Time-resolved dosimetric verification of respiratory-gated radiotherapy exposures using a high-resolution 2D ionisation chamber array

The aim of this work was to track and verify the delivery of respiratory-gated irradiations, performed with three versions of TrueBeam linac, using a novel phantom arrangement that combined the OCTAVIUS® SRS 1000 array with a moving platform. The platform was programmed to generate sinusoidal motion of the array. This motion was tracked using the real-time position management (RPM) system and four amplitude gating options were employed to interrupt MV beam delivery when the platform was not located within set limits. Time-resolved spatial information extracted from analysis of x-ray fluences measured by the array was compared to the programmed motion of the platform and to the trace recorded by the RPM system during the delivery of the x-ray field. Temporal data recorded by the phantom and the RPM system were validated against trajectory log files, recorded by the linac during the irradiation, as well as oscilloscope waveforms recorded from the linac target signal. Gamma analysis was employed to compare time-integrated 2D x-ray dose fluences with theoretical fluences derived from the probability density function for each of the gating settings applied, where gamma criteria of 2%/2 mm, 1%/1 mm and 0.5%/0.5 mm were used to evaluate the limitations of the RPM system. Excellent agreement was observed in the analysis of spatial information extracted from the SRS 1000 array measurements. Comparisons of the average platform position with the expected position indicated absolute deviations of  <0.5 mm for all four gating settings. Differences were observed when comparing time-resolved beam-on data stored in the RPM files and trajectory logs to the true target signal waveforms. Trajectory log files underestimated the cycle time between consecutive beam-on windows by 10.0  ±  0.8 ms. All measured fluences achieved 100% pass-rates using gamma criteria of 2%/2 mm and 50% of the fluences achieved pass-rates  >90% when criteria of 0.5%/0.5 mm were used. Results using this novel phantom arrangement indicate that the RPM system is capable of accurately gating x-ray exposure during the delivery of a fixed-field treatment beam.

Fuzzy logic-based implicit authentication for mobile access control

In order to address the increasing compromise of user privacy on mobile devices, a Fuzzy Logic based implicit authentication scheme is proposed in this paper. The proposed scheme computes an aggregate score based on selected features and a threshold in real-time based on current and historic data depicting user routine. The tuned fuzzy system is then applied to the aggregated score and the threshold to determine the trust level of the current user. The proposed fuzzy-integrated implicit authentication scheme is designed to: operate adaptively and completely in the background, require minimal training period, enable high system accuracy while provide timely detection of abnormal activity. In this paper, we explore Fuzzy Logic based authentication in depth. Gaussian and triangle-based membership functions are investigated and compared using real data over several weeks from different Android phone users. The presented results show that our proposed Fuzzy Logic approach is a highly effective, and viable scheme for lightweight real-time implicit authentication on mobile devices.

Life expectancy for community-based patients with heart failure from time of diagnosis

AIMS: Heart failure has been demonstrated in previous studies to have a dismal prognosis. However, the modern-day prognosis of patients with new onset heart failure diagnosed in the community managed within a disease management programme is not known. The purpose of this study is to report on prognosis of patients presenting with new onset heart failure in the community who are subsequently followed in a disease management program.

METHODS AND RESULTS: A review of patients referred to a rapid access heart failure diagnostic clinic between 2002 and 2012 was undertaken. Details of diagnosis, demographics, medical history, medications, investigations and mortality data were analysed. A total of 733 patients were seen in Rapid Access Clinic for potential new diagnosis of incident of heart failure. 38.9% (n=285) were diagnosed with heart failure, 40.7% (n=116) with HF-REF and 59.3% (n=169) with HF-PEF. There were 84 (29.5%) deaths in the group of patients diagnosed with heart failure; 41 deaths (35.3%) occurred in patients with HF-REF and 43 deaths (25.4%) occurred in patients with HF-PEF. In patients with heart failure, 52.4% (n=44) died from cardiovascular causes. 63.8% of HF patients were alive after 5 years resulting on average in a month per year loss of life expectancy over that period compared with aged matched simulated population.

CONCLUSIONS: In this community-based cohort, the prognosis of heart failure was better than reported in previous studies. This is likely due to the impact of prompt diagnosis, the improvement in therapies and care within a disease management structure.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.