cssi/SciSciGPT-SciSciNet huggingface dataset:
A mathematical and computational model of the calcium dynamics in Caenorhabditis elegans ASH sensory neuron

We propose a mathematical and computational model that captures the stimulus-generated Ca2+ transients in the C. elegans ASH sensory neuron. The rationale is to develop a tool that will enable a cross-talk between modeling and experiments, using modeling results to guide targeted experimental efforts. The model is built based on biophysical events and molecular cascades known to unfold as part of neurons' Ca2+ homeostasis mechanism, as well as on Ca2+ signaling events. The state of ion channels is described by their probability of being activated or inactivated, and the remaining molecular states are based on biochemically defined kinetic equations or known biochemical motifs. We estimate the parameters of the model using experimental data of hyperosmotic stimulus-evoked Ca2+ transients detected with a FRET sensor in young and aged worms, unstressed and exposed to oxidative stress. We use a hybrid optimization method composed of a multi-objective genetic algorithm and nonlinear least-squares to estimate the model parameters. We first obtain the model parameters for young unstressed worms. Next, we use these values of the parameters as a starting point to identify the model parameters for stressed and aged worms. We show that the model, in combination with experimental data, corroborates literature results. In addition, we demonstrate that our model can be used to predict ASH response to complex combinations of stimulation pulses. The proposed model includes for the first time the ASH Ca2+ dynamics observed during both "on" and "off" responses. This mathematical and computational effort is the first to propose a dynamic model of the Ca2+ transients' mechanism in C. elegans neurons, based on biochemical pathways of the cell's Ca2+ homeostasis machinery. We believe that the proposed model can be used to further elucidate the Ca2+ dynamics of a key C. elegans neuron, to guide future experiments on C. elegans neurobiology, and to pave the way for the development of more mathematical models for neuronal Ca2+ dynamics.
Identification of biologically active sites in laminin an extracellular matrix protein

Laminin-1, a major component of basement membranes, has multiple biological activities including promotion of cell adhesion, spreading, migration, growth, neurite outgrowth and tumor metastasis. Several active sites on laminin-1 have been identified previously. We modified these biologically active peptides to enhance their activities. The multimeric YIGSR (Tyr-Ile-Gly-Ser-Arg) peptides assembled on a branched lysine core were found to strongly enhance the activity of YIGSR in inhibiting tumor growth and metastasis. We also found the all-D-configuration peptide segment containing the IKVAV (Ile-Lys-Val-Ala-Val) sequence had similar biological activities to the native all-L-peptide in vitro and in vivo. These results suggest that these modified compounds are potentially useful for clinical applications. We have identified new active sequences from the laminin alpha 1 chain carboxyl-terminal globular domain (G domain). Using a systematic screening for cell binding sites with 113 overlapping synthetic peptides, we found five peptides (AG-10, AG-22, AG-32, AG-56, and AG-73) showed cell attachment activities with cell-type specificities. AG-10 and AG-32 were found to interact with integrins. AG-73 caused metastases of B16-F10 mouse melanoma cells to the liver colonization in mice. Additionally AG-73 was found to promote neurite outgrowth. Moreover, this peptide inhibited laminin mediated acinar-like development of a human submandibular gland cell line. The AG-73 domain on laminin-1 could be one of the most important biologically active sites. These active peptides may useful for study of the molecular mechanism of laminin-receptor interactions and for development of therapeutic reagents for tumor metastasis and angiogenasis.
A formal synthesis of the callipeltoside aglycone.

A synthesis of the macrocyclic core structure of callipeltoside A and a C9 epimer has been achieved by applications of chiral vinylzinc or Kishi−Nozaki−Hiyama (K−N−H) additions, Roskamp homologations, and acylketene or intramolecular K−N−H macrolactonizations as key bond-forming steps.
Sample Complexity for Non-Truthful Mechanisms

This paper considers the design of non-truthful mechanisms from samples. We identify a parameterized family of mechanisms with strategically simple winner-pays-bid, all-pay, and truthful payment formats. In general (not necessarily downward-closed) single-parameter feasibility environments we prove that the family has low representation and generalization error. Specifically, polynomially many bid samples suffice to identify and run a mechanism that is e-close in Bayes-Nash equilibrium revenue or welfare to that of the optimal truthful mechanism.
Metal ion-assisted peptide cyclization

Abstract We describe an efficient chemoselective method for Ag+ ion-assisted lactamization or lactonization of linear peptides to obtain end-to-end and sidechain-to-end cyclic peptides in aqueous buffered solutions.
Accurate Sub-population Detection and Mapping Across Single Cell Experiments with PopCorn.

The identification of sub-populations of cells present in a sample and the comparison of such sub-populations across samples are among the most frequently performed analyzes of single-cell data. Current tools for these kinds of data, however, fall short in their ability to adequately perform these tasks. We introduce a novel method, PopCorn (single cell sub-Populations Comparison), allowing for the identification of sub-populations of cells present within individual experiments while simultaneously performing sub-populations mapping across these experiments. PopCorn utilizes several novel algorithmic solutions enabling the execution of these tasks with unprecedented precision. As such, PopCorn provides a much-needed tool for comparative analysis of populations of single cells.
Synthesis and stereochemical assignment of brasilibactin A.

