cssi/SciSciGPT-SciSciNet huggingface dataset:
The Structure of Absorptive Capacity in Three Product Development Strategies

This study develops and tests theory about different forms of absorptive capacity that support radical, differentiation and imitation product development strategies. Absorptive capacity theory provides a generalized explanation for how firms exploit their embeddedness in relationships with buyers and suppliers. We develop and test theory that relates combinations of four components of absorptive capacity (R&D capability, product development capability, cooperative embeddedness, and competitive embeddedness) to success rates in three product development strategies. We used data from the American pharmaceutical industry to estimate generalized linear mixed models. Our results confirm known relationships between R&D capability, alliance network position, and the development of radically new products, but reveal different sets of factors that influence differentiation and imitation. We describe a previously undetected influence of competitive embeddedness on the development of radically new products, a contrasting absorptive capacity structure for generic product development, and a mixed structure for differentiated product development.
A metabolomics study of ascorbic acid-induced in situ freezing tolerance in spinach ( Spinacia oleracea L.)

Freeze-thaw stress is one of the major environmental constraints that limit plant growth and reduce productivity and quality. Plants exhibit a variety of cellular dysfunctions following freeze-thaw stress, including accumulation of reactive oxygen species (ROS). This means that enhancement of antioxidant capacity by exogenous application of antioxidants could potentially be one of the strategies for improving freezing tolerance (FT) of plants. Exogenous application of ascorbic acid (AsA), as an antioxidant, has been shown to improve plant tolerance against abiotic stresses but its effect on FT has not been investigated. We evaluated the effect of AsA-feeding on FT of spinach (Spinacia oleracea L.) at whole plant and excised-leaf level, and conducted metabolite profiling of leaves before and after AsA treatment to explore metabolic explanation for change in FT. AsA application did not impede leaf growth, instead slightly promoted it. Temperature-controlled freeze-thaw tests revealed AsA-fed plants were more freezing tolerant as indicated by: (a) less visual damage/mortality; (b) lower ion leakage; and (c) less oxidative injury, lower abundance of free radicals ( O 2 · - and H2O2). Comparative leaf metabolite profiling revealed clear separation of metabolic phenotypes for control versus AsA-fed leaves. Specifically, AsA-fed leaves had greater abundance of antioxidants (AsA, glutathione, alpha- & gamma-tocopherol) and compatible solutes (proline, galactinol, and myo-inositol). AsA-fed leaves also had higher activity of antioxidant enzymes (superoxide dismutase, ascorbate peroxidase, and catalase). These changes, together, may improve FT via alleviating freeze-induced oxidative stress as well as protecting membranes from freeze desiccation. Additionally, improved FT by AsA-feeding may potentially include enhanced cell wall/lignin augmentation and bolstered secondary metabolism as indicated by diminished level of phenylalanine and increased abundance of branched amino acids, respectively.
Low-PAPR Multi-Channel OOK Waveform for IEEE 802.11ba Wake-Up Radio

The peak-to-average-power ratio (PAPR) of the frequency domain multiplexed wake-up signals (WUSs) specified in IEEE P802.11ba can be very large and difficult to manage since it depends on the number and allocation of the active channels, and the data rate on each channel. To address this issue, we propose a transmission scheme based on complementary sequences (CSs) for multiple WUSs multiplexed in the frequency domain. We discuss how to construct CSs compatible with the framework of IEEE P802.11ba by exploiting a recursive Golay complementary pair (GCP) construction to reduce the instantaneous power fluctuations in time. We compare the proposed scheme with the other options under a non-linear power amplifier (PA) distortion. Numerical results show that the proposed scheme can lower the PAPR of the transmitted signal in frequency division multiple access (FDMA) scenarios more than 3 dB and yields a superior error rate performance under severe PA distortion.
Contraction Analysis of Nonlinear DAE Systems

This article studies the contraction properties of nonlinear differential-algebraic equation (DAE) systems. Such systems typically appear as a singular perturbation reduction of a multiple-time-scale differential system. In addition, a given DAE may result from the reduction of many “synthetic” differential systems. We show that an important property of a contracting DAE system is that the reduced system always contracts faster than any synthetic counterpart. At the same time, there always exists a synthetic system, whose contraction rate is arbitrarily close to that of the DAE. Synthetic systems are useful for the analysis of attraction basins of nonlinear DAE systems. As any rational DAE system can be represented in quadratic form, the Jacobian of the synthetic system can be made affine in the system variables. This allows for scalable techniques to construct attraction basin approximations, based on uniformly negative matrix measure conditions for the synthetic system Jacobian.
Change Detection with the Kernel Cumulative Sum Algorithm

