cssi/SciSciGPT-SciSciNet huggingface dataset:
On the Key Exposure Problem in Chameleon Hashes.

Chameleon signatures were introduced by Krawczyk and Rabin, being non-interactive signature schemes that provide non-transferability. However, that first construction employs a chameleon hash that suffers from a key exposure problem: The non-transferability property requires willingness of the recipient in consequentially exposing a secret key, and therefore invalidating all signatures issued to the same recipient’s public key. To address this key-revocation issue, and its attending problems of key redistribution, storage of state information, and greater need for interaction, an identity-based scheme was proposed in [1], while a fully key-exposure free construction, based on the elliptic curves with pairings, appeared later in [7]. Herein we provide several constructions of exposure-free chameleon hash functions based on different cryptographic assumptions, such as the RSA and the discrete logarithm assumptions. One of the schemes is a novel construction that relies on a single trapdoor and therefore may potentially be realized over a large set of cryptographic groups (where the discrete logarithm is hard).
On self-adjoint boundary conditions for singular Sturm–Liouville operators bounded from below

Abstract We extend the classical boundary values (0.1) g ( a ) = − W ( u a ( λ 0 , ⋅ ) , g ) ( a ) = lim x ↓ a ⁡ g ( x ) u ˆ a ( λ 0 , x ) , g [ 1 ] ( a ) = ( p g ′ ) ( a ) = W ( u ˆ a ( λ 0 , ⋅ ) , g ) ( a ) = lim x ↓ a ⁡ g ( x ) − g ( a ) u ˆ a ( λ 0 , x ) u a ( λ 0 , x ) , for regular Sturm–Liouville operators associated with differential expressions of the type τ = r ( x ) − 1 [ − ( d / d x ) p ( x ) ( d / d x ) + q ( x ) ] for a.e. x ∈ ( a , b ) ⊂ R , to the case where τ is singular on ( a , b ) ⊆ R and the associated minimal operator T m i n is bounded from below. Here u a ( λ 0 , ⋅ ) and u ˆ a ( λ 0 , ⋅ ) denote suitably normalized principal and nonprincipal solutions of τ u = λ 0 u for appropriate λ 0 ∈ R , respectively. Our approach to deriving the analog of (0.1) in the singular context employing principal and nonprincipal solutions of τ u = λ 0 u is closely related to a seminal 1992 paper by Niessen and Zettl [58] . We also recall the well-known fact that the analog of the boundary values in (0.1) characterizes all self-adjoint extensions of T m i n in the singular case in a manner familiar from the regular case. We briefly discuss the singular Weyl–Titchmarsh–Kodaira m-function and finally illustrate the theory in some detail with the examples of the Bessel, Legendre, and Kummer (resp., Laguerre) operators.
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy

The evolution of a deep neural network trained by the gradient descent can be described by its neural tangent kernel (NTK) as introduced in [20], where it was proven that in the infinite width limit the NTK converges to an explicit limiting kernel and it stays constant during training. The NTK was also implicit in some other recent papers [6,13,14]. In the overparametrization regime, a fully-trained deep neural network is indeed equivalent to the kernel regression predictor using the limiting NTK. And the gradient descent achieves zero training loss for a deep overparameterized neural network. However, it was observed in [5] that there is a performance gap between the kernel regression using the limiting NTK and the deep neural networks. This performance gap is likely to originate from the change of the NTK along training due to the finite width effect. The change of the NTK along the training is central to describe the generalization features of deep neural networks. In the current paper, we study the dynamic of the NTK for finite width deep fully-connected neural networks. We derive an infinite hierarchy of ordinary differential equations, the neural tangent hierarchy (NTH) which captures the gradient descent dynamic of the deep neural network. Moreover, under certain conditions on the neural network width and the data set dimension, we prove that the truncated hierarchy of NTH approximates the dynamic of the NTK up to arbitrary precision. This description makes it possible to directly study the change of the NTK for deep neural networks, and sheds light on the observation that deep neural networks outperform kernel regressions using the corresponding limiting NTK.
Volatility markets underreacted to the early stages of the COVID-19 pandemic

VIX futures prices rose slowly in late February and early March 2020 as the COVID-19 pandemic took hold Futures price premiums, defined as futures prices minus real-time statistical forecasts of future VIX values, turned sharply negative and remained negative until mid-April Trading strategies based on estimated premiums profited from the subsequent increase in market volatility and equity market crash The underreaction of futures prices to growing pandemic risks poses a puzzle for standard asset pricing models Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online © 2020 The Author(s) Published by Oxford University Press on behalf of The Society for Financial Studies All rights reserved
Agricultural productivity and deforestation: Evidence from input subsidies and ethnic favoritism in Malawi

Abstract This paper studies the underlying relationship between agricultural productivity and deforestation by analyzing the impacts of a large fertilizer and seed subsidy program in Malawi. In the absence of well-defined subsidy eligibility criteria, we demonstrate that areas with a high proportion of individuals of the same ethnicity as the president received more subsidized fertilizer and deforested less compared to areas with other predominant ethnicities. We provide evidence that subsidized fertilizer increased yields and reduced pressure to expand agriculture and that the findings are not confounded by increases in public sector employment or other public assistance programs. The results suggest that policies aimed at increasing small-scale agricultural productivity may have positive environmental spillovers.
A causal exposure response function with local adjustment for confounding: Estimating health effects of exposure to low levels of ambient fine particulate matter.

