cssi/SciSciGPT-SciSciNet huggingface dataset:
Permutation Strikes Back: The Power of Recourse in Online Metric Matching

In this paper, we study the online metric matching with recourse (OMM-Recourse) problem. Given a metric space with k servers, a sequence of clients is revealed online. A client must be matched to an available server on arrival. Unlike the classical online matching model where the match is irrevocable, the recourse model permits the algorithm to rematch existing clients upon the arrival of a new client. The goal is to maintain an online matching with a near-optimal total cost, while at the same time not rematching too many clients. For the classical online metric matching problem without recourse, the optimal competitive ratio for deterministic algorithms is 2k-1, and the best-known randomized algorithms have competitive ratio O(log² k). For the much-studied special case of line metric, the best-known algorithms have competitive ratios of O(log k). Improving these competitive ratios (or showing lower bounds) are important open problems in this line of work. In this paper, we show that logarithmic recourse significantly improves the quality of matchings we can maintain online. For general metrics, we show a deterministic O(log k)-competitive algorithm, with O(log k) recourse per client, an exponential improvement over the 2k-1 lower bound without recourse. For line metrics we show a deterministic 3-competitive algorithm with O(log k) amortized recourse, again improving the best-known O(log k)-competitive algorithms without recourse. The first result (general metrics) simulates a batched version of the classical algorithm for OMM called Permutation. The second result (line metric) also uses Permutation as the foundation but makes non-trivial changes to the matching to balance the competitive ratio and recourse. Finally, we also consider the model when both clients and servers may arrive or depart dynamically, and exhibit a simple randomized O(log n)-competitive algorithm with O(log Δ) recourse, where n and Δ are the number of points and the aspect ratio of the underlying metric. We remark that no non-trivial bounds are possible in this fully-dynamic model when no recourse is allowed.
Mastering the Working Sequence in Human-Robot Collaborative Assembly Based on Reinforcement Learning

A long-standing goal of the Human-Robot Collaboration (HRC) in manufacturing systems is to increase the collaborative working efficiency. In line with the trend of Industry 4.0 to build up the smart manufacturing system, the collaborative robot in the HRC system deserves better designing to be more self-organized and to find the superhuman proficiency by self-learning. Inspired by the impressive machine learning algorithms developed by Google Deep Mind like Alphago Zero, in this paper, the human-robot collaborative assembly working process is formatted into a chessboard and the selection of moves in the chessboard is used to analogize the decision-making by both human and robot in the HRC assembly working process. To obtain the optimal policy of the working sequence to maximize the working efficiency, agents in the system are trained with a self-play algorithm based on reinforcement learning, without guidance or domain knowledge beyond game rules. A convolution neural network (CNN) is also trained to predict the distribution of the priority of move selections and whether a working sequence is the one resulting in the maximum of the HRC efficiency. A height-adjustable standing desk assembly is used to demonstrate the proposed HRC assembly algorithm and its efficiency in real-time task planning.
Nanopore sequencing at Mars, Europa, and microgravity conditions.

Nanopore sequencing, as represented by Oxford Nanopore Technologies’ MinION, is a promising technology for in situ life detection and for microbial monitoring including in support of human space exploration, due to its small size, low mass (~100 g) and low power (~1 W). Now ubiquitous on Earth and previously demonstrated on the International Space Station (ISS), nanopore sequencing involves translocation of DNA through a biological nanopore on timescales of milliseconds per base. Nanopore sequencing is now being done in both controlled lab settings as well as in diverse environments that include ground, air, and space vehicles. Future space missions may also utilize nanopore sequencing in reduced gravity environments, such as in the search for life on Mars (Earth-relative gravito-inertial acceleration (GIA) g = 0.378), or at icy moons such as Europa (g = 0.134) or Enceladus (g = 0.012). We confirm the ability to sequence at Mars as well as near Europa or Lunar (g = 0.166) and lower g levels, demonstrate the functionality of updated chemistry and sequencing protocols under parabolic flight, and reveal consistent performance across g level, during dynamic accelerations, and despite vibrations with significant power at translocation-relevant frequencies. Our work strengthens the use case for nanopore sequencing in dynamic environments on Earth and in space, including as part of the search for nucleic-acid based life beyond Earth.
Awas: AADL information flow and error propagation analysis framework

The continued maturation of industry standard architecture description languages is providing a foundation for more sophisticated analyses earlier in the system engineering process. The Architecture Analysis and Design Language (AADL) and its supporting annotation sub-languages provide the ability to model system hardware/software components as well as information flows within the system. Such flows include conventional notions of data/control flows, security-oriented information flows, and fault/error propagation paths that are supported by the AADL Error Modeling Annex (EMv2)—all of which are central to engineering safety/security-critical systems.
ATM inhibition synergizes with fenofibrate in high grade serous ovarian cancer cells