Brasilibactin A, a naturally occurring siderophore related to the mycobactins, has been synthesized in six steps. Use of asymmetric titanium-mediated aldol reactions allowed the preparation of both diastereomers from a common synthetic intermediate, thus allowing the relative stereochemistry of the natural product to be assigned. Brasilibactin A exhibits no inhibition of histone deacetylases (HDACs) in spite of the N-formyl-N-hydroxy lysine moiety that is expected to affect the activity of these metal-dependent lysine-modifying enzymes.
An environmentally-friendly one-pot synthesis of 4-sulfonyl benzoic acids

This Letter reports an environmentally-friendly one-pot SNAr reaction of thiols to 4-halobenzoic acid methyl esters to provide 4-substituted sulfone benzoic acids and picolinic acids after bleach-mediated oxidative workup. These acid intermediates were synthesized on gram scale, are perfect partners for library synthesis, and have good physical chemical properties useful for drug discovery.
How does audit firm emphasis on client relationship quality influence auditors’ inferences about and responses to potential persuasion in client communications?

Abstract Many audit firms use client relationship management tools (e.g., client satisfaction surveys); however, overemphasizing relationship quality potentially makes auditors susceptible to client influence. Audit seniors, the main point of contact with clients, could be most vulnerable. In an experiment, we manipulate the presence of a potential client persuasion attempt in response to auditor inquiry (expressions of high confidence) and an audit firm’s emphasis on relationship quality (desire to achieve high client satisfaction ratings for the current year’s audit). We examine how these variables jointly influence the extent to which audit seniors infer persuasion from client explanations and, importantly, whether that inference is reflected in their actions. We find that auditors infer to an incrementally greater extent that client persuasion is present when they encounter high confidence when relationship quality is emphasized; however, they do not respond by collecting more relevant audit evidence under these conditions. Our findings suggest that auditors do not pursue audit evidence that could reduce their reliance on client-provided information and, thereby, limit client influence, even when they infer client persuasion to a greater extent.
Revisiting the Effect of Population Size on Cumulative Cultural Evolution

Previous models of cultural evolution found that larger populations can better maintain complex technologies because they contain more highly skilled people whom others can imitate. These models, however, do not distinguish the effects of population size from population density or network size; a learner’s social network includes the entire population. Does population size remain important when populations are subdivided and networks are realistically small? I use a mathematical model to show that population size has little effect on equilibrium levels of mean skill under a wide range of conditions. The effects of network size and transmission error rate usually overshadow that of population size. Population size can, however, affect the rate at which a population approaches equilibrium, by increasing the rate at which innovations arise. This effect is small unless innovation is very rare. Population size should predict technological complexity in the real world, then, only if technological evolution is a slow, innovation-limited process. Population density and “connectedness” have similar affects to population size, though density can also affect equilibrium skill. I discuss the results of this analysis in light of the current empirical debate.
Latent Retrieval for Weakly Supervised Open Domain Question Answering

Recent work on open domain question answering (QA) assumes strong supervision of the supporting evidence and/or assumes a blackbox information retrieval (IR) system to retrieve evidence candidates. We argue that both are suboptimal, since gold evidence is not always available, and QA is fundamentally different from IR. We show for the first time that it is possible to jointly learn the retriever and reader from question-answer string pairs and without any IR system. In this setting, evidence retrieval from all of Wikipedia is treated as a latent variable. Since this is impractical to learn from scratch, we pre-train the retriever with an Inverse Cloze Task. We evaluate on open versions of five QA datasets. On datasets where the questioner already knows the answer, a traditional IR system such as BM25 is sufficient. On datasets where a user is genuinely seeking an answer, we show that learned retrieval is crucial, outperforming BM25 by up to 19 points in exact match.
Addition of diamines to methylthiopyridones

Thiopyridone derivatives react with diamines: ethylenediamine, 1,3-pro- pylenediamine and 1,4-butylenediamine to produce bicyclic addition com- pounds. Ethanolamine reacts with thiopyridone derivatives to afford only open chain adducts. Diethylenetriamine and 2(2-aminoethylamino)ethanol in reaction with thiopyridones yielded seven membered ring tricyclic derivatives. The procedures described here constitute a relatively sim- ple method to prepare these novel heterocycles
Substituted azabicyclo[2.2.1]heptanes via nitrenium ion rearrangement

Abstract N-chlorination of aryl substituted azabicycloheptanes and subsequent rearrangement provided the endo arylated azabicyclo[2.2.1]heptanes.
Competitive rearrangements of alkylacetoxycarbenes

