Joint longitudinal and survival-cure models in tumour xenograft experiments

In tumour xenograft experiments, treatment regimens are administered, and the tumour volume of each individual is measured repeatedly over time. Survival data are recorded because of the death of some individuals during the observation period. Also, cure data are observed because of a portion of individuals who are completely cured in the experiments. When modelling these data, certain constraints have to be imposed on the parameters in the models to account for the intrinsic growth of the tumour in the absence of treatment. Also, the likely inherent association of longitudinal and survival‐cure data has to be taken into account in order to obtain unbiased estimators of parameters. In this paper, we propose such models for the joint modelling of longitudinal and survival‐cure data arising in xenograft experiments. Estimators of parameters in the joint models are obtained using a Markov chain Monte Carlo approach. Real data analysis of a xenograft experiment is carried out, and simulation studies are also conducted, showing that the proposed joint modelling approach outperforms the separate modelling methods in the sense of mean squared errors

An evolutionary algorithm with double-level archives for multiobjective optimization

Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing all the sub-problems simultaneously, there are two issues not fully addressed, i.e., distribution of solutions often depends on a priori problem decomposition, and the lack of population diversity among sub-problems. In this paper, a MOEA with double-level archives is developed. The algorithm takes advantages of both the multiobjective-problemlevel and the sub-problem-level approaches by introducing two types of archives, i.e., the global archive and the sub-archive. In each generation, self-reproduction with the global archive and cross-reproduction between the global archive and sub-archives both breed new individuals. The global archive and sub-archives communicate through cross-reproduction, and are updated using the reproduced individuals. Such a framework thus retains fast convergence, and at the same time handles solution distribution along Pareto front (PF) with scalability. To test the performance of the proposed algorithm, experiments are conducted on both the widely used benchmarks and a set of truly disconnected problems. The results verify that, compared with state-of-the-art MOEAs, the proposed algorithm offers competitive advantages in distance to the PF, solution coverage, and search speed

Electron doping evolution of the magnetic excitations in NaFe1−x_{1-x}Cox_xAs

We use time-of-flight (ToF) inelastic neutron scattering (INS) spectroscopy to investigate the doping dependence of magnetic excitations across the phase diagram of NaFe$_{1-x}$Co$_x$As with $x=0, 0.0175, 0.0215, 0.05,$ and $0.11$. The effect of electron-doping by partially substituting Fe by Co is to form resonances that couple with superconductivity, broaden and suppress low energy ($E\le 80$ meV) spin excitations compared with spin waves in undoped NaFeAs. However, high energy ($E> 80$ meV) spin excitations are weakly Co-doping dependent. Integration of the local spin dynamic susceptibility $\chi^{\prime\prime}(\omega)$ of NaFe$_{1-x}$Co$_x$As reveals a total fluctuating moment of 3.6 $\mu_B^2$/Fe and a small but systematic reduction with electron doping. The presence of a large spin gap in the Co-overdoped nonsuperconducting NaFe$_{0.89}$Co$_{0.11}$As suggests that Fermi surface nesting is responsible for low-energy spin excitations. These results parallel Ni-doping evolution of spin excitations in BaFe$_{2-x}$Ni$_x$As$_2$, confirming the notion that low-energy spin excitations coupling with itinerant electrons are important for superconductivity, while weakly doping dependent high-energy spin excitations result from localized moments.Comment: 14 pages, 16 figure

Phase Separation, Competition, and Volume Fraction Control in NaFe1−x_{1-x}Cox_xAs

We report a detailed nuclear magnetic resonance (NMR) study by combined $^{23}$Na and $^{75}$As measurements over a broad range of doping to map the phase diagram of NaFe$_{1-x}$Co$_x$As. In the underdoped regime ($x \le$ 0.017), we find a magnetic phase with robust antiferromagnetic (AFM) order, which we denote the {\it s}-AFM phase, cohabiting with a phase of weak and possibly proximity-induced AFM order ({\it w}-AFM) whose volume fraction $V \simeq 8$\% is approximately constant. Near optimal doping, at $x = 0.0175$, we observe a phase separation between static antiferromagnetism related to the {\it s}-AFM phase and a paramagnetic (PM) phase related to {\it w}-AFM. The volume fraction of AFM phase increases upon cooling, but both the N{\'e}el temperature and the volume fraction can be suppressed systematically by applying a $c$-axis magnetic field. On cooling below $T_c$, superconductivity occupies the PM region and its volume fraction grows at the expense of the AFM phase, demonstrating a phase separation of the two types of order based on volume exclusion. At higher dopings, static antiferromagnetism and even critical AFM fluctuations are completely suppressed by superconductivity. Thus the phase diagram we establish contains two distinct types of phase separation and reflects a strong competition between AFM and superconducting phases both in real space and in momentum space. We suggest that both this strict mutual exclusion and the robustness of superconductivity against magnetism are consequences of the extreme two-dimensionality of NaFeAs.Comment: 12 pages, 6 figure