While therapies targeting deficiencies in the homologous recombination (HR) pathway are emerging as the standard treatment for high grade serous ovarian cancer (HGSOC) patients, this strategy is limited to the ~50% of patients with a deficiency in this pathway. Therefore, patients with HR-proficient tumors are likely to be resistant to these therapies and require alternative strategies. We found that the HR gene Ataxia Telangiectasia Mutated (ATM) is wildtype and its activity is upregulated in HGSOC compared to normal fallopian tube tissue. Interestingly, multiple pathways related to metabolism are inversely correlated with ATM expression in HGSOC specimens, suggesting that combining ATM inhibition with metabolic drugs would be effective. Analysis of FDA-approved drugs from the Dependency Map demonstrated that ATM-low cells are more sensitive to fenofibrate, a PPARα agonist that affects multiple cellular metabolic pathways. Consistently, PPARα signaling is associated with ATM expression. We validated that combined inhibition of ATM and treatment with fenofibrate is synergistic in multiple HGSOC cell lines by inducing senescence. Together, our results suggest that metabolic changes induced by ATM inhibitors are a potential target for the treatment of HGSOC.
Development and Testing of a Novel Automated Insect Capture Module for Sample Collection and Transfer

There exists an urgent need for efficient tools in disease surveillance to help model and predict the spread of disease. The transmission of insect-borne diseases poses a serious concern to public health officials and the medical and research community at large. In the modeling of this spread, we face bottlenecks in (1) the frequency at which we are able to sample insect vectors in environments that are prone to propagating disease, (2) manual labor needed to set up and retrieve surveillance devices like traps, and (3) the return time in analyzing insect samples and determining if an infectious disease is spreading in a region. To help address these bottlenecks, we present in this paper the design, fabrication, and testing of a novel automated insect capture module (ICM) or trap that aims to improve the rate of transferring samples collected from the environment via aerial robots. The ICM features an ultraviolet light attractant, passive capture mechanism, panels which can open and close for access to insects, and a small onboard computer for automated operation and data logging. At the same time, the ICM is designed to be accessible; it is small-scale, lightweight and low-cost, and can be integrated with commercially available aerial robots. Indoor and outdoor experimentation validates ICM’s feasibility in insect capturing and safe transportation. The device can help bring us one step closer toward achieving fully autonomous and scalable epidemiology by leveraging autonomous robots technology to aid the medical and research community.
Characterizing Capacity of Flexible Loads for Providing Grid Support

Flexible loads are a resource for the Balancing Authority (BA) of the future to aid in the balance of supply and demand in the power grid. Consequently, it is of interest for a BA to know how much flexibility a collection of loads has, so to successfully incorporate flexible loads into grid level resource allocation. Loads’ flexibility is limited by all their Quality of Service (QoS) requirements. In this work we present a characterization of capacity for a collection of flexible loads that is useful for long-term planning. This characterization is in terms of the power spectral density (PSD) of the demand deviation. Two advantages of our characterization are: (i) it easily allows a BA to perform resource allocation of flexible loads, especially for long-term planning, and (ii) it allows for precise definitions of the power and energy capacity for a collection of flexible loads.
$Q$-Series and Quantum Spin Networks

The tail of a quantum spin network in the two-sphere is a q-series associated to the network. We study the existence of the head and tail functions of quantum spin networks colored by 2n. We comput...
Fundamental resource trade-offs for encoded distributed optimization

Dealing with the shear size and complexity of today's massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments is that some of the worker nodes may run slow. These nodes a.k.a.~stragglers can significantly slow down computation as the slowest node may dictate the overall computational time. A recent computational framework, called encoded optimization, creates redundancy in the data to mitigate the effect of stragglers. In this paper we develop novel mathematical understanding for this framework demonstrating its effectiveness in much broader settings than was previously understood. We also analyze the convergence behavior of iterative encoded optimization algorithms, allowing us to characterize fundamental trade-offs between convergence rate, size of data set, accuracy, computational load (or data redundancy), and straggler toleration in this framework.
Recurrence relations and Benford’s law

There are now many theoretical explanations for why Benford’s law of digit bias surfaces in so many diverse fields and data sets. After briefly reviewing some of these, we discuss in detail recurrence relations. As these are discrete analogues of differential equations and model a variety of real world phenomena, they provide an important source of systems to test for Benfordness. Previous work showed that fixed depth recurrences with constant coefficients are Benford modulo some technical assumptions which are usually met; we briefly review that theory and then prove some new results extending to the case of linear recurrence relations with non-constant coefficients. We prove that, for certain families of functions f and g, a sequence generated by a recurrence relation of the form $$a_{n+1} = f(n)a_n + g(n)a_{n-1}$$ is Benford for all initial values. The proof proceeds by parameterizing the coefficients to obtain a recurrence relation of lower degree, and then converting to a new parameter space. From there we show that for suitable choices of f and g where f(n) is nondecreasing and $$g(n)/f(n)^2 \rightarrow 0$$ as $$n \rightarrow \infty $$ , the main term dominates and the behavior is equivalent to equidistribution problems previously studied. We also describe the results of generalizing further to higher-degree recurrence relations and multiplicative recurrence relations with non-constant coefficients, as well as the important case when f and g are values of random variables.
Localization of epileptic seizure focus by computerized analysis of fMRI recordings