Abstract Absolute rate constants are determined for (1,2) acetyl, carbon, and hydride shifts in cyclobutylacetoxycarbene and isopropylacetoxycarbene; comparative reactivities are examined.
The infrared absorption cross-section and refractive-index data in HITRAN

Abstract The cross-sections and indices of refraction on the HIgh-resolution TRANsmission (HITRAN) database are summarized. HITRAN contains a tabulation of cross-sections of atmospheric chemical reservoir and source species, chlorofluorocarbons, hydrochlorofluorocarbons, and hydrofluorocarbons, and indices of refraction of liquid and solid compounds. The temperature and pressure dependences of the cross-sections and the temperature dependence of the indices of refraction are illustrated. Data uncertainties and applications are discussed, and some future needs of the remote-sensing community are identified.
Blowup algebras of rational normal scrolls

We determine the equations of the blowup of $\mathbb{P}^n$ along a $d$-fold rational normal scroll $S$, and we prove that the Rees ring and special fiber ring of $S \subseteq \mathbb{P}^n$ are Koszul algebras.
Regio-, stereo-, and enantioselectivity in hydrocarbon conversion on metal surfaces.

Selectivity is one of the most important criteria for the design of new catalytic processes. More selective catalysis could be both cheaper and greener because it does not waste reactants, does not...
Synthesis of bicyclo[2.2.2]oct-5-en-2-ones via a tandem intermolecular Michael addition intramolecular aldol process (a bridged Robinson annulation)

A novel one-pot synthesis of the several bicyclo[2.2.2]oct-5-en-2-ones 19 has been developed in which a cyclic or acyclic ketone 18 is reacted with a cyclic enone 6 in the presence of strong acid to give the bicyclic enone product 19. Alternatively, the intermediate diketone 21 can be prepared separately and subjected to the reaction conditions to give the bicyclic enones 19 in good yields.
Derived Functors of Differential Operators

In their work on differential operators in positive characteristic, Smith and Van den Bergh define and study the derived functors of differential operators; they arise naturally as obstructions to differential operators reducing to positive characteristic. In this note, we provide formulas for the ring of differential operators as well as these derived functors of differential operators. We apply these descriptions to show that differential operators behave well under reduction to positive characteristic under certain hypotheses. We show that these functors also detect a number of interesting properties of singularities.
Asymmetric synthesis of γ-perfluoroalkyl(aryl) butyrolactones via organoboranes

Abstract Asymmetric ‘allyl’boration of fluorinated aldehydes with α-pinene-based ‘allyl’ boranes provides the corresponding homoallylic alcohols in high ee and de, which upon hydroboration, followed by oxidation with TPAP/NMO furnish γ-perfluoroalkyl(aryl)-γ-butyrolactones.
Kinetics of the NCN Radical

The kinetics of the NCN + NO reaction has been studied using laser-induced fluorescence spectroscopy over the temperature range 298−573 K to measure total rate constants and time-resolved infrared diode laser spectroscopy as a probe for possible products. The reaction has a rate constant of k(NCN + NO) = (2.88 ± 0.2) × 10-13 cm3 molecule-1 s-1 at 298 K and low (∼3 Torr) total pressure. The rate constant displays both a temperature as well as a pressure dependence, indicating that adduct formation is a major product channel. Only very small amounts of other products were detected. Upper limits for the low-pressure rate constants of NCN + O2, C2H4, and NO2 were also obtained.
Consensus or Deadlock? Consequences of Simple Behavioral Rules for Coordination in Group Decisions

Coordinated collective behaviors often emerge from simple rules governing the interactions of individuals in groups. We model mechanisms of coordination among ants during cooperative transport, a challenging task that requires a consensus on travel direction. Our goal is to determine whether groups following simple behavioral rules can reach a consensus using minimal information. Using deterministic and stochastic models, we investigate behavioral factors that affect coordination. We define and investigate three types of behavioral rules governing individual behavior that differ in the information available: individuals either 1) have no information, 2) can measure transport success, or 3) measure success while also knowing whether they are aligned with the majority. We find that groups break deadlocks only if individuals more readily give up when they are going against the majority, corresponding to rule type 3 –such groups are “informed.” These behavioral rules succeed through positive and negative feedbacks that are implemented in our model via a single mechanism: individuals only need to measure the relative group sizes to make effective decisions. We also find that groups reach consensus more quickly if they have either a shared bias, high sensitivity to group behavior, or finely tuned persistence. Each of these is a potential adaptation for efficient cooperative transport. This flexibility makes the behavioral rules in the informed case relatively robust to deficiencies in the individuals’ capabilities. While inspired by ants, our results are generalizable to other collective decisions with deadlocks, and demonstrate that groups of behaviorally simple individuals with no memory and extremely limited information can break symmetry and reach a consensus in a decision between two equal options.
Production of jets at the tevatron

