cssi/SciSciGPT-SciSciNet huggingface dataset:
Polarization and Public Health: Partisan Differences in Social Distancing during the Coronavirus Pandemic.

We study partisan differences in Americans' response to the COVID-19 pandemic. Political leaders and media outlets on the right and left have sent divergent messages about the severity of the crisis, which could impact the extent to which Republicans and Democrats engage in social distancing and other efforts to reduce disease transmission. We develop a simple model of a pandemic response with heterogeneous agents that clarifies the causes and consequences of heterogeneous responses. We use location data from a large sample of smartphones to show that areas with more Republicans engaged in less social distancing, controlling for other factors including public policies, population density, and local COVID cases and deaths. We then present new survey evidence of significant gaps at the individual level between Republicans and Democrats in self-reported social distancing, beliefs about personal COVID risk, and beliefs about the future severity of the pandemic.
Correction to: The International Conference on Intelligent Biology and Medicine 2019: computational methods for drug interactions

After publication of this supplement article [1], it is requested the grant ID in the Funding section should be corrected from NSF grant IIS-7811367 to NSF grant IIS-1902617.
Deep learning for ranking response surfaces with applications to optimal stopping problems

In this paper, we propose deep learning algorithms for ranking response surfaces with applications to optimal stopping problems in financial mathematics. The problem of ranking response surfaces is...
Why We (Probably) Must Deliberately Infect

In the griof a pandemic of proportions that have not been seen for generations, some have proposed conducting â€œhuman challengeâ€ vaccine trials in which health
Implementation Considerations in a Numerical Analysis Problem Solving System

It has become apparent in the last few years that while general-purpose, problem-oriented computer languages have greatly eased the man--machine communication problem, a great deal remains to be accomplished if the computer is to realize its full potential.
Predicting The Outcome of Marketing Negotiations: Role-Playing versus Unaided Opinions

Role -playing and unaided opinions were used to forecast the outcome of three negotiations. Consistent with prior re search, role-playing yielded more accurate predictions. In two studies on marketing negotiations, the predictions based on role-playing were correct for 53% of the predictions while unaided opinions were correct for only 7% (p < 0.001).
Competition as a savings incentive: A field experiment at a homeless shelter

Abstract This paper describes a randomized field experiment testing the impact of a savings competition on the behavior of homeless individuals staying at a transitional shelter. When monetary prizes were offered for achieving the highest saving rates within a particular month, average savings increased by $80 (a 30% increase in savings rate) while income and attendance at case management meetings remained unchanged. However, repeating the competition in the following month had no effect because responsive savers selected out of the shelter after the first month. In summary, while a savings competition can increase savings in the short run, its effect may be limited to the intensive margin and may diminish with repetition.
Robust learning in expert networks: a comparative analysis

Human experts as well as autonomous agents in a referral network must decide whether to accept a task or refer to a more appropriate expert, and if so to whom. In order for the referral network to improve over time, the experts must learn to estimate the topical expertise of other experts. This article extends concepts from Multi-agent Reinforcement Learning and Active Learning to referral networks for distributed learning in referral networks. Among a wide array of algorithms evaluated, Distributed Interval Estimation Learning (DIEL), based on Interval Estimation Learning, was found to be superior for learning appropriate referral choices, compared to 𝜖-Greedy, Q-learning, Thompson Sampling and Upper Confidence Bound (UCB) methods. In addition to a synthetic data set, we compare the performance of the stronger learning-to-refer algorithms on a referral network of high-performance Stochastic Local Search (SLS) SAT solvers where expertise does not obey any known parameterized distribution. An evaluation of overall network performance and a robustness analysis is conducted across the learning algorithms, with an emphasis on capacity constraints and evolving networks, where experts with known expertise drop off and new experts of unknown performance enter — situations that arise in real-world scenarios but were heretofore ignored.
First passage time study of DNA strand displacement

Abstract DNA strand displacement, in which a single-stranded nucleic acid invades a DNA duplex, is pervasive in genomic processes and DNA engineering applications. The kinetics of strand displacement have been studied in bulk; however, the kinetics of the underlying strand exchange were obfuscated by a slow bimolecular association step. Here, we use a novel single-molecule fluorescence resonance energy transfer approach termed the “fission” assay to obtain the full distribution of first passage times of unimolecular strand displacement. At a frame time of 4.4 ms, the first passage time distribution for a 14-nucleotide displacement domain exhibited a nearly monotonic decay with little delay. Among the eight different sequences we tested, the mean displacement time was on average 35 ms and varied by up to a factor of 13. The measured displacement kinetics also varied between complementary invaders and between RNA and DNA invaders of the same base sequence, except for T → U substitution. However, displacement times were largely insensitive to the monovalent salt concentration in the range of 0.25–1 M. Using a one-dimensional random walk model, we infer that the single-step displacement time is in the range of ∼30–300 μs, depending on the base identity. The framework presented here is broadly applicable to the kinetic analysis of multistep processes investigated at the single-molecule level.
Operations on Integral Lifts of K(n)

