cssi/SciSciGPT-SciSciNet huggingface dataset:
Stochastic Artificial Potentials for Online Safe Navigation

Consider a convex set of which we remove an arbitrary number of disjoints convex sets—the obstacles—and a convex function whose minimum is the agent's goal. We consider a local and stochastic approximation of the gradient of a Rimon–Koditschek navigation function where the attractive potential is the convex function that the agent is minimizing. In particular, we show that if the estimate available to the agent is unbiased, convergence to the desired location while avoiding the obstacles is guaranteed with probability one under the same geometrical conditions as in the deterministic case. Qualitatively these conditions are that the ratio between the maximum and minimum eigenvalue of the Hessian of the objective function is not too large and that the obstacles are not too flat or too close to the desired destination. Moreover, we show that for biased estimates convergence to a point arbitrarily close to the goal is achieved with probability one. The assumptions on the bias for the result to hold are motivated by the study of the estimate of the gradient of a Rimon–Koditschek navigation function for sensor models that fit circles around the obstacles. Numerical examples explore the practical value of these theoretical results.
Learning to Separate Multiple Illuminants in a Single Image

We present a method to separate a single image captured under two illuminants, with different spectra, into the two images corresponding to the appearance of the scene under each individual illuminant. We do this by training a deep neural network to predict the per-pixel reflectance chromaticity of the scene, which we use in conjunction with a previous flash/no-flash image-based separation algorithm to produce the final two output images. We design our reflectance chromaticity network and loss functions by incorporating intuitions from the physics of image formation. We show that this leads to significantly better performance than other single image techniques and even approaches the quality of the two image separation method.
Recurrences for Eulerian Polynomials of Type B and Type D

We introduce new recurrences for the type B and type D Eulerian polynomials, and interpret them combinatorially. These recurrences are analogous to a well-known recurrence for the type A Eulerian polynomials. We also discuss their relationship to polynomials introduced by Savage and Visontai in connection to the real-rootedness of the corresponding Eulerian polynomials.
Dense piecewise planar RGB-D SLAM for indoor environments

The paper exploits weak Manhattan constraints to parse the structure of indoor environments from RGB-D video sequences in an online setting. We extend the previous approach for single view parsing of indoor scenes to video sequences and formulate the problem of recovering the floor plan of the environment as an optimal labeling problem solved using dynamic programming. The temporal continuity is enforced in a recursive setting, where labeling from previous frames is used as a prior term in the objective function. In addition to recovery of piecewise planar weak Manhattan structure of the extended environment, the orthogonality constraints are also exploited by visual odometry and pose graph optimization. This yields reliable estimates in the presence of large motions and absence of distinctive features to track. We evaluate our method on several challenging indoors sequences demonstrating accurate SLAM and dense mapping of low texture environments. On existing TUM benchmark [19] we achieve competitive results with the alternative approaches which fail in our environments.
Personalized cancer therapy design: Robustness vs. optimality

Intermittent Androgen Suppression (IAS) is a treatment strategy for delaying or even preventing time to relapse of advanced prostate cancer. IAS consists of alternating cycles of therapy (in the form of androgen suppression) and off-treatment periods. The level of prostate specific antigen (PSA) in a patient's serum is frequently monitored to determine when the patient will be taken off therapy and when therapy will resume. In spite of extensive recent clinical experience with IAS, the design of an ideal protocol for any given patient remains one of the main challenges associated with effectively implementing this therapy. We use a threshold-based policy for optimal IAS therapy design that is parameterized by lower and upper PSA threshold values and is associated with a cost metric that combines clinically relevant measures of therapy success. We apply Infinitesimal Perturbation Analysis (IPA) to a Stochastic Hybrid Automaton (SHA) model of prostate cancer evolution under IAS and derive unbiased estimators of the cost metric gradient with respect to various model and therapy parameters. These estimators are subsequently used for system analysis. By evaluating sensitivity estimates with respect to several model parameters, we identify critical ones and demonstrate that relaxing the optimality condition in favor of increased robustness to modeling errors provides an alternative objective to therapy design for at least some patients.
Optimization over continuous and multi-dimensional decisions with observational data

We consider the optimization of an uncertain objective over continuous and multidimensional decision spaces in problems in which we are only provided with observational data. We propose a novel algorithmic framework that is tractable, asymptotically consistent, and superior to comparable methods on example problems. Our approach leverages predictive machine learning methods and incorporates information on the uncertainty of the predicted outcomes for the purpose of prescribing decisions. We demonstrate the efficacy of our method on examples involving both synthetic and real data sets.
Equivariant resolution of singularities in characteristic 0

A new proof of equivariant resolution of singularities under a finite group action in characteristic 0 is provided. We assume we know how to resolve singularities without group action. We first prove equivariant resolution of toroidal singularities. Then we reduce the general case to the toroidal case.
Random triangle removal

