cssi/SciSciGPT-SciSciNet huggingface dataset:
Were Urban Cowboys Enough to Control Covid-19? Local Shelter-in-Place Orders and Coronavirus Case Growth

One of the most common policy prescriptions to reduce the spread of COVID-19 has been to legally enforce social distancing through shelter-in-place orders (SIPOs). This study examines the role of localized urban SIPO policy in curbing COVID-19 cases. Specifically, we explore (i) the comparative effectiveness of county-level SIPOs in urbanized as compared to non-urbanized areas, (ii) the mechanisms through which SIPO adoption in urban counties yields COVID-related health benefits, and (iii) whether late adoption of a statewide SIPO yields health benefits beyond those achieved from early adopting counties. We exploit the unique laboratory of Texas, a state in which the early adoption of local SIPOs by densely populated counties covered almost two-thirds of the state's population prior to adoption of a statewide SIPO on April 2, 2020. Using an event study framework, we document that countywide SIPO adoption is associated with an 8 percent increase in the percent of residents who remain at home full-time and between a 13 to 19 percent decrease in foot-traffic at venues that may contribute to the spread of COVID-19 such as restaurants, bars, hotels, and entertainment venues. These social distancing effects are largest in urbanized and densely populated counties. Then, we find that in early adopting urban counties, COVID-19 case growth fell by 21 to 26 percentage points two-and-a-half weeks following adoption of a SIPO, a result robust to controls for county-level heterogeneity in COVID-19 outbreak timing, coronavirus testing, the age distribution, and political preferences. We find that approximately 90 percent of the curbed growth in COVID-19 cases in Texas came from the early adoption of SIPOs by urbanized counties, suggesting that the later statewide shelter-in-place mandate yielded relatively few health benefits.
Differentiating Among High-Achieving Learners: A Comparison of Classical Test Theory and Item Response Theory on Above-Level Testing:

This study investigated the application of item response theory (IRT) to expand the range of ability estimates for gifted (hereinafter referred to as high-achieving) students’ performance on an abo...
An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Abstract Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this work, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.
A Local Limit Theorem and Delocalization of Eigenvectors for Polynomials in Two Matrices

We propose a boundary regularity condition for the $M_n(\mathbb{C})$-valued subordination functions in free probability to prove the local limit theorem and delocalization of eigenvectors for polynomials in two random matrices. We prove this through estimating the pair of $M_n(\mathbb{C})$-valued approximate subordination functions for the sum of two $M_n(\mathbb{C})$-valued random matrices $\gamma_1\otimes C_N+\gamma_2\otimes U_N^*D_NU_N$, where $C_N$, $D_N$ are deterministic diagonal matrices, and $U_N$ is Haar unitary.
An analysis of International Health Regulations Emergency Committees and Public Health Emergency of International Concern Designations.

Introduction Nine events have been assessed for potential declaration of a Public Health Emergency of International Concern (PHEIC). A PHEIC is defined as an extraordinary event that constitutes a public health risk to other states through international spread and requires a coordinated international response. The WHO Director-General convenes Emergency Committees (ECs) to provide their advice on whether an event constitutes a PHEIC. The EC rationales have been criticised for being non-transparent and contradictory to the International Health Regulations (IHR). This first comprehensive analysis of EC rationale provides recommendations to increase clarity of EC decisions which will strengthen the IHR and WHO’s legitimacy in future outbreaks. Methods 66 EC statements were reviewed from nine public health outbreaks of influenza A, Middle East respiratory syndrome coronavirus, polio, Ebola virus disease, Zika, yellow fever and coronavirus disease-2019. Statements were analysed to determine which of the three IHR criteria were noted as contributing towards the EC’s justification on whether to declare a PHEIC and what language was used to explain the decision. Results Interpretation of the criteria were often vague and applied inconsistently. ECs often failed to describe and justify which criteria had been satisfied. Discussion Guidelines must be developed for the standardised interpretation of IHR core criteria. The ECs must clearly identify and justify which criteria have contributed to their rationale for or against PHEIC declaration. Conclusion Striving for more consistency and transparency in EC justifications would benefit future deliberations and provide more understanding and support for the process.
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates

Many applications of computational social science aim to infer causal conclusions from non-experimental data. Such observational data often contains confounders, variables that influence both potential causes and potential effects. Unmeasured or latent confounders can bias causal estimates, and this has motivated interest in measuring potential confounders from observed text. For example, an individual’s entire history of social media posts or the content of a news article could provide a rich measurement of multiple confounders.Yet, methods and applications for this problem are scattered across different communities and evaluation practices are inconsistent.This review is the first to gather and categorize these examples and provide a guide to data-processing and evaluation decisions. Despite increased attention on adjusting for confounding using text, there are still many open problems, which we highlight in this paper.
Estimated Policy Rules for Capital Controls

