cssi/SciSciGPT-SciSciNet huggingface dataset:
Sites of Circadian Clock Neuron Plasticity Mediate Sensory Integration and Entrainment

Summary Networks of circadian timekeeping in the brain display marked daily changes in neuronal morphology. In Drosophila melanogaster, the striking daily structural remodeling of the dorsal medial termini of the small ventral lateral neurons has long been hypothesized to mediate endogenous circadian timekeeping. To test this model, we have specifically abrogated these sites of daily neuronal remodeling through the reprogramming of neural development and assessed the effects on circadian timekeeping and clock outputs. Remarkably, the loss of these sites has no measurable effects on endogenous circadian timekeeping or on any of the major output functions of the small ventral lateral neurons. Rather, their loss reduces sites of glutamatergic sensory neurotransmission that normally encodes naturalistic time cues from the environment. These results support an alternative model: structural plasticity in critical clock neurons is the basis for proper integration of light and temperature and gates sensory inputs into circadian clock neuron networks.
Analysis of KNN Information Estimators for Smooth Distributions

KSG mutual information estimator, which is based on the distances of each sample to its $k$ -th nearest neighbor, is widely used to estimate mutual information between two continuous random variables. Existing work has analyzed the convergence rate of this estimator for random variables whose densities are bounded away from zero in its support. In practice, however, KSG estimator also performs well for a much broader class of distributions, including not only those with bounded support and densities bounded away from zero, but also those with bounded support but densities approaching zero, and those with unbounded support. In this paper, we analyze the convergence rate of the error of KSG estimator for smooth distributions, whose support of density can be both bounded and unbounded. As KSG mutual information estimator can be viewed as an adaptive recombination of KL entropy estimators, in our analysis, we also provide convergence analysis of KL entropy estimator for a broad class of distributions.
Blind adaptive multiuser detection for uplink long-code CDMA systems

In the uplink of a long-code CDMA system, base station knows spreading codes of all serviced users. Given propagation delays, a blind adaptive CMA-based approach, with the aid of a set of MMSE-like constraints parameterized by channel-like vectors, is proposed to detect all users' symbols simultaneously. As by-products, the channel-like vectors are also obtained for all users. Since the constraints involve covariance of the received data, which is time varying and can not be obtained by traditional sample average, we thus propose to approximate it using estimated signature matrix and noise power. Simulation results show satisfactory performance of the proposed method.
The congruence subgroup problem for a family of branch groups

We construct a family of groups which generalize the Hanoi towers group and study the congruence subgroup problem for the groups in this family. We show that unlike the Hanoi towers group, the grou...
Locating resonances on hyperbolic cones

In this note we explicitly compute the resonances on hyperbolic cones. These are hyperbolic manifolds with a conic singularity equipped with a warped product metric. The calculation is based on separation of variables and Kummer's connection formulae for hypergeometric functions. To our knowledge this is the one of the few explicit calculations of resonances that does not rely on the resolvent being a two-point function.
Peer effects in the diffusion of water‐saving agricultural technologies

We investigate the role of peer effects in the diffusion of an important water‐saving irrigation technology: low energy precise application (LEPA). Using detailed irrigation behavior data for growers in the High Plains Aquifer region of Kansas covering 1990–2014, we find clear evidence of peer influence in adoption of LEPA, net of environmental factors. Specifically, an additional neighboring LEPA installation within 1 km increases the probability of adoption by about 0.3 percentage points, on average, and this effect diminishes with distance. Our empirical estimates indicate that in the absence of peer effects, LEPA adoption would have been about 10% lower (1,000–1,600 fewer installations) per year. In addition, we find that growers install LEPA in response to higher energy prices.
Differential metabolic and multi-tissue transcriptomic responses to fructose consumption among genetically diverse mice.

Abstract Understanding how individuals react differently to the same treatment is a major concern in precision medicine. Metabolic challenges such as the one posed by high fructose intake are important determinants of disease mechanisms. We embarked on studies to determine how fructose affects differential metabolic dysfunctions across genetically dissimilar mice, namely, C57BL/6 J (B6), DBA/2 J (DBA) and FVB/NJ (FVB), by integrating physiological and gene regulatory mechanisms. We report that fructose has strain-specific effects, involving tissue-specific gene regulatory cascades in hypothalamus, liver, and white adipose tissues. DBA mice showed the largest numbers of genes associated with adiposity, congruent with their highest susceptibility to adiposity gain and glucose intolerance across the three tissues. In contrast, B6 and FVB mainly exhibited cholesterol phenotypes, accompanying the largest number of adipose genes correlating with total cholesterol in B6, and liver genes correlating with LDL in FVB mice. Tissue-specific network modeling predicted strain-and tissue-specific regulators such as Fgf21 (DBA) and Lss (B6), which were subsequently validated in primary hepatocytes. Strain-specific fructose-responsive genes revealed susceptibility for human diseases such that genes in liver and adipose tissue in DBA showed strong enrichment for human type 2 diabetes and obesity traits. Liver and adipose genes in FVB were mostly related to lipid traits, and liver and adipose genes in B6 showed relevance to most cardiometabolic traits tested. Our results show that fructose induces gene regulatory pathways that are tissue specific and dependent on the genetic make-up, which may underlie interindividual variability in cardiometabolic responses to high fructose consumption.
New materials physics.