In the last two decades ambient levels of air pollution have declined substantially. At the same time the Clean Air Act mandates that the National Ambient Air Quality Standards (NAAQS) must be routinely assessed to protect populations based on the latest science. Therefore, researchers should continue to address the following question: is exposure to levels of air pollution below the NAAQS harmful to human health? Furthermore, the contentious nature surrounding environmental regulations urges us to cast this question within a causal inference framework. Several parametric and semiparametric regression approaches have been used to estimate the exposure-response (ER) curve between long-term exposure to ambient air pollution concentrations and health outcomes. However, most of the existing approaches are not formulated within a formal framework for causal inference, adjust for the same set of potential confounders across all levels of exposure and do not account for model uncertainty regarding covariate selection and the shape of the ER. In this paper we introduce a Bayesian framework for the estimation of a causal ER curve called LERCA (Local Exposure Response Confounding Adjustment), which: (a) allows for different confounders and different strength of confounding at the different exposure levels, and (b) propagates model uncertainty regarding confounders’ selection and the shape of the ER. Importantly, LERCA provides a principled way of assessing the observed covariates’ confounding importance at different exposure levels, providing researchers with important information regarding the set of variables to measure and adjust for in regression models. Using simulation studies, we show that state-of-the-art approaches perform poorly in estimating the ER curve in the presence of local confounding. LERCA is used to evaluate the relationship between long-term exposure to ambient PM$_{2.5}$, a key regulated pollutant, and cardiovascular hospitalizations for 5,362 zip codes in the continental U.S. and located near a pollution monitoring site, while adjusting for a potentially varying set of confounders across the exposure range. Our data set includes rich health, weather, demographic and pollution information for the years of 2011–2013. The estimated exposure-response curve is increasingly indicating that higher ambient concentrations lead to higher cardiovascular hospitalization rates, and ambient PM$_{2.5}$ was estimated to lead to an increase in cardiovascular hospitalization rates when focusing at the low-exposure range. Our results indicate that there is no threshold for the effect of PM$_{2.5}$ on cardiovascular hospitalizations.
Self-Training for Unsupervised Parsing with PRPN.

Neural unsupervised parsing (UP) models learn to parse without access to syntactic annotations, while being optimized for another task like language modeling. In this work, we propose self-training for neural UP models: we leverage aggregated annotations predicted by copies of our model as supervision for future copies. To be able to use our model’s predictions during training, we extend a recent neural UP architecture, the PRPN (Shen et al., 2018a), such that it can be trained in a semi-supervised fashion. We then add examples with parses predicted by our model to our unlabeled UP training data. Our self-trained model outperforms the PRPN by 8.1% F1 and the previous state of the art by 1.6% F1. In addition, we show that our architecture can also be helpful for semi-supervised parsing in ultra-low-resource settings.
Development of fluorescence polarization-based competition assay for nicotinamide N-methyltransferase.

Abstract Methylation-mediated pathways play important roles in the progression of various diseases. Thus, targeting methyltransferases has proven to be a promising strategy for developing novel therapies. Nicotinamide N-methyltransferase (NNMT) is a major metabolic enzyme involved in epigenetic regulation through catalysis of methyl transfer from the cofactor S-adenosyl- l -methionine onto nicotinamide and other pyridines. Accumulating evidence infers that NNMT is a novel therapeutic target for a variety of diseases such as cancer, diabetes, obesity, cardiovascular and neurodegenerative diseases. Therefore, there is an urgent need to discover potent and specific inhibitors for NNMT to assess its therapeutical potential. Herein, we reported the design and synthesis of a fluorescent probe II138, exhibiting a Kd value of 369 ± 14 nM for NNMT. We also established a fluorescence polarization (FP)-based competition assay for evaluation of NNMT inhibitors. Importantly, the unique feature of this FP competition assay is its capability to identify inhibitors that interfere with the interaction of the NNMT active site directly or allosterically. In addition, this assay performance is robust with a Z'factor of 0.76, indicating its applicability in high-throughput screening for NNMT inhibitors.
Self-learning how to swim at low Reynolds number

Machine learning is integrated into low-Reynolds-number locomotion to enable a class of self-learning, adaptive (smart), micro-swimmers. Instead of specifying locomotory gaits in advance, a self-learning swimmer develops and adapts its propulsion strategy based on interactions with the surroundings via reinforcement learning. Without requiring prior knowledge, the swimmer can recover previously known propulsion strategies, and improve and adapt in different media. This development can enable the design of smart micro-robots with robust locomotive capabilities in complex environments
Anomaly Detection Under Controlled Sensing Using Actor-Critic Reinforcement Learning