Online change detection involves monitoring a stream of data for changes in the statistical properties of incoming observations. A good change detector will detect any changes shortly after they occur, while raising few false alarms. Although there are algorithms with confirmed optimality properties for this task, they rely on the exact specifications of the relevant probability distributions and this limits their practicality. In this work we describe a kernel-based variant of the Cumulative Sum (CUSUM) change detection algorithm that can detect changes under less restrictive assumptions. Instead of using the likelihood ratio, which is a parametric quantity, the Kernel CUSUM (KCUSUM) algorithm compares incoming data with samples from a reference distribution using a statistic based on the Maximum Mean Discrepancy (MMD) non-parametric testing framework. The KCUSUM algorithm is applicable in settings where there is a large amount of background data available and it is desirable to detect a change away from this background setting. Exploiting the random-walk structure of the test statistic, we derive bounds on the performance of the algorithm, including the expected delay and the average time to false alarm.
Using Reinforcement Learning With Partial Vehicle Detection for Intelligent Traffic Signal Control

Intelligent Traffic Signal Control (ITSC) systems have attracted the attention of researchers and the general public alike as a means of alleviating traffic congestion. Recently, the vehicular wireless technologies have enabled a cost-efficient way to achieve ITSC by detecting vehicles using Vehicle to Infrastructure (V2I) wireless communications. Traditional ITSC algorithms, in most cases, assume that every vehicle is detected, such as by a camera or a loop detector, but a V2I implementation would detect only those vehicles equipped with wireless communications capability. We examine a family of transportation systems, which we will refer to as ‘Partially Detected Intelligent Transportation Systems’. An algorithm that can perform well under a small detection rate is highly desirable due to gradual increasing penetration rates of the underlying technologies such as Dedicated Short Range Communications (DSRC) technology. Reinforcement Learning (RL) approach in Artificial Intelligence (AI) could provide indispensable tools for such problems where only a small portion of vehicles are detected by the ITSC system. In this paper, we report a new RL algorithm for Partially Detected Intelligent Traffic Signal Control (PD-ITSC) systems. The performance of this system is studied under different car flows, detection rates, and types of the road network. Our system is able to efficiently reduce the average waiting time of vehicles at an intersection, even with a low detection rate, thus reducing the travel time of vehicles.
Prior Experience Alters the Appearance of Blurry Object Borders

Object memories activated by borders serve as priors for figure assignment: figures are more likely to be perceived on the side of a border where a well-known object is sketched. Do object memories also affect the appearance of object borders? Memories represent past experience with objects; memories of well-known objects include many with sharp borders because they are often fixated. We investigated whether object memories affect appearance by testing whether blurry borders appear sharper when they are contours of well-known objects versus matched novel objects. Participants viewed blurry versions of one familiar and one novel stimulus simultaneously for 180 ms; then made comparative (Exp. 1) or equality judgments regarding perceived blur (Exps. 2–4). For equivalent levels of blur, the borders of well-known objects appeared sharper than those of novel objects. These results extend evidence for the influence of past experience to object appearance, consistent with dynamic interactive models of perception.
The super tree property at the successor of a singular

For an inaccessible cardinal κ, the super tree property (ITP) at κ holds if and only if κ is supercomact. However, just like the tree property, it can hold at successor cardinals. We show that ITP holds at the successor of the limit of ω many supercompact cardinals. Then we show that it can consistently hold at ℵω+1. We also consider a stronger principle, ISP and certain weaker variations of it. We determine which level of ISP can hold at a successor of a singular. These results fit in the broad program of testing how much compactness can exist in the universe, and obtaining large cardinal-type properties at smaller cardinals.
Correlated Multi-Armed Bandits with A Latent Random Source

Multi-armed bandit models are widely studied sequential decision-making problems that exemplify the exploration-exploitation trade-off. We study a novel correlated multi-armed bandit model where the rewards obtained from the arms are functions of a common latent random variable. We propose and analyze the performance of the C-UCB algorithm that leverages the correlations between arms to reduce the cumulative regret (i.e., to increase the total reward obtained after T rounds). Unlike the standard UCB algorithm that pulls all sub-optimal arms O(log T) times, the C-UCB algorithm takes only O(1) times to identify that some arms, which we refer to as non-competitive arms, are optimal. Thus, we effectively reduce a K-armed bandit problem to a C + 1−armed bandit problem with C < K denoting the number of competitive, where C can be computed from the reward functions. A key consequence is that when C = 0, our algorithm achieves a constant (i.e., O(1)) regret instead of the standard O(log T) scaling with the number of rounds T . Establishing lower bounds for the regret, we show that the C-UCB algorithm is order-wise optimal and demonstrate its superiority against other algorithms via numerical simulations.
How Managers Use Multiple Media: Discrepant Events, Power, and Timing in Redundant Communication