Abstract Measurements of the inclusive jet cross section and the dijet angular distribution using data from the Tevatron are presented. Comparisons to NLO QCD show good agreement below 250 GeV, but CDF data show an excess at higher ET; qualitative agreement is seen between the CDF and DO cross sections. Analysis of the dijet angular distributions exclude quark compositeness below 2.1 TeV.
Synthesis of Refractory Ceramics via Rapid Metathesis Reactions between Solid-State Precursors

Chemical exchange (metathesis) reactions are used in many syntheses of important solids. While metathesis reactions in the liquid and gas phase are well-known, metathesis reactions from solid-state precursors have received much less attention. This review details work on the synthesis of refractory ceramics via rapid metathesis reactions between solid metal halides and alkali (or alkaline earth) metal main group compounds (e.g., Li3N or MgB2). The discussion includes thermodynamic considerations in choosing appropriate precursor couples. Through a careful choice of precursors, rapid, highly exothermic reactions can reach high temperatures (>1000 °C) on very short time scales (<1 s). The products are often crystalline and single phase with crystallite sizes varying from tens of angstroms to a few microns, depending on the refractory nature of the material and the reaction conditions (i.e., scale and the use of inert additives). The utility of this metathesis route is demonstrated by metal nitride, boron ni...
The first synthesis of 1,5-diazacyclooctan-2-one and differentially protected 1,5-diazacyclooctanes

An efficient, high-yielding synthesis of 1,5-diazacyclooctan-2-one and subsequent elaboration to a differentially protected 1,5-diazacyclooctane is disclosed.
A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Br...
Poisson Cox Point Processes for Vehicular Networks

This paper analyzes statistical properties of the Poisson line Cox point process useful in the modeling of vehicular networks. The point process is created by a two-stage construction: a Poisson line process to model road infrastructure and independent Poisson point processes, conditionally on the Poisson lines, to model vehicles on the roads. We derive basic properties of the point process, including the general quadratic position of the points, the nearest distance distribution, the Laplace functional, the densities of facets of the Cox–Voronoi tessellation, and the asymptotic behavior of the typical Voronoi cell under vehicular densification. These properties are closely linked to features that are important in vehicular networks.
Finite type invariants of integral homology 3-spheres: A survey

This is a survey on the current status of the study of finite type invariants of integral homology 3-spheres based on lectures given in the workshop on knot theory at Banach International Center of Mathematics, Warsaw, July 1995. As a new result, we show that the space of finite type invariants of integral homology 3-spheres is a graded polynomial algebra generated by invariants additive under the connected sum. We also discuss some open questions on this subject.
3D ab initio modeling in cryo-EM by autocorrelation analysis

Single-Particle Reconstruction (SPR) in Cryo-Electron Microscopy (cryo-EM) is the task of estimating the 3D structure of a molecule from a set of noisy 2D projections, taken from unknown viewing directions. Many algorithms for SPR start from an initial reference molecule, and alternate between refining the estimated viewing angles given the molecule, and refining the molecule given the viewing angles. This scheme is called iterative refinement. Reliance on an initial, user-chosen reference introduces model bias, and poor initialization can lead to slow convergence. Furthermore, since no ground truth is available for an unsolved molecule, it is difficult to validate the obtained results. This creates the need for high quality ab initio models that can be quickly obtained from experimental data with minimal priors, and which can also be used for validation. We propose a procedure to obtain such an ab initio model directly from raw data using Kam's autocorrelation method. Kam's method has been known since 1980, but it leads to an underdetermined system, with missing orthogonal matrices. Until now, this system has been solved only for special cases, such as highly symmetric molecules or molecules for which a homologous structure was already available. In this paper, we show that knowledge of just two clean projections is sufficient to guarantee a unique solution to the system. This system is solved by an optimization-based heuristic. For the first time, we are then able to obtain a low-resolution ab initio model of an asymmetric molecule directly from raw data, without 2D class averaging and without tilting. Numerical results are presented on both synthetic and experimental data.
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural Networks

Shot boundary detection (SBD) is an important component of many video analysis tasks, such as action recognition’ video indexing, summarization and editing. Previous work typically used a combination of low-level features like color histograms, in conjunction with simple models such as SVMs to predict shot changes. Instead, we propose to learn shot detection end-to-end, from pixels to final shot boundaries. For training such a model, we rely on our insight that all shot boundaries are generated. Thus, we create a dataset with one million frames and automatically generated transitions such as cuts, dissolves and fades. In order to efficiently analyze hours of videos, we propose a Convolutional Neural Network (CNN) which is fully convolutional in time, thus allowing to use a large temporal context without the need to repeatedly processing frames. With this architecture our method obtains state-of-the-art results on the RAI dataset, while running at an unprecedented speed of more than 120x real-time.
Direct runge-kutta discretization achieves acceleration

