cssi/SciSciGPT-SciSciNet huggingface dataset:
Relation between large dimension operators and oscillator algebra of Young diagrams

The operators with large scaling dimensions can be labeled by Young diagrams. Among other bases, the operators using restricted Schur polynomials have been known to have a large N but nonplanar limit under which they map to states of a system of harmonic oscillators. We analyze the oscillator algebra acting on pairs of long rows or long columns in the Young diagrams of the operators. The oscillator algebra can be reached by a Inonu–Wigner contraction of the u(2) algebra inside of the u(p) algebra of p giant gravitons. We present evidences that integrability in this case can persist at higher loops due to the presence of the oscillator algebra which is expected to be robust under loop corrections in the nonplanar large N limit.
ORIGIN(S) OF THE HIGHLY IONIZED HIGH-VELOCITY CLOUDS BASED ON THEIR DISTANCES*

Previous Hubble Space Telescope and FUSE observations have revealed highly ionized high-velocity clouds (HVCs) or more generally low H I column HVCs along extragalactic sight lines over 70%-90% of the sky. The distances of these HVCs have remained largely unknown hindering from distinguishing a Galactic origin (e.g., outflow, inflow) from a Local Group origin (e.g., warm-hot intergalactic medium). We present the first detection of highly ionized HVCs in the Cosmic Origins Spectrograph spectrum of the early-type star HS 1914+7134 (l = 103°, b = +24°) located in the outer region of the Galaxy at d 14.9 kpc. Two HVCs are detected in absorption at v LSR = –118 and –180 km s–1 in several species, including C IV, Si IV, Si III, Al II, C II, Si II, O I, but H I 21 cm emission is only seen at –118 km s–1. Within 17° of HS 1914+7134, we found HVC absorption of low and high ions at similar velocities toward five extragalactic sight lines, suggesting that these HVCs are related. The component at –118 km s–1 is likely associated with the outer arm of the Milky Way. The highly ionized HVC at –180 km s–1 is possibly an HVC plunging at high speed onto the thick disk of the Milky Way. This is the second detection of highly ionized HVCs toward Galactic stars, supporting a Galactic origin for at least some of these low H I column density HVCs.
Discovery of a New, Polar-Orbiting Debris Stream in the Milky Way Stellar Halo

We show that there is a low metallicity tidal stream that runs along l = 143{sup o} in the South Galactic Cap, about 34 kpc from the Sun, discovered from SEGUE stellar velocities. Since the most concentrated detections are in the Cetus constellation, and the orbital path is nearly polar, we name it the Cetus Polar Stream (CPS). Although it is spatially coincident with the Sgr dwarf trailing tidal tail at b = -70{sup o}, the metallicities ([Fe/H] = -2.1), ratio of blue straggler to blue horizontal branch stars, and velocities of the CPS stars differ from Sgr. Some CPS stars may contaminate previous samples of Sgr dwarf tidal debris. The unusual globular cluster NGC 5824 is located along an orbit fit to the CPS, with the correct radial velocity.
Adaptive Online Estimation of Piecewise Polynomial Trends

We consider the framework of non-stationary stochastic optimization [Besbes et al, 2015] with squared error losses and noisy gradient feedback where the dynamic regret of an online learner against a time varying comparator sequence is studied. Motivated from the theory of non-parametric regression, we introduce a new variational constraint that enforces the comparator sequence to belong to a discrete $k^{th}$ order Total Variation ball of radius $C_n$. This variational constraint models comparators that have piece-wise polynomial structure which has many relevant practical applications [Tibshirani, 2014]. By establishing connections to the theory of wavelet based non-parametric regression, we design a polynomial time algorithm that achieves the nearly optimal dynamic regret of $\tilde{O}(n^{\frac{1}{2k+3}}C_n^{\frac{2}{2k+3}})$. The proposed policy is adaptive to the unknown radius $C_n$. Further, we show that the same policy is minimax optimal for several other non-parametric families of interest.
On rational homology disk smoothings of valency 4 surface singularities

Thanks to the recent work of Bhupal, Stipsicz, Szabo, and the author, one has a complete list of resolution graphs of weighted homogeneous complex surface singularities admitting a rational homology disk ("QHD") smoothing, i.e., one with Milnor number 0. They fall into several classes, the most interesting of which are the three classes whose resolution dual graph has central vertex with valency 4. We give a uniform "quotient construction" of the QHD smoothings for these classes; it is an explicit Q-Gorenstein smoothing, yielding a precise description of the Milnor fibre and its non-abelian fundamental group. This had already been done for two of these classes in a previous paper; what is new here is the construction of the third class, which is far more difficult. In addition, we explain the existence of two different QHD smoothings for the first class. We also prove a general formula for the dimension of a QHD smoothing component for a rational surface singularity. A corollary is that for the valency 4 cases, such a component has dimension 1 and is smooth. Another corollary is that "most" H-shaped resolution graphs cannot be the graph of a singularity with a QHD smoothing. This result, plus recent work of Bhupal-Stipsicz, is evidence for a general Conjecture: The only complex surface singularities with a QHD smoothing are the (known) weighted homogeneous examples.
Hubble space telescope snapshot search for planetary nebulae in globular clusters of the local group

