cssi/SciSciGPT-SciSciNet huggingface dataset:
Does BLEU score work for code migration

Statistical machine translation (SMT) is a fast-growing sub-field of computational linguistics. Until now, the most popular automatic metric to measure the quality of SMT is BiLingual Evaluation Understudy (BLEU) score. Lately, SMT along with the BLEU metric has been applied to a Software Engineering task named code migration. (In) Validating the use of BLEU score could advance the research and development of SMT-based code migration tools. Unfortunately, there is no study to approve or disapprove the use of BLEU score for source code. In this paper, we conducted an empirical study on BLEU score to (in) validate its suitability for the code migration task due to its inability to reflect the semantics of source code. In our work, we use human judgment as the ground truth to measure the semantic correctness of the migrated code. Our empirical study demonstrates that BLEU does not reflect translation quality due to its weak correlation with the semantic correctness of translated code. We provided counter-examples to show that BLEU is ineffective in comparing the translation quality between SMT-based models. Due to BLEU's ineffectiveness for code migration task, we propose an alternative metric RUBY, which considers lexical, syntactical, and semantic representations of source code. We verified that RUBY achieves a higher correlation coefficient with the semantic correctness of migrated code, 0.775 in comparison with 0.583 of BLEU score. We also confirmed the effectiveness of RUBY in reflecting the changes in translation quality of SMT-based translation models. With its advantages, RUBY can be used to evaluate SMT-based code migration models.
Building energy load forecasting using Deep Neural Networks

Ensuring sustainability demands more efficient energy management with minimized energy wastage. Therefore, the power grid of the future should provide an unprecedented level of flexibility in energy management. To that end, intelligent decision making requires accurate predictions of future energy demand/load, both at aggregate and individual site level. Thus, energy load forecasting have received increased attention in the recent past. However, it has proven to be a difficult problem. This paper presents a novel energy load forecasting methodology based on Deep Neural Networks, specifically, Long Short Term Memory (LSTM) algorithms. The presented work investigates two LSTM based architectures: 1) standard LSTM and 2) LSTM-based Sequence to Sequence (S2S) architecture. Both methods were implemented on a benchmark data set of electricity consumption data from one residential customer. Both architectures were trained and tested on one hour and one-minute time-step resolution datasets. Experimental results showed that the standard LSTM failed at one-minute resolution data while performing well in one-hour resolution data. It was shown that S2S architecture performed well on both datasets. Further, it was shown that the presented methods produced comparable results with the other deep learning methods for energy forecasting in literature.
Rapidly Star-forming Galaxies At High Redshifts

Herschel has opened new windows into studying the evolution of rapidly star-forming galaxies out to high redshifts. Today’s massive starbursts are characterized by star formation rates (SFRs) of ~100 + M ⊙ / yr and display a chaotic morphology and nucleated star formation indicative of a major merger. At z ~ 2, galaxies of similar mass and SFR are characterized by ordered rotation and distributed star formation. The emerging cold accretion paradigm provides an intuitive understanding for such differences. In it, halo accretion rates govern the supply of gas into star-forming regions, modulated by strong outflows. The high accretion rates at high- z drive more rapid star formation, while also making disks thicker and clumpier; the clumps are expected to be short-lived in the presence of strong galactic outflows as observed. Hence equivalently rapid star-formers at high redshift are not analogous to local merger-driven starbursts, but rather to local disks with highly enhanced accretion rates.
Linear and nonlinear spectroscopy from quantum master equations

We investigate the accuracy of the second-order time-convolutionless (TCL2) quantum master equation for the calculation of linear and nonlinear spectroscopies of multichromophore systems. We show that even for systems with non-adiabatic coupling, the TCL2 master equation predicts linear absorption spectra that are accurate over an extremely broad range of parameters and well beyond what would be expected based on the perturbative nature of the approach; non-equilibrium population dynamics calculated with TCL2 for identical parameters are significantly less accurate. For third-order (two-dimensional) spectroscopy, the importance of population dynamics and the violation of the so-called quantum regression theorem degrade the accuracy of TCL2 dynamics. To correct these failures, we combine the TCL2 approach with a classical ensemble sampling of slow microscopic bath degrees of freedom, leading to an efficient hybrid quantum-classical scheme that displays excellent accuracy over a wide range of parameters. In the spectroscopic setting, the success of such a hybrid scheme can be understood through its separate treatment of homogeneous and inhomogeneous broadening. Importantly, the presented approach has the computational scaling of TCL2, with the modest addition of an embarrassingly parallel prefactor associated with ensemble sampling. The presented approach can be understood as a generalized inhomogeneous cumulant expansion technique, capable of treating multilevel systems with non-adiabatic dynamics.
The density of critical percolation clusters touching the boundaries of strips and squares