We study gradient-based optimization methods obtained by directly discretizing a second-order ordinary differential equation (ODE) related to the continuous limit of Nesterov's accelerated gradient method. When the function is smooth enough, we show that acceleration can be achieved by a stable discretization of this ODE using standard Runge-Kutta integrators. Specifically, we prove that under Lipschitz-gradient, convexity and order-(s + 2) differentiability assumptions, the sequence of iterates generated by discretizing the proposed second-order ODE converges to the optimal solution at a rate of O(N-2 s/s+1), where s is the order of the Runge-Kutta numerical integrator. Furthermore, we introduce a new local flatness condition on the objective, under which rates even faster than O(N-2) can be achieved with low-order integrators and only gradient information. Notably, this flatness condition is satisfied by several standard loss functions used in machine learning. We provide numerical experiments that verify the theoretical rates predicted by our results.
On randomized distributed coordinate descent with quantized updates

In this paper, we study the randomized distributed coordinate descent algorithm with quantized updates. In the literature, the iteration complexity of the randomized distributed coordinate descent algorithm has been characterized under the assumption that machines can exchange updates with an infinite precision. We consider a practical scenario in which the messages exchange occurs over channels with finite capacity, and hence the updates have to be quantized. We derive sufficient conditions on the quantization error such that the algorithm with quantized update still converge. We further verify our theoretical results by running an experiment, where we apply the algorithm with quantized updates to solve a linear regression problem.
On rational Dyck paths and the enumeration of factor-free Dyck words

Abstract Motivated by independent results of Bizley and Duchon, we study rational Dyck paths and their subset of factor-free elements. On the one hand, we give a bijection between rational Dyck paths and regular Dyck paths with ascents colored by factor-free words. This bijection leads to a new statistic based on the reducibility level of the paths for which we provide a corresponding formula. On the other hand, we prove an inverse relation for certain sequences defined via partial Bell polynomials, and we use it to derive a formula for the enumeration of factor-free words. In addition, we give alternative formulas for various enumerative sequences that appear in the context of rational Dyck paths.
Upper bounds for the number of primitive ray class characters with conductor below a given bound

We present upper bounds on certain sums which are related to Artin's primitive root conjecture and are also used in counting ray class characters.
Perron-frobenius theory in nearly linear time: positive eigenvectors, M-matrices, graph kernels, and other applications

In this paper we provide nearly linear time algorithms for several problems closely associated with the classic Perron-Frobenius theorem, including computing Perron vectors, i.e. entrywise non-negative eigenvectors of non-negative matrices, and solving linear systems in asymmetric M-matrices, a generalization of Laplacian systems. The running times of our algorithms depend nearly linearly on the input size and polylogarithmically on the desired accuracy and problem condition number.Leveraging these results we also provide improved running times for a broader range of problems including computing random walk-based graph kernels, computing Katz centrality, and more. The running times of our algorithms improve upon previously known results which either depended polynomially on the condition number of the problem, required quadratic time, or only applied to special cases.We obtain these results by providing new iterative methods for reducing these problems to solving linear systems in Row-Column Diagonally Dominant (RCDD) matrices. Our methods are related to the classic shift-and-invert preconditioning technique for eigenvector computation and constitute the first alternative to the result in Cohen et al. (2016) for reducing stationary distribution computation and solving directed Laplacian systems to solving RCDD systems.
The Hardy-Lorentz spaces H p,q (R n )

We deal with the Hardy-Lorentz spaces H p,q (R n ) where 0 < p � 1, 0 < q � 1. We discuss the atomic decomposition of the elements in these spaces, their interpolation properties, and the behavior of singular integrals and other operators acting on them. The real variable theory of the Hardy spaces represents a fruitful set- ting for the study of maximal functions and singular integral operators. In fact, it is because of the failure of these operators to preserve L 1 that the Hardy space H 1 assumes its prominent place in harmonic analysis. Now, for many of these operators, the role of L 1 can just as well be played by H 1,∞ , or Weak H 1 . However, although these operators are amenable to H 1 -L 1 and H 1,∞ -L 1,∞ estimates, interpolation between H 1 and H 1,∞ has not been available. Similar considerations apply to H p and Weak H p for 0 < p < 1. The purpose of this paper is to provide an interpolation result for the Hardy-Lorentz spaces H p,q , 0 < p ≤ 1, 0 < q ≤ ∞, including the case of Weak H p as an end point for real interpolation. Since in this context neither truncations are available nor reiteration applies, the atomic decomposition will be the key ingredient in dealing with interpolation. The paper is organized as follows. The Lorentz spaces, including criteria that ensure membership in L p,q , 0 < p < ∞, 0 < q ≤ ∞, are discussed in Section 1. In Section 2 we show that distributions in H p,q have an atomic de- composition in terms of H p atoms with coefficients in an appropriate mixed norm space. An interesting application of this decomposition is to H p,q -L p,∞ estimates for Calderon-Zygmund singular integral operators, p < q ≤ ∞. Also, by manipulating the different levels of the atomic decomposition, we show that, for 0 < q1 < q < q2 ≤ ∞, H p,q is an intermediate space between H p,q1 and H p,q2 . This result applies to Calderon-Zygmund singular integral
Logarithmic vector-valued modular forms

