We present a technique for simultaneous power-combining and wavelength-conversion of multiple fiber lasers into a single, longer wavelength in a different band through Raman-based, nonlinear power combining. We illustrate this by power combining of two independent Ytterbium lasers into a single wavelength around 1.5micron with high output powers of upto 99W. A high conversion efficiency of ~64% of the quantum limited efficiency and a high level of wavelength conversion with >85% of the output power in the final wavelength is demonstrated. The proposed method enables power-scaling in various wavelength bands where conventional fiber lasers are unavailable or limited in power.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1364/OE.26.004954 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Department of Environmental Health Sciences and Technology, Institute of Health, Jimma University, Jimma, Ethiopia.
Recycling excreta resources through resource-oriented toilet systems (ROTS) holds transformative potential, yet adoption remains limited, especially where benefits could be high. This study aims to understand constraints hindering the adoption of ROTS in one such area in Ethiopia. Based on a survey among 476 households comprising 2393 individuals, we examine the plans to use ROTS and willingness to pay for ROTS and apply structural equation modelling to analyze the drivers of these two outcomes while comparing the explanative power of the extended technology acceptance model, extended theory of planned behaviour, and their combined model.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Radiology, Radiotherapy and Hematology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
In a previous preliminary study, radiomic features from the largest and the hottest lesion in baseline F-FDG PET/CT (bPET/CT) of classical Hodgkin's Lymphoma (cHL) predicted early response-to-treatment and prognosis. Aim of this large retrospectively-validated study is to evaluate the predictive role of two-lesions radiomics in comparison with other clinical and conventional PET/CT models. cHL patients with bPET/CT between 2010 and 2020 were retrospectively included and randomized into training-validation sets.
View Article and Find Full Text PDFRev Sci Instrum
January 2025
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA.
This work describes the design and implementation of optics for EXCLAIM, the EXperiment for Cryogenic Large-Aperture Intensity Mapping. EXCLAIM is a balloon-borne telescope that will measure integrated line emission from carbon monoxide at redshifts z < 1 and ionized carbon ([CII]) at redshifts z = 2.5 - 3.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry, University of British Columbia, Vancouver, British Columbia V6T 1Z1, Canada.
We present an algorithm that combines quantum scattering calculations with probabilistic machine-learning models to predict quantum dynamics rate coefficients for a large number of state-to-state transitions in molecule-molecule collisions much faster than with direct solutions of the Schrödinger equation. By utilizing the predictive power of Gaussian process regression with kernels, optimized to make accurate predictions outside of the input parameter space, the present strategy reduces the computational cost by about 75%, with an accuracy within 5%. Our method uses temperature dependences of rate coefficients for transitions from the isolated states of initial rotational angular momentum j, determined via explicit calculations, to predict the temperature dependences of rate coefficients for other values of j.
View Article and Find Full Text PDFJ Dent Sci
December 2024
Blood Transfusion Haematology Hospital No. 2, Ho Chi Minh City, Viet Nam.
Background/purpose: Oral squamous cell carcinoma (OSCC) is notorious for its low survival rates, due to the advanced stage at which it is commonly diagnosed. To enhance early detection and improve prognostic assessments, our study harnesses the power of machine learning (ML) to dissect and interpret complex patterns within mRNA-sequencing (RNA-seq) data and clinical-histopathological features.
Materials And Methods: 206 retrospective Vietnamese OSCC formalin-fixed paraffin-embedded (FFPE) tumor samples, of which 101 were subjected to RNA-seq for classification based on gene expression.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!