Several recent studies have found that managers engage in redundant communication; that is, they send the same message to the same recipient sequentially through two or more unique media. Given how busy most managers are, and how much information their subordinates receive on a daily basis, this practice seems, initially, quite puzzling. We conducted an ethnographic investigation to examine the nature of events that compelled managers to engage in redundant communication. Our study of the communication patterns of project managers in six companies across three industries indicates that redundant communication is a response to unexpected endogenous or exogenous threats to meeting work goals. Managers used two distinct forms of redundant communication to mobilize team members toward mitigating potentially threatening discrepant events—unforeseen disruptive occurrences during the regular course of work. Managers with positional power over team members reactively followed up on a single communication when their attempt to communicate the existence of a threatening discrepant event failed, and they determined that a second communication was needed to enable its joint interpretation and to gain buy-in. In contrast, managers without positional power over team members proactively used redundant communication to enroll team members in the interpretation process—leading team members to believe that they had come up with the idea that completion of their project was under threat—and then to solidify those interpretations. Moreover, findings indicate that managers used different types of technologies for these sequential pairings based on whether their motivation was simply to transmit a communication of threat or to persuade people that a threat existed. We discuss the implications of these findings for theory about, and the practice of, technologically mediated communication, power, and interpretation in organizations.
On statistical mechanics of vortex lines

An ensemble of a large number of vortex lines in cylindrical bounded domain is being considered. A system of equations determining the statistical characteristics of vortex line motion is derived from the assumption that this motion is ergodic and vortex lines are sufficiently smooth. The smoothness of vortex lines is characterized by vortex diffusivity. Both cases of finite and infinite vortex diffusivity are discussed. The continuum limit equations are obtained.
Improving global access to new vaccines: intellectual property, technology transfer, and regulatory pathways

The 2012 World Health Assembly Global Vaccine Action Plan called for global access to new vaccines within 5 years of licensure. Current approaches have proven insufficient to achieve sustainable vaccine pricing within such a timeline. Paralleling the successful strategy of generic competition to bring down drug prices, a clear consensus is emerging that market entry of multiple suppliers is a critical factor in expeditiously bringing down prices of new vaccines. In this context, key target objectives for improving access to new vaccines include overcoming intellectual property obstacles, streamlining regulatory pathways for biosimilar vaccines, and reducing market entry timelines for developing-country vaccine manufacturers by transfer of technology and know-how. I propose an intellectual property, technology, and know-how bank as a new approach to facilitate widespread access to new vaccines in low- and middle-income countries by efficient transfer of patented vaccine technologies to multiple developing-country vaccine manufacturers.
Regulation of catechol synthesis in an adrenergic clone of mouse neuroblastoma

Publisher Summary This chapter discusses studies analyzing regulation of catechol synthesis in an adrenergic clone of mouse neuroblastoma. From the mouse neuroblastoma cell culture system, clones were derived which were examined for tyrosine hydroxylase, choline acetyltransferase and acetylcholinesterase. Three major types of clones were found (1) adrenergic, (2) cholinergic and (3) clones that do not synthesize acetylcholine or catechols (inactive). All major types of clones had high levels of acetylcholinesterase and electrically excitable membranes. Except for one inactive clone, all clones were able to form neurites. No clone had high levels of both choline acetyltransferase and tyrosine hydroxylase. The results showed that mouse neuroblastoma C1300 is a heterogeneous cell population comprising at least three cell types when classified with respect to neurotransmitter synthesis. To investigate the biosynthesis of catecholamines, the adrenergic neuroblastoma clone (NIE-115) with the highest level of tyrosine hydroxylase was studied. The activity of tyrosine hydroxylase in crude sonicates of N1E-115 is comparable to that found in lysed granules of the adrenal medulla which is regarded as a very rich source of this enzyme. This chapter reports results with N1E-115 on transport of neurotransmitter precursors and regulation of tyrosine hydroxylase.
Dissolving and stabilizing soft WB2 and MoB2 phases into high-entropy borides via boron-metals reactive sintering to attain higher hardness

Abstract Five single-phase WB2- and MoB2-containing high-entropy borides (HEBs) have been made via reactive spark plasma sintering of elemental boron and metals. A large reactive driving force enables the full dissolution of 10−20 mol. % WB2 to form dense, single-phase HEBs, including (Ti0.2Zr0.2Hf0.2Mo0.2W0.2)B2, (Ti0.2Ta0.2Cr0.2Mo0.2W0.2)B2, (Zr0.2Hf0.2Nb0.2Ta0.2W0.2)B2, and (Zr0.225Hf0.225Ta0.225Mo0.225W0.1)B2; the successful fabrication of such single-phase WB2-containing HEBs has not been reported before. In the processing science, this result serves perhaps the best example demonstrating that the phase formation in high-entropy ceramics can strongly depend on the kinetic route. A scientifically interesting finding is that HEBs containing softer WB2 and/or MoB2 components are significantly harder than (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)B2 (with harder binary boride components). This exemplifies that high-entropy ceramics can achieve unexpected properties.
Community pharmacy response to infection control during COVID-19. A cross-sectional survey

