cssi/SciSciGPT-SciSciNet huggingface dataset:
The Impact of HIV/AIDS on Human Capital Investment in Sub-Saharan Africa: New Evidence

The risk of AIDS-related mortality increased dramatically throughout the 1990s. This paper updates previous work by Fortson (2011) to examine the impact of mortality risk on human capital investment during the deadliest period of the pandemic. We combine Demographic Health Survey data from 30 countries, across 60 survey waves, to generate a sample of over 1,300,000 observations. Cohort-specific analysis using the updated sample yields new evidence that the negative relationship between HIV prevalence and schooling steepened as mortality risk increased. The reduction in schooling is largest for women, and along the extensive margin of the schooling decision. The findings indicate that the decline in human capital investment associated with the HIV/AIDS pandemic prior to the availability of treatment was larger in magnitude than previously understood, but may be reversing rapidly as access to treatment is expanded.
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis

Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However, the impact of label noise has not received sufficient attention. Recent studies have shown that label noise can significantly impact the performance of deep learning models in many machine learning and computer vision applications. This is especially concerning for medical applications, where datasets are typically small, labeling requires domain expertise and suffers from high inter- and intra-observer variability, and erroneous predictions may influence decisions that directly impact human health. In this paper, we first review the state-of-the-art in handling label noise in deep learning. Then, we review studies that have dealt with label noise in deep learning for medical image analysis. Our review shows that recent progress on handling label noise in deep learning has gone largely unnoticed by the medical image analysis community. To help achieve a better understanding of the extent of the problem and its potential remedies, we conducted experiments with three medical imaging datasets with different types of label noise, where we investigated several existing strategies and developed new methods to combat the negative effect of label noise. Based on the results of these experiments and our review of the literature, we have made recommendations on methods that can be used to alleviate the effects of different types of label noise on deep models trained for medical image analysis. We hope that this article helps the medical image analysis researchers and developers in choosing and devising new techniques that effectively handle label noise in deep learning.
Ultra-Wideband Air-to-Ground Propagation Channel Characterization in an Open Area

This article studies the air-to-ground ultra-wideband channel through propagation measurements between 3.1 to 4.8 GHz using unmanned-aerial-vehicles (UAVs). Different line-of-sight (LOS) and obstructed-LOS scenarios and two antenna orientations were used in the experiments. Multipath channel statistics for different propagation scenarios were obtained, and the Saleh–Valenzuela model was found to provide a good fit for the statistical channel model. An analytical path loss model based on antenna gains in the elevation plane is provided for unobstructed UAV hovering and moving (in a circular path) propagation scenarios.
Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise Comparisons.

A number of applications (e.g., AI bot tournaments, sports, peer grading, crowdsourcing) use pairwise comparison data and the Bradley-Terry-Luce (BTL) model to evaluate a given collection of items (e.g., bots, teams, students, search results). Past work has shown that under the BTL model, the widely-used maximum-likelihood estimator (MLE) is minimax-optimal in estimating the item parameters, in terms of the mean squared error. However, another important desideratum for designing estimators is fairness. In this work, we consider fairness modeled by the notion of bias in statistics. We show that the MLE incurs a suboptimal rate in terms of bias. We then propose a simple modification to the MLE, which "stretches" the bounding box of the maximum-likelihood optimizer by a small constant factor from the underlying ground truth domain. We show that this simple modification leads to an improved rate in bias, while maintaining minimax-optimality in the mean squared error. In this manner, our proposed class of estimators provably improves fairness represented by bias without loss in accuracy.
Applications of minimally invasive multimodal telemetry for continuous monitoring of brain function and intracranial pressure in macaques with acute viral encephalitis.

Alphaviruses such as Venezuelan equine encephalitis virus (VEEV) and Eastern equine encephalitis virus (EEEV) are arboviruses that can cause severe zoonotic disease in humans. Both VEEV and EEEV are highly infectious when aerosolized and can be used as biological weapons. Vaccines and therapeutics are urgently needed, but efficacy determination requires animal models. The cynomolgus macaque (Macaca fascicularis) provides a relevant model of human disease, but questions remain whether vaccines or therapeutics can mitigate CNS infection or disease in this model. The documentation of alphavirus encephalitis in animals relies on traditional physiological biomarkers and behavioral/neurological observations by veterinary staff; quantitative measurements such as electroencephalography (EEG) and intracranial pressure (ICP) can recapitulate underlying encephalitic processes. We detail a telemetry implantation method suitable for continuous monitoring of both EEG and ICP in awake macaques, as well as methods for collection and analysis of such data. We sought to evaluate whether changes in EEG/ICP suggestive of CNS penetration by virus would be seen after aerosol exposure of naive macaques to VEEV IC INH9813 or EEEV V105 strains compared to mock-infection in a cohort of twelve adult cynomolgus macaques. Data collection ran continuously from at least four days preceding aerosol exposure and up to 50 days thereafter. EEG signals were processed into frequency spectrum bands (delta: [0.4 - 4Hz); theta: [4 - 8Hz); alpha: [8-12Hz); beta: [12-30] Hz) and assessed for viral encephalitis-associated changes against robust background circadian variation while ICP data was assessed for signal fidelity, circadian variability, and for meaningful differences during encephalitis. Results indicated differences in delta, alpha, and beta band magnitude in infected macaques, disrupted circadian rhythm, and proportional increases in ICP in response to alphavirus infection. This novel enhancement of the cynomolgus macaque model offers utility for timely determination of onset, severity, and resolution of encephalitic disease and for the evaluation of vaccine and therapeutic candidates.
Five direct behavior rating multi-item scales: Sensitivity to the effects of classroom interventions

