cssi/SciSciGPT-SciSciNet huggingface dataset:
Endoscopic navigation in the absence of CT imaging

Clinical examinations that involve endoscopic exploration of the nasal cavity and sinuses often do not have a reference image to provide structural context to the clinician. In this paper, we present a system for navigation during clinical endoscopic exploration in the absence of computed tomography (CT) scans by making use of shape statistics from past CT scans. Using a deformable registration algorithm along with dense reconstructions from video, we show that we are able to achieve submillimeter registrations in in-vivo clinical data and are able to assign confidence to these registrations using confidence criteria established using simulated data.
Entropy accumulation near quantum critical points: effects beyond hyperscaling

Entropy accumulation near a quantum critical point was expected based on general scaling arguments, and has recently been explicitly observed. We explore this issue further in two canonical models for quantum criticality, with particular attention paid to the potential effects beyond hyperscaling. In the case of a one-dimensional transverse field Ising model, we derive the specific scaling form of the free energy. It follows from this scaling form that the singular temperature dependence at the critical field has a vanishing prefactor but the singular field dependence at zero temperature is realized. For the spin-density-wave model above its upper critical dimension, we show that the dangerously irrelevant quartic coupling comes into the free energy in a delicate way but in the end yields only subleading contributions beyond hyperscaling. We conclude that entropy accumulation near quantum critical point is a robust property of both models.
O2- and CO-rich Atmospheres for Potentially Habitable Environments on TRAPPIST-1 Planets

Small exoplanets of nearby M-dwarf stars present the possibility of finding and characterizing habitable worlds within the next decade. TRAPPIST-1, an ultracool M-dwarf star, was recently found to have seven Earth-sized planets of predominantly rocky composition. The planets e, f, and g could have a liquid water ocean on their surface given appropriate atmospheres of N₂ and CO₂. In particular, climate models have shown that the planets e and f can sustain a global liquid water ocean, for ≥0.2 bar CO₂ plus 1 bar N₂, or ≥2 bar CO₂, respectively. These atmospheres are irradiated by ultraviolet emission from the star's moderately active chromosphere, and the consequence of this irradiation is unknown. Here we show that chemical reactions driven by the irradiation produce and maintain more than 0.2 bar O₂ and 0.05 bar CO if the CO₂ is ≥0.1 bar. The abundance of O₂ and CO can rise to more than 1 bar under certain boundary conditions. Because of this O₂–CO runaway, habitable environments on the TRAPPIST-1 planets entail an O₂- and CO-rich atmosphere with coexisting O₃. The only process that would prevent runaway is direct recombination of O₂ and CO in the ocean, a reaction that is facilitated biologically. Our results indicate that O₂, O₃, and CO should be considered together with CO₂ as the primary molecules in the search for atmospheric signatures from temperate and rocky planets of TRAPPIST-1 and other M-dwarf stars.
Late formation of silicon carbide in type II supernovae

We have found that individual presolar silicon carbide (SiC) dust grains from supernovae show a positive correlation between 49Ti and 28Si excesses, which is attributed to the radioactive decay of the short-lived (t½ = 330 days) 49V to 49Ti in the inner highly 28Si-rich Si/S zone. The 49V-49Ti chronometer shows that these supernova SiC dust grains formed at least 2 years after their parent stars exploded. This result supports recent dust condensation calculations that predict a delayed formation of carbonaceous and SiC grains in supernovae. The astronomical observation of continuous buildup of dust in supernovae over several years can, therefore, be interpreted as a growing addition of C-rich dust to the dust reservoir in supernovae.
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers

To build an interpretable neural text classifier, most of the prior work has focused on designing inherently interpretable models or finding faithful explanations. A new line of work on improving model interpretability has just started, and many existing methods require either prior information or human annotations as additional inputs in training. To address this limitation, we propose the variational word mask (VMASK) method to automatically learn task-specific important words and reduce irrelevant information on classification, which ultimately improves the interpretability of model predictions. The proposed method is evaluated with three neural text classifiers (CNN, LSTM, and BERT) on seven benchmark text classification datasets. Experiments show the effectiveness of VMASK in improving both model prediction accuracy and interpretability.
FAST MODES AND DUSTY HORSESHOES IN TRANSITIONAL DISKS

The brightest transitional protoplanetary disks are often azimuthally asymmetric: their millimeter-wave thermal emission peaks strongly on one side. Dust overdensities can exceed ∼100:1, while gas densities vary by factors less than a few. We propose that these remarkable ALMA observations—which may bear on how planetesimals form—reflect a gravitational global mode in the gas disk. The mode is (1) fast—its pattern speed equals the disk's mean Keplerian frequency; (2) of azimuthal wavenumber m = 1, displacing the host star from the barycenter; and (3) Toomre-stable. We solve for gas streamlines including the indirect stellar potential in the frame rotating with the pattern speed, under the drastic simplification that gas does not feel its own gravity. Near corotation, the gas disk takes the form of a horseshoe-shaped annulus. Dust particles with aerodynamic stopping times much shorter or much longer than the orbital period are dragged by gas toward the horseshoe center. For intermediate stopping times, dust converges toward a ∼45° wide arc on the corotation circle. Particles that do not reach their final accumulation points within disk lifetimes, either because of gas turbulence or long particle drift times, conform to horseshoe-shaped gas streamlines. Our mode is not self-consistent because we neglect gasmore » self-gravity; still, we expect that trends between accumulation location and particle size, similar to those we have found, are generically predicted by fast modes and are potentially observable. Unlike vortices, global modes are not restricted in radial width to the pressure scale height; their large radial and azimuthal extents may better match observations.« less
Gravity Dual for a Model of Perception