This paper borrows the tradition of estimating policy reaction functions from monetary policy literature to ask whether capital controls respond to macroprudential or mercantilist motivations. I explore this question using a novel, weekly dataset on capital control actions in 21 emerging economies from 2001 to 2015. I introduce a new proxy for mercantilist motivations: the weighted appreciation of an emerging-market currency against its top five trade competitors. This proxy Granger causes future net initiations of non-tariff barriers in most countries. Emerging markets systematically respond to both mercantilist and macroprudential motivations. Policymakers respond to trade competitiveness concerns by using both instruments—inflow tightening and outflow easing. They use only inflow tightening in response to macroprudential concerns. Policy is acyclical to foreign debt; however, high levels of this debt reduces countercyclicality to mercantilist concerns. Higher exchange rate pass-through to export prices, and having an inflation targeting regime with non-freely floating exchange rates, increase responsiveness to mercantilist concerns.
Improved Natural Language Generation via Loss Truncation

Neural language models are usually trained to match the distributional properties of large-scale corpora by minimizing the log loss. While straightforward to optimize, this approach forces the model to reproduce all variations in the dataset, including noisy and invalid references (e.g., misannotations and hallucinated facts). Even a small fraction of noisy data can degrade the performance of log loss. As an alternative, prior work has shown that minimizing the distinguishability of generated samples is a principled and robust loss that can handle invalid references. However, distinguishability has not been used in practice due to challenges in optimization and estimation. We propose loss truncation: a simple and scalable procedure which adaptively removes high log loss examples as a way to optimize for distinguishability. Empirically, we demonstrate that loss truncation outperforms existing baselines on distinguishability on a summarization task. Furthermore, we show that samples generated by the loss truncation model have factual accuracy ratings that exceed those of baselines and match human references.
Automatic feature extraction of waveform signals for in-process diagnostic performance improvement

In this paper, a new methodology is presented for developing a diagnostic system using waveform signals with limited or with no prior fault information. The key issues studied in this paper are automatic fault detection, optimal feature extraction, optimal feature subset selection, and diagnostic performance assessment. By using this methodology, a diagnostic system can be developed and its performance is continuously improved as the knowledge of process faults is automatically accumulated during production. As a real example, the tonnage signal analysis for stamping process monitoring is provided to demonstrate the implementation of this methodology.
Submodular clustering in low dimensions

We study a clustering problem where the goal is to maximize the coverage of the input points by k chosen centers. Specifically, given a set of n points P ⊆ ℝ^d, the goal is to pick k centers C ⊆ ℝ^d that maximize the service ∑_{p∈P}φ(𝖽(p,C)) to the points P, where 𝖽(p,C) is the distance of p to its nearest center in C, and φ is a non-increasing service function φ: ℝ+ → ℝ+. This includes problems of placing k base stations as to maximize the total bandwidth to the clients - indeed, the closer the client is to its nearest base station, the more data it can send/receive, and the target is to place k base stations so that the total bandwidth is maximized. We provide an n^{e^-O(d)} time algorithm for this problem that achieves a (1-e)-approximation. Notably, the runtime does not depend on the parameter k and it works for an arbitrary non-increasing service function φ: ℝ+ → ℝ+.
Biologically plausible mechanisms underlying motor response correction during reward-based decision-making

Abstract Our propensity to acclimate to new surroundings and flexibly choose an optimal behavior for a maximal reward (i.e., optimal outcome) is natural, for it affects our survival. A line of studies suggested that the anterior cingulate cortex (ACC) could be a potential hub for adaptive behaviors, but its exact functions remain poorly understood. One experimental study suggested that ACC can enable monkeys to correct errors, but another study found that a legion of ACC did not impair monkeys’ ability to correct errors. Instead, it made monkeys incapable of maintaining their optimal actions. Given the importance of ACC in reward-based decision-making, it is imperative to better understand the functions of ACC in reward-based decision-making. To this end, we sought biologically-plausible mechanisms to account for the two seemingly conflicting results mentioned above by utilizing a computational model. From our simulations, we found that 1) the interplay between the prefrontal cortex (PFC) and ACC can account for both experimental observations and 2) ACC can correct behavioral responses by reading out and updating motor plans (guiding future motor responses) stored in PFC.
Field Experiments and the Practice of Policy

Esther Duflo delivered her Prize Lecture on Sunday 8 December 2019, at the Aula Magna, Stockholm University.
Supplier certification and quality investment in supply chains

Global sourcing has made quality management a more challenging task, and supplier certification has emerged as a solution to overcome suppliers' informational advantage about their product quality. This article analyzes the impact of certification standards on the supplier's investment in quality, when a buyer outsources the production process. Based on our results, deterministic certification may lead to under-investment in quality improvement technology for efficient suppliers, thereby leading to potential supply chain inefficiency. The introduction of noisy certification may alleviate this under-investment problem, when the cost of information asymmetry is high. While allowing noisy certification always empowers the buyer to offer a menu to screen among heterogeneous suppliers, the buyer may optimally choose only a limited number of certification standards. Our analysis provides a clear-cut prediction of the types of certifiers the buyer should use for heterogeneous suppliers, and we identify the conditions under which the supplier benefits from noisy certification. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013
What matters to patients? A timely question for value-based care.