This very rough sketch is a sequel to [27, 28]; it presents evidence that operations on lifts of the functors K(n) to cohomology theories with values in modules over valuation rings \({\mathfrak {o}_L}\) of local number fields, indexed by Lubin–Tate groups of such fields, are extensions of the groups of automorphisms of the associated group laws, by the exterior algebras on the normal bundle to the orbit of the group law in the space of lifts.
Quantifying the Security Cost of Migrating Protocols to Practice

We give a framework for relating the concrete security of a “reference” protocol (say, one appearing in an academic paper) to that of some derived, “real” protocol (say, appearing in a cryptographic standard). It is based on the indifferentiability framework of Maurer, Renner, and Holenstein (MRH), whose application has been exclusively focused upon non-interactive cryptographic primitives, e.g., hash functions and Feistel networks. Our extension of MRH is supported by a clearly defined execution model and two composition lemmata, all formalized in a modern pseudocode language. Together, these allow for precise statements about game-based security properties of cryptographic objects (interactive or not) at various levels of abstraction. As a real-world application, we design and prove tight security bounds for a potential TLS 1.3 extension that integrates the SPAKE2 password-authenticated key-exchange into the handshake.
Preserving injectivity under subgaussian mappings and its application to compressed sensing

Abstract The field of compressed sensing has become a major tool in high-dimensional analysis, with the realization that vectors can be recovered from relatively very few linear measurements as long as the vectors lie in a low-dimensional structure, typically the vectors that are zero in most coordinates with respect to a basis. However, there are many applications where we instead want to recover vectors that are sparse with respect to a dictionary rather than a basis. That is, we assume the vectors are linear combinations of at most s columns of a d × n matrix D, where s is very small relative to n and the columns of D form a (typically overcomplete) spanning set. In this direction, we show that as a matrix D stays bounded away from zero in norm on a set S and a provided map Φ comprised of i.i.d. subgaussian rows has number of measurements at least proportional to the square of w ( D S ) , the Gaussian width of the related set D S , then with high probability the composition Φ D also stays bounded away from zero. As a specific application, we obtain that the null space property of order s is preserved under such subgaussian maps with high probability. Consequently, we obtain stable recovery guarantees for dictionary-sparse signals via the l 1 -synthesis method with only O ( s log ⁡ ( n / s ) ) random measurements and a minimal condition on D, which complements the compressed sensing literature.
Iterated group products and leakage resilience against NC 1 .

We show that if NC 1 6 L, then for every elementof the alternating group At, circuits of depth O(logt) cannot distinguish between a uniform vector over (At) t with product = � and one with product = identity. Combined with a recent construction by the author and Viola in the setting of leakage-resilient cryptography (STOC '13), this gives a compiler that produces circuits withstanding leakage from NC 1 (assuming NC 1 6 L). For context, leakage from NC 1 breaks nearly all previous constructions, and security against leakage from P is impossible. We build on work by Cook and McKenzie (J. Algorithms '87) establishing the rela- tionship between L = logarithmic space and the symmetric group St. Our techniques include a novel algorithmic use of commutators to manipulate the cycle structure of permutations in At.
Homeostatic mechanisms may shape the type and duration of oscillatory modulation

Neural oscillations are observed ubiquitously in the mammalian brain, but their stability is known to be rather variable. Some oscillations are tonic and last for seconds or even minutes. Other oscillations appear as unstable bursts. Likewise, some oscillations rely on excitatory AMPAergic synapses, but others are GABAergic and inhibitory. Why this diversity exists is not clear. We hypothesized Ca2+-dependent homeostasis could be important in finding an explanation. We tested this hypothesis in a highly simplified model of hippocampal neurons. In this model homeostasis profoundly alters the modulatory effect of neural oscillations. Under homeostasis, tonic AMPAergic oscillations actually decrease excitability and desynchronize firing. Tonic oscillations that are synaptically GABAergic-like those in real hippocampus-don't provoke a homeostatic response, however. If our simple model is correct, homeostasis can explain why the theta rhythm in the hippocampus is synaptically inhibitory: GABA has little to no intrinsic homeostatic response and so can preserve the pyramidal cell's natural dynamic range. Based on these results we speculate that homeostasis may explain why AMPAergic oscillations in cortex, and in hippocampus, often appear as bursts. Bursts do not interact with the slow homeostatic time constant and so retain their normal excitatory effect.NEW & NOTEWORTHY The intricate interplay of neuromodulators, like acetylcholine, with homeostasis is well known. The interplay between oscillatory modulation and homeostasis is not. We studied oscillatory modulation and homeostasis for the first time using a simplified model of hippocampus. We report a paradoxical result: Ca-mediated homeostasis causes AMPAergic oscillations to become effectively inhibitory. This result, along with other new observations, means homeostasis might be just as complex and important for oscillations as it is for other neuromodulators.
Neural Topological SLAM for Visual Navigation