Abstract One of the salient features of human perception is its invariance under dilatation in addition to the Euclidean group, but its non-invariance under special conformal transformation. We investigate a holographic approach to the information processing in image discrimination with this feature. We claim that a strongly coupled analogue of the statistical model proposed by Bialek and Zee can be holographically realized in scale invariant but non-conformal Euclidean geometries. We identify the Bayesian probability distribution of our generalized Bialek–Zee model with the GKPW partition function of the dual gravitational system. We provide a concrete example of the geometric configuration based on a vector condensation model coupled with the Euclidean Einstein–Hilbert action. From the proposed geometry, we study sample correlation functions to compute the Bayesian probability distribution.
Bootstrap confidence intervals for isotonic estimators in a stereological problem

Let $\mathbf{X}=(X_{1},X_{2},X_{3})$ be a spherically symmetric random vector of which only $(X_{1},X_{2})$ can be observed. We focus attention on estimating $F$, the distribution function of the squared radius $Z:=X_{1}^{2}+X_{2}^{2}+X_{3}^{2}$, from a random sample of $(X_{1},X_{2})$. Such a problem arises in astronomy where $(X_{1},X_{2},X_{3})$ denotes the three dimensional position of a star in a galaxy but we can only observe the projected stellar positions $(X_{1},X_{2})$. We consider isotonic estimators of $F$ and derive their limit distributions. The results are nonstandard with a rate of convergence $\sqrt{n/{\log n}}$. The isotonized estimators of $F$ have exactly half the limiting variance when compared to naive estimators, which do not incorporate the shape constraint. We consider the problem of constructing point-wise confidence intervals for $F$, state sufficient conditions for the consistency of a bootstrap procedure, and show that the conditions are met by the conventional bootstrap method (generating samples from the empirical distribution function).
New Atomic Decompositions of Bergman Spaces on Bounded Symmetric Domains

We provide a large family of atoms for Bergman spaces on irreducible bounded symmetric domains. The atomic decompositions are derived using the holomorphic discrete series representations for the domain, and the approach is inspired by recent advances in wavelet and coorbit theory. Our results vastly generalize previous work by Coifman and Rochberg. Their atoms correspond to translates of a constant function at a discrete subset of the automorphism group of the domain. In this paper we show that atoms can be obtained as translates of any holomorphic function with rapidly decreasing coefficients (including polynomials). This approach also settles the relation between atomic decompositions for the bounded and unbounded realizations of the domain.
Gravitational collapse of thick domain walls

Numerical simulations are performed of the gravitational collapse of a scalar field with a λ4 potential. Comparisons for the wall motion and stress-energy are made with the thin shell approximation. It is found that the thin shell approximation generally works well, especially for the motion of the wall. However, the approximation is not as good at late times as it is at early times.
LIFTING THE DUSTY VEIL WITH NEAR- AND MID-INFRARED PHOTOMETRY. I. DESCRIPTION AND APPLICATIONS OF THE RAYLEIGH-JEANS COLOR EXCESS METHOD

The Milky Way (MW) remains a primary laboratory for understanding the structure and evolution of spiral galaxies, but typically we are denied clear views of MW stellar populations at low Galactic latitudes because of extinction by interstellar dust. However, the combination of Two Micron All-Sky Survey (2MASS) near-infrared (NIR) and Spitzer-IRAC mid-infrared (MIR) photometry enables a powerful method for determining the line-of-sight reddening to any star: the sampled wavelengths lie in the Rayleigh-Jeans part of the spectral energy distribution of most stars, where, to first order, all stars have essentially the same intrinsic color. Thus, changes in stellar NIR-MIR colors due to interstellar reddening are readily apparent, and (under an assumed extinction law) the observed colors and magnitudes of stars can be easily and accurately restored to their intrinsic values, greatly increasing their usefulness for Galactic structure studies. In this paper, we explore this 'Rayleigh-Jeans Color Excess' (RJCE) method and demonstrate that use of even a simple variant of the RJCE method based on a single reference color, (H -[4.5{mu}]), can rather accurately remove dust effects from previously uninterpretable 2MASS color-magnitude diagrams of stars in fields along the heavily reddened Galactic midplane, with results far superior to those derived frommore » application of other dereddening methods. We also show that 'total' Galactic midplane extinction looks rather different from that predicted using 100{mu} emission maps from the IRAS/ISSA and COBE/DIRBE instruments as presented by Schlegel et al. Instead, the Galactic midplane extinction strongly resembles the distribution of {sup 13}CO (J = 1{yields}0) emission. Future papers will focus on refining the RJCE method and applying the technique to understand better not only dust and its distribution but also the distribution of stars intermixed with the dust in the low-latitude Galaxy.« less
Further Evidence Suggestive of a Solar Influence on Nuclear Decay Rates