By computerized analysis of cortical activity recorded via fMRI for pediatric epilepsy patients, we implement algorithmic localization of epileptic seizure focus within one of eight cortical lobes. Our innovative machine learning techniques involve intensive analysis of large matrices of mutual information coefficients between pairs of anatomically identified cortical regions. Drastic selection of pairs of regions with biologically significant inter-connectivity provides efficient inputs for our multi-layer perceptron (MLP) classifier. By imposing rigorous parameter parsimony to avoid overfitting, we construct a small-size MLP with very good percentages of successful classification.
Laboratory Findings Associated With Severe Illness and Mortality Among Hospitalized Individuals With Coronavirus Disease 2019 in Eastern Massachusetts.

Importance The coronavirus disease 2019 (COVID-19) pandemic has placed unprecedented stress on health systems across the world, and reliable estimates of risk for adverse hospital outcomes are needed. Objective To quantify admission laboratory and comorbidity features associated with critical illness and mortality risk across 6 Eastern Massachusetts hospitals. Design, Setting, and Participants Retrospective cohort study of all individuals admitted to the hospital who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by polymerase chain reaction across these 6 hospitals through June 5, 2020, using hospital course, prior diagnoses, and laboratory values in emergency department and inpatient settings from 2 academic medical centers and 4 community hospitals. The data were extracted on June 11, 2020, and the analysis was conducted from June to July 2020. Exposures SARS-CoV-2. Main Outcomes and Measures Severe illness defined by admission to intensive care unit, mechanical ventilation, or death. Results Of 2511 hospitalized individuals who tested positive for SARS-CoV-2 (of whom 50.9% were male, 53.9% White, and 27.0% Hispanic, with a mean [SD ]age of 62.6 [19.0] years), 215 (8.6%) were admitted to the intensive care unit, 164 (6.5%) required mechanical ventilation, and 292 (11.6%) died. L1-regression models developed in 3 of these hospitals yielded an area under the receiver operating characteristic curve of 0.807 for severe illness and 0.847 for mortality in the 3 held-out hospitals. In total, 212 of 292 deaths (72.6%) occurred in the highest-risk mortality quintile. Conclusions and Relevance In this cohort, specific admission laboratory studies in concert with sociodemographic features and prior diagnosis facilitated risk stratification among individuals hospitalized for COVID-19.
Sexually dimorphic DNA damage responses and mutation avoidance in the mouse germline

Germ cells specified during fetal development form the foundation of the mammalian germline. These primordial germ cells (PGCs) undergo rapid proliferation, yet the germline is highly refractory to mutation accumulation compared with somatic cells. Importantly, while the presence of endogenous or exogenous DNA damage has the potential to impact PGCs, there is little known about how these cells respond to stressors. To better understand the DNA damage response (DDR) in these cells, we exposed pregnant mice to ionizing radiation (IR) at specific gestational time points and assessed the DDR in PGCs. Our results show that PGCs prior to sex determination lack a G1 cell cycle checkpoint. Additionally, the response to IR-induced DNA damage differs between female and male PGCs post-sex determination. IR of female PGCs caused uncoupling of germ cell differentiation and meiotic initiation, while male PGCs exhibited repression of piRNA metabolism and transposon derepression. We also used whole-genome single-cell DNA sequencing to reveal that genetic rescue of DNA repair-deficient germ cells (Fancm-/- ) leads to increased mutation incidence and biases. Importantly, our work uncovers novel insights into how PGCs exposed to DNA damage can become developmentally defective, leaving only those genetically fit cells to establish the adult germline.
A Level Set Approach to Online Sensing and Trajectory Optimization with Time Delays

Abstract Presented is a method to compute certain classes of Hamilton-Jacobi equations that result from optimal control and trajectory generation problems with time delays. Many robotic control and trajectory problems have limited information of the operating environment a priori and must continually perform online trajectory optimization in real time after collecting measurements. The sensing and optimization can induce a significant time delay, and must be accounted for when computing the trajectory. This paper utilizes the generalized Hopf formula, which avoids the exponential dimensional scaling typical of other numerical methods for computing solutions to the Hamilton-Jacobi equation. We present as an example a robot that incrementally predicts a communication channel from measurements as it travels. As part of this example, we introduce a seemingly new generalization of a non-parametric formulation of robotic communication channel estimation. New communication measurements are used to improve the channel estimate and online trajectory optimization with time-delay compensation is performed.
Parallel transport time-dependent density functional theory calculations with hybrid functional on summit