Abstract Starting from a complete graph on n vertices, repeatedly delete the edges of a uniformly chosen triangle. This stochastic process terminates once it arrives at a triangle-free graph, and the fundamental question is to estimate the final number of edges (equivalently, the time it takes the process to finish, or how many edge-disjoint triangles are packed via the random greedy algorithm). Bollobas and Erdős (1990) conjectured that the expected final number of edges has order n 3 / 2 . An upper bound of o ( n 2 ) was shown by Spencer (1995) and independently by Rodl and Thoma (1996). Several bounds were given for variants and generalizations (e.g., Alon, Kim and Spencer (1997) and Wormald (1999)), while the best known upper bound for the original question of Bollobas and Erdős was n 7 / 4 + o ( 1 ) due to Grable (1997). No nontrivial lower bound was available. Here we prove that with high probability the final number of edges in random triangle removal is equal to n 3 / 2 + o ( 1 ) , thus confirming the 3/2 exponent conjectured by Bollobas and Erdős and matching the predictions of Gordon, Kuperberg, Patashnik, and Spencer (1996). For the upper bound, for any fixed e > 0 we construct a family of exp ⁡ ( O ( 1 / e ) ) graphs by gluing O ( 1 / e ) triangles sequentially in a prescribed manner, and dynamically track the number of all homomorphisms from them, rooted at any two vertices, up to the point where n 3 / 2 + e edges remain. A system of martingales establishes concentration for these random variables around their analogous means in a random graph with corresponding edge density, and a key role is played by the self-correcting nature of the process. The lower bound builds on the estimates at that very point to show that the process will typically terminate with at least n 3 / 2 − o ( 1 ) edges left.
A coarse-grid incremental pressure projection method for accelerating low Reynolds number incompressible flow simulations

Coarse-grid projection (CGP) multigrid techniques are applicable to sets of equations that include at least one decoupled linear elliptic equation. In CGP, the linear elliptic equation is solved on a coarsened grid compared to the other equations, leading to savings in computation time and complexity. One of the most important applications of CGP is when a pressure correction scheme is used to obtain a numerical solution to the Navier–Stokes equations. In that case, there is an elliptic pressure Poisson equation. Depending on the pressure correction scheme used, the CGP method and its performance in terms of acceleration rate and accuracy level vary. The CGP framework has been established for non-incremental pressure projection techniques. In this article, we apply CGP methodology for the first time to incremental pressure correction schemes. Both standard and rotational forms of the incremental algorithms are considered. The influence of velocity Dirichlet and natural homogenous boundary conditions in regular and irregular domains with structured and unstructured triangular finite element meshes is investigated. $$L^2$$ norms demonstrate that the level of accuracy of the velocity and the pressure fields is preserved for up to three levels of coarsening. For the test cases investigated, the speedup factors range approximately from 1.2 to 102.7.
Area bounds for free boundary minimal surfaces in a geodesic ball in the sphere

Abstract We extend to higher dimensions earlier sharp bounds for the area of two dimensional free boundary minimal surfaces contained in a geodesic ball of the round sphere. This follows work of Brendle and Fraser-Schoen in the euclidean case.
Improved Path-length Regret Bounds for Bandits

We study adaptive regret bounds in terms of the variation of the losses (the so-called path-length bounds) for both multi-armed bandit and more generally linear bandit. We first show that the seemingly suboptimal path-length bound of (Wei and Luo, 2018) is in fact not improvable for adaptive adversary. Despite this negative result, we then develop two new algorithms, one that strictly improves over (Wei and Luo, 2018) with a smaller path-length measure, and the other which improves over (Wei and Luo, 2018) for oblivious adversary when the path-length is large. Our algorithms are based on the well-studied optimistic mirror descent framework, but importantly with several novel techniques, including new optimistic predictions, a slight bias towards recently selected arms, and the use of a hybrid regularizer similar to that of (Bubeck et al., 2018). Furthermore, we extend our results to linear bandit by showing a reduction to obtaining dynamic regret for a full-information problem, followed by a further reduction to convex body chasing. We propose a simple greedy chasing algorithm for squared 2-norm, leading to new dynamic regret results and as a consequence the first path-length regret for general linear bandit as well.
Defect energetics of cubic hafnia from quantum Monte Carlo simulations