We consider logarithmic vector- and matrix-valued modular forms of integral weight $k$ associated with a $p$-dimensional representation $\rho: SL_2(\mathbb{Z}) \to GL_p(\mathbb{C})$ of the modular group, subject only to the condition that $\rho(T)$ has eigenvalues of absolute value 1. The main result is the construction of meromorphic matrix-valued Poincar\'e series associated to $\rho$ for all large enough weights. The component functions are logarithmic $q$-series, i.e., finite sums of products of $q$-series and powers of $\log q$. We derive several consequences, in particular we show that the space $\mathcal{H}(\rho)=\oplus_k \mathcal{H}(k, \rho)$ of all holomorphic logarithmic vector-valued modular forms associated to $\rho$ is a free module of rank $p$ over the ring of classical holomorphic modular forms on $SL_2(\mathbb{Z})$.
Derived equivalent surfaces and abelian varieties, and their zeta functions

In this paper, it is demonstrated that derived equivalence between smooth, projective, connected schemes that are either surfaces or abelian implies equality of zeta functions.
Real Representations of Finite Symplectic Groups over Fields of Characteristic Two

We prove that when $q$ is a power of $2$, every complex irreducible representation of $\mathrm{Sp}(2n, \mathbb{F}_q)$ may be defined over the real numbers, that is, all Frobenius-Schur indicators are 1. We also obtain a generating function for the sum of the degrees of the unipotent characters of $\mathrm{Sp}(2n, \mathbb{F}_q)$, or of $\mathrm{SO}(2n+1, \mathbb{F}_q)$, for any prime power $q$.
Beyond prediction: A framework for inference with variational approximations in mixture models.

Variational inference is a popular method for estimating model parameters and conditional distributions in hierarchical and mixed models, which arise frequently in many settings in the health, soci...
Performance Analysis of Network Coding with IEEE 802.11 DCF in Multi-Hop Wireless Networks

Network coding is an effective idea to boost the capacity of wireless networks, and a variety of studies have explored its advantages in different scenarios. However, there is not much analytical study on throughput and end-to-end delay of network coding in multi-hop wireless networks considering the specifications of IEEE 802.11 Distributed Coordination Function. In this paper, we utilize queuing theory to propose an analytical framework for bidirectional unicast flows in multi-hop wireless mesh networks. We study the throughput and end-to-end delay of inter-flow network coding under the IEEE 802.11 standard with CSMA/CA random access and exponential back-off time considering clock freezing and virtual carrier sensing, and formulate several parameters such as the probability of successful transmission in terms of bit error rate and collision probability, waiting time of packets at nodes, and retransmission mechanism. Our model uses a multi-class queuing network with stable queues, where coded packets have a non-preemptive higher priority over native packets, and forwarding of native packets is not delayed if no coding opportunities are available. Finally, we use computer simulations to verify the accuracy of our analytical model.
Lyapunov exponent and Wasserstein metric as validation tools for assessing short-time dynamics and quantitative model evaluation of large-eddy simulation

In this work, methods for the evaluation of LES-quality and LES-accuracy are presented, which include the Lyapunov exponent for the analysis of short-time predictability of LES-calculation and the Wasserstein metric for the quantitative assessment of simulation results. Both methods are derived and evaluated in application to the Volvo test case. Both the non-reacting and reacting cases are calculated. For the non- reacting cases, good agreement with the experimental data is achieved by solvers at high numerical resolution. The reacting cases are more challenging due to the small length scale of the flame and the suppression of sinuous mode of absolute instability by the density ratio. The analysis of the turbulent simulation data using the concept of the Lyapunov exponent and the Wasserstein metric provides a more quantitative approach to assess the mesh dependency of the simulation results. The convergence of the Lyapunov exponent is shown to be a more sensitive and stronger indication of mesh-independence. Though grid convergence for the reacting cases cannot be reached with the chosen resolutions, the Lyapunov exponents and the Wasserstein metric are shown to be capable of identifying quantity-specific sensitivities with respect to the numerical resolution, while requiring significantly less computational resources than acquiring profiles of conventional turbulent statistics.
Enhanced Energy Management System With Corrective Transmission Switching Strategy—Part II: Results and Discussion

This paper presents a novel procedure for energy management system (EMS) that can utilize the flexibility in transmission networks in a practical way. With the proposed enhanced EMS procedure, the reliability benefits that are provided by corrective transmission switching (CTS) in real-time contingency analysis can be translated into significant cost savings in real-time security-constrained economic dispatch. Simulation results show that the congestion cost with consideration of CTS is largely reduced as CTS can relieve potential post-contingency network violations. The effects of integrating CTS in existing EMS procedure on markets are also analyzed. In conclusion, this two-part paper shows that CTS can achieve substantial reliability benefits, as well as significant cost savings.
Passivity and Passivity Indices of Nonlinear Systems Under Operational Limitations using Approximations

In this paper, we will discuss how operational limitations affect input–output behaviours of the system. In particular, we will provide a formulation for passivity and passivity indices of a nonlin...
Tridiagonal pairs and the q-tetrahedron algebra