We consider the density of two-dimensional critical percolation clusters, constrained to touch one or both boundaries, in infinite strips, half-infinite strips and squares, as well as several related quantities for the infinite strip. Our theoretical results follow from conformal field theory and are compared with high-precision numerical simulation. For example, we show that the density of clusters touching both boundaries of an infinite strip of unit width (i.e. crossing clusters) is proportional to (sinπy)−5/48{[cos(πy/2)]1/3+[sin(πy/2)]1/3−1}. We also determine numerically contours for the density of clusters crossing squares and long rectangles with open boundaries on the sides and compare with theory for the density along an edge.
Mining Open Government Data Used in Scientific Research

In the following paper, we describe results from mining citations, mentions, and links to open government data (OGD) in peer-reviewed literature. We inductively develop a method for categorizing how OGD are used by different research communities, and provide descriptive statistics about the publication years, publication outlets, and OGD sources. Our results demonstrate that, 1. The use of OGD in research is steadily increasing from 2009 to 2016; 2. Researchers use OGD from 96 different open government data portals, with data.gov.uk and data.gov being the most frequent sources; and, 3. Contrary to previous findings, we provide evidence suggesting that OGD from developing nations, notably India and Kenya, are being frequently used to fuel scientific discoveries. The findings of this paper contribute to ongoing research agendas aimed at tracking the impact of open government data initiatives, and provides an initial description of how open government data are valuable to diverse scientific research communities.
Holomorphic open book decompositions

Emmanuel Giroux showed that every contact structure on a closed three dimensional manifold is supported by an open book decomposition. We will extend this result by showing that the open book decomposition can be chosen in such a way that the pages are solutions to a homologically perturbed Holomorphic Curve equation.
No Strong Geometric Beaming in the Ultraluminous Neutron Star Binary NGC 300 ULX-1 (SN 2010da) from Swift and Gemini

We have obtained near-simultaneous Swift/XRT imaging and Gemini GMOS spectroscopy for the ultraluminous X-ray source (ULX) NGC~300 ULX-1 (formerly designated SN~2010da). The observed X-ray emission is consistent with an inhomogeneous wind that partially obscures a central, bright inner accretion disk. We simultaneously fit eleven 0.3-10 keV spectra obtained over a $\sim$1 year time period (2016 April to 2017 July) using the same partial covering model, and find that although the covering fraction varies significantly (from 78% to consistent with 0%), the unabsorbed luminosity remains essentially constant across all observations ($2-6\times10^{39}$ erg s$^{-1}$). A relatively high 0.3-10 keV fractional variability amplitude ($F_{\rm var}$) of $\sim$30% is observed in all eleven observations. Optical spectra from Gemini exhibit numerous emission lines (e.g., H$\alpha$, H$\beta$, He II $\lambda$4686) which suggest that the neutron star primary is photoionizing material in the immediate vicinity of the binary. We compare the He II $\lambda$4686 line luminosity ($\sim7-9\times10^{35}$ erg s$^{-1}$) to the contemporaneous soft X-ray emission and find the X-ray emission is broadly consistent with the observed He II line luminosity. The combination of our X-ray observations and optical spectroscopy suggest that geometric beaming effects in the ULX-1 system are minimal, making ULX-1 one of only a few bona fide ULXs to be powered by accretion onto a neutron star.
Low power analog-to-digital conversion in millimeter wave systems: Impact of resolution and bandwidth on performance

The wide bandwidth and large number of antennas used in millimeter wave systems put a heavy burden on the power consumption at the receiver. In this paper, using an additive quantization noise model, the effect of analog-digital conversion (ADC) resolution and bandwidth on the achievable rate is investigated for a multi-antenna system under a receiver power constraint. Two receiver architectures, analog and digital combining, are compared in terms of performance. Results demonstrate that: (i) For both analog and digital combining, there is a maximum bandwidth beyond which the achievable rate decreases; (ii) Depending on the operating regime of the system, analog combiner may have higher rate but digital combining uses less bandwidth when only ADC power consumption is considered, (iii) digital combining may have higher rate when power consumption of all the components in the receiver front-end are taken into account.
Supersymmetric Landau-Ginzburg tensor models

We study two dimensional $$ \mathcal{N} $$ = (2, 2) Landau-Ginzburg models with tensor valued superfields with the aim of constructing large central charge superconformal field theories which are solvable using large N techniques. We demonstrate the viability of such constructions and motivate the study of anisotropic tensor models. Such theories are a novel deformation of tensor models where we break the continuous symmetries while preserving the large N solvability. Specifically, we examine theories with superpotentials involving tensor contractions chosen to pick out melonic diagrams. The anisotropy is introduced by further biasing individual terms by different coefficients, all of the same order, to retain large N scaling. We carry out a detailed analysis of the resulting low energy fixed point and comment on potential applications to holography. Along the way we also examine gauged versions of the models (with partial anisotropy) and find generically that such theories have a non-compact Higgs branch of vacua.
STUDY OF INTERSTELLAR MOLECULAR CLOUDS USING FORMALDEHYDE ABSORPTION TOWARD EXTRAGALACTIC RADIO SOURCES