Recent analyses of nuclear decay data show evidence of variations suggestive of a solar influence. Analyses of datasets acquired at the Brookhaven National Laboratory (BNL) and at the Physikalisch-Technische Bundesanstalt (PTB) both show evidence of an annual periodicity and of periodicities with sidereal frequencies in the neighborhood of 12.25 year−1 (at a significance level that we have estimated to be 10−17). It is notable that this implied rotation rate is lower than that attributed to the solar radiative zone, suggestive of a slowly rotating solar core. This leads us to hypothesize that there may be an “inner tachocline” separating the core from the radiative zone, analogous to the “outer tachocline” that separates the radiative zone from the convection zone. The Rieger periodicity (which has a period of about 154 days, corresponding to a frequency of 2.37 year−1) may be attributed to an r-mode oscillation with spherical-harmonic indices l=3,m=1, located in the outer tachocline. This suggests that we may test the hypothesis of a solar influence on nuclear decay rates by searching BNL and PTB data for evidence of a “Rieger-like” r-mode oscillation, with l=3,m=1, in the inner tachocline. The appropriate search band for such an oscillation is estimated to be 2.00 – 2.28 year−1. We find, in both datasets, strong evidence of a periodicity at 2.11 year−1. We estimate that the probability of obtaining these results by chance is 10−12.
X-ray and Radio Observations of the Massive Star Forming Region IRAS 20126+4104

We present results from Chandra ACIS-I and Karl G. Jansky Very Large Array 6 cm continuum observations of the IRAS 20126+4104 massive star-forming region. We detect 150 X-ray sources within the 17' × 17' ACIS-I field, and a total of 13 radio sources within the 92 primary beam at 4.9 GHz. Among these observtions are the first 6 cm detections of the central sources reported by Hofner et al., namely, I20N1, I20S, and I20var. A new variable radio source is also reported. Searching the 2MASS archive, we identified 88 near-infrared (NIR) counterparts to the X-ray sources. Only four of the X-ray sources had 6 cm counterparts. Based on an NIR color–color analysis and on the Besancon simulation of Galactic stellar populations, we estimate that approximately 80 X-ray sources are associated with this massive star-forming region. We detect an increasing surface density of X-ray sources toward the massive protostar and infer the presence of a cluster of at least 43 young stellar objects within a distance of 1.2 pc from the massive protostar.
Discovery of a Magnetic DZ White Dwarf with Zeeman-Split Lines of Heavy Elements

A spectroscopic survey of unstudied Luyten half-second proper-motion stars has resulted in the discovery of an unusual new magnetic white dwarf. LHS 2534 proves to be the first magnetic DZ, showing Zeeman-split Na I and Mg I components, as well as Ca I and Ca II lines for which Zeeman components are blended. The Na I splittings result in a mean surface field strength estimate of 1.92 MG. Apart from the magnetic field, LHS 2534 is one of the most heavily blanketed and coolest DZ white dwarfs at Teff ~ 6000 K.
Note on sums involving the Euler function

In this note, we provide refined estimates of the following sums involving the Euler totient function: $$\sum_{n\le x} \phi\left(\left[\frac{x}{n}\right]\right) \qquad \text{and} \qquad \sum_{n\le x} \frac{\phi([x/n])}{[x/n]}$$ where $[x]$ denotes the integral part of real $x$. The above summations were recently considered by Bordelles et al. and Wu.
Disentangling Planets and Stellar Activity for Gliese 667C

Gliese 667C is an M1.5V star with a multi-planet system, including planet candidates in the habitable zone. The exact number of planets in the system is unclear, because the existing radial velocity (RV) measurements are known to contain contributions from stellar magnetic activity. Following our analysis of Gliese 581, we have analyzed the effect of stellar activity on the HARPS/HARPS-TERRA RVs of GJ 667C, finding a significant RV-activity correlation when using the width (FWHM) of the HARPS cross-correlation function to trace the magnetic activity. When we correct for this correlation, we confirm the detections of the previously observed planets b and c in the system, while simultaneously ascribing the RV signal near 90 days ("planet d") to an artifact of the stellar rotation. We are unable to confirm the existence of the additional RV periodicities described in Anglada-Escude et al. in our activity-corrected data.
Contact structures, excisions and sutured monopole Floer homology

In this paper, we explore the interplay between contact structures and sutured monopole Floer homology. First, we study the behavior of contact elements, which were defined by Baldwin and Sivek, under the operation of performing Floer excisions, which was introduced to the context of sutured monopole Floer homology by Kronheimer and Mrowka. We then compute the sutured monopole Floer homology of some special balanced sutured manifolds, using tools closely related to contact geometry. For application, we obtain an exact triangle for the oriented skein relation in monopole theory and derive a connected sum formula for sutured monopole Floer homology.
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships

We investigate the methods of microstructure representation for the purpose of predicting processing condition from microstructure image data. A binary alloy (uranium–molybdenum) that is currently under development as a nuclear fuel was studied for the purpose of developing an improved machine learning approach to image recognition, characterization, and building predictive capabilities linking microstructure to processing conditions. Here, we test different microstructure representations and evaluate model performance based on the F1 score. A F1 score of 95.1% was achieved for distinguishing between micrographs corresponding to ten different thermo-mechanical material processing conditions. We find that our newly developed microstructure representation describes image data well, and the traditional approach of utilizing area fractions of different phases is insufficient for distinguishing between multiple classes using a relatively small, imbalanced original dataset of 272 images. To explore the applicability of generative methods for supplementing such limited datasets, generative adversarial networks were trained to generate artificial microstructure images. Two different generative networks were trained and tested to assess performance. Challenges and best practices associated with applying machine learning to limited microstructure image datasets are also discussed. Our work has implications for quantitative microstructure analysis and development of microstructure–processing relationships in limited datasets typical of metallurgical process design studies.
Controlling transistor threshold voltages using molecular dipoles

We develop a theoretical model for how organic molecules can control the electronic and transport properties of an underlying transistor channel to whose surface they are chemically bonded. The influence arises from a combination of long-ranged dipolar electrostatics due to the molecular head groups as well as short-ranged charge transfer and interfacial dipole driven by equilibrium band alignment between the molecular backbone and the reconstructed semiconductor surface atoms.
BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits

Clustering is a ubiquitous task in data science. Compared to the commonly used $k$-means clustering, $k$-medoids clustering requires the cluster centers to be actual data points and support arbitrary distance metrics, which permits greater interpretability and the clustering of structured objects. Current state-of-the-art $k$-medoids clustering algorithms, such as Partitioning Around Medoids (PAM), are iterative and are quadratic in the dataset size $n$ for each iteration, being prohibitively expensive for large datasets. We propose BanditPAM, a randomized algorithm inspired by techniques from multi-armed bandits, that reduces the complexity of each PAM iteration from $O(n^2)$ to $O(n \log n)$ and returns the same results with high probability, under assumptions on the data that often hold in practice. As such, BanditPAM matches state-of-the-art clustering loss while reaching solutions much faster. We empirically validate our results on several large real-world datasets, including a coding exercise submissions dataset, the 10x Genomics 68k PBMC single-cell RNA sequencing dataset, and the MNIST handwritten digits dataset. In these experiments, we observe that BanditPAM returns the same results as state-of-the-art PAM-like algorithms up to 4x faster while performing up to 200x fewer distance computations. The improvements demonstrated by BanditPAM enable $k$-medoids clustering on a wide range of applications, including identifying cell types in large-scale single-cell data and providing scalable feedback for students learning computer science online. We also release highly optimized Python and C++ implementations of our algorithm.
The Use of Covariates and Random Effects in Evaluating Predictive Biomarkers Under a Potential Outcome Framework.

Predictive or treatment selection biomarkers are usually evaluated in a subgroup or regression analysis with focus on the treatment-by-marker interaction. Under a potential outcome framework (Huang, Gilbert and Janes [Biometrics 68 (2012) 687-696]), a predictive biomarker is considered a predictor for a desirable treatment benefit (defined by comparing potential outcomes for different treatments) and evaluated using familiar concepts in prediction and classification. However, the desired treatment benefit is un-observable because each patient can receive only one treatment in a typical study. Huang et al. overcome this problem by assuming monotonicity of potential outcomes, with one treatment dominating the other in all patients. Motivated by an HIV example that appears to violate the monotonicity assumption, we propose a different approach based on covariates and random effects for evaluating predictive biomarkers under the potential outcome framework. Under the proposed approach, the parameters of interest can be identified by assuming conditional independence of potential outcomes given observed covariates, and a sensitivity analysis can be performed by incorporating an unobserved random effect that accounts for any residual dependence. Application of this approach to the motivating example shows that baseline viral load and CD4 cell count are both useful as predictive biomarkers for choosing antiretroviral drugs for treatment-naive patients.
Orbifold homeomorphism finiteness based on geometric constraints

We show that any collection of n-dimensional orbifolds with sectional curvature and volume uniformly bounded below, diameter bounded above, and with only isolated singular points contains orbifolds of only finitely many orbifold homeomorphism types. This is a generalization to the orbifold category of a similar result for manifolds proven by Grove, Petersen, and Wu. It follows that any Laplace isospectral collection of orbifolds with sectional curvature uniformly bounded below and having only isolated singular points also contains only finitely many orbifold homeomorphism types. The main steps of the argument are to show that any sequence from the collection has subsequence that converges to an orbifold, and then to show that the homeomorphism between the underlying spaces of the limit orbifold and an orbifold from the subsequence that is guaranteed by Perelman’s stability theorem must preserve orbifold structure.
THE DISCOVERY OF A MASSIVE CLUSTER OF RED SUPERGIANTS WITH GLIMPSE