Single stars in ancient globular clusters (GCs) are believed incapable of producing planetary nebulae (PNs), because their post-asymptotic-giant-branch evolutionary timescales are slower than the dissipation timescales for PNs. Nevertheless, four PNs are known in Galactic GCs. Their existence likely requires more exotic evolutionary channels, including stellar mergers and common-envelope binary interactions. I carried out a snapshot imaging search with the Hubble Space Telescope (HST) for PNs in bright Local Group GCs outside the Milky Way. I used a filter covering the 5007 A nebular emission line of [O iii], and another one in the nearby continuum, to image 66 GCs. Inclusion of archival HST frames brought the total number of extragalactic GCs imaged at 5007 A to 75, whose total luminosity slightly exceeds that of the entire Galactic GC system. I found no convincing PNs in these clusters, aside from one PN in a young M31 cluster misclassified as a GC, and two PNs at such large angular separations from an M31 GC that membership is doubtful. In a ground-based spectroscopic survey of 274 old GCs in M31, Jacoby et al. found three candidate PNs. My HST images of one of them suggest that the [O iii] emission actually arises from ambient interstellar medium rather than a PN; for the other two candidates, there are broadband archival UV HST images that show bright, blue point sources that are probably the PNs. In a literature search, I also identified five further PN candidates lying near old GCs in M31, for which follow-up observations are necessary to confirm their membership. The rates of incidence of PNs are similar, and small but nonzero, throughout the GCs of the Local Group.
A NEAR HORIZON CFT DUAL FOR KERR–NEWMAN AdS

We show that the near horizon regime of a Kerr–Newman AdS (KNAdS) black hole, given by its two-dimensional analogue a la Robinson and Wilczek (Phys. Rev. Lett.95, 011303 (2005)), is asymptotically AdS2 and dual to a one-dimensional quantum conformal field theory (CFT). The s-wave contribution of the resulting CFT's energy–momentum tensor together with the asymptotic symmetries, generate a centrally extended Virasoro algebra, whose central charge reproduces the Bekenstein–Hawking entropy via Cardy's formula. Our derived central charge also agrees with the near extremal Kerr/CFT correspondence (Phys. Rev. D80, 124008 (2009)) in the appropriate limits. We also compute the Hawking temperature of the KNAdS black hole by coupling its Robinson and Wilczek two-dimensional analogue (RW2DA) to conformal matter.
Testing a Dynamical Equilibrium Model of the Extraplanar Diffuse Ionized Gas in NGC 891

The observed scale heights of extraplanar diffuse ionized gas (eDIG) layers exceed their thermal scale heights by a factor of a few in the Milky Way and other nearby edge-on disk galaxies. Here, we test a dynamical equilibrium model of the extraplanar diffuse ionized gas layer in NGC 891, where we ask whether the thermal, turbulent, magnetic field, and cosmic ray pressure gradients are sufficient to support the layer. In optical emission line spectroscopy from the SparsePak integral field unit on the WIYN 3.5-meter telescope, the H-alpha emission in position-velocity space suggests that the eDIG is found in a ring between galactocentric radii of R_min = 2 kpc. We find that the thermal (sigma_th = 11 km/s) and turbulent (sigma_turb = 25 km/s) velocity dispersions are insufficient to satisfy the hydrostatic equilibrium equation given an exponential electron scale height of h_z = 1.0 kpc. Using a literature analysis of radio continuum observations from the CHANG-ES survey, we demonstrate that the magnetic field and cosmic ray pressure gradients are sufficient to stably support the gas at R >= 8 kpc if the cosmic rays are sufficiently coupled to the system (gamma_cr = 1.45). Thus, a stable dynamical equilibrium model is viable only if the extraplanar diffuse ionized gas is found in a thin ring around R = 8 kpc, and non-equilibrium models such as a galactic fountain flow are of interest for further study.
Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models pre- dict future increases in environmental variability and biological invasions are becoming increasingly fre- quent. A key to developing effective responses to bio- logical invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integrodifference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in re- production and an illustrative example with published data for the perennial herb, Calathea ovandensis .T hese examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal auto- correlations in vital rates inflate variability in inva- sion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates "remember" the past.
Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion

A case-based reasoning (CBR) system solves a new problem by retrieving ‘cases’ that are similar to the given problem. If such a system can achieve high accuracy, it is appealing owing to its simplicity, interpretability, and scalability. In this paper, we demonstrate that such a system is achievable for reasoning in knowledge-bases (KBs). Our approach predicts attributes for an entity by gathering reasoning paths from similar entities in the KB. Our probabilistic model estimates the likelihood that a path is effective at answering a query about the given entity. The parameters of our model can be efficiently computed using simple path statistics and require no iterative optimization. Our model is non-parametric, growing dynamically as new entities and relations are added to the KB. On several benchmark datasets our approach significantly outperforms other rule learning approaches and performs comparably to state-of-the-art embedding-based approaches. Furthermore, we demonstrate the effectiveness of our model in an “open-world” setting where new entities arrive in an online fashion, significantly outperforming state-of-the-art approaches and nearly matching the best offline method.
Exploring BERT’s Sensitivity to Lexical Cues using Tests from Semantic Priming

