We present a method for the optimization of high-order harmonic generation based on wave-front correction of the driving laser beam. The technique exploits wave-front adaptive control by means of a deformable mirror, governed by an optimization procedure.
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http://dx.doi.org/10.1364/ol.29.000207 | DOI Listing |
Environ Int
January 2025
Institute of Atmospheric Environment, Chinese Academy of Environmental Planning, Beijing 100012, China; Center of Synergistic Control for Reducing Pollution and Carbon Emissions, Chinese Academy of Environmental Planning, Beijing 100012, China. Electronic address:
To address the concern of optimization problem of China's PM control and the limitation of computational efficiencies for traditional air quality models, we developed an integrated analysis framework to efficiently establish the identification and cost-benefit assessment of PM control pathways in China by constructing a rapid PM exposure response method based on the high-order decoupled direct method (HDDM) and coupling the sequential least square algorithm (SLSQP) and health impact assessment model. Six emission reduction scenarios with varying decision preferences were analyzed. Our study provides a methodological approach for the rapid optimization of emission pathways of major air pollutants in China with flexible options in terms of objectives and constraints, fully considering the diverse differences in environmental, health, and economic impacts among different pollution sources simultaneously.
View Article and Find Full Text PDFMaterials (Basel)
December 2024
Ulsan Ship and Ocean College, Ludong University, Yantai 264025, China.
This study introduces a novel analytical framework for investigating the vibration characteristics of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) elliptical cylindrical shells under arbitrary boundary conditions. Unlike previous studies that focused on simplified geometries or specific boundary conditions, this work combines the least-squares weighted residual method (LSWRM) with an adapted variational principle, addressing high-order vibration errors and ensuring continuity across structural segments. The material properties are modeled using an extended rule of mixtures, capturing the effects of carbon nanotube volume fractions and distribution types on structural dynamics.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
: The accurate and early distinction of glioblastomas (GBMs) from single brain metastases (BMs) provides a window of opportunity for reframing treatment strategies enabling optimal and timely therapeutic interventions. We sought to leverage physiologically sensitive parameters derived from diffusion tensor imaging (DTI) and dynamic susceptibility contrast (DSC)-perfusion-weighted imaging (PWI) along with machine learning-based methods to distinguish GBMs from single BMs. : Patients with histopathology-confirmed GBMs ( = 62) and BMs ( = 26) and exhibiting contrast-enhancing regions (CERs) underwent 3T anatomical imaging, DTI and DSC-PWI prior to treatment.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
Université Paris-Saclay, CNRS, Institut des Sciences Moléculaires d'Orsay, 91405 Orsay, France.
We present the design of a VMI spectrometer optimized for attosecond spectroscopy in the 0-40 eV energy range. It is based on a compact three-electrode configuration where the lens shape, size, and material have been optimized using numerical simulations to improve the spectral resolution by a factor of ∼5 relative to the initial design [Eppink and Parker, Rev. Sci.
View Article and Find Full Text PDFEntropy (Basel)
December 2024
School of Mathematics, Renmin University of China, Beijing 100872, China.
Maximum correntropy criterion (MCC) has been an important method in machine learning and signal processing communities since it was successfully applied in various non-Gaussian noise scenarios. In comparison with the classical least squares method (LS), which takes only the second-order moment of models into consideration and belongs to the convex optimization problem, MCC captures the high-order information of models that play crucial roles in robust learning, which is usually accompanied by solving the non-convexity optimization problems. As we know, the theoretical research on convex optimizations has made significant achievements, while theoretical understandings of non-convex optimization are still far from mature.
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