We report the discovery of a previously unknown massive Galactic star cluster at l = 29.{sup 0}22, b = -0.{sup 0}20. Identified visually in mid-IR images from the Spitzer GLIMPSE survey, the cluster contains at least eight late-type supergiants, based on follow-up near-IR spectroscopy, and an additional 3-6 candidate supergiant members having IR photometry consistent with a similar distance and reddening. The cluster lies at a local minimum in the {sup 13}CO column density and 8 {mu}m emission. We interpret this feature as a hole carved by the energetic winds of the evolving massive stars. The {sup 13}CO hole seen in molecular maps at V {sub LSR} {approx} 95 km s{sup -1} corresponds to near/far kinematic distances of 6.1/8.7 {+-} 1 kpc. We calculate a mean spectrophotometric distance of 7.0{sup +3.7} {sub -2.4} kpc, broadly consistent with the kinematic distances inferred. This location places it near the northern end of the Galactic bar. For the mean extinction of A{sub V} = 12.6 {+-} 0.5 mag (A{sub K} = 1.5 {+-} 0.1 mag), the color-magnitude diagram of probable cluster members is well fit by isochrones in the age range 18-24 Myr. The estimated cluster mass is {approx}20,000 M {sub sun}. Withmore » the most massive original cluster stars likely deceased, no strong radio emission is detected in this vicinity. As such, this red supergiant (RSG) cluster is representative of adolescent massive Galactic clusters that lie hidden behind many magnitudes of dust obscuration. This cluster joins two similar RSG clusters as residents of the volatile region where the end of our Galaxy's bar joins the base of the Scutum-Crux spiral arm, suggesting a recent episode of widespread massive star formation there.« less
Control of fixed points and existence and uniqueness of centric linking systems

A. Chermak has recently proved that to each saturated fusion system over a finite p-group, there is a unique associated centric linking system. B. Oliver extended Chermak’s proof by showing that all the higher cohomological obstruction groups relevant to unique existence of centric linking systems vanish. Both proofs indirectly assume the classification of finite simple groups. We show how to remove this assumption, thereby giving a classification-free proof of the Martino–Priddy conjecture concerning the p-completed classifying spaces of finite groups. Our main tool is a 1971 result of the first author on control of fixed points by p-local subgroups. This result is directly applicable for odd primes, and we show how a slight variation of it allows applications for $$p=2$$ in the presence of offenders.
Special embeddings of weighted Sobolev spaces with nontrivial power weights

In prior work, the author has characterized the real numbers $$a,b,c$$ and $$1\le p,q,r<\infty $$ such that the weighted Sobolev space $$ W_{\{a,b\}}^{1,(q,p)}(\mathbb R ^{N}\backslash \{0\}):=\{u\in L_{loc}^{1}(\mathbb R ^{N}\backslash \{0\}):|x|^{\frac{a}{q}}u\in L^{q}(\mathbb R ^{N}),|x|^{\frac{b}{p}}\nabla u\in (L^{p}(\mathbb R ^{N}))^{N}\}$$ is continuously embedded into $$L^{r}(\mathbb R ^{N};|x|^{c}dx):=\{u \text{ measurable} :|x|^{\frac{c}{r}}u\in L^{r}(\mathbb R ^{N})\}.$$ This paper discusses the embedding question for $$W_{\{a,b\}}^{1,(\infty ,p)}(\mathbb R ^{N}\backslash \{0\}):=\{u\in L_{loc}^{1}(\mathbb R ^{N}\backslash \{0\}):|x|^{a}u\in L^{\infty }(\mathbb R ^{N}),|x|^{\frac{b}{p}}\nabla u\in (L^{p}(\mathbb R ^{N}))^{N}\},$$ which is not the space obtained by the formal substitution $$q=\infty $$ in the previous definition of $$W_{\{a,b\}}^{1,(q,p)}(\mathbb R ^{N}\backslash \{0\}),$$ unless $$a=0.$$ The corresponding embedding theorem identifies all the real numbers $$a,b,c$$ and $$1\le p,r<\infty $$ such that $$W_{\{a,b\}}^{1,(\infty ,p)}(\mathbb R ^{N}\backslash \{0\})$$ is continuously embedded in $$L^{r}(\mathbb R ^{N};|x|^{c}dx).$$ A notable feature is that such embeddings exist only when $$ a\ne 0$$ and, in particular, have no analog in the unweighted setting. It is also shown that the embeddings are always accounted for by multiplicative rather than just additive norm inequalities. These inequalities are natural extensions of the Caffarelli–Kohn–Nirenberg inequalities which, in their known form, are restricted to functions of $$ C_{0}^{\infty }(\mathbb R ^{N})$$ and do not incorporate supremum norms.
The Structural Evolution of Forming and Early Stage Star Clusters

