Comparison of carboplatin and doxorubicin-based chemotherapy protocols in 470 dogs after amputation for treatment of appendicular osteosarcoma.

BackgroundMany chemotherapy protocols have been reported for treatment of canine appendicular osteosarcoma (OSA), but outcome comparisons in a single population are lacking.ObjectiveTo evaluate the effects of protocol and dose intensity (DI) on treatment outcomes for carboplatin and doxorubicin-based chemotherapy protocols.AnimalsFour hundred and seventy dogs with appendicular OSA.MethodsA retrospective cohort study was performed comprising consecutive dogs treated (1997-2012) with amputation followed by 1 of 5 chemotherapy protocols: carboplatin 300 mg/m(2) IV q21d for 4 or 6 cycles (CARBO6), doxorubicin 30 mg/m(2) IV q14d or q21d for 5 cycles, and alternating carboplatin 300 mg/m(2) IV and doxorubicin 30 mg/m(2) IV q21d for 3 cycles. Adverse events (AE) and DI were evaluated. Kaplan-Meier survival curves and Cox proportional hazards regression were used to compare disease-free interval (DFI) and survival time (ST) among protocols.ResultsThe overall median DFI and ST were 291 days and 284 days, respectively. A lower proportion of dogs prescribed CARBO6 experienced AEs compared to other protocols (48.4% versus 60.8-75.8%; P = .001). DI was not associated with development of metastases or death. After adjustment for baseline characteristics and prognostic factors, none of the protocols provided a significant reduction in risk of development of metastases or death.Conclusions and clinical importanceAlthough choice of protocol did not result in significant differences in DFI or ST, the CARBO6 protocol resulted in a lower proportion of dogs experiencing AEs, which could be advantageous in maintaining high quality of life during treatment. DI was not a prognostic indicator in this study

Real-Time Implementation of Intelligent Actuator Control with a Transducer Health Monitoring Capability

This paper presents a concept of feedback control for smart actuators that are compatible with smart sensors, communication protocols, and a hierarchical Integrated System Health Management (ISHM) architecture developed by NASA s Stennis Space Center. Smart sensors and actuators typically provide functionalities such as automatic configuration, system condition awareness and self-diagnosis. Spacecraft and rocket test facilities are in the early stages of adopting these concepts. The paper presents a concept combining the IEEE 1451-based ISHM architecture with a transducer health monitoring capability to enhance the control process. A control system testbed for intelligent actuator control, with on-board ISHM capabilities, has been developed and implemented. Overviews of the IEEE 1451 standard, the smart actuator architecture, and control based on this architecture are presented

Formation Control of Nonlinear Multi-Agent Systems Using Three-Layer Neural Networks

This paper considers a leader-following formation control problem for heterogeneous, second-order, uncertain, input-affine, nonlinear multi-agent systems modeled by a directed graph. A tunable, three-layer neural network (NN) is proposed with an input layer, two hidden layers, and an output layer to approximate an unknown nonlinearity. Unlike commonly used trial and error efforts to select the number of neurons in a conventional NN, in this case an \textit{a priori} knowledge allows one to set up the number of neurons in each layer. The NN weights tuning laws are derived using the Lyapunov theory. The leader-following and formation control problems are addressed by a robust integral of the sign of the error (RISE) feedback and a NN-based control. The RISE feedback term compensates for unknown leader dynamics and the unknown, bounded disturbance in the agent error dynamics. The NN-based term compensates for the unknown nonlinearity in the dynamics of multi-agent systems, and semi-global asymptotic tracking results are rigorously proven using the Lyapunov stability theory. The results of the paper are compared with two previous results to evaluate the efficiency and performance of the proposed method.Comment: 12 pages, 11 figures, submitted to IEEE Transactions on Neural Networks and Learning System

The European Central Bank, machinic enslavement, and the Greek public sector

This article investigates the role of the European Central Bank (ECB) in transferring financial and moral responsibility for the Eurozone crisis from the private to the public sector. Focusing on Greece, I argue that the ECB constructed the morality of the public debtor in such a way as to make this transfer of responsibility easier and the imposition of austerity measures justifiable. This in part relied on a shift in the ECB’s discourse, which came to define the crisis exclusively in terms of public sector responsibility. However, the ECB also employed a range of non-linguistic policy measures aimed at intervening in the crisis. To interpret these measures I draw on Deleuze and Guattari’s concept of ‘machinic enslavement’, arguing that the ECB contributed to the Greek crisis not only by defining it discursively but also by reshaping the country’s financial infrastructure in crucial ways

Wireless Sensor Networks Fault Detection and Identification

We have developed and experimentally tested a set of models for the detection and identification of sensor faults that commonly occur in wireless sensor networks. Considered faults include outlier, spike, variance, high-frequency noise, offset, gain, and drift faults. These faults affect the system operations and can endanger operators, final users, and the general public. The fault detection models are divided into two classes: data-centric models, which only analyze a single data stream, and system-centric models, which consider the overall system. For data-centric models, we use the magnitude, the gradient, and the variance of raw sensor data to model faults. For system-centric models, we introduce variogram-based techniques that allow faults to be detected by comparing readings from multiple sensors that measure related phenomena. For data-centric and system-centric sensor fault detection, we show how a few model parameters affect the sensitivity of wireless sensor network fault models. We present simulation and experimental results that illustrate the fault detection and identification models. The system is intended for health monitoring applications of the NASA Stennis Space Center (SSC) test stands and widely distributed support systems, including pressurized gas lines, propellant delivery systems, and water coolant lines. The testbed consists of Coremicro® reconfigurable embedded smart sensor nodes [29] capable of wireless communication, a network-capable application processor, a wireless base station, the software that supports sensor and actuator health monitoring, a database server, and a smartphone running a health monitoring Android application