This review presents a survey of, and guide to, New Materials Physics research. It begins with an overview of the goals of New Materials Physics and then presents important ideas and techniques for the design and growth of new materials. An emphasis is placed on the use of compositional phase diagrams to inform and motivate solution growth of single crystals. The second half of this review focuses on the vital process of generating actionable ideas for the growth and discovery of new materials and ground states. Motivations ranging from (1) wanting a specific compound, to (2) wanting a specific ground state to (3) wanting to explore for known and unknown unknowns, will be discussed and illustrated with abundant examples. The goal of this review is to inform, inspire, an even entertain, as many practitioners of this field as possible.
Cooperative Beamforming With Predictive Relay Selection for Urban mmWave Communications

While millimeter wave (mmWave) communications promise high data rates, their sensitivity to blockage and severe signal attenuation present challenges in their deployment in urban settings. One effective way to mitigate those effects and increase communication range is relaying in combination with beamforming. However, relay-assisted beamforming also requires relay selection, a process that not only is resource demanding due to the need for explicit Channel State Information (CSI), but also introduces network latency. In this paper, we introduce a relay beamforming approach for mmWave communications in an urban scenario, which exploits the shadowing-induced correlation structure of the channel to reduce both latency and CSI estimation overhead. Our system model consists of static relays deployed in clusters across streets. Under that setting, we propose a novel, resource efficient scheme for joint optimal relay selection and distributed cooperative beamforming that maximizes the expected Signal-to-Interference plus Noise Ratio (SINR) at the destination, under power constraints. In particular, assuming a time-slotted system operation, one relay from each cluster is optimally selected at each time slot to participate in optimal beamforming at the next time slot. The key novelty of the proposed scheme is that relay selection is implemented in a predictive and distributed manner, by exploiting channel correlations and by using past and present measurements of magnitude CSI. As a result, at each time slot, optimal beamforming based on relays selected in the previous slot and optimal predictive relay selection for the next time slot are implemented completely in parallel. This parallelization eliminates delays induced by sequential execution of relay selection and beamforming, and substantially reduces CSI estimation overhead. Simulations confirm that the proposed relay selection scheme outperforms any randomized selection policy, while, at the same time, achieves comparable performance to an ideal selection scheme that relies on perfect CSI estimates for all candidate relays.
Non-autonomous parabolic bifurcation

Let $f(z) = z+z^2+O(z^3)$ and $f_\epsilon(z) = f(z) + \epsilon^2$. A classical result in parabolic bifurcation in one complex variable is the following: if $N-\frac{\pi}{\epsilon}\to 0$ we obtain $(f_\epsilon)^{N} \to \mathcal{L}_f$, where $\mathcal{L}_f$ is the Lavaurs map of $f$. In this paper we study a \textit{non-autonomous} parabolic bifurcation. We focus on the case of $f_0(z)=\frac{z}{1-z}$. Given a sequence $\{\epsilon_i\}_{1\leq i\leq N}$, we denote $f_n(z) = f_0(z) + \epsilon_n^2$. We give sufficient and necessary conditions on the sequence $\{\epsilon_i\}$ that imply that $f_{N}\circ\ldots f_{1} \to \textrm{Id}$ (the Lavaurs map of $f_0$). We apply our results to prove parabolic bifurcation phenomenon in two dimensions for some class of maps.
Adaptive bias and attitude observer on the special orthogonal group for true-north gyrocompass systems: Theory and preliminary results:

This article reports an adaptive sensor bias observer and attitude observer operating directly on SO(3) for true-north gyrocompass systems that utilize six-degree-of-freedom inertial measurement un...
Data transforming augmentation for heteroscedastic models

Data augmentation (DA) turns seemingly intractable computational problems into simple ones by augmenting latent missing data. In addition to computational simplicity, it is now well-established tha...
Separation of hemodynamic signals from GCaMP fluorescence measured with wide-field imaging.

