cssi/SciSciGPT-SciSciNet huggingface dataset:
Performance Guarantees for Adaptive Estimation of Sparse Signals

This paper studies adaptive sensing for estimating the nonzero amplitudes of a sparse signal with the aim of providing analytical guarantees on the performance gain due to adaptive resource allocation. We consider a previously proposed optimal two-stage policy for allocating sensing resources. For positive powers $q$ , we derive tight upper bounds on the mean $q$ th-power error resulting from the optimal two-stage policy and corresponding lower bounds on the improvement over nonadaptive uniform sensing. It is shown that the adaptation gain is related to the detectability of nonzero signal components as characterized by Chernoff coefficients, thus quantifying analytically the dependence on the sparsity level of the signal, the signal-to-noise ratio (SNR), and the sensing resource budget. For fixed sparsity levels and increasing SNR or sensing budget, we obtain the rate of convergence to oracle performance and the rate at which the fraction of resources spent on the first exploratory stage decreases to zero. For a vanishing fraction of nonzero components, the gain increases without bound as a function of SNR and sensing budget. Numerical simulations demonstrate that the bounds on adaptation gain are quite tight in nonasymptotic regimes as well.
School spending and new construction

Abstract School districts that vote in favor of property tax levies may signal that they are education-oriented. Through Tiebout sorting and housing developer activity, new residents might move to such communities. New retail development may occur near these new residents, and office firms that rely on high-skilled residents might be drawn too. Using regression discontinuity we find school districts that renew property tax levies have a higher value of new construction than districts that do not renew these school expenditures. School tax levy renewal is responsible for 14% of new residential construction and 25% of new commercial construction.
Humanizing brands: When brands seem to be like me, part of me, and in a relationship with me

Abstract We review a growing body of research in consumer behavior that has examined when consumers humanize brands by perceiving them as like, part of, or in a relationship with themselves. One research stream shows that sometimes consumers perceive brands as having human-like forms, minds, and personality characteristics. A second stream identifies ways that a consumer perceives a brand as being congruent with or connected to the self. Finally, a third highlights that consumers can view brands in ways that are analogous to the types of relationships they have with people. We review research in these three areas and point out connections among these research streams. In part, we accomplish this by showing that factors associated with the SEEK model, which are designed to explain anthropomorphic tendencies, are also relevant to other ways of humanizing brands. We identify major propositions derived from this research and several areas for which additional research is needed. We conclude with recommendations for the many opportunities for expanding our conceptual and empirical understanding of this domain.
Single-particle dynamics in a nonlinear accelerator lattice: attaining a large tune spread with octupoles in IOTA

Fermilab is constructing the Integrable Optics Test Accelerator (IOTA) as the centerpiece of the Accelerator R&D Program towards high-intensity circular machines. One of the factors limiting the beam intensity in present circular accelerators is collective instabilities, which can be suppressed by a spread of betatron frequencies (tunes) through the Landau damping mechanism or by an external damper, if the instability is slow enough. The spread is usually created by octupole magnets, which introduce the tune dependence on the amplitude and, in some cases, by a chromatic spread (tune dependence on particle's momentum). The introduction of octupoles usually has both beneficial (improved Landau damping) and harmful properties, such as a resonant behavior and a reduction of the dynamic aperture. One of the research goals at the IOTA ring is to achieve a large betatron tune spread, while retaining a large dynamic aperture, using conventional octupole magnets in a special but realistic accelerator configuration. The configuration, although not integrable by design, approximates an autonomous 2D Hamiltonian system. In this paper, we present results of computer simulations of an electron beam in the IOTA by particle tracking and the Frequency Map Analysis. The results show that the ring's octupole magnets can be configured to provide a betatron tune shift of 0.08 (for particles at large amplitudes) with the dynamical aperture of over 20 beam sigma for a 150-MeV electron beam. The influence of the synchrotron motion, lattice errors, and magnet imperfections is insignificant for the parameters and levels of tolerances set by the design of the ring. The described octupole insert could be beneficial for enhancing Landau damping in high intensity machines.
Strip model for steel plate shear walls with beam-connected web plates

Abstract Steel plate shear walls comprise web plates connected to beams and columns, also referred to as vertical and horizontal boundary elements, respectively. When loaded laterally, web plates induce high flexural and axial demands in the columns due to the development of an inclined tension field. An alternative lateral force-resisting system is proposed in which the steel plate shear wall web plates are attached only to the beams to avoid high flexural demands in the columns resulting from the inclined tension. In this study, beam-connected web plate behavior is characterized using validated finite element models, a simplified strip model is proposed to simulate hysteretic web plate behavior, and equations for the inclination angle of the partial tension field and compressive strength of strips are presented. A comparison between the finite element model, the current strip model from the literature, and the new proposed strip model is provided. Results indicate that the proposed model successfully estimates beam and column demands, base shear capacity, and energy dissipation capacity of the beam-connected web plate for a wide range of web plate aspect ratios and height-to-thickness ratios.
Pseudo-Wigner Matrices