Background Our healthcare system is moving towards patient-centered and value-based care models that prioritize health outcomes that matter to patients. However, little is known about what aspects of care patients would prioritize when presented with choices of desirable attributes and whether these patient priorities differ based on certain demographics. Objective To assess patients’ priorities for a range of attributes in ambulatory care consultations across five key health service delivery domains and determine potential associations between patient priorities and certain demographic profiles. Methods Using a What Matters to You survey patients ranked in order of importance various choices related to five health service domains (patient-physician relationship, personal responsibility, test/procedures, medications, and cost). Subjects were selected from two Johns Hopkins affiliated primary care clinics and a third gastroenterology subspecialty clinic over a period of 11 months. We calculated the percentage of respondents who selected each quality as their top 1–3 choice. Univariate and multivariate analyses determined demographic characteristics associated with patient priorities. Results Humanistic qualities of physicians, leading a healthy lifestyle, shared decision making (SDM) for medications and tests/procedures as well as knowledge about insurance coverage were the most frequently ranked choices. Privately insured and more educated patients were less likely to rank humanistic qualities highly. Those with younger age, higher educational attainment and private insurance had higher odds of ranking healthy lifestyle as a top choice. Those with more education had higher odds of ranking SDM as a top choice. Conclusions Identifying what matters most to patients is useful as we move towards patient-centered and Value Based Care Models. Our findings suggest that patients have priorities on qualities they value across key health service domains. Multiple factors including patient demographics can be predictors of these priorities. Elucidating these preferences is a challenging but a valuable step in the right direction.
Sensitivity analysis of treatment effect to unmeasured confounding in observational studies with survival and competing risks outcomes

No unmeasured confounding is often assumed in estimating treatment effects in observational data, whether using classical regression models or approaches such as propensity scores and inverse probability weighting. However, in many such studies collection of confounders cannot possibly be exhaustive in practice, and it is crucial to examine the extent to which the resulting estimate is sensitive to the unmeasured confounders. We consider this problem for survival and competing risks data. Due to the complexity of models for such data, we adapt the simulated potential confounder approach of Carnegie et al (2016), which provides a general tool for sensitivity analysis due to unmeasured confounding. More specifically, we specify one sensitivity parameter to quantify the association between an unmeasured confounder and the exposure or treatment received, and another set of parameters to quantify the association between the confounder and the time-to-event outcomes. By varying the magnitudes of the sensitivity parameters, we estimate the treatment effect of interest using the stochastic expectation-maximization (EM) and the EM algorithms. We demonstrate the performance of our methods on simulated data, and apply them to a comparative effectiveness study in inflammatory bowel disease. An R package "survSens" is available on CRAN that implements the proposed methodology.
NISQ+: boosting quantum computing power by approximating quantum error correction

Quantum computers are growing in size, and design decisions are being made now that attempt to squeeze more computation out of these machines. In this spirit, we design a method to boost the computational power of nearterm quantum computers by adapting protocols used in quantum error correction to implement “Approximate Quantum Error Correction (AQEC):” By approximating fully-fledged error correction mechanisms, we can increase the compute volume (qubits $\times$ gates, or “Simple Quantum Volume (SQV)”) of near-term machines. The crux of our design is a fast hardware decoder that can approximately decode detected error syndromes rapidly. Specifically, we demonstrate a proof-of-concept that approximate error decoding can be accomplished online in near-term quantum systems by designing and implementing a novel algorithm in superconducting Single Flux Quantum (SFQ) logic technology. This avoids a critical decoding backlog, hidden in all offline decoding schemes, that leads to idle time exponential in the number of T gates in a program [58].Our design utilizes one SFQ processing module per physical quantum bit. Employing state-of-the-art SFQ synthesis tools, we show that the circuit area, power, and latency are within the constraints of typical, contemporary quantum system designs. Under a pure dephasing error model, the proposed accelerator and AQEC solution is able to expand SQV by factors between 3,402 and 11,163 on expected near-term machines. The decoder achieves a 5% accuracy threshold as well as pseudo-thresholds of approximately 5%, 4.75%, 4.5%, and 3.5% physical error rates for code distances 3, 5, 7, and 9, respectively. Decoding solutions are achieved in a maximum of $\sim$20 nanoseconds on the largest code distances studied. By avoiding the exponential idle time in offline decoders, we achieve a 10x reduction in required code distances to achieve the same logical performance as alternative designs.
Cell-type-specific promoters for C. elegans glia