We consider the problem of detecting anomalies among a given set of processes using their noisy binary sensor measurements. The noiseless sensor measurement corresponding to a normal process is 0, and the measurement is 1 if the process is anomalous. The decision-making algorithm is assumed to have no knowledge of the number of anomalous processes. The algorithm is allowed to choose a subset of the sensors at each time instant until the confidence level on the decision exceeds the desired value. Our objective is to design a sequential sensor selection policy that dynamically determines which processes to observe at each time and when to terminate the detection algorithm. The selection policy is designed such that the anomalous processes are detected with the desired confidence level while incurring minimum cost which comprises the delay in detection and the cost of sensing. We cast this problem as a sequential hypothesis testing problem within the framework of Markov decision processes, and solve it using the actor-critic deep reinforcement learning algorithm. This deep neural network-based algorithm offers a low complexity solution with good detection accuracy. We also study the effect of statistical dependence between the processes on the algorithm performance. Through numerical experiments, we show that our algorithm is able to adapt to any unknown statistical dependence pattern of the processes.
Being watched in an investment game setting: Behavioral changes when making risky decisions

Abstract We design a laboratory experiment to test for behavioral differences due to observation within a novel arena: investment games. We find that fund managers are more risk-averse when investors can observe their investment allocations. This effect is more pronounced when investors, in addition to observing the allocations, can also observe the investment outcomes. Interestingly, allowing investors to observe how their investment is allocated does not impact how much they invest. Last, when the outcome of the risky investment is public knowledge, disclosing managers’ allocations leads them to return more tokens to investors and to expropriate fewer tokens for themselves at the end of the game, ceteris paribus. We discuss potential causes of these effects.
Complementarities as an antitrust defense

We employ a Cournot model with interdependent demands to explore the interaction between demand and cost complementarities in mitigating upward pricing pressure, post-merger. The analysis reveals t...
What determines school segregation? The crucial role of neighborhood factors

Abstract We develop a novel strategy to identify the relative importance of school and neighborhood factors in determining school segregation. Using detailed student enrollment and residential location data, our research design compares differences in student composition between adjacent Census blocks served by different schools to analogous differences between those schools. Our findings indicate that neighborhood factors explain around 62% of racial segregation and 44% of economic segregation across all schools, playing an even more pronounced role in urban areas, where school segregation has been especially acute. These findings suggest that the involvement of urban planners is essential when attempting to confront inequality of opportunity through education.
Sustained attention and vigilance deficits associated with HIV and a history of methamphetamine dependence.

Abstract Background Human immunodeficiency virus (HIV)-associated neurocognitive disorders persist in the era of antiretroviral therapy. One factor that is elevated among persons with HIV (PWH) and independently associated with neurocognitive impairment is methamphetamine dependence (METH). Such dependence may further increase cognitive impairment among PWH, by delaying HIV diagnosis (and thus, antiretroviral therapy initiation), which has been posited to account for persistent cognitive impairment among PWH, despite subsequent treatment-related viral load suppression (VLS; 50 copies of the virus per milliliter in plasma or cerebrospinal fluid). This study examined the main and interactive (additive versus synergistic) effects of HIV and history of METH on the sustained attention and vigilance cognitive domain, while controlling for VLS. Methods Participants included 205 (median age = 44 years; 77% males; HIV-/METH- n = 67; HIV+/METH - n = 49; HIV-/METH+ n = 36; HIV+/METH+ n = 53) individuals enrolled in the Translational Methamphetamine AIDS Research Center, who completed Conners’ and the 5-Choice continuous performance tests (CPTs). Results METH participants exhibited deficits in sustained attention and vigilance; however, these effects were not significant after excluding participants who had a positive urine toxicology screen for methamphetamine. Controlling for VLS, PWH did not have worse sustained attention and vigilance, but consistently displayed slower reaction times across blocks, relative to HIV- participants. There was no HIV x METH interaction on sustained attention and vigilance. Conclusions Recent methamphetamine use among METH people and detectable viral loads are detrimental to sustained attention and vigilance. These findings highlight the need for prompt diagnosis of HIV and initiation of antiretroviral therapy, and METH use interventions.
Recipes for Structural Fairness in Games

Background. Although fairness is central to society and to games that are taken seriously, the structural aspect of fairness has not been addressed as a problem of games.Aim. To resolve the problem...
A Simpler Strong Refutation of Random k-XOR.