We consider the problem of generating pseudo-random matrices based on the similarity of their spectra to Wigner’s semicircular law. We introduce the notion of an $r$ -independent pseudo-Wigner matrix ensemble and prove the closeness of the spectra of its matrices to the semicircular density in the Kolmogorov distance. We give an explicit construction of a family of $N \times N$ pseudo-Wigner ensembles using dual BCH codes and show that the Kolmogorov complexity of the obtained matrices is of the order of ${\mathrm{log}}(N)$ bits for a fixed designed Kolmogorov distance precision. We compare our construction with the quasi-random graphs introduced by Chung et al. and demonstrate that the pseudo-Wigner matrices pass stronger randomness tests than the adjacency matrices of these graphs (lifted by the mapping $0 \rightarrow 1$ and $1 \rightarrow -1$ ) do. Finally, we provide numerical simulations verifying our theoretical results.
Proofs of two conjectures of Kenyon and Wilson on Dyck tilings

Recently, Kenyon and Wilson introduced a certain matrix M in order to compute pairing probabilities of what they call the double-dimer model. They showed that the absolute value of each entry of the inverse matrix $M^-1$ is equal to the number of certain Dyck tilings of a skew shape. They conjectured two formulas on the sum of the absolute values of the entries in a row or a column of $M^-1$. In this paper we prove the two conjectures. As a consequence we obtain that the sum of the absolute values of all entries of $M^-1$ is equal to the number of complete matchings. We also find a bijection between Dyck tilings and complete matchings.
Theory of Mind predicts cooperative behavior

Abstract Explanations for cooperation in Prisoner’s Dilemma games have generated significant interest. While institutional explanations have offered considerable explanatory ability, a psychological measure of Theory of the Mind that measures an individual’s ability to process social and emotional cognition offers new insights. Using this measure, we examine how it explains (un)cooperative behavior. We find that subjects who have higher ToM are less cooperative and extract higher payoffs.
Fourier transform of anisotropic Hardy spaces

Abstract. We show that if f is in an anisotropic Hardy space H A, 0 < p ≤ 1, with respect to a dilation matrix A, then its Fourier transform f satisfies the pointwise estimate |f(ξ)| ≤ C||f ||Hp A ρ∗(ξ) 1 p −1 . Here, ρ∗ is a quasi-norm associated with the transposed matrix A∗. This leads to necessary conditions for functions m to be multipliers on H A, as well as further pointwise characterizations on f and a generalization of the HardyLittlewood inequality on the integrability of f . This last result is strengthened through the use of rearrangement functions.
Bulk connectedness and boundary entanglement

We prove, for any state in a conformal field theory defined on a set of boundary manifolds with corresponding classical holographic bulk geometry, that for any bipartition of the boundary into two non-clopen sets, the density matrix cannot be a tensor product of the reduced density matrices on each region of the bipartition. In particular, there must be entanglement across the bipartition surface. We extend this no-go theorem to general, arbitrary partitions of the boundary manifolds into non-clopen parts, proving that the density matrix cannot be a tensor product. This result gives a necessary condition for states to potentially correspond to holographic duals.
Character-level deep conflation for business data analytics

Connecting different text attributes associated with the same entity (conflation) is important in business data analytics since it could help merge two different tables in a database to provide a more comprehensive profile of an entity. However, the conflation task is challenging because two text strings that describe the same entity could be quite different from each other for reasons such as misspelling. It is therefore critical to develop a conflation model that is able to truly understand the semantic meaning of the strings and match them at the semantic level. To this end, we develop a character-level deep conflation model that encodes the input text strings from character level into finite dimension feature vectors, which are then used to compute the cosine similarity between the text strings. The model is trained in an end-to-end manner using back propagation and stochastic gradient descent to maximize the likelihood of the correct association. Specifically, we propose two variants of the deep conflation model, based on long-short-term memory (LSTM) recurrent neural network (RNN) and convolutional neural network (CNN), respectively. Both models perform well on a real-world business analytics dataset and significantly outperform the baseline bag-of-character (BoC) model.
Are there topological black-hole solitons in string theory?