We study the degree of angular substructure in the stellar position distribution of young members of Galactic star-forming regions, looking for correlations with distance from cluster center, surface number density of stars, and local dynamical age. To this end we adopt the catalog of members in 18 young (~1-3 Myr) clusters from the Massive Young Star-Forming Complex Study in Infrared and X-ray Survey and the statistical analysis of the angular dispersion parameter, δADP, N. We find statistically significant correlation between δADP, N and physical projected distance from the center of the clusters, with the centers appearing smoother than the outskirts, consistent with more rapid dynamical processing on local dynamical, free-fall or orbital timescales. Similarly, smoother distributions are seen in regions of higher surface density, or older dynamical ages. These results indicate that dynamical processing that erases substructure is already well-advanced in young, sometimes still-forming, clusters. Such observations of the dissipation of substructure have the potential to constrain theoretical models of the dynamical evolution of young and forming clusters.
A Search for Optical Pulsations from Two Young Southern Pulsars

We report on high-speed optical photometry of the radio positions of two young rotation-powered pulsars. No pulsations were detected from the optical counterpart proposed by Caraveo et al. for PSR B1509-58, with a 2 σ upper limit on the pulsed fraction of less than 12%, significantly lower than that measured in the five known optical pulsars. Given its low pulsed fraction, high optical luminosity, and significant (8%) chance coincidence probability, we suggest that this candidate is not associated with the pulsar. We also find that the still unidentified optical counterpart of PSR B1706-44 has R18 and lies within 3'' of an R=16.6 star.
Low-intensity vibration restores nuclear YAP levels and acute YAP nuclear shuttling in mesenchymal stem cells subjected to simulated microgravity

Reducing the musculoskeletal deterioration that astronauts experience in microgravity requires countermeasures that can improve the effectiveness of otherwise rigorous and time-expensive exercise regimens in space. The ability of low-intensity vibrations (LIV) to activate force-responsive signaling pathways in cells suggests LIV as a potential countermeasure to improve cell responsiveness to subsequent mechanical challenge. Mechanoresponse of mesenchymal stem cells (MSC), which maintain bone-making osteoblasts, is in part controlled by the “mechanotransducer” protein YAP (Yes-associated protein), which is shuttled into the nucleus in response to cyto-mechanical forces. Here, using YAP nuclear shuttling as a measurement outcome, we tested the effect of 72 h of clinostat-induced simulated microgravity (SMG) and daily LIV application (LIVDT) on the YAP nuclear entry driven by either acute LIV (LIVAT) or Lysophosphohaditic acid (LPA), applied after the 72 h period. We hypothesized that SMG-induced impairment of acute YAP nuclear entry would be alleviated by the daily application of LIVDT. Results showed that while both acute LIVAT and LPA treatments increased nuclear YAP entry by 50 and 87% over the basal levels in SMG-treated MSCs, nuclear YAP levels of all SMG groups were significantly lower than non-SMG controls. LIVDT, applied in parallel to SMG, restored the SMG-driven decrease in basal nuclear YAP to control levels as well as increased the LPA-induced but not LIVAT-induced YAP nuclear entry over SMG only, counterparts. These cell-level observations suggest that daily LIV treatments are a feasible countermeasure for restoring basal nuclear YAP levels and increasing the YAP nuclear shuttling in MSCs under SMG.
Prenatal exposure to per- and polyfluoroalkyl substances in association with autism spectrum disorder in the MARBLES study.

Abstract Background Prenatal exposure to per- and polyfluoroalkyl substances (PFAS) has shown potential to adversely affect child brain development, but epidemiologic evidence remains inconsistent. We examined whether prenatal exposure to PFAS was associated with increased risk of autism spectrum disorder (ASD). Methods Participants were 173 mother–child pairs from MARBLES ( M arkers of A utism R isk in B abies – L earning E arly S igns), a high-risk ASD cohort. At 3 years old, children were clinically confirmed for ASD and classified into ASD (n = 57) and typical development (TD, n = 116). We quantified nine PFAS in maternal serum collected during pregnancy. We examined associations of ASD with individual PFAS as well as the combined effect of PFAS on ASD using scores of the first principal component (PC-1) accounting for the largest variance. Results Prenatal perfluorooctanoate (PFOA) and perfluorononanoate (PFNA) showed positive associations (per 2-fold relative increase in concentration: relative risk (RR) = 1.20, 95% CI: 0.90, 1.61 [PFOA]; RR = 1.24, 95% CI: 0.91, 1.69 [PFNA]), while perfluorohexane sulfonate (PFHxS) showed a negative association (RR = 0.88, 95% CI: 0.77, 1.01) with ASD risk. When examining associations of ASD with untransformed PFAS concentrations, PFOA, PFNA, and PC-1 were associated with increased ASD risk (per nanogram per milliliter increase: RR = 1.31, 95% CI: 1.04, 1.65; RR = 1.79, 95% CI: 1.13, 2.85; RR = 1.10, 95% CI: 0.97, 1.25, respectively), while the RR of PFHxS moved toward the null. Conclusions From this high-risk ASD cohort, we observed increased risk of ASD in children exposed to PFOA and PFNA. Further studies should be conducted in the general population because this population may have a larger fraction of cases resulting from genetic sources.
Bounds for discrete multilinear spherical maximal functions