This paper addresses a well-known and strong source of contamination in wide-field calcium-imaging data: hemodynamics. To guide researchers toward the best method to separate calcium signals from h...
Spillover effects of a husband's retirement on a woman's health: Evidence from urban China

Despite an increasing number of studies measuring the effect of retirement on individual well-being, research on spillover effects of one spouse's retirement on another spouse's well-being is limited. If such an effect exists but is not considered, it would result in an underestimation of the total retirement effect. This article examines the effect a man's retirement has on his wife's mental and physical health. Using data from the China Health and Retirement Longitudinal Survey (CHARLS), I exploit the large increase in the probability of retirement at the legal retirement age for urban male wage earners in China as a natural experiment. I implement a fuzzy regression discontinuity design to compare the health outcomes of women whose husbands recently retired with those whose husbands are close to retiring. Findings indicate that the retirement of her spouse improves a woman's physical and mental well-being, most likely by increasing the frequency of her social interactions and exercise.
Synthesis, Characterization, and Reactivity of Chromium(VI) Alkylidenes

Chromium(VI) dialkyls are remarkably acidic, yielding a set of anionic chromium alkylidenes upon deprotonation with KN(TMS)2. We describe the characterization of three anionic chromium alkylidenes ...
Arctic boundaries of the ice model on three-bundle domains

In this paper we consider the six-vertex model at ice point on an arbitrary three-bundle domain, which is a generalization of the domain-wall ice model on the square (or, equivalently, of a uniformly random alternating sign matrix). We show that this model exhibits the arctic boundary phenomenon, whose boundary is given by a union of explicit algebraic curves. This was originally predicted by Colomo and Sportiello (J Stat Phys 164:1488–1523, 2016) as one of the initial applications of a general heuristic that they introduced for locating arctic boundaries, called the (geometric) tangent method. Our proof uses a probabilistic analysis of non-crossing directed path ensembles to provide a mathematical justification of their tangent method heuristic in this case, which might be of independent interest.
Muscle contraction induces osteogenic levels of cortical bone strain despite muscle weakness in a mouse model of Osteogenesis Imperfecta

Abstract Mechanical interactions between muscle and bone have long been recognized as integral to bone integrity. However, few studies have directly measured these interactions within the context of musculoskeletal disease. In this study, the osteogenesis imperfecta murine model (oim/oim) was utilized because it has both reduced bone and muscle properties, allowing direct assessment of whether weakened muscle is able to engender strain on weakened bone. To do so, a strain gauge was attached to the tibia of healthy and oim/oim mice, muscles within the posterior quadrant of the lower hind limb were stimulated, and bone strain during muscle contraction was measured. Results indicated that the relationship between maximum muscle torque and maximum engendered strain is altered in oim/oim bone, with less torque required to engender strain compare to wild-type and heterozygous mice. Maximum muscle torque at 150 Hz stimulation frequency was able to engender ~1500 μɛ in oim/oim animals. However, even though the strain engendered in the oim/oim mice was high relative to historical bone formation thresholds, the maximum strain values were still significantly lower than that of the wild-type mice. These results are promising in that they suggest that muscle stimulation may be a viable means of inducing bone formation in oim/oim and potentially other disease models where muscle weakness/atrophy exist.
Molecular and histologic outcomes following spinal cord injury in spiny mice, Acomys cahirinus

The spiny mouse (Acomys cahirinus) appears to be unique among mammals by showing little scarring or fibrosis after skin or muscle injury, but the Acomys response to spinal cord injury (SCI) is unknown. We tested the hypothesis that Acomys would have molecular and immunohistochemical evidence of reduced spinal inflammation and fibrosis following SCI as compared to C57BL/6 mice (Mus), which similar to all mammals studied to date exhibits spinal scarring following SCI. Initial experiments used two pathway-focused RT-PCR gene arrays ("wound healing" and "neurogenesis") to evaluate tissue samples from the C2-C6 spinal cord 3 days after a C3/C4 hemi-crush injury (C3Hc). Based on the gene array results, specific genes were selected for RT-qPCR evaluation using species-specific primers. The results supported our hypothesis by showing increased inflammation and fibrosis related gene expression (Serpine 1, Plau, and Timp1) in Mus as compared to Acomys (p < .05). RT-qPCR also showed enhanced stem cell and axonal guidance related gene expression (Bmp2, GDNF, and Shh) in Acomys compared to Mus (p < .05). Immunohistochemical evaluation of the spinal lesion at 4 weeks postinjury indicated less collagen IV immunostaining in Acomys (p < .05). Glial fibrillary acidic protein (GFAP) and ionized calcium binding adaptor molecule 1(IBA1) immunostaining indicated morphological differences in the appearance of astrocytes and macrophages/microglia in Acomys. Collectively, the molecular and histologic results support the hypothesis that Acomys has reduced spinal inflammation and fibrosis following SCI. We suggest that Acomys may be a useful comparative model to study adaptive responses to SCI.
Two Diagrams with Many Stories: Incorporating Finance into Teaching Global Strategy

ABSTRACTIn this paper, we propose two diagrams, the corporate strategic framework diagram and the free cash flow diagram, to teach students how the finance function is integrated to other business ...
An Analysis of Universality in Blackbody Radiation

