cssi/SciSciGPT-SciSciNet huggingface dataset:
NONLINEAR BEHAVIOR OF BARYON ACOUSTIC OSCILLATIONS FROM THE ZEL'DOVICH APPROXIMATION USING A NON-FOURIER PERTURBATION APPROACH

Baryon acoustic oscillations are an excellent technique to constrain the properties of dark energy in the universe. In order to accurately characterize the dark energy equation of state, we must understand the effects of both the nonlinearities and redshift space distortions on the location and shape of the acoustic peak. In this paper, we consider these effects using the Zel'dovich approximation and a novel approach to second-order perturbation theory. The second-order term of the Zel'dovich power spectrum is built from convolutions of the linear power spectrum with polynomial kernels in Fourier space, suggesting that the corresponding term of the Zel'dovich correlation function can be written as a sum of quadratic products of a broader class of correlation functions, expressed through simple spherical Bessel transforms of the linear power spectrum. We show how to systematically perform such a computation. We explicitly prove that our result is the Fourier transform of the Zel'dovich power spectrum and compare our expressions to numerical simulations. Finally, we highlight the advantages of writing the nonlinear expansion in configuration space, as this calculation is easily extended to redshift space, and the higher-order terms are mathematically simpler than their Fourier counterparts.
Is the Lightest Kaluza-Klein Particle a Viable Dark Matter Candidate?

Abstract In models with universal extra dimensions (i.e., in which all Standard Model fields, including fermions, propagate into compact extra dimensions) momentum conservation in the extra dimensions leads to the conservation of Kaluza–Klein (KK) number at each vertex. KK number is violated by loop effects because of the orbifold imposed to reproduce the chiral Standard Model with zero modes, however, a KK parity remains at any order in perturbation theory which leads to the existence of a stable lightest KK particle (LKP). In addition, the degeneracy in the KK spectrum is lifted by radiative corrections so that all other KK particles eventually decay into the LKP. We investigate cases where the Standard Model lives in five or six dimensions with compactification radius of TeV−1 size and the LKP is the first massive state in the KK tower of either the photon or the neutrino. We derive the relic density of the LKP under a variety of assumptions about the spectrum of first tier KK modes. We find that both the KK photon and the KK neutrino, with masses at the TeV scale, may have appropriate annihilation cross sections to account for the dark matter, Ω M ∼0.3 .
Structured Attention for Unsupervised Dialogue Structure Induction

Inducing a meaningful structural representation from one or a set of dialogues is a crucial but challenging task in computational linguistics. Advancement made in this area is critical for dialogue system design and discourse analysis. It can also be extended to solve grammatical inference. In this work, we propose to incorporate structured attention layers into a Variational Recurrent Neural Network (VRNN) model with discrete latent states to learn dialogue structure in an unsupervised fashion. Compared to a vanilla VRNN, structured attention enables a model to focus on different parts of the source sentence embeddings while enforcing a structural inductive bias. Experiments show that on two-party dialogue datasets, VRNN with structured attention learns semantic structures that are similar to templates used to generate this dialogue corpus. While on multi-party dialogue datasets, our model learns an interactive structure demonstrating its capability of distinguishing speakers or addresses, automatically disentangling dialogues without explicit human annotation.
A Low Mach Number Model for Moist Atmospheric Flows

AbstractA low Mach number model for moist atmospheric flows is introduced that accurately incorporates reversible moist processes in flows whose features of interest occur on advective rather than acoustic time scales. Total water is used as a prognostic variable, so that water vapor and liquid water are diagnostically recovered as needed from an exact Clausius–Clapeyron formula for moist thermodynamics. Low Mach number models can be computationally more efficient than a fully compressible model, but the low Mach number formulation introduces additional mathematical and computational complexity because of the divergence constraint imposed on the velocity field. Here, latent heat release is accounted for in the source term of the constraint by estimating the rate of phase change based on the time variation of saturated water vapor subject to the thermodynamic equilibrium constraint. The authors numerically assess the validity of the low Mach number approximation for moist atmospheric flows by contrasting t...
Mirror symmetry and line operators

We study half-BPS line operators in 3d $$ \mathcal{N} $$ = 4 gauge theories, focusing in particular on the algebras of local operators at their junctions. It is known that there are two basic types of such line operators, distinguished by the SUSY subalgebras that they preserve; the two types can roughly be called “Wilson lines” and “vortex lines,” and are exchanged under 3d mirror symmetry. We describe a large class of vortex lines that can be characterized by basic algebraic data, and propose a mathematical scheme to compute the algebras of local operators at their junctions — including monopole operators — in terms of this data. The computation generalizes mathematical and physical definitions/analyses of the bulk Coulomb-branch chiral ring. We fully classify the junctions of half-BPS Wilson lines and of half-BPS vortex lines in abelian gauge theories with sufficient matter. We also test our computational scheme in a non-abelian quiver gauge theory, using a 3d-mirror-map of line operators from work of Assel and Gomis.
Theoretical Models of Optical Transients. I. A Broad Exploration of the Duration–Luminosity Phase Space