Glia shape the development and function of the C. elegans nervous system, especially its sense organs and central neuropil (nerve ring). Cell-type-specific promoters allow investigators to label or manipulate individual glial cell types, and therefore provide a key tool for deciphering glial function. In this technical resource, we compare the specificity, brightness, and consistency of cell-type-specific promoters for C. elegans glia. We identify a set of promoters for the study of seven glial cell types (F16F9.3, amphid and phasmid sheath glia; F11C7.2, amphid sheath glia only; grl-2, amphid and phasmid socket glia; hlh-17, cephalic (CEP) sheath glia; and grl-18, inner labial (IL) socket glia) as well as a pan-glial promoter (mir-228). We compare these promoters to promoters that are expressed more variably in combinations of glial cell types (delm-1 and itx-1). We note that the expression of some promoters depends on external conditions or the internal state of the organism, such as developmental stage, suggesting glial plasticity. Finally, we demonstrate an approach for prospectively identifying cell-type-specific glial promoters using existing single-cell sequencing data, and we use this approach to identify two novel promoters specific to IL socket glia (col-53 and col-177).
BarrierFinder : recognizing ad hoc barriers

Ad hoc synchronizations are pervasive in multi-threaded programs. Due to their diversity and complexity, understanding the enforced synchronization relationships of ad hoc synchronizations is challenging but crucial to multi-threaded program development and maintenance. Existing techniques can partially detect primitive ad hoc synchronizations, but they cannot recognize complete implementations or infer the enforced synchronization relationships. In this paper, we propose a framework to automatically identify complex ad hoc synchronizations in full and infer their synchronization relationships. We instantiate the framework with a tool called BarrierFinder, which features various techniques, including program slicing and bounded symbolic execution, to efficiently explore the interleaving space of ad hoc synchronizations within multi-threaded programs and collect execution traces. BarrierFinder then uses these traces to characterize ad hoc synchronizations into different types with a focus on recognizing barriers. Our evaluation shows that BarrierFinder is both effective and efficient in doing this, and BarrierFinder is also helpful for programmers to understand the correctness of their implemented ad hoc synchronizations.
The Trade and Welfare Impacts of the U.S. Retaliatory Tariff on EU Olive Oil

We investigate the welfare and trade impacts of U.S. retaliatory tariffs from the Airbus WTO dispute on EU olive oil, using a calibrated multi-market partial-equilibrium displacement model. The model accounts for four differentiated types of retail olive oil in the U.S. market. U.S. retailer-blenders source olive oil in eight foreign markets and domestically and for two qualities of oil (virgin, other), and in two shipping container types (non-bulk, bulk). We consider two main scenarios: A 100% tariff on all EU olive oils as initially announced by the USTR, and the actual and final 25% tariff on non-bulk Spanish olive oil. The first scenario leads to significant loss of welfare for U.S. consumers of $924 million, much reduced EU olive oil exports to the United States ($354 million), and increased imports from non-EU sources ($90 million). The second scenario has much more muted effects, with mitigated welfare losses for U.S. consumers ($55 million), strong decreases of Spanish olive oil exports shipped in smaller containers, much larger exports of bulk Spanish olive oil and other olive oils. Aggregate EU exports to the United States are slightly lower given the substantial trade diversion induced by the targeted tariff. We discuss the political economy of the contrasting initial announcement and limited implemented retaliation.
The shapes of wine and table grape leaves: An ampelometric study inspired by the methods of Pierre Galet

The shapes of grapevine leaves have been critical to correctly identify economically important varieties throughout history. The correspondence of homologous features in nearly all grapevine species and varieties has enabled advanced morphometric approaches to mathematically classify leaf shape. These approaches either model leaves through the measurement of numerous vein lengths and angles or measure a finite number of corresponding landmarks and use Procrustean approaches to superimpose points and perform statistical analyses. Hand illustrations, too, play an important role in grapevine identification, as details omitted using the above methods can be visualized. Here, I use a saturating number of pseudo-landmarks to capture intricate, local features in grapevine leaves: the curvature of veins and the shapes of serrations. Using these points, averaged leaf shapes for 60 varieties of wine and table grapes are calculated that preserve features. A pairwise Procrustes distance matrix of the overall morphological similarity of each variety to the other classifies leaves into two main groups, deeply lobed and more entire, that correspond to the measurements of sinus depth by Pierre Galet. Using the system of Galet, pseudo-landmarks are converted into relative distance and angle measurements. Both Galet-inspired and Procrustean methods allow increased accuracy in predicting variety compared to a finite number of landmarks. Using Procrustean pseudo-landmarks captures grapevine leaf shape at the same level of detail as drawings and provides a quantitative method to arrive at mean leaf shapes representing varieties that can be used within a predictive statistical framework.
Knockout of the gene encoding the extracellular matrix protein SNED1 results in early neonatal lethality and craniofacial malformations