Cubic hafnia (${\mathrm{HfO}}_{2}$) is of great interest for a number of applications in electronics because of its high dielectric constant. However, common defects in such applications degrade the properties of hafina. We have investigated the electronic properties of oxygen vacancies and nitrogen substitution in cubic ${\mathrm{HfO}}_{2}$ using first-principles calculations based on density functional theory (DFT) and many-body diffusion Monte Carlo (DMC) methods. We investigate five different charge defect states of oxygen vacancies, as well as substitutional N defects which can lead to local magnetic moments. Both DMC and DFT calculations shows that an oxygen vacancy induces strong lattice relaxations around the defect. Finally, we compare defect formation energies, charge and spin densities obtained from DMC with results obtained using DFT. While the obtained formation energies from DMC are 0.6--1.5 eV larger than those from $\mathrm{GGA}+U$, the agreement for the most important defects, neutral and positively charged oxygen vacancies, and nitrogen substitutional defect, under oxygen-poor conditions are in reasonably good agreement. Our work confirms that nitrogen can act to passivate cubic hafnia for applications in electronics.
Parent and offspring genotypes influence gene expression in early life

Parents can have profound effects on offspring fitness. Little, however, is known about the mechanisms through which parental genetic variation influences offspring physiology in natural systems. White-throated sparrows (Zonotrichia albicollis, WTSP) exist in two genetic morphs, tan and white, controlled by a large polymorphic supergene. Morphs mate disassortatively, resulting in two pair types: tan male × white female (T × W) pairs, which provide biparental care and white male × tan female (W × T) pairs, which provide female-biased care. To investigate how parental composition impacts offspring, we performed RNA-seq on whole blood of WTSP nestlings sampled from nests of both pair types. Parental pair type had a large effect on nestling gene expression, with 881 genes differentially expressed (DE) and seven correlated gene coexpression modules. The DE genes and modules expressed at higher levels in W × T nests with female-biased parental care function in metabolism and stress-related pathways resulting from the overrepresentation of proteolysis and stress-response genes (e.g., SOD2, NR3C1). These results show that parental genotypes and/or associated behaviours influence nestling physiology, and highlight avenues of further research investigating the ultimate implications for the maintenance of this polymorphism. Nestlings also exhibited morph-specific gene expression, with 92 differentially expressed genes, comprising immunity genes and genes encompassed by the supergene. Remarkably, we identified the same regulatory hub genes in these blood-derived expression networks as were previously identified in adult WTSP brains (EPM2A, BPNT1, TAF5L). These hub genes were located within the supergene, highlighting the importance of this gene complex in structuring regulatory networks across diverse tissues.
Global Guarantees for Blind Demodulation with Generative Priors

We study a deep learning inspired formulation for the blind demodulation problem, which is the task of recovering two unknown vectors from their entrywise multiplication. We consider the case where the unknown vectors are in the range of known deep generative models, $\mathcal{G}^{(1)}:\mathbb{R}^n\rightarrow\mathbb{R}^\ell$ and $\mathcal{G}^{(2)}:\mathbb{R}^p\rightarrow\mathbb{R}^\ell$. In the case when the networks corresponding to the generative models are expansive, the weight matrices are random and the dimension of the unknown vectors satisfy $\ell = \Omega(n^2+p^2)$, up to log factors, we show that the empirical risk objective has a favorable landscape for optimization. That is, the objective function has a descent direction at every point outside of a small neighborhood around four hyperbolic curves. We also characterize the local maximizers of the empirical risk objective and, hence, show that there does not exist any other stationary points outside of these neighborhood around four hyperbolic curves and the set of local maximizers. We also implement a gradient descent scheme inspired by the geometry of the landscape of the objective function. In order to converge to a global minimizer, this gradient descent scheme exploits the fact that exactly one of the hyperbolic curve corresponds to the global minimizer, and thus points near this hyperbolic curve have a lower objective value than points close to the other spurious hyperbolic curves. We show that this gradient descent scheme can effectively remove distortions synthetically introduced to the MNIST dataset.
Approximate symmetries and gravity

There are strong reasons to believe that global symmetries of quantum theories cannot be exact in the presence of gravity. While this has been argued at the qualitative level, establishing a quantitative statement is more challenging. In this work we take new steps towards quantifying symmetry violation in EFTs with gravity. First, we evaluate global charge violation by microscopic black holes present in a thermal system, which represents an irreducible, universal effect at finite temperature. Second, based on general QFT considerations, we propose that local symmetry-violating processes should be faster than black hole-induced processes at any sub-Planckian temperature. Such a proposal can be seen as part of the “swampland” program to constrain EFTs emerging from quantum gravity. Considering an EFT perspective, we formulate a con- jecture which requires the existence of operators violating global symmetry and places quantitative bounds on them. We study the interplay of our conjecture with emergent symmetries in QFT. In models where gauged U(1)’s enforce accidental symmetries, we find that constraints from the Weak Gravity Conjecture can ensure that our conjecture is satisfied. We also study the consistency of the conjecture with QFT models of emergent symmetries such as extradimensional localization, the Froggatt-Nielsen mechanism, and the clockwork mechanism.
VoiceID Loss: Speech Enhancement for Speaker Verification