The duration-luminosity phase space of optical transients is used, mostly heuristically, to compare various classes of transient events, to explore the origin of new transients, and to influence optical survey observing strategies. For example, several observational searches have been guided by intriguing voids and gaps in this phase space. However we should ask: Do we expect to find transients in these voids given our understanding of the various heating sources operating in astrophysical transients? In this work, we explore a broad range of theoretical models and empirical relations to generate optical light curves and to populate the duration-luminosity phase space (DLPS). We explore transients powered by adiabatic expansion, radioactive decay, magnetar spin-down, and circumstellar interaction. For each heating source, we provide a concise summary of the basic physical processes, a physically motivated choice of model parameter ranges, an overall summary of the resulting light curves and their the occupied range in the DLPS, and how the various model input parameters affect the light curves. We specifically explore the key voids discussed in the literature: the intermediate luminosity gap between classical novae and supernovae, and short-duration transients ( -15 mag). Finally, we explore the detection potential of optical surveys (e.g., LSST) in the DLPS and quantify the notion that short-duration and dim transients are exponentially more difficult to discover in untargeted surveys.
Straight-Leg Walking Through Underconstrained Whole-Body Control

We present an approach for achieving a natural, efficient gait on bipedal robots using straightened legs and toe-off. Our algorithm avoids complex height planning by allowing a whole-body controller to determine the straightest possible leg configuration at run-time. The controller solutions are biased towards a straight leg configuration by projecting leg joint angle objectives into the null-space of the other quadratic program motion objectives. To allow the legs to remain straight throughout the gait, toe-off was utilized to increase the kinematic reachability of the legs. The toe-off motion is achieved through underconstraining the foot position, allowing it to emerge naturally. We applied this approach of under-specifying the motion objectives to the Atlas humanoid, allowing it to walk over a variety of terrain. We present both experimental and simulation results and discuss performance limitations and potential improvements.
Control and ultrasonic actuation of a gas–liquid interface in a microfluidic chip

This paper describes the design and manufacturing of a microfluidic chip, allowing for the actuation of a gas–liquid interface and of the neighboring fluid. The first way to control the interface motion is to apply a pressure difference across it. In this case, the efficiency of three different micro-geometries at anchoring the interface is compared. Also, the critical pressures needed to move the interface are measured and compared to a theoretical result. The second way to control the interface motion is by ultrasonic excitation. When the excitation is weak, the interface exhibits traveling waves, which follow a dispersion equation. At stronger ultrasonic levels, standing waves appear on the interface, with frequencies that are half the integer multiple of the excitation frequency. An associated microstreaming flow field observed in the vicinity of the interface is characterized. The meniscus and associated streaming flow have the potential to transport particles and mix reagents.
FLUCTUATION THEOREMS WITHOUT TIME-REVERSAL SYMMETRY

Fluctuation theorems establish deep relations between observables away from thermal equilibrium. Until recently, the research on fluctuation theorems was focused on time-reversal-invariant systems. In this review we address some newly discovered fluctuation relations that hold without the time-reversal symmetry, in particular, in the presence of an external magnetic field. One family of relations connects nonlinear transport coefficients in the opposite magnetic fields. Another family relates currents and noises at a fixed direction of the magnetic field in chiral systems, such as the edges of some quantum Hall liquids. We review the recent experimental and theoretical research, including the controversy about the microreversibility without the time-reversal symmetry, consider the applications of fluctuation theorems to the physics of topological states of matter, and discuss open problems.
Probing Blazar Emission Processes with Optical/Gamma-Ray Flare Correlations

Even with several thousand {\it Fermi}-LAT blazar detections, the $\gamma$-ray emission mechanism is poorly understood. We explore correlated optical/$\gamma$-ray flux variations for 178 {\it Fermi}-LAT blazars regularly monitored by KAIT, SMARTS, and the Steward Observatory. Out of the 178 sources, 121 show a measurable ($>1\sigma$) discrete correlation function peak. Using the derived time-lags and Bayesian block light-curve decompositions, we measure the fraction of common and orphan flares between the two bands. After accounting for sampling and sensitivity limitations we quantify for the first time the true orphan flare rates of optical and $\gamma$-ray flares: 54.5\% of optical and 20\% of $\gamma$-ray flares are orphan events. Both the intraband temporal relation and the small orphan $\gamma$-ray flare fraction point toward leptonic processes as the likely mechanism for the high-energy emission. Motivated to discriminate between synchrotron self-Compton and external-Compton dominance in individual sources, we use the flux-flux variations to determine the slope $m$ of the ${\rm log}\,f_{\rm opt} - {\rm log}\,f_{\gamma}$ dependence. The slope distribution suggests a bimodal population with high and intermediate synchrotron-peak objects showing larger $m$ than low synchrotron-peak objects. We find that $m$ is naturally decreased through pollution from the orphan (typically optical) flares and develop a method to statistically recover, given the sources' measured orphan flare rate, the intrinsic $m$. While source classes show composite behavior, the majority of BL Lac objects favor $m=2$, indicating a synchrotron self-Compton origin for the $\gamma$-rays. No preference for either $m$ is found in flat spectrum radio quasars.
An atomistic fingerprint algorithm for learning ab initio molecular force fields.