Background The extracellular matrix (ECM) is a fundamental component of multicellular organisms that orchestrates developmental processes and controls cell and tissue organization. We previously identified the novel ECM protein SNED1 as a promoter of breast cancer metastasis and showed that its level of expression negatively correlated with breast cancer patient survival. Here, we sought to identify the roles of SNED1 during murine development. Results We generated two novel Sned1 knockout mouse strains and showed that Sned1 is essential since homozygous ablation of the gene led to early neonatal lethality. Phenotypic analysis of the surviving knockout mice revealed a role for SNED1 in the development of craniofacial and skeletal structures since Sned1 knockout resulted in growth defects, nasal cavity occlusion, and craniofacial malformations. Sned1 is widely expressed in embryos, notably by cell populations undergoing epithelial-to-mesenchymal transition, such as the neural crest cells. We further show that mice with a neural-crest-cell-specific deletion of Sned1 survive, but display facial anomalies partly phenocopying the global knockout mice. Conclusions Our results demonstrate requisite roles for SNED1 during development and neonatal survival. Importantly, the deletion of 2q37.3 in humans, a region that includes the SNED1 locus, has been associated with facial dysmorphism and short stature.
Contemporary Endovascular Outcomes for Critical Limb Ischemia Are Still Failing to Meet Society for Vascular Surgery Objective Performance Goals

Objectives:The Society for Vascular Surgery (SVS) created Objective Performance Goals (OPGs) for critical limb ischemia (CLI) in 2009. It was previously shown that endovascular therapy for CLI was ...
Magnetic Models of Solar Flares

A solar flare is interpreted as the explosive release of magnetic energy associated with a current sheet in the solar atmosphere. The release is due to field-line reconnection caused by the tearing-mode instability. Current sheets may be classified into closed and open, depending on whether the adjacent field lines are closed (contained in the sun's atmosphere) or open, extending into interplanetary space. A high-energy event requires an open current sheet. It is shown that certain types of photospheric motion may lead to the formation of current sheets. One of these is associated with high-energy events, another with filaments, and a third with surge flares.
Characterization of structure and growth evolution for nc-Si:H in the tandem photovoltaic device configuration

Spectroscopic ellipsometry (SE) is used to study growth evolution of bottom cell p-type doped and intrinsic hydrogenated silicon (Si:H) layers in p-i-n amorphous/nanocrystalline (a-Si:H/nc-Si:H) tandem photovoltaic (PV) devices. From SE data collected in situ during Si:H growth, crystallite coalescence transitions are identified as well as variations in optical response, in the form of the complex dielectric function (e = e1 + ie2), also consistent with transitions from mixed (a+nc) to single phase nc-Si:H during growth. A growth evolution diagram for the i-layer in the tandem PV device configuration is constructed. Device properties are related to p- and i-layer structure.
Smooth and singular maximal averages over 2D hypersurfaces and associated Radon transforms

Abstract We prove L p boundedness results, p > 2 , for local maximal averaging operators over a smooth 2D hypersurface S with either a C 1 density function or a density function with a singularity that grows as | ( x , y ) | − β for β 2 . Suppose one is in coordinates such that the surface is localized near some ( x 0 , y 0 , z 0 ) at which ( 0 , 0 , 1 ) is normal to the surface, and suppose the surface is represented as the graph of z 0 + s ( x − x 0 , y − y 0 ) near ( x 0 , y 0 ) , with s ( 0 , 0 ) = 0 . It is shown that as long as the Taylor series of the Hessian determinant of s ( x , y ) at ( 0 , 0 ) is not identically zero, the maximal averaging operator is bounded on L p for p > max ⁡ ( 2 , 1 / g ) , where g is an index based on the growth rate of the distribution function of s ( x , y ) near the origin. Standard examples show that the exponent 1 / g is best possible whenever the tangent plane to S at ( x 0 , y 0 , z 0 ) does not contain the origin. This theorem improves on the main result of [19] , using different methods. We use closely related methods to prove L p to L α p Sobolev estimates for Radon transform operators with the same density functions, with no excluded cases. In the g 1 / 2 case, there is an interval I containing 2 for which L p to L α p boundedness is proven for α g when p ∈ I , and for such p one can never gain more than g derivatives.
On 3 + 1 Lorentzian Einstein manifolds with one rotational isometry

We consider 3 + 1 rotationally symmetric Lorentzian Einstein spacetime manifolds with $$\varLambda >0$$ and reduce the field equations to 2 + 1 Einstein’s equations coupled to ‘shifted’ wave maps. Subsequently, we prove various (explicit) positive mass-energy theorems. No smallness is assumed.
Squashed Giants: Bound States of Giant Gravitons