We present new Very Large Array 6?cm H2CO observations toward four extragalactic radio continuum sources (B0212+735, 3C?111, NRAO?150, and BL?Lac) to explore the structure of foreground Galactic clouds as revealed by absorption variability. This project adds a new epoch in the monitoring observations of the sources reported by Marscher and collaborators in the mid-1990s. Our new observations confirm the monotonic increase in H2CO absorption strength toward NRAO?150. We do not detect significant variability of our 2009 spectra with respect to the 1994 spectra of 3C111, B0212+735, and BL?Lac; however, we find significant variability of the 3C111 2009 spectrum with respect to archive observations conducted in 1991 and 1992. Our analysis supports that changes in absorption lines could be caused by chemical and/or geometrical gradients in the foreground clouds and not necessarily by small-scale (~10?AU) high-density molecular clumps within the clouds.
Modeling a Maunder minimum

We introduce on/off intermittency into a mean field dynamo model by imposing stochastic fluctuations in either the alpha effect or through the inclusion of a fluctuating electromotive force. Sufficiently strong small scale fluctuations with time scales of the order of 0.3–3 years can produce long term variations in the system on time scales of the order of hundreds of years. However, global suppression of magnetic activity in both hemispheres at once was not observed. The variation of the magnetic field does not resemble that of the sunspot number, but is more reminiscent of the 10Be record. The interpretation of our results focuses attention on the connection between the level of magnetic activity and the sunspot number, an issue that must be elucidated if long term solar effects are to be well understood. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
STAR Overview of Hard Probe Observables

Abstract Parton energy loss, quarkonium sequential melting and particle production from electromagnetic interactions are tools to study Quark Gluon Plasma properties. The STAR detector, with large acceptance at mid-rapidity, excellent particle identification and wide transverse momentum coverage, is able to study these probes in details. In Hard Probes 2015, the STAR collaboration reported measurements of reconstructed jets, heavy-flavor physics, di-lepton production and the performance of new detectors in seven presentations and one poster. Given the rich results from STAR, this overview report will focus on a few selected results on jets and ϒ measurements in Au+Au collisions at s NN = 200 GeV , J / ψ production in p+p collisions at s NN = 500 GeV , and the di-electron spectrum in the low mass region from the Beam Energy Scan – Phase I.
The VERITAS Extragalactic non-Blazar Program

VERITAS is an array of four 12-m diameter imaging atmospheric-Cherenkov telescopes located in southern Arizona. Its aim is to study the very high energy (VHE: E > 100 GeV) -ray emission from astrophysical objects. In addition to the study of blazars, the VERITAS extragalactic science program develops a comprehensive observational program of extragalactic non-blazar sources. The study of Active Galactic Nuclei (AGN) is intensively pursued through the large MWL observational campaign on non-blazar radio galaxies. The success of these MWL campaigns has for the first time provided insights to the inner structures of jets r esponsible for -ray emission. The problem of the origin and acceleration of ultra-high energy cosmic rays is pursued th rough the observation of the starburst galaxy M 82, whose detection at VHE delivers important insights on the possible acceleration mechanisms. Finally, investigation of globular clusters places important limits on the millisecond pulsar contribution to their addressed -ray emission. The VERITAS extragalactic non-blazar science program and its results a re presented.
Lukewarm Dark Matter: Bose Condensation of Ultralight Particles

We discuss the thermal evolution and Bose-Einstein condensation of ultralight dark matter particles at finite, realistic cosmological temperatures. We find that if these particles decouple from regular matter before Standard Model particles annihilate, their temperature will be about 0.9 K. This temperature is substantially lower than the temperature of cosmic microwave background neutrinos and thus big bang nucleosynthesis remains unaffected. In addition, the temperature is consistent with WMAP 7-year+BAO+H0 observations without fine-tuning. We focus on particles of mass of m ~ 10–23 eV, which have Compton wavelength of galactic scales. Agglomerations of these particles can form stable halos and naturally prohibit small-scale structure. They avoid over-abundance of dwarf galaxies and may be favored by observations of dark matter distributions. We present numerical as well as approximate analytical solutions of the Friedmann-Klein-Gordon equations and study the cosmological evolution of this scalar field dark matter from the early universe to the era of matter domination. Today, the particles in the ground state mimic pressureless matter, while the excited state particles are radiation like.
Cognitive biomarker prioritization in Alzheimer's Disease using brain morphometric data.