Through the formulation of his law of thermal emission, Kirchhoff conferred upon blackbody radiation the quality of universality [G. Kirchhoff, Annalen der Physik, 1860, v. 109, 275]. Consequently, modern physics holds that such radiation is independent of the nature and shape of the emitting object. Recently, Kirchhoff’s experimental work and theoretical conclusions have been reconsidered [P. M. L. Robitaille. IEEE Transactions on Plasma Science, 2003, v. 31(6), 1263]. In this work, Einstein’s derivation of the Planckian relation is reexamined. It is demonstrated that claims of universality in blackbody radiation are invalid.
Generating justifications for norm-related agent decisions

We present an approach to generating natural language justifications of decisions derived from norm-based reasoning. Assuming an agent which maximally satisfies a set of rules specified in an object-oriented temporal logic, the user can ask factual questions (about the agent’s rules, actions, and the extent to which the agent violated the rules) as well as “why” questions that require the agent comparing actual behavior to counterfactual trajectories with respect to these rules. To produce natural-sounding explanations, we focus on the subproblem of producing natural language clauses from statements in a fragment of temporal logic, and then describe how to embed these clauses into explanatory sentences. We use a human judgment evaluation on a testbed task to compare our approach to variants in terms of intelligibility, mental model and perceived trust.
DDTCDR: Deep Dual Transfer Cross Domain Recommendation

Cross domain recommender systems have been increasingly valuable for helping consumers identify the most satisfying items from different categories. However, previously proposed cross-domain models did not take into account bidirectional latent relations between users and items. In addition, they do not explicitly model information of user and item features, while utilizing only user ratings information for recommendations. To address these concerns, in this paper we propose a novel approach to cross-domain recommendations based on the mechanism of dual learning that transfers information between two related domains in an iterative manner until the learning process stabilizes. We develop a novel latent orthogonal mapping to extract user preferences over multiple domains while preserving relations between users across different latent spaces. Combining with autoencoder approach to extract the latent essence of feature information, we propose Deep Dual Transfer Cross Domain Recommendation (DDTCDR) model to provide recommendations in respective domains. We test the proposed method on a large dataset containing three domains of movies, book and music items and demonstrate that it consistently and significantly outperforms several state-of-the-art baselines and also classical transfer learning approaches.
Fair division with multiple pieces

Abstract Given a set of p players, we consider problems concerning envy-free allocation of collections of k pieces from given sets of goods or chores. We show that if p = n and each player prefers k pieces in any division of a cake into n pieces, then there exists a division of the cake where at least p k 2 − k + 1 players get their desired k pieces each. We further show that if p = k ( n − 1 ) + 1 and each player prefers k pieces, one piece from each of k cakes, in any division of the k cakes into n pieces each, then there exists a division of the cakes where at least p k 2 − k players get their desired k pieces each. Finally we prove that if p ≥ k ( n − 1 ) + 1 and each player prefers one shift in each of k days that are partitioned into n shifts each, then, given that players prefer empty shifts if possible (e.g., if salaries are fixed and do not depend on the number of working hours), there exist n ( 1 + ln k ) players covering all the shifts, and moreover, if k = 2 then n players suffice. Our proofs combine topological methods and theorems of Furedi, Lovasz and Gallai from hypergraph theory.
Safe Linear Stochastic Bandits

We introduce the safe linear stochastic bandit framework—a generalization of linear stochastic bandits—where, in each stage, the learner is required to select an arm with an expected reward that is no less than a predetermined (safe) threshold with high probability. We assume that the learner initially has knowledge of an arm that is known to be safe, but not necessarily optimal. Leveraging on this assumption, we introduce a learning algorithm that systematically combines known safe arms with exploratory arms to safely expand the set of safe arms over time, while facilitating safe greedy exploitation in subsequent stages. In addition to ensuring the satisfaction of the safety constraint at every stage of play, the proposed algorithm is shown to exhibit an expected regret that is no more than O(√T log(T)) after T stages of play.
Phase-Modulated Interferometry, Spectroscopy, and Refractometry using Entangled Photon Pairs

The authors demonstrate a form of two-photon-counting interferometry by measuring the coincidence counts between single-photon-counting detectors at an output port of a Mach-Zehnder Interferometer (MZI) following injection of broad-band time-frequency-entangled photon pairs (EPP) generated from collinear spontaneous parametric down conversion into a single input port. Spectroscopy and refractometry are performed on a sample inserted in one internal path of the MZI by scanning the other path in length, which acquires phase and amplitude information about the samples linear response. Phase modulation and lock-in detection are introduced to increase detection signal-to-noise ratio and implement a down-sampling technique for scanning the interferometer delay, which reduces the sampling requirements needed to reproduce fully the temporal interference pattern. The phase-modulation technique also allows the contributions of various quantum-state pathways leading to the final detection outcomes to be extracted individually. Feynman diagrams frequently used in the context of molecular spectroscopy are used to describe the interferences resulting from the coherence properties of time-frequency EPPs passing through the MZI. These results are an important step toward implementation of a proposed method for molecular spectroscopy, i.e. quantum-light-enhanced two-dimensional spectroscopy.
Symmetric polymorphisms and efficient decidability of promise CSPs