Models trained to estimate word probabilities in context have become ubiquitous in natural language processing. How do these models use lexical cues in context to inform their word probabilities? To answer this question, we present a case study analyzing the pre-trained BERT model with tests informed by semantic priming. Using English lexical stimuli that show priming in humans, we find that BERT too shows “priming”, predicting a word with greater probability when the context includes a related word versus an unrelated one. This effect decreases as the amount of information provided by the context increases. Follow-up analysis shows BERT to be increasingly distracted by related prime words as context becomes more informative, assigning lower probabilities to related words. Our findings highlight the importance of considering contextual constraint effects when studying word prediction in these models, and highlight possible parallels with human processing.
Strange Attractors in Periodically-Kicked Degenerate Hopf Bifurcations

We prove that spiral sinks (stable foci of vector fields) can be transformed into strange attractors exhibiting sustained, observable chaos if subjected to periodic pulsatile forcing. We show that this phenomenon occurs in the context of periodically-kicked degenerate supercritical Hopf bifurcations. The results and their proofs make use of a k-parameter version of the theory of rank one maps.
REMARKS ON THE COSMOLOGICAL CONSTANT

The acceleration of the surface of last scatter (SLS) must somehow reflect the energy content within it. A test particle at the SLS is assumed to experience a linear combination of two forces: one Newtonian, the other pseudo-Newtonian describable by a cosmological constant Λ in general relativity. In the Λ description, which is surely too unimaginative, the size of Λ reflects only the comparable magnitudes of the Newtonian and pseudo-Newtonian forces; any claim of fine tuning due to quantum mechanics is probably illusory.
Gap Formation by Planets in Turbulent Protostellar Disks

The processes of planet formation and migration depend intimately on the interaction between planetesimals and the gaseous disks in which they form. The formation of gaps in the disk can severely limit the mass of the planet and its migration toward the protostar. We investigate the process of gap formation through magnetohydrodynamic simulations in which internal stress arises self-consistently from turbulence generated by the magnetorotational instability. The simulations investigate three different planetary masses and two disk temperatures to bracket the tidal (thermal) and viscous gap opening conditions. The results are in general qualitative agreement with previous simulations of gap formation but show significant differences. In the presence of MHD turbulence, the gaps produced are shallower and asymmetrically wider than those produced with pure hydrodynamics. The rate of gap formation is also slowed, with accretion occurring across the developing gap. Viscous hydrodynamics does not adequately describe the evolution, however, because planets capable of producing gaps also may be capable of affecting the level of MHD turbulence in different regions of the disk.
Characterization of the generalized Chebyshev-type polynomials of first kind

Orthogonal polynomials have very useful properties in the mathematical problems, so recent years have seen a great deal in the field of approximation theory using orthogonal polynomials. In this paper, we characterize a sequence of the generalized Chebyshev-type polynomials of the first kind \(\left\{\mathscr{T}_{n}^{(M,N)}(x)\right\}_{n\in\mathbb{N}\cup\{0\}},\) which are orthogonal with respect to the measure \(\frac{\sqrt{1-x^{2}}}{\pi}dx+M\delta_{-1}+N\delta_{1},\) where \(\delta_{x}\) is a singular Dirac measure and \(M,N\geq 0.\) Then we provide a closed form of the constructed polynomials in term of the Bernstein polynomials \(B_{k}^{n}(x).\) We conclude the paper with some results on the integration of the weighted generalized Chebyshev-type with the Bernstein polynomials.
An HST Proper-motion Study of the Large-scale Jet of 3C273

E.T.M. acknowledges HST Grant GO-13327. E.T.M. and M.G. also acknolwedge NASA grant 14-ADAP14-0122.
A Multiscale Modeling of Triple-Heterojunction Tunneling FETs

A high performance triple-heterojunction (3HJ) design has been previously proposed for tunneling FETs (TFETs). Compared with single HJ TFETs, the 3HJ TFETs have both shorter tunneling distance and two transmission resonances that significantly improve the ON-state current ( ${I}_{\scriptscriptstyle {\text {ON}}}$ ). Coherent quantum transport simulation predicts that ${I}_{\scriptscriptstyle {\text {ON}}} = 460~\mu \textsf {A}/\mu \textsf {m}$ can be achieved at gate length $\text {Lg} = 15~\textsf {nm}$ , supply voltage ${V}_{\textsf {DD}} = 0.3~\textsf {V}$ , and OFF-state current ${I}_{\scriptscriptstyle {\text {OFF}}} = 1~\textsf {nA}/\mu \textsf {m}$ . However, strong electron–phonon and electron–electron scattering in the heavily doped leads implies that the 3HJ devices operate far from the ideal coherent limit. In this paper, such scattering effects are assessed by a newly developed multiscale transport model, which combines the ballistic nonequilibrium Green’s function method for the channel and the drift-diffusion scattering method for the leads. Simulation results show that the thermalizing scattering in the leads both degrades the 3HJ TFET’s subthreshold swing through scattering-induced leakage and reduces the turn-ON current through the access resistance. Assuming bulk scattering rates and carrier mobilities, the ${I}_{\scriptscriptstyle {\text {ON}}}$ is dropped from $460~\mu \textsf {A}/\mu \textsf {m}$ down to $254~\mu \textsf {A}/\mu \textsf {m}$ , which is still much larger than the single HJ TFET case.
The Physical and Chemical Status of Pre-Protostellar Core B68