Direct Behavior Rating (DBR) is a tool designed for the assessment of behavioral changes over time. Unlike methods for summative evaluations, the development of progress monitoring tools requires evaluation of sensitivity to change. The present study aimed to evaluate this psychometric feature of five newly developed DBR Multi-Item Scales (DBR-MIS). Teachers identified students with behaviors interfering with their learning or the learning of others and implemented a Daily Report Card (DRC) intervention in the classroom settings for two months. The analyses were performed on 31 AB single case studies. Change metrics were calculated at an individual level by using Tau-UA vs. B + trend B and Hedges' g and at a scale-level by using Mixed Effect Meta-Analysis, Hierarchical Linear Models (HLMs), and Between-Case Standardized Mean Difference (BC-SMD). HLMs were estimated considering both fixed and random effects of intervention and linear trend within the intervention phase. The results supported sensitivity to change for three DBR-MIS (i.e., Academic Engagement, Organizational Skills, and Disruptive Behavior), and the relative magnitudes were consistent across the metrics. Sensitivity to change of DBR-MIS Interpersonal Skills received moderate support. Conversely, empirical evidence was not provided for sensitivity to change of DBR-MIS Oppositional Behavior. Particular emphasis was placed on the intervention trend in that responses to behavioral interventions might occur gradually or require consistency over time in order to be observed by raters. Implications for the use of the new DBR-MIS in the context of progress monitoring of social-emotional behaviors are discussed.
Coupled Control Systems: Periodic Orbit Generation With Application to Quadrupedal Locomotion

A robotic system can be viewed as a collection of lower-dimensional systems that are coupled via reaction forces (Lagrange multipliers) enforcing holonomic constraints. Inspired by this viewpoint, this letter presents a novel formulation for nonlinear control systems that are subject to coupling constraints via virtual “coupling” inputs that abstractly play the role of Lagrange multipliers. The main contribution of this letter is a process—mirroring solving for Lagrange multipliers in robotic systems—wherein we isolate subsystems free of coupling constraints that provably encode the full-order dynamics of the coupled control system from which it was derived. This dimension reduction is leveraged in the formulation of a nonlinear optimization problem for the isolated subsystem that yields periodic orbits for the full-order coupled system. We consider the application of these ideas to robotic systems, which can be decomposed into subsystems. Specifically, we view a quadruped as a coupled control system consisting of two bipedal robots, wherein applying the framework developed allows for gaits (periodic orbits) to be generated for the individual biped yielding a gait for the full-order quadrupedal dynamics. This is demonstrated on a quadrupedal robot through simulation and walking experiments on rough terrains.
Perfect Soliton Crystals on Demand

We report the on-demand generation of perfect soliton crystals in a LiNbO 3 microresonator, with an arbitrary dialing of the comb line spacing from 1 to 11 times of the free-spectral range of the resonator.
An Uplink Control Channel Design With Complementary Sequences for Unlicensed Bands

In this paper, two modulation schemes based on complementary sequences (CSs) are proposed for uplink control channels in unlicensed bands. These schemes address high peak-to-average-power ratio (PAPR) under non-contiguous resource allocation in the frequency domain and reduce the maximum PAPR to 3 dB. The first scheme allows the users to transmit a small amount of uplink control information (UCI) such as acknowledgment signals and does not introduce a trade-off between PAPR and co-channel interference (CCI). The second scheme, which enables up to 21 UCI bits for a single user or 11 UCI bits for three users in an interlace, is based on a new theorem introduced in this paper. This theorem leads distinct CSs compatible with a wide variety of resource allocations while capturing the inherent relationship between CSs and Reed-Muller (RM) codes, which makes CSs more useful for practical systems. The numerical results show that the proposed schemes maintain the low-PAPR benefits without increasing the error rate for non-contiguous resource allocations in the frequency domain.
On the quantum complexity of closest pair and related problems