In the field of constraint satisfaction problems (CSP), promise CSPs are an exciting new direction of study. In a promise CSP, each constraint comes in two forms: "strict" and "weak," and in the associated decision problem one must distinguish between being able to satisfy all the strict constraints versus not being able to satisfy all the weak constraints. The most commonly cited example of a promise CSP is the approximate graph coloring problem---which has recently benefited from multiple breakthroughs [BKO19, WŽ19] due to a systematic study of promise CSPs under the lens of "polymorphisms," operations that map tuples in the strict form of each constraint to a tuple in its weak form. In this work, we present a simple algorithm which in polynomial time solves the decision problem for all promise CSPs that admit infinitely many symmetric polymorphisms, that is the coordinates are permutation invariant. This generalizes previous work of the authors [BG19]. We also extend this algorithm to a more general class of block-symmetric polymorphisms. As a corollary, this single algorithm solves all polynomial-time tractable Boolean CSPs simultaneously. These results give a new perspective on Schaefer's classic theorem and shed further light on how symmetries of polymorphisms enable algorithms.
Flight Recovery of MAVs with Compromised IMU

Micro Aerial Vehicles (MAVs) rely on onboard attitude and position sensors for autonomous flight. Due to their size, weight, and power (SWaP) constraints, most modern MAVs use miniaturized inertial measurement units (IMUs) to provide attitude feedback, which is critical for flight stabilization and control. However, recent adversarial attack studies have demonstrated that many commonly used IMUs are vulnerable to attacks exploiting their physical characteristics. Conventional redundancy-based approaches are not effective against such attacks because redundant IMUs have the same or similar physical vulnerabilities. In this paper, we present a novel fault-tolerant solution for IMU compromised scenarios, using separate position and heading information to restore the failed attitude states. Rather than adding more IMU alternatives for recovery, the proposed method is intended to minimize any modifications to the existing system and control program. Thus, it is particularly useful for vehicles that have tight SWaP constraints while requiring simultaneous high performance and safety demands. To execute the recovery logic properly, a robust estimator was designed for fine-grained detection and isolation of the faulty sensors. The effectiveness of the proposed approach was validated on a quadcopter MAV through both simulation and experimental flight tests.
Independence properties of the truncated multivariate elliptical distributions

Abstract We characterize the truncated multivariate normal random vectors for which two complementary sub-vectors are mutually independent, and an analogous characterization is obtained for multivariate truncated elliptical distributions. An application to testing data on high-school and college test scores is provided.
Lower Bounds Against Sparse Symmetric Functions of ACC Circuits: Expanding the Reach of #SAT Algorithms.

We continue the program of proving circuit lower bounds via circuit satisfiability algorithms. So far, this program has yielded several concrete results, proving that functions in Quasi-NP = NTIME[n^{(log n)^O(1)}] and NEXP do not have small circuits (in the worst case and/or on average) from various circuit classes C, by showing that C admits non-trivial satisfiability and/or #SAT algorithms which beat exhaustive search by a minor amount. In this paper, we present a new strong lower bound consequence of non-trivial #SAT algorithm for a circuit class {C}. Say a symmetric Boolean function f(x₁,…,x_n) is sparse if it outputs 1 on O(1) values of ∑_i x_i. We show that for every sparse f, and for all "typical" C, faster #SAT algorithms for C circuits actually imply lower bounds against the circuit class f ∘ C, which may be stronger than C itself. In particular: - #SAT algorithms for n^k-size C-circuits running in 2ⁿ/n^k time (for all k) imply NEXP does not have f ∘ C-circuits of polynomial size. - #SAT algorithms for 2^{n^e}-size C-circuits running in 2^{n-n^e} time (for some e > 0) imply Quasi-NP does not have f ∘ C-circuits of polynomial size. Applying #SAT algorithms from the literature, one immediate corollary of our results is that Quasi-NP does not have EMAJ ∘ ACC⁰ ∘ THR circuits of polynomial size, where EMAJ is the "exact majority" function, improving previous lower bounds against ACC⁰ [Williams JACM'14] and ACC⁰ ∘ THR [Williams STOC'14], [Murray-Williams STOC'18]. This is the first nontrivial lower bound against such a circuit class.
Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT

According to the LTE-U Forum specification, a LTE-U base-station (BS) reduces its duty cycle from 50% to 33% when it senses an increase in the number of co-channel Wi-Fi basic service sets (BSSs) from one to two. The detection of the number of Wi-Fi BSSs that are operating on the channel in real-time, without decoding the Wi-Fi packets, still remains a challenge. In this paper, we present a novel machine learning (ML) approach that solves the problem by using energy values observed during LTE-U OFF duration. Observing the energy values (at LTE-U BS OFF time) is a much simpler operation than decoding the entire Wi-Fi packets. In this work, we implement and validate the proposed ML based approach in real-time experiments, and demonstrate that there are two distinct patterns between one and two Wi-Fi APs. This approach delivers an accuracy close to 100% compared to auto-correlation (AC) and energy detection (ED) approaches.
Low temperature platinum chemical vapor deposition on functionalized self-assembled monolayers