This paper studies the problem of image-goal navigation which involves navigating to the location indicated by a goal image in a novel previously unseen environment. To tackle this problem, we design topological representations for space that effectively leverage semantics and afford approximate geometric reasoning. At the heart of our representations are nodes with associated semantic features, that are interconnected using coarse geometric information. We describe supervised learning-based algorithms that can build, maintain and use such representations under noisy actuation. Experimental study in visually and physically realistic simulation suggests that our method builds effective representations that capture structural regularities and efficiently solve long-horizon navigation problems. We observe a relative improvement of more than 50% over existing methods that study this task.
SCDE: Sentence Cloze Dataset with High Quality Distractors From Examinations

We introduce SCDE, a dataset to evaluate the performance of computational models through sentence prediction. SCDE is a human created sentence cloze dataset, collected from public school English examinations. Our task requires a model to fill up multiple blanks in a passage from a shared candidate set with distractors designed by English teachers. Experimental results demonstrate that this task requires the use of non-local, discourse-level context beyond the immediate sentence neighborhood. The blanks require joint solving and significantly impair each other’s context. Furthermore, through ablations, we show that the distractors are of high quality and make the task more challenging. Our experiments show that there is a significant performance gap between advanced models (72%) and humans (87%), encouraging future models to bridge this gap.
Learning Instance Occlusion for Panoptic Segmentation

Panoptic segmentation requires segments of both “things” (countable object instances) and “stuff” (uncountable and amorphous regions) within a single output. A common approach involves the fusion of instance segmentation (for “things”) and semantic segmentation (for “stuff”) into a non-overlapping placement of segments, and resolves overlaps. However, instance ordering with detection confidence do not correlate well with natural occlusion relationship. To resolve this issue, we propose a branch that is tasked with modeling how two instance masks should overlap one another as a binary relation. Our method, named OCFusion, is lightweight but particularly effective in the instance fusion process. OCFusion is trained with the ground truth relation derived automatically from the existing dataset annotations. We obtain state-of-the-art results on COCO and show competitive results on the Cityscapes panoptic segmentation benchmark.
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC

Replica exchange Monte Carlo (reMC), also known as parallel tempering, is an important technique for accelerating the convergence of the conventional Markov Chain Monte Carlo (MCMC) algorithms. However, such a method requires the evaluation of the energy function based on the full dataset and is not scalable to big data. The naive implementation of reMC in mini-batch settings introduces large biases, which cannot be directly extended to the stochastic gradient MCMC (SGMCMC), the standard sampling method for simulating from deep neural networks (DNNs). In this paper, we propose an adaptive replica exchange SGMCMC (reSGMCMC) to automatically correct the bias and study the corresponding properties. The analysis implies an acceleration-accuracy trade-off in the numerical discretization of a Markov jump process in a stochastic environment. Empirically, we test the algorithm through extensive experiments on various setups and obtain the state-of-the-art results on CIFAR10, CIFAR100, and SVHN in both supervised learning and semi-supervised learning tasks.
Bit-Interleaved Coded Multiple Beamforming in Millimeter-Wave Massive MIMO Systems

An analysis of the diversity gain for bit-interleaved coded multiple beamforming (BICMB) method in millimeter-wave (mm-Wave) massive multiple-input multiple-output (MIMO) systems is carried out for both the single-user and multi-user scenarios. We show that full diversity gain and full spatial multiplexing order can be achieved in both scenarios. Also, we show that the diversity gain in the multi-user scenario is independent of the number of users in the system. The assumption here is that the channel state information (CSI) is known at both sides of the transmitter and the receiver and the number of antennas in each remote antenna unit (RAU) tends to infinity. Based on these assumptions, the diversity gain for the single-user scenario is $\frac {\left ({\sum _{i,j}\beta _{ij}}\right)^{2}}{\sum _{i,j}\beta _{ij}^{2}L_{ij}^{-1}}$ where $L_{ij}$ is the number of propagation paths and $\beta _{ij}$ is the large scale fading coefficient between the $i$ th RAU in the transmitter and the $j$ th RAU in the receiver. The diversity gain in the multi-user scenario for the $k$ th user is $\frac {M^{2}}{\sum _{j}L_{kj}^{-1}}$ where $M$ represents the number of RAUs at the transmitter. Simulation results show that when the perfect CSI assumption is satisfied, the use of BICMB results in the diversity gain values predicted by the analysis.
Structural Insights of Transcriptionally Active, Full-Length Androgen Receptor Coactivator Complexes

Steroid receptors activate gene transcription by recruiting coactivators to initiate transcription of their target genes. For most nuclear receptors, the ligand-dependent activation function domain-2 (AF-2) is a primary contributor to the nuclear receptor (NR) transcriptional activity. In contrast to other steroid receptors, such as ERα, the activation function of androgen receptor (AR) is largely dependent on its ligand-independent AF-1 located in its N-terminal domain (NTD). It remains unclear why AR utilizes a different AF domain from other receptors despite that NRs share similar domain organizations. Here, we present cryoelectron microscopy (cryo-EM) structures of DNA-bound full-length AR and its complex structure with key coactivators, SRC-3 and p300. AR dimerization follows a unique head-to-head and tail-to-tail manner. Unlike ERα, AR directly contacts a single SRC-3 and p300. The AR NTD is the primary site for coactivator recruitment. The structures provide a basis for understanding assembly of the AR:coactivator complex and its domain contributions for coactivator assembly and transcriptional regulation.
“Whatever It Takes”: Danger, Necessity, and Realism in American Public Policy:

