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This is a work-in-progress paper. The flipped classroom (FC) model is a well established teaching strategy dating to 1970’s practices in the Soviet Union. FC has two decades of use in post-secondary education since it was proposed by Lage et al. However, breaking studies find no academic improvement with FC model among minority students. Rather, it distances at-risk students. Indeed, certain demographics prefer authoritative over dialogic instruction style. We are motivated to determine FCs effectiveness with students at a medium-sized Hispanic Serving Institution (HSI) and Minority Serving Institution (MSI). For one of our NSF grant activities, we piloted two variations of the flipped classroom model. The key idea is that literature finds that FC classes need better regulation of underperforming students. Generally, the FC models in our work included peer-instruction, active learning, recorded lectures, and pre-assessment quizzes. There were no post-assessment assignments or traditional homework. Some sections employed Just-in-Time-Teaching, and careful selection of groups according to skill (within-class homogenous grouping). Other sections experimented with diversity and inclusion-based grouping and project-based learning. Students at the university are non-traditional, a term used to describe individuals who meet some of the following criteria: having a significant gap between post-secondary education and high-school graduation, being financially independent from their parents, having dependents, and working twenty or more hours per week. 60% of the individuals at our campus are Pell eligible. We study an intersectional inequality: wage-based work is disinclined to accommodate students attending lecture during the work day, and minorities may not prefer dialogic instruction. We analyze student attitudes since Fall 2020, among tens of class sections and hundreds of students. Class sections in the study are upper-division core courses in Computer Science, Computer Engineering and Electrical Engineering. Data is collected from mostly online sections during the COVID-19 pandemic. A pre- and post-surveys were administered collecting demographic information and student attitudes. Hispanic/Latino(a) students found videos to be a complete study medium—that it was not required to seek out third-party materials to prepare for class. They found the class to be more engaging, and self-identified that they could identify previous concepts important to the task at hand. Results were surprising because there were no statistically significant differences with a general population’s exposure to FC. Hispanic/Latino(a)s find the FC model described in our work engaging and effective. 

The high-energy radiative output, from the X-ray to the ultraviolet, of exoplanet host stars drives photochemical reactions and mass loss in the upper regions of planetary atmospheres. In order to place constraints on the atmospheric properties of the three closest terrestrial exoplanets transiting M dwarfs, we observe the high-energy spectra of the host stars LTT 1445A and GJ 486 in the X-ray withXMM-NewtonandChandraand in the ultraviolet with HST/COS and STIS. We combine these observations with estimates of extreme-ultraviolet flux, reconstructions of the Lyαlines, and stellar models at optical and infrared wavelengths to produce panchromatic spectra from 1 Å to 20 µm for each star. While LTT 1445Ab, LTT 1445Ac, and GJ 486b do not possess primordial hydrogen-dominated atmospheres, we calculate that they are able to retain pure CO₂atmospheres if starting with 10, 15, and 50% of Earth’s total CO₂budget, respectively, in the presence of their host stars’ stellar wind. We use age-activity relationships to place lower limits of 2.2 and 6.6 Gyr on the ages of the host stars LTT 1445A and GJ 486. Despite both LTT 1445A and GJ 486 appearing inactive at optical wavelengths, we detect flares at ultraviolet and X-ray wavelengths for both stars. In particular, GJ 486 exhibits two far-ultraviolet flares with absolute energies of 10^29.5and 10^30.1erg (equivalent durations of 4357 ± 96 and 19 724 ± 169 s) occurring 3 h apart. Based on the timing of the observations, we suggest that these high-energy flares are related and indicative of heightened flaring activity that lasts for a period of days, but our interpretations are limited by sparse time-sampling. Consistent high-energy monitoring is needed to determine the duration and extent of high-energy activity on individual M dwarfs and the population as a whole. 

This Letter extends a recent IceCube sterile neutrino search to include unstable sterile neutrinos within the context of a model termed $3+1+\mathrm{Decay}$ , which expands upon the $3+1$ model by introducing sterile neutrino decay to invisible particles with coupling constant $g^2$ . The model is attractive since it reduces tension between oscillation experiments within the global fits and with constraints that come from cosmological observables. The analysis uses 10.7 years of up-going muon neutrino data with energy 500 GeV to 100 TeV and with improved reconstruction and modeling of systematics. The best-fit point is found to be $g^2=0$ , ${\sin }^2\left(2{\theta }_{24}\right)=0.16$ , and $\mathrm{\Delta }{m}_{41}^2=3.5{\mathrm{eV}}^2$ , in agreement with the recent $3+1$ sterile neutrino search. Values of $g^2\ge \pi$ are excluded at 95% confidence level. This result substantially limits decay parameter space indicated by recent global fits, disfavoring the decay scenario. 