The closest pair problem is a fundamental problem of computational geometry: given a set of n points in a d-dimensional space, find a pair with the smallest distance. A classical algorithm taught in introductory courses solves this problem in O(n log n) time in constant dimensions (i.e., when d = O(1)). This paper asks and answers the question of the problem's quantum time complexity. Specifically, we give an O(n2/3) algorithm in constant dimensions, which is optimal up to a polylogarithmic factor by the lower bound on the quantum query complexity of element distinctness. The key to our algorithm is an efficient history-independent data structure that supports quantum interference.In polylog(n) dimensions, no known quantum algorithms perform better than brute force search, with a quadratic speedup provided by Grover's algorithm. To give evidence that the quadratic speedup is nearly optimal, we initiate the study of quantum fine-grained complexity and introduce the Quantum Strong Exponential Time Hypothesis (QSETH), which is based on the assumption that Grover's algorithm is optimal for CNF-SAT when the clause width is large. We show that the naive Grover approach to closest pair in higher dimensions is optimal up to an no(1) factor unless QSETH is false. We also study the bichromatic closest pair problem and the orthogonal vectors problem, with broadly similar results.
Private Information Delivery

We introduce the problem of private information delivery (PID), comprised of $K$ messages, a user, and $N$ servers (each holds $M\leq K$ messages) that wish to deliver one out of $K$ messages to the user privately, i.e., without revealing the delivered message index to the user. The information theoretic capacity of PID, $C$ , is defined as the maximum number of bits of the desired message that can be privately delivered per bit of total communication to the user. For the PID problem with $K$ messages, $N$ servers, $M$ messages stored per server, and $N \geq \lceil \frac {K}{M} \rceil $ , we provide an achievable scheme of rate $1/\lceil \frac {K}{M} \rceil $ and an information theoretic converse of rate $M/K$ , i.e., the PID capacity satisfies $1/\lceil \frac {K}{M} \rceil \leq C \leq M/K$ . This settles the capacity of PID when $\frac {K}{M}$ is an integer. When $\frac {K}{M}$ is not an integer, we show that the converse rate of $M/K$ is achievable if $N \geq \frac {K}{\gcd (K,M)} - \left({\frac {M}{\gcd (K,M)}-1}\right)\left({\lfloor \frac {K}{M} \rfloor -1}\right)$ , and the achievable rate of $1/\lceil \frac {K}{M} \rceil $ is optimal if $N = \lceil \frac {K}{M} \rceil $ . Otherwise if $\lceil \frac {K}{M} \rceil , we give an improved achievable scheme and prove its optimality for several small settings.
Medial Axis Isoperimetric Profiles

Recently proposed as a stable means of evaluating geometric compactness, the isoperimetric profile of a planar domain measures the minimum perimeter needed to inscribe a shape with prescribed area varying from 0 to the area of the domain. While this profile has proven valuable for evaluating properties of geographic partitions, existing algorithms for its computation rely on aggressive approximations and are still computationally expensive. In this paper, we propose a practical means of approximating the isoperimetric profile and show that for domains satisfying a "thick neck" condition, our approximation is exact. For more general domains, we show that our bound is still exact within a conservative regime and is otherwise an upper bound. Our method is based on a traversal of the medial axis which produces efficient and robust results. We compare our technique with the state-of-the-art approximation to the isoperimetric profile on a variety of domains and show significantly tighter bounds than were previously achievable.
Wireless Federated Learning with Local Differential Privacy

In this paper, we study the problem of federated learning (FL) over a wireless channel, modeled by a Gaussian multiple access channel (MAC), subject to local differential privacy (LDP) constraints. We show that the superposition nature of the wireless channel provides a dual benefit of bandwidth efficient gradient aggregation, in conjunction with strong LDP guarantees for the users. We propose a private wireless gradient aggregation scheme, which shows that when aggregating gradients from K users, the privacy leakage per user scales as $\mathcal{O}\left( {\frac{1}{{\sqrt K }}} \right)$ compared to orthogonal transmission in which the privacy leakage scales as a constant. We also present analysis for the convergence rate of the proposed private FL aggregation algorithm and study the tradeoffs between wireless resources, convergence, and privacy.
Development of an inexpensive Raman-compatible substrate for the construction of a microarray screening platform

Biomaterial microarrays are being developed to facilitate identifying the extrinsic cues that elicit stem cell fate decisions to self-renew, differentiate and remain quiescent. Raman microspectroscopy, often combined with multivariate analysis techniques such as partial least square-discriminant analysis (PLS-DA), could enable the non-invasive identification of stem cell fate decisions made in response to extrinsic cues presented at specific locations on these microarrays. Because existing biomaterial microarrays are not compatible with Raman microspectroscopy, here, we develop an inexpensive substrate that is compatible with both single-cell Raman spectroscopy and the chemistries that are often used for biomaterial microarray fabrication. Standard deposition techniques were used to fabricate a custom Raman-compatible substrate that supports microarray construction. We validated that spectra from living cells on functionalized polyacrylamide (PA) gels attached to the custom Raman-compatible substrate are comparable to spectra acquired from a more expensive commercially available substrate. We also showed that the spectra acquired from individual living cells on functionalized PA gels attached to our custom substrates were of sufficient quality to enable accurate identification of cell phenotypes using PLS-DA models of the cell spectra. We demonstrated this by using cells from laboratory lines (CHO and transfected CHO cells) as well as adult stem cells that were freshly isolated from mice (long-term and short-term hematopoietic stem cells). The custom Raman-compatible substrate reported herein may be used as an inexpensive substrate for constructing biomaterial microarrays that enable the use of Raman microspectroscopy to non-invasively identify the fate decisions of stem cells in response to extrinsic cues.
Approximation Algorithms for D-optimal Design

