG1)and anti-PD-L1(SP142)antibodies and PCR.METHODS This prospective single-center observational cohort study included 148 patients with BC.PD-L1 expression in immune cells was assessed by the IHC method with anti-PD-L1(PDCD1 LG1)and anti-PD-L1(SP142)antibodies and by PCR.The concordance of PD-L1 scores between tests was assessed with positive percentage agreement(PPA)and negative percentage agreement(NPA).The strength of the agreement between the methods was calculated via the Cohen kappa index.P<0.05 was considered statistically significant.RESULTS Regardless of the method used to assess marker expression,PD-L1 expression was significantly more often detected in patients with negative estrogen receptor status,human epidermal growth factor receptor-2-positive(HER2+)status,luminal B HER+BC,nonluminal HER+BC and triple-negative BC.PPA and NPA were 38.3%and 70.4%,respectively,for PD-L1(PDCD1 LG1)and PD-L1(SP142);26.3%and 63.3%,respectively,for PD-L1(PDCD1 LG1)and PD-L1(PCR);and 36.5%and 74.4%,respectively,for PD-L1(SP142)and PD-L1(PCR).Cohen's kappa index for PD-L1(PDCD1 LG1)and PD-L1(SP142)was 0.385(95%CI:0.304–0.466),that for PD-L1(PDCD1 LG1)and PD-L1(PCR)was 0.207(95%CI:0.127–0.287),and that for PD-L1(SP142)and PD-L1(PCR)was 0.389(95%CI:0.309–0.469).CONCLUSION Thus,all three markers of PD-L1 expression are associated with the characteristics of aggressive BC,demonstrating moderate concordance between the tests.
文摘BACKGROUND Gastric cancer(GC)is one of the most common malignancies worldwide,and Helicobacter pylori(HP)infection is a well-established risk factor for its development.Programmed death-ligand 1(PD-L1)expression is a crucial biomarker for predicting the efficacy of immune checkpoint inhibitors in cancer treatment.While HP infection and PD-L1 expression in GC may be linked,the relationship between them remains unclear,in part because there have been conflicting results reported from various studies.AIM To perform a meta-analysis to assess the relationship between HP and PD-L1 expression in patients with GC.METHODS A systematic literature review was conducted using PubMed,Embase,Cochrane Library,and Web of Science databases.Observational studies that examined the association between HP infection and PD-L1 expression in patients with GC were included.Odds ratios and 95%confidence intervals were calculated to estimate the association.Heterogeneity was assessed using Cochrane’s Q test and I²statistic.A random-effects model was used due to significant heterogeneity across studies.RESULTS Fourteen studies involving a total of 3069 patients with GC were included.The pooled analysis showed a significant association between HP infection and increased PD-L1 expression in GC tissues(odd ratio=1.69,95%confidence interval:1.24-2.29,P<0.001,I^(2)=59%).Sensitivity analyses confirmed the robustness of these findings.Subgroup analyses did not show significant variation based on geographic region,sample size,or method of PD-L1 assessment.Publication bias was minimal,as shown by funnel plots and Egger’s regression test.CONCLUSION HP infection is associated with increased PD-L1 expression in GC,suggesting that HP status may influence the response to programmed cell death protein 1/PD-L1 blockade therapy.
基金supported by National Natural Science Foundation of China(61100159,61233007)National High Technology Research and Development Program of China(863 Program)(2011AA040103)+2 种基金Foundation of Chinese Academy of Sciences(KGCX2-EW-104)Financial Support of the Strategic Priority Research Program of Chinese Academy of Sciences(XDA06021100)the Cross-disciplinary Collaborative Teams Program for Science,Technology and Innovation,of Chinese Academy of Sciences-Network and System Technologies for Security Monitoring and Information Interaction in Smart Grid Energy Management System for Micro-smart Grid
基金Financial support from the National Natural Science Foundation of China (22022816, 22078358)。
文摘Recent research on deterministic methods for circulating cooling water systems optimization has been well developed. However, the actual operating conditions of the system are mostly variable, so the system obtained under deterministic conditions may not be stable and economical. This paper studies the optimization of circulating cooling water systems under uncertain circumstance. To improve the reliability of the system and reduce the water and energy consumption, the influence of different uncertain parameters is taken into consideration. The chance constrained programming method is used to build a model under uncertain conditions, where the confidence level indicates the degree of constraint violation. Probability distribution functions are used to describe the form of uncertain parameters. The objective is to minimize the total cost and obtain the optimal cooling network configuration simultaneously.An algorithm based on Monte Carlo method is proposed, and GAMS software is used to solve the mixed integer nonlinear programming model. A case is optimized to verify the validity of the model. Compared with the deterministic optimization method, the results show that when considering the different types of uncertain parameters, a system with better economy and reliability can be obtained(total cost can be reduced at least 2%).
基金the National Key R&D Program of China(No.2023YFE0208700)National Natural Sci-ence Foundation of China(No.92163109 and 52072095)+7 种基金Shenzhen Science and Technology Program(No.RCJC20231211090000001,GXWD20231129101105001)the National Natural Science Foundation of China(No.52205590)the Natural Science Foundation of Jiangsu Province(No.BK20220834)the Start-up Research Fund of Southeast University(No.RF1028623098)the State Key Laboratory of Robotics and Systems(HIT)(No.SKLRS-2024-KF-11)National Natural Science Foundation of China(No.52202348)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011491)Shenzhen Science and Technology Program(Nos.GXWD20220818224716001,KJZD20231023100302006).
文摘Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.