Radio pulses generated by cosmic-ray air showers can be used to reconstruct key properties like the energy and depth of the electromagnetic component of cosmic-ray air showers. Radio detection threshold, influenced by natural and anthropogenic radio background, can be reduced through various techniques. In this work, we demonstrate that convolutional neural networks (CNNs) are an effective way to lower the threshold. We developed two CNNs: a classifier to distinguish radio signal waveforms from background noise and a denoiser to clean contaminated radio signals. Following the training and testing phases, we applied the networks to air-shower data triggered by scintillation detectors of the prototype station for the enhancement of IceTop, IceCube’s surface array at the South Pole. Over a four-month period, we identified 554 cosmic-ray events in coincidence with IceTop, approximately five times more compared to a reference method based on a cut on the signal-to-noise ratio. Comparisons with IceTop measurements of the same air showers confirmed that the CNNs reliably identified cosmic-ray radio pulses and outperformed the reference method. Additionally, we find that CNNs reduce the false-positive rate of air-shower candidates and effectively denoise radio waveforms, thereby improving the accuracy of the power and arrival time reconstruction of radio pulses. 

Abstract IceCube is a Cherenkov detector instrumenting over a cubic kilometer of glacial ice deep under the surface of the South Pole. The DeepCore sub-detector lowers the detection energy threshold to a few GeV, enabling the precise measurements of neutrino oscillation parameters with atmospheric neutrinos. The reconstruction of neutrino interactions inside the detector is essential in studying neutrino oscillations. It is particularly challenging to reconstruct sub-100 GeV events with the IceCube detectors due to the relatively sparse detection units and detection medium. Convolutional neural networks (CNNs) are broadly used in physics experiments for both classification and regression purposes. This paper discusses the CNNs developed and employed for the latest IceCube-DeepCore oscillation measurements [1]. These CNNs estimate various properties of the detected neutrinos, such as their energy, direction of arrival, interaction vertex position, flavor-related signature, and are also used for background classification. 

Abstract Rotating nonaxisymmetric neutron stars (NSs) are promising sources for continuous gravitational waves (CWs). CWs may, if detected, inform us about the internal structure and equation of state of NSs. Here, we present a narrowband search for CWs from known pulsars, for which a matched-filter search can be applied. Narrowband searches are robust to mismatches between electromagnetic (EM) and gravitational emissions, in contrast to fully targeted searches where they are assumed to be phase-locked. In this work, we search for the CW counterparts emitted by 34 pulsars using data from the first and second parts of the fourth LIGO–Virgo–KAGRA observing run. We use the 5n-vector narrowband pipeline, which applies frequency-domain matched filtering. In previous searches, it covered a narrow range in the frequency—frequency time derivative (f— $\dot{f}$ ) space. Here, we also explore a range in the second time derivative of the frequency $\ddot{f}$ around the EM observations. Additionally, for the first time, we target sources in a binary system with this kind of search. We find no evidence for CWs and therefore set upper limits on the strain amplitude emitted by each pulsar. For 20 analyses, we report an upper limit below the theoretical spin-down limit. The tightest constraint is for pulsar PSR J0534+2200 (the Crab pulsar), for which our strain upper limit on the CW amplitude corresponds to ≤0.04% of the spin-down power being radiated in the CW channel. 

Abstract We detail the population properties of binary neutron star, neutron star–black hole binary, and binary black hole mergers using 158 events from the cumulative Gravitational-Wave Transient Catalog 4.0. The black hole primary mass distribution consists of a power-law-like continuum that steepens above 35M_⊙with overdensities at 10M_⊙and 35M_⊙. Binary black holes with primary masses near 10M_⊙are more likely to have less massive secondaries, with a mass ratio distribution peaking at $q=0.71_{-0.11}^{+0.12}$ , potentially a signature of stable mass transfer during binary evolution. Black hole spins are inferred to be nonextremal, with 90% of black holes havingχ < 0.6, and preferentially aligned with binary orbits, implying many merging binaries form in isolation. However, we find that a significant fraction, 0.23–0.41, of binaries have negative effective inspiral spins, suggesting many could be formed dynamically in gas-free environments. We find evidence for correlation between effective inspiral spin and mass ratio, driven either by variation in the mode of the distribution or the width. The binary black hole merger rate increases with redshift, consistent with the cosmic star formation density. While there is no evidence of the mass spectrum evolving with redshift, the distribution of effective inspiral spin is found to broaden as redshift increases out toz ≈ 1. We infer the local merger rates (atz= 0) to be 8.8–250 Gpc⁻³yr⁻¹for binary neutron stars, 9.3–86 Gpc⁻³yr⁻¹for neutron star–black hole binaries, and 13–26 Gpc⁻³yr⁻¹for binary black holes; all values reflect central 90% credible intervals.