In this paper, we propose VoiceID loss, a novel loss function for training a speech enhancement model to improve the robustness of speaker verification. In contrast to the commonly used loss functions for speech enhancement such as the L2 loss, the VoiceID loss is based on the feedback from a speaker verification model to generate a ratio mask. The generated ratio mask is multiplied pointwise with the original spectrogram to filter out unnecessary components for speaker verification. In the experiments, we observed that the enhancement network, after training with the VoiceID loss, is able to ignore a substantial amount of time-frequency bins, such as those dominated by noise, for verification. The resulting model consistently improves the speaker verification system on both clean and noisy conditions.
Price Discovery in High Resolution

U.S. equity market data are currently timestamped to nanosecond precision. This permits models of price dynamics at resolutions sufficient to capture the reactions of the fastest agents. Direct estimation of multivariate time series models at sub-millisecond frequencies nevertheless poses substantial challenges. To facilitate such analyses, this paper applies long distributed lag models, computations that take advantage of the inherent sparsity of price transitions, and bridged modeling. At resolutions ranging from 1 s down to 10 μs, I estimate representative models for two stocks (IBM and NVDA) bearing on three topics of current interest. The first analysis examines the extent to which the conventional source of market data (the consolidated tape) accurately reflects the prices observed by agents who subscribe (at additional cost) to direct exchange feeds. At a 1-s resolution, the information share of the direct feeds is indistinguishable from that of the consolidated tape. At resolutions of 100 and 10 μs, however, the direct feeds are totally dominant, and the consolidated share approaches zero. The second analysis examines the quotes from the primary listing exchange vs. the non-listing exchanges. Here, too, information shares that are essentially indeterminate at 1-s resolution become much more distinct at higher resolutions. Although listing exchanges execute about one-fifth of the trading volume, their information shares are slightly above one-half. The third analysis examines quotes, lit trades, and dark trades. At a 1-s resolution, dark trades appear to have a small, but discernible, information contribution. This vanishes at higher resolutions. Quotes and lit trades essentially account for all price discovery, with information shares of roughly 65% and 35%, respectively.
Principles for enhancing virus capsid capacity and stability from a thermophilic virus capsid structure.

The capsids of double-stranded DNA viruses protect the viral genome from the harsh extracellular environment, while maintaining stability against the high internal pressure of packaged DNA. To elucidate how capsids maintain stability in an extreme environment, we use cryoelectron microscopy to determine the capsid structure of thermostable phage P74-26 to 2.8-A resolution. We find P74-26 capsids exhibit an overall architecture very similar to those of other tailed bacteriophages, allowing us to directly compare structures to derive the structural basis for enhanced stability. Our structure reveals lasso-like interactions that appear to function like catch bonds. This architecture allows the capsid to expand during genome packaging, yet maintain structural stability. The P74-26 capsid has T = 7 geometry despite being twice as large as mesophilic homologs. Capsid capacity is increased with a larger, flatter major capsid protein. Given these results, we predict decreased icosahedral complexity (i.e. T ≤ 7) leads to a more stable capsid assembly. Viral capsids need to protect the genome against harsh environmental conditions and cope with high internal pressure from the packaged genome. Here, the authors determine the structure of the thermostable phage P74-26 capsid at 2.8-A resolution and identify features underlying enhanced capsid capacity and structural stability.
THE IMPACT OF THE ECONOMIC CRISIS ON ORTHOPAEDIC RESEARCH IN GREECE

Background The economic crisis has significantly altered the quality of life in Greece. The obvious negative impact on the offered social and health services has been adequately analysed. We aimed to determine whether the economic crisis has influenced the quantity and quality of Orthopaedic research in Greece, as mirrored from the papers presented at the annual meetings of Hellenic Association of Orthopaedic Surgery between the years 2008–2014. Methods The abstracts of the papers (oral and posters) presented in these meetings have been examined. Details regarding the department of origin were registered. We determined the level of evidence (according to the AAOS classification system), found the amount of papers that were published in PubMed journal and noted if a department of another country participated. Results Through the years 2008–2014 the papers concerning clinical and basic orthopaedic research that were presented were 146, 207, 304, 331, 318, 234 and 191 respectively. The percentage of those that were level 1 studies was approximately 2%, 3%, 2%, 3%, 2%, 4% and 4% respectively. The percentage of level 2 studies was 2%, 1%, 2%, 3%, 1%, 3% and 0%. Level 3 studies were the 10%, 9%, 7%, 7%, 7%, 9% and 6%. The percentage of level 4 studies was 75%, 74%, 60%, 59%, 61%, 65% and 64%. Level 5 studies were the 10%, 17%, 31%, 27%, 28%, 19% and 26%. Each year, the papers that were published in PubMed were 7%, 21%, 13%, 7%, 6%, 6% and 9%. A department of another country participated in 18%, 17%, 18%, 16%, 16%, 21% and 13% of the total of papers. Conclusion As the economic crisis deepens, the quantity of the presented papers has been reduced. More importantly, the percentage of level 1 and 2 studies has been remained steadily low. Also, we could remark a reduction on the published studies in PubMed journals. These results raise concerns about the potential impact of the crisis in the future. Level of Evidence IV
Enumerating Dihedral Hopf-Galois Structures Acting on Dihedral Extensions

Abstract The work of Greither and Pareigis details the enumeration of the Hopf-Galois structures (if any) on a given separable field extension. For an extension L / K which is classically Galois with G = G a l ( L / K ) the Hopf algebras in question are of the form ( L [ N ] ) G where N ≤ B = P e r m ( G ) is a regular subgroup that is normalized by the left regular representation λ ( G ) ≤ B . We consider the case where both G and N are isomorphic to a dihedral group D n for any n ≥ 3 . Using the normal block systems inherent to the left regular representation of each D n , (and every other regular permutation group isomorphic to D n ) we explicitly enumerate all possible such N which arise.
The Israeli Acute Paralysis Virus IRES captures host ribosomes by mimicking a ribosomal state with hybrid tRNAs

Colony collapse disorder (CCD) is a multi‐faceted syndrome decimating bee populations worldwide, and a group of viruses of the widely distributed Dicistroviridae family have been identified as a causing agent of CCD. This family of viruses employs non‐coding RNA sequences, called internal ribosomal entry sites (IRESs), to precisely exploit the host machinery for viral protein production. Using single‐particle cryo‐electron microscopy (cryo‐EM), we have characterized how the IRES of Israeli acute paralysis virus (IAPV) intergenic region captures and redirects translating ribosomes toward viral RNA messages. We reconstituted two in vitro reactions targeting a pre‐translocation and a post‐translocation state of the IAPV‐IRES in the ribosome, allowing us to identify six structures using image processing classification methods. From these, we reconstructed the trajectory of IAPV‐IRES from the early small subunit recruitment to the final post‐translocated state in the ribosome. An early commitment of IRES/ribosome complexes for global pre‐translocation mimicry explains the high efficiency observed for this IRES. Efforts directed toward fighting CCD by targeting the IAPV‐IRES using RNA‐interference technology are underway, and the structural framework presented here may assist in further refining these approaches.
How Are We Affecting Spinopelvic Parameters in Patients with Idiopathic Scoliosis

Purpose: It is well known that poor relationship between pelvic incidence and lumbar lordosis has an effect on quality of life for adult patients with spinal deformity. The effect of posterior fusion for AIS on spinopelvic parameters is still not clear. The purpose of this study was to examine the spinopelvic parameters in AIS patients who have undergone posterior spinal fusions according to their spinal fusion level. Methods: We conducted a retrospective review of 89 AIS patients, 31 males and 58 females, who underwent posterior spinal fusion (PSF) with instrumentation …
You can hear the local orientability of an orbifold

Abstract A Riemannian orbifold is a mildly singular generalization of a Riemannian manifold which is locally modeled on the quotient of a connected, open manifold under a finite group of isometries. If all of the isometries used to define the local structures of an entire orbifold are orientation preserving, we call the orbifold locally orientable. We use heat invariants to show that a Riemannian orbifold which is locally orientable cannot be Laplace isospectral to a Riemannian orbifold which is not locally orientable. As a corollary we observe that a Riemannian orbifold that is not locally orientable cannot be Laplace isospectral to a Riemannian manifold.
The security of all private-key bits in isogeny-based schemes

Abstract We study the computational hardness of recovering single bits of the private key in the supersingular isogeny Diffie–Hellman (SIDH) key exchange and similar schemes. Our objective is to give a polynomial-time reduction between the problem of computing the private key in SIDH to the problem of computing any of its bits. The parties in the SIDH protocol work over elliptic curve torsion groups of different order N . Our results depend on the parity of N . Our main result shows that if N is odd, then each of the top and lower O ( log log N ) bits of the private key is as hard to compute, with any noticeable advantage, as the entire key. A similar, but conditional, result holds for each of the middle bits. This condition can be checked, and heuristically holds almost always. The case of even N is a bit more challenging. We give several results, one of which is similar to the result for an odd N , under the assumption that one always succeeds to recover the designated bit. To achieve these results we extend the solution to the chosen-multiplier hidden number problem, for domains of a prime-power order, by studying the Fourier coefficients of single-bit functions over these domains.
Maximizing Multivariate Information With Error-Correcting Codes

Multivariate mutual information provides a conceptual framework for characterizing higher-order interactions in complex systems. Two well-known measures of multivariate information—total correlation and dual total correlation—admit a spectrum of measures with varying sensitivity to intermediate orders of dependence. Unfortunately, these intermediate measures have not received much attention due to their opaque representation of information. Here we draw on results from matroid theory to show that these measures are closely related to error-correcting codes. This connection allows us to derive the class of global maximizers for each measure, which coincide with maximum distance separable codes of order $k$ . In addition to deepening the understanding of these measures and multivariate information more generally, we use these results to show that previously proposed bounds on information geometric quantities are met with equality for the global min and max.
Expanding a Database-derived Biomedical Knowledge Graph via Multi-relation Extraction from Biomedical Abstracts

Abstract Knowledge graphs support multiple research efforts by providing contextual information for biomedical entities, constructing networks, and supporting the interpretation of high-throughput analyses. These databases are populated via some form of manual curation, which is difficult to scale in the context of an increasing publication rate. Data programming is a paradigm that circumvents this arduous manual process by combining databases with simple rules and heuristics written as label functions, which are programs designed to automatically annotate textual data. Unfortunately, writing a useful label function requires substantial error analysis and is a nontrivial task that takes multiple days per function. This makes populating a knowledge graph with multiple nodes and edge types practically infeasible. We sought to accelerate the label function creation process by evaluating the extent to which label functions could be re-used across multiple edge types. We used a subset of an existing knowledge graph centered on disease, compound, and gene entities to evaluate label function re-use. We determined the best label function combination by comparing a baseline database-only model with the same model but added edge-specific or edge-mismatch label functions. We confirmed that adding additional edge-specific rather than edge-mismatch label functions often improves text annotation and shows that this approach can incorporate novel edges into our source knowledge graph. We expect that continued development of this strategy has the potential to swiftly populate knowledge graphs with new discoveries, ensuring that these resources include cutting-edge results.
Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem

The paper studies continuous-time distributed gradient descent (DGD) and considers the problem of showing that in nonconvex optimization problems, DGD typically converges to local minima rather than saddle points. In centralized settings, the problem of demonstrating nonconvergence to saddle points is typically handled by way of the stable-manifold theorem from classical dynamical systems theory. However, the classical stable-manifold theorem is not applicable in the distributed setting. The paper develops an appropriate stable-manifold theorem for DGD. This shows that convergence to saddle points may only occur from a low-dimensional stable manifold. Under appropriate assumptions (e.g., coercivity), the result implies that DGD almost always converges to local minima.
Surface phenomena in Fermi liquids

We formulate a general theory of surface phenomena for a zero-temperature Fermi liquid. The similarities between Classical and Quantum surface motion are studied the comparison leading to an expression for the surface energy of the liquid. We show, within the time-dependent self-consistent field approximation, that the dynamical modes of the system include Landau's zero-sound waves as well as surface vibrations. Exploiting the close relation between “spurious modes” and surface waves, an approximate dispersion relation is derived for the latter. We show that the existence of a gap in the fluid's particle-hole spectrum is essential if surface modes are to propagate. Thus in a “normal” Fermi-fluid odd-parity vibrations propagate at sufficiently long wavelength while even-parity ones are damped. The effect of surface modes on the nuclear optical potential is studied. The propagation of such modes implies a peak in absorption at the surface of the nucleus. The observation of surface waves in 3He is also discussed.
Pole Dynamics for Elliptic Solutions of the Korteweg-deVries Equation

The real, nonsingular elliptic solutions of the Korteweg-de Vries equation are studied through the time dynamics of their poles in the complex plane. The dynamics of these poles is governed by a dynamical system with a constraint. This constraint is solvable for any finite number of poles located in the fundamental domain of the elliptic function, often in many different ways. Special consideration is given to those elliptic solutions that have a real nonsingular soliton limit.
CHOP: Bypassing runtime bounds checking through convex hull Optimization

Abstract Unsafe memory accesses in programs written using popular programming languages like C/C++ have been among the leading causes for software vulnerability. Prior memory safety checkers such as SoftBound enforce memory spatial safety by checking if every access to array elements are within the corresponding array bounds. However, it often results in high execution time overhead due to the cost of executing the instructions associated with bounds checking. To mitigate this problem, redundant bounds check elimination techniques are needed. In this paper, we propose CHOP, a Convex Hull Optimization based framework, for bypassing redundant memory bounds checking via profile-guided inferences. In contrast to existing check elimination techniques that are limited by static code analysis, our solution leverages a model-based inference to identify redundant bounds checking based on runtime data from past program executions. For a given function, it rapidly derives and updates a knowledge base containing sufficient conditions for identifying redundant array bounds checking. We evaluate CHOP on real-world applications and benchmark (such as SPEC) and the experimental results show that on average 80.12% of dynamic bounds check instructions can be avoided, resulting in improved performance up to 95.80% over SoftBound.
Searching for a Roommate: A Correspondence Audit Examining Racial/Ethnic and Immigrant Discrimination among Millennials:

Survey research finds that millennials have less prejudiced views of racial/ethnic minorities than other generations, leading some to label millennials as postracial. However, attitudinal survey re...
Cell-Surface Proteomic Profiling in the Fly Brain Uncovers Wiring Regulators

Summary Molecular interactions at the cellular interface mediate organized assembly of single cells into tissues and, thus, govern the development and physiology of multicellular organisms. Here, we developed a cell-type-specific, spatiotemporally resolved approach to profile cell-surface proteomes in intact tissues. Quantitative profiling of cell-surface proteomes of Drosophila olfactory projection neurons (PNs) in pupae and adults revealed global downregulation of wiring molecules and upregulation of synaptic molecules in the transition from developing to mature PNs. A proteome-instructed in vivo screen identified 20 cell-surface molecules regulating neural circuit assembly, many of which belong to evolutionarily conserved protein families not previously linked to neural development. Genetic analysis further revealed that the lipoprotein receptor LRP1 cell-autonomously controls PN dendrite targeting, contributing to the formation of a precise olfactory map. These findings highlight the power of temporally resolved in situ cell-surface proteomic profiling in discovering regulators of brain wiring.
Feature-interaction aware configuration prioritization for configurable code

Unexpected interactions among features induce most bugs in a configurable software system. Exhaustively analyzing all the exponential number of possible configurations is prohibitively costly. Thus, various sampling techniques have been proposed to systematically narrow down the exponential number of legal configurations to be analyzed. Since analyzing all selected configurations can require a huge amount of effort, fault-based configuration prioritization, that helps detect faults earlier, can yield practical benefits in quality assurance. In this paper, we propose CoPro, a novel formulation of feature-interaction bugs via common program entities enabled/disabled by the features. Leveraging from that, we develop an efficient feature-interaction-aware configuration prioritization technique for a configurable system by ranking the configurations according to their total number of potential bugs. We conducted several experiments to evaluate CoPro on the ability to detect configuration-related bugs in a public benchmark. We found that CoPro outperforms the state-of-the-art configuration prioritization techniques when we add them on advanced sampling algorithms. In 78% of the cases, CoPro ranks the buggy configurations at the top 3 positions in the resulting list. Interestingly, CoPro is able to detect 17 not-yet-discovered feature-interaction bugs.
Enhancer transcription identifies cis-regulatory elements for photoreceptor cell types

Identification of cell-type specific cis-regulatory elements (CREs) is critical for understanding development and disease, although identification of functional regulatory elements remains challenging. We hypothesized that context-specific CREs could be identified by context-specific non-coding RNA (ncRNA) profiling, based on the observation that active CREs produce ncRNAs. We applied ncRNA profiling to identify rod and cone photoreceptor CREs from wild-type and mutant mouse retinas, defined by presence or absence of the rod-specific transcription factor (TF), Nrl, respectively. Nrl-dependent ncRNA expression strongly correlated with epigenetic profiles of rod and cone photoreceptors, identified thousands of candidate rod- and cone-specific CREs, and identified motifs for rod- and cone-specific TFs. Colocalization of NRL and the retinal TF CRX correlated with rod-specific ncRNA expression, whereas CRX alone favored cone-specific ncRNA expression, providing quantitative evidence that heterotypic TF interactions distinguish cell type-specific CRE activity. We validated the activity of novel Nrl-dependent ncRNA-defined CREs in developing cones. This work supports differential ncRNA profiling as a platform for the identification of cell-type specific CREs and discovery of molecular mechanisms underlying TF-dependent CRE activity.
Parsing synthetic aperture radar measurements of snow in complex terrain: Scaling behaviour and sensitivity to snow wetness and landcover

This study investigates the spatial signatures of seasonal snow in Synthetic Aperture Radar (SAR) observations at different spatial scales and for different physiographic regions. Sentinel-1 C-band (SAR) backscattering coefficients (BSC) were analyzed in the Swiss Alps (SA), in high elevation forest and grasslands in Grand Mesa (GM), Colorado, and in North Dakota (ND) croplands. GM BSC exhibit 10 dB sensitivity to wetness at small scales (~100 m) over homogeneous grassland. Sensitivity decreases to 5 dB in the presence of trees, and it is demonstrated that VH BSC sensitivity enables wet snow mapping below the tree-line. Area-variance scaling relationships show minima at ~100 m and 150–250 m, respectively, in barren and grasslands in SA and GM, increasing up to 1 km and longer in GM forests and ND agricultural fields. The spatial organization of BSC (as described by 1D-directional BSC wavelength spectra) exhibits multi-scaling behavior in the 100–1000 m range with a break at (180–360 m) that is also present in UAVSAR L-band measurements in GM. Spectral slopes in GM forested areas steepen during accumulation and flatten in the melting season with mirror behavior for grasslands reflecting changes in scattering mechanisms with snow depth and wetness, and vegetation mass and structure. Overall, this study reveals persistent patterns of SAR scattering variability spatially organized by land-cover, topography and regional winds with large inter-annual variability tied to precipitation. This dynamic scaling behavior emerges as an integral physical expression of snowpack variability that can be used to model sub-km scales and for downscaling applications.
Effects of Teachers' Praise-To-Reprimand Ratios on Elementary Students' On-Task Behaviour.