Molecular fingerprints, i.e., feature vectors describing atomistic neighborhood configurations, is an important abstraction and a key ingredient for data-driven modeling of potential energy surface and interatomic force. In this paper, we present the density-encoded canonically aligned fingerprint algorithm, which is robust and efficient, for fitting per-atom scalar and vector quantities. The fingerprint is essentially a continuous density field formed through the superimposition of smoothing kernels centered on the atoms. Rotational invariance of the fingerprint is achieved by aligning, for each fingerprint instance, the neighboring atoms onto a local canonical coordinate frame computed from a kernel minisum optimization procedure. We show that this approach is superior over principal components analysis-based methods especially when the atomistic neighborhood is sparse and/or contains symmetry. We propose that the “distance” between the density fields be measured using a volume integral of their pointwise difference. This can be efficiently computed using optimal quadrature rules, which only require discrete sampling at a small number of grid points. We also experiment on the choice of weight functions for constructing the density fields and characterize their performance for fitting interatomic potentials. The applicability of the fingerprint is demonstrated through a set of benchmark problems.
Torsional rigidity, isospectrality and quantum graphs

We study torsional rigidity for graph and quantum graph analogs of well-known pairs of isospectral non-isometric planar domains. We prove that such isospectral pairs are distinguished by torsional rigidity.
Two-dimensional algebra in lattice gauge theory

We provide a visual and intuitive introduction to effectively calculating in 2-groups along with explicit examples coming from non-Abelian 1- and 2-form gauge theory. In particular, we utilize string diagrams, tools similar to tensor networks, to compute the parallel transport along a surface using approximations on a lattice. We prove a convergence theorem for the surface transport in the continuum limit. Locality is used to define infinitesimal parallel transport, and two-dimensional algebra is used to derive finite versions along arbitrary surfaces with sufficient orientation data. The correct surface ordering is dictated by two-dimensional algebra and leads to an interesting diagrammatic picture for gauge fields interacting with particles and strings on a lattice. The surface ordering is inherently complicated, but we prove a simplification theorem confirming earlier results of Schreiber and Waldorf. Assuming little background, we present a simple way to understand some abstract concepts of higher category theory. In doing so, we review all the necessary categorical concepts from the tensor network point of view as well as many aspects of higher gauge theory.We provide a visual and intuitive introduction to effectively calculating in 2-groups along with explicit examples coming from non-Abelian 1- and 2-form gauge theory. In particular, we utilize string diagrams, tools similar to tensor networks, to compute the parallel transport along a surface using approximations on a lattice. We prove a convergence theorem for the surface transport in the continuum limit. Locality is used to define infinitesimal parallel transport, and two-dimensional algebra is used to derive finite versions along arbitrary surfaces with sufficient orientation data. The correct surface ordering is dictated by two-dimensional algebra and leads to an interesting diagrammatic picture for gauge fields interacting with particles and strings on a lattice. The surface ordering is inherently complicated, but we prove a simplification theorem confirming earlier results of Schreiber and Waldorf. Assuming little background, we present a simple way to understand some abstract concepts of higher cat...
BLEU might be Guilty but References are not Innocent

The quality of automatic metrics for machine translation has been increasingly called into question, especially for high-quality systems. This paper demonstrates that, while choice of metric is important, the nature of the references is also critical. We study different methods to collect references and compare their value in automated evaluation by reporting correlation with human evaluation for a variety of systems and metrics. Motivated by the finding that typical references exhibit poor diversity, concentrating around translationese language, we develop a paraphrasing task for linguists to perform on existing reference translations, which counteracts this bias. Our method yields higher correlation with human judgment not only for the submissions of WMT 2019 English to German, but also for Back-translation and APE augmented MT output, which have been shown to have low correlation with automatic metrics using standard references. We demonstrate that our methodology improves correlation with all modern evaluation metrics we look at, including embedding-based methods.To complete this picture, we reveal that multi-reference BLEU does not improve the correlation for high quality output, and present an alternative multi-reference formulation that is more effective.
TARN: A SDN-based traffic analysis resistant network architecture