We consider giant gravitons in the maximally supersymmetric type-IIB plane-wave, in the presence of a constant NSNS B-field background. We show that in response to the background B-field the giant graviton would take the shape of a deformed three-sphere, the size and shape of which depend on the B-field, and that the giant becomes classically unstable once the B-field is larger than a critical value Bcr. In particular, for the B-field which is (anti-)self-dual under the SO(4) isometry of the original giant S3, the closed string metric is that of a round S3, while the open string metric is a squashed three-sphere. The squashed giant can be interpreted as a bound state of a spherical three-brane and circular D-strings. We work out the spectrum of geometric fluctuations of the squashed giant and study its stability. We also comment on the gauge theory which lives on the brane (which is generically a noncommutative theory) and a possible dual gauge theory description of the deformed giant.
METALLICITY EVOLUTION OF THE SIX MOST LUMINOUS M31 DWARF SATELLITES

We present global metallicity properties, metallicity distribution functions (MDFs), and radial metallicity profiles for the six most luminous M31 dwarf galaxy satellites: M32, NGC 205, NGC 185, NGC 147, Andromeda VII, and Andromeda II. The results presented are the first spectroscopic MDFs for dwarf systems surrounding a host galaxy other than the Milky Way (MW). Our sample consists of individual metallicity measurements for 1243 red giant branch member stars spread across these six systems. We determine metallicities based on the strength of the Ca II triplet lines using the empirical calibration of Carrera et al., which is calibrated over the metallicity range –4 < [Fe/H] <+0.5. We find that these M31 satellites lie on the same luminosity-metallicity relationship as the MW dwarf satellites. We do not find a trend between the internal metallicity spread and galaxy luminosity, contrary to previous studies. The MDF widths of And II and And VII are similar to the MW dwarf spheroidal (dSph) satellites of comparable luminosity; however, our four brightest M31 dwarf satellites are more luminous than any of the MW dSphs and have broader MDFs. The MDFs of our six M31 dwarf satellites are consistent with the leaky box model of chemical evolution, although our metallicity errors allow a wide range of evolution models. We find a significant radial gradient in metallicity in only two of our six systems, NGC 185 and Andromeda II, and flat radial metallicity gradients in the rest of our sample with no observed correlation between rotational support and radial metallicity gradients. Although the average properties and radial trends of the M31 dwarf galaxies agree with their MW counterparts at similar luminosity, the detailed MDFs are different, particularly at the metal-rich end.
Convergence Rates in L 2 for Elliptic Homogenization Problems

We study rates of convergence of solutions in L2 and H1/2 for a family of elliptic systems \({\{\mathcal{L}_\varepsilon\}}\) with rapidly oscillating coefficients in Lipschitz domains with Dirichlet or Neumann boundary conditions. As a consequence, we obtain convergence rates for Dirichlet, Neumann, and Steklov eigenvalues of \({\{\mathcal{L}_\varepsilon\}}\) . Most of our results, which rely on the recently established uniform estimates for the L2 Dirichlet and Neumann problems in Kenig and Shen (Math Ann 350:867–917, 2011; Commun Pure Appl Math 64:1–44, 2011) are new even for smooth domains.
SUBFACTORS OF INDEX LESS THAN 5, PART 2: TRIPLE POINTS

We summarize the known obstructions to subfactors with principal graphs which begin with a triple point. One is based on Jones's quadratic tangles techniques, although we apply it in a novel way. The other two are based on connections techniques; one due to Ocneanu, and the other previously unpublished, although likely known to Haagerup. We then apply these obstructions to the classification of subfactors with index below 5. In particular, we eliminate three of the five families of possible principal graphs called "weeds" in the classification from S. Morrison and N. Snyder, Subfactors of index less than 5, part 1: the principal graph odometer, to appear in Comm. Math. Phys.
JIMWLK evolution, Lindblad equation and quantum-classical correspondence

In the Color Glass Condensate (CGC) effective theory, the physics of valence gluons with large longitudinal momentum is reflected in the distribution of color charges in the transverse plane. Averaging over the valence degrees of freedom is effected by integrating over classical color charges with some quasi probability weight functional W [j] whose evolution with rapidity is governed by the JIMWLK equation. In this paper, we reformulate this setup in terms of effective quantum field theory on valence Hilbert space governed by the reduced density matrix $$ \hat{\rho} $$ for hard gluons, which is obtained after properly integrating out the soft gluon “environment”. We show that the evolution of this density matrix with rapidity in the dense and dilute limits has the form of Lindblad equation. The quasi probability distribution (weight) functional W is directly related to the reduced density matrix $$ \hat{\rho} $$ through the generalization of the Wigner-Weyl quantum-classical correspondence, which reformulates quantum dynamics on Hilbert space in terms of classical dynamics on the phase space. In the present case the phase space is non Abelian and is spanned by the components of transverse color charge density j. The same correspondence maps the Lindblad equation for $$ \hat{\rho} $$ into the JIMWLK evolution equation for W .
The Largest Eigenvalue of Real Symmetric, Hermitian and Hermitian Self-dual Random Matrix Models with Rank One External Source, Part I