Abstract Pharmacies have been practicing innovative infection control measures during COVID-19. This article seeks to explore the current activities undertaken across various community pharmacy settings in relation to the safety of the workplace environment for staff and patients. Methods An online cross-sectional survey was conducted in Australia during the COVID-19 outbreak from 1st to 30th April 2020, addressing community pharmacist's awareness and response to infection and sanitation control. Results A total of 137 pharmacists took part in the survey. Regular cleaning took place in the pharmacy, but the use of gloves while cleaning was not regularly practice (48.18%). In addition, only 46.72% of respondents reported observing script baskets being cleaned and disinfected. About one-third (37.96%) of pharmacists were aware of the two-step cleaning and disinfecting process, with only 18.98% of pharmacist practicing such cleaning procedures. More than half of surveyed pharmacists reported having difficulty keeping up with pharmacy practice and infection control guidelines during the pandemic. Conclusion This study demonstrates that the majority of pharmacists are not fully aware of the proper infection control measures needed in a community pharmacy setting. Pharmacists must play a bigger role in infection control measures to ensure staff and public health safety.
Efficient computation of higher-order variational integrators in robotic simulation and trajectory optimization

This paper addresses the problem of efficiently computing higher-order variational integrators in simulation and trajectory optimization of mechanical systems as those often found in robotic applications. We develop O(n) algorithms to evaluate the discrete Euler-Lagrange (DEL) equations and compute the Newton direction for solving the DEL equations, which results in linear-time variational integrators of arbitrarily high order. To our knowledge, no linear-time higher-order variational or even implicit integrators have been developed before. Moreover, an \(O(n^2)\) algorithm to linearize the DEL equations is presented, which is useful for trajectory optimization. These proposed algorithms eliminate the bottleneck of implementing higher-order variational integrators in simulation and trajectory optimization of complex robotic systems. The efficacy of this paper is validated through comparison with existing methods, and implementation on various robotic systems—including trajectory optimization of the Spring Flamingo robot, the LittleDog robot and the Atlas robot. The results illustrate that the same integrator can be used for simulation and trajectory optimization in robotics, preserving mechanical properties while achieving good scalability and accuracy.
Congruences for Coefficients of Modular Functions in Levels 3, 5, and 7 with Poles at 0

Abstract We give congruences modulo powers of p ∈ { 3 , 5 , 7 } for the Fourier coefficients of certain modular functions in level p with poles only at 0, answering a question posed by Andersen and the first author and continuing work done by the authors and Moss. The congruences involve a modulus that depends on the base p expansion of the modular form's order of vanishing at ∞.
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response.

Artificial Intelligence (AI) has become an integral part of modern-day security solutions for its ability to learn very complex functions and handling "Big Data". However, the lack of explainability and interpretability of successful AI models is a key stumbling block when trust in a model's prediction is critical. This leads to human intervention, which in turn results in a delayed response or decision. While there have been major advancements in the speed and performance of AI-based intrusion detection systems, the response is still at human speed when it comes to explaining and interpreting a specific prediction or decision. In this work, we infuse popular domain knowledge (i.e., CIA principles) in our model for better explainability and validate the approach on a network intrusion detection test case. Our experimental results suggest that the infusion of domain knowledge provides better explainability as well as a faster decision or response. In addition, the infused domain knowledge generalizes the model to work well with unknown attacks, as well as opens the path to adapt to a large stream of network traffic from numerous IoT devices.
Reflection positivity and Levin–Wen models

Abstract We give a transparent algebraic formulation of our pictorial approach to the reflection positivity (RP), that we introduced in a previous paper. We apply this quantization to the 2 + 1 Levin–Wen model to obtain 1 + 1 anyonic/quantum spin chain theory on the boundary, possibly entangled in the bulk. The reflection positivity property has played a central role in both mathematics and physics, as well as providing a crucial link between the two subjects. In a previous paper we gave a new geometric approach to understanding reflection positivity in terms of pictures. Here we give a transparent algebraic formulation of our pictorial approach. We use insights from this translation to establish the reflection positivity property for the fashionable Levin–Wen models with respect both to vacuum and to bulk excitations. We believe these methods will be useful for understanding a variety of other problems.
Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap

Training robotic policies in simulation suffers from the sim-to-real gap, as simulated dynamics can be different from real-world dynamics. Past works tackled this problem through domain randomization and online system-identification. The former is sensitive to the manually-specified training distribution of dynamics parameters and can result in behaviors that are overly conservative. The latter requires learning policies that concurrently perform the task and generate useful trajectories for system identification. In this work, we propose and analyze a framework for learning exploration policies that explicitly perform task-oriented exploration actions to identify task-relevant system parameters. These parameters are then used by model-based trajectory optimization algorithms to perform the task in the real world. We instantiate the framework in simulation with the Linear Quadratic Regulator as well as in the real world with pouring and object dragging tasks. Experiments show that task-oriented exploration helps model-based policies adapt to systems with initially unknown parameters, and it leads to better task performance than task-agnostic exploration.
Drag force to all orders in gradients