Real-time time-dependent density functional theory (rt-TDDFT) with hybrid exchange-correlation functional has wide-ranging applications in chemistry and material science simulations. However, it can be thousands of times more expensive than a conventional ground state DFT simulation, and hence is limited to small systems. In this paper, we accelerate hybrid functional rt-TDDFT calculations using the parallel transport gauge formalism, and the GPU implementation on Summit. Our implementation can efficiently scale to 786 GPUs for a large system with 1536 silicon atoms, and the wall clock time is only 1.5 hours per femtosecond. This unprecedented speed enables the simulation of large systems with more than 1000 atoms using rt-TDDFT and hybrid functional.
Equivalent non-isotopic spheres in 4-manifolds

We construct infinitely many smooth oriented 4-manifolds containing pairs of homotopic, smoothly embedded 2-spheres that are not topologically isotopic, but that are equivalent by an ambient diffeomorphism inducing the identity on homology. These examples show that Gabai's recent "Generalized" 4D Lightbulb Theorem does not generalize to arbitrary 4-manifolds. In contrast, we also show that there are smoothly embedded 2-spheres that are both equivalent and topologically isotopic, but not smoothly isotopic.
Scalar and spinor effective actions in global de Sitter

In this paper, we compute the effective action of both a scalar field and a Dirac spinor field in the global de Sitter space of any dimension d using the in-/out-state formalism. We show that there is particle production in even dimensions for both scalar field and spinor field. The in-out vacuum amplitude $$ {\mathcal{Z}}_{\mathrm{in}/\mathrm{out}} $$ is divergent at late times. By using dimensional regularization, we extract the finite part of log $$ {\mathcal{Z}}_{\mathrm{in}/\mathrm{out}} $$ for d even and the logarithmically divergent part of log $$ {\mathcal{Z}}_{\mathrm{in}/\mathrm{out}} $$ for d odd. We also find that the regularized in-out vacuum amplitude equals the ratio of determinants associated with different quantizations in AdSd upon the identification of certain parameters in the two theories.
IMPROVED PHOTOMETRIC REDSHIFTS WITH SURFACE LUMINOSITY PRIORS

We apply Bayesian statistics with prior probabilities of galaxy surface luminosity (SL) to improve photometric redshifts. We apply the method to a sample of 1266 galaxies with spectroscopic redshifts in the GOODS North and South fields at 0.1 . z . 2.0. We start with spectrophotometric redshifts (SPZs) based on Probing Evolution and Reionization Spectroscopically grism spectra, which cover a wavelength range of 6000–9000u combined with (U)BV iz(JHK) broadband photometry in the GOODS fields. The accuracy of SPZ redshifts is estimated to be �(�(z)) = 0.035 with an systematic offset of –0.026, where �(z) = �z/(1+z), for galaxies in redshift range of 0.5 . z . 1.25. The addition of the SL prior probability helps break the degeneracy of SPZ redshifts between low redshift 4000 u break galaxies and high-redshift Lyman break galaxies which are mostly catastrophic outliers. For the 1138 galaxies at z . 1.6, the fraction of galaxies with redshift deviation �(z) > 0.2 is reduced from 15.0% to 10.4%, while the rms scatter of the fractional redshift error does not change much.
VULCAN PLANETS: INSIDE-OUT FORMATION OF THE INNERMOST SUPER-EARTHS

The compact multi-transiting systems discovered by Kepler challenge traditional planet formation theories. These fall into two broad classes: (1) formation further out followed by migration and (2) formation in situ from a disk of gas and planetesimals. In the former, an abundance of resonant chains is expected, which the Kepler data do not support. In the latter, required disk mass surface densities may be too high. A recently proposed mechanism hypothesizes that planets form in situ at the pressure trap associated with the dead-zone inner boundary (DZIB) where radially drifting pebbles accumulate. This scenario predicts planet masses (Mp ) are set by the gap-opening process that then leads to DZIB retreat, followed by sequential, inside-out planet formation (IOPF). For typical disk accretion rates, IOPF predictions for Mp , Mp versus orbital radius r, and planet-planet separations are consistent with observed systems. Here we investigate the IOPF prediction for how the masses, M p, 1, of the innermost (Vulcan) planets vary with r. We show that for fiducial parameters, M p, 1 5.0(r/0.1 AU) M ⊕, independent of the disk's accretion rate at time of planet formation. Then, using Monte Carlo sampling of a population of these innermost planets, we test this predicted scaling against observed planet properties, allowing for intrinsic dispersions in planetary densities and Kepler's observational biases. These effects lead to a slightly shallower relation M p, 1r 0.9 ± 0.2, which is consistent with M p, 1r 0.7 ± 0.2 of the observed Vulcans. The normalization of the relation constrains the gap-opening process, favoring relatively low viscosities in the inner dead zone.
Heterobilayers of 2D materials as a platform for excitonic superfluidity.

