cssi/SciSciGPT-SciSciNet huggingface dataset:
The Focusing Cubic NLS on Exterior Domains in Three Dimensions

We consider the focusing cubic NLS in the exterior $\Omega$ of a smooth, compact, strictly convex obstacle in three dimensions. We prove that the threshold for global existence and scattering is the same as for the problem posed on Euclidean space. Specifically, we prove that if $E(u_0)M(u_0)<E(Q)M(Q)$ and $\|\nabla u_0\|_2\|u_0\|_2<\|\nabla Q\|_2\|Q\|_2$, the corresponding solution to the initial-value problem with Dirichlet boundary conditions exists globally and scatters to linear evolutions asymptotically in the future and in the past. Here, $Q(x)$ denotes the ground state for the focusing cubic NLS in $\mathbb{R}^3$.
Gross-Siebert’s slab functions and open GW invariants for toric Calabi-Yau manifolds

This paper derives an equality between the slab functions in Gross-Siebert program and generating functions of open Gromov-Witten invariants for toric Calabi-Yau manifolds, and thereby confirms a conjecture of Gross-Siebert on symplectic enumerative meaning of slab functions. The proof is based on the open mirror theorem of Chan-Cho-Lau-Tseng [CCLT13]. It shows an instance of correspondence between tropical and symplectic geometry in the open sector.
MOST BOSON QUANTUM STATES ARE ALMOST MAXIMALLY ENTANGLED

The geometric measure E of entanglement of an m qubit quantum state takes maximal possible value m. In previous work of Gross, Flammia, and Eisert, it was shown that E ≥ m − O(log m) with high probability as m → ∞. They show, as a consequence, that the vast majority of states are too entangled to be computationally useful. In this paper, we show that for m qubit Boson quantum states (those that are actually available in current designs for quantum computers), the maximal possible geometric measure of entanglement is log2 m, opening the door to many computationally universal states. We further show the corresponding concentration result that E ≥ log2 m − O(log log m) with high probability as m → ∞. We extend these results also to m-mode n-bit Boson quantum states.
On partitions with fixed number of even-indexed and odd-indexed odd parts

Abstract This article is an extensive study of partitions with fixed number of odd and even-indexed odd parts. We use these partitions to generalize recent results of C. Savage and A. Sills. Moreover, we derive explicit formulas for generating functions for partitions with bounds on the largest part, the number of parts and with a fixed value of BG-rank or with a fixed value of alternating sum of parts. We extend the work of C. Boulet, and as a result, obtain a four-variable generalization of Gaussian binomial coefficients. In addition, we provide combinatorial interpretation of the Berkovich–Warnaar identity for Rogers–Szegő polynomials.
A Prototype Combination TPC Cherenkov Detector with GEM Readout for Tracking and Particle Identification and its Potential Use at an Electron Ion Collider

A prototype detector is being developed which combines the functions of a Time Projection Chamber for charged particle tracking and a Cherenkov detector for particle identification. The TPC consists of a 10×10×10 cm 3 drift volume where the charge is drifted to a 10×10 cm 2 triple GEM detector. The charge is measured on a readout plane consisting of 2×10 mm 2 chevron pads which provide a spatial resolution ∼ 100 μm per point in the chevron direction along with dE/dx information. The Cherenkov portion of the detector consists of a second 10×10 cm 2 triple GEM with a photosensitive CsI photocathode on the top layer. This detector measures Cherenkov light produced in the drift gas of the TPC by high velocity particles which are above threshold. CF 4 or CF 4 mixtures will be used as the drift gas which are highly transparent to UV light and can provide excellent efficiency for detecting Cherenkov photons. The drift gas is also used as the operating gas for both GEM detectors. The prototype detector has been constructed and is currently being tested in the lab with sources and cosmic rays, and additional tests are planned in the future to study the detector in a test beam.
Constraining the Clustering Transition for Colorings of Sparse Random Graphs