We have investigated the physical and chemical status of the pre-protostellar core B68. A previous extinction study suggested that the density profile of B68 is remarkably consistent with a Bonnor-Ebert sphere with 2.1 M⊙ at 16 K. We mapped B68 in C3H2, CCS, and NH3 with the Deep Space Network (DSN) 70 m telescope at Goldstone. Our results show that the NH3 peak coincides with the dust continuum peak, whereas CCS and C3H2 are offset from the NH3 and dust peaks. The B68 chemical structure is consistent with that seen in other such pre-protostellar cores (L1498 and L1544) and is explained by time-dependent chemical models that include depletion. We measured the kinetic temperature of B68 with NH3 (1, 1) and (2, 2) spectra obtained with a DSN 34 m telescope. We find that the kinetic temperature of B68 is only 11 K, which is significantly lower than that previously assumed. We also derive the nonthermal line width in B68 and show that B68 is thermally dominated with little contribution from turbulence support (less than 10%). We consider a modified Bonnor-Ebert sphere to include effects of turbulence and magnetic fields and use it to constrain the uncertainties in its distance determination. We conclude that the distance to B68 is ~95 pc with a corresponding mass of ~1.0 M⊙. If some magnetic field is present, it can be further away (beyond ~100 pc) and still satisfy the density structure of a Bonnor-Ebert sphere. The sulfur (CS and CCS) and carbon chain (C3H2) molecules are heavily depleted in B68 and do not trace the dense interior region. We see some evidence for depletion of NH3 at the core center roughly on a scale similar to that of N2H+. Our observations do not preclude any instability such as the onset of collapse, or slow contraction, occurring in the center of the core, which cannot be resolved with our beam size (45'').
Spectroscopic, structural, and theoretical studies of halide complexes with a urea-based tripodal receptor.

A urea-based tripodal receptor L substituted with p-cyanophenyl groups has been studied for halide anions using 1H NMR spectroscopy, density functional theory (DFT) calculations, and X-ray crystallography. The 1H NMR titration studies suggest that the receptor forms a 1:1 complex with an anion, showing a binding trend in the order of fluoride > chloride > bromide > iodide. The interaction of a fluoride anion with the receptor was further confirmed by 2D NOESY and 19F NMR spectroscopy in DMSO-d6. DFT calculations indicate that the internal halide anion is held by six NH···X interactions with L, showing the highest binding energy for the fluoride complex. Structural characterization of the chloride, bromide, and silicon hexafluoride complexes of [LH+] reveals that the anion is externally located via hydrogen bonding interactions. For the bromide or chloride complex, two anions are bridged with two receptors to form a centrosymmetric dimer, while for the silicon hexafluoride complex, the anion is located wit...
Hierarchical Evolution in Poor Groups of Galaxies

To examine the evidence for hierarchical evolution on mass scales of ~1013-1014 M☉, we apply a statistic that measures correlations between galaxy velocity and projected position (Dressler & Shectman) to data for six poor groups of galaxies, HCG 42, HCG 62, NGC 533, NGC 2563, NGC 5129, and NGC 741. Each group has more than 30 identified members (Zabludoff & Mulchaey). The statistic is sensitive to clumps of galaxies on the sky whose mean velocity and velocity dispersion deviate from the kinematics of the group as a whole. The kinematics of galaxies within ~0.1 h-1 Mpc of the group center do not deviate from the global values, supporting our earlier claim that the group cores are close to virialization or virialized. We detect significant substructure (at ≥99.9% confidence) in two of the groups with the most confirmed members, HCG 62 and NGC 741, that is attributable mostly to a subgroup lying ~0.3-0.4 h−1 Mpc outside of the core. We conclude that at least some poor groups, like rich clusters, are evolving via the accretion of smaller structures from the field. With larger poor group surveys, the incidence of such accretion and the distribution of subgroup masses are potential constraints of cosmological models on mass scales of 1013-1014 M☉ and on physical scales of 0.5 h-1 Mpc.
Hyperfine Mixing and the Semileptonic Decays of Double-Heavy Baryons in a Quark Model