Destination IP prefix-based routing protocols are core to Internet routing today. Internet autonomous systems (AS) possess fixed IP prefixes, while packets carry the intended destination AS's prefix in their headers, in clear text. As a result, network communications can be easily identified using IP addresses and become targets of a wide variety of attacks, such as DNS/IP filtering, distributed Denial-of-Service (DDoS) attacks, man-in-the-middle (MITM) attacks, etc. In this work, we explore an alternative network architecture that fundamentally removes such vulnerabilities by disassociating the relationship between IP prefixes and destination networks, and by allowing any end-to-end communication session to have dynamic, short-lived, and pseudo-random IP addresses drawn from a range of IP prefixes rather than one. The concept is seemingly impossible to realize in todays Internet. We demonstrate how this is doable today with three different strategies using software defined networking (SDN), and how this can be done at scale to transform the Internet addressing and routing paradigms with the novel concept of a distributed software defined Internet exchange (SDX). The solution works with both IPv4 and IPv6, whereas the latter provides higher degrees of IP addressing freedom. Prototypes based on Open vSwitches (OVS) have been implemented for experimentation across the PEERING BGP testbed. The SDX solution not only provides a technically sustainable pathway towards large-scale traffic analysis resistant network (TARN) support, it also unveils a new business model for customer-driven, customizable and trustable end-to-end network services.
Conserved currents for electromagnetic fields in the Kerr spacetime

We construct a variety of conserved currents for test electromagnetic fields on a Kerr background. Our procedure, which involves the symplectic product for electromagnetism and symmetry operators, generates the conserved currents given by Andersson, Backdahl, and Blue (2015), as well as a new conserved current. These currents reduce to the sum of (positive powers of) the Carter constants of photons in the geometric optics limit, and generalize the current for scalar fields discovered by Carter (1977) involving the Killing tensor. We furthermore show that the fluxes of our new current through null infinity and the horizon are finite.
Inflation as a response to protect the Holographic Principle

A model where the inflationary phase emerges as a response to protect the Fischler–Susskind holographic bound is described. A two-fluid model in a closed universe inflation picture is assumed, and a discussion on conditions under which it is possible to obtain an additional exponential expansion phase as those currently observed is given.
Fast Communication-Efficient Spectral Clustering over Distributed Data

The last decades have seen a surge of interests in distributed computing thanks to advances in clustered computing and big data technology. Existing distributed algorithms typically assume all the data are already in one place , and divide the data and conquer on multiple machines. However, it is increasingly often that the data are located at a number of distributed sites, and one wishes to compute over all the data with low communication overhead. For spectral clustering, we propose a novel framework that enables its computation over such distributed data, with “minimal” communications while a major speedup in computation. The loss in accuracy is negligible compared to the non-distributed setting. Our approach allows local parallel computing at where the data are located, thus turns the distributed nature of the data into a blessing; the speedup is most substantial when the data are evenly distributed across sites. Experiments on synthetic and large UC Irvine datasets show almost no loss in accuracy with our approach while a 2x speedup under various settings with two distributed sites. As the transmitted data need not be in their original form, our framework readily addresses the privacy concern for data sharing in distributed computing.
Gaining insight from large data volumes with ease

Efficient handling of large data-volumes becomes a necessity in today’s world. It is driven by the desire to get more insight from the data and to gain a better understanding of user trends which can be transformed into economic incentives (profits, cost-reduction, various optimization of data workflows, and pipelines). In this paper, we discuss how modern technologies are transforming well established patterns in HEP communities. The new data insight can be achieved by embracing Big Data tools for a variety of use cases, from analytics and monitoring to training Machine Learning models on a terabyte scale. We provide concrete examples within the context of the CMS experiment where Big Data tools are already playing or would play a significant role in daily operations
A Spread-Spectrum SQUID Multiplexer

The transition-edge sensor (TES) is a mature, high-resolution x-ray spectrometer technology that provides a much higher efficiency than dispersive spectrometers such as gratings and crystal spectrometers. As larger arrays are developed, time-division multiplexing schemes operating at MHz frequencies are being replaced by microwave SQUID multiplexers using frequency-division multiplexing at GHz frequencies. However, the multiplexing factor achievable with microwave SQUIDs is limited by the high slew rate on the leading edge of x-ray pulses. In this paper, we propose a new multiplexing scheme for high-slew-rate TES x-ray calorimeters: the spread-spectrum SQUID multiplexer, which has the potential to enable higher multiplexing factors, especially in applications with lower photon-arrival rates.
Rank parity for congruent supersingular elliptic curves

A recent paper of Shekhar compares the ranks of elliptic curves $E_1$ and $E_2$ for which there is an isomorphism $E_1[p] \simeq E_2[p]$ as $\mathrm{Gal}(\bar{\mathbf{Q}}/\mathbf{Q})$-modules, where $p$ is a prime of good ordinary reduction for both curves. In this paper we prove an analogous result in the case where $p$ is a prime of good supersingular reduction.
An acoustical analogue of a galactic-scale gravitational-wave detector