The reaction pathways of Pt CVD using (COD)PtMe2 – xClx (x = 0, 1, 2) have been investigated on functionalized self-assembled monolayers (SAMs) as models for organic substrates. Residual gas analysis for (COD)PtMe2 and (COD)PtMeCl is consistent with the loss of methyl radicals as the initial step in deposition, while for (COD)PtCl2, the first step is the loss of a chlorine radical. It is further shown using x-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry that the deposition process leads to chemical damage of the SAM layer and little Pt deposition. Using this understanding, it is demonstrated that the Pt CVD rate can be controlled using a radical trap. In the presence of 1,4-cyclohexadiene, a well-known alkyl radical trap, Pt deposition was increased by 5× to 10×, creating a room-temperature effective Pt CVD process.
Attacking vision-based perception in end-to-end autonomous driving models

Abstract Recent advances in machine learning, especially techniques such as deep neural networks, are enabling a range of emerging applications. One such example is autonomous driving, which often relies on deep learning for perception. However, deep learning-based perception has been shown to be vulnerable to a host of subtle adversarial manipulations of images. Nevertheless, the vast majority of such demonstrations focus on perception that is disembodied from end-to-end control. We present novel end-to-end attacks on autonomous driving in simulation, using simple physically realizable attacks: the painting of black lines on the road. These attacks target deep neural network models for end-to-end autonomous driving control. A systematic investigation shows that such attacks are easy to engineer, and we describe scenarios (e.g., right turns) in which they are highly effective. We define several objective functions that quantify the success of an attack and develop techniques based on Bayesian Optimization to efficiently traverse the search space of higher dimensional attacks. Additionally, we define a novel class of hijacking attacks, where painting lines on the road cause the driverless car to follow a target path. Through the use of network deconvolution, we provide insights into the successful attacks, which appear to work by mimicking activations of entirely different scenarios. Our code is available on https://github.com/xz-group/AdverseDrive
Probing the chiral limit of M_pi and f_pi in 2+1 flavor QCD with domain wall fermions from QCDOC

We present results for the pseudoscalar meson masses and decay constants on 2+1 flavor DWF configurations with different sea quark masses and an inverse lattice spacing of 1.6(1) GeV, with a focus on chiral fits at small quark masses. The calculation is done on 16^3x32x8 lattices generated with the DBW2 gauge action.
Time and Frequency

Accuracy Degree of conformity of a measured or calculated value to its definition. Allan deviation cy, (7) Statistic used to estimate frequency stability. Coordinated Universal Time (UTC) International atomic time scale used by all major countries. Nominal frequency Ideal frequency, with zero uncertainty relative to its definition. Q Quality factor of an oscillator, estimated by dividing the resonance frequency by the resonance width. Resonance frequency Natural frequency of an oscillator, based on the repetition of a periodic event. Second Duration of 9,192,631,770 periods of the radiation corresponding to the transition between two hyperfine levels of the ground state of the cesium-133 atom. Stability Statistical estimate of the frequency or time fluctuations of a signal over a given time interval. Synchronization Process of setting two or more clocks to the same time. Syntonization Process of setting two or more oscillators to the same frequency. Time scale Agreed-upon system for keeping time. THIS article is an overview of time and frequency technology. It introduces basic time and frequency concepts and describes the devices that produce time and frequency signals and information. It explains how these devices work and how they are measured. Section I introduces the basic concepts of time and frequency and provides some historical background. Section I1 discusses time and frequency measurements and the specifications used to state the measurement results. Section 111 discusses time and frequency standards. These devices are grouped into two categories: quartz and atomic oscillators. Section IV discusses time and frequency transfer, or the process of using a clock or frequency standard to measure or set a device at another location.
A Study of Measurements in Curvature of the Spine

(1) The cases of right dorsal curvature show no evidence of unilateral weakness. (2) The cases of left dorsal curvature also show no evidence of unilateral weakness. (3) The cases of round shoulders show similar equality between the strength of the two sides. (4) The miscellaneous cases, including wry-neck and other deformities, show bilateral equality in the strength of trunk-muscles. These cases of spinal curvature suggest that unilateral muscular weakness does not enter as an etiological factor in idiopathic curvature of the spine. It may be added that in nearly all the cases of curvature studied, a detailed history of deforming posture in sitting, standing, or more especially sleeping, was obtained which seems to suggest an essential etiology of the trouble.
The Norm of the Fourier Transform on Compact or Discrete Abelian Groups