We point out that the celebrated Hawking effect of quantum instability of black holes seems to be a purely semiclassical but nonperturbative effect in string theory. Studying quantum dynamics of strings in the gravitational background of black holes we find classical instability due to emission of massless string excitations. The topology of a black hole seems to play a fundamental role in developing the string theory classical instability due to the effect of sigma model instantons. We argue that string theory allows for a qualitative description of black holes with very small masses and it predicts topological solitons with quantized spectrum of masses. These solitons would not decay into string massless excitations but could be pair-created and may annihilate also. Semiclassical mass quantization of topological solitons in string theory is based on the argument showing the existence of nontrivial zeros of the beta function of the renormalization group.
SINR and Throughput of Dense Cellular Networks With Stretched Exponential Path Loss

Distance-based attenuation is a critical aspect of wireless communications. As opposed to the ubiquitous power-law path loss model, this paper proposes a stretched exponential path loss model that is suitable for short-range communication. In this model, the signal power attenuates over a distance $r$ as $e^{-\alpha r^{\beta }}$ , where $\alpha$ and $\beta$ are tunable parameters. Using experimental propagation measurements, we show that the proposed model is accurate for short to moderate distances in the range $r \in ~(5,300)$ meters and so is a suitable model for dense and ultradense networks. We integrate this path loss model into a downlink cellular network with base stations modeled by a Poisson point process, and derive expressions for the coverage probability, potential throughput, and area spectral efficiency. Although the most general result for coverage probability has a double integral, several special cases are given, where the coverage probability has a compact or even closed form. We then show that the potential throughput is maximized for a particular BS density and then collapses to zero for high densities, assuming a fixed signal-to-interference-plus-noise ratio (SINR) threshold. We next prove that the area spectral efficiency, which assumes an adaptive SINR threshold, is nondecreasing with the BS density and converges to a constant for high densities.
Efficient motion planning for problems lacking optimal substructure

We consider the motion-planning problem of planning a collision-free path of a robot in the presence of risk zones. The robot is allowed to travel in these zones but is penalized in a super-linear fashion for consecutive accumulative time spent there. We suggest a natural cost function that balances path length and risk-exposure time. Specifically, we consider the discrete setting where we are given a graph, or a roadmap, and we wish to compute the minimal-cost path under this cost function. Interestingly, paths defined using our cost function do not have an optimal substructure. Namely, subpaths of an optimal path are not necessarily optimal. Thus, the Bellman condition is not satisfied and standard graph-search algorithms such as Dijkstra cannot be used. We present a path-finding algorithm, which can be seen as a natural generalization of Dijkstra's algorithm. Our algorithm runs in $O\left((n_B\cdot n) \log( n_B\cdot n) + n_B\cdot m\right)$ time, where~$n$ and $m$ are the number of vertices and edges of the graph, respectively, and $n_B$ is the number of intersections between edges and the boundary of the risk zone. We present simulations on robotic platforms demonstrating both the natural paths produced by our cost function and the computational efficiency of our algorithm.
Parameter Optimization for Interaction between C-Terminal Domains of HIV-1 Capsid Protein

HIV-1 capsid proteins (CAs) assemble into a capsid that encloses the viral RNA. The binding between a pair of C-terminal domains (CTDs) constitutes a major interface in both the CA dimers and the large CA assemblies. Here, we attempt to use a general residue-level coarse-grained model to describe the interaction between two isolated CTDs in Monte Carlo simulations. With the standard parameters that depend only on the residue types, the model predicts a much weaker binding in comparison to the experiments. Detailed analysis reveals that some Lennard-Jones parameters are not compatible with the experimental CTD dimer structure, thus resulting in an unfavorable interaction energy. To improve the model for the CTD binding, we introduce ad hoc modifications to a small number of Lennard-Jones parameters for some specific pairs of residues at the binding interface. Through a series of extensive Monte Carlo simulations, we identify the optimal parameters for the CTD–CTD interactions. With the refined model parame...
A comprehensive model for provenance

In this paper, we propose a provenance model able to represent the provenance of any data object captured at any abstraction layer (workflow/process/OS) and present an abstract schema of the model. The expressive nature of the model makes it potential to be utilized in real world data processing systems.
Adversarial ranking for language generation

Generative adversarial networks (GANs) have great successes on synthesizing data. However, the existing GANs restrict the discriminator to be a binary classifier, and thus limit their learning capacity for tasks that need to synthesize output with rich structures such as natural language descriptions. In this paper, we propose a novel generative adversarial network, RankGAN, for generating high-quality language descriptions. Rather than training the discriminator to learn and assign absolute binary predicate for individual data sample, the proposed RankGAN is able to analyze and rank a collection of human-written and machine-written sentences by giving a reference group. By viewing a set of data samples collectively and evaluating their quality through relative ranking scores, the discriminator is able to make better assessment which in turn helps to learn a better generator. The proposed RankGAN is optimized through the policy gradient technique. Experimental results on multiple public datasets clearly demonstrate the effectiveness of the proposed approach.
Macroeconomic dynamics and the IS puzzle