We define a discrete version of the bilinear spherical maximal function, and show bilinear $$l^{p}(\mathbb {Z}^d)\times l^{q}(\mathbb {Z}^d) \rightarrow l^{r}(\mathbb {Z}^d)$$ bounds for $$d \ge 3$$ , $$\frac{1}{p} + \frac{1}{q} \ge \frac{1}{r}$$ , $$r>\frac{d}{d-2}$$ and $$p,q\ge 1$$ . Due to interpolation, the key estimate is an $$l^{p}(\mathbb {Z}^d)\times l^{\infty }(\mathbb {Z}^d) \rightarrow l^{p}(\mathbb {Z}^d)$$ bound, which holds when $$d \ge 3$$ , $$p>\frac{d}{d-2}$$ . A key feature of our argument is the use of the circle method which allows us to decouple the dimension from the number of functions compared to the work of Cook.
Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning. Specifically, there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization, power efficiency and computation speed. Diffractive deep neural networks (D2NNs) form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers. D2NNs have demonstrated success in various tasks, including object classification, the spectral encoding of information, optical pulse shaping and imaging. Here, we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning. After independently training 1252 D2NNs that were diversely engineered with a variety of passive input filters, we applied a pruning algorithm to select an optimized ensemble of D2NNs that collectively improved the image classification accuracy. Through this pruning, we numerically demonstrated that ensembles of N = 14 and N = 30 D2NNs achieve blind testing accuracies of 61.14 ± 0.23% and 62.13 ± 0.05%, respectively, on the classification of CIFAR-10 test images, providing an inference improvement of >16% compared to the average performance of the individual D2NNs within each ensemble. These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems. Scientists in USA have demonstrated significant improvements in the performance of diffractive optical networks, marking a major step forward for their use in optics-based computation and machine learning. There is renewed interest in optical computing hardware due to its potential advantages, including parallelization, power efficiency, and computation speed. Diffractive optical networks utilize deep learning-based design of successive diffractive layers to all-optically process information as the light is transmitted from the input to the output plane. Led by Aydogan Ozcan, a team of researchers from University of California, Los Angeles has significantly improved the statistical inference performance of diffractive optical networks using feature engineering and ensemble learning. Using a pruning algorithm, they searched through 1,252 unique diffractive networks to design ensembles of desired size that substantially improve the overall system’s all-optical image classification accuracy.
Demand shocks and economic fluctuations

Abstract This paper studies conditions under which demand-side shocks can generate realistic business cycles in RBC models. Although highly persistent demand shocks are necessary for generating procyclical investment, variable capacity utilization and habit formation can reduce the required degree of persistence.
The Evolving Domestic and International Law Against Foreign Corruption: Some New and Old Dilemmas Facing the International Lawyer

For over two decades, the Foreign Corrupt Practices Act ("FCPA") and, more recently, the Organization for Economic Cooperation and Development Convention on Combating Bribery of Foreign Public Officials in International Business Transactions ("OECD Convention") have delineated to U.S. lawyers and their clients which international transactions are proscribed and punished as corrupt. However, like any other statute, the FCPA and the OECD Convention are unable to cover all the permutations of activity that would seemingly constitute transnational corruption. This Article explores what is prohibited and permissible under the FCPA and the OECD Convention, highlighting the tension between operating outside the coverage of these legal precepts while still complying with the rules of professional conduct. It concludes by demonstrating, by means of various scenarios, that there is no substitute for a lawyer's reliance on her professional and ethical judgment.
Reply to “The Effects of ‘Early Offers’ in Medical Malpractice Cases: Evidence from Texas”

This article is a reply to the critique by Black, Hyman, and Silver (BHS) of our 2007 Journal of Legal Studies article, “An Empirical Assessment of Early Offer Reform for Medical Malpractice.” The early offer reform gives insurers the option of making an early offer that will expedite payment of claimants' economic losses and reasonable attorney fees. Using data on closed medical malpractice claims from the Texas Department of Insurance (TDI), our 2007 article estimates the financial impact of this proposal by comparing the expected payments to claimants under the early offer reform to the payments tinder current tort rules. A central component of our calculation of expected payments is unique information on insurers' reserves associated with the claim; actual payments are reported in the TDI data for all litigated and settled cases involving payments of at least $10,000. The BHS article misrepresents fundamental aspects of our empirical analysis, including the following. BHS set out to correct our purported “false assumption” that all claims have a 1.0 probability of success, which is a problem that arises because BHS omit the probability of claimant success from the formula that is presented in our paper. BHS's error is compounded as their discussion of our paper fails to recognize that our use of reserve amounts in the analysis incorporates the insurers’ estimates of the likelihood of claimant success, Indeed, they neither acknowledge our use of the insurer reserve data, nor do they use the insurer reserve information in their paper. BHS claim incorrectly that our analysis does not discount deferred payments whereas in fact it does. Our early offer analysis uses data for both litigated and settled claims, avoiding the selection bias and measurement error problems associated with BHS's extrapolation from the 2 percent of paid claims that are litigated to the universe of all settled and litigated claims. The BHS article also reflects a misunderstanding of the operation of the early offer reform.
Efficient monte carlo CVA estimation

This paper presents an overview of the efficient Monte Carlo counterparty credit risk (CCR) estimation framework recently developed by Ghamami and Zhang (2014). We focus on the estimation of credit value adjustment (CVA), one of the most widely used and regulatory-driven counterparty credit risk measures. Our proposed efficient CVA estimators are developed based on novel applications of well-known mean square error (MSE) reduction techniques in the simulation literature. Our numerical examples illustrate that the efficient estimators outperform the existing crude estimators of CVA substantially in terms of MSE.
Informed consent and the elusive dichotomy between standard and experimental therapy.