Excitonic condensate has been long-sought within bulk indirect-gap semiconductors, quantum wells, and 2D material layers, all tried as carrying media. Here, we propose intrinsically stable 2D semiconductor heterostructures with doubly-indirect overlapping bands as optimal platforms for excitonic condensation. After screening hundreds of 2D materials, we identify candidates where spontaneous excitonic condensation mediated by purely electronic interaction should occur, and hetero-pairs Sb2Te2Se/BiTeCl, Hf2N2I2/Zr2N2Cl2, and LiAlTe2/BiTeI emerge promising. Unlike monolayers, where excitonic condensation is hampered by Peierls instability, or other bilayers, where doping by applied voltage is required, rendering them essentially non-equilibrium systems, the chemically-specific heterostructures predicted here are lattice-matched, show no detrimental electronic instability, and display broken type-III gap, thus offering optimal carrier density without any gate voltages, in true-equilibrium. Predicted materials can be used to access different parts of electron-hole phase diagram, including BEC-BCS crossover, enabling tantalizing applications in superfluid transport, Josephson-like tunneling, and dissipationless charge counterflow. Here, the authors screen hundreds of 2D materials and identify the candidates where spontaneous excitonic condensation mediated by purely electronic interaction should occur in true equilibrium. Hetero-pairs Sb2Te2Se/BiTeCl, Hf2N2I2/Zr2N2Cl2, and LiAlTe2/BiTeI emerge as promising.
Hydrodynamic transport in strongly coupled disordered quantum field theories

We compute direct current (dc) thermoelectric transport coecients in strongly coupled quantum eld theories without long lived quasiparticles, at nite temperature and charge density, and disordered on long wavelengths compared to the length scale of local thermaliza- tion. Many previous transport computations in strongly coupled systems are interpretable hydrodynamically, despite formally going beyond the hydrodynamic regime. This includes momentum relaxation times previously derived by the memory matrix formalism, and non- perturbative holographic results; in the latter case, this is subject to some important sub- tleties. Our formalism may extend some memory matrix computations to higher orders in the perturbative disorder strength, as well as give valuable insight into non-perturbative regimes. Strongly coupled metals with quantum critical contributions to transport gener- ically transition between coherent and incoherent metals as disorder strength is increased at xed temperature, analogous to mean eld holographic treatments of disorder. From a
Altered functional connectivity of cortical networks in semantic variant Primary Progressive Aphasia.

Abstract As their illness progresses, patients with the semantic variant of Primary Progressive Aphasia (svPPA) frequently exhibit peculiar behaviors indicative of altered visual attention or an increased interest in artistic endeavors. In the present study, we examined changes within and between large-scale functional brain networks that may explain this altered visual behavior. We first examined the connectivity of the visual association network, the dorsal attention network, and the default mode network in healthy young adults (n = 89) to understand the typical architecture of these networks in the healthy brain. We then compared the large-scale functional connectivity of these networks in a group of svPPA patients (n = 12) to a group of age-matched cognitively normal controls (n = 30). Our results showed that the between-network connectivity of the dorsal attention and visual association networks was elevated in svPPA patients relative to controls. We further showed that this heightened between-network connectivity was associated with a decrease in the within-network connectivity of the default mode network, possibly due to progressive degeneration of the anterior temporal lobes in svPPA. These results suggest that focal neurodegeneration can lead to the reorganization of large-scale cognitive networks beyond the primarily affected network(s), possibly contributing to cognitive or behavioral changes that are commonly present as part of the clinical phenotype of svPPA.
Synchronization and control in intrinsic and designed computation: An information-theoretic analysis of competing models of stochastic computation

We adapt tools from information theory to analyze how an observer comes to synchronize with the hidden states of a finitary, stationary stochastic process. We show that synchronization is determined by both the process’s internal organization and by an observer’s model of it. We analyze these components using the convergence of state-block and block-state entropies, comparing them to the previously known convergence properties of the Shannon block entropy. Along the way we introduce a hierarchy of information quantifiers as derivatives and integrals of these entropies, which parallels a similar hierarchy introduced for block entropy. We also draw out the duality between synchronization properties and a process’s controllability. These tools lead to a new classification of a process’s alternative representations in terms of minimality, synchronizability, and unifilarity.
MODELING THE LARGE-SCALE BIAS OF NEUTRAL HYDROGEN

We present new analytical estimates of the large-scale bias of neutral hydrogen (H I). We use a simple, non-parametric model which monotonically relates the total mass of a halo M{sub tot} with its H I mass M{sub HI} at zero redshift; for earlier times we assume limiting models for the {Omega}{sub HI} evolution consistent with the data presently available, as well as two main scenarios for the evolution of our M{sub HI}-M{sub tot} relation. We find that both the linear and the first nonlinear bias terms exhibit a strong evolution with redshift, regardless of the specific limiting model assumed for the H I density over time. These analytical predictions are then shown to be consistent with measurements performed on the Millennium Simulation. Additionally, we show that this strong bias evolution does not sensibly affect the measurement of the H I power spectrum.
Measuring the Slope of the Dust Extinction Law and the Power Spectrum of Dust Clouds Using Differentially Reddened Globular Clusters