Strong refutation of random CSPs is a fundamental question in theoretical computer science that has received particular attention due to the long-standing gap between the information-theoretic limit and the computational limit. This gap is recently bridged by Raghavendra, Rao and Schramm where they study sub-exponential algorithms for the regime between the two limits. In this work, we take a simpler approach to their algorithm and analysis.
On transfer learning of neural networks using bi-fidelity data for uncertainty propagation

Due to their high degree of expressiveness, neural networks have recently been used as surrogate models for mapping inputs of an engineering system to outputs of interest. Once trained, neural networks are computationally inexpensive to evaluate and remove the need for repeated evaluations of computationally expensive models in uncertainty quantification applications. However, given the highly parameterized construction of neural networks, especially deep neural networks, accurate training often requires large amounts of simulation data that may not be available in the case of computationally expensive systems. In this paper, to alleviate this issue for uncertainty propagation, we explore the application of transfer learning techniques using training data generated from both high- and low-fidelity models. We explore two strategies for coupling these two datasets during the training procedure, namely, the standard transfer learning and the bi-fidelity weighted learning. In the former approach, a neural network model mapping the inputs to the outputs of interest is trained based on the low-fidelity data. The high-fidelity data is then used to adapt the parameters of the upper layer(s) of the low-fidelity network, or train a simpler neural network to map the output of the low-fidelity network to that of the high-fidelity model. In the latter approach, the entire low-fidelity network parameters are updated using data generated via a Gaussian process model trained with a small high-fidelity dataset. The parameter updates are performed via a variant of stochastic gradient descent with learning rates given by the Gaussian process model. Using three numerical examples, we illustrate the utility of these bi-fidelity transfer learning methods where we focus on accuracy improvement achieved by transfer learning over standard training approaches.
Logarithmic Equilibrium on the Sphere in the Presence of Multiple Point Charges

With the sphere $$\mathbb {S}^2 \subset \mathbb {R}^3$$ as a conductor holding a unit charge with logarithmic interactions, we consider the problem of determining the support of the equilibrium measure in the presence of an external field consisting of finitely many point charges on the surface of the sphere. We determine that for any such configuration, the complement of the equilibrium support is the stereographic preimage from the plane of a union of classical quadrature domains, whose orders sum to the number of point charges.
Managing internationalization and innovation tradeoffs in entrepreneurial firms: Evidence from transition economies

Abstract For entrepreneurial firms (EFs), internationalization and innovation present two major avenues for growth. Prior research, based primarily on EFs from advanced economies, demonstrates mixed insights for the relationship between these strategies. A deeper understanding of the tradeoffs involved in the internationalization-innovation relationship may help better comprehend the issue. In this study, we draw on the organizational learning and capabilities-based literatures to examine the relationship in the context of EFs in transition economies (EFTEs). Our findings suggest that in EFTEs, internationalization is negatively associated with the likelihood of innovation. We also find that three knowledge-based capabilities of EFTEs (absorptive capacity, appropriation capability, and managerial capability) positively moderate the aforementioned negative relationship. We do not find any evidence of reverse causality (EFTE innovation impacting internationalization). Our research provides novel insights to the IE literature by shedding light on the internationalization–innovation tradeoffs that EFTEs experience.
Invariant theory for coincidental complex reflection groups

V.F. Molchanov considered the Hilbert series for the space of invariant skew-symmetric tensors and dual tensors with polynomial coefficients under the action of a real reflection group, and he speculated that it had a certain product formula involving the exponents of the group. We show that Molchanov’s speculation is false in general but holds for all coincidental complex reflection groups when appropriately modified using exponents and co-exponents. These are the irreducible well-generated (i.e., duality) reflection groups with exponents forming an arithmetic progression and include many real reflection groups and all non-real Shephard groups, e.g., the Shephard-Todd infinite family G(d, 1, n). We highlight consequences for the q-Narayana and q-Kirkman polynomials, giving simple product formulas for both, and give a q-analogue of the identity transforming the h-vector to the f-vector for the coincidental finite type cluster/Cambrian complexes of Fomin–Zelevinsky and Reading. We include the determination of the Hilbert series for the non-coincidental irreducible complex reflection groups as well.
Hecke Eigensystems for (mod p) Modular Forms of PEL Type and Algebraic Modular Forms

We show that, under suitable assumptions, the systems of Hecke eigenvalues arising from (mod p) modular forms of PEL-type associated to an algebraic group G of type A or C coincide with the Hecke eigensystems arising from (mod p) algebraic modular forms for an inner form of G. We treat explicitly the case of unitary groups, and we give in this case an asymptotic formula for the number of eigensystems. The paper generalizes results of J-P. Serre for GL(2) and A. Ghitza for GSp(2g).
Computational study of trimer self-assembly and fluid phase behavior

The fluid phase diagram of trimer particles composed of one central attractive bead and two repulsive beads was determined as a function of simple geometric parameters using flat-histogram Monte Carlo methods. A variety of self-assembled structures were obtained including spherical micelle-like clusters, elongated clusters, and densely packed cylinders, depending on both the state conditions and shape of the trimer. Advanced simulation techniques were employed to determine transitions between self-assembled structures and macroscopic phases using thermodynamic and structural definitions. Simple changes in particle geometry yield dramatic changes in phase behavior, ranging from macroscopic fluid phase separation to molecular-scale self-assembly. In special cases, both self-assembled, elongated clusters and bulk fluid phase separation occur simultaneously. Our work suggests that tuning particle shape and interactions can yield superstructures with controlled architecture.
Elementary derivations of identities for bilateral basic hypergeometric series