We calculate the norm of the Fourier operator from $$L^p(X)$$ to $$L^q({\hat{X}})$$ when X is an infinite locally compact abelian group that is, furthermore, compact or discrete. This subsumes the sharp Hausdorff–Young inequality on such groups. In particular, we identify the region in (p, q)-space where the norm is infinite, generalizing a result of Fournier, and setting up a contrast with the case of finite abelian groups, where the norm was determined by Gilbert and Rzeszotnik. As an application, uncertainty principles on such groups expressed in terms of Renyi entropies are discussed.
Active Learning for Undirected Graphical Model Selection

This paper studies graphical model selection, i.e., the problem of estimating a graph of statistical relationships among a collection of random variables. Conventional graphical model selection algorithms are passive, i.e., they require all the measurements to have been collected before processing begins. We propose an active learning algorithm that uses junction tree representations to adapt future measurements based on the information gathered from prior measurements. We prove that, under certain conditions, our active learning algorithm requires fewer scalar measurements than any passive algorithm to reliably estimate a graph. A range of numerical results validate our theory and demonstrates the benefits of active learning.
Hybrid cybernetic model-based simulation of continuous production of lignocellulosic ethanol: Rejecting abruptly changing feed conditions

Fermenting various sugars derived from lignocellulosic biomass promises to be attractive for producing ethanol, an important alternative fuel. Diversity of lignocellulosic biomass sources and pre-processing variations mean entering sugars are expected to experience large, though infrequent, changes. Recent developments in hybrid cybernetic modeling allow efficient in silico studies. This enables studying sequential linearization-based model predictive control for ensuring high productivity and conversion, for a chemostat seeded with yeast capable of co-fermentation. An appropriate controlled variable (conversion) and control formulation are ascertained. Also, a recently proposed hidden-Markov disturbance model, capable of describing the aforesaid changes, results in closed-loop performance superior to the typical integrated white-noise assumption.
The Use of Blanket Guarantees in Banking Crises

Policymakers often use guarantees on bank liabilities to prevent or contain bank runs during systemic banking crises, but their success has been debated. Using a sample of 42 episodes of banking crises, this paper finds that blanket guarantees do help to reduce liquidity pressures on banks, but only partially since they do not stem withdrawals from non-residents. Withdrawals following the announcement of guarantees are much more pronounced for non-resident liabilities than for foreign-currency denominated deposits—which may also be held by residents—suggesting that the results on non-residents are not driven by foreign-currency risk but by concerns about the government’s ability and commitment to honor the guarantee to non-resident liability holders.
New daily persistent headache.

Purpose of reviewThe entity of new daily persistent headache is a recognized form of chronic daily headache with a unique clinical presentation. This review will discuss the clinical characteristics, triggering factors, possible underlying pathogenesis and treatment options for this syndrome. It wil
Fourier Spectral Methods for Nonlocal Models

Efficient and accurate spectral solvers for nonlocal models in any spatial dimension are presented. The approach we pursue is based on the Fourier multipliers of nonlocal Laplace operators introduced in Alali and Albin (Appl Anal :1–21, 2019). It is demonstrated that the Fourier multipliers, and the eigenvalues in particular, can be computed accurately and efficiently. This is achieved through utilizing the hypergeometric representation of the Fourier multipliers in which their computation in n dimensions reduces to the computation of a 1D smooth function given in terms of 2F3. We use this representation to develop spectral techniques to solve periodic nonlocal time-dependent problems. For linear problems, such as the nonlocal diffusion and nonlocal wave equations, we use the diagonalizability of the nonlocal operators to produce a semi-analytic approach. For nonlinear problems, we present a pseudo-spectral method and apply it to solve a Brusselator model with nonlocal diffusion. Accuracy and efficiency of the spectral solvers are discussed.
Raman Analysis of Electron-Phonon Interactions in GaN Films

Raman analysis of film quality, phonon-plasmon coupling, and phonon-exciton interaction in GaN films with varying Si doping levels is presented. The films exhibit a small stress component ∽0.1 GPa, calculated from the frequency shift of the E2 mode. No correlation between the stress and the doping concentration was found. No forbidden Raman lines were detected in the spectra, implying high quality oriented films. The Raman lineshape of the E2 mode is a Lorentzian with similar linewidths at room temperature and at 10K indicating a homogeneous lifetime broadening mechanism which is not significantly affected by the change in temperature. The linewidth is also independent of Si concentration. The phonon-plasmon mixed frequency modes were calculated to be at ω−.=86 cm−1 and at ω+=741 cm−1 The modes are not present in the spectra and the only effect of the plasmons is a change of the Al(LO) lineshape. Analysis of the A1(LO) line indicated a uniform spatial doping distribution. A resonance effect was observed for the symmetry-allowed A1(LO) mode at T=10K with sub bandgap excitation light. The resonance interaction is consistent with the free exciton model.
Agglomerative Forces and Cluster Shapes