We present three methods for measuring the slope of the Galactic dust extinction law, RV, and a method for measuring the fine-scale structure of dust clouds in the direction of differentially reddened globular clusters. We apply these techniques to BVI photometry of stars in the low-latitude Galactic globular cluster NGC 4833, which displays spatially variable extinction/reddening about a mean AV ≈ 1. An extensive suite of Monte Carlo simulations is used to characterize the efficacy of the methods. The essence of the first two methods is to determine, for an assumed value of RV, the relative visual extinction δAV of each cluster horizontal-branch (HB) star with respect to an empirical HB locus; the locus is derived from the color-magnitude diagram (CMD) of a subset of stars in a small region near the cluster center for which differential extinction/reddening are relatively small. A star-by-star comparison of δAV from the (B - V, V) CMD with that from the (V - I, V) CMD is used to find the optimal RV. In the third method RV is determined by minimizing the scatter in the HB in the (B - V, V) CMD after correcting the photometry for extinction and reddening using the dust maps of Schlegel, Finkbeiner, & Davis. The weighted average of the results from the three methods gives RV = 3.0 ± 0.4 for the dust along the line of sight to NGC 4833. The fine-scale structure of the dust is quantified via the difference, (ΔAV)ij ≡ (δAV)i - (δAV)j, between pairs of cluster HB stars (i, j) as a function of their angular separation rij. The variance (mean square scatter) of (ΔAV)ij is found to have a power-law dependence on angular scale: var(r) ∝ rβ, with β = +0.9 ± 0.1. This translates into an angular power spectrum P(κ) ∝ κα, with the index α = -1.9 ± 0.1 for r ~ 1'–5', where κ ≡ 1/r. The dust angular power spectrum on small scales (from optical data) matches smoothly onto the larger scale power spectrum derived from Schlegel et al.'s far-infrared map of the dust thermal emission.
An intriguing solar microflare observed with RHESSI, Hinode, and TRACE

Aims. We investigate particle acceleration and heating in a solar microflare. Methods. In a microflare with non-thermal emission to remarkably high energies (>50 keV), we investigate the hard X-rays with RHESSI imaging and spectroscopy and the resulting thermal emission seen in soft X-rays with Hinode/XRT and in EUV with TRACE. Results. The non-thermal footpoints observed with RHESSI spatially and temporally match bright footpoint emission in soft X-rays and EUV. There is the possibility that the non-thermal spectrum extends down to 4 keV. The hard X-ray burst clearly does not follow the expected Neupert effect, with the time integrated hard X-rays not matching the soft X-ray time profile. So, although this is a simple microflare with good X-ray observation coverage it does not fit the standard flare model.
Koszul complexes, Birkhoff normal form and the magnetic Dirac operator

We consider the semiclassical Dirac operator coupled to a magnetic potential on a large class of manifolds, including all metric contact manifolds. We prove a sharp Weyl law and a bound on its eta invariant. In the absence of a Fourier integral parametrix, the method relies on the use of almost analytic continuations combined with the Birkhoff normal form and local index theory.
Disentangling degenerate solutions from primary transit and secondary eclipse spectroscopy of exoplanets

Infrared transmission and emission spectroscopy of exoplanets, recorded from primary transit and secondary eclipse measurements, indicate the presence of the most abundant carbon and oxygen molecul...
Can the Discrepancy between Locally and Globally Derived Neutral Hydrogen Mass Functions be Explained by a Varying Value of M

I investigate whether it is possible to reconcile the recent Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) observation that the neutral hydrogen mass function (HIMF) across different galactic densities has the same, non-flat, faint-end slope, with observations of isolated galaxies and many galaxy groups that show their HIMFs to have flat faint-end slopes. I find that a fairly simple model in which the position of the knee in the mass function of each individual group is allowed to vary is able to account for both of these observations. If this model reflects reality, the ALFALFA results point to an interesting "conspiracy" whereby the differing group HIMFs always sum up to form global HIMFs with the same faint-end slope in different environments. More generally, this result implies that global environmental HIMFs do not necessarily reflect the HIMFs in individual groups belonging to that environment and cannot be used to directly measure variations in group-specific HIMFs with environment.
Data Races and the Discrete Resource-time Tradeoff Problem with Resource Reuse over Paths