Cognitive assessments represent the most common clinical routine for the diagnosis of Alzheimer’s Disease (AD). Given a large number of cognitive assessment tools and time-limited office visits, it is important to determine a proper set of cognitive tests for different subjects. Most current studies create guidelines of cognitive test selection for a targeted population, but they are not customized for each individual subject. In this manuscript, we develop a machine learning paradigm enabling personalized cognitive assessments prioritization. We adapt a newly developed learning-to-rank approach $${\mathtt {PLTR}}$$ to implement our paradigm. This method learns the latent scoring function that pushes the most effective cognitive assessments onto the top of the prioritization list. We also extend $${\mathtt {PLTR}}$$ to better separate the most effective cognitive assessments and the less effective ones. Our empirical study on the ADNI data shows that the proposed paradigm outperforms the state-of-the-art baselines on identifying and prioritizing individual-specific cognitive biomarkers. We conduct experiments in cross validation and level-out validation settings. In the two settings, our paradigm significantly outperforms the best baselines with improvement as much as 22.1% and 19.7%, respectively, on prioritizing cognitive features. The proposed paradigm achieves superior performance on prioritizing cognitive biomarkers. The cognitive biomarkers prioritized on top have great potentials to facilitate personalized diagnosis, disease subtyping, and ultimately precision medicine in AD.
Time-dependent discrimination advantages for harmonic sounds suggest efficient coding for memory

Perceptual systems have finite memory resources and must store incoming signals in compressed formats. To explore whether representations of a sound's pitch might derive from this need for compression, we compared discrimination of harmonic and inharmonic sounds across delays. In contrast to inharmonic spectra, harmonic spectra can be summarized, and thus compressed, using their fundamental frequency (f0). Participants heard two sounds and judged which was higher. Despite being comparable for sounds presented back-to-back, discrimination was better for harmonic than inharmonic stimuli when sounds were separated in time, implicating memory representations unique to harmonic sounds. Patterns of individual differences (correlations between thresholds in different conditions) indicated that listeners use different representations depending on the time delay between sounds, directly comparing the spectra of temporally adjacent sounds, but transitioning to comparing f0s across delays. The need to store sound in memory appears to determine reliance on f0-based pitch and may explain its importance in music, in which listeners must extract relationships between notes separated in time.
Successive Refinement of Privacy

This work examines a novel question: how much randomness is needed to achieve local differential privacy (LDP)? A motivating scenario is providing multiple levels of privacy to multiple analysts, either for distribution or for heavy hitter estimation, using the same (randomized) output. We call this setting successive refinement of privacy , as it provides hierarchical access to the raw data with different privacy levels. For example, the same randomized output could enable one analyst to reconstruct the input, while another can only estimate the distribution subject to LDP requirements. This extends the classical Shannon (wiretap) security setting to local differential privacy. We provide (order-wise) tight characterizations of privacy-utility-randomness trade-offs in several cases for distribution estimation, including the standard LDP setting under a randomness constraint. We also provide a non-trivial privacy mechanism for multi-level privacy. Furthermore, we show that we cannot reuse random keys over time while preserving privacy of each user.
Magnetometry using sodium fluorescence with synchronous modulation of two-photon resonant light fields

We have demonstrated a technique for remote magnetometry using fluorescence measurements in a sodium cell. This technique utilizes two-photon resonance instead of single-photon resonance to generate magnetic resonances with synchronous modulation of two laser fields. A strong magnetic resonance with its dip matching the Larmor frequency, ΩL, is produced when a magnetic field perpendicular to the laser propagation direction is applied. A magnetic field sensitivity of 45 pT/√Hz is measured at a 35% modulation duty cycle where ΩL resonance has a maximum amplitude. We have discussed ways to further improve the sensitivity closer to the shot-noise limit by making changes to our existing setup. An additional magnetic resonance at 3ΩL is also formed due to two-photon resonance, which can be utilized in determining the magnetic field orientation. We have developed a theoretical model based on density matrix equations to study the magnetic resonances under different conditions and also for validating our experimental observations.
3D printing an external-cavity diode laser housing

The ability to control the frequency of an external-cavity diode laser (ECDL) is an essential component for undergraduate laboratories and atomic physics research. Typically, the housing for the ECDL's diffraction grating and piezoelectric transducer is either purchased commercially or machined from metal. Here, we present an alternative to these commonly used options that utilizes 3D printing, a tool available in many physics departments. We characterize the performance of our ECDL system using atomic spectroscopy and self-heterodyne interferometry and show that it is sufficient for use in undergraduate spectroscopy experiments and a number of research applications, where extremely narrow laser linewidths are not necessary. The performance and affordability of 3D-printed designs make them an appealing option for future use.
Permutation orbifolds of Virasoro vertex algebras and W-algebras

Abstract We study permutation orbifolds of the 2-fold and 3-fold tensor product for the Virasoro vertex algebra V c of central charge c. In particular, we show that for all but finitely many central charges ( V c ⊗ 3 ) Z 3 is a W-algebra of type ( 2 , 4 , 5 , 6 3 , 7 , 8 3 , 9 3 , 10 2 ) . We also study orbifolds of their simple quotients and obtain new realizations of certain rational affine W-algebras associated to a principal nilpotent element. Further analysis of permutation orbifolds of the celebrated ( 2 , 5 ) -minimal vertex algebra L − 22 5 is presented.
Long-term trend and solar cycle in the middle atmosphere temperature revealed from merged HALOE and SABER datasets

