On-Line Identification of Autonomous Underwater Vehicles through Global Derivative-Free Optimization

We describe the design and implementation of an on-line identification scheme for Autonomous Underwater Vehicles (AUVs). The proposed method estimates the dynamic parameters of the vehicle based on a global derivative-free optimization algorithm. It is not sensitive to initial conditions, unlike other on-line identification schemes, and does not depend on the differentiability of the model with respect to the parameters. The identification scheme consists of three distinct modules: a) System Excitation, b) Metric Calculator and c) Optimization Algorithm. The System Excitation module sends excitation inputs to the vehicle. The Optimization Algorithm module calculates a candidate parameter vector, which is fed to the Metric Calculator module. The Metric Calculator module evaluates the candidate parameter vector, using a metric based on the residual of the actual and the predicted commands. The predicted commands are calculated utilizing the candidate parameter vector and the vehicle state vector, which is available via a complete navigation module. Then, the metric is directly fed back to the Optimization Algorithm module, and it is used to correct the estimated parameter vector. The procedure continues iteratively until the convergence properties are met. The proposed method is generic, demonstrates quick convergence and does not require a linear formulation of the model with respect to the parameter vector. The applicability and performance of the proposed algorithm is experimentally verified using the AUV Girona 500. © 2013 IEEE

ICAR: endoscopic skull‐base surgery

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TRF2 inhibits a cell-extrinsic pathway through which natural killer cells eliminate cancer cells

Dysfunctional telomeres suppress tumour progression by activating cell-intrinsic programs that lead to growth arrest. Increased levels of TRF2, a key factor in telomere protection, are observed in various human malignancies and contribute to oncogenesis. We demonstrate here that a high level of TRF2 in tumour cells decreased their ability to recruit and activate natural killer (NK) cells. Conversely, a reduced dose of TRF2 enabled tumour cells to be more easily eliminated by NK cells. Consistent with these results, a progressive upregulation of TRF2 correlated with decreased NK cell density during the early development of human colon cancer. By screening for TRF2-bound genes, we found that HS3ST4--a gene encoding for the heparan sulphate (glucosamine) 3-O-sulphotransferase 4--was regulated by TRF2 and inhibited the recruitment of NK cells in an epistatic relationship with TRF2. Overall, these results reveal a TRF2-dependent pathway that is tumour-cell extrinsic and regulates NK cell immunity