Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury

PurposeTo study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements.Methods and MaterialsThe brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; VD with different D for different distributions). Predictive ability of EUDVD (EUD of VD) for radiation-induced brain injury was assessed by receiver operating characteristics curve (ROC) and area under the curve (AUC). The optimal volume-effect parameter a of EUD was selected when AUC was maximal (mAUC). Correlations between mAUC, a and D were analyzed by Pearson correlation analysis. Both mAUC and a in brain and half-brain were compared by using paired samples t-tests. The optimal DV and VD points were selected for a simple comparison.ResultsThe mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal a value was 21.5/22. When D increased, mAUC of EUDVD increased, while a decreased. The mAUC reached the maximum value when D was 50–55 Gy, and a was always 1 when D ≥55 Gy. The difference of mAUC/a between brain and half-brain was not significant. If a was in range of 1 to 22, AUC of brain/half-brain EUDV55 Gy (0.857–0.830/0.845–0.830) was always larger than that of brain/half-brain EUD (0.681–0.819/0.691–0.821). The AUCs of optimal dose/volume points were 0.801 (brain D2.5 cc), 0.823 (brain V70 Gy), 0.818 (half-brain D1 cc), and 0.827 (half-brain V69 Gy), respectively. Mean dose (equal to EUDVD with a = 1) of high-dose volume (V50 Gy–V60 Gy) was superior to traditional EUD and dose/volume points.ConclusionVolume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability.

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

The Diffusion Isotope Effect and Diffusion Mechanism in Liquid Cu-Ag and Cu-Ni Alloys

In this paper, the diffusion isotope effect and diffusion mechanism are investigated by means of molecular dynamics simulations in two liquid alloys, Ni-Ag and Ni-Cu. The values for the diffusion isotope effect parameter allow for the estimate of the number of atoms which are moving cooperatively in a basic diffusion event as experienced by a given atomic species. It is shown that the composition dependence of ND is typically very small. However, the temperature dependence of this parameter is much more pronounced. In addition, it is shown that, on average, in these alloys and temperatures considered, ND is limited to the range: 5<ND<17. This is consistent with results of molecular dynamics simulations on the average coordination number calculations. This would suggest that, together with a given atom, depending on temperature, the neighbouring atoms are all involved in the basic diffusion event.

Dynamic Analysis of Social Networks of Learners’ Online Peers1 Interaction Behavior in Smoking Cession Education

Objectives: We investigated the dynamic changes in the impact of online peer support on individual behavior, using the online smoking cessation community as an example. Methods: This study included a longitudinal sample of 52 adolescents (aged 17-21) who volunteered to quit smoking in an online smoking cessation community. We described an actor-based model for online friendship network-smoking cessation behavior co-evolution, using social network dynamic analysis to study the interaction between learners to explore the impact of online peer support on adolescent smoking cessation behavior. Results: Three RSiena models exhibited high goodness of fit in the structural effect part (The estimated values of the three reciprocity effect parameters were 1.7067, 1.07384, and 1.07401, respectively). The estimated value of the in-degree effect parameter of smoking cessation behavior influenced by network structure was 0.0934. Conclusions: Online peer support has a significant impact on the propensity for adolescents to select offline friends. The more online peers’ support, the better results of teenagers online smoking cessation. Online peer support significantly affects the changes in individual behaviors.

Generalized r-Lambert Function in the Analysis of Fixed Points and Bifurcations of Homographic 2-Ricker Maps

This paper aims to study the nonlinear dynamics and bifurcation structures of a new mathematical model of the [Formula: see text]-Ricker population model with a Holling type II per-capita birth function, where the Allee effect parameter is [Formula: see text]. A generalized [Formula: see text]-Lambert function is defined on the 3D parameters space to determine the existence and variation of the number of nonzero fixed points of the homographic [Formula: see text]-Ricker maps considered. The singularity points of the generalized [Formula: see text]-Lambert function are identified with the cusp points on a fold bifurcation of the homographic [Formula: see text]-Ricker maps. In this approach, the application of the transcendental generalized [Formula: see text]-Lambert function is demonstrated based on the analysis of local and global bifurcation structures of this three-parameter family of homographic maps. Some numerical studies are included to illustrate the theoretical results.