Abstract The q -tetrahedron algebra ⊠ q was recently introduced and has been studied in connection with tridiagonal pairs. In this paper we further develop this connection. Let K denote an algebraically closed field and let q denote a nonzero scalar in K that is not a root of unity. Let V denote a vector space over K with finite positive dimension and let A , A ∗ denote a tridiagonal pair on V . Let { θ i } i = 0 d , (resp. { θ i ∗ } i = 0 d ) denote a standard ordering of the eigenvalues of A (resp. A ∗ ). Ito and Terwilliger have shown that when θ i = q 2 i - d and θ i ∗ = q d - 2 i ( 0 ⩽ i ⩽ d ) there exists an irreducible ⊠ q -module structure on V such that the ⊠ q generators x 01 , x 23 act as A , A ∗ respectively. In this paper we examine the case in which there exists a nonzero scalar c in K such that θ i = q 2 i - d and θ i ∗ = q 2 i - d + cq d - 2 i for 0 ⩽ i ⩽ d . In this case we associate to A , A ∗ a polynomial P in one variable and prove the following theorem as our main result. Theorem The following are equivalent: 1. [(i)] There exists a ⊠ q -module structure on V such that x 01 acts as A and x 30 + cx 23 acts as A ∗ , where x 01 , x 30 , x 23 are standard generators for ⊠ q . 2. [(ii)] P ( q 2 d - 2 ( q - q - 1 ) - 2 ) ≠ 0 . Suppose (i) and (ii) hold. Then the ⊠ q -module structure on V is unique and irreducible.
Understanding the Computational Requirements of Virtualized Baseband Units Using a Programmable Cloud Radio Access Network Testbed

Cloud Radio Access Network (C-RAN) is emerging as a transformative architecture for the next generation of mobile cellular networks. In C-RAN, the Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in a centralized processing center. While the potential benefits of C-RAN have been studied extensively from the theoretical perspective, there are only a few works that address the system implementation issues and characterize the computational requirements of the virtualized BBU. In this paper, a programmable C-RAN testbed is presented where the BBU is virtualized using the OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment (UEs) are implemented using USRP boards. Extensive experiments have been performed in a FDD downlink LTE emulation system to characterize the performance and computing resource consumption of the BBU under various conditions. It is shown that the processing time and CPU utilization of the BBU increase with the channel resources and with the Modulation and Coding Scheme (MCS) index, and that the CPU utilization percentage can be well approximated as a linear increasing function of the maximum downlink data rate. These results provide real-world insights into the characteristics of the BBU in terms of computing resource and power consumption, which may serve as inputs for the design of efficient resource-provisioning and allocation strategies in C-RAN systems.
Fast and Accurate, Convolutional Neural Network Based Approach for Object Detection from UAV

Unmanned Aerial Vehicles (UAVs), have intrigued different people from all walks of life, because of their pervasive computing capabilities. UAV equipped with vision techniques, could be leveraged to establish navigation autonomous control for UAV itself. Also, object detection from UAV could be used to broaden the utilization of drone to provide ubiquitous surveillance and monitoring services towards military operation, urban administration and agriculture management. As the data-driven technologies evolved, machine learning algorithm, especially the deep learning approach has been intensively utilized to solve different traditional computer vision research problems. Modern Convolutional Neural Networks based object detectors could be divided into two major categories: one-stage object detector and two-stage object detector. In this study, we utilize some representative CNN based object detectors to execute the computer vision task over Stanford Drone Dataset (SDD). State-of-the-art performance has been achieved in utilizing focal loss dense detector RetinaNet based approach for object detection from UAV in a fast and accurate manner.
Guided-wave Brillouin scattering in air

Photonic-bandgap fibers have had major impact from fundamental studies of photon–atom interactions to new applications in nonlinear optics. While much is known about the optical properties of these fibers, relatively little is known about their optomechanical properties. Here we identify a new form of optomechanical coupling in gas-filled hollow-core fibers. We show that forward Brillouin scattering is produced by air in the core of a photonic bandgap fiber. A single Brillouin resonance is identified at 35 MHz, which corresponds to a guided sound wave within the center of an air-filled hollow-core fiber. A simple analytical model, refined by numerical simulations, is developed that accurately predicts the Brillouin coupling strength and frequency from the gas and fiber parameters, revealing that this optomechanical interaction is highly tailorable. This new mechanism could become the basis for new types of sensing and spectroscopy. Moreover, this previously unknown nonlinearity within hollow core fibers represents a power and noise limitation that requires further consideration.
EMBEDDINGS, NORMAL INVARIANTS AND FUNCTOR CALCULUS