Experimental design is a classical statistics problem, and its aim is to estimate an unknown vector from linear measurements where a Gaussian noise is introduced in each measurement. For the combin...
Efficacy of uncovered colonic stents for extrinsic versus intrinsic malignant large bowel obstruction

Previous studies evaluating self-expandable metal stents (SEMS) for management of malignant extrinsic colon obstruction have yielded conflicting results. We evaluated the efficacy of uncovered SEMS for extrinsic colon malignancy (ECM) versus intrinsic colon malignancy (ICM). Retrospective review of all patients referred for colonic SEMS at a tertiary cancer center between 2007 and 2018 was performed. Primary outcome measures were technical success, clinical success, intervention rate, and overall survival. 138 patients with ECM and 119 patients with ICM underwent attempted stent placement. The rectum and/or sigmoid colon was the most common stricture site. Technical success was lower in the ECM group [86% vs 96% (p = .009)]. Clinical success was lower in the ECM group both at 7 days [82% vs 95% (p = .004)] and at 90 days [60% vs 86% (p < .001)]. Subsequent intervention was required more frequently [44% vs 35%; p = .23] and earlier [median 9 vs 132 days; p < .001] in the ECM group. Median overall survival in the ECM group was 92 vs 167 days. Among predictive variables analyzed, the ECM group had a higher frequency of peritoneal metastasis (87% vs 32%; p < .001), multifocal strictures with requirement for multiple stents (20% vs 6%; p = .002), sharp angulated strictures (39% vs 25%; p = .04) , and radiation therapy (21% vs 10%; p = .02). Colonic SEMS for ECM is associated with lower technical and clinical success with earlier intervention rates compared with ICM. Our findings can be used to better inform patients and referring providers as well as guide new stent design to enhance efficacy in this population.
Sharing of Climate Risks across World Regions

Climate change impacts are stochastic and highly uncertain and moreover heterogeneous across regions. That is, there is a potential to sharing this risk ex-ante across regions and hence to reduce t...
Deep Sigma Point Processes.

We introduce Deep Sigma Point Processes, a class of parametric models inspired by the compositional structure of Deep Gaussian Processes (DGPs). Deep Sigma Point Processes (DSPPs) retain many of the attractive features of (variational) DGPs, including mini-batch training and predictive uncertainty that is controlled by kernel basis functions. Importantly, since DSPPs admit a simple maximum likelihood inference procedure, the resulting predictive distributions are not degraded by any posterior approximations. In an extensive empirical comparison on univariate and multivariate regression tasks we find that the resulting predictive distributions are significantly better calibrated than those obtained with other probabilistic methods for scalable regression, including variational DGPs--often by as much as a nat per datapoint.
A sharp necessary condition for rectifiable curves in metric spaces

In his 1990 Inventiones paper, P. Jones characterized subsets of rectifiable curves in the plane, using a multiscale sum of what is now known as Jones β -numbers, numbers measuring flatness in a given scale and location. This work was generalized to Rn by Okikiolu, to Hilbert space by the second author, and has many variants in a variety of metric settings. Notably, in 2005, Hahlomaa gave a sufficient condition for a subset of a metric space to be contained in a rectifiable curve. We prove the sharpest possible converse to Hahlomaa’s theorem for doubling curves, and then deduce some corollaries for subsets of metric and Banach spaces, as well as the Heisenberg group.
Logical Signal Processing: A Fourier Analysis of Temporal Logic

What is the frequency content of temporal logic formulas? That is, when we monitor a signal against a formula, which frequency bands of the signal are relevant to the logic and should be preserved, and which can be safely discarded? This question is relevant whenever signals are filtered or compressed before being monitored, which is almost always the case for analog signals. To answer this question, we focus on monitors that measure the robustness of a signal relative to a specification in Signal Temporal Logic. We prove that robustness monitors can be modeled using Volterra series. We then study the Fourier transforms of these Volterra representations, and provide a method to derive the Fourier transforms of entire formulas. We also make explicit the measurement process in temporal logic and re-define it on the basis of distributions to make it compatible with measurements in signal processing. Experiments illustrate these results. Beyond compression, this work enables the integration of temporal logic monitoring into common signal processing tool chains as just another signal processing operation, and enables a common formalism to study both logical and non-logical operations in the frequency domain, which we refer to as Logical Signal Processing.
Understanding climate change over the southwestern Mediterranean using high-resolution simulations