By precisely monitoring the “ticks” of Nature's most precise clocks (millisecond pulsars), scientists are trying to detect the “ripples in spacetime” (gravitational waves) produced by the inspirals of supermassive black holes in the centers of distant merging galaxies. Here, we describe a relatively simple demonstration that uses two metronomes and a microphone to illustrate several techniques used by pulsar astronomers to search for and detect gravitational waves. An adapted version of this demonstration could be used as an instructional laboratory investigation at the undergraduate level.
ON THE VALIDITY OF COLLIDER-MASS SCALING FOR MOLECULAR ROTATIONAL EXCITATION

Rate coefficients for collisional processes such as rotational and vibrational excitation are essential inputs in many astrophysical models. When rate coefficients are unknown, they are often estimated using known values from other systems. The most common example is to use He-collider rate coefficients to estimate values for other colliders, typically H2, using scaling arguments based on the reduced mass of the collision system. This procedure is often justified by the assumption that the inelastic cross section is independent of the collider. Here we explore the validity of this approach focusing on rotational inelastic transitions for collisions of H, para-H2, 3 He, and 4 He with CO in its vibrational ground state. We compare rate coefficients obtained via explicit calculations to those deduced by standard reduced-mass scaling. Not surprisingly, inelastic cross sections and rate coefficients are found to depend sensitively on both the reduced mass and the interaction potential energy surface. We demonstrate that standard reduced-mass scaling is not valid on physical and mathematical grounds, and as a consequence, the common approach of multiplying a rate coefficient for a molecule-He collision system by the constant factor of ∼1.4 to estimate the rate coefficient for para-H2 collisions is deemed unreliable. Furthermore, we test an alternative analytic scaling approach based on the strength of the interaction potential and the reduced mass of the collision systems. Any scaling approach, however, may be problematic when low-energy resonances are present; explicit calculations or measurements of rate coefficients are to be preferred.
Pedestrian Motion Model Using Non-Parametric Trajectory Clustering and Discrete Transition Points

This letter presents a pedestrian motion model that includes both low level trajectory patterns, and high level discrete transitions. The inclusion of both levels creates a more general predictive model, allowing for more meaningful prediction and reasoning about pedestrian trajectories, as compared to the current state of the art. The model uses an iterative clustering algorithm with Dirichlet Process Gaussian Processes to cluster trajectories into continuous motion patterns and hypothesis testing to identify discrete transitions in the data called transition points . The model iteratively splits full trajectories into sub-trajectory clusters based on transition points, where pedestrians make discrete decisions. State transition probabilities are then learned over the transition points and trajectory clusters. The model is for online prediction of motions, and detection of anomalous trajectories. The proposed model is validated on the Duke Multi-Target, Multi-Camera Tracking Project (Duke MTMC) dataset to demonstrate identification of low level trajectory clusters and high level transitions, and the ability to predict pedestrian motion and detect anomalies online with high accuracy.
Structured Pruning of Large Language Models

Large language models have recently achieved state of the art performance across a wide variety of natural language tasks. Meanwhile, the size of these models and their latency have significantly increased, which makes their usage costly, and raises an interesting question: do language models need to be large? We study this question through the lens of model compression. We present a generic, structured pruning approach by parameterizing each weight matrix using its low-rank factorization, and adaptively removing rank-1 components during training. On language modeling tasks, our structured approach outperforms other unstructured and block-structured pruning baselines at various compression levels, while achieving significant speedups during both training and inference. We also demonstrate that our method can be applied to pruning adaptive word embeddings in large language models, and to pruning the BERT model on several downstream fine-tuning classification benchmarks.
SPIN-ORBIT CORRELATIONS AND SINGLE-SPIN ASYMMETRIES

Several examples for the role of orbital angular momentum and spin-orbit correlations in hadron structure are discussed.
Contractibility of deformation spaces of G-trees

Forester has defined spaces of simplicial tree actions for a finitely generated group, called deformation spaces. Culler and Vogtmann’s Outer space is an example of a deformation space. Using ideas from Skora’s proof of the contractibility of Outer space, we show that under some mild hypotheses deformation spaces are contractible. AMS Classification 20E08; 20F65, 20F28
DIRECT DETECTION OF PLANETS ORBITING LARGE ANGULAR DIAMETER STARS: SENSITIVITY OF AN INTERNALLY OCCULTING SPACE-BASED CORONAGRAPH

