Accelerator Measurements of Magnetically Induced Radio Emission from Particle Cascades with Applications to Cosmic-Ray Air Showers

For 50 years, cosmic-ray air showers have been detected by their radio emission. We present the first laboratory measurements that validate electrodynamics simulations used in air shower modeling. An experiment at SLAC provides a beam test of radio-frequency (rf) radiation from charged particle cascades in the presence of a magnetic field, a model system of a cosmic-ray air shower. This experiment provides a suite of controlled laboratory measurements to compare to particle-level simulations of rf emission, which are relied upon in ultrahigh-energy cosmic-ray air shower detection. We compare simulations to data for intensity, linearity with magnetic field, angular distribution, polarization, and spectral content. In particular, we confirm modern predictions that the magnetically induced emission in a dielectric forms a cone that peaks at the Cherenkov angle and show that the simulations reproduce the data within systematic uncertainties

Mesonic screening masses at high temperature and finite density

We compute the first perturbative correction to the static correlation lengths of light quark bilinears in hot QCD with finite quark chemical potentials. The correction is small and positive, with mu-dependence depending on the relative sign of chemical potentials and the number of dynamical flavors. The computation is carried out using a three-dimensional effective theory for the lowest fermionic Matsubara mode. We also compute the full correlator in free theory and find a rather complicated general mu-dependence at shorter distances. Finally, rough comparisons with lattice simulations are discussed.Comment: 24 pages, 5 figures, JHEP style. Minor corrections and clarifications, version to appear in JHE

Picosecond timing of Microwave Cherenkov Impulses from High-Energy Particle Showers Using Dielectric-loaded Waveguides

We report on the first measurements of coherent microwave impulses from high-energy particle-induced electromagnetic showers generated via the Askaryan effect in a dielectric-loaded waveguide. Bunches of 12.16 GeV electrons with total bunch energy of $\sim 10^3-10^4$ GeV were pre-showered in tungsten, and then measured with WR-51 rectangular (12.6 mm by 6.3 mm) waveguide elements loaded with solid alumina ($Al_2 O_3$) bars. In the 5-8 GHz $TE_{10}$ single-mode band determined by the presence of the dielectric in the waveguide, we observed band-limited microwave impulses with amplitude proportional to bunch energy. Signals in different waveguide elements measuring the same shower were used to estimate relative time differences with 2.3 picosecond precision. These measurements establish a basis for using arrays of alumina-loaded waveguide elements, with exceptional radiation hardness, as very high precision timing planes for high-energy physics detectors.Comment: 16 pages, 15 figure

Accelerator measurements of magnetically-induced radio emission from particle cascades with applications to cosmic-ray air showers

For fifty years, cosmic-ray air showers have been detected by their radio emission. We present the first laboratory measurements that validate electrodynamics simulations used in air shower modeling. An experiment at SLAC provides a beam test of radio-frequency (RF) radiation from charged particle cascades in the presence of a magnetic field, a model system of a cosmic-ray air shower. This experiment provides a suite of controlled laboratory measurements to compare to particle-level simulations of RF emission, which are relied upon in ultra-high-energy cosmic-ray air shower detection. We compare simulations to data for intensity, linearity with magnetic field, angular distribution, polarization, and spectral content. In particular, we confirm modern predictions that the magnetically induced emission in a dielectric forms a cone that peaks at the Cherenkov angle and show that the simulations reproduce the data within systematic uncertainties.Comment: 5 pages, 7 figure

Development Toward a Ground-Based Interferometric Phased Array for Radio Detection of High Energy Neutrinos

The in-ice radio interferometric phased array technique for detection of high energy neutrinos looks for Askaryan emission from neutrinos interacting in large volumes of glacial ice, and is being developed as a way to achieve a low energy threshold and a large effective volume at high energies. The technique is based on coherently summing the impulsive Askaryan signal from multiple antennas, which increases the signal-to-noise ratio for weak signals. We report here on measurements and a simulation of thermal noise correlations between nearby antennas, beamforming of impulsive signals, and a measurement of the expected improvement in trigger efficiency through the phased array technique. We also discuss the noise environment observed with an analog phased array at Summit Station, Greenland, a possible site for an interferometric phased array for radio detection of high energy neutrinos.Comment: 13 Pages, 14 Figure