We study the energy loss of a heavy quark slowly moving through an evolving strongly coupled plasma. We use the linearized fluid/gravity correspondence to describe small perturbations of the medium flow with general spacetime dependence. This all order linearized hydrodynamics results in a drag force exerted on a heavy quark even when it is at rest with the fluid element. We show how the general contribution to the drag force can be derived order by order in the medium velocity gradients and provide explicit results valid up to the third order. We then obtain an approximate semi-analytic result for the drag force to all orders in the gradient expansion but linearized in the medium velocity. Thus, the effects of a class of hydrodynamic gradients on the drag force are re-summed, giving further insight into the dissipative properties of strongly coupled plasmas. The all order result allows us to study the drag force in the non-hydrodynamic regime of linear medium perturbations that vary rapidly in space and time.
Performance of MPI Sends of Non-Contiguous Data

We present an experimental investigation of the performance of MPI derived datatypes. While solutions with hardware support can achieve high performance, we show that vanilla approaches fall short. For messages up to the megabyte range most schemes perform comparably to each other and to manual copying into a regular send buffer. However, for large messages the internal buffering of MPI causes marked differences in efficiency. We show how schemes that acknowledge the importance of buffer management give both the highest performance and a simple usage.
Superconducting tunnel junction receiver for 2.6 mm

A 110–118 GHz receiver based on a superconducting quasiparticle tunnel junction mixer is described. The single-sideband noise temperature is as low as 68 ± 3 K. This is nearly twice the sensitivity of any other receiver at this frequency.
Resiliency analysis and improvement of variational quantum factoring in superconducting qubit

Variational algorithm using Quantum Approximate Optimization Algorithm (QAOA) can solve the prime factorization problem in near-term noisy quantum computers. Conventional Variational Quantum Factoring (VQF) requires a large number of 2-qubit gates (especially for factoring a large number) resulting in deep circuits. The output quality of the deep quantum circuit is degraded due to errors limiting the computational power of quantum computing. In this paper, we explore various transformations to optimize the QAOA circuit for integer factorization. We propose two criteria to select the optimal quantum circuit that can improve the noise resiliency of VQF.
An Investigation of Three-Finger Toxin-nAChR Interactions through Rosetta Protein Docking.

Three-finger toxins (3FTX) are a group of peptides that affect multiple receptor types. One group of proteins affected by 3FTX are nicotinic acetylcholine receptors (nAChR). Structural information on how neurotoxins interact with nAChR is limited and is confined to a small group of neurotoxins. Therefore, in silico methods are valuable in understanding the interactions between 3FTX and different nAChR subtypes, but there are no established protocols to model 3FTX–nAChR interactions. We followed a homology modeling and protein docking protocol to address this issue and tested its success on three different systems. First, neurotoxin peptides co-crystallized with acetylcholine binding protein (AChBP) were re-docked to assess whether Rosetta protein–protein docking can reproduce the native poses. Second, experimental data on peptide binding to AChBP was used to test whether the docking protocol can qualitatively distinguish AChBP-binders from non-binders. Finally, we docked eight peptides with known α7 and muscle-type nAChR binding properties to test whether the protocol can explain the differential activities of the peptides at the two receptor subtypes. Overall, the docking protocol predicted the qualitative and some specific aspects of 3FTX binding to nAChR with reasonable success and shed light on unknown aspects of 3FTX binding to different receptor subtypes.
Baryon Chiral Dynamics

Many of the constraints of chiral symmetry on the interaction of pions and nucleons at low energies were worked out long before the advent of QCD (Current algebra, PCAC). Later it was realized that the corrections to these symmetry relations can be obtained by implementing the chiral symmetry and its breaking by the quark masses into an effective Lagrangian describing the interaction of mesons and baryons. This method is called chiral perturbation theory (CHPT).l It allows one to compute the expansion of QCD amplitudes and transition currents in powers of the external momenta and quark masses; it has become one of the standard tools to analyze the strong interactions at low energy. Over the last few years, the progress in this field in the baryon sector has been twofold: on one hand, we have reached a new level of precision in many of the classical applications: by now, the full one loop result for the nucleon form factors and the pion-nucleon scattering amplitude in the isospin limit is k n ~ w n . ~ ~ ~ Even the first two-loop result has been obtained: the chirai expansion of the nucleon mass has been worked out to fifth order.4 On the other hand, the framework has been extended and applied to a whole range of new processes: the effective Lagrangian has been extended to include electromagnetism, making it possible to disentangle strong and electromagnetic isospin ~ io l a t ion .~ This effective theory of QCD+QED has been used to calculate next-to-leading order isospin violating effects in the pion-nucleon scattering amplitude6 and to study the properties of the r p bound state.7 Another extension of the framework incorporates the A-resonance as an explicit degree of freedom into the effective Lagrangian, thereby summing up the potentially large higher-order terms in the chiral expansion associated with this resonance.a Despite all of this impressive progress, we are still short of having the answers to some very old questions, like, for example, what is the value of the
On Cross-Corpus Generalization of Deep Learning Based Speech Enhancement