There are two mentalities of rule, idealism and realism, which differ in their assumptions about how far government policy can be guided by principles alone. The late 1990s were a highpoint for ide...
Performance Analysis of Intelligent Reflective Surfaces for Wireless Communication

A statistical characterization of the fundamental performance bounds of an intelligent reflective surface (IRS) intended for aiding wireless communications is presented. To this end, the outage probability, average symbol error probability and achievable rate bounds are derived in closed-form. By virtue of an asymptotic analysis in high signal-to-noise ratio (SNR) regime, the achievable diversity order is derived. Thereby, we show that a diversity gain in the order of the number of passive reflective elements embedded within the IRS can be achieved with only controllable phase adjustments. Thus, IRS has a great potential of boosting the wireless performance by intelligently controlling the propagation channels without employing additional active radio frequency chains.
Optimal Periodic Multi-Agent Persistent Monitoring of a Finite Set of Targets with Uncertain States

We investigate the problem of persistently monitoring a finite set of targets with internal states that evolve with linear stochastic dynamics using a finite set of mobile agents. We approach the problem from the infinite-horizon perspective, looking for periodic movement schedules for the agents. Under linear dynamics and some standard assumptions on the noise distribution, the optimal estimator is a Kalman-Bucy filter. It is shown that when the agents are constrained to move only over a line and that they can see at most one target at a time, the optimal movement policy is such that the agent is always either moving with maximum speed or dwelling at a fixed position. Periodic trajectories of this form admit finite parameterization, and we show how to compute a stochastic gradient estimate of the performance with respect to the parameters that define the trajectory using Infinitesimal Perturbation Analysis. A gradient-descent scheme is used to compute locally optimal parameters. This approach allows us to deal with a very long persistent monitoring horizon using a small number of parameters.
Inexact Online Proximal-gradient Method for Time-varying Convex Optimization.

This paper considers an online proximal-gradient method to track the minimizers of a composite convex function that may continuously evolve over time. The online proximal-gradient method is "inexact," in the sense that: (i) it relies on an approximate first-order information of the smooth component of the cost; and, (ii) the proximal operator (with respect to the non-smooth term) may be computed only up to a certain precision. Under suitable assumptions, convergence of the error iterates is established for strongly convex cost functions. On the other hand, the dynamic regret is investigated when the cost is not strongly convex, under the additional assumption that the problem includes feasibility sets that are compact. Bounds are expressed in terms of the cumulative error and the path length of the optimal solutions. This suggests how to allocate resources to strike a balance between performance and precision in the gradient computation and in the proximal operator.
Cytokine and Growth Factor Response in a Rat Model of Radiation Induced Injury to the Submental Muscles.

Submental muscles (i.e., mylohyoid and geniohyoid) play a vital role during swallowing, protecting the airway from ingested material. To design therapies to reduce the functional deficits associated with radiation treatment relies in part on our understanding of the changes in the cytokine and growth factor response that can impact muscle function. The purpose of this study is to quantify changes in the inflammatory, pro-fibrotic, and pro-angiogenic factors following 48 Gy of fractionated radiation to the mylohyoid muscle. We hypothesized that (1) irradiation will provoke increases in TGF-1β and MMP-2 mRNA in the mylohyoid muscle; and (2) muscles surrounding the target location (i.e., geniohyoid and digastric muscles) will exhibit similar alterations in their gene expression profiles. Rats were exposed to 6 fractions of 8 Gy using a 6 MeV electron beam on a clinical linear accelerator. The highest dose curve was focused at the mylohyoid muscle. After 2- and 4-weeks post-radiation, the mylohyoid, geniohyoid, and digastric muscles were harvested. Expression of TNF-α, IFNγ, IL-1β, IL-6, TGF-1β, VEGF, MMP-2, and MMP-9 mRNA was analyzed via PCR and/or RT-PCR. TGF-1β, MMP-2, and IL-6 expression was upregulated in the irradiated mylohyoid compared to non-irradiated controls. No notable changes in TNF-α, IFNγ, and IL-1β mRNA expression were observed in irradiated muscles. Differing expression profiles were found in the surrounding muscles post-radiation. Results demonstrated that irradiation provokes molecular signals involved in the regulation of wound healing, which could lead to fibrosis or atrophy in the swallowing muscle after radiation.
XACT-Seq Comprehensively Defines the Promoter-Position and Promoter-Sequence Determinants for Initial-Transcription Pausing