Abstract The middle atmosphere temperature trend and solar cycle have been studied with long-term ground-based and satellite datasets and/or model simulations. Single satellite observations for middle atmosphere temperature are not long enough (less than 2 solar cycles) to derive long-term trend and solar cycle effects with great confidence. Using a nearly 30-year dataset merged from the Halogen Occultation Experiment (HALOE) observations between 1991 and 2005 and the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) observations between 2002 and 2019, we study the long-term trend and solar cycle in the middle atmosphere temperature between 45°S and 45°N. The cooling trend is significant below 75 km with a maximum value of ~ -1.2 K/decade near 60–70 km in the southern hemisphere (SH) tropical and subtropical region. The SH cooling trend is larger than its counterpart in the northern hemisphere (NH). The trend derived from the SABER only dataset is ~1.5 times smaller than that derived from the merged dataset, which is consistent with the upper stratospheric ozone recovery after 1995. The positive temperature response to the 11-year solar cycle is ~1 K/100 solar flux units (sfu) in the upper stratosphere and lower mesosphere and increase to more than 2 K/100 sfu in the upper mesosphere of the middle latitudes. The temperature responses show clear hemispheric asymmetry with stronger responses below 70 km but weaker above in the SH than those in the NH. This is likely related to hemispheric asymmetry of wave activities induced by indirect solar radiation.
Revisiting the Quasi Biennial Oscillation as Seen in ERA5. Part I: Description and Momentum Budget

The dynamics and momentum budget of the quasi-biennial oscillation (QBO) are examined in the ERA5 reanalysis and compared with those in ERA-I. Because of ERA5's higher spatial resolution it is capable of resolving a broader spectrum of atmospheric waves and allows for a better representation of the wave-mean flow interactions, both of which are of crucial importance for QBO studies. It is shown that the QBO-induced mean meridional circulation, which is mainly confined to the winter hemisphere, is strong enough to interrupt the tropical upwelling during the descent of the westerly shear zones. Since the momentum advection tends to damp the QBO, the wave forcing is responsible for both the downward propagation and for the maintenance of the QBO. It is shown that half the required wave forcing is provided by resolved waves during the descent of both westerly and easterly regimes. Planetary-scale waves account for most of the resolved wave forcing of the descent of westerly shear zones and small-scale gravity (SSG) waves with wavelengths shorter than 2000 km account for the remainder. SSG waves account for most of the resolved forcing of the descent of the easterly shear zones. The representation of the mean fields in the QBO is very similar in ERA5 and ERA-I but the resolved wave forcing is shown to be substantially stronger in ERA5. The contributions of the various equatorially-trapped wave modes to the QBO forcing are documented in Part II.
An Intersectional Analysis of COVID-19 Unemployment

Using the April 2020 Current Population Survey (CPS) micro dataset, we explore the racialized and gendered effects of the COVID-19 pandemic on the probability of being unemployed. The distribution of the pandemic-induced job losses for women and men or for different racial/ethnic categories has been studied in the recent literature. We contribute to this literature by providing an intersectional analysis of unemployment under COVID-19, where we examine the differences in the likelihood of unemployment across groups of White men, White women, Black men, Black women, Hispanic men, and Hispanic women. As a case of study of the COVID-19 recession, our work engages with the broader empirical literature testing the discrimination theories based on the unexplained gap after accounting for observable characteristics of women, men, and different races/ethnicities and their labor market positions. Controlling for individual characteristics such as education and age, as well as industry and occupation effects, we show that women of all three racial/ethnic categories are more likely to be unemployed compared to men, yet there are substantial differences across these groups based on different unemployment measures. Hispanic women have the highest likelihood of being unemployed, followed by Black women, who are still more likely to be unemployed than White women. We also examine if the ability to work from home has benefited any particular group in terms of lowering their likelihood of unemployment during the pandemic. We find that in industries with a high degree of teleworkable jobs, White women, Black men, and Hispanic men are no longer more likely to be unemployed relative to White men. However, Black women and Hispanic Women still experience a significantly higher probability of job loss compared to White men even if they are employed in industries with highly teleworkable jobs. As we control for both individual and aggregate factors, our results suggest that these differences are not simply the result of overrepresentation of women of color in certain industries and occupations; rather, unobservable factors such as discrimination could be at work.
Two robust tools for inference about causal effects with invalid instruments.