In recent years, supervised approaches using deep neural networks (DNNs) have become the mainstream for speech enhancement. It has been established that DNNs generalize well to untrained noises and speakers if trained using a large number of noises and speakers. However, we find that DNNs fail to generalize to new speech corpora in low signal-to-noise ratio (SNR) conditions. In this work, we establish that the lack of generalization is mainly due to the channel mismatch, i.e. different recording conditions between the trained and untrained corpus. Additionally, we observe that traditional channel normalization techniques are not effective in improving cross-corpus generalization. Further, we evaluate publicly available datasets that are promising for generalization. We find one particular corpus to be significantly better than others. Finally, we find that using a smaller frame shift in short-time processing of speech can significantly improve cross-corpus generalization. The proposed techniques to address cross-corpus generalization include channel normalization, better training corpus, and smaller frame shift in short-time Fourier transform (STFT). These techniques together improve the objective intelligibility and quality scores on untrained corpora significantly.
The generalized distance spectrum of a graph and applications

The generalized distance matrix of a graph is the matrix whose entries depend only on the pairwise distances between vertices, and the generalized distance spectrum is the set of eigenvalues of thi...
Discussion of “ETFs and information transfer across firms”

Abstract Bhojraj, Mohanram, and Zhang (2020) examine how the presence of different types of Exchange Traded Funds (ETFs) affects information transfer across firms. Using earnings announcements as an information event, the authors document that sector ETFs improve informational efficiency by better facilitating information transfer across firms. Furthermore, sector ETFs reduce post-earnings announcement drift. However, the findings using broad ETFs are mixed. In this discussion, I first place the paper within the broader literature that investigates the informational efficiency of stock prices. Second, I highlight the key insights and contributions of the paper. Third, I discuss empirical design issues and the interpretation of findings. Lastly, I suggest areas for future research.
SNARGs for bounded depth computations and PPAD hardness from sub-exponential LWE

We construct a succinct non-interactive publicly-verifiable delegation scheme for any log-space uniform circuit under the sub-exponential Learning With Errors (LWE) assumption. For a circuit C:{0,1}N→{0,1} of size S and depth D, the prover runs in time poly(S), the communication complexity is D · polylog(S), and the verifier runs in time (D+N) ·polylog(S). To obtain this result, we introduce a new cryptographic primitive: a lossy correlation-intractable hash function family. We use this primitive to soundly instantiate the Fiat-Shamir transform for a large class of interactive proofs, including the interactive sum-check protocol and the GKR protocol, assuming the sub-exponential hardness of LWE. Additionally, by relying on the result of Choudhuri et al. (STOC 2019), we establish (sub-exponential) average-case hardness of PPAD, assuming the sub-exponential hardness of LWE.
Hasse polynomials of L-functions of certain exponential sums

Abstract In this paper, we focus on computing the higher slope Hasse polynomials of L-functions of certain exponential sums associated to the following family of Laurent polynomials f ( x 1 , … , x n + 1 ) = ∑ i = 1 n a i x n + 1 ( x i + 1 x i ) + a n + 1 x n + 1 + 1 x n + 1 , where a i ∈ F q ⁎ , i = 1 , 2 , … , n + 1 . We find a simple formula for the Hasse polynomial of the slope one side and study the irreducibility of these Hasse polynomials. We will also provide a simple form of all the higher slope Hasse polynomials for n = 3 , answering an open question of Zhang and Feng.
Quenched Survival of Bernoulli Percolation on Galton–Watson Trees

We explore the survival function for percolation on Galton–Watson trees. Letting g(T, p) represent the probability a tree T survives Bernoulli percolation with parameter p, we establish several results about the behavior of the random function $$g(\mathbf{T}, \cdot )$$ , where $$\mathbf{T}$$ is drawn from the Galton–Watson distribution. These include almost sure smoothness in the supercritical region; an expression for the $$k\text {th}$$ -order Taylor expansion of $$g(\mathbf{T}, \cdot )$$ at criticality in terms of limits of martingales defined from $$\mathbf{T}$$ (this requires a moment condition depending on k); and a proof that the $$k\text {th}$$ order derivative extends continuously to the critical value. Each of these results is shown to hold for almost every Galton–Watson tree.
Springer’s work on unipotent classes and Weyl group representations

Abstract We discuss some of the contributions of T.A. Springer (1926–2011) to the theory of algebraic groups, with emphasis on his work on unipotent classes and representations of Weyl groups.
Mutations on COVID-19 diagnostic targets.

