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Single-cell RNA-sequencing (scRNA-seq) stands as a powerful tool for deciphering cellular heterogeneity and exploring gene expression profiles at high resolution. However, its high cost renders it impractical for extensive sample cohorts…

A new double time-of-flight (dTOF) neutron spectroscopy technique has been developed for pulsed broad spectrum sources with a duty cycle that results in frame overlap, where fast neutrons from a given pulse overtake slower neutrons from…

Instrumentation and Detectors · Physics 2020-10-07 K. P. Harrig , B. L. Goldblum , J. A. Brown , D. L. Bleuel , L. A. Bernstein , J. Bevins , M. Harasty , T. A. Laplace , E. F. Matthews

The standard model predicts that, in addition to a proton, an electron, and an antineutrino, a continuous spectrum of photons is emitted in the $\beta$ decay of the free neutron. We report on the RDK II experiment which measured the photon…

The neutrinos detected from the next Galactic core-collapse supernova will contain valuable information on the internal dynamics of the explosion. One mechanism leading to a temporal evolution of the neutrino signal is the variation of the…

Astrophysics · Physics 2008-11-26 James P. Kneller , Gail C. McLaughlin , Justin Brockman

The UCNA experiment was designed to measure the neutron $\beta$-asymmetry parameter $A_0$ using polarized ultracold neutrons (UCN). UCN produced via downscattering in solid deuterium were polarized via transport through a 7 T magnetic…

We present a new experimental method for measuring the process of Coherent Elastic Neutrino Nucleus Scattering (CENNS). This method uses a detector situated transverse to a high energy neutrino beam production target. This detector would be…

We present a new approach to Nuclear Quadrupole Resonance (NQR)/Nuclear Magnetic Resonance (NMR) spectroscopy, the Damp-Enhanced Superregenerative Nuclear Spin Analyser (DESSA). This system integrates Superregenerative principles with…

Instrumentation and Detectors · Physics 2023-12-15 Tomas Sikorsky , Andrzej Pelczar , Stephan Schneider , Thorsten Schumm

Superfluid neutron matter is a key ingredient in the composition of neutron stars. The physics of the inner crust is largely dependent on that of its $S$-wave neutron superfluid which has made its presence known through pulsar glitches and…

Nuclear Theory · Physics 2021-02-03 Georgios Palkanoglou , Alexandros Gezerlis

I calculate the diffuse flux of electron antineutrinos from all supernovae using the information on the neutrino spectrum from SN987A and the information on the rate of supernovae from direct supernova observations. The interval of flux…

Astrophysics · Physics 2009-11-13 Cecilia Lunardini

In this paper we describe the development and first tests of a neutron spectrometer designed for high flux environments, such as the ones found in fast nuclear reactors. The spectrometer is based on the conversion of neutrons impinging on…

Instrumentation and Detectors · Physics 2015-12-09 M. Osipenko , M. Ripani , G. Ricco , B. Caiffi , F. Pompili , M. Pillon , M. Angelone , G. Verona-Rinati , R. Cardarelli , G. Mila , S. Argiro

The spallation neutrons were produced by the irradiation of Pb with 250 MeV protons. The Pb target was surrounded by water which was used to slow down the emitted neutrons. The moderated neutrons in the water bath were measured by using the…

Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the science return of these observations in the absence of…

Cosmology and Nongalactic Astrophysics · Physics 2023-09-11 Helen Qu , Masao Sako

Calculations of neutral-current neutrino-nucleus scattering cross sections are important for interpreting low- and intermediate-energy neutrino data, where terrestrial measurements remain limited. The first observation of coherent elastic…

High Energy Physics - Phenomenology · Physics 2026-05-18 Muhammad Farooq , Shakeel Mahmood , Muhammad Faisal Khan

Novel multiplexing triple-axis neutron scattering spectrometers yield significant improvements of the common triple-axis instruments. While the planar scattering geometry keeps ensuring compatibility with complex sample environments, a…

Data Analysis, Statistics and Probability · Physics 2026-03-02 Jakob Lass , Henrik Jacobsen , Daniel G. Mazzone , Kim Lefmann

The field of Radiation Oncology is uniquely positioned to benefit from the use of artificial intelligence to fully automate the creation of radiation treatment plans for cancer therapy. This time-consuming and specialized task combines…

Image and Video Processing · Electrical Eng. & Systems 2024-10-15 Kuancheng Wang , Hai Siong Tan , Rafe Mcbeth

The precise measurement of the antineutrino spectra produced by isotope fission in reactors is of great significance for studying neutrino oscillations, refining nuclear databases, and addressing the reactor antineutrino anomaly. In this…

High Energy Physics - Phenomenology · Physics 2025-04-10 Jian Chen , Jun Wang , Wei Wang , Yuehuan Wei

Accurate segmentation is a crucial step in medical image analysis and applying supervised machine learning to segment the organs or lesions has been substantiated effective. However, it is costly to perform data annotation that provides…

Computer Vision and Pattern Recognition · Computer Science 2021-10-29 Yunxiang Li , Jingxiong Li , Ruilong Dan , Shuai Wang , Kai Jin , Guodong Zeng , Jun Wang , Xiangji Pan , Qianni Zhang , Huiyu Zhou , Qun Jin , Li Wang , Yaqi Wang

Direct numerical simulations (DNS) of turbulent channel flows up to $Re_{\tau} \approx 1000$ are conducted to investigate the three-dimensional (consisting of streamwise wavenumber, spanwise wavenumber and frequency) spectrum of wall…

Fluid Dynamics · Physics 2022-03-14 Bowen Yang , Zixuan Yang

Mass spectrometry is a powerful and widely used tool for identifying molecular structures due to its sensitivity and ability to profile complex samples. However, translating spectra into full molecular structures is a difficult,…

Machine Learning · Computer Science 2026-03-13 Ghaith Mqawass , Tuan Le , Fabian Theis , Djork-Arné Clevert

Recent works have highlighted scale invariance or symmetry present in the weight space of a typical deep network and the adverse effect it has on the Euclidean gradient based stochastic gradient descent optimization. In this work, we show…

Machine Learning · Computer Science 2015-11-04 Vijay Badrinarayanan , Bamdev Mishra , Roberto Cipolla
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