The severe wintertime precipitation decline projected by global climate models (GCMs) over the Southwestern Mediterranean makes this region a major climate change hotspot. Here, we evaluate the performance of the MIT Regional Climate Model (MRCM) in simulating seasonal and inter-annual regional climatic features over Northwestern Africa and the Iberian Peninsula (NWAIP), and develop and interpret regional climate change projections over the same region under the RCP4.5 and 8.5 scenarios, at a resolution of 12 km, driven by three carefully selected GCMs. MRCM succeeds in correctly capturing the spatio-temporal patterns of precipitation when forced by ERA-Interim reanalysis data. In addition to substantial year-round warming, the MRCM ensemble projects a significant decline in precipitation during winter and spring under continued anthropogenic forcing. Even with significant climate change mitigation, the drying is relatively large, with an average of − 34% in precipitation over Morocco’s three main watersheds during spring, and − 22% during winter. Projections for the Iberian Peninsula are less severe, though drying trends are still robust. The consistency of the precipitation projections is discussed in the light of physical mechanisms acting at the regional scale. Being located downwind of a large desert, the region is particularly vulnerable to the changes in circulation projected by global models. The latter will advect dry air from the Sahara, which will suppress precipitation. The local topography also contributes to these trends. Overall, our results elucidate the physical processes responsible for winter and spring drying in the southwestern Mediterranean.
Deep Representation Learning for Multimodal Brain Networks

Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology, for an individual brain, mining a discriminative network representation from the multimodal brain networks is non-trivial. The recent success of deep learning techniques on graph-structured data suggests a new way to model the non-linear cross-modality relationship. However, current deep brain network methods either ignore the intrinsic graph topology or require a network basis shared within a group. To address these challenges, we propose a novel end-to-end deep graph representation learning (Deep Multimodal Brain Networks - DMBN) to fuse multimodal brain networks. Specifically, we decipher the cross-modality relationship through a graph encoding and decoding process. The higher-order network mappings from brain structural networks to functional networks are learned in the node domain. The learned network representation is a set of node features that are informative to induce brain saliency maps in a supervised manner. We test our framework in both synthetic and real image data. The experimental results show the superiority of the proposed method over some other state-of-the-art deep brain network models.
The physical mechanisms of fast radio bursts.

Fast radio bursts are mysterious millisecond-duration transients prevalent in the radio sky. Rapid accumulation of data in recent years has facilitated an understanding of the underlying physical mechanisms of these events. Knowledge gained from the neighbouring fields of gamma-ray bursts and radio pulsars has also offered insights. Here I review developments in this fast-moving field. Two generic categories of radiation model invoking either magnetospheres of compact objects (neutron stars or black holes) or relativistic shocks launched from such objects have been much debated. The recent detection of a Galactic fast radio burst in association with a soft gamma-ray repeater suggests that magnetar engines can produce at least some, and probably all, fast radio bursts. Other engines that could produce fast radio bursts are not required, but are also not impossible. The mechanisms and origins of fast radio bursts are reviewed in connection with data and insights from the neighbouring fields of gamma-ray bursts and radio pulsars.
First-passage properties of the Pólya urn process

We study first-passage statistics of the Polya urn model. In this random process, the urn contains balls of two types. In each step, one ball is drawn randomly from the urn, and subsequently placed back into the urn together with an additional ball of the same type. We derive the probability Gn that the balls of the two types become equal in number, for the first time, when there are a total of 2n balls. This first-passage probability decays algebraically, Gn ~ n − 2, when n is large. We also derive the probability that a tie ever happens. This probability is between zero and one, so a tie may occur in some realizations but not in others. The likelihood of a tie is appreciable only if the initial difference in the number of balls is of the order of the square root of the total number of balls.
Observational Nonstationarity of AGN Variability: The Only Way to Go Is Down!

To gain insights into long-term Active Galactic Nuclei (AGN) variability, we analyze an AGN sample from the Sloan Digital Sky Survey (SDSS) and compare their photometry with observations from the Hyper Suprime-Cam survey (HSC) observed $\langle 14.85 \rangle$ years after SDSS. On average, the AGN are fainter in HSC than SDSS. We demonstrate that the difference is not due to subtle differences in the SDSS versus HSC filters or photometry. The decrease in mean brightness is redshift dependent, consistent with expectations for a change that is a function of the rest-frame time separation between observations. At a given redshift, the mean decrease in brightness is stronger for more luminous AGN and for objects with longer time separation between measurements. We demonstrate that the dependence on redshift and luminosity of measured mean brightness decrease is consistent with simple models of Eddington ratio variability in AGN on long (Myr, Gyr) timescales. We show how our results can be used to constrain the variability and demographic properties of AGN populations.
Stability of Twisted States in the Kuramoto Model on Cayley and Random Graphs

The Kuramoto model of coupled phase oscillators on complete, Paley, and Erdős–Renyi (ER) graphs is analyzed in this work. As quasirandom graphs, the complete, Paley, and ER graphs share many structural properties. For instance, they exhibit the same asymptotics of the edge distributions, homomorphism densities, graph spectra, and have constant graph limits. Nonetheless, we show that the asymptotic behavior of solutions in the Kuramoto model on these graphs can be qualitatively different. Specifically, we identify twisted states, steady-state solutions of the Kuramoto model on complete and Paley graphs, which are stable for one family of graphs but not for the other. On the other hand, we show that the solutions of the initial value problems for the Kuramoto model on complete and random graphs remain close on finite time intervals, provided they start from close initial conditions and the graphs are sufficiently large. Therefore, the results of this paper elucidate the relation between the network structure and dynamics in coupled nonlinear dynamical systems. Furthermore, we present new results on synchronization and stability of twisted states for the Kuramoto model on Cayley and random graphs.
Fourier Analysis of Blazar Variability

Blazars display strong variability on multiple timescales and in multiple radiation bands. Their variability is often characterized by power spectral densities (PSDs) and time lags plotted as functions of the Fourier frequency. We develop a new theoretical model based on the analysis of the electron transport (continuity) equation, carried out in the Fourier domain. The continuity equation includes electron cooling and escape, and a derivation of the emission properties includes light travel time effects associated with a radiating blob in a relativistic jet. The model successfully reproduces the general shapes of the observed PSDs and predicts specific PSD and time lag behaviors associated with variability in the synchrotron, synchrotron self-Compton (SSC), and external Compton (EC) emission components, from sub-mm to γ-rays. We discuss applications to BL Lacertae objects and to flat-spectrum radio quasars (FSRQs), where there are hints that some of the predicted features have already been observed. We also find that FSRQs should have steeper PSD power-law indices than BL Lac objects at Fourier frequencies . 10 −4 Hz, in qualitative agreement with previously reported observations by the Fermi Large Area Telescope. Subject headings: BL Lacertae objects: general — quasars: general — radiation mechanisms: nonthermal — galaxies: active — galaxies: jets
Exact distribution of the Generalized Shiryaev–Roberts stopping time under the minimax Brownian motion setup

ABSTRACTWe consider the quickest change-point detection problem where the aim is to detect the onset of a prespecified drift in “live”-monitored standard Brownian motion; the change-point is assumed unknown (nonrandom). The object of interest is the distribution of the stopping time associated with the Generalized Shryaev–Roberts (GSR) detection procedure set up to “sense” the presence of the drift in the Brownian motion under surveillance. Specifically, we seek the GSR stopping time's survival function (the tail probability that no alarm is triggered by the GSR procedure prior to a given point in time), and distinguish two scenarios: (a) when the drift never sets in (prechange regime) and (b) when the drift is in effect ab initio (postchange regime). Under each scenario, we obtain a closed-form formula for the respective survival function, with the GSR statistic's (deterministic) nonnegative headstart assumed arbitrarily given. The two formulae are found analytically, through direct solution of the respe...
Rescuing the nonjet (NJ) azimuth quadrupole from the flow narrative

According to the flow narrative commonly applied to high-energy nuclear collisions a cylindrical-quadrupole component of 1D azimuth angular correlations is conventionally denoted by quantity υ 2 and interpreted to represent elliptic flow. Jet angular correlations may also contribute to υ 2 data “nonflow” depending on the method used to calculate υ 2 , but 2D graphical methods are available to insure accurate separation. The nonjet (NJ) quadrupole has various properties inconsistent with a flow interpretation, including the observation that NJ quadrupole centrality variation in A-A collisions has no relation to strongly-varying jet modication (“jet quenching”) in those collisions commonly attributed to jet interaction with a flowing dense medium. In this presentation I describe isolation of quadrupole spectra from pt-differential υ 2 (pt ) data from the RHIC and LHC. I demonstrate that quadrupole spectra have characteristics very different from the single-particle spectra for most hadrons, that quadrupole spectra indicate a common boosted hadron source for a small minority of hadrons that “carry” the NJ quadrupole structure, that the narrow source-boost distribution is characteristic of an expanding thin cylindrical shell (strongly contradicting hydro descriptions), and that in the boost frame a single universal quadrupole spectrum (Levy distribution) on transverse mass mt accurately describes data for several hadron species scaled according to their statistical-model abundances. The quadrupole spectrum shape changes very little from RHIC to LHC energies. Taken in combination those characteristics strongly suggest a unique nonflow (and nonjet) QCD mechanism for the NJ quadrupole conventionally represented by υ 2 .
Machine Translation System Selection from Bandit Feedback

Adapting machine translation systems in the real world is a difficult problem. In contrast to offline training, users cannot provide the type of fine-grained feedback (such as correct translations) typically used for improving the system. Moreover, different users have different translation needs, and even a single user's needs may change over time. In this work we take a different approach, treating the problem of adaptation as one of selection. Instead of adapting a single system, we train many translation systems using different architectures, datasets, and optimization methods. Using bandit learning techniques on simulated user feedback, we learn a policy to choose which system to use for a particular translation task. We show that our approach can (1) quickly adapt to address domain changes in translation tasks, (2) outperform the single best system in mixed-domain translation tasks, and (3) make effective instance-specific decisions when using contextual bandit strategies.
Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic Policies

Offline reinforcement learning, wherein one uses off-policy data logged by a fixed behavior policy to evaluate and learn new policies, is crucial in applications where experimentation is limited such as medicine. We study the estimation of policy value and gradient of a deterministic policy from off-policy data when actions are continuous. Targeting deterministic policies, for which action is a deterministic function of state, is crucial since optimal policies are always deterministic (up to ties). In this setting, standard importance sampling and doubly robust estimators for policy value and gradient fail because the density ratio does not exist. To circumvent this issue, we propose several new doubly robust estimators based on different kernelization approaches. We analyze the asymptotic mean-squared error of each of these under mild rate conditions for nuisance estimators. Specifically, we demonstrate how to obtain a rate that is independent of the horizon length.
Proof of the Ergodic Hypothesis for Typical Hard Ball Systems

We consider the system of $$ N (\geq 2) $$ hard balls with masses $$ m_{1}, \ldots, m_{N} $$ and radius r in the flat torus $$ \mathbb{T}_{L}^{\nu} = \mathbb{R}^{\nu} / L \cdot \mathbb{Z}^{\nu} $$ of size $$ L, \nu \geq 3 $$ . We prove the ergodicity (actually, the Bernoulli mixing property) of such systems for almost every selection $$ (m_{1}, \ldots, m_{N}; L) $$ of the outer geometric parameters. This theorem complements my earlier result that proved the same, almost sure ergodicity for the case $$ \nu = 2 $$ . The method of that proof was primarily dynamical-geometric, whereas the present approach is inherently algebraic.
On multilinear oscillatory integrals, nonsingular and singular

Basic questions concerning nonsingular multilinear operators with oscillatory factors are posed and partially answered. L p norm inequalities are established for multilinear integral operators of Calderon-Zygmund type which incorporate oscillatory factors e i P , where P is a real-valued polynomial
Building an Optimal Census of the Solar Neighborhood with Pan-STARRS Data

We estimate the fidelity of solar neighborhood (D 5 combined with a proper-motion cut ranging from μ/σμ > 1-8 achieves 99% reliability and 60% completeness.
FREE FERMIONIC HETEROTIC MODEL BUILDING AND ROOT SYSTEMS

We consider an alternative derivation of the GSO Projection in the free fermionic construction of the weakly coupled heterotic string in terms of root systems, as well as the interpretation of the GSO Projection in this picture. We then present an algorithm to systematically and efficiently generate input sets (i.e. basic vectors) in order to study landscape statistics with minimal computational cost. For example, the improvement at order 6 is ≈10-13 over a traditional brute force approach, and improvement increases with order. We then consider an example of statistics on a relatively simple class of models.
Spin-Driven Emergent Antiferromagnetism and Metal-Insulator Transition in Nanoscale p-Si

The entanglement of the charge, spin and orbital degrees of freedom can give rise to emergent behavior especially in thin films, surfaces and interfaces. Often, materials that exhibit those properties require large spin orbit coupling. We hypothesize that the emergent behavior can also occur due to spin, electron and phonon interactions in widely studied simple materials such as Si. That is, large intrinsic spin-orbit coupling is not an essential requirement for emergent behavior. The central hypothesis is that when one of the specimen dimensions is of the same order (or smaller) as the spin diffusion length, then non-equilibrium spin accumulation due to spin injection or spin-Hall effect (SHE) will lead to emergent phase transformations in the non-ferromagnetic semiconductors. In this experimental work, we report spin mediated emergent antiferromagnetism and metal insulator transition in a Pd (1 nm)/Ni81Fe19 (25 nm)/MgO (1 nm)/p-Si (~400 nm) thin film specimen. The spin-Hall effect in p-Si, observed through Rashba spin-orbit coupling mediated spin-Hall magnetoresistance behavior, is proposed to cause the spin accumulation and resulting emergent behavior. The phase transition is discovered from the diverging behavior in longitudinal third harmonic voltage, which is related to the thermal conductivity and heat capacity.
Comparing instanton contributions with exact results in N=2 supersymmetric scale invariant theories

We discuss the general issues and ambiguities involved in matching the exact results for the low energy effective action of scale invariant = 2 supersymmetric QCD to those obtained by instanton methods. We resolve the reported disagreements and verify agreement between an infinite series of coefficients in the low energy effective actions calculated in the two approaches. In particular, we show that the exact low-energy effective couplings for SU(N) for all N with 2N fundamental hypermultiplets agree at a special vacuum on the Coulomb branch where a large unbroken discrete global symmetry makes the matching of parameters relatively straightforward.
Resolving the Sub-AU-scale Gas and Dust Distribution in FU Orionis Sources

We present Keck Interferometer observations of the three prototypical FU Orionis stars, FU Ori, V1057 Cyg, and V1515 Cyg. With a spatial resolution of a few milliarcseconds and a spectral resolution of λ/Δλ = 2000, our near-infrared observations spatially resolve gas and dust emission extending from stellocentric radii of ~0.05 AU to several AU. We fit these data with accretion disk models where each stellocentric radius of the disk is represented by a supergiant-type stellar emission spectrum at the disk temperature. A disk model is consistent with the data for FU Ori, although we require some local asymmetry in the disk. For V1057 Cyg the disk model does not fit our data well, especially compared to the fit quality achieved for FU Ori. We speculate that a disk wind may be contributing substantially to the observed near-IR emission in this source. The data for V1515 Cyg are noisier than the data obtained for the other two objects and do not strongly constrain the validity of an accretion disk model.
A High-Resolution Study of the Slowly Contracting, Starless Core L1544