This paper investigates the space of codimension zero embeddings of a Poincare duality space in a disk. One of our main results exhibits a tower that interpolates from the space of Poincare immersions to a certain space of “unlinked” Poincare embeddings. The layers of this tower are described in terms of the coefficient spectra of the identity appearing in Goodwillie’s homotopy functor calculus. We also answer a question posed to us by Sylvain Cappell. The appendix proposes a conjectural relationship between our tower and the manifold calculus tower for the smooth embedding space.
D-branes and near extremal black holes at low energies

It has been observed recently that many properties of some near extremal black holes can be described in terms of bound states of $D$-branes. Using a nonrenormalization theorem we argue that the $D$-brane description is the correct quantum gravity description of the black hole at low energies. The low-energy theory includes the black hole degrees of freedom that account for the entropy and describes also Hawking radiation. The description is unitary and there seems to be no information loss at low energies.
Elliptic Curves of Unbounded Rank and Chebyshev's Bias

We establish a conditional equivalence between quantitative unboundedness of the analytic rank of elliptic curves over $\mathbb Q$ and the existence of highly biased elliptic curve prime number races. We show that conditionally on a Riemann Hypothesis and on a hypothesis on the multiplicity of the zeros of $L(E,s)$, large analytic ranks translate into an extreme Chebyshev bias. Conversely, we show under a certain linear independence hypothesis on zeros of $L(E,s)$ that if highly biased elliptic curve prime number races do exist, then the Riemann Hypothesis holds for infinitely many elliptic curve $L$-functions and there exist elliptic curves of arbitrarily large rank.
Disconnected, fragmented, or united? a trans-disciplinary review of network science

During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to unify what has become a diverging body of literature. I argue that social and natural scientists fail to see eye to eye because they have diverging academic goals. Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. In the following pages I discuss the differences between both of these literatures by summarizing the parallel theories advanced to explain link formation and the applications used by scholars in each field to justify their approach to network science. I conclude by providing an outlook on how these literatures can be further unified.
A note on 0-bipolar knots of concordance order two

Let $\mathcal{T}$ be the group of smooth concordance classes of topologically slice knots, and $\{0\}\subset\cdots\subset \mathcal{T}_{n+1}\subset\mathcal{T}_{n}\subset \cdots\subset \mathcal{T}_{0}\subset \mathcal{T}$ be the bipolar filtration. In this paper, we show that a proper collection of the knots employed by Hedden, Kim, and Livingston to prove $\mathbb{Z}_2^{\infty} < \mathcal{T}$ can be used to see $\mathbb{Z}_2^{\infty} < \mathcal{T}_0/\mathcal{T}_1$.
Quantized Decentralized Consensus Optimization

We consider the problem of decentralized consensus optimization, where the sum of $n$ convex functions are minimized over $n$ distributed agents that form a connected network. In particular, we consider the case that the communicated local decision variables among nodes are quantized in order to alleviate the communication bottleneck in distributed optimization. We propose the Quantized Decentralized Gradient Descent (QDGD) algorithm, in which nodes update their local decision variables by combining the quantized information received from their neighbors with their local information. We prove that under standard strong convexity and smoothness assumptions for local cost functions, QDGD achieves a vanishing mean solution error. To the best of our knowledge, this is the first algorithm that achieves vanishing consensus error in the presence of quantization noise. Moreover, we provide simulation results that show tight agreement between our derived theoretical convergence rate and the experimental results.
SIMPLICIAL FLAT NORM WITH SCALE

We study the multiscale simplicial flat norm (MSFN) problem, which computes flat norm at various scales of sets defined as oriented subcomplexes of finite simplicial complexes in arbitrary dimensions. We show that MSFN is NP-complete when homology is defined over integers. We cast MSFN as an instance of integer linear optimization. Following recent results on related problems, the MSFN integer program can be solved in polynomial time by solving its linear programming relaxation, when the simplicial complex satisfies a simple topological condition (absence of relative torsion). Our most significant contribution is the simplicial deformation theorem, which states that one may approximate a general current with a simplicial current while bounding the expansion of its mass. We present explicit bounds on the quality of this approximation, which indicate that the simplicial current gets closer to the original current as we make the simplicial complex finer. MSFN opens up the possibilities of using flat norm to denoise or extract scale information of large data sets in arbitrary dimensions. On the other hand, it allows one to employ the large body of algorithmic results on simplicial complexes to address more general problems related to currents.
Effect of Cell-Selection on the Effective Fading Distribution in a Downlink $K$ -Tier HetNet

This letter characterizes the statistics of effective fading gain in multi-tier cellular networks with strongest base station (BS) cell association policy. First, we derive the probability of association with the ${n}$ -th nearest BS in the ${k}$ -th tier. Next, we use this result to derive the probability density function of the channel fading gain (effective fading) experienced by the user when associating with the strongest BS. Interestingly, our results show that the effective channel gain distribution solely depends upon the original channel fading and the path-loss exponent. Moreover, we show that in the case of Nakagami- ${m}$ fading channels (Gamma distribution), the distribution of the effective fading is also Gamma but with a gain of ${({\alpha }/{2})}$ in the shape parameter, where ${\alpha }$ is the path-loss exponent.