Although many educators are familiar with a suggested 3:1 or 4:1 praise-to-reprimand ratio (PRR), relatively little research has been conducted on this subject. Three years of data collected across...
Elucidating the Role of the Organic Cation in Tuning the Optical Response of Two-Dimensional Organic-Inorganic Halide Perovskites by Computational Investigation

Layered hybrid organic–inorganic halide perovskites (OIHPs) are receiving increased attention for optoelectronic applications, including photovoltaics, light-emitting diodes, and nonlinear optics. ...
Non-myopic Planetary Exploration Combining In Situ and Remote Measurements

Remote sensing measurements can provide crucial information about the material properties of a planetary surface but their application is limited by their spatial resolution, typically tens of meters per pixel, when constituent materials are mixed at much finer scale. Consequently the orbital observations must be validated with in situ measurements from a spectrometer on the ground. In planetary exploration this means that a rover must visit selected locations that jointly improve a model of the environment and satisfy mobility and sampling constraints. Conventional planning methods used in this situation follow sub-optimal greedy strategies that are not scalable to large areas. We show how the problem can be effectively defined in a Markov Decision Process framework and propose a planning algorithm based on Monte Carlo Tree Search, which is efficient but devoid of these drawbacks thereby providing superior performance. We evaluate our approach using hyperspectral imagery of a well-studied geologic site in Cuprite, Nevada.
Stereocontrol of Michael hydride reduction by a remote hydroxyl group: a strategy for stereorational total synthesis of spatane diterpenes

Synthese du spatadiene-13,17 ol-5 a partir de la cyclopentene-2one et de la methyl-6 norbornene-5 one-2
Modified diagonals and linear relations between small diagonals

We prove that the vanishings of the modified diagonal cycles of Gross and Schoen govern the $\mathbb{Z}$-linear relations between small $m$-diagonals $\text{pt}^{\{1,\ldots,n\}\setminus A}\times\Delta_A$ in the rational Chow ring of $X^n$ for $A$ ranging over $m$-element subsets of $\{1,\ldots,n\}$. Our results generalize to arbitrary symmetric classes in place of the diagonal in $X^m$, and with different types of inclusions $A^\bullet(X^m)_{\mathbb{Q}}^{S_m} \hookrightarrow A^\bullet(X^n)_{\mathbb{Q}}$. The combinatorial heart of this paper, which may be of independent interest, is showing the $\mathbb{Z}$-linear relations between elementary symmetric polynomials $e_k(x_{a_1},\ldots,x_{a_m}) \in \mathbb{Z}[x_1,\ldots,x_n]$ are generated by the $S_n$-translates of a certain alternating sum over the facets of a hyperoctahedron.
Minimizing intersection points of curves under virtual homotopy

A flat virtual link is a finite collection of oriented closed curves &#x1d50f; on an oriented surface M considered up to virtual homotopy, i.e., a composition of elementary stabilizations, destabilizations...
The Variance of the Number of Zeros for Complex Random Polynomials Spanned by OPUC

Let $$\{\varphi _k\}_{k=0}^\infty $$ be a sequence of orthonormal polynomials on the unit circle with respect to a probability measure $$ \mu $$. We study the variance of the number of zeros of random linear combinations of the form $$\begin{aligned} P_n(z)=\sum _{k=0}^{n}\eta _k\varphi _k(z), \end{aligned}$$where $$\{\eta _k\}_{k=0}^n $$ are complex-valued random variables. Under the assumption that the distribution for each $$\eta _k$$ satisfies certain uniform bounds for the fractional and logarithmic moments, for the cases when $$\{\varphi _k\}$$ are regular in the sense of Ullman–Stahl–Totik or are such that the measure of orthogonality $$\mu $$ satisfies $$d\mu (\theta )=w(\theta )d\theta $$ where $$w(\theta )=v(\theta )\prod _{j=1}^J|\theta - \theta _j|^{\alpha _j}$$, with $$v(\theta )\ge c>0$$, $$\theta ,\theta _j\in [0,2\pi )$$, and $$\alpha _j>0$$, we give a quantitative estimate on the variance of the number of zeros of $$P_n$$ in sectors that intersect the unit circle. When $$\{\varphi _k\}$$ are real-valued on the real-line from the Nevai class and $$\{\eta _k\}$$ are i.i.d. complex-valued standard Gaussian, we obtain a formula for the limiting value of variance of the number of zeros of $$P_n$$ in annuli that do not contain the unit circle.