Abstract We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions yield agglomeration clusters that are much larger than the underlying agglomerative forces themselves. Empirically, we demonstrate that our model’s assumptions are present in the structure of technology and labor flows within Silicon Valley. Our model further identifies how the lengths over which agglomerative forces operate influence the shapes and sizes of industrial clusters; we confirm these predictions using variations across patent technology clusters.
An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction

Abstract Microstructure quantification is an essential component of materials science studies, yet, there are no widely applicable, standard methodologies, for image data representation in complex microstructures. Recently, machine learning methods have demonstrated success in image recognition tasks across disciplines, including materials science. In this work, we develop an approach for microstructure quantification for the purpose of kinetic modeling of a discontinuous precipitation reaction. We develop our approach in a case study on a U-Mo alloy which experiences this phase transformation during sub-eutectoid annealing. Prediction of material processing history based on image data (classification), calculation of area fraction of phases present in the micrographs (segmentation), and kinetic modeling from segmentation results were performed as part of this study. Results indicate that features extracted using a convolutional neural network (CNN) represent microstructure image data well, and segmentation via k-means clustering agree well with manually annotated images. Classification accuracy of original and segmented images is both 94% for a 5-class classification problem. Kinetic modeling results are consistent with previously reported data that employed manual thresholding. The image quantification and kinetic modeling approach developed and presented here aims to reduce researcher bias introduced into the characterization process, and allows for efficiently leveraging information in limited, unbalanced image data sets.
The structure of state corporate taxation and its impact on state tax revenues and economic activity

Abstract This paper documents facts about the state corporate tax structure — tax rates, base rules, and credits — and investigates its consequences for state tax revenue and economic activity. We present three main findings. First, tax base rules and credits explain more of the variation in state corporate tax revenues than tax rates do. Second, although states typically do not offset tax rate changes with base and credit changes, the effects of tax rate changes on tax revenue and economic activity depend on the breadth of the base. Third, as states have narrowed their tax bases, the relationship between tax rates and tax revenues has diminished. Overall, changes in state tax bases have made the state corporate tax system more favorable for corporations and are reducing the extent to which tax rate increases raise corporate tax revenue.
Toward an understanding of why suggestions work in charitable fundraising: Theory and evidence from a natural field experiment

Abstract People respond to those who ask. Within the charitable fundraising community, the power of the ask represents the backbone of most fundraising strategies. Despite this, the optimal design of communication strategies has received less formal attention. For their part, economists have recently explored how communication affects empathy, altruism, and giving rates to charities. Our study takes a step back from this literature to examine how suggestions–a direct ask for a certain amount of money–affect giving rates. We find that our suggestion amounts affect both the intensive and extensive margins: more people give and they tend to give the suggested amount. The resulting insights help us understand why people give, why messages work, and deepen practitioners' understanding of how to use messages to leverage more giving.
Retail Deliveries by Drones: How Will Logistics Networks Change?

Emerging technologies such as drone delivery services enable retailers to cost‐effectively offer unprecedented delivery speed and adaptable delivery lead times using dedicated aerial vehicles for individual orders. A natural and important question arises: What is the impact of a drone delivery system (DDS) on a retailer’s extant logistics parameters, for example, the number of customer‐facing delivery centers (last‐mile warehouses) it uses and delivery lead times it offers? On the one hand, the ability to reach customers faster than through traditional means argues for more centralization of delivery services. On the other hand, more decentralization can allow the retailer to offer hitherto unheard‐of delivery lead times and thereby spur demand. We show that, as drone technology matures and becomes more cost‐effective, delivery networks will become increasingly decentralized while delivering products at faster speeds. While perfect delivery customization—under which each demand location is offered a customized delivery guarantee—is theoretically feasible under a DDS, it may not be practical to implement such a finely differentiated delivery strategy. Instead, we show that retailers can recover a significant portion of the profit under this ideal scenario by offering limited delivery‐time customization, that is, partitioning the market into a few delivery “zones” and offering the best feasible delivery guarantee for each zone. In physically congested metropolitan markets, where retailers may be forced to operate with only a few delivery centers, it may be optimal to operate a DDS by offering delivery guarantees that are inferior to the best possible in order to throttle unprofitable demand. In such markets, the effectiveness of limited delivery‐time customization increases as the extent of physical congestion increases.
Mapping county-level mobility pattern changes in the United States in response to COVID-19

To contain the COVID-19 epidemic, one of the non-pharmacological epidemic control measures is reducing the transmission rate of SARS-COV-2 in the population through social distancing. An interactive web-based mapping platform that provides timely quantitative information on how people in different counties and states reacted to the social distancing guidelines was developed by the GeoDS Lab @UW-Madison with the support of the National Science Foundation RAPID program. The web portal integrates geographic information systems (GIS) and daily updated human mobility statistical patterns (median travel distance and stay-at-home dwell time) derived from large-scale anonymized and aggregated smartphone location big data at the county-level in the United States, and aims to increase risk awareness of the public, support data-driven public health and governmental decision-making, and help enhance community responses to the COVID-19 pandemic.