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http://dx.doi.org/10.1385/1-59259-184-1:317 | DOI Listing |
Rev Sci Instrum
September 2025
LAPLACE, Université de Toulouse, CNRS, INPT, UPS, 118 route de Narbonne, 31062 Toulouse, France.
A two-axis thrust stand is developed and validated experimentally, enabling direct and simultaneous measurements of two components of the thrust vector of an electric thruster. It is made of two piled-up single-axis stages, each having a hanging deformable parallelogram geometry. A mass deposition calibration method is used to calibrate the thrust stand, including crosstalk between axes.
View Article and Find Full Text PDFComput Biol Med
September 2025
Postgraduate Program in Computing, Center for Technological Development, Federal University of Pelotas, Pelotas, 96010-610, Rio Grande do Sul, Brazil.
In the task of image classification for emotion recognition, facial expression data is commonly used. However, electrical brain signals generated by neural activity provide data with greater integrity. We can capture these signals non-invasively using electroencephalogram (EEG) recording devices.
View Article and Find Full Text PDFActa Crystallogr E Crystallogr Commun
September 2025
College of Materials Science and Opto-electronic Technology University of Chinese Academy of Sciences, Huairou Beijing 101408 People's Republic of China.
The title complex, [Fe(CHN)(CHN)]·3CH, possesses inversion symmetry with the iron(II) atom located on a center of symmetry. The metal atom is coordinated in a symmetric octa-hedral geometry by four pyrrole N atoms of the porphyrin ligand in the equatorial plane and two N atoms of 1-methyl-imidazole ligands in the axial sites; the complex crystallizes with three toluene solvent mol-ecules. The average Fe-N (N is a porphyrin N atom) bond length is 1.
View Article and Find Full Text PDFAnn Stat
February 2025
Department of Statistics, Pennsylvania State University.
Random objects are complex non-Euclidean data taking values in general metric spaces, possibly devoid of any underlying vector space structure. Such data are becoming increasingly abundant with the rapid advancement in technology. Examples include probability distributions, positive semidefinite matrices and data on Riemannian manifolds.
View Article and Find Full Text PDFSci Rep
September 2025
Department of Research Analytics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
Complex geometries achievable with resin-based 3D printing are susceptible to lower levels of surface roughness, particularly in areas where support structures are attached and removed. The slicing parameter serves as the cornerstone for developing a model for predicting the corresponding output. In the present research, a resin 3D printer is used to fabricate the specimens in accordance with the combination of important parameters that were recovered utilizing the design of the experiment (DoE).
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