We give elementary derivations of several classical and some new summation and transformation formulae for bilateral basic hypergeometric series. For motivation, we review our previous simple proof (Proc. Amer. Math. Soc. 130 (2002), 1103-1111) of Bailey's very-well-poised $_6\psi_6$ summation. Using a similar but different method, we now give elementary derivations of some transformations for bilateral basic hypergeometric series. In particular, these include M. Jackson's very-well-poised $_8\psi_8$ transformation, a very-well-poised $_{10}\psi_{10}$ transformation, by induction, Slater's general transformation for very-well-poised $_{2r}\psi_{2r}$ series, and Slater's transformation for general $_{r}\psi_{r}$ series. Finally, we derive some new transformations for bilateral basic hypergeometric series of a specific type.
Models for Accretion-Disk Fluctuations through Self-Organized Criticality Including Relativistic Effects

The possibility that some of the observed X-ray and optical variability in active galactic nuclei and galactic black hole candidates is produced in accretion disks through the development of a self-organized critical state is reconsidered. New simulations, including more complete calculations of relativistic effects, do show that this model can produce light-curves and power-spectra for the variability which agree with the range observed in optical and X-ray studies of AGN and X-ray binaries. However, the universality of complete self-organized criticality is not quite achieved. This is mainly because the character of the variations depend quite substantially on the extent of the unstable disk region. If it extends close to the innermost stable orbit then a physical scale is introduced and the scale-free character of self-organized criticality is vitiated. Significant dependence of the power spectrum density slope on the type of diffusion within the disk and a weaker dependence on the amount of differential rotation are noted. When general relativistic effects are incorporated in the models, additional substantial differences are produced if the disk is viewed from directions far from the accretion disk axis.
PROBING PLANET FORMING ZONES WITH RARE CO ISOTOPOLOGUES

The properties of the midplane of planet-forming protostellar disks remain largely unprobed by observations due to the high optical depth of common molecular lines and the continuum. However, rotational emission lines from rare isotopologues may have optical depths near unity in the vertical direction, so that the lines are strong enough to be detected, yet remain transparent enough to trace the disk midplane. Here we present a chemical model of an evolving T-Tauri disk and predict the optical depths of rotational transitions of CO isotopologues. CO does not freeze out in our modeled region within 70AU around a sunlike star. However, the abundance of CO decreases because of the formation of complex organic molecules (COM), producing effect that can be misinterpreted as the “snow line”. The optical depths of low-order rotational lines of C17O are around unity, which suggests it may be possible to see into the disk midplane using C17O. With our computed CO/H2 abundance ratio, such ALMA observations would provide estimates of the gaseous disk masses by measuring the intensity of C17O emission.
On the Contribution of Gamma-Ray Bursts to the Galactic Inventory of Some Intermediate-Mass Nuclei

Light curves from a growing number of gamma-ray bursts (GRBs) indicate that GRBs copiously produce radioactive Ni moving outward at fractions of the speed of light. We calculate nuclear abundances of elements accompanying the outflowing Ni under the assumption that this Ni originates from a wind blown off of a viscous accretion disk. We also show that GRBs likely contribute appreciably to the Galactic inventory of 42Ca, 45Sc, 46Ti, 49Ti, and 63Cu, and may be an important site for the production of 64Zn.
Connecting high-redshift galaxy populations through observations of local Damped Lyman Alpha dwarf galaxies

I report on observations of the z=0.01 dwarf galaxy SBS1543+593 which is projected onto the background QSO HS1543+5921. As a star-forming galaxy first noted in emission, this dwarf is playing a pivotal role in our understanding of high-redshift galaxy populations, because it also gives rise to a Damped Lyman Alpha system. This enabled us to analyze, for the first time, the chemical abundance of $\alpha$ elements in a Damped Lyman Alpha galaxy using both, emission and absorption diagnostics. We find that the abundances agree with one another within the observational uncertainties. I discuss the implications of this result for the interpretation of high-redshift galaxy observations. A catalog of dwarf-galaxy--QSO projections culled from the Sloan Digital Sky Survey is provided to stimulate future work.
Imaging Universal Conductance Fluctuations in Graphene

We study conductance fluctuations (CF) and the sensitivity of the conductance to the motion of a single scatterer in two-dimensional massless Dirac systems. Our extensive numerical study finds limits to the predicted universal value of CF. We find that CF are suppressed for ballistic systems near the Dirac point and approach the universal value at sufficiently strong disorder. The conductance of massless Dirac fermions is sensitive to the motion of a single scatterer. CF of order e(2)/h result from the motion of a single impurity by a distance comparable to the Fermi wavelength. This result applies to graphene systems with a broad range of impurity strength and concentration while the dependence on the Fermi wavelength can be explored via gate voltages. Our prediction can be tested by comparing graphene samples with varying amounts of disorder and can be used to understand interference effects in mesoscopic graphene devices.
Mode-conversion of the extraordinary wave at the upper hybrid resonance in the presence of small-amplitude density fluctuations