The splicing co-factor Barricade/Tat-SF1, is required for cell cycle and lineage progression in Drosophila neural stem cells

Stem cells need to balance self-renewal and differentiation for correct tissue development and homeostasis. Defects in this balance can lead to developmental defects or tumor formation. In recent years, mRNA splicing has emerged as one important mechanism regulating cell fate decisions. Here we address the role of the evolutionary conserved splicing co-factor Barricade (Barc)/Tat-SF1/CUS2 in Drosophila neural stem cell (neuroblast) lineage formation. We show that Barc is required for the generation of neurons during Drosophila brain development by ensuring correct neural progenitor proliferation and differentiation. Barc associates with components of the U2 small nuclear ribonucleic proteins (snRNP), and its depletion causes alternative splicing in form of intron retention in a subset of genes. Using bioinformatics analysis and a cell culture based splicing assay, we found that Barc-dependent introns share three major traits: they are short, GC rich and have weak 3' splice sites. Our results show that Barc, together with the U2snRNP, plays an important role in regulating neural stem cell lineage progression during brain development and facilitates correct splicing of a subset of introns

Predicting seizure recurrence after an initial seizure-like episode from routine clinical notes using large language models: A retrospective cohort study

Background: The evaluation and management of first-time seizure-like events in children can be difficult because these episodes are not always directly observed and might be epileptic seizures or other conditions (seizure mimics). We aimed to evaluate whether machine learning models using real-world data could predict seizure recurrence after an initial seizure-like event. Methods: This retrospective cohort study compared models trained and evaluated on two separate datasets between Jan 1, 2010, and Jan 1, 2020: electronic medical records (EMRs) at Boston Children's Hospital and de-identified, patient-level, administrative claims data from the IBM MarketScan research database. The study population comprised patients with an initial diagnosis of either epilepsy or convulsions before the age of 21 years, based on International Classification of Diseases, Clinical Modification (ICD-CM) codes. We compared machine learning-based predictive modelling using structured data (logistic regression and XGBoost) with emerging techniques in natural language processing by use of large language models. Findings: The primary cohort comprised 14 021 patients at Boston Children's Hospital matching inclusion criteria with an initial seizure-like event and the comparison cohort comprised 15 062 patients within the IBM MarketScan research database. Seizure recurrence based on a composite expert-derived definition occurred in 57% of patients at Boston Children's Hospital and 63% of patients within IBM MarketScan. Large language models with additional domain-specific and location-specific pre-training on patients excluded from the study (F1-score 0·826 [95% CI 0·817-0·835], AUC 0·897 [95% CI 0·875-0·913]) performed best. All large language models, including the base model without additional pre-training (F1-score 0·739 [95% CI 0·738-0·741], AUROC 0·846 [95% CI 0·826-0·861]) outperformed models trained with structured data. With structured data only, XGBoost outperformed logistic regression and XGBoost models trained with the Boston Children's Hospital EMR (logistic regression: F1-score 0·650 [95% CI 0·643-0·657], AUC 0·694 [95% CI 0·685-0·705], XGBoost: F1-score 0·679 [0·676-0·683], AUC 0·725 [0·717-0·734]) performed similarly to models trained on the IBM MarketScan database (logistic regression: F1-score 0·596 [0·590-0·601], AUC 0·670 [0·664-0·675], XGBoost: F1-score 0·678 [0·668-0·687], AUC 0·710 [0·703-0·714]). Interpretation: Physician's clinical notes about an initial seizure-like event include substantial signals for prediction of seizure recurrence, and additional domain-specific and location-specific pre-training can significantly improve the performance of clinical large language models, even for specialised cohorts.</p