文摘BACKGROUND Sleep problems are particularly prevalent in people with depression or anxiety disorder.Although mindfulness has been suggested as an important component in alleviating insomnia,no comprehensive review and meta-analysis has been conducted to evaluate the effects of different mindfulness-based intervention(MBI)programs on sleep among people with depression or anxiety disorder.AIM To compare the effects of different MBI programs on sleep among people with depression or anxiety disorder.METHODS Related publications in Embase,Medline,PubMed and PsycINFO databases were systematically searched from January 2010 to June 2020 for randomised controlled trials.Data were synthesized using a random-effects or a fixed-effects model to analyse the effects of various MBI programs on sleep problems among people with depression or anxiety disorder.The fixed-effects model was used when heterogeneity was negligible,and the random-effects model was used when heterogeneity was significant to calculate the standardised mean differences(SMDs)and 95%confidence intervals(CIs).RESULTS We identified 397 articles,of which 10 randomised controlled trials,involving a total of 541 participants,were included in the meta-analysis.Studies of internet mindfulness meditation intervention(IMMI),mindfulness meditation(MM),mindfulness-based cognitive therapy(MBCT),mindfulness-based stress reduction(MBSR)and mindfulness-based touch therapy(MBTT)met the inclusion criteria.The greatest effect sizes are reported in favour of MBTT,with SMDs of-1.138(95%CI:-1.937 to-0.340;P=0.005),followed by-1.003(95%CI:-1.645 to-0.360;P=0.002)for MBCT.SMDs of-0.618(95%CI:-0.980 to-0.257;P=0.001)and-0.551(95%CI:-0.842 to-0.260;P<0.0001)were reported for IMMI and MBSR in the pooling trials,respectively.Significant effects on sleep problem improvement are shown in all reviewed MBI programs,except MM,for which the effect size was shown to be nonsignificant.CONCLUSION All MBI programs(MBTT,MBCT,IMMI and MBSR),except MM,are effective options to improve sleep problems among people with depression or anxiety disorder.
文摘This paper deals with the estimation of crest settlement in a concrete face rockfill dam （CFRD）, utilizing intelligent methods. Following completion of dam construction, considerable movements of the crest and the body of the dam can develop during the first impoundment of the reservoir. Although there is vast experience worldwide in CFRD design and construction, few accurate experimental relationships are available to predict the settlement in CFRD. The goal is to advance the development of intelligent methods to estimate the subsidence of dams at the design stage. Due to dam zonifieation and uncertainties in material properties, these methods appear to be the appropriate choice. In this study, the crest settlement behavior of CFRDs is analyzed based on compiled data of 24 CFRDs constructed during recent years around the world, along with the utilization of gene ex- pression programming （GEP） and adaptive neuro-fuzzy inference system （ANFIS） methods. In addition, dam height （H）, shape factor （St）, and time （t, time after first operation） are also assessed, being considered major factors in predicting the settlement behavior. From the relationships proposed, the values ofR2 for both equations of GEP （with and without constant） were 0.9603 and 0.9734, and for the three approaches of ANFIS （grid partitioning （GP）, subtractive clustering method （SCM）, and fuzzy c-means clustering （FCM）） were 0.9693, 0.8657, and 0.8848, respectively. The obtained results indicate that the overall behavior evaluated by this approach is consistent with the measured data of other CFRDs.
基金supported by Canada First Research Excellence Fund,Medicine by Design(to CMM)。
文摘Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.
基金The work of B. Pang and Z.-P. Jiang has been supported in part by the National Science Foundation (No. ECCS-1501044).
文摘This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discretetime systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing in finite-horizon PI methods are discussed. Then, both data-drive n off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control.
基金supported by the National Natural Science Foundation of China(Grant Nos.61034002,61233001,61273140,61304086,and 61374105)the Beijing Natural Science Foundation,China(Grant No.4132078)
文摘A policy iteration algorithm of adaptive dynamic programming（ADP） is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then,the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks,the developed optimal tracking control scheme for chaotic systems is verified by a simulation.
基金Science and Technology Program of Guangzhou,No.202102010077International Science Foundation of Guangzhou Fuda Cancer Hospital,No.Y2020-ZD-03.
文摘BACKGROUND Irreversible electroporation(IRE)is a novel local tumor ablation approach with the potential to activate the host’s immune system.However,this approach is insufficient to prevent cancer progression,and complementary approaches are required for effective immunotherapy.AIM To assess the immunomodulatory effects and mechanism of IRE combined antiprogrammed cell death protein 1(PD-1)treatment in subcutaneous pancreatic cancer models.METHODS C57BL-6 tumor-bearing mice were randomly divided into four groups:Control group;IRE group;anti-PD-1 group;and IRE+anti-PD-1 group.Tumor-infiltrating T,B,and natural killer cell levels and plasma concentrations of T helper type 1 cytokines(interleukin-2,interferon-γ,and tumor necrosis factor-α)were evaluated.Real-time PCR was used to determine the expression of CD8(marker of CD8+T cells)in tumor tissues of the mice of all groups at different points of time.The growth curves of tumors were drawn.RESULTS The results demonstrated that the IRE+anti-PD-1 group exhibited significantly higher percentages of T lymphocyte infiltration,including CD4+and CD8+T cells compared with the control group.Additionally,the IRE+anti-PD-1 group showed increased infiltration of natural killer and B cells,elevated cytokine levels,and higher CD8 mRNA expression.Tumor volume was significantly reduced in the IRE+anti-PD-1 group,indicating a more pronounced therapeutic effect.CONCLUSION The combination of IRE and anti-PD-1 therapy promotes CD8+T cell immunity responses,leading to a more effective reduction in tumor volume and improved therapeutic outcomes,which provides a new direction for ablation and immunotherapy of pancreatic cancer.