Summary Pausing by RNA polymerase (RNAP) during transcription elongation, in which a translocating RNAP uses a “stepping” mechanism, has been studied extensively, but pausing by RNAP during initial transcription, in which a promoter-anchored RNAP uses a “scrunching” mechanism, has not. We report a method that directly defines the RNAP-active-center position relative to DNA with single-nucleotide resolution (XACT-seq; “crosslink-between-active-center-and-template sequencing”). We apply this method to detect and quantify pausing in initial transcription at 411 (∼4,000,000) promoter sequences in vivo in Escherichia coli. The results show initial-transcription pausing can occur in each nucleotide addition during initial transcription, particularly the first 4 to 5 nucleotide additions. The results further show initial-transcription pausing occurs at sequences that resemble the consensus sequence element for transcription-elongation pausing. Our findings define the positional and sequence determinants for initial-transcription pausing and establish initial-transcription pausing is hard coded by sequence elements similar to those for transcription-elongation pausing.
Laws of 4D Printing

Abstract Three-dimensional (3D) printing is an additive manufacturing process. Accordingly, four-dimensional (4D) printing is a manufacturing process that involves multiple research fields. 4D printing conserves the general attributes of 3D printing (such as material waste reduction, and elimination of molds, dies, and machining) and further enables the fourth dimension of products to provide intelligent behavior over time. This intelligent behavior is encoded (usually by an inverse mathematical problem) into stimuli-responsive multi-materials during printing, and is enabled by stimuli after printing. The main difference between 3D and 4D printed structures is the presence of one additional dimension, which provides for smart evolution over time. However, currently there is no general formula for modeling and predicting this additional dimension. Herein, by starting from fundamentals, we derive and validate a general bi-exponential formula with a particular format that can model the time-dependent behavior of nearly all 4D (hydro-, photochemical-, photothermal-, solvent-, pH-, moisture-, electrochemical-, electrothermal-, ultrasound-, etc. -responsive) structures. We show that two types of time constants are needed to capture the correct time-dependent behavior of 4D multi-materials. We introduce the concept of mismatch-driven stress at the interface of active and passive materials in 4D multi-material structures, leading to one of the two time constants. We develop and extract the other time constant from our unified model of time-dependent behavior of nearly all stimuli-responsive materials. Our results starting from the most fundamental concepts and ending with governing equations can serve as general design principles for future research in the field of 4D printing, where time-dependent behaviors should be properly understood, modeled, and predicted.
Conscience Wars in the Americas

Across the globe, public and private actors are now invoking conscience as a ground for objecting to laws or judicial decisions that confer on citizens reproductive and LGBT rights. Conscience clai...
Decay of Solutions to the Linearized Free Surface Navier–Stokes Equations with Fractional Boundary Operators

In this paper we consider a slab of viscous incompressible fluid bounded above by a free boundary, bounded below by a flat rigid interface, and acted on by gravity. The unique equilibrium is a flat slab of quiescent fluid. It is well-known that equilibria are asymptotically stable but that the rate of decay to equilibrium depends heavily on whether or not surface tension forces are accounted for at the free interface. The aim of the paper is to better understand the decay rate by studying a generalization of the linearized dynamics in which the surface tension operator is replaced by a more general fractional-order differential operator, which allows us to continuously interpolate between the case without surface tension and the case with surface tension. We study the decay of the linearized problem in terms of the choice of the generalized operator and in terms of the horizontal cross-section. In the case of a periodic cross-section we identify a critical order of the differential operator at which the decay rate transitions from almost exponential to exponential.
Correlation of central corneal thickness and associated factors in premature infants with and without retinopathy of prematurity

Abstract Objective Central corneal thickness (CCT) in premature infants is described in racially homogenous populations, and factors affecting CCT in infants are relatively unknown. This study describes CCT in premature infants and its association of steroid and oxygen requirements, gestational age (GA), birth weight (BW), race, and their relationship with CCT and corneal haze. Methods CCT measurements of 87 infants/174 eyes screened for retinopathy of prematurity were taken between 30 and 44 weeks of GA. CCT was analyzed using a mixed model for its relationship with BW, GA, race, corneal clarity, steroid, and oxygen use. Results Average CCT decreased at a rate of 12.3 μm/week. Caucasians had the thickest corneas and Hispanics the thinnest (p 0.05) Conclusions CCT varies by racial group in premature infants. Lower BW and GA are associated with increased CCT at baseline but thin at a faster rate. Average, CCT decreases at a rate of 12.3 μm/week between 30 and 44 weeks of GA and averages 550 μm by 44 weeks of GA.
Regular potential games

Abstract A fundamental problem with the Nash equilibrium concept is the existence of certain “structurally deficient” equilibria that (i) lack fundamental robustness properties, and (ii) are difficult to analyze. The notion of a “regular” Nash equilibrium was introduced by Harsanyi. Such equilibria are isolated, highly robust, and relatively simple to analyze. A game is said to be regular if all equilibria in the game are regular. In this paper it is shown that almost all potential games are regular. That is, except for a closed subset with Lebesgue measure zero, all potential games are regular. As an immediate consequence of this, the paper also proves an oddness result for potential games: In almost all potential games, the number of Nash equilibrium strategies is finite and odd. Specialized results are given for weighted potential games, exact potential games, and games with identical payoffs. Applications of the results to game-theoretic learning are discussed.
An Innovative Setup for High-Throughput Respirometry of Small Aquatic Animals

Metabolic rate is often measured as a phenotype in evolutionary genetics, among other fields including many facets of physiology, behavior, and ecology, because it impacts organismal fitness, is repeatable and heritable, and is responsive to numerous environmental variables. Aquatic respirometry, a method used to measure metabolic rate, has allowed key questions in these fields to be investigated, namely: 1) why do individuals from the same population exhibit up to three fold differences in metabolic rate, 2) how does metabolic rate change during an individual’s lifetime, and 3) what metabolic rate is advantageous in a specific environment? Current respirometry studies often suffer from small sample sizes and rely on low throughput approaches to measure metabolic rate, making it difficult to answer these and other relevant ecological and evolutionary questions due to lack of power, failure to capture true biological variation, and confounding variables, like time, that are introduced due to limitations in methodology. Here we describe a scalable high-throughput intermittent flow respirometer (HIFR) design and use it to measure the metabolic rates of 19 aquatic animals in one night while reducing equipment costs and time by more than 50%.
Romeo: A Design Tool for Embedding Transformable Parts in 3D Models to Robotically Augment Default Functionalities

Reconfiguring shapes of objects enables transforming existing passive objects with robotic functionalities, e.g., a transformable coffee cup holder can be attached to a chair's armrest, a piggy bank can reach out an arm to 'steal' coins. Despite the advance in end-user 3D design and fabrication, it remains challenging for non-experts to create such 'transformables' using existing tools due to the requirement of specific engineering knowledge such as mechanisms and robotic design. We present Romeo -- a design tool for creating transformables to robotically augment objects' default functionalities. Romeo allows users to transform an object into a robotic arm by expressing at a high level what type of task is expected. Users can select which part of the object to be transformed, specify motion points in space for the transformed part to follow and the corresponding action to be taken. Romeo then automatically generates a robotic arm embedded in the transformable part ready for fabrication. A design session validated this tool where participants used Romeo to accomplish controlled design tasks and to open-endedly create coin-stealing piggy banks by transforming 3D objects of their own choice.
The Planck Satellite LFI and the Microwave Background: Importance of the 4 K Reference Targets

Armed with ∼4 K reference targets, the Planck satellite low frequency instrument (LFI) is intended to map the microwave anisotropies of the sky from the second Lagrange point, L2. Recently, the complete design and pre-flight testing of these ∼4 K targets has been published (Valenziano L. et al., JINST 4, 2009, T12006). The receiver chain of the LFI is based on a pseudo-correlation architecture. Consequently, the presence of a ∼3 K microwave background signal at L2 can be established, if the ∼4 K reference targets function as intended. Conversely, demonstration that the targets are unable to provide the desired emission implies that the ∼3 K signal cannot exist, at this location. Careful study reveals that only the second scenario can be valid. This analysis thereby provides firm evidence that the monopole of the microwave background, as initially detected by Penzias and Wilson, is being produced by the Earth itself.
SEAN: Social Environment for Autonomous Navigation

Social navigation research is performed on a variety of robotic platforms, scenarios, and environments. Making comparisons between navigation algorithms is challenging because of the effort involved in building these systems and the diversity of platforms used by the community; nonetheless, evaluation is critical to understanding progress in the field. In a step towards reproducible evaluation of social navigation algorithms, we propose the Social Environment for Autonomous Navigation (SEAN). SEAN is a high visual fidelity, open source, and extensible social navigation simulation platform which includes a toolkit for evaluation of navigation algorithms. We demonstrate SEAN and its evaluation toolkit in two environments with dynamic pedestrians and using two different robots.
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus.

End-to-end (E2E) automatic speech recognition (ASR) systems lack the distinct language model (LM) component that characterizes traditional speech systems. While this simplifies the model architecture, it complicates the task of incorporating text-only data into training, which is important to the recognition of tail words that do not occur often in audio-text pairs. While shallow fusion has been proposed as a method for incorporating a pre-trained LM into an E2E model at inference time, it has not yet been explored for very large text corpora, and it has been shown to be very sensitive to hyperparameter settings in the beam search. In this work, we apply shallow fusion to incorporate a very large text corpus into a state-of-the-art E2EASR model. We explore the impact of model size and show that intelligent pruning of the training set can be more effective than increasing the parameter count. Additionally, we show that incorporating the LM in minimum word error rate (MWER) fine tuning makes shallow fusion far less dependent on optimal hyperparameter settings, reducing the difficulty of that tuning problem.
Secret key distillation over satellite-to-satellite free-space optics channel with a limited-sized aperture eavesdropper in the same plane of the legitimate receiver

