dynamic parameter
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2022 ◽  
Vol 8 ◽  
Author(s):  
Haris Omić ◽  
Johannes Phillip Kläger ◽  
Harald Herkner ◽  
Stephan W. Aberle ◽  
Heinz Regele ◽  
...  

Introduction: The absolute BK viral load is an important diagnostic surrogate for BK polyomavirus associated nephropathy (PyVAN) after renal transplant (KTX) and serial assessment of BK viremia is recommended. However, there is no data indicating which particular viral load change, i.e., absolute vs. relative viral load changes (copies/ml; percentage of the preceding viremia) is associated with worse renal graft outcomes.Materials and Methods: In this retrospective study of 91 biopsy proven PyVAN, we analyzed the interplay of exposure time, absolute and relative viral load kinetics, baseline risk, and treatment strategies as risk factors for graft loss after 2 years using a multivariable Poisson-model.Results: We compared two major treatment strategies: standardized immunosuppression (IS) reduction (n = 53) and leflunomide (n = 30). The median viral load at the index biopsy was 2.15E+04 copies/ml (interquartile range [IQR] 1.70E+03–1.77E+05) and median peak viremia was 3.6E+04 copies/ml (IQR 2.7E+03–3.3E+05). Treatment strategies and IS-levels were not related to graft loss. After correction for baseline viral load and estimated glomerular filtration rate (eGFR), absolute viral load decrease/unit remained an independent risk factor for graft loss [incidence rate ratios [IRR] = 0.77, (95% CI 0.61–0.96), p = 0.02].Conclusion: This study provides evidence for the prognostic importance of absolute BK viremia kinetics as a dynamic parameter indicating short-term graft survival independently of other established risk factors.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Qihui Ling ◽  
Juchuan Dai ◽  
Xingyun He ◽  
Shengzhao Chen ◽  
Zhewu Chen

The dynamic parameter allocation of the suspension system has an important influence on the comprehensive driving performance of the tracked vehicle. Usually, the allocation of suspension parameters is based on a single performance index, which has the disadvantage of not being able to achieve multi-performance optimization. Therefore, a novel optimization method using multi-performance index-oriented is presented. Firstly, considering the vertical vibration excitation caused by road roughness, the input (excitation) model of road roughness is embedded to establish the parametric dynamic model of the tracked vehicle. Then, the evaluation index and its quantitative algorithm, which reflect the multi-aspect performance of the suspension system, are proposed. Moreover, the parameter allocation objective function based on multi-index information fusion is designed. Finally, two allocation optimization methods are presented to solve the parameter allocation, i.e., equal weight allocation and expert knowledge-based weight allocation. By comparing the results obtained by the two methods, it is found that the performance of the suspension system can be improved effectively by optimizing the parameters of suspension stiffness and damping. Furthermore, the optimization of weight allocation based on expert knowledge is more effective. These provide a better knowledge reference for suspension system design.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Quentin Sabbagh ◽  
Gwennan André-Grégoire ◽  
Carolina Alves-Nicolau ◽  
Aurélien Dupont ◽  
Nicolas Bidère ◽  
...  

AbstractGlioblastoma is a devastating tumor of the central nervous system characterized by a poor survival and an extremely dark prognosis, making its diagnosis, treatment and monitoring highly challenging. Numerous studies have highlighted extracellular vesicles (EVs) as key players of tumor growth, invasiveness and resistance, as they carry and disseminate oncogenic material in the local tumor microenvironment and at distance. However, whether their quality and quantity reflect individual health status and changes in homeostasis is still not fully elucidated. Here, we separated EVs from plasma collected at different time points alongside with the clinical management of GBM patients. Our findings confirm that plasmatic EVs could be separated and characterized with standardized protocols, thereby ensuring the reliability of measuring vesiclemia, i.e. extracellular vesicle concentration in plasma. This unveils that vesiclemia is a dynamic parameter, which could be reflecting tumor burden and/or response to treatments. Further label-free liquid chromatography tandem mass spectrometry unmasks the von Willebrand Factor (VWF) as a selective protein hallmark for GBM-patient EVs. Our data thus support the notion that EVs from GBM patients showed differential protein cargos that can be further surveyed in circulating EVs, together with vesiclemia.


2021 ◽  
Vol 11 (22) ◽  
pp. 10988
Author(s):  
Jun Cheng ◽  
Shusheng Bi ◽  
Chang Yuan ◽  
Lin Chen ◽  
Yueri Cai ◽  
...  

At present, the absolute positioning accuracy and control accuracy of industrial serial robots need to be improved to meet the accuracy requirements of precision manufacturing and precise control. An accurate dynamic model is an important theoretical basis for solving this problem, and precise dynamic parameters are the prerequisite for precise control. The research of dynamics and parameter identification can greatly promote the application of robots in the field of precision manufacturing and automation. In this paper, we study the dynamical modeling and dynamic parameter identification of an industrial robot system with six rotational DOF (6R robot system) and propose a new method for identifying dynamic parameters. Our aim is to provide an accurate mathematical description of the dynamics of the 6R robot and to accurately identify its dynamic parameters. First, we establish an unconstrained dynamic model for the 6R robot system and rewrite it to obtain the dynamic parameter identification model. Second, we establish the constraint equations of the 6R robot system. Finally, we establish the dynamic model of the constrained 6R robot system. Through the ADAMS simulation experiment, we verify the correctness and accuracy of the dynamic model. The experiments prove that the result of parameter identification has extremely high accuracy and the dynamic model can accurately describe the 6R robot system mathematically. The dynamic modeling method proposed in this paper can be used as the theoretical basis for the study of 6R robot system dynamics and the study of dynamics-based control theory.


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