The authors solve the IS puzzle for the G7 countries. They find that five of the G7 countries have the expected significant negative relationship between the output gap and the realrate gap; the time series of the remaining two show material deviation from expected IScurve behavior. The authors show that the observed time dependence of the interaction between the output and real-rate gaps can be represented in a parsimonious and practical manner using the theory of anelasticity that unifies partial-adjustment specifications of the IS curve.
Footstep and motion planning in semi-unstructured environments using randomized possibility graphs

Traversing environments with arbitrary obstacles poses significant challenges for bipedal robots. In some cases, whole body motions may be necessary to maneuver around an obstacle, but most existing footstep planners can only select from a discrete set of predetermined footstep actions; they are unable to utilize the continuum of whole body motion that is truly available to the robot platform. Existing motion planners that can utilize whole body motion tend to struggle with the complexity of large-scale problems. We introduce a planning method, called the “Randomized Possibility Graph”, which uses high-level approximations of constraint manifolds to rapidly explore the “possibility” of actions, thereby allowing lower-level motion planners to be utilized more efficiently. We demonstrate simulations of the method working in a variety of semi-unstructured environments. In this context, “semi-unstructured” means the walkable terrain is flat and even, but there are arbitrary 3D obstacles throughout the environment which may need to be stepped over or maneuvered around using whole body motions.
Fully Automated Learning for Application-Specific Web Video Classification.

Personalization applications such as content recommendations, product recommendations and advertisements, and social network related recommendations, can be quite beneficial for both service providers and users. Such applications need to understand user preferences in order to provide customized services. As user engagement with web videos has grown significantly, understanding user preferences based on videos viewed looks promising. The above requires ability to classify web videos into a set of categories appropriate for the personalization application. However, such categories may be substantially different from common categories like Sports, Music, Comedy, etc. used by video sharing websites, leading to lack of labeled training videos for such categories. In this paper, we study the feasibility and effectiveness of a fully automated framework to obtain training videos to enable classification of web videos to any arbitrary set of categories, as desired by the personalization application. We investigate the desired properties in training data that can lead to high performance of the trained classification models. We then develop an approach to identify and score keywords based on their suitability to retrieve training videos, with the desired properties, for the specified set of categories. Experimental results on several sets of categories demonstrate the ability of the proposed approach to obtain effective training data, and hence achieve high video classification performance.
The Cost of Capital for Alternative Investments

This paper studies the cost of capital for alternative investments. We document that the risk prole of the aggregate hedge fund universe can be accurately matched by a simple index put option writing strategy that oers monthly liquidity and complete transparency over its state-contingent payos. The contractual nature of the put options in the benchmark portfolio allows us to evaluate appropriate required rates of return as a function of investor risk preferences and the underlying distribution of market returns. This simple framework produces a number of distinct predictions about the cost of capital for alternatives relative to traditional mean-variance analysis.
FPGA-based Electronics for Confocal Line-Scanners with Linear Detector Arrays

Linear detector arrays are conveniently driven by FPGA-based electronics and enable simple line-scanning confocal microscope configurations. Their responsivity and signal-to-noise ratio for reflectance line-scanning is comparable to that of standard APD detectors for point-scanning.
Newer Antibiotics for the Surgeon

It is an honor for me to have been asked by Dr. Ronald Elkins and the Program Committee to deliver the 21st Annual Thomas G. Orr Memorial Lecture. Dr. Orr was born in 1834 and was an Alpha Omega Alpha graduate of Johns Hopkins University in 1910. Among his many ,accomplishments, he was a founding member of the American Board of Surgery, president of the Western Surgical Association, the second president of the Southwestern Surgical Congress, and president of the American Surgical Association. For 25 years, he was professor and chairman of the department of surgery at the University of Kansas, where he was also professor of bacteriology. As professor of bacteriology, I am sure that Dr. Orr would be amazed today to see the number and spectrum of newer antibiotics. A survey of 1 million hospital admissions to 338 hospitals determined that 42 percent were surgical admissions; however, these patients accounted far 71 percent of nosocomial infections [I]. The annual cost of nosocomial infections exceeds 1.5 billion dollars [2]. Preoperative antibiotics are usually administered to patients undergoing elective operations after arrival in the operating room. Animal studies demonstrate that wound infections are related to the time from contamination of a wound or incision until the administration of an antibiotic. The longer the delay from contamination until antibiotic administration, the greater the inflammatory response [3]. Several factors must be considered when comparing newer antibiotics, including pharmacologic properties, cost, in vitro activity, toxicity, and clinical efficacy. The longer the half-life, the less frequent the dosing. Less frequent administration means decreased cost due to less nursing and pharmacy time required to mix and administer the antibiotic, using fewer intravenous infusions. A true
Epidermal growth factor receptor restoration rescues the fatty liver regeneration in mice.