Instrumental variables have been widely used to estimate the causal effect of a treatment on an outcome. Existing confidence intervals for causal effects based on instrumental variables assume that all of the putative instrumental variables are valid; a valid instrumental variable is a variable that affects the outcome only by affecting the treatment and is not related to unmeasured confounders. However, in practice, some of the putative instrumental variables are likely to be invalid. This paper presents two tools to conduct valid inference and tests in the presence of invalid instruments. First, we propose a simple and general approach to construct confidence intervals based on taking unions of well-known confidence intervals. Second, we propose a novel test for the null causal effect based on a collider bias. Our two proposals outperform traditional instrumental variable confidence intervals when invalid instruments are present and can also be used as a sensitivity analysis when there is concern that instrumental variables assumptions are violated. The new approach is applied to a Mendelian randomization study on the causal effect of low-density lipoprotein on globulin levels.
Age-Delay Tradeoffs in Queueing Systems

We consider an ${m}$ server system in which each server can service at most one update packet at a time. The system designer controls (1) scheduling - the order in which the packets get serviced, (2) routing - the server that an arriving update packet joins for service, and (3) the service time distribution with fixed service rate. Given a fixed update generation process, we prove a strong age-delay and age-delay variance tradeoff, wherein, as the average AoI approaches its minimum, the packet delay and its variance approach infinity. In order to prove this result, we consider two special cases of the $m$ server system, namely, a single server system with last come first served with preemptive service and an infinite server system. In both these cases, we derive sufficient conditions to show that three heavy tailed service time distributions, namely Pareto, log-normal, and Weibull, asymptotically minimize the average AoI as their tail gets heavier, and establish the age-delay tradeoff results. We provide an intuitive explanation as to why such a seemingly counter intuitive age-delay tradeoff is natural, and that it should exist in many systems.
GaN/AlGaN 2DEGs in the quantum regime: Magneto-transport and photoluminescence to 60 tesla

Using high magnetic fields up to 60 T, we report magneto-transport and photoluminescence (PL) studies of a two-dimensional electron gas (2DEG) in a GaN/AlGaN heterojunction grown by molecular-beam epitaxy. Transport measurements demonstrate that the quantum limit can be exceeded (Landau level filling factor ν < 1) and show evidence for the ν = 2 / 3 fractional quantum Hall state. Simultaneous optical and transport measurements reveal synchronous quantum oscillations of both the PL intensity and the longitudinal resistivity in the integer quantum Hall regime. PL spectra directly reveal the dispersion of occupied Landau levels in the 2DEG and, therefore, the electron mass. These results demonstrate the utility of high (pulsed) magnetic fields for detailed measurements of quantum phenomena in high-density 2DEGs.
Exploring Controllable Text Generation Techniques.

Neural controllable text generation is an important area gaining attention due to its plethora of applications. Although there is a large body of prior work in controllable text generation, there is no unifying theme. In this work, we provide a new schema of the pipeline of the generation process by classifying it into five modules. The control of attributes in the generation process requires modification of these modules. We present an overview of different techniques used to perform the modulation of these modules. We also provide an analysis on the advantages and disadvantages of these techniques. We further pave ways to develop new architectures based on the combination of the modules described in this paper.
A Modular Architecture for Procedural Generation of Towns, Intersections and Scenarios for Testing Autonomous Vehicles

Simulation-based testing is critical for ensuring safety of autonomous vehicles. Autonomous vehicles are enabled by deep learning techniques which require a large quantity of data. With simulation testing, we can create rare events for testing and training of autonomous vehicles. Procedural generation of roads and modeling of driving behaviors in an easily extendable architecture ensures that we are able to create rare scenarios at scale with minimal artistic burden. In this paper, we present CruzWay, a system that both supports and creates these scenarios. With CruzWay, we are able to procedurally generate town sized road networks or road intersections. CruzWay supports generation of road meshes as well as navigation meshes from SUMO road network files. CruzWay can generate cars as well as pedestrians run by behavior trees (BTs) in this environment. The self-contained, modular nature of BTs in combination with procedural roads allows us to create a large number of scenarios.
House Prices and Macroprudential Policies: Evidence from City-level Data in India

This paper examines the efficacy of macroprudential policies in addressing housing prices in a developing country while underscoring the importance of fundamental factors. The estimated models using city-level data for India suggest a strong influence of fundamental factors in driving housing prices. There is compelling evidence of the effectiveness of macroprudential tools viz., Loan-to-value (LTV) ratio, risk weights, and provisioning requirements, in influencing housing price movements. A granular analysis suggests an even stronger impact on housing prices of a change in the regulatory LTV ratio for large-sized vis-a-vis small-sized mortgages, which buttresses their potency in fighting house price speculations. A tightening of the risk weights on the housing assets of banks causes significant downward pressure on house prices. Similarly, regulatory changes in standard asset provisioning on housing loans also influence house prices.
Nonconvex Matrix Factorization From Rank-One Measurements