Conventionally, unconditional information security has been studied by quantum cryptography although the assumption of an omnipotent eavesdropper is too strict for some realistic implementations. In this paper, we study the realistic secret key distillation over a satellite-to-satellite free space optics channel where we assume a limited-sized aperture eavesdropper (Eve) in the same plane of the legitimate receiver (Bob) and determine the secret key rate (SKR) lower bounds correspondingly. We first study the input power dependency without assumptions on Bob’s detection scheme before optimizing the input power to determine lower bounds as functions of transmission distances, center frequency or Eve aperture radius. Then we calculate analytical expressions regarding the SKR lower bound and upper bound as transmission distance goes to infinity. We also incorporate specific discrete variable (DV) and continuous variable (CV) protocols for comparison. We demonstrate that significantly higher SKR lower bounds can be achieved compared to traditional unrestricted Eve scenario.
Representations of integers as sums of primes from a Beatty sequence

We study the problem of representing integers as sums of prime numbers from a fixed Beatty sequence $B_{\alpha,\beta}$, where $\alpha>1$ is irrational and of finite type.
Extending the Langevin model to variable-density pressure-gradient-driven turbulence

We extend the generalized Langevin model (D.C. Haworth and S.B. Pope, A generalized Langevin model for turbulent flows, Phys. Fluids 29 (1986) p. 387), originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, to variable-density (VD) pressure-gradient-driven flows. VD effects due to nonuniform mass concentrations (e.g. mixing of different species) are considered. In the extended model, large density fluctuations leading to large differential fluid accelerations are accounted for. This is an essential ingredient to represent the strong coupling between the density and velocity fields in VD hydrodynamics driven by active scalar mixing. The small-scale anisotropy, a fundamentally non-Kolmogorovian feature of pressure-gradient-driven flows, is captured by a tensorial stochastic diffusion term. The extension is so constructed that it reduces to the original Langevin model in the limit of constant density. We show that coupling a Lagrangian mass-density partic...
Quasisymmetric graphs and Zygmund functions

A quasisymmetric graph is a curve whose projection onto a line is a quasisymmetric map. We show that this class of curves is related to solutions of the reduced Beltrami equation and to a generalization of the Zygmund class Λ*. This relation makes it possible to use the tools of harmonic analysis to construct nontrivial examples of quasisymmetric graphs and of quasiconformal maps. Kovalev was supported by the NSF grant DMS-0968756.
The Final Integrations of the Caltech Submillimeter Observatory

We present the final observations of the Caltech Submillimeter Observatory, taken toward Orion KL, prior to its decommissioning after nearly three decades of operation.
Percolation on strings and the cover-up of the c = 1 disaster

We study percolation on the worldsheets of string theory for c = 0, 12, 1 and 2. For c 1. It thus appears likely that simulations for c = 2,3… on numerically accessible lattices will fail to capture even the qualitative behavior of the continuum limit.
Apex-angle-dependent resonances in triangular split-ring resonators

Along with other frequency selective structures (Pendry et al. in IEEE Trans Microw Theory Tech 47(11):2075–2084, 1999) (circles and squares), triangular split-ring resonators (TSRRs) only allow frequencies near the center resonant frequency to propagate. Further, TSRRs are attractive due to their small surface area (Vidhyalakshmi et al. in Stopband characteristics of complementary triangular split ring resonator loaded microstrip line, 2011), comparatively, and large quality factors (Q) as previously investigated by Gay-Balmaz et al. (J Appl Phys 92(5):2929–2936, 2002). In this work, we examine the effects of varying the apex angle on the resonant frequency, the Q factor, and the phase shift imparted by the TSRR element within the GHz frequency regime.
Decay Rates of Various Bottomonium systems

Using the Bodwin-Braaten-Lepage factorization theorem in heavy quarkonium decay and production processes, the authors calculated matrix elements associated with S- and P-wave bottomonium decays via lattice QCD simulation methods. In this work, they report preliminary results on the operator matching between the lattice expression and the continuum expression at one loop level. Phenomenological implications are discussed using these preliminary {ovr MS} matrix elements.
Superfluid transition in a chiron gas

Low temperature measurements of the magnetic susceptibility of LaCuO4 doped with Sr (LSCO) suggest that superconducting transition is associated with the disappearance of the vortex liquid. This note draws attention to the possibility that these vortices can be identified with the soliton-like charge carriers introduced in a previous theory of spin–orbit localization in layered poor conductors. In two-dimensions, these solitons are vortex-like, while in three-dimensional systems they are monopole-like. In either case, there is a natural mechanism for the pairing of spin-up and spin-down solitons. At low temperatures, there is a also cross-over transition which is a function of carrier density between a state where the solitons can move independently and a condensate state where the spin-up and spin-down solitons in neighbouring layers are paired.
MONTE CARLO SIMULATIONS OF GLOBULAR CLUSTER EVOLUTION. VI. THE INFLUENCE OF AN INTERMEDIATE-MASS BLACK HOLE