We present interferometric observations of N2H+ (1-0) in the starless, dense core L1544 in Taurus. Redshifted self-absorption, indicative of inward motions, is found toward the center of an elongated core. The data are fit by a nonspherical model consisting of two isothermal, rotating, centrally condensed layers. Through a hybrid global-individual fit to the spectra, we map the variation of infall speed at scales ~1400 AU and find values ~0.08 km s-1 around the core center. The inward motions are small in comparison to thermal, rotational, and gravitational speeds but are large enough to suggest that L1544 is very close to forming a star.
Coarse-grained modeling of DNA curvature

The interaction of DNA with proteins occurs over a wide range of length scales, and depends critically on its local structure. In particular, recent experimental work suggests that the intrinsic curvature of DNA plays a significant role on its protein-binding properties. In this work, we present a coarse grained model of DNA that is capable of describing base-pairing, hybridization, major and minor groove widths, and local curvature. The model represents an extension of the recently proposed 3SPN.2 description of DNA [D. M. Hinckley, G. S. Freeman, J. K. Whitmer, and J. J. de Pablo, J. Chem. Phys. 139, 144903 (2013)], into which sequence-dependent shape and mechanical properties are incorporated. The proposed model is validated against experimental data including melting temperatures, local flexibilities, dsDNA persistence lengths, and minor groove width profiles.
Epimorphisms and boundary slopes of 2–bridge knots

In this article we study a partial ordering on knots in S 3 where K1 K2 if there is an epimorphism from the knot group of K1 onto the knot group of K2 which preserves peripheral structure. If K1 is a 2‐bridge knot and K1 K2 , then it is known that K2 must also be 2‐bridge. Furthermore, Ohtsuki, Riley and Sakuma give a construction which, for a given 2‐bridge knot Kp=q , produces infinitely many 2‐bridge knots Kp0=q0 with Kp0=q0 Kp=q . After characterizing all 2‐bridge knots with 4 or less distinct boundary slopes, we use this to prove that in any such pair, Kp0=q0 is either a torus knot or has 5 or more distinct boundary slopes. We also prove that 2‐bridge knots with exactly 3 distinct boundary slopes are minimal with respect to the partial ordering. This result provides some evidence for the conjecture that all pairs of 2‐bridge knots with Kp0=q0 Kp=q arise from the Ohtsuki‐Riley‐Sakuma construction. 57M25
Discovery and information-theoretic characterization of transcription factor binding sites that act cooperatively

Transcription factor binding to the surface of DNA regulatory regions is one of the primary causes of regulating gene expression levels. A probabilistic approach to model protein-DNA interactions at the sequence level is through position weight matrices (PWMs) that estimate the joint probability of a DNA binding site sequence by assuming positional independence within the DNA sequence. Here we construct conditional PWMs that depend on the motif signatures in the flanking DNA sequence, by conditioning known binding site loci on the presence or absence of additional binding sites in the flanking sequence of each site's locus. Pooling known sites with similar flanking sequence patterns allows for the estimation of the conditional distribution function over the binding site sequences. We apply our model to the Dorsal transcription factor binding sites active in patterning the Dorsal-Ventral axis of Drosophila development. We find that those binding sites that cooperate with nearby Twist sites on average contain about 0.5 bits of information about the presence of Twist transcription factor binding sites in the flanking sequence. We also find that Dorsal binding site detectors conditioned on flanking sequence information make better predictions about what is a Dorsal site relative to background DNA than detection without information about flanking sequence features.
Tilings of hexagons with a removed triad of bowties

Abstract In this paper we consider arbitrary hexagons on the triangular lattice with three arbitrary bowtie-shaped holes, whose centers form an equilateral triangle. The number of lozenge tilings of such general regions is not expected — and indeed is not — given by a simple product formula. However, when considering a certain natural normalized counterpart R of any such region R, we prove that the ratio between the number of tilings of R and the number of tilings of R is given by a simple, conceptual product formula. Several seemingly unrelated previous results from the literature — including Lai's formula for hexagons with three dents and Ciucu and Krattenthaler's formula for hexagons with a removed shamrock — follow as immediate special cases of our result.
An Algorithmic Approach to Limit Cycles of Nonlinear Differential Systems: The Averaging Method Revisited

This paper introduces an algorithmic approach to the analysis of bifurcation of limit cycles from the centers of nonlinear continuous differential systems via the averaging method. We develop three algorithms to implement the averaging method. The first algorithm allows to transform the considered differential systems to the normal formal of averaging. Here, we restricted the unperturbed term of the normal form of averaging to be identically zero. The second algorithm is used to derive the computational formulae of the averaged functions at any order. The third algorithm is based on the first two algorithms that determines the exact expressions of the averaged functions for the considered differential systems. The proposed approach is implemented in Maple and its effectiveness is shown by several examples. Moreover, we report some incorrect results in published papers on the averaging method.