Hepatic steatosis is a common histological finding in obese patients. Even mild steatosis is associated with delayed hepatic regeneration and poor outcomes following liver resection or transplantat...
Distributional impact analysis: toolkit and illustrations of impacts beyond the average treatment effect

Program evaluations often focus on average treatment effects. However, average treatment effects miss important aspects of policy evaluation, such as the impact on inequality and whether treatment harms some individuals. A growing literature develops methods to evaluate such issues by examining the distributional impacts of programs and policies. This toolkit reviews methods to do so, focusing on their application to randomized control trials. The paper emphasizes two strands of the literature: estimation of impacts on outcome distributions and estimation of the distribution of treatment impacts. The article then discusses extensions to conditional treatment effect heterogeneity, that is, to analyses of how treatment impacts vary with observed characteristics. The paper offers advice on inference, testing, and power calculations, which are important when implementing distributional analyses in practice. Finally, the paper illustrates select methods using data from two randomized evaluations.
Assessment of Proteinuria Using Random Urine Samples

To determine the feasibility of accurately assessing proteinuria using random urine samples, 24-hour urine samples were obtained from five healthy adult volunteers and 15 children (ages 5 to 17 years) with renal disease. Protein concentration was measured using a Coomassie blue binding technique, and total protein excretion was compared with the urinary protein/creatinine ratio (U P /U Cr ). Total protein excretion varied from 28.3 mg to 12.3 gm, or 15.4 to 8500 mg/m 2 /day, and U P /U Cr ranged from 27.9 to 7650 μg/mg in the 24-hour samples; the correlation was highly significant (r=0.99; P P /U Cr were established by examining random urine samples in 219 healthy individuals (ages 1 month to 61 years). Age-related differences in protein concentration were noted, and 95th percentiles were calculated as the upper limit of normal. The results of our study indicate that U P /U Cr is an accurate assessment of quantitative protein excretion and could largely replace the collection of timed urine samples for the assessment of proteinuria.
Tampon-Related Toxic Shock Syndrome. Histopathologic and Clinical Findings in a Fatal Case

Toxic-shock syndrome (TSS) is consistently associated with penicillin-resistant Staphylococcus aureus in the vagina of menstruating women who use tampons. Increasing evidence implicates Staphylococcal toxin(s) in the pathogenesis of the condition, but the nature and biological effects of such toxin(s) are not established. Comprehensive postmortem studies and histopathologic data are few and largely unknown. The autopsy of a 15-year-old girl with this syndrome showed extensive superficial ulcerations and thrombophlebitis of the vagina, with bacteria on the mucosal surface only. Systemic phlebitis and capillaritis, visceral interstitial edema and acute inflammation involving various organs suggest a toxic effect, which is primarily manifested by widespread vascular damage. The histogenesis of the vaginal ulcerations remains unclarified, although they probably contribute to the absorption of toxin(s).
Omphalocele, Cryptorchidism, and Brain Malformations

Nineteen male infants died with a large omphalocele and 52% had associated cryptorchidism. However, two different groups with both omphalocele and cryptorchidism were recognized: (1) Eleven patients with omphalocele without brain malformation and an incidence of undescended testes not significantly different from the normal population; (2) Eight patients with omphalocele and brain malformation all having cryptorchidism. A comparison of the groups indicated that intact intraabdominal pressure during intrauterine life is not a main driving force of testicular descent, whereas normal testicular descent may occur only when the brain is normally developed. Whenever a child with omphalocele and cryptorchidism is examined, careful evaluation of the central nervous system is indicated. This triad of malformations may have prognostic and therapeutic implications.
Treatment of Bilateral Wilms’ Tumors—a 22-yr Experience

A total of 157 children with Wilms' tumors weretreated at The Children's Memorial Hospital during the years 1956–1978. Fourteen (or 9%) of these children had bilateral lesions. During the early years, treatment consisted of surgical excision of one kidney with radiation to the second tumor. During the second decade of this study a more aggressive approach to bilateral tumors was used consisting of nephrectomy on the side of the large tumor, with a heminephrectomy on the contralateral side and chemotherapy. More recently, we have attempted bilateral heminephrectomy when possible, together with increasingly aggressive chemotherapy. This series of patients allows us to compare the results of various treatment modalities among our own patients as well as those reported from other pediatric surgical centers.
An analytical solubility model for nitrogen–methane–ethane ternary mixtures