High-contrast imaging observations of large angular diameter stars enable complementary science questions to be addressed compared to the baseline goals of proposed missions like the Terrestrial Planet Finder-Coronagraph, New World's Observer, and others. Such targets, however, present a practical problem in that finite stellar size results in unwanted starlight reaching the detector, which degrades contrast. In this paper, we quantify the sensitivity, in terms of contrast, of an internally occulting, space-based coronagraph as a function of stellar angular diameter, from unresolved dwarfs to the largest evolved stars. Our calculations show that an assortment of band-limited image masks can accommodate a diverse set of observations to help maximize mission scientific return. We discuss two applications based on the results: the spectro-photometric study of planets already discovered with the radial velocity technique to orbit evolved stars, which we elucidate with the example of Pollux b, and the direct detection of planets orbiting our closest neighbor, α Centauri, whose primary component is on the main sequence but subtends an appreciable angle on the sky. It is recommended that similar trade studies be performed with other promising internal, external, and hybrid occulter designs for comparison, as there is relevance to a host of interesting topics in planetary science and related fields.
Tight-binding parameters from the full-potential linear muffin-tin orbital method: A feasibility study on NiAl

We have examined a method of direct extraction of accurate tight-binding parameters from an ab-initio band-structure calculation. The linear muffin-tin potential method, in its full-potential implementation, has been used to provide the hamiltonian and overlap matrix elements in the momentum space. These matrix elements are Fourier transformed to real space to produce the tight-binding parameters. The feasibility of this method has been tested on the intermetallic alloy NiAl, using spd orbitals for each atom. The parameters generated for this alloy have been used as input to a real-space calculation of the local density of states using the recursion method.
Existence of Quasinormal Modes for Kerr–AdS Black Holes

This paper establishes the existence of quasinormal frequencies converging exponentially to the real axis for the Klein–Gordon equation on a Kerr–AdS spacetime when Dirichlet boundary conditions are imposed at the conformal boundary. The proof is adapted from results in Euclidean scattering about the existence of scattering poles generated by time-periodic approximate solutions to the wave equation.
A packaged, fiber-coupled waveguide-enhanced Raman spectroscopic sensor

Waveguide-enhanced Raman spectroscopy (WERS) is a promising technique for sensitive and selective detection of chemicals in a compact chip-scale platform. Coupling light on and off the sensor chip with fibers however presents challenges because of the fluorescence and Raman background generated by the pump light in the fibers; as a result all WERS demonstrations to date have used free-space coupling via lenses. We report a packaged, fiber-bonded WERS chip that filters the background on-chip through collection of the backscattered Raman light. The packaged sensor is integrated in a ruggedized flow cell for reliable measurement over arbitrary time periods. We also derive the figures of merit for WERS sensing with the backscattered Raman signal and compare waveguide geometries with respect to their filtering performance and signal to noise ratio.
Lipid Bilayer Hydrodynamic Drag

This paper uses imaging and tracking techniques to measure the drag coefficient of membrane spheres, showing that their properties are indistinguishable from those of solid spheres
THE DEVELOPMENT AND SCIENTIFIC IMPACT OF THE CHANDRA X-RAY OBSERVATORY

I review the operational capabilities of the Chandra X-ray Observatory, including some of the spectacular results obtained by the general observer community. A natural theme of this talk is that Chandra is revealing outflows of great quantities of energy that were not previously observable. I highlight the Chandra studies of powerful X-ray jets. This subject is only possible due to the sub-arcsecond resolution of the X-ray telescope.
Forces on fields

In electromagnetism, as in Newton's mechanics, action is always equal to reaction. The force from the electromagnetic field on matter is balanced by an equal and opposite force from matter on the field. We generally speak only of forces exerted by the field, not forces exerted upon the field. But, we should not be hesitant to speak of forces acting on the field. The electromagnetic field closely resembles a relativistic fluid and responds to forces in the same way. Analyzing this analogy sheds light on the inertial role played by the field's mass, the status of Maxwell's stress tensor, and the nature of the electromagnetic field.
U-duality and integral structures

Abstract We analyze the U-duality group of the case of a type II superstring compactified to four dimensions on a K3 surface times a torus. The various limits of this theory are considered which have interpretations as type IIA and IIB superstrings, the heterotic string, and eleven-dimensional supergravity, allowing all these theories to be directly related to each other. The integral structure which appears in the Ramond-Ramond sector of the type II superstring is related to the quantum cohomology of general Calabi-Yau threefolds which allows the moduli space of type II superstring compactifications on Calabi-Yau manifolds to be analyzed.
Quantum vorticity in nature

Quantum vorticity occurs in superfluidity, which arises from a spatial variation of the quantum phase. As such, it can occur in diverse systems over a wide range of scales, from the electroweak sector and QCD of the standard model of particle theory, through the everyday world, to the cosmos. I review the observable manifestations, and their unified description in terms of an order parameter that is a complex scalar field.
On the ample cone of a rational surface with an anticanonical cycle

Let Y be a smooth rational surface, and let D be a cycle of rational curves on Y that is an anticanonical divisor, i.e., an element of |−KY|. Looijenga studied the geometry of such surfaces Y in case D has at most five components and identified a geometrically significant subset R of the divisor classes of square −2 orthogonal to the components of D. Motivated by recent work of Gross, Hacking, and Keel on the global Torelli theorem for pairs (Y,D), we attempt to generalize some of Looijenga’s results in case D has more than five components. In particular, given an integral isometry f of H2(Y) that preserves the classes of the components of D, we investigate the relationship between the condition that f preserves the “generic” ample cone of Y and the condition that f preserves the set R.
PoliteCamera: Respecting Strangers’ Privacy in Mobile Photographing