Abstract Effective, sensitive, and reliable diagnostic reagents are of paramount importance for combating the ongoing coronavirus disease 2019 (COVID-19) pandemic when there is neither a preventive vaccine nor a specific drug available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It will cause a large number of false-positive and false-negative tests if currently used diagnostic reagents are undermined. Based on genotyping of 31,421 SARS-CoV-2 genome samples collected up to July 23, 2020, we reveal that essentially all of the current COVID-19 diagnostic targets have undergone mutations. We further show that SARS-CoV-2 has the most mutations on the targets of various nucleocapsid (N) gene primers and probes, which have been widely used around the world to diagnose COVID-19. To understand whether SARS-CoV-2 genes have mutated unevenly, we have computed the mutation rate and mutation h-index of all SARS-CoV-2 genes, indicating that the N gene is one of the most non-conservative genes in the SARS-CoV-2 genome. We show that due to human immune response induced APOBEC mRNA (C > T) editing, diagnostic targets should also be selected to avoid cytidines. Our findings might enable optimally selecting the conservative SARS-CoV-2 genes and proteins for the design and development of COVID-19 diagnostic reagents, prophylactic vaccines, and therapeutic medicines. Availability Interactive real-time online Mutation Tracker .
An Exploratory Study of Bot Commits

Background: Bots help automate many of the tasks performed by software developers and are widely used to commit code in various social coding platforms. At present, it is not clear what types of activities these bots perform and understanding it may help design better bots, and find application areas which might benefit from bot adoption. Aim: We aim to categorize the Bot Commits by the type of change (files added, deleted, or modified), find the more commonly changed file types, and identify the groups of file types that tend to get updated together. Method: 12,326,137 commits made by 461 popular bots (that made at least 1000 commits) were examined to identify the frequency and the type of files added/ deleted/ modified by the commits, and association rule mining was used to identify the types of files modified together. Result: Majority of the bot commits modify an existing file, a few of them add new files, while deletion of a file is very rare. Commits involving more than one type of operation are even rarer. Files containing data, configuration, and documentation are most frequently updated, while HTML is the most common type in terms of the number of files added, deleted, and modified. Files of the type "Markdown","Ignore List", "YAML", "JSON" were the types that are updated together with other types of files most frequently. Conclusion: We observe that majority of bot commits involve single file modifications, and bots primarily work with data, configuration, and documentation files. A better understanding if this is a limitation of the bots and, if overcome, would lead to different kinds of bots remains an open question.
Information and Memory in Dynamic Resource Allocation

We propose a general framework, dubbed stochastic processing under imperfect information (SPII), to study the impact of information constraints and memories on dynamic resource allocation. The fram...
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms appropriate for training. Considering that these networks often have very different performance characteristics than traditional neural networks, it is often unclear how to set either the network topology or the hyperparameters to achieve optimal performance. In this work, we introduce a Bayesian approach for optimizing the hyperparameters of an algorithm for training binary communication networks that can be deployed to neuromorphic hardware. We show that by optimizing the hyperparameters on this algorithm for each dataset, we can achieve improvements in accuracy over the previous state-of-the-art for this algorithm on each dataset (by up to 15 percent). This jump in performance continues to emphasize the potential when converting traditional neural networks to binary communication applicable to neuromorphic hardware.
On the Price of Satisficing in Network User Equilibria

When network users are satisficing decision makers, the resulting traffic pattern attains a satisficing user equilibrium, which may deviate from the (perfectly rational) user equilibrium. In a sati...
Automated Service Discovery for Social Internet-of-Things Systems

In this paper, we propose to design an automated service discovery process to allow mobile crowdsourcing task requesters select a small set of devices out of a large-scale Internet-of-things (IoT) network to execute their tasks. To this end, we proceed by dividing the large-scale IoT network into several virtual communities whose members share strong social IoT relations. Two community detection algorithms, namely Louvain and order statistics local method (OSLOM) algorithms, are investigated and applied to a real-world IoT dataset to form non-overlapping and overlapping IoT devices groups. Afterwards, a natural language process (NLP)-based approach is executed to handle crowdsourcing textual requests and accordingly find the list of IoT devices capable of effectively accomplishing the tasks. This is performed by matching the NLP outputs, e.g., type of application, location, required trustworthiness level, with the different detected communities. The proposed approach effectively helps in automating and reducing the service discovery procedure and recruitment process for mobile crowdsourcing applications.
Nf2 fine-tunes proliferation and tissue alignment during closure of the optic fissure in the embryonic mouse eye