We consider the limiting location and limiting distribution of the largest eigenvalue in real symmetric (β=1), Hermitian (β=2), and Hermitian self-dual (β=4) random matrix models with rank 1 external source. They are analyzed in a uniform way by a contour integral representation of the joint probability density function of eigenvalues. Assuming the “one-band” condition and certain regularities of the potential function, we obtain the limiting location of the largest eigenvalue when the nonzero eigenvalue of the external source matrix is not the critical value, and further obtain the limiting distribution of the largest eigenvalue when the nonzero eigenvalue of the external source matrix is greater than the critical value. When the nonzero eigenvalue of the external source matrix is less than or equal to the critical value, the limiting distribution of the largest eigenvalue will be analyzed in a subsequent paper. In this paper we also give a definition of the external source model for all β>0.
Tracing electron beams in the sun's corona with radio dynamic imaging spectroscopy

We report observations of type III radio bursts at decimeter wavelengths (type IIIdm bursts)—signatures of suprathermal electron beams propagating in the low corona—using the new technique of radio dynamic imaging spectroscopy provided by the recently upgraded Karl G. Jansky Very Large Array. For the first time, type IIIdm bursts were imaged with high time and frequency resolution over a broad frequency band, allowing electron beam trajectories in the corona to be deduced. Together with simultaneous hard X-ray and extreme ultraviolet observations, we show that these beams emanate from an energy release site located in the low corona at a height below ~15 Mm, and propagate along a bundle of discrete magnetic loops upward into the corona. Our observations enable direct measurements of the plasma density along the magnetic loops, and allow us to constrain the diameter of these loops to be less than 100 km. These overdense and ultra-thin loops reveal the fundamentally fibrous structure of the Sun's corona. The impulsive nature of the electron beams, their accessibility to different magnetic field lines, and the detailed structure of the magnetic release site revealed by the radio observations indicate that the localized energy release is highly fragmentary in time and space, supporting a bursty reconnection model that involves secondary magnetic structures for magnetic energy release and particle acceleration.
Causal Estimation with Functional Confounders

Causal inference relies on two fundamental assumptions: ignorability and positivity. We study causal inference when the true confounder value can be expressed as a function of the observed data; we call this setting estimation with functional confounders (EFC). In this setting ignorability is satisfied, however positivity is violated, and causal inference is impossible in general. We consider two scenarios where causal effects are estimable. First, we discuss interventions on a part of the treatment called functional interventions and a sufficient condition for effect estimation of these interventions called functional positivity. Second, we develop conditions for nonparametric effect estimation based on the gradient fields of the functional confounder and the true outcome function. To estimate effects under these conditions, we develop Level-set Orthogonal Descent Estimation (LODE). Further, we prove error bounds on LODE’s effect estimates, evaluate our methods on simulated and real data, and empirically demonstrate the value of EFC.
Logarithmic forms and differential equations for Feynman integrals

We describe in detail how a d log representation of Feynman integrals leads to simple differential equations. We derive these differential equations directly in loop momentum or embedding space making use of a localization trick and generalized unitarity. For the examples we study, the alphabet of the differential equation is related to special points in kinematic space, described by certain cut equations which encode the geometry of the Feynman integral. At one loop, we reproduce the motivic formulae described by Goncharov [1] that reappeared in the context of Feynman integrals in [2–4]. The d log representation allows us to generalize the differential equations to higher loops and motivates the study of certain mixed-dimension integrals.
The Eating Habits of Milky Way Mass Halos: Destroyed Dwarf Satellites and the Metallicity Distribution of Accreted Stars

In this paper, we study the mass spectrum of destroyed dwarfs that contribute to the accreted stellar mass of Milky Way (MW)-mass (Mvir ~ 1012.1 M⊙) halos using a suite of 45 zoom-in dissipationless simulations. Empirical models are employed to relate (peak) subhalo mass to dwarf stellar mass, and we use constraints from z = 0 observations and hydrodynamical simulations to estimate the metallicity distribution of the accreted stellar material. The dominant contributors to the accreted stellar mass are relatively massive dwarfs with Mstar ~ 108–1010M⊙. Halos with more quiescent accretion histories tend to have lower mass progenitors (108–109 M⊙), and lower overall accreted stellar masses. Ultra-faint mass (Mstar 108 M⊙ can contribute a considerable fraction (~20%–60%) of metal-poor stars if their metallicity distributions have significant metal-poor tails. Finally, we find that the generic assumption of a quiescent assemblymore » history for the MW halo seems to be in tension with the mass spectrum of its surviving dwarfs. In conclusion, we suggest that the MW could be a "transient fossil"; a quiescent halo with a recent accretion event(s) that disguises the preceding formation history of the halo.« less
Dark matter and LHC: What is the connection?