Camera is a standard on-board sensor of modern mobile phones. It makes photo taking popular due to its convenience and high resolution. However, when users take a photo of a scenery, a building or a target person, a stranger may also be unintentionally captured in the photo. Such photos expose the location and activity of strangers, and hence may breach their privacy. In this paper, we propose a cooperative mobile photographing scheme called PoliteCamera to protect strangers’ privacy. Through the cooperation between a photographer and a stranger, the stranger’s face in a photo can be automatically blurred upon his request when the photo is taken. Since multiple strangers nearby the photographer might send out blurring requests but not all of them are in the photo, an adapted balanced convolutional neural network (ABCNN) is proposed to determine whether the requesting stranger is in the photo based on facial attributes. Evaluations demonstrate that the ABCNN can accurately predict facial attributes and PoliteCamera can provide accurate privacy protection for strangers.
LOW-METALLICITY ABSORBERS ACCOUNT FOR HALF OF THE DENSE CIRCUMGALACTIC GAS AT z ≲ 1* **

We present an analysis of the metallicity distribution of the dense circumgalactic medium (CGM) of galaxies at 0.1 19.0) show a much lower fraction of metal-poor gas; therefore, the metallicity distribution of gas in and around galaxies depends sensitively on N(H I) at z -1) pLLSs and LLSs as arising in outflows, recycling winds, and tidally-stripped gas around galaxies. The low-metallicity pLLSs and LLSs imply that the CGM of z < 1 galaxies is also host to a substantial mass of cool, dense, low-metallicity gas that may ultimately accrete onto the galaxies.
Strategies for Fiscal Consolidation in Japan

Abstract Japan's key fiscal challenge is to put public finances on a more sustainable footing. This paper investigates the macroeconomic implications of alternative fiscal strategies for Japan using the IMF's Global Fiscal Model. The results suggest that (i) an adjustment package that achieves primary balance through lower social transfers and government spending and a higher VAT is the most viable option and has a smaller negative impact on growth than other fiscal measures; (ii) achieving primary balance is not sufficient to stabilize the net debt ratio; (iii) prefunding future aging costs provides greater long-term benefits compared with less front-loaded strategies; (iv) tax reform involving shifting from corporate taxation to consumption taxation could mitigate the short-term output losses associated with fiscal consolidation; (v) the spillovers to the rest of the world from consolidation in Japan are positive in the medium term, but modest.
Synthetic-to-real domain adaptation for lane detection

Accurate lane detection, a crucial enabler for autonomous driving, currently relies on obtaining a large and diverse labeled training dataset. In this work, we explore learning from abundant, randomly generated synthetic data, together with unlabeled or partially labeled target domain data, instead. Randomly generated synthetic data has the advantage of controlled variability in the lane geometry and lighting, but it is limited in terms of photo-realism. This poses the challenge of adapting models learned on the unrealistic synthetic domain to real images. To this end we develop a novel autoencoder-based approach that uses synthetic labels unaligned with particular images for adapting to target domain data. In addition, we explore existing domain adaptation approaches, such as image translation and self-supervision, and adjust them to the lane detection task. We test all approaches in the unsupervised domain adaptation setting in which no target domain labels are available and in the semi-supervised setting in which a small portion of the target images are labeled. In extensive experiments using three different datasets, we demonstrate the possibility to save costly target domain labeling efforts. For example, using our proposed autoencoder approach on the llamas and tuSimple lane datasets, we can almost recover the fully supervised accuracy with only 10% of the labeled data. In addition, our autoencoder approach outperforms all other methods in the semi-supervised domain adaptation scenario.
Is Reading Prosody Related to Reading Comprehension? A Meta-analysis

We examined the relation between reading prosody and reading comprehension, using a systematic review and meta-analysis to estimate the strength of the relation and to understand whether the streng...
Power System Time Domain Simulation Using a Differential Transformation Method

This paper proposes a novel approach for power system dynamic simulation based on the Differential Transformation (DT). The DT is introduced to study power systems as high-dimensional nonlinear dynamical systems for the first time, and is able to avoid computations of high-order derivatives with nonlinear differential equations by its transform rules. This paper first proposes and proves several new transform rules for generic non-linear functions that often appear in power system models, and then uses these rules to transform representative power system models such as the synchronous machine model with trigonometric functions and the exciter model with exponential and square root functions. The paper also designs a DT-based simulation scheme that allows significantly prolonged time steps to reduce simulation time compared to a traditional numerical approach. The numerical stability, accuracy and time performance of the proposed new DT-based simulation approach are compared with widely used numerical methods on the IEEE 39-bus system and Polish 2383-bus system.
Estimates of electron correlation based on density expansions