We consider the problem of recovering low-rank matrices from random rank-one measurements, which spans numerous applications including covariance sketching, phase retrieval, quantum state tomography, and learning shallow polynomial neural networks, among others. Our approach is to directly estimate the low-rank factor by minimizing a nonconvex least-squares loss function via vanilla gradient descent, following a tailored spectral initialization. When the true rank is bounded by a constant, this algorithm is guaranteed to converge to the ground truth (up to global ambiguity) with near-optimal sample complexity and computational complexity. To the best of our knowledge, this is the first guarantee that achieves near-optimality in both metrics. In particular, the key enabler of near-optimal computational guarantees is an implicit regularization phenomenon: without explicit regularization, both spectral initialization and the gradient descent iterates automatically stay within a region incoherent with the measurement vectors. This feature allows one to employ much more aggressive step sizes compared with the ones suggested in prior literature, without the need of sample splitting.
Economic Effects of Transparency in International Equity Markets: A Review and Suggestions for Future Research

Economic Effects of Transparency in International Equity Markets: A Review and Suggestions for Future Research
The Economics of Structured Finance

The essence of structured finance activities is the pooling of economic assets like loans, bonds, and mortgages, and the subsequent issuance of a prioritized capital structure of claims, known as tranches, against these collateral pools. As a result of the prioritization scheme used in structuring claims, many of the manufactured tranches are far safer than the average asset in the underlying pool. This ability of structured finance to repackage risks and to create “safe” assets from otherwise risky collateral led to a dramatic expansion in the issuance of structured securities, most of which were viewed by investors to be virtually risk-free and certified as such by the rating agencies. At the core of the recent financial market crisis has been the discovery that these securities are actually far riskier than originally advertised. We examine how the process of securitization allowed trillions of dollars of risky assets to be transformed into securities that were widely considered to be safe, and argue that two key features of the structured finance machinery fueled its spectacular growth. First, we show that most securities could only have received high credit ratings if the rating agencies were extraordinarily confident about their ability to estimate the underlying securities’ default risks, and how likely defaults were to be correlated. Using the prototypical structured finance security—the collateralized debt obligation (CDO)—as an example, we illustrate that issuing a capital structure amplifies errors in evaluating the risk of the underlying securities.
How Planned Parenthood v. Casey (Pretty Much) Settled the Abortion Wars

More than twenty-one years after Robert Bork’s failed Supreme Court nomination and seventeen years after Planned Parenthood of Southeastern Pennsylvania v. Casey, the rhetoric of abortion politics remains unchanged. Pro-choice interests, for example, argue that states are poised to outlaw abortion and that Roe v. Wade is vulnerable to overruling. In this Essay, I will debunk those claims. First, I will explain how Casey’s approval of limited abortion rights reflected an emerging national consensus in 1992. Second, I will explain why the Supreme Court is unlikely to risk political backlash by formally modifying Casey—either by restoring the trimester test or by overruling Roe altogether. Third (and most important), I will explain how it is that Casey stabilized state abortion politics. The national consensus favoring limited abortion rights remains intact. Correspondingly, the template of laws approved by the Supreme Court in Casey were politically popular at the time of Casey and remain politically popular today. Indeed, since Pennsylvania has always been one of the most restrictive states when it comes to abortion regulation, very few states are interested in pushing the boundaries of what Casey allows. And while a handful of outlier states have pushed the boundaries of what Casey allows, these states (which account for a quite small percentage of abortions) have largely worked within parameters set by the Court in Casey. Perhaps most telling, neither the confirmation of Chief Justice Roberts and Justice Alito nor the Supreme Court’s approval of federal partial-birth abortion legislation has significantly impacted state antiabortion efforts. For all these reasons, pro-choice and pro-life interests would be better served shifting their energies away from legalistic fights over abortion regulation and toward shaping the hearts and minds of the women who may seek abortions and the doctors and clinics that may provide abortion services. author. Goodrich Professor of Law and Professor of Government, College of William and Mary. Thanks to Caitlin Borgmann, Dave Garrow, Michael Green, Robert Post, Reva Siegel, Elizabeth Tulis, and Tim Zick for helping me think about the topics addressed in this Essay. Thanks to Amanda Christensen, Andrea Johnson, Fred Dingledy, and especially to Nicole Mansker for helping me research this Essay.
Invariants of curves in RP 2 and R 2

Author(s): Thompson, Abigail | Abstract: There is an elegant relation found by Fabricius-Bjerre [Math. Scand 40 (1977) 20--24] among the double tangent lines, crossings, inflections points, and cusps of a singular curve in the plane. We give a new generalization to singular curves in RP^2. We note that the quantities in the formula are naturally dual to each other in RP^2, and we give a new dual formula.
International Cooperation on Migration: Theory and Practice