In spherical tokamaks, the electron plasma frequency is greater than the electron cyclotron frequency. Electromagnetic waves in the electron cyclotron range of frequencies are unsuitable for directly heating such plasmas due to their reduced accessibility. However, mode-conversion of the extraordinary wave to the electron Bernstein wave (X-B mode-conversion) at the upper hybrid resonance makes it possible to efficiently couple externally-launched electromagnetic wave energy into an overdense plasma core. Traditional mode-conversion models describe an X-mode wave propagating in a potential containing two cutoffs that bracket a single wave resonance. Often, however, the mode-conversion region is in the edge, where turbulent fluctuations and blobs can generate abrupt cutoffs and scattering of the incident X-mode wave. We present a new framework for studying the X-B mode-conversion which makes the inclusion of these fluctuations analytically tractable. In the new approach, the high-field cutoff is modelled as an infinite barrier, which manifests as a boundary condition applied to a wave equation involving only one cutoff adjacent to the resonance on the low-field side. The new model reproduces the main features of the previous approach, yet is more suitable for analyzing experimental observations and extrapolating to higher dimensions. We then develop an analytical estimate for the effect of small-amplitude, quasi-monochromatic density fluctuations on the X-B mode-conversion efficiency using perturbation theory. We find that Bragg backscattering of the launched X-mode wave reduces the mode-conversion efficiency significantly when the fluctuation wavenumber is resonant with the wavenumber of the incident X-mode wave. These analytical results are corroborated by numerically integrating the mode-conversion equations.
SharpEdge: an asynchronous and core-agnostic solution to guarantee bounded-delays

What are the key properties that a network should have to provide bounded-delay guarantees for the packets? In this paper, we attempt to answer this question. To that end, we explore the theory of bounded-delay networks and provide the necessary and the sufficient conditions required to have deterministic bounded-delays in the network. We prove that as long as a network is work-conserving, independent of the packet scheduling and queue management algorithms used in the switches, it is sufficient to shape the traffic properly at the edge of the network to meet hard bounded-delays in the network. Using the derived theorems, we present SharpEdge, a novel design to meet deterministic bounded-delays in the network. To the best of our knowledge, SharpEdge is the first scheme that can meet all following key properties: (1) it supports coexistence of different classes of traffic, while it can guarantee their different required bounded-delays, (2) it does not require any changes in the core of the network, (3) it supports both periodic and bursty traffic patterns, and (4) it does not require any time synchronization between network devices.
Optical Studies of the Transient Dipping X-Ray Sources X1755–338 and X1658–298 in Quiescence

We have studied the optical counterparts of X1755-338 and X1658-298 in their X-ray "off" states. The first observations of X1755-338 in quiescence show that the counterpart, V4134 Sgr, has faded by more than 3.5 mag in V. If the mass donor in the system is an M0 V star, as implied by the period, our upper limits on the brightness of the counterpart suggest that it is more distant than 4 kpc. We observed V2134 Oph, the optical counterpart of X1658-298, on several occasions in 1997 April/May and found the source only ~1 mag fainter than when it is X-ray bright. Contemporaneous X-ray data confirm that the source remains in the quiescent state during our optical observations. Our optical light curve, folded on the 7.1 hr orbital period, does not show any modulation across the binary cycle. It is possible that the absence of detectable X-ray emission, despite the indication for an accretion disk and activity in the system, is related to a structure in the disk that permanently obscures the central X-ray source. The optical properties of V2134 Oph are unique among the known X-ray transients.
Modulus--Pressure Equation for Confined Fluids

Ultrasonic experiments allow one to measure the elastic modulus of bulk solid or fluid samples. Recently such experiments have been carried out on fluid-saturated nanoporous glass to probe the modulus of a confined fluid. In our previous work [G. Y. Gor et al., J. Chem. Phys., 143, 194506 (2015)], using Monte Carlo simulations we showed that the elastic modulus K of a fluid confined in a mesopore is a function of the pore size. Here we focus on the modulus-pressure dependence K(P), which is linear for bulk materials, a relation known as the Tait-Murnaghan equation. Using transition-matrix Monte Carlo simulations we calculated the elastic modulus of bulk argon as a function of pressure and argon confined in silica mesopores as a function of Laplace pressure. Our calculations show that while the elastic modulus is strongly affected by confinement and temperature, the slope of the modulus versus pressure is not. Moreover, the calculated slope is in a good agreement with the reference data for bulk argon and experimental data for confined argon derived from ultrasonic experiments. We propose to use the value of the slope of K(P) to estimate the elastic moduli of an unknown porous medium.
Evolution of the Solar Nebula. IX. Gradients in the Spatial Heterogeneity of the Short-lived Radioisotopes 60 Fe and 26 Al and the Stable Oxygen Isotopes