The semileptonic decays of the lowest-lying double-heavy baryons are treated in a quark model. For the Ξbb, hyperfine mixing in the spin wave function leaves the total rate for decay into the lowest lying daughter baryons essentially unchanged, but changes the relative rates into the Ξbc and . The same pattern is obtained in the decays of the Ωbb. For the Ξbc, this mixing leads to factor of about 17 suppression in the decay rate to the when wave functions truncated to the largest components are used, but the total semileptonic decay rate of the parent baryon remains essentially unchanged. For the Ωbc, the decay to the is suppressed by a factor of more than 25 from the unmixed case. When the full wave functions are used, the large suppression of the decays to the and persists.
Primordial power spectrum from the Dapor–Liegener model of loop quantum cosmology

We compute the predictions for the power spectrum of scalar perturbations from a recent new proposal for the effective Hamiltonian of loop quantum cosmology. The model provides an attractive picture of the early cosmos, in which our classical Friedmann–Lemaitre–Robertson–Walker universe emerges from a quantum phase where the spacetime curvature remains constant and of Planckian size. We compare the predictions for the cosmic microwave background with previous results obtained within loop quantum cosmology, and discuss the differences and similarities. The analysis provides an example of the way differences between quantization schemes can be translated to physical observables.
Strong-weak Chern-Simons-matter dualities from a lattice construction

We provide a lattice demonstration of (2+1)-dimensional field theory dualities relating free Dirac or Majorana fermions to strongly-interacting bosonic Chern-Simons-matter theories. Specifically, we prove the recent conjecture that U(N ) level-1 with Nf gauged complex Wilson-Fisher scalars (where 1 ≤ Nf ≤ N ) is dual to Nf Dirac fermions, as well as the analogous conjecture relating SO(N ) theories with real Wilson-Fisher scalars to Majorana fermions for 1 ≤ Nf ≤ N − 2. Furthermore, we discover new dualities that allow us to explain the interesting phase structure of the SO(N ) theories with N − 1 and N scalars, for all N ≥ 2.
Puzzles in K-homology of Grassmannians

Knutson, Tao, and Woodward formulated a Littlewood-Richardson rule for the cohomology ring of Grassmannians in terms of puzzles. Vakil and Wheeler-Zinn-Justin have found additional triangular puzzle pieces that allow one to express structure constants for $K$-theory of Grassmannians. Here we introduce two other puzzle pieces of hexagonal shape, each of which gives a Littlewood-Richardson rule for $K$-homology of Grassmannians. We also explore the corresponding eight versions of $K$-theoretic Littlewood-Richardson tableaux.
Heat Kernels with Functional Connectomes Reveal Atypical Energy Transport in Peripheral Subnetworks in Autism

Autism is increasing in prevalence and is a neurodevelopmental disorder characterised by impairments in communication skills and social behaviour. Connectomes enable a systems-level representation of the brain with recent interests in understanding the distributed nature of higher order cognitive function using modules or subnetworks. By dividing the connectome according to a central component of the brain critical for its function (it’s hub), we investigate network organisation in autism from hub through to peripheral subnetworks. We complement this analysis by extracting features of energy transport computed from heat kernels fitted with increasing time steps. This heat kernel framework is advantageous as it can capture the energy transported in all direct and indirect pathways between pair-wise regions over ’time’, with features that have correspondence to small-world properties. We apply our framework to resting-state functional MRI connectomes from a large, publically available autism dataset, ABIDE. We show that energy propagating through the brain over time are different between subnetworks, and that heat kernel features significantly differ between autism and controls. Furthermore, the hub was functionally preserved and similar to controls, however, increasing statistical significance between groups was found in increasingly peripheral subnetworks. Our results support the increasing opinion of non-hub regions playing an important role in functional organisation. This work shows that analysing autism by subnetworks with the heat kernel reflects the atypical activations in peripheral regions as alterations in energy dispersion and may provide useful features towards understanding the distributed impact of this disorder on the functional connectome.
QCD Sum Rules: Bridging the Gap between Short and Large Distances

I discuss aspects of the QCD sum rule method which attracted theorists' attention in earnest at a relatively late stage and are not yet fully solved. This is a slightly abbreviated version of the talk delivered at 15th International QCD Conference “QCD 10,” June 28 – July 3, 2010, Montpellier, France.
Empirical Constraints on the Origin of Fast Radio Bursts: Volumetric Rates and Host Galaxy Demographics as a Test of Millisecond Magnetar Connection