Abstract Saturn's moon Titan has surface liquids of liquid hydrocarbons and a thick, cold, nitrogen atmosphere, and is a target for future exploration. Critical to the design and operation of vehicles for this environment is knowledge of the amount of dissolved nitrogen gas within the cryogenic liquid methane and ethane seas. This paper rigorously reviews experimental data on the vapor-liquid equilibrium of nitrogen/methane/ethane mixtures, noting the possibility for split liquid phases, and presents simple analytical models for conveniently predicting solubility of nitrogen in pure liquid ethane, pure liquid methane, and a mixture of liquid ethane and methane. Model coefficients are fit to three temperature ranges near the critical point, intermediate range, and near the freezing point to permit accurate predictions across the full range of thermodynamic conditions. The models are validated against the consolidated database of 2356 experimental data points, with mean absolute error between data and model less than 8% for both binary nitrogen/methane and nitrogen/ethane systems, and less than 17% for the ternary nitrogen/methane/ethane system. The model can be used to predict the mole fractions of ethane, methane, and nitrogen as a function of location within the Titan seas.
Uncompensated Care and the Collapse of Hospital Payment Regulation: An Illustration of the Tinbergen Rule

The primary objective of “all-payer” rate setting—regulatory regimes through which states set hospital payment rates for all insurers—was to control costs through consistent, centrally regulated pa...
Field patterns: A new type of wave with infinitely degenerate band structure

Field pattern materials (FP-materials) are space-time composites with PT-symmetry in which the one-dimensional-spatial distribution of the constituents changes in time in such a special manner to give rise to a new type of waves, which we call field pattern waves (FP-waves) (Milton G. W. and Mattei O., Proc. R. Soc. A , 473 (2017) 20160819; Mattei O. and Milton G. W., New J. Phys. , 19 (2017) 093022). Specifically, due to the special periodic space-time geometry of these materials, when an instantaneous disturbance propagates through the system, the branching of the characteristic lines at the space-time interfaces between phases does not lead to a chaotic cascade of disturbances but concentrates on an orderly pattern of disturbances: this is the field pattern. In this letter, by applying Bloch-Floquet theory, we show that the dispersion diagrams associated with these FP-materials are infinitely degenerate: associated with each point on the dispersion diagram is an infinite space of Bloch functions. Each generalized function is concentrated on a specific field pattern, each parameterized by a variable that we call the launch parameter. The dynamics separates into independent dynamics on the different field patterns, each with the same dispersion relation.
Gene network analysis identifies a central post-transcriptional regulator of cellular stress survival

Cells adapt to shifts in their environment by remodeling transcription. Measuring changes in transcription at the genome scale is now routine, but defining the functional significance of individual genes within large gene expression datasets remains a major challenge. We applied a network-based algorithm to interrogate publicly available gene expression data to predict genes that serve major functional roles in Caulobacter crescentus stress survival. This approach identified GsrN, a conserved small RNA that is directly activated by the general stress sigma factor, σT, and functions as a potent post-transcriptional regulator of survival across distinct conditions including osmotic and oxidative stress. Under hydrogen peroxide stress, GsrN protects cells by base pairing with the leader of katG mRNA and activating expression of KatG catalase/peroxidase protein. We conclude that GsrN convenes a post-transcriptional layer of gene expression that serves a central functional role in Caulobacter stress physiology.
Disentangling the Roles of Institutional and Individual Poverty in the Identification of Gifted Students

Although the relationships between family income and student identification for gifted programming are well documented, less is known about how school and district wealth are related to student identification. To examine the effects of institutional and individual poverty on student identification, we conducted a series of three-level regression models. Students of poverty are generally less likely to be identified for gifted services, even after controlling for prior math and reading achievement. Furthermore, school poverty predicts the percentage of gifted students identified in a school. Within districts, even after controlling for reading and math scores, the poorer schools in a district have lower identification rates. Whereas students of poverty are generally less likely to be identified for gifted services, poor students in poor schools are even less likely to be identified as gifted.
Geography, community, household: Adoption of distributed solar power across India

Abstract We investigate the determinants of distributed solar technology adoption at the village and household level in India. Using spatial data on insolation, census records, and original surveys, we show that remote and poor but large villages with abundant sunshine have led the wave of solar technology adoption as an alternative to grid electricity. At the household level, however, wealth and financial access are positively associated with solar technology adoption, a result that holds for both solar lanterns and home systems. Moreover, remote villages are more likely to see solar technology adoption when households have access to finance through banks. We also find that the use of household solar technology is strongly associated with a household's subjective satisfaction with domestic lighting. These results demonstrate that understanding solar technology adoption requires considering both community and household characteristics. They also underscore the importance of financial access as a precondition for using distributed solar power as an alternative to grid connectivity.
Grain boundary complexions and the strength of nanocrystalline metals: Dislocation emission and propagation