Short-lived radioisotopes (SLRIs) such as 60Fe and 26Al were likely injected into the solar nebula in a spatially and temporally heterogeneous manner. Marginally gravitationally unstable (MGU) disks, of the type required to form gas giant planets, are capable of rapid homogenization of isotopic heterogeneity as well as of rapid radial transport of dust grains and gases throughout a protoplanetary disk. Two different types of new models of an MGU disk in orbit around a solar-mass protostar are presented. The first set has variations in the number of terms in the spherical harmonic solution for the gravitational potential, effectively studying the effect of varying the spatial resolution of the gravitational torques responsible for MGU disk evolution. The second set explores the effects of varying the initial minimum value of the Toomre Q stability parameter, from values of 1.4 to 2.5, i.e., toward increasingly less unstable disks. The new models show that the basic results are largely independent of both sets of variations. MGU disk models robustly result in rapid mixing of initially highly heterogeneous distributions of SLRIs to levels of ~10% in both the inner ( 10 AU) disk regions, and to even lower levels (~2%) in intermediate regions, where gravitational torques are most effective at mixing. These gradients should have cosmochemical implications for the distribution of SLRIs and stable oxygen isotopes contained in planetesimals (e.g., comets) formed in the giant planet region (~5 to ~10 AU) compared to those formed elsewhere.
Accurate nonadiabatic quantum dynamics on the cheap: Making the most of mean field theory with master equations

In this article, we show how Ehrenfest mean field theory can be made both a more accurate and efficient method to treat nonadiabatic quantum dynamics by combining it with the generalized quantum master equation framework. The resulting mean field generalized quantum master equation (MF-GQME) approach is a non-perturbative and non-Markovian theory to treat open quantum systems without any restrictions on the form of the Hamiltonian that it can be applied to. By studying relaxation dynamics in a wide range of dynamical regimes, typical of charge and energy transfer, we show that MF-GQME provides a much higher accuracy than a direct application of mean field theory. In addition, these increases in accuracy are accompanied by computational speed-ups of between one and two orders of magnitude that become larger as the system becomes more nonadiabatic. This combination of quantum-classical theory and master equation techniques thus makes it possible to obtain the accuracy of much more computationally expensive approaches at a cost lower than even mean field dynamics, providing the ability to treat the quantum dynamics of atomistic condensed phase systems for long times.
Strontium and Barium in Early-type Galaxies

The detailed abundance patterns of the stars within galaxies provide a unique window into the history of star formation (SF) at early times. Two widely used 'chronometers' include the {alpha} and iron-peak elements, which are created on short and long timescales, respectively. These two clocks have been widely used to estimate SF timescales from moderate-resolution spectra of early-type galaxies. Elements formed via s-process neutron captures (e.g., Sr and Ba) comprise a third type of chronometer, as the site of the main s-process is believed to be intermediate and low-mass asymptotic giant branch stars. The [{alpha}/Ba] ratio in particular should provide a powerful new constraint on the SF histories of galaxies, in part because it is insensitive to the uncertain distribution of Type Ia supernovae detonation times and the overall Ia rate. Here we present new measurements of the abundance of Sr and Ba in nearby early-type galaxies by applying stellar population synthesis tools to high signal-to-noise optical spectra. We find a strong anti-correlation between [Mg/Fe] and [Ba/Fe], and a strong positive correlation between [Mg/Ba] and galaxy velocity dispersion. These trends are consistent with the idea that more massive galaxies formed their stars on shorter timescales compared to less massive galaxies,more » and rule out several other proposed explanations for the observed super-solar [Mg/Fe] values in massive galaxies. In contrast, [Sr/Fe] {approx}0, with no strong variation across the sample. It is difficult to interpret the Sr trends without detailed chemical evolution models owing to the multiplicity of proposed nucleosynthetic sites for Sr.« less
MEASURING THE IRREVERSIBILITY OF NUMERICAL SCHEMES FOR REVERSIBLE STOCHASTIC DIFFERENTIAL EQUATIONS

For a stationary Markov process the detailed balance condition is equivalent to the time-reversibility of the process. For stochastic differential equations (SDE’s), the time discretization of numerical schemes usually destroys the time-reversibility property. Despite an extensive literature on the numerical analysis for SDE’s, their stability properties, strong and/or weak error estimates, large deviations and infinite-time estimates, no quantitative results are known on the lack of reversibility of discrete-time approximation processes. In this paper we provide such quantitative estimates by using the concept of entropy production rate, inspired by ideas from non-equilibrium statistical mechanics. The entropy production rate for a stochastic process is defined as the relative entropy (per unit time) of the path measure of the process with respect to the path measure of the time-reversed process. By construction the entropy production rate is nonnegative and it vanishes if and only if the process is reversible. Crucially, from a numerical point of view, the entropy production rate is an a posteriori quantity, hence it can be computed in the course of a simulation as the ergodic average of a certain functional of the process (the so-called Gallavotti−Cohen (GC) action functional). We compute the entropy production for various numerical schemes such as explicit Euler−Maruyama and explicit Milstein’s for reversible SDEs with additive or multiplicative noise. In addition we analyze the entropy production for the BBK integrator for the Langevin equation. The order (in the time-discretization step Δt ) of the entropy production rate provides a tool to classify numerical schemes in terms of their (discretization-induced) irreversibility. Our results show that the type of the noise critically affects the behavior of the entropy production rate. As a striking example of our results we show that the Euler scheme for multiplicative noise is not an adequate scheme from a reversibility point of view since its entropy production rate does not decrease with Δt .
Stopping Time Convergence for Processes Associated with Dirichlet Forms