Since the Great Depression of the 1930s, international economic cooperation has flourished on many issues. The Reciprocal Trade Agreements program of the United States laid the groundwork for the General Agreement on Tariffs and Trade (GATT), now subsumed within the World Trade Organization (WTO). Trade liberalization under WTO/GATT auspices has reduced tariffs on dutiable goods imports in developed countries from an average of 30 to 40 percent in 1947 to an average of around 4 percent today.1 The WTO General Agreement on Trade in Services has made significant initial progress in opening national services markets to companies based abroad. The WTO Agreement on Trade-Related Aspects of Intellectual Property Rights has, for better or worse, produced international harmonization in many aspects of patent, copyright, and trademark law. Bank regulators in the developed economies have cooperated through a series of Basel Accords. For roughly a quarter century, the International Monetary Fund orchestrated multilateral cooperation on exchange rates under the Bretton Woods system. And at the bilateral and plurilateral level, hundreds of investment agreements—standalone bilateral investment treaties and investment provisions in preferential trade agreements—afford a variety of protections to foreign investors in developed and developing countries. Conspicuously absent from this list is international cooperation on migration. Although, as shall be seen, more cooperation
Controlling for Quality in House Price Indices

Given the importance of house prices it is not surprising that house price indices are used for many purposes. One of the factors that differentiates these indices is the house price determinants (such as structural characteristics and neighborhood quality) that are accounted for—that is, held constant. Indices are usually generated from house price regressions. It is shown that, regardless of the desired level of accounting, it is necessary to control for all significant determinants of house prices in these regressions to obtain unbiased estimates of the growth in house prices. An empirical example shows that not controlling for neighborhood quality can lead to substantial biases in estimates of house price appreciation rates even if the index does not account for this factor.
The Predictive Value of Expenses Excluded from Pro Forma Earnings

We investigate the informational properties of pro forma earnings. This increasingly popular measure of earnings excludes certain expenses that the company deems non-recurring, non-cash, or otherwise unimportant for understanding the future value of the firm. We find, however, that these expenses are far from unimportant. Higher levels of exclusions lead to predictably lower future cash flows. We also find that investors do not fully appreciate the lower cash flow implications at the time of the earnings announcement. A trading strategy based on the excluded expenses yields a large positive abnormal return in the years following the announcement, and persists after controlling for various risk factors and other anomalies.
Intellectual Property Rights, Conflict of Laws and International Jurisdiction: Applicability of ALI Principles in Japan?

The American Legal Institute’s (ALI) recent project, Intellectual Property: Principles Governing Jurisdiction, Choice of Law, and Judgments in Transnational Disputes (ALI Principles),1 provides an important jumping-off point in the discourse on the need for private international law on intellectual property rights (IPR). This paper is considering the applicability of the ALI Principles to the Japanese legal system, specifically whether these principles could, or should, be successfully adopted by Japanese Courts.
Agenda chasing and contests among news providers

This article studies competition in contests with a focus on the news industry that is increasingly influenced by social media. The model assumes publishers to pick a single topic from a large pool based on the topics' prior “success” probabilities, thereby “chasing” potentially successful topics. Firms that publish topics that become successful divide a “reward” which can change with the number of competing firms and the number of successful topics. The results show that share structures can be categorized into three types that, in turn, lead to qualitatively different outcomes for the contest.
How Can We Create Collaborative Design Knowledge in Politicized Contexts

This commentary notes that the authors of the Special Issue propose that organization design knowledge will be more actionable if it is created in collaboration with the organization’s members. I draw attention to a risk in the co-creation of design knowledge: increasing the politicization of the already politically fraught process of organizational design. The reasons why collaborative design-knowledge creation may increase politicking are described, and ideas for managing it are suggested.
$THH$ and base-change for Galois extensions of ring spectra

We treat the question of base-change in THH for faithful Galois extensions of ring spectra in the sense of Rognes. Given a faithful Galois extension A → B of ring spectra, we consider whether the map THH(A) ⊗AB → THH(B) is an equivalence. We reprove and extend positive results of Weibel and Geller, and McCarthy and Minasian, and offer new examples of Galois extensions for which base-change holds. We also provide a counterexample where base-change fails.
Generalized Seismic Phase Detection with Deep Learning

To optimally monitor earthquake‐generating processes, seismologists have sought to lower detection sensitivities ever since instrumental seismic networks were started about a century ago. Recently, it has become possible to search continuous waveform archives for replicas of previously recorded events (i.e., template matching), which has led to at least an order of magnitude increase in the number of detected earthquakes and greatly sharpened our view of geological structures. Earthquake catalogs produced in this fashion, however, are heavily biased in that they are completely blind to events for which no templates are available, such as in previously quiet regions or for very large‐magnitude events. Here, we show that with deep learning, we can overcome such biases without sacrificing detection sensitivity. We trained a convolutional neural network (ConvNet) on the vast hand‐labeled data archives of the Southern California Seismic Network to detect seismic body‐wave phases. We show that the ConvNet is extremely sensitive and robust in detecting phases even when masked by high background noise and when the ConvNet is applied to new data that are not represented in the training set (in particular, very large‐magnitude events). This generalized phase detection framework will significantly improve earthquake monitoring and catalogs, which form the underlying basis for a wide range of basic and applied seismological research.