Abstract Grain boundary complexions have been observed to affect the mechanical behavior of nanocrystalline metals, improving both strength and ductility. While an explanation for the improved ductility exists, the observed effect on strength remains unexplained. In this work, we use atomistic simulations to explore the influence of ordered and disordered complexions on two deformation mechanisms which are essential for nanocrystalline plasticity, namely dislocation emission and propagation. Both ordered and disordered grain boundary complexions in Cu-Zr are characterized by excess free volume and promote dislocation emission by reducing the critical emission stress. Alternatively, these complexions are characterized by strong dislocation pinning regions that increase the flow stress required for dislocation propagation. Such pinning regions are caused by ledges and solute atoms at the grain-complexion interfaces and may be dependent on the complexion state as well as the atomic size mismatch between the matrix and solute elements. The trends observed in our simulations of dislocation propagation align with the available experimental data, suggesting that dislocation propagation is the rate-limiting mechanism behind plasticity in nanocrystalline Cu-Zr alloys.
Multi-camera volumetric PIV for the study of jumping fish

Archer fish accurately jump multiple body lengths for aerial prey from directly below the free surface. Multiple fins provide combinations of propulsion and stabilization, enabling prey capture success. Volumetric flow field measurements are crucial to characterizing multi-propulsor interactions during this highly three-dimensional maneuver; however, the fish’s behavior also drives unique experimental constraints. Measurements must be obtained in close proximity to the water’s surface and in regions of the flow field which are partially-occluded by the fish body. Aerial jump trajectories must also be known to assess performance. This article describes experiment setup and processing modifications to the three-dimensional synthetic aperture particle image velocimetry (SAPIV) technique to address these challenges and facilitate experimental measurements on live jumping fish. The performance of traditional SAPIV algorithms in partially-occluded regions is characterized, and an improved non-iterative reconstruction routine for SAPIV around bodies is introduced. This reconstruction procedure is combined with three-dimensional imaging on both sides of the free surface to reveal the fish’s three-dimensional wake, including a series of propulsive vortex rings generated by the tail. In addition, wake measurements from the anal and dorsal fins indicate their stabilizing and thrust-producing contributions as the archer fish jumps.
Opening the Black Box of Outer Space: The Case of Jason-3

If we look at a rendering of planet Earth from a bird’s eye view, we see a very familiar sight - satellites orbiting the planet like electrons, each one a testament to humanity’s expansion beyond E...
WTO tariff commitments and temporary protection: Complements or substitutes?

Abstract There is a long-held notion in the trade policy literature that traditional tariff instruments and temporary protection (TP) measures are substitutes. Despite this prediction, there is only mixed empirical evidence for a link between tariff reductions and the usage pattern of antidumping, safeguard and countervailing duties. Based on recent theoretical advances, I argue in this paper that the relevant trade policy margin for implementing TP measures is instead tariff overhangs, the difference between WTO bound and applied tariffs. Lower tariff overhangs constrain countries to raise their MFN applied rates without legal repercussions, independent of past tariff changes. Using detailed sectoral data for a sample of 30 WTO member countries during the period 1996–2014, I find strong evidence for an inverse link between tariff overhangs and TP activity. This result implies that tariff overhangs and TP measures are substitutes, vindicating the importance of existing tariff commitments as a key determinant of alternative protection instruments.
Experience With Intrauterine Device Insertion in Never Sexually Active Adolescents: A Retrospective Cohort Study

Background Intrauterine devices can offer both contraceptive and noncontraceptive benefits to never sexually active adolescents. There are increasing data on intrauterine device use in adolescents; however, most data on intrauterine devices in adolescents are related to contraceptive use. There is very limited literature on intrauterine device placement in adolescents who have never been sexually active. Objective The objective of the study was to compare intrauterine device insertion success between never sexually active and sexually active cohorts. Study Design We performed a retrospective chart review of patients aged 10–20 years with attempted intrauterine device insertion at a children’s hospital between October 2015 and September 2017. Results A total of 210 patients were included, of whom 82 were never sexually active. Never sexually active adolescents were younger at insertion (15.6 vs 16.7 years, P Conclusion To our knowledge, this is the first study describing intrauterine device insertion in never sexually active patients. Although office success rates were lower, intrauterine device insertion in never sexually active adolescents was very successful overall, and intrauterine devices should be offered to this population.
Cruising and on-street parking pricing: A difference-in-difference analysis of measured parking search time and distance in San Francisco

Abstract When on-street parking is scarce, the cost of parking includes the extra time and fuel spent searching for a parking space (or cruising). Cruising also unnecessarily contributes to local congestion, vehicle emissions, air pollution, and climate change. The theoretical literature shows that these social costs can be reduced, or even eliminated, if high-quality information on the demand for and supply of parking is used to set parking prices at optimal levels. Not surprisingly, cities plagued by parking shortages, congested streets, and limited financial resources are interested in parking policies that reduce cruising and improve the efficient use of their existing parking and roadway infrastructure. The current study sheds light on the effect of the San Francisco parking pricing program (known as SFpark) on curbside parking search time and distance in urban neighborhoods on non-commuter parking. The study differs from previous empirical evaluations of similar parking pricing programs in its use of direct field measurements of parking search time and distance, rather than simulated data or proxy variables, such as parking availability. We use generalized mixed effect difference-in-difference models with data collected before and after the implementation of SFpark in both treatment and control areas to estimates effects of the San Francisco smart parking project, most importantly the demand responsive parking pricing scheme. The models control for time effects by using data from a separate control area, as opposed to using variables such as block face parking price and employment. The results suggest a significant reduction in average parking search time and distance due to SFpark. Average parking search time and distance declines by approximately 15% and 12%, respectively, from the control to the treatment areas.
Empowering cities : good for growth? - Evidence from the People’s Republic of China