Convergence is proved for solutions un of Dirichlet problems in regions with many small excluded sets (holes), as the holes become smaller and more numerous. The problem is formulated probabilistically in the context of general Dirichlet forms, for random and nonrandom excluded sets. Sufficient conditions are given in Theorem 2.1 under which the sequence of entrance times or hitting times of the excluded sets converges in the stable topology. Convergence in the stable topology is a strengthened form of convergence in distribution, introduced by Renyi. Stable convergence of the entrance times implies convergence of the solutions un of the corresponding Dirichlet problems. Theorem 2.1 applies to Dirichlet forms such that the Markov process associated with the form has continuous paths and satisfies an absolute continuity condition for occupation time measures (Eq. 2.4). Conditions for convergence are formulated in terms of the sum of the expectations of the equilibrium measures for the excluded sets. The proof of convergence uses the fact that any martingale with respect to the natural filtration of the process must be continuous. In the case that the excluded sets are iid random, Theorem 2.1 strengthens previous results for the classical Brownian motion setting.
The quantum character of buckling instabilities in thin rods

Here the buckling of inextensible rods due to axial body forces is mapped to 1D, nonrelativistic, time-independent quantum mechanics. Focusing on the pedagogical case of rods confined to 2D, three simple and physically realizable applications of the mapping are given in detail; the quantum counterparts of these are particle in a box, particle in a delta-function well, and particle in a triangular well. A fourth application examines the buckling counterpart of a quantum many-body problem (in the Hartree approximation). Through a fifth application, given in the form of an exercise, the reader can explore the surprising consequences of adding a second transverse dimension to the rod buckling problem and imposing periodic boundary conditions.
Parametrically Amplified Low-Power MEMS Capacitive Humidity Sensor.

We present the design, fabrication, and response of a polymer-based Laterally Amplified Chemo-Mechanical (LACM) humidity sensor based on mechanical leveraging and parametric amplification. The device consists of a sense cantilever asymmetrically patterned with a polymer and flanked by two stationary electrodes on the sides. When exposed to a humidity change, the polymer swells after absorbing the analyte and causes the central cantilever to bend laterally towards one side, causing a change in the measured capacitance. The device features an intrinsic gain due to parametric amplification resulting in an enhanced signal-to-noise ratio (SNR). Eleven-fold magnification in sensor response was observed via voltage biasing of the side electrodes without the use of conventional electronic amplifiers. The sensor showed a repeatable and recoverable capacitance change of 11% when exposed to a change in relative humidity from 25–85%. The dynamic characterization of the device also revealed a response time of ~1 s and demonstrated a competitive response with respect to a commercially available reference chip.
QCD breaks Lorentz invariance and colour

In the previous work [A. P. Balachandran and S. Vaidya, Eur. Phys. J. Plus 128, 118 (2013)], we have argued that the algebra of non-Abelian superselection rules is spontaneously broken to its maximal Abelian subalgebra, that is, the algebra generated by its completing commuting set (the two Casimirs, isospin and a basis of its Cartan subalgebra). In this paper, alternative arguments confirming these results are presented. In addition, Lorentz invariance is shown to be broken in quantum chromodynamics (QCD), just as it is in quantum electrodynamics (QED). The experimental consequences of these results include fuzzy mass and spin shells of coloured particles like quarks, and decay life times which depend on the frame of observation [D. Buchholz, Phys. Lett. B 174, 331 (1986); D. Buchholz and K. Fredenhagen, Commun. Math. Phys. 84, 1 (1982; J. Frohlich, G. Morchio and F. Strocchi, Phys. Lett. B 89, 61 (1979); A. P. Balachandran, S. Kurkcuoglu, A. R. de Queiroz and S. Vaidya, Eur. Phys. J. C 75, 89 (2015); A. P. Balachandran, S. Kurkcuoglu and A. R. de Queiroz, Mod. Phys. Lett. A 28, 1350028 (2013)]. In a paper under preparation, these results are extended to the ADM Poincare group and the local Lorentz group of frames. The renormalisation of the ADM energy by infrared gravitons is also studied and estimated.
Bayesian goodness of fit tests: a conversation for David Mumford

The problem of making practical, useful goodness of fit tests in the Bayesian paradigm is largely open. We introduce a class of special cases (testing for uniformity: have the cards been shuffled enough; does my random generator work) and a class of sensible Bayes tests inspired by Mumford, Wu and Zhu. Calculating these tests presents the challenge of 'doubly intractable distributions'. In present circumstances, modern MCMC techniques are up to the challenge. But many other problems remain. Our paper is didactic, we hope to induce the reader to help take it further.