The localization of the repeating FRB 121102 to a low-metallicity dwarf galaxy at $z=0.193$, and its association with a quiescent radio source, suggests the possibility that FRBs originate from magnetars, formed by the unusual supernovae in such galaxies. We investigate this via a comparison of magnetar birth rates, the FRB volumetric rate, and host galaxy demographics. We calculate average volumetric rates of possible millisecond magnetar production channels such as superluminous supernovae (SLSNe), long and short gamma-ray bursts (GRBs), and general magnetar production via core-collapse supernovae. For each channel we also explore the expected host galaxy demographics using their known properties. We determine for the first time the number density of FRB emitters (the product of their volumetric birthrate and lifetime), $R_{\rm FRB}\tau\approx 10^4$Gpc$^{-3}$, assuming that FRBs are predominantly emitted from repetitive sources similar to FRB 121102 and adopting a beaming factor of 0.1. By comparing rates we find that production via rare channels (SLSNe, GRBs) implies a typical FRB lifetime of $\approx$30-300 yr, in good agreement with other lines of argument. The total energy emitted over this time is consistent with the available energy stored in the magnetic field. On the other hand, any relation to magnetars produced via normal core-collapse supernovae leads to a very short lifetime of $\approx$0.5yr, in conflict with both theory and observation. We demonstrate that due to the diverse host galaxy distributions of the different progenitor channels, many possible sources of FRB birth can be ruled out with $\lesssim 10$ host galaxy identifications. Conversely, targeted searches of galaxies that have previously hosted decades-old SLSNe and GRBs may be a fruitful strategy for discovering new FRBs and related quiescent radio sources, and determining the nature of their progenitors.
Not minding the gap: Does ride-hailing serve transit deserts?

Abstract Transit has long connected people to opportunities but access to transit varies greatly across space. In some cases, unevenly distributed transit supply creates gaps in service that impede travelers' abilities to cross space and access jobs or other opportunities. With the advent of ride-hailing services like Uber and Lyft, however, travelers now have a new potential to gain automobility without high car purchase costs and in the absence of reliable transit service. Research remains mixed on whether ride-hailing serves as a modal complement or substitute to transit or whether ride-hailing fills transit service needs gaps. This study measures transit supply in Chicago and compares it to ride-hailing origins and destinations to examine if ride-hailing fills existing transit service gaps. Findings reveal clustering of ride-hailing pickups and drop-offs across the City of Chicago, but that the number of ride-hailing pickups and drop-offs was most strongly associated with high neighborhood median household income rather than measures of transit supply. In bivariate analyses, transit service was not associated with ride-hailing trip ends. But after controlling for neighborhood socioeconomic status, transit dependency, population density, and employment density, we found fewer ride-hailing trips in neighborhoods where bus service dominated and significantly more ride-hailing trips where rail service was prevalent. Patterns were slightly different for overnight weekend ride-hailing pick-ups, where higher transit density predicted a greater number of trips in nearby tracts. Additional research and policy is needed to ensure that ride-hailing services provide travel options to those who need them the most and fill transit gaps in low-income communities when options to increase service are limited.
Optimal Control of a Thermistor Problem with Vanishing Conductivity

An optimal control of a steady state thermistor problem is considered where the convective boundary coefficient is taken to be the control variable. A distinct feature of this paper is that the problem is considered in $${\mathbb {R}}^d$$, where $$d>2$$, and the electrical conductivity is allowed to vanish above a threshold temperature value. Existence of the state system is proved. An objective functional is introduced, existence of the optimal control is proved, and the optimality system is derived.
Mixing of the Exclusion Process with Small Bias

We analyze the mixing behavior of the biased exclusion process on a path of length n as the bias $$\beta _n$$ tends to 0 as $$n \rightarrow \infty $$ . We show that the sequence of chains has a pre-cutoff, and interpolates between the unbiased exclusion and the process with constant bias. As the bias increases, the mixing time undergoes two phase transitions: one when $$\beta _n$$ is of order 1 / n, and the other when $$\beta _n$$ is order $$\log n/n$$ .
Stirring by squirmers

We analyse a simple ‘Stokesian squirmer’ model for the enhanced mixing due to swimming micro-organisms. The model is based on a calculation of Thiffeault & Childress (Phys. Lett. A, vol. 374, 2010, p. 3487), where fluid particle displacements due to inviscid swimmers are added to produce an effective diffusivity. Here we show that, for the viscous case, the swimmers cannot be assumed to swim an infinite distance, even though their total mass displacement is finite. Instead, the largest contributions to particle displacement, and hence to mixing, arise from random changes of direction of swimming and are dominated by the far-field stresslet term in our simple model. We validate the results by numerical simulation. We also calculate non-zero Reynolds number corrections to the effective diffusivity. Finally, we show that displacements due to randomly swimming squirmers exhibit probability distribution functions with exponential tails and a short-time superdiffusive regime, as found previously by several authors. In our case, the exponential tails are due to ‘sticking’ near the stagnation points on the squirmer's surface.
Finding the Next Superhard Material through Ensemble Learning.

An ensemble machine-learning method is demonstrated to be capable of finding superhard materials by directly predicting the load-dependent Vickers hardness based only on the chemical composition. A total of 1062 experimentally measured load-dependent Vickers hardness data are extracted from the literature and used to train a supervised machine-learning algorithm utilizing boosting, achieving excellent accuracy (R2 = 0.97). This new model is then tested by synthesizing and measuring the load-dependent hardness of several unreported disilicides and analyzing the predicted hardness of several classic superhard materials. The trained ensemble method is then employed to screen for superhard materials by examining more than 66 000 compounds in crystal structure databases, which show that 68 known materials have a Vickers hardness ≥40 GPa at 0.5 N (applied force) and only 10 exceed this mark at 5 N. The hardness model is then combined with the data-driven phase diagram generation tool to expand the limited number of reported high hardness compounds. Eleven ternary borocarbide phase spaces are studied, and more than ten thermodynamically favorable compositions with a hardness above 40 GPa (at 0.5 N) are identified, proving this ensemble model's ability to find previously unknown materials with outstanding mechanical properties.
Origin of robust exceptional points: Restricted bulk zero-mode

We unveil the origin of robust exceptional points in photonic lattices: without invoking sublattice symmetry, this exceptional point is a restricted bulk zero-mode that meets certain condition only in the site adjacent to the boundary.
Biobank Scale Pharmacogenomics Informs the Genetic Underpinnings of Simvastatin Use.