This paper utilizes a countrywide process of county-to-city upgrading in the 1990s to identify whether extending the powers of urban local governments leads to better firm outcomes. The paper hypot...
Round- and Message-Optimal Distributed Graph Algorithms

Distributed graph algorithms that separately optimize for either the number of rounds used or the total number of messages sent have been studied extensively. However, algorithms simultaneously efficient with respect to both measures have been elusive. For example, only very recently was it shown that for Minimum Spanning Tree (MST), an optimal message and round complexity is achievable (up to polylog terms) by a single algorithm in the CONGEST model of communication. In this paper we provide algorithms that are simultaneously round- and message-optimal for a number of well-studied distributed optimization problems. Our main result is such a distributed algorithm for the fundamental primitive of computing simple functions over each part of a graph partition. From this algorithm we derive round- and message-optimal algorithms for multiple problems, including MST, Approximate Min-Cut and Approximate Single Source Shortest Paths, among others. On general graphs all of our algorithms achieve worst-case optimal O (D+√ n) round complexity and O (m) message complexity. Furthermore, our algorithms require an optimal O (D) rounds and O (n) messages on planar, genus-bounded, treewidth-bounded and pathwidth-bounded graphs.
Factors influencing hospital readmission penalties: Are they really under hospitals' control?

Abstract The Hospital Readmissions Reduction Program (HRRP) established by the Centers for Medicare & Medicaid Services (CMS) penalizes hospitals that have excessive readmission rates. Research is needed to determine if there are factors that influence readmission penalties but may be out of the control of hospitals. In this study, we compare a set of geo-demographic, hospital, and quality of care characteristics of hospitals penalized by HRRP with those not penalized, and determine these characteristics' association with the likelihood of penalization as well as the extent of penalties. We collected and integrated data from multiple sources such as the HRRP Supplemental Data File, the Hospital Compare database, CMS Impact files, the HCAHPS survey, and the U.S. census. We followed a two-step estimation procedure. First, we estimated a logistic regression model to find the relationship between various characteristics and whether a hospital was penalized. Second, we estimated a linear regression model to find the relationship between these characteristics and the extent of penalties. Results show that both the likelihood and the extent of penalties varied across several characteristics related to geo-demographics (such as location in the census division, urban vs. rural location, and racial make-up of the area), hospitals (such as ownership, bed capacity, teaching status, and case mix index), and quality of care (such as quality of communication by doctors and information provided at the time of discharge). Although quality of care characteristics are under hospitals' control and can be improved, geo-demographic and hospital characteristics are likely consistent over time and largely out of the control of hospitals. The study supports the case for a comprehensive revision of HRRP's scoring methodology to calculate readmission penalties.
Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms

We consider a class of popular distributed non-convex optimization problems, in which agents connected by a network $\mathcal {G}$ collectively optimize a sum of smooth (possibly non-convex) local objective functions. We address the following question: if the agents can only access the gradients of local functions, what are the fastest rates that any distributed algorithms can achieve, and how to achieve those rates. First, we show that there exist difficult problem instances, such that it takes a class of distributed first-order methods at least $\mathcal {O}(1/\sqrt{\xi ({ \mathcal {G} })} \times \bar{L} /{\epsilon })$ communication rounds to achieve certain $\epsilon$ -solution [where $\xi ({ \mathcal {G} })$ denotes the spectral gap of the graph Laplacian matrix, and $\bar{L}$ is some Lipschitz constant]. Second, we propose (near) optimal methods whose rates match the developed lower rate bound (up to a ploylog factor). The key in the algorithm design is to properly embed the classical polynomial filtering techniques into modern first-order algorithms. To the best of our knowledge, this is the first time that lower rate bounds and optimal methods have been developed for distributed non-convex optimization problems.
SaaS: Speed as a Supervisor for Semi-supervised Learning

We introduce the SaaS Algorithm for semi-supervised learning, which uses learning speed during stochastic gradient descent in a deep neural network to measure the quality of an iterative estimate of the posterior probability of unknown labels. Training speed in supervised learning correlates strongly with the percentage of correct labels, so we use it as an inference criterion for the unknown labels, without attempting to infer the model parameters at first. Despite its simplicity, SaaS achieves competitive results in semi-supervised learning benchmarks.