Let $\Omega_q$ denote the set of proper $[q]$-colorings of the random graph $G_{n,m}, m=dn/2$ and let $H_q$ be the graph with vertex set $\Omega_q$ and an edge $\{\sigma,\tau\}$ where $\sigma,\tau$ are mappings $[n]\to[q]$ iff $h(\sigma,\tau)=1$. Here $h(\sigma,\tau)$ is the Hamming distance $|\{v\in [n]:\sigma(v)\neq\tau(v)\}|$. We show that w.h.p. $H_q$ contains a single giant component containing almost all colorings in $\Omega_q$ if $d$ is sufficiently large and $q\geq \frac{cd}{\log d}$ for a constant $c>3/2$.
On formal codegrees of fusion categories

We prove a general result which implies that the global and Frobenius-Perron dimensions of a fusion category generate Galois invariant ideals in the ring of algebraic integers.
Interpolating between Hilbert–Samuel and Hilbert–Kunz multiplicity

Abstract We define a function, called s-multiplicity, that interpolates between Hilbert–Samuel multiplicity and Hilbert–Kunz multiplicity by comparing powers of ideals to the Frobenius powers of ideals. The function is continuous in s, and its value is equal to Hilbert–Samuel multiplicity for small values of s and is equal to Hilbert–Kunz multiplicity for large values of s. We prove that it has an Associativity Formula generalizing the Associativity Formulas for Hilbert–Samuel and Hilbert–Kunz multiplicity. We also define a family of closures such that if two ideals have the same s-closure then they have the same s-multiplicity, and the converse holds under mild conditions. We describe the s-multiplicity of monomial ideals in toric rings as a certain volume in real space.
Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

Abstract : The Tor anonymity network has been shown vulnerable to traffic analysis attacks by autonomous systems and Internet exchanges, which can observe different overlay hops belonging to the same circuit. We evaluate whether network path prediction techniques provide an accurate picture of the threat from such adversaries, and whether they can be used to avoid this threat. We perform a measurement study by collecting 17.2 million traceroutes from Tor relays to destinations around the Internet. We compare the collected traceroute paths to predicted paths using state-of-the-art path inference techniques. We find that only 20.0% of predicted paths match paths seen in the traceroutes. We also consider the impact that prediction errors have on Tor security. Using a simulator to choose paths over a week, our traceroutes indicate a user could expect 10.9% of paths to contain an AS compromise and 0.9% to have an IX compromise with default Tor selection. We find modifying the path selection to choose paths predicted to be safe still presents a 5.3-1% chance of compromise in a week while making 5.1% of paths fail with 96% failing unnecessarily due to false positives in path inferences. Our results demonstrate more measurement and better path prediction is necessary to mitigate the risk of AS and IX adversaries to Tor.
Stability criteria of 3D inviscid shears

Recent numerical studies in the area of transition to turbulence discovered that the classical plane Couette flow, plane Poiseuille flow, and pipe Poiseuille flow share some universal 3D steady coherent structure in the form of a "streak-roll-critical layer". As the Reynolds number approaches infinity, the steady coherent structure approaches a 3D limiting shear of the form (U(y, z), 0, 0) in velocity variables. All such 3D shears are steady states of the 3D Euler equations. This raises the importance of investigating the stability of such inviscid 3D shears in contrast to the classical Rayleigh theory of inviscid 2D shears. Several general criteria of stability for such inviscid 3D shears are derived. In the Appendix, an argument is given to show that a 2D limiting shear can only be the classical laminar shear.
A new proof of Sárközy’s theorem

It is a striking and elegant fact (proved independently by Furstenberg and Sarkozy) that in any subset of the natural numbers of positive upper density there necessarily exist two distinct elements whose difference is given by a perfect square. In this article we present a new and simple proof of this result by adapting an argument originally developed by Croot and Sisask to give a new proof of Roth's theorem.
A constraint-based algorithm for causal discovery with cycles, latent variables and selection bias

Causal processes in nature may contain cycles, and real datasets may violate causal sufficiency as well as contain selection bias. No constraint-based causal discovery algorithm can currently handle cycles, latent variables and selection bias (CLS) simultaneously. I therefore introduce an algorithm called cyclic causal inference (CCI) that makes sound inferences with a conditional independence oracle under CLS, provided that we can represent the cyclic causal process as a non-recursive linear structural equation model with independent errors. Empirical results show that CCI outperforms the cyclic causal discovery algorithm in the cyclic case as well as rivals the fast causal inference and really fast causal inference algorithms in the acyclic case. An R implementation is available at https://github.com/ericstrobl/CCI .
Classical theory of laser-assisted spontaneous bremsstrahlung

We study the process of laser-assisted spontaneous electron bremsstrahlung by running classical trajectories in a combined Coulomb and laser (ac) fields. Due to chaotic scattering in the combined Coulomb and ac fields, the radiation probability as a function of the impact parameter and the constant phase of the laser field exhibits fractal structures. However, these structures are smeared out when the cross section is integrated over the impact parameter and averaged over the phase. We analyze the role of different types of orbits, including the trapped orbits, and the dependence of the radiation probability on the impact parameter and the initial phase of the ac field. We show that, at low incident electron kinetic energy, the Coulomb focusing leads to a substantial extension of the range of impact parameters contributing to the bremsstrahlung cross section and results in a substantial increase (by one to two orders of magnitude) of the cross section as compared with the pure Coulomb case. As examples, we discuss the case of relatively high ponderomotive energy ${E}_{p}$ when we obtain an efficient production of photons with frequencies up to $2{E}_{p}$, and the case of low ${E}_{p}$ when only infrared photons are produced. Overall accuracy of the classical approach is estimated to be very good, although it does not describe resonant processes studied previously by quantum-mechanical methods.
Exploring Teacher Adaptive Expertise in the Context of Elementary School Science Reforms

Across the country, states are adopting and implementing either Next Generation Science Standards (NGSS) or new state standards inspired by NGSS. Educators and researchers play a key role in the re...
Viral taxonomy derived from evolutionary genome relationships

We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.
Odorant receptors from Culex quinquefasciatus and Aedes aegypti sensitive to floral compounds.

Abstract Mosquitoes rely heavily on the olfactory system to find a host for a bloodmeal, plants for a source of energy and suitable sites for oviposition. Here, we examined a cluster of eight odorant receptors (ORs), which includes one OR, CquiOR1, previously identified to be sensitive to plant-derived compounds. We cloned 5 ORs from Culex quinquefasciatus and two ORs from Aedes aegypti, ie, CquiOR2, CquiOR4, CquiOR5, CquiOR84, CquiOR85, AaegOR14, and AaegOR15 and then deorphanized these receptors using the Xenopus oocyte recording system and a large panel of odorants. 2-Phenylethanol, phenethyl formate, and phenethyl propionate were the best ligands for CquiOR4 somewhat resembling the profile of AaegOR15, which gave the strongest responses to phenethyl propionate, phenethyl formate, and acetophenone. In contrast, the best ligands for CquiOR5 were linalool, PMD, and linalool oxide. CquiOR4 was predominantly expressed in antennae of nonblood fed female mosquitoes, with transcript levels significantly reduced after a blood meal. 2-Phenylethanol showed repellency activity comparable to that of DEET at 1%. RNAi experiments suggest that at least in part 2-phenylethanol-elicited repellency is mediated by CquiOR4 activation.
What Do Deviations from Covered Interest Parity and Higher FX Hedging Costs Mean for Asia

Asian countries have high demand for US dollars and are sensitive to US dollar funding costs. An important, but often overlooked, component of these costs is the basis spread in the cross-currency swap market that emerges when there are deviations from covered interest parity (CIP). CIP deviations mean that investors need to pay a premium to borrow US dollars or other currencies on a hedged basis via the cross-currency swap markets. These deviations can be explained by regulatory changes since the GFC, which have limited arbitrage opportunities and country-specific factors that contribute to a mismatch in the demand and supply of US dollars. We find that an increase in the basis spread tightens financial conditions in net debtor countries, while eases financial conditions in net creditor countries. The main reason is that net debtor countries are, in general, unable to substitute smoothly to other domestic funding channels. Policies that promote reliable alternative funding sources, such as long-term corporate bond market, or stable long-term investors, including a “hedging counterpart of last resort,” can help stabilize financial intermediation when US dollar funding markets come under stress.
End-to-End Learning on 3D Protein Structure for Interface Prediction

Despite an explosion in the number of experimentally determined, atomically detailed structures of biomolecules, many critical tasks in structural biology remain data-limited. Whether performance in such tasks can be improved by using large repositories of tangentially related structural data remains an open question. To address this question, we focused on a central problem in biology: predicting how proteins interact with one another—that is, which surfaces of one protein bind to those of another protein. We built a training dataset, the Database of Interacting Protein Structures (DIPS), that contains biases but is two orders of magnitude larger than those used previously. We found that these biases significantly degrade the performance of existing methods on gold-standard data. Hypothesizing that assumptions baked into the hand-crafted features on which these methods depend were the source of the problem, we developed the first end-to-end learning model for protein interface prediction, the Siamese Atomic Surfacelet Network (SASNet). Using only spatial coordinates and identities of atoms, SASNet outperforms state-of-the-art methods trained on gold-standard structural data, even when trained on only 3% of our new dataset. Code and data available at https://github.com/drorlab/DIPS.
Characterizing Bias in Classifiers using Generative Models

Models that are learned from real-world data are often biased because the data used to train them is biased. This can propagate systemic human biases that exist and ultimately lead to inequitable treatment of people, especially minorities. To characterize bias in learned classifiers, existing approaches rely on human oracles labeling real-world examples to identify the "blind spots" of the classifiers; these are ultimately limited due to the human labor required and the finite nature of existing image examples. We propose a simulation-based approach for interrogating classifiers using generative adversarial models in a systematic manner. We incorporate a progressive conditional generative model for synthesizing photo-realistic facial images and Bayesian Optimization for an efficient interrogation of independent facial image classification systems. We show how this approach can be used to efficiently characterize racial and gender biases in commercial systems.
Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning

We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the model is able to transfer voices across languages, e.g. synthesize fluent Spanish speech using an English speaker's voice, without training on any bilingual or parallel examples. Such transfer works across distantly related languages, e.g. English and Mandarin. Critical to achieving this result are: 1. using a phonemic input representation to encourage sharing of model capacity across languages, and 2. incorporating an adversarial loss term to encourage the model to disentangle its representation of speaker identity (which is perfectly correlated with language in the training data) from the speech content. Further scaling up the model by training on multiple speakers of each language, and incorporating an autoencoding input to help stabilize attention during training, results in a model which can be used to consistently synthesize intelligible speech for training speakers in all languages seen during training, and in native or foreign accents.
Kostant’s weight multiplicity formula and the Fibonacci and Lucas numbers

Consider the weight $\lambda$ which is the sum of all simple roots of a simple Lie algebra. Using Kostant's weight multiplicity formula we describe and enumerate the contributing terms to the multiplicity of the zero weight in the representation with highest weight $\lambda$. We prove that in Lie algebras of type $A$ and $B$, the number of contributing terms to the multiplicity of the zero-weight space in the representation with highest weight $\lambda$ is given by a Fibonacci number, and that in Lie algebras of type $C$ and $D$, the analogous result is given by a multiple of a Lucas number.
Transcriptomic analysis implicates necroptosis in disease progression and prognosis in myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are characterized by ineffective hematopoiesis and cytopenias due to uncontrolled programmed cell death. The presence of pro-inflammatory cytokines and constitutive activation of innate immunity signals in MDS cells suggest inflammatory cell death, such as necroptosis, may be responsible for disease phenotype. We evaluated 64 bone marrow samples from 55 patients with MDS or chronic myelomonocytic leukemia (CMML) obtained prior to (n = 46) or after (n = 18) therapy with hypomethylating agents (HMAs). RNA from sorted bone marrow CD34+ cells was isolated and subject to amplification and RNA-Seq. Compared with healthy controls, expression levels of MLKL (CMML: 2.09 log2FC, p = 0.0013; MDS: 1.89 log2FC, p = 0.003), but not RIPK1 or RIPK3, were significantly upregulated. Higher expression levels of MLKL were associated with lower hemoglobin levels at diagnosis (−0.19 log2FC per 1 g/dL increase of Hgb, p = 0.03). Significant reduction in MLKL levels was observed after HMA therapy (−1.06 log2FC, p = 0.05) particularly among nonresponders (−2.89 log2FC, p = 0.06). Higher RIPK1 expression was associated with shorter survival (HR 1.92, 95% CI 1.00–3.67, p = 0.049 by Cox proportional hazards). This data provides further support for a role of necroptosis in MDS, and potentially response to HMAs and prognosis. This data also indicate that RIPK1/RIPK3/MLKL are potential therapeutic targets in MDS.
Long time-series monitoring of an abyssal site in the NE Pacific: an introduction

Deep-Sea Research II 45 (1998) 573—586 Long time-series monitoring of an abyssal site in the NE Pacific: an introduction K.L. Smith, Jr.!,*, E.R.M. Druffel ! Marine Biology Research Division 0202, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA 92093-0202, USA Department of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA Received 20 October 1997; in revised form 31 October 1997; accepted 4 November 1997 1. Introduction Abyssal regions of the world ocean cover more than 50% of the Earth’s surface (Gage and Tyler, 1991) but the biogeochemical processes in the sediments and deep water column of this vast expanse of our globe are poorly understood. The cycling of material through these deep-sea regions is intimately linked to the organic matter produced in the euphotic zone. The material sinks as particulate matter, undergoing various physical and biochemical transformations in the water column before reach- ing the seafloor. Temporal variability of plankton production in the upper ocean is well documented. The fraction of this production that escapes the euphotic zone as particulate organic matter sinking into the deep sea also exhibits temporal variability, reflecting the changes in surface water production. Independent long time-series measurements of particulate organic matter fluxes to abyssal depths (e.g. Deuser et al., 1981; Honjo, 1982; Deuser, 1986; Haake et al., 1993) and time-lapse photographic records of phytodetrital pulses reaching the sea floor (e.g. Billett et al., 1983; Lampitt, 1985; Rice et al., 1986), although taken in widely separated areas of the deep ocean, have been invaluable for predicting events in other regions. However, the cycling of organic matter in the deep ocean has been difficult to evaluate because synoptic measurements on sufficiently long time scales are rare. The lack of long time-series measurements to examine concurrently the input of a pelagi- cally derived food supply and its impact on benthic boundary layer (BBL) processes *Corresponding author. Fax: 001 619 534 7313; e-mail: ksmith@ucsd.edu. 0967-0645/98/$19.00 ( 1998 Elsevier Science Ltd. All rights reserved. PII: S 0 9 6 7 - 0 6 4 5 ( 9 7 ) 0 0 0 9 4 - 5
TCAD Model for TeraFET Detectors Operating in a Large Dynamic Range

Technology computer-aided design (TCAD) models for AlGaAs/InGaAs and AlGaN/GaN and silicon-on-insulator (SOI) TeraFETs are in good agreement with the measured current–voltage characteristics and the response to the sub-THz radiation. They allowed us to establish the physical mechanism of the observed response saturation at high intensities, not reproduced by the analytical model. By activating or deactivating different physical mechanisms in the TCAD models, we show that the response saturation is caused by the gate leakage for AlGaAs/InGaAs heterostructure field effect transistors (HFETs) and AlGaN/GaN HFETs and by the avalanche effect for SOI mosfet s.
Natural variation in the contribution of microbial density to inducible immune dynamics.

Immune responses evolve to balance the benefits of microbial killing against the costs of autoimmunity and energetic resource use. Models that explore the evolution of optimal immune responses generally include a term for constitutive immunity, or the level of immunological investment prior to microbial exposure, and for inducible immunity, or investment in immune function after microbial challenge. However, studies rarely consider the functional form of inducible immune responses with respect to microbial density, despite the theoretical dependence of immune system evolution on microbe- versus immune-mediated damage to the host. In this study, we analyse antimicrobial peptide (AMP) gene expression from seven wild-caught flour beetle populations (Tribolium spp.) during acute infection with the virulent bacteria Bacillus thuringiensis (Bt) and Photorhabdus luminescens (P.lum) to demonstrate that inducible immune responses mediated by the humoral IMD pathway exhibit natural variation in both microbe density-dependