scholarly journals Generation and compression of a target plasma for magnetized target fusion

1998 ◽  
Author(s):  
R.C. Kirkpatrick ◽  
I.R. Lindemuth ◽  
P.T. Sheehey
Keyword(s):  
Magnetized Target Fusion ◽  
Target Plasma

Target Plasma Formation for Magnetic Compression/Magnetized Target Fusion

1995 ◽  
Vol 75 (10) ◽  
pp. 1953-1956 ◽  
Author(s):  
I. R. Lindemuth ◽  
R. E. Reinovsky ◽  
R. E. Chrien ◽  
J. M. Christian ◽  
C. A. Ekdahl ◽  
...  
Keyword(s):  
Plasma Formation ◽  
Magnetized Target Fusion ◽  
Magnetic Compression ◽  
Target Plasma

ENERGETIC PROTON ACCELERATION BY ULTRAINTENSE LASER PULSES IN INHOMOGENEOUS PLASMA TARGETS

2007 ◽  
Vol 21 (03n04) ◽  
pp. 642-646 ◽  
Author(s):  
A. ABUDUREXITI ◽  
Y. MIKADO ◽  
T. OKADA
Keyword(s):  
Laser Pulse ◽  
Inhomogeneous Plasma ◽  
Laser Pulses ◽  
Proton Acceleration ◽  
Particle In Cell ◽  
Target Plasma ◽  
Plasma Target ◽  
Experimental Process ◽  
Foil Target ◽  
Proton Bunch

Particle-in-Cell (PIC) simulations of fast particles produced by a short laser pulse with duration of 40 fs and an intensity of 1020W/cm2 interacting with a foil target are performed. The experimental process is numerically simulated by considering a triangular concave target illuminated by an ultraintense laser. We have demonstrated increased acceleration and higher proton energies for triangular concave targets. We also determined the optimum target plasma conditions for maximum proton acceleration. The results indicated that a change in the plasma target shape directly affects the degree of contraction accelerated proton bunch.

DESIGN AND FEATURES OF A MAGNETIZED TARGET FUSION EXPERIMENT

2009 ◽  
Author(s):  
T. P. Intrator ◽  
G. A. Wurden ◽  
W. J. Waganaar ◽  
R. Renneke ◽  
M. Kostora ◽  
...  
Keyword(s):  
Magnetized Target Fusion

scholarly journals External Evaluation of Population Pharmacokinetic Models and Bayes-Based Dosing of Infliximab

Pharmaceutics ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1191
Author(s):  
Celine Konecki ◽  
Catherine Feliu ◽  
Yoann Cazaubon ◽  
Delphine Giusti ◽  
Marcelle Tonye-Libyh ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Inflammatory Diseases ◽  
Plasma Concentrations ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Models ◽  
External Evaluation ◽  
Immunomodulatory Treatment ◽  
Weighted Residuals ◽  
Prediction Distribution ◽  
Target Plasma

Despite the well-demonstrated efficacy of infliximab in inflammatory diseases, treatment failure remains frequent. Dose adjustment using Bayesian methods has shown in silico its interest in achieving target plasma concentrations. However, most of the published models have not been fully validated in accordance with the recommendations. This study aimed to submit these models to an external evaluation and verify their predictive capabilities. Eight models were selected for external evaluation, carried out on an independent database (409 concentrations from 157 patients). Each model was evaluated based on the following parameters: goodness-of-fit (comparison of predictions to observations), residual error model (population weighted residuals (PWRES), individual weighted residuals (IWRES), and normalized prediction distribution errors (NPDE)), and predictive performances (prediction-corrected visual predictive checks (pcVPC) and Bayesian simulations). The performances observed during this external evaluation varied greatly from one model to another. The eight evaluated models showed a significant bias in population predictions (from −7.19 to 7.38 mg/L). Individual predictions showed acceptable bias and precision for six of the eight models (mean error of −0.74 to −0.29 mg/L and mean percent error of −16.6 to −0.4%). Analysis of NPDE and pcVPC confirmed these results and revealed a problem with the inclusion of several covariates (weight, concomitant immunomodulatory treatment, presence of anti-drug antibodies). This external evaluation showed satisfactory results for some models, notably models A and B, and highlighted several prospects for improving the pharmacokinetic models of infliximab for clinical-biological application.

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