Uveal coloboma represents one of the most common congenital ocular malformations accounting for up to 10% of childhood blindness (~1 in 5000 live birth). Coloboma originates from defective fusion of the optic fissure (OF), a transient gap that forms during eye morphogenesis by asymmetric, ventral invagination. Genetic heterogeneity combined with the activity of developmentally regulated genes suggests multiple mechanisms regulating OF closure. The tumor suppressor and FERM domain protein Neurofibromin 2 (NF2) controls diverse processes in cancer, development and regeneration, via Hippo pathway and cytoskeleton regulation. In humans, NF2 mutations can cause ocular abnormalities, including coloboma, however, its actual role in OF closure is unknown. Using conditional inactivation in the embryonic mouse eye, our data indicate that loss of Nf2 function results in a novel underlying cause for coloboma. In particular, mutant eyes show substantially increased retinal pigmented epithelium (RPE) proliferation in the fissure region with concomitant acquisition of RPE cell fate. Cells lining the OF margin can maintain RPE fate ectopically and fail to transition from neuroepithelial to cuboidal shape. In the dorsal RPE of the optic cup, Nf2 inactivation leads to a robust increase in cell number, with local disorganization of the cytoskeleton components F-actin and pMLC2. We propose that RPE hyperproliferation is the primary cause for the observed defects causing insufficient alignment of the OF margins in Nf2 mutants and failure to fuse properly, resulting in persistent coloboma. Our findings indicate that limiting proliferation particularly in the RPE layer is a critical mechanism during OF closure.
Local Immunodeficiency: Role of Neutral Viruses

This paper analyzes the role of neutral viruses in the phenomenon of local immunodeficiency. We show that, even in the absence of altruistic viruses, neutral viruses can support the existence of persistent viruses and thus local immunodeficiency. However, in all such cases neutral viruses can maintain only bounded (relatively small) concentration of persistent viruses. Moreover, in all such cases the state of local immunodeficiency could only be marginally stable, while it is known that altruistic viruses can maintain stable local immunodeficiency. We also present an absolutely minimal cross-immunoreactivity network where a stable and robust state of local immunodeficiency can be maintained. It is now a challenge to synthetic biology to build such small networks with stable local immunodeficiency. Another important challenge for biology is to understand which types of viruses can play a role of persistent, altruistic and neutral ones and whether a role which a given virus plays depends on the structure (topology) of a given cross-immunoreactivity network.
Virtual domination of 3–manifolds

For any closed oriented hyperbolic 3-manifold M, and any closed oriented 3-manifold N, we will show that M admits a finite cover M ' , such that there exists a degree-2 map f : M ' ! N, i.e. M virtually 2-dominates N. 1.1. Background and the Main Result. Traditionally, essential codimension-1 objects in 3-manifolds, e.g. incompressible surfaces, taut foliations, essential laminations, are very important and interesting objects in 3-manifold topology. There are various methods to construct such essential codimension-1 objects, and most of the constructions use topological methods. Recently, in (KM1), Kahn and Markovic used hyperbolic geometry and dynamical system to show the following Surface Subgroup Theorem: for any closed hyperbolic 3-manifold M, there exists a closed hyperbolic surface S, such that there is a π1-injective almost totally geodesic immersion S # M. Building on Wise's work ((Wi)), Agol showed that the groups of hyperbolic 3-manifolds are virtually special and LERF ((Ag)). Agol's result admits us to find a finite cover of M, such that S lifts to an embedded incompressible surface, which solves Thurston's Virtual Haken Conjecture ((Th2)). Actually, it is the Surface Subgroup Theorem that admits Wise's machine on geometric group theory available for studying closed hyperbolic 3-manifolds. In (Su), for any closed hyperbolic 3-manifold M, we used Kahn-Markovic surfaces to construct an immersed π1-injective 2-complex Xn # M. Here the 2-complex Xn is a local model of homological Zn-torsion. Then the results of Agol ((Ag)) and Haglund-Wise ((HW)) can be applied to Xn # M, and we showed the following result: for any finite abelian group A, and any closed hyperbolic 3-manifold M, M admits a finite cover M ' , such that A is a direct summand of Tor(H1(M ' ;Z)) (see (Su)). The proof of the above result suggests us to construct some other type of immersed π1-injective 2-complexes in closed hyperbolic 3-manifolds. Then LERF or other virtual properties of hyperbolic 3-manifolds will imply some other nice results. In this paper, we will give another application of this idea, and show the following result. Theorem 1.1. For any closed oriented hyperbolic 3-manifold M, and any closed oriented 3- manifold N, M admits a finite cover M ' , such that there exists a degree-2 map f : M ' → N, i.e. M virtually 2-dominates N. Remark 1.2. In a previous version of this paper, we used results in (Ga), and could only show that any closed oriented hyperbolic 3-manifold virtually dominates any closed oriented 3-manifold, but with no bound on the degree of the non-zero degree map. The author wants