A rich academic literature exists about issues of informed consent in medical care, and, to a lesser extent, about a variety of issues posed by human experimentation. Most commentators regard patient autonomy as a desirable— though in practice often unattainable—goal, and near unanimity exists about the necessity for even fuller disclosure before experimenting on subjects. Although this Article intentionally side-steps the broader debate about informed consent, it challenges the conventional wisdom that special disclosure rules should apply in the experimental context. Clinical trials have become big business. Estimates suggest that as many as twenty million Americans have enrolled in formal biomedical studies, though, as a measure of the full scope of medical experimentation on humans, that figure may represent only the proverbial tip of the iceberg. Historically, sponsors of clinical trials recruited subjects informally, counting on word of mouth among physicians and also perhaps posting flyers around college campuses.
Medical-Legal Partnerships: Origins and Ethical Lessons

This paper examines ethical conceptions of physician and attorney obligations during the course of providing treatment and representation to the indigent disabled. Within this context I argue that, despite the limited resources with which the lawyers and doctors who serve this community work, full compliance with ethical obligations is required. It is required not only by the codes governing physician and lawyer behavior but also by the realities of the adversary system: a system that low income disabled persons must access in order to obtain income and health care supports. Further, within the specific context of disability benefits litigation, an historical analysis of social security and private disability decisions and trends reveals that the specific mechanism necessary to effectively advocate on behalf of the disabled is in fact the medical-legal partnership. This is precisely because the medical-legal partnership is what has been used by the Social Security Administration and private insurance companies to defend their internal decisions to deny benefits. While relatively recent discussions about medical-legal partnerships come from advocates for the poor and underserved, in fact medical-legal partnerships originated with government and private sector advocates. As increasingly complex definitions of disability have been created and then codified by regulations on the public sector side and within insurance contracts on the private side, doctors who are used as consultants to review claimants’ evidence have had to be trained regarding the manner in which these definitions are to be applied to the evidence provided. In other words, the consulted have become the consulters and an interdisciplinary medical-legal partnership is effectively created. The result is that a claimant is often facing not only a more powerful, greater-resourced opponent but also one that presents what effectively is an interdisciplinary defense team. In this manner, claims reviewers have successfully tipped the scales too far in their favor – rending the fabric of the already tenuous safety net for the disabled. To re-balance these scales and repair the safety net, I conclude with a call for an acceptance of ethically defined professional roles which encompass the obligation to create more similar partnerships in the future.
Implications of Shareholder Diversification on Corporate Law and Organization: The Case of the Business Judgment Rule

As a practical matter, the presumption against liability established by corporate law's business judgment rule is all but impossible to overcome, at least in cases where directors lack any apparent conflict of interest. Over the years, courts and commentators have offered a variety of explanations for the deference afforded to directors by the business judgment rule, including judges' lack of business expertise, the need to encourage entrepreneurial risk taking by corporate directors, and the availability of other mechanisms to provide directors with incentives to avoid mismanagement. The problem with these explanations is not so much that they lack truth, but rather that they frequently "prove too much" because they apply with equal force to numerous other situations involving non-business professionals (e.g., doctors) in which the rule of ordinary negligence commonly applies. Against this backdrop, this paper develops a different explanation for the business judgment rule, one that focuses on the special preferences of diversified shareholders. As the paper explains, shareholders are unique among legal principals in their ability to diversify away much of the risk (i.e., uncertainty as to future outcomes) associated with acts of their agents, the corporation’s officers and directors. Because shareholders need not take risks that can be eliminated through diversification, shareholders generally prefer their agents to ignore such risks in assessing the adequacy of project returns. By insulating managers from personal liability for corporate losses, the business judgment rule helps achieve this goal
PRODUCT DIFFERENTIATION THROUGH EXCLUSIVITY: Is there a One-Market-Power-Rent Theorem?

In systems industries, combinations of components are consumed together to generate user benefits. Arrangements among component providers sometimes limit consumers’ ability to mix-and-match components, and such exclusive arrangements have been highly controversial. We examine the competitive and welfare effects of exclusive arrangements among system components in a model of relatively differentiated applications that run on relatively undifferentiated platforms. We show that there is no “One-Market-Power-Rent Theorem.” Specifically, exclusive deals with providers of differentiated applications can raise platforms’ margins without reducing applications’ margins, so that overall industry profits rise. Hence, for a given set of components and prices, exclusive arrangements can reduce consumer welfare by limiting consumer choice and raising equilibrium prices. In some cases, however, exclusivity can raise consumer welfare by increasing the equilibrium number of platforms, which leads to lower prices relative to the monopoly outcome that would prevail absent exclusivity.