We review what can (and cannot) be learned if dark matter is detected in one or more experiments, emphasizing the importance of combining LHC data with direct, astrophysical and cosmological probes of dark matter. We briefly review the conventional picture of a thermally produced WIMP relic density and its connection with theories of electroweak symmetry breaking. We then discuss both experimental and theoretical reasons why one might generically expect this picture to fail. If this is the case, we argue that a combined effort bringing together all types of data — combined with explicitly constructed theoretical models — will be the only way to achieve a complete understanding of the dark matter in our universe and become confident that any candidate actually provides the relic density.
D-branes, discrete torsion and the McKay correspondence

We analyze the D-branes of a type-IIB string theory on an orbifold singularity including the possibility of discrete torsion following the work of Douglas et al. First we prove some general results about the moduli space of a point associated to the ``regular representation'' of the orbifold group. This includes some analysis of the ``wrapped branes'' which necessarily appear when the orbifold singularity is not isolated. Next we analyze the stringy homology of the orbifold using the McKay correspondence and the relationship between K-theory and homology. We find that discrete torsion and torsion in this stringy homology are closely-related concepts but that they differ in general. Lastly we question to what extent the D-1 brane may be thought of as being dual to a string.
Asymmetric, closed-form, finite-parameter models of multinomial choice

Abstract Class imbalance, where there are great differences between the number of observations associated with particular discrete outcomes, is common within transportation and other fields. In the statistics literature, one explanation for class imbalance that has been hypothesized is an asymmetric (rather than the typically symmetric) choice probability function. Unfortunately, few relatively simple models exist for testing this hypothesis in transportation settings—settings that are inherently multinomial. Our paper fills this gap. In particular, we address the following questions: “how can one construct asymmetric, closed-form, finite-parameter models of multinomial choice” and “how do such models compare against commonly used symmetric models?” Methodologically, we introduce (1) a new class of closed-form, finite-parameter, multinomial choice models, (2) a procedure for using these models to extend existing binary choice models to the multinomial setting, and (3) a procedure for creating new binary choice models (both symmetric and asymmetric). Together, our contributions allow us to create new asymmetric, closed-form, finite-parameter multinomial choice models. We demonstrate our methods by developing four new asymmetric, multinomial choice models. Empirically, most of our models strongly dominate the multinomial logit (MNL) model in terms of in-sample and out-of-sample log-likelihoods. Moreover, analyzing two policy applications, we find practical differences between the MNL and our new asymmetric models. Our results suggest that while asymmetric models may not always outperform symmetric ones, asymmetric choice models are worth testing because they might have better statistical performance and entail substantively different policy and financial implications when compared with traditional symmetric models, such as the MNL.
Solar Active Region Coronal Jets. II. Triggering and Evolution of Violent Jets

We study a series of X-ray-bright, rapidly-evolving active-region coronal jets outside the leading sunspot of AR 12259, using Hinode/XRT, SDO/AIA and HMI, and IRIS data. The detailed evolution of such rapidly evolving "violent" jets remained a mystery after our previous investigation of active region jets (Sterling et al. 2016, Paper 1). The jets we investigate here erupt from three localized subregions, each containing a rapidly evolving (positive) minority-polarity magnetic-flux patch bathed in a (majority) negative-polarity magnetic-flux background. At least several of the jets begin with eruptions of what appear to be thin (thickness <~2") miniature-filament (minifilament) "strands" from a magnetic neutral line where magnetic flux cancelation is ongoing, consistent with the magnetic configuration presented for coronal-hole jets in Sterling et al. (2015). Some jets strands are difficult/impossible to detect, perhaps due to, e.g. their thinness, obscuration by surrounding bright or dark features, or the absence of erupting cool-material minifilaments in those jets. Tracing in detail the flux evolution in one of the subregions, we find bursts of strong jetting occurring only during times of strong flux cancelation. Averaged over seven jetting episodes, the cancelation rate was ~1.5x10^19 Mx/hr. An average flux of ~5x10^18 Mx canceled prior to each episode, arguably building up ~10^28 - 10^29 ergs of free magnetic energy per jet. From these and previous observations, we infer that flux cancelation is the fundamental process responsible for the pre-eruption buildup and triggering of at least many jets in active regions, quiet regions, and coronal holes.
Compressibility of Positive Semidefinite Factorizations and Quantum Models

We investigate compressibility of the dimension of positive semidefinite matrices, while approximately preserving their pairwise inner products. This can either be regarded as compression of positive semidefinite factorizations of nonnegative matrices or (if the matrices are subject to additional normalization constraints) as compression of quantum models. We derive both lower and upper bounds on compressibility. Applications are broad and range from the analysis of experimental data to bounding the one-way quantum communication complexity of Boolean functions.