A determinacy race occurs if two or more logically parallel instructions access the same memory location and at least one of them tries to modify its content. Races are often undesirable as they can lead to nondeterministic and incorrect program behavior. A data race is a special case of a determinacy race which can be eliminated by associating a mutual-exclusion lock with the memory location in question or allowing atomic accesses to it. However, such solutions can reduce parallelism by serializing all accesses to that location. For associative and commutative updates to a memory cell, one can instead use a reducer, which allows parallel race-free updates at the expense of using some extra space. More extra space usually leads to more parallel updates, which in turn contributes to potentially lowering the overall execution time of the program. We start by asking the following question. Given a fixed budget of extra space for mitigating the cost of races in a parallel program, which memory locations should be assigned reducers and how should the space be distributed among those reducers in order to minimize the overall running time? We argue that under reasonable conditions the races of a program can be captured by a directed acyclic graph (DAG), with nodes representing memory cells and arcs representing read-write dependencies between cells. We then formulate our original question as an optimization problem on this DAG. We concentrate on a variation of this problem where space reuse among reducers is allowed by routing every unit of extra space along a (possibly different) source to sink path of the DAG and using it in the construction of multiple (possibly zero) reducers along the path. We consider two different ways of constructing a reducer and the corresponding duration functions (i.e., reduction time as a function of space budget). We generalize our race-avoiding space-time tradeoff problem to a discrete resource-time tradeoff problem with general non-increasing duration functions and resource reuse over paths of the given DAG. For general DAGs, we show that even if the entire DAG is available offline the problem is strongly NP-hard under all three duration functions, and we give approximation algorithms for solving the corresponding optimization problems. We also prove hardness of approximation for the general resource-time tradeoff problem and give a pseudo-polynomial time algorithm for series-parallel DAGs.
Using conditional generative adversarial networks to reduce the effects of latency in robotic telesurgery

The introduction of surgical robots brought about advancements in surgical procedures. The applications of remote telesurgery range from building medical clinics in underprivileged areas, to placing robots abroad in military hot-spots where accessibility and diversity of medical experience may be limited. Poor wireless connectivity may result in a prolonged delay, referred to as latency, between a surgeon's input and action which a robot takes. In surgery, any micro-delay can injure a patient severely and, in some cases, result in fatality. One way to increase safety is to mitigate the effects of latency using deep learning aided computer vision. While the current surgical robots use calibrated sensors to measure the position of the arms and tools, in this work, we present a purely optical approach that provides a measurement of the tool position in relation to the patient's tissues. This research aimed to produce a neural network that allowed a robot to detect its own mechanical manipulator arms. A conditional generative adversarial network (cGAN) was trained on 1107 frames of a mock gastrointestinal robotic surgery from the 2015 EndoVis Instrument Challenge and corresponding hand-drawn labels for each frame. When run on new testing data, the network generated near-perfect labels of the input images which were visually consistent with the hand-drawn labels and was able to do this in 299 ms. These accurately generated labels can then be used as simplified identifiers for the robot to track its own controlled tools. These results show potential for conditional GANs as a reaction mechanism, such that the robot can detect when its arms move outside the operating area in a patient. This system allows for more accurate monitoring of the position of surgical instruments in relation to the patient's tissue, increasing safety measures that are integral to successful telesurgery systems.
Applications of a new formula for OPUC with periodic Verblunsky coefficients

We find a new formula for the orthonormal polynomials corresponding to a measure $$\mu $$ on the unit circle whose Verblunsky coefficients are periodic. The formula is presented using the Chebyshev polynomials of the second kind and the discriminant of the periodic sequence. We present several applications including a resolution of a problem suggested by Simon (Commun Pure Appl Math 59(7):1042–1062, 2006) regarding the existence of singular points in the bands of the support of the measure and a universality result at all points of the essential support of $$\mu $$ .
Self-Destructing Dark Matter

We present Self-Destructing Dark Matter (SDDM), a new class of dark matter models which are detectable in large neutrino detectors. In this class of models, a component of dark matter can transition from a long-lived state to a short-lived one by scattering off of a nucleus or an electron in the Earth. The short-lived state then decays to Standard Model particles, generating a dark matter signal with a visible energy of order the dark matter mass rather than just its recoil. This leads to striking signals in large detectors with high energy thresholds. We present a few examples of models which exhibit self destruction, all inspired by bound state dynamics in the Standard Model. The models under consideration exhibit a rich phenomenology, possibly featuring events with one, two, or even three lepton pairs, each with a fixed invariant mass and a fixed energy, as well as non-trivial directional distributions. This motivates dedicated searches for dark matter in large underground detectors such as Super-K, Borexino, SNO+, and DUNE.
Origins and Interpretation of Tidal Debris

The stellar debris structures that have been discovered around the Milky Way and other galaxies are thought to be formed from the disruption of satellite stellar systems—dwarf galaxies or globular clusters—by galactic tidal fields. The total stellar mass in these structures is typically tiny compared to the galaxy around which they are found, and it is hence easy to dismiss them as inconsequential. However, they are remarkably useful as probes of a galaxy’s history (as described in this chapter) and mass distribution (covered in a companion chapter in this volume). This power is actually a consequence of their apparent insignificance: their low contribution to the overall mass makes the physics that describes them both elegant and simple and this means that their observed properties are relatively easy to understand and interpret.
Persistent Homology in Sparse Regression and Its Application to Brain Morphometry

Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by treating the the tuning parameter as an additional dimension, persistent homological structures over the parameter space is introduced and explored. The structures are then further exploited in drastically speeding up the computation using the proposed soft-thresholding technique. The topological structures are further used as multivariate features in the tensor-based morphometry (TBM) in characterizing white matter alterations in children who have experienced severe early life stress and maltreatment. These analyses reveal that stress-exposed children exhibit more diffuse anatomical organization across the whole white matter region.
Information-Based Optimal Subdata Selection for Big Data Linear Regression

Extraordinary amounts of data are being produced in many branches of science. Proven statistical methods are no longer applicable with extraordinary large datasets due to computational limitations....
On an asymptotic series of Ramanujan

An asymptotic series in Ramanujan’s second notebook (Entry 10, Chap. 3) is concerned with the behavior of the expected value of φ(X) for large λ where X is a Poisson random variable with mean λ and φ is a function satisfying certain growth conditions. We generalize this by studying the asymptotics of the expected value of φ(X) when the distribution of X belongs to a suitable family indexed by a convolution parameter. Examples include the binomial, negative binomial, and gamma families. Some formulas associated with the negative binomial appear new.
Two diverse models of embedding class one

Abstract Embedding theorems have continued to be a topic of interest in the general theory of relativity since these help connect the classical theory to higher-dimensional manifolds. This paper deals with spacetimes of embedding class one, i.e., spacetimes that can be embedded in a five-dimensional flat spacetime. These ideas are applied to two diverse models, a complete solution for a charged wormhole admitting a one-parameter group of conformal motions and a new model to explain the flat rotation curves in spiral galaxies without the need for dark matter.
High Resolution Imaging of Very Low Mass Spectral Binaries: Three Resolved Systems and Detection of Orbital Motion in an L/T Transition Binary

We present high resolution Laser Guide Star Adaptive Optics imaging of 43 late-M, L and T dwarf systems with Keck/NIRC2. These include 17 spectral binary candidates, systems whose spectra suggest the presence of a T dwarf secondary. We resolve three systems: 2MASS J1341–3052, SDSS J1511+0607 and SDSS J2052–1609; the first two are resolved for the first time. All three have projected separations <8 AU and estimated periods of 14–80 years. We also report a preliminary orbit determination for SDSS J2052–1609 based on six epochs of resolved astrometry between 2005 and 2010. Among the 14 unresolved spectral binaries, 5 systems were confirmed binaries but remained unresolved, implying a minimum binary fraction of 47_(-11)^(+12) for this sample. Our inability to resolve most of the spectral binaries, including the confirmed binaries, supports the hypothesis that a large fraction of very low mass systems have relatively small separations and are missed with direct imaging.
A Pan-STARRS + UKIDSS search for young, wide planetary-mass companions in Upper Scorpius

We have combined optical and NIR photometry from Pan-STARRS 1 and UKIDSS to search the young (5-10 Myr) star-forming region of Upper Scorpius for wide ( Almost-Equal-To 400-4000 AU) substellar companions down to {approx}5 M{sub Jup}. Our search is Almost-Equal-To 4 mag deeper than previous work based on the Two Micron All Sky Survey. We identified several candidates around known stellar members using a combination of color selection and spectral energy distribution fitting. Our follow-up spectroscopy has identified two new companions as well as confirmed two companions previously identified from photometry, with spectral types of M7.5-M9 and masses of {approx}15-60 M{sub Jup}, indicating a frequency for such wide substellar companions of {approx}0.6% {+-} 0.3%. Both USco 1610-1913B and USco 1612-1800B are more luminous than expected for their spectral type compared with known members of Upper Sco. HIP 77900B has an extreme mass ratio (M{sub 2}/M{sub 1} Almost-Equal-To 0.005) and an extreme separation of 3200 AU. USco 1602-2401B also has a very large separation of 1000 AU. We have also confirmed a low-mass stellar companion, USco 1610-2502B (730 AU, M5.5). Our substellar companions appear both non-coeval with their primary stars according to evolutionary models and, as a group, are systematically moremore » luminous than the Upper Sco cluster sequence. One possible reason for these luminosity discrepancies could be different formation processes or accretion histories for these objects.« less
The Link between Rare-Earth Peak Formation and the Astrophysical Site of the R Process

The primary astrophysical source of the rare earth elements is the rapid neutron capture process ($r$ process). The rare earth peak that is seen in the solar $r$-process residuals has been proposed to originate as a pile-up of nuclei during the end of the $r$ process. We introduce a new method utilizing Monte Carlo studies of nuclear masses in the rare earth region, that includes self-consistently adjusting $\beta$-decay rates and neutron capture rates, to find the mass surfaces necessary for the formation of the rare earth peak. We demonstrate our method with two types of astrophysical scenarios, one corresponding conditions typical of core-collapse supernova winds and one corresponding to conditions typical of the ejection of the material from the tidal tails of neutron star mergers. In each type of astrophysical conditions, this method successfully locates a region of enhanced stability in the mass surface that is responsible for the rare earth peak. For each scenario, we find that the change in the mass surface has qualitatively different features, thus future measurements can shed light on the type of environment in which the $r$ process occurred.