We present results from a series of Monte Carlo (MC) simulations investigating the imprint of a central intermediatemass black hole (IMBH) on the structure of a globular cluster. We investigate the three-dimensional and projected density profiles, and stellar disruption rates for idealized as well as realistic cluster models, taking into account a stellar mass spectrum and stellar evolution, and allowing for a larger, more realistic number of stars than was previously possible with direct N-body methods. We compare our results to other N-body and Fokker‐Planck simulations published previously. We find, in general, very good agreement for the overall cluster structure and dynamical evolution between direct N-body simulations and our MC simulations. Significant differences exist in the number of stars that are tidally disrupted by the IMBH, and this is most likely caused by the wandering motion of the IMBH, not included in the MC scheme. These differences, however, are negligible for the final IMBH masses in realistic cluster models, as the disruption rates are generally much lower than for single-mass clusters. As a direct comparison to observations we construct a detailed model for the cluster NGC 5694, which is known to possess a central surface brightness cusp consistent with the presence of an IMBH. We find that not only the inner slope but also the outer part of the surface brightness profile agree well with observations. However, there is only a slight preference for models harboring an IMBH compared to models without.
Equidistribution and counting for orbits of geometrically finite hyperbolic groups

Let G be the identity component of SO(n, 1), n ≥ 2, acting linearly on a finite dimensional real vector space V . Consider a vector w0 ∈ V such that the stabilizer of w0 is a symmetric subgroup of G or the stabilizer of the line Rw0 is a parabolic subgroup of G. For any non-elementary discrete subgroup Γ of G with its orbit w0Γ discrete, we compute an asymptotic formula (as T → ∞) for the number of points in w0Γ of norm at most T , provided that the Bowen-Margulis-Sullivan measure on T1(Γ\Hn) and the Γ-skinning size of w0 are finite. The main ergodic ingredient in our approach is the description for the limit- ing distribution of the orthogonal translates of a totally geodesically immersed closed submanifold of Γ\Hn. We also give a criterion on the finiteness of the Γ-skinning size of w0 for Γ geometrically finite. Mathematics department, Brown university, Providence, RI 02912 and Korea Insti- tute for Advanced Study, Seoul, Korea E-mail address: heeoh@math.brown.edu Department of Mathematics, The Ohio State University, Columbus, OH 43210 E-mail address: shah@math.osu.edu
Using data and respecting users

As data becomes increasingly valuable, firms face financial pressures to capture that data and extract its value. Consumers, on the other hand, have reason to fear that such data might not be used in their best interests. How can a firm capture data, respect consumer privacy, and create value all at the same time? This article takes technical and legal approaches to offer three solutions that alter the reward to risk ratio from the consumer’s perspective. The first aligns incentives, the second saves masked data, and the third saves masked algorithms. Together, these three approaches offer a range of ways to deliver value from data analysis while protecting users and respecting their trust.
Stochastic renormalization group and gradient flow

A non-perturbative and continuous definition of RG transformations as stochastic processes is proposed, inspired by the observation that the functional RG equations for effective Boltzmann factors may be interpreted as Fokker-Planck equations. The result implies a new approach to Monte Carlo RG that is amenable to lattice simulation. Long-distance correlations of the effective theory are shown to approach gradient-flowed correlations, which are simpler to measure. The Markov property of the stochastic RG transformation implies an RG scaling formula which allows for the measurement of anomalous dimensions when transcribed into gradient flow expectation values.
Estimating local daytime population density from census and payroll data

Daytime population density reflects where people commute and spend their waking hours. It carries significant weight as urban planners and engineers site transportation infrastructure and utilities...
Displaced vertex signatures of doubly charged scalars in the type-II seesaw and its left-right extensions

The type-II seesaw mechanism with an isospin-triplet scalar ΔL provides one of the most compelling explanations for the observed smallness of neutrino masses. The triplet contains a doubly-charged component $$ {H}_{{}^L}^{\pm \pm } $$ , which dominantly decays to either same-sign dileptons or to a pair of W bosons, depending on the size of the triplet vacuum expectation value. However, there exists a range of Yukawa couplings fL of the triplet to the charged leptons, wherein a relatively light $$ {H}_{{}^L}^{\pm \pm } $$ tends to be long-lived, giving rise to distinct displaced-vertex signatures at the high-energy colliders. We find that the displaced vertex signals from the leptonic decays $$ {H}_{{}^L}^{\pm \pm}\to {\ell}_{\alpha}^{\pm }{\ell}_{{}^{\beta}}^{\pm } $$ could probe a broad parameter space with 10−10 ≲ |fL| ≲ 10−6 and $$ 45.6\ GeV<{M}_{H_L^{\pm \pm }}\lesssim 200\ GeV $$ at the high-luminosity LHC. Similar sensitivity can also be achieved at a future 1 TeV e+e− collider. The mass reach can be extended to about 500GeV at a future 100TeV proton-proton collider. Similar conclusions apply for the right-handed triplet $$ {H}_{{}^R}^{\pm \pm } $$ in the TeV-scale left-right symmetric models, which provide a natural embedding of the type-II seesaw. We show that the displaced vertex signals are largely complementary to the prompt same-sign dilepton pair searches at the LHC and the low-energy, high-intensity/precision measurements, such as neutrinoless double beta decay, charged lepton flavor violation, electron and muon anomalous magnetic moments, muonium-antimuonium oscillation and Moller scattering.