Studying drug-metabolizing enzymes, encoded by pharmacogenes, may inform biological mechanisms underlying the diseases for which a medication is prescribed. Until recently, pharmacogenes could not be studied at biobank scale. In 7,649 unrelated African-ancestry (AFR) and 326,214 unrelated European-ancestry (EUR) participants from the UK Biobank, we associated pharmacogene haplotypes from 50 genes with 265 (EUR) and 17 (AFR) medication use phenotypes using generalized linear models. In EUR, N-acetyltransferase 2 (NAT2) metabolizer phenotype and activity score were associated with simvastatin use. The dose of NAT2*1 was associated with simvastatin use when compared with NAT2*5 (the most common haplotype). This association was robust to effects of low-density lipoprotein cholesterol (LDL-C) concentration (NAT2*1 odds ratio (OR) = 1.07, 95% CI: 1.05-1.09, P = 1.14 × 10-8 ) and polygenic risk for LDL-C concentration (NAT2*1 OR = 1.09, 95% CI: 1.04-1.14, P = 2.26 × 10-4 ). Interactive effects between NAT2*1 and simvastatin use on LDL-C concentration (OR = 0.957, 95% CI: 0.916-0.998, P = 0.045) were replicated in the electronic Medical Records and Genomics Pharmacogenetic Sequencing Pilot (eMERGE-PGx) cohort (OR = 0.987, 95% CI: 0.976-0.998, P = 0.029). We used biobank-scale data to uncover and replicate an association between NAT2 locus variation and better response to statin therapy. Testing NAT2 alleles may be useful for making clinical decisions regarding the potential benefit (e.g., absolute risk reduction) in LDL-C concentration prior to statin treatment.
High Fermi velocities and small cyclotron masses in LaAlGe

We report quantum oscillation measurements of LaAlGe, a Lorentz-violating type-II Weyl semimetal with tilted Weyl cones. Very small quasiparticle masses and very high Fermi velocities were detected at the Fermi surface. Whereas three main frequencies have been observed, the angular dependence of two Fermi surface sheets indicates possible two-dimensional (2D) character despite the absence of the 2D structural features such as van der Waals bonds. Such conducting states may offer a good platform for low-dimensional polarized spin current in magnetic RAlGe (R = Ce, Pr) materials.
An automated homecage system for multiwhisker detection and discrimination learning in mice

Automated, homecage behavioral training for rodents has many advantages: it is low stress, requires little interaction with the experimenter, and can be easily manipulated to adapt to different experimental conditions. We have developed an inexpensive, Arduino-based, homecage training apparatus for sensory association training in freely-moving mice using multiwhisker air current stimulation coupled to a water reward. Animals learn this task readily, within 1-2 days of training, and performance progressively improves with training. We examined the parameters that regulate task acquisition using different stimulus intensities, directions, and reward valence. Learning was assessed by comparing anticipatory licking for the stimulus compared to the no-stimulus (blank) trials. At high stimulus intensities (>9 psi), animals showed markedly less participation in the task. Conversely, very weak air current intensities (1-2 psi) were not sufficient to generate rapid learning behavior. At intermediate stimulus intensities (5-6 psi), a majority of mice learned that the multiwhisker stimulus predicted the water reward after 24-48 hrs of training. Both exposure to isoflurane and lack of whiskers decreased animals' ability to learn the task. Following training at an intermediate stimulus intensity, mice were able to transfer learning behavior when exposed to a lower stimulus intensity, an indicator of perceptual learning. Mice learned to discriminate between two directions of stimulation rapidly and accurately, even when the angular distance between the stimuli was <15 degrees. Switching the reward to a more desirable reward, aspartame, had little effect on learning trajectory. Our results show that a tactile association task in an automated homecage environment can be monitored by anticipatory licking to reveal rapid and progressive behavioral change. These Arduino-based, automated mouse cages enable high-throughput training that facilitate analysis of large numbers of genetically modified mice with targeted manipulations of neural activity.
Determining The Magnetic Potential In The Fractional Magnetic Calder\'on Problem

We determine both the magnetic potential and the electric potential from the exterior partial measurements of the Dirichlet-to-Neumann map in the fractional linear magnetic Calderon problem by usin...
New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics

Motivation Accurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target-decoy approaches (TDAs) and decoy-free approaches (DFAs) have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra. Results We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms. Availabilityand implementation https://github.com/shawn-peng/FDR-estimation. Supplementary information Supplementary data are available at Bioinformatics online.
Speaker Separation Using Speaker Inventories and Estimated Speech

We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation. SSUSIES contains two methods, speaker separation using speaker inventories (SSUSI) and speaker separation using estimated speech (SSUES). SSUSI performs speaker separation with the help of speaker inventory. By combining the advantages of permutation invariant training (PIT) and speech extraction, SSUSI significantly outperforms conventional approaches. SSUES is a widely applicable technique that can substantially improve speaker separation performance using the output of first-pass separation. We evaluate the models on both speaker separation and speech recognition metrics.
The activity of yeast Apn2 AP endonuclease at uracil-derived AP sites is dependent on the major carbon source

Yeast Apn2 is an AP endonuclease and DNA 3'-diesterase that belongs to the Exo III family with homology to the E. coli exonuclease III, Schizosaccharomyces pombe eth1, and human AP endonucleases APEX1 and APEX2. In the absence of Apn1, the major AP endonuclease in yeast, Apn2 can cleave the DNA backbone at an AP lesion initiating the base excision repair pathway. To study the role and relative contribution of Apn2, we took advantage of a reporter system that was previously used to delineate how uracil-derived AP sites are repaired. At this reporter, disruption of the Apn1-initiated base excision repair pathway led to a significant elevation of A:T to C:G transversions. Here we show that such highly elevated A:T to C:G transversion mutations associated with uracil residues in DNA are abolished when apn1∆ yeast cells are grown in glucose as the primary carbon source. We also show that the disruption of Apn2, either by the complete gene deletion or by the mutation of a catalytic residue, results in a similarly reduced rate of the uracil-associated mutations. Overall, our results indicate that Apn2 activity is regulated by the glucose repression pathway in yeast.
Higher-dimensional gap theorems for the maximum metric

Recently, the first author together with Jens Marklof studied generalizations of the classical three distance theorem to higher-dimensional toral rotations, giving upper bounds in all dimensions fo...
Shape Memory Alloys and Their Applications in Power Generation and Refrigeration

The shape memory effect is closely related to the reversible martensitic phase transformation, which is diffusionless and involves shear deformation. The recoverable transformation between the two phases with different crystalline symmetry results in reversible changes in physical properties such as electrical conductivity, magnetization, and elasticity. Accompanying the transformation is a change of entropy. Fascinating applications are developed based on these changes. In this paper, the history, fundamentals and technical challenges of both thermoelastic and ferromagnetic shape memory alloys are briefly reviewed; applications related to energy conversion such as power generation and refrigeration as well as recent developments will be discussed.
A Pedagogy of Preparation: Helping Underprepared Students Succeed in College-Level Coursework in Community Colleges

This paper presents an overall educational philosophy of working with students underprepared for college-level work, which we term “a pedagogy of preparation.” We consider how instructors scaffolded instruction to foster college readiness in students who were now able to enroll in college-level work regardless of academic preparation after state-level legislation (SB 1720) that dramatically altered the delivery of developmental education in the Florida College System (FCS). We also consider how collaboration increased among campus personnel after the legislation to foster college readiness in students underprepared for college-level work.
A novel machine learning-based optimization algorithm (ActivO) for accelerating simulation-driven engine design

Abstract A novel design optimization approach (ActivO) that employs an ensemble of machine learning algorithms is presented. The proposed approach is a surrogate-based scheme, where the predictions of a weak leaner and a strong learner are utilized within an active learning loop. The weak learner is used to identify promising regions within the design space to explore, while the strong learner is used to determine the exact location of the optimum within promising regions. For each design iteration, exploration is done by randomly selecting evaluation points within regions where the weak learner-predicted fitness is high. The global optimum obtained by using the strong learner as a surrogate is also evaluated to enable rapid convergence once the most promising region has been identified. First, the performance of ActivO was compared against five other optimizers on a cosine mixture function with 25 local optima and one global optimum. In the second problem, the objective was to minimize indicated specific fuel consumption of a compression-ignition internal combustion (IC) engine while adhering to desired constraints associated with in-cylinder pressure and emissions. Here, the efficacy of the proposed approach is compared to that of a genetic algorithm, which is widely used within the internal combustion engine community for engine optimization, showing that ActivO reduces the number of function evaluations needed to reach the global optimum, and thereby time-to-design by 80%. Furthermore, the optimization of engine design parameters leads to savings of around 1.9% in energy consumption, while maintaining operability and acceptable pollutant emissions.
A review of archival auditing research

Abstract We define higher audit quality as greater assurance of high financial reporting quality. Researchers use many proxies for audit quality, with little guidance on choosing among them. We provide a framework for systematically evaluating their unique strengths and weaknesses. Because it is inextricably intertwined with financial reporting quality, audit quality also depends on firms’ innate characteristics and financial reporting systems. Our review of the models commonly used to disentangle these constructs suggests the need for better conceptual guidance. Finally, we urge more research on the role of auditor and client competency in driving audit quality.