Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions
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A deep water electroshocking platform (DEP), developed to characterize larval lampreys (ammocoetes) and associated habitat in depths up to 15 m, was recently tested in the field. The DEP samples 0.55 m2∙min-1 without requiring ammocoete transport to the surface. Searches were conducted at a known rearing location (mouth of the Wind River, WA) and at locations on the Cowlitz River, WA, where ammocoetes had not previously been found. At the mouth of the Wind River, video imaged ammocoetes ranged from 50 to 150 mm in water depths between 1.5 m and 4.5 m and were more common in sediments containing organic silt. Ammocoetes (n=137) were detected at 61% of locations sampled (summer) and 50% of the locations sampled (winter). Following the field verification, the DEP was used on the lower 11.7 km of the Cowlitz River, WA. Ammocoetes (n=41) were found with a detection rate of 26% at specific search locations. Cowlitz River sediment containing ammocoetes was also dominated by silt with organic material, often downstream of alluvial bars in water depths from 0.8 to 1.7 m. Test results indicated a high sampling efficiency, favorable detection rates, and little or no impact to ammocoetes and their surrounding benthic environments.
Accurately estimating rolling and air resistance is essential for predicting the energy consumption of vehicles. This study presents a field-based approach using a rolldown test to simultaneously determine rolling and air resistance coefficients. Unlike prior methods that frequently used simulations or models, we employ a goal programming methodology to improve precision and evaluate the actual vehicle and environmental conditions. Our methodology was tested using a Class 8 Freightliner eCascadia on a surveyed road section, ensuring controlled conditions for data collection. By analyzing the time–velocity relationship across multiple test runs, we derived resistance coefficients for both loaded and unloaded conditions. The study confirms that rolling resistance is largely independent of velocity at low speeds but exhibits a nonlinear dependency at higher speeds. Additionally, road surface conditions, tire condition, axle configuration, aerodynamic properties, and weather conditions significantly impact resistance values, emphasizing the need for real-world testing rather than relying solely on standardized projections. Our results align with existing literature while demonstrating the efficacy of the goal programming approach in refining resistance estimates. This work contributes to improved vehicle energy modeling, offering practical insights for fleet operators and policymakers seeking accurate energy consumption predictions for electric trucks operating under varying environmental conditions.
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Knowing the site of {gamma}-ray emission in active galactic nucleus jets will do much for our understanding of the physics of the source. In particular, if the emission region is close to the black hole then absorption of {gamma}-rays with photons from the broad-line region could become significant. Such absorption is predicted to produce two specific spectral breaks in the {gamma}-ray spectra of Flat Spectrum Radio Quasars (FSRQs). We test this hypothesis using three years of Fermi observations of nine bright FSRQs. A simple power-law fit to the spectrum of each source can be significantly improved by introducing a break, but the break energies are inconsistent with those predicted by the double-absorber model. In some cases the fit can be further improved by a log-parabola. In addition, by dividing the data from each source into two equal epochs we find that the best description of an object's spectrum often varies between a log-parabola and a broken power law.
We present a medium-resolution spectroscopic survey of late-type giant stars at mid-Galactic latitudes of (30 Degree-Sign < |b| < 60 Degree-Sign ), designed to probe the properties of this population to distances of {approx}9 kpc. Because M giants are generally metal-rich and we have limited contamination from thin disk stars by the latitude selection, most of the stars in the survey are expected to be members of the thick disk (([Fe/H]) {approx} -0.6) with some contribution from the metal-rich component of the nearby halo. Here we report first results for 1799 stars. The distribution of radial velocity (RV) as a function of l for these stars shows (1) the expected thick disk population and (2) local metal-rich halo stars moving at high speeds relative to the disk, which in some cases form distinct sequences in RV-l space. High-resolution echelle spectra taken for 34 of these ''RV outliers'' reveal the following patterns across the [Ti/Fe]-[Fe/H] plane: 17 of the stars have abundances reminiscent of the populations present in dwarf satellites of the Milky Way, 8 have abundances coincident with those of the Galactic disk and a more metal-rich halo, and 9 of the stars fall on the locus defined by the majority of stars in the halo. The chemical abundance trends of the RV outliers suggest that this sample consists predominantly of stars accreted from infalling dwarf galaxies. A smaller fraction of stars in the RV outlier sample may have been formed in the inner Galaxy and subsequently kicked to higher eccentricity orbits, but the sample is not large enough to distinguish conclusively between this interpretation and the alternative that these stars represent the tail of the velocity distribution of the thick disk. Our data do not rule out the possibility that a minority of the sample could have formed from gas in situ on their current orbits. These results are consistent with scenarios where the stellar halo, at least as probed by M giants, arises from multiple formation mechanisms; however, when taken at face value, our results for metal-rich halo giants suggest a much higher proportion to be accreted than found by Carollo et al. and more like the fraction suggested in the analysis by Nissen and Schuster and Schuster et al. We conclude that M giants with large RVs can provide particularly fruitful samples to mine for accreted structures and that some of the velocity sequences may indeed correspond to real physical associations resulting from recent accretion events.
If broad absorption line (BAL) quasars represent a high-covering-fraction evolutionary state (even if this is not the sole factor governing the presence of BALs), it is expected that they should show an excess of mid-infrared radiation compared to normal quasars. Some previous studies have suggested that this is not the case. We perform the first analysis of the IR properties of radio-loud BAL quasars, using IR data from WISE and optical (rest-frame ultraviolet) data from SDSS, and compare the BAL quasar sample with a well-matched sample of unabsorbed quasars. We find a statistically significant excess in the mid- to near-infrared luminosities of BAL quasars, particularly at rest-frame wavelengths of 1.5 and 4 {mu}m. Our sample was previously used to show that BALs are observed along many lines of sight toward quasars, but with an overabundance of more edge-on sources, suggesting that orientation factors into the appearance of BALs. The evidence here-of a difference in IR luminosities between BAL quasars and unabsorbed quasars-can be ascribed to evolution. This suggests that a merging of the current BAL paradigms is needed to fully describe the class.
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The possibility that nucleosynthesis in neutron star mergers may reach fissioning nuclei introduces significant uncertainties in predicting the relative abundances of $r$-process material from such events. We evaluate the impact of using sets of fission yields given by the 2016 GEF code for spontaneous (sf), neutron-induced $((n, f))$, and $β$-delayed (βdf) fission processes which take into account the approximate initial excitation energy of the fissioning compound nucleus. We further explore energy-dependent fission dynamics in the $r$ process by considering the sensitivity of our results to the treatment of the energy sharing and de-excitation of the fission fragments using the FREYA code. We show that the asymmetric-to-symmetric yield trends predicted by GEF 2016 can reproduce the high-mass edge of the second $r$-process peak seen in solar data and examine the sensitivity of this result to the mass model and astrophysical conditions applied. We consider the effect of fission yields and barrier heights on the nuclear heating rates used to predict kilonova light curves. We find that fission barriers influence the contribution of 254 Cf spontaneous fission to the heating at ~100 d, such that a light curve observation consistent with such late-time heating would both confirm that actinides were produced in the event and imply the fission barriers are relatively high along the 254 Cf β-feeding path. We lastly determine the key nuclei responsible for setting the r-process abundance pattern by averaging over thirty trajectories from a 1.2–1.4 M ⊙ neutron star merger simulation. Finally, we show it is largely the odd-N nuclei undergoing $(Z, N)(n, f)$ and $(Z, N)β$df that control the relative abundances near the second peak. We find the 'hot spots' for β-delayed and neutron-induced fission given all mass models considered and show most of these nuclei lie between the predicted $N$ = 184 shell closure and the location of currently available experimental decay data.
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Primordial black holes (PBHs) are an important tool in cosmology to probe the primordial spectrum of small-scale curvature perturbations that reenter the cosmological horizon during radiation domination epoch. We numerically solve the evolution of spherically symmetric highly perturbed configurations to clarify the criteria of PBHs formation using an extremely wide class of curvature profiles characterized by five parameters, (in contrast to only two parameters used in all previous papers) which specify the curvature profiles not only at the central region but also at the outer boundary of configurations. It is shown that formation or non-formation of PBHs is determined essentialy by only two master parameters one of which can be presented as an integral of curvature over initial configurations and the other is presented in terms of the position of the boundary and the edge of the core.
A new algorithm for the determination of the initial flavour of B 0 s mesons is presented. The algorithm is based on two neural networks and exploits the b hadron production mechanism at a hadron collider. The first network is trained to select charged kaons produced in association with the B 0 s meson. The second network combines the kaon charges to assign the B 0 s flavour and estimates the probability of a wrong assignment. The algorithm is calibrated using data corresponding to an integrated luminosity of 3 fb –1 collected by the LHCb experiment in proton-proton collisions at 7 and 8 TeV centre-of-mass energies. The calibration is performed in two ways: by resolving the B 0 s – B ¯ 0 s flavour oscillations in B 0 s → D – s π + decays, and by analysing flavour-specific B * s 2 (5840) 0 → B + K – decays. The tagging power measured in B 0 s → D – s π + decays is found to be (1.80 ± 0.19 (stat) ± 0.18 (syst))%, which is an improvement of about 50% compared to a similar algorithm previously used in the LHCb experiment.
Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.
Line-of-sight magnetograms from the Helioseismic and Magnetic Imager (HMI) of the Solar Dynamics Observatory (SDO) are analyzed using a diagnostic known as the magnetic range of influence (MRoI). The MRoI is a measure of the length over which a photospheric magnetogram is balanced and so its application gives the user a sense of the connective length scales in the outer solar atmosphere. The MRoI maps and histograms inferred from the SDO/HMI magnetograms primarily exhibit four scales: a scale of a few megameters that can be associated with granulation, a scale of a few tens of megameters that can be associated with super-granulation, a scale of many hundreds to thousands of megameters that can be associated with coronal holes and active regions, and a hitherto unnoticed scale that ranges from 100 to 250 Mm. We infer that this final scale is an imprint of the (rotationally driven) giant convective scale on photospheric magnetism. This scale appears in MRoI maps as well-defined, spatially distributed concentrations that we have dubbed ''g-nodes''. Furthermore, using coronal observations from the Atmospheric Imaging Assembly on SDO, we see that the vicinity of these g-nodes appears to be a preferred location for the formation of extreme-ultraviolet (and likely X-Ray) brightpoints. These observations and straightforward diagnostics offer the potential of a near real-time mapping of the Sun's largest convective scale, a scale that possibly reaches to the very bottom of the convective zone.