Two methods for estimating the correlation energy of molecules and other electronic systems are discussed based on the assumption that the correlation energy can be partitioned between atomic regions. In the first method, the electron density is expanded in terms of atomic contributions using rigorous electron repulsion bounds, and in the second method, correlation contributions are associated with basis function pairs. These methods do not consider the detailed nature of localized excitations but instead define a correlation energy per electron factor that is unique to a specific atom. The correlation factors are basis function dependent and are determined by configuration interaction (CI) calculations on diatomic and hydride molecules. The correlation energy estimates are compared with the results of high-level CI calculations for a test set of 27 molecules representing a wide range of bonding environments (average error of 2.6%). An extension based on truncated CI calculations in which d-type and hydrogen p-type functions are eliminated from the virtual space combined with estimates of dynamical correlation contributions using atomic correlation factors is discussed and applied to the dissociation of several molecules.
FURTHER RESULTS ON MEASURING THE WELL-BEING OF THE POOR USING INCOME AND CONSUMPTION

In the U.S., analyses of poverty rates and the effects of anti-poverty programs rely almost exclusively on income data. In earlier work (Meyer and Sullivan, 2003) we emphasized that conceptual arguments generally favor using consumption data to measure the well-being of the poor, and, on balance, data quality issues favor consumption in the case of single mothers. Our earlier work did not show that income and consumption differ in practice. Here we further examine data quality issues and show that important conclusions about recent trends depend on whether one uses consumption or income. Changes in the distribution of resources for single mothers differ sharply in recent years depending on whether measured by income or consumption. Measures of overall and sub-group poverty also sharply differ. In addition to examining broader populations and a longer time period, we also consider new dimensions of data quality such as survey and item nonresponse, imputation, and precision. Finally, we demonstrate the flaws in a recent paper that compares income and consumption data.
The role of the chief legal officer in corporate governance

Abstract The CLO shapes and enforces corporate governance, but is faced with a dual-role paradox that requires her to act as both monitor of corporate governance and executive of the firm. We study the role of the CLO under environments that are most likely to impact governance and pressure the firm to either emphasize or marginalize the CLO's role as monitor or facilitator. Using the financial shock of a securities class action lawsuit on large corporations, we measure changes in CLO value through the metrics of total and relative compensation of the CLO and other C-suite members. After controlling for relevant variables such as growth and total assets, we find that when firms have more insiders on their board of directors, the CLO's compensation declines when the preceding year's Tobin's Q is high. CLO compensation increases under conditions of high opacity, but that compensation partially erodes in high Tobin's Q environments. We also find that a lawsuit increases CFO and CEO turnover but not the CLO's. Our results have implications for corporate governance, the dual and potentially conflicting role of CLO as gatekeeper and monitor, executive compensation, and agency costs.
The Survival Rate of Defined‐Benefit Plans, 1987‐1995

We look at the survival rate of defined-benefit pension plans with at least 500 participants over the period 1987–1995. We find that termination in favor of defined-contribution plans is a rare event and that the vast majority of these plans survive, albeit often under a different plan sponsor or in a new merged plan. Indeed, the frequency of mergers is an important feature in the pension market and partially explains the growing number of large defined-benefit plans.
The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior

This article establishes that a low‐dimensional vector of cognitive and noncognitive skills explains a variety of labor market and behavioral outcomes. Our analysis addresses the problems of measurement error, imperfect proxies, and reverse causality that plague conventional studies. Noncognitive skills strongly influence schooling decisions and also affect wages, given schooling decisions. Schooling, employment, work experience, and choice of occupation are affected by latent noncognitive and cognitive skills. We show that the same low‐dimensional vector of abilities that explains schooling choices, wages, employment, work experience, and choice of occupation explains a wide variety of risky behaviors.
The rise of trust decanting in the United States

In a trust decanting, a trustee who under the terms of a trust (the first trust) has a discretionary power over distribution uses that power to distribute the trust property to a new trust (the second trust) with updated provisions, leaving behind the sediment of the first trust’s stale provisions. This article canvasses the rise of trust decanting in American trust practice, taking notice of its common law origins, its contrast with traditional American doctrine on trust modification and termination, the proliferation of state trust decanting statutes, and several areas of doctrinal divergence across the states.
Nudging with care: the risks and benefits of social information

Nudges are popular types of interventions. Recent years have seen the rise of ‘norm-nudges’—nudges whose mechanism of action relies on social norms, eliciting or changing social expectations. Norm-nudges can be powerful interventions, but they can easily fail to be effective and can even backfire unless they are designed with care. We highlight important considerations when designing norm-nudges and discuss a general model of social behavior based on social expectations and conditional preferences. We present the results of several experiments wherein norm-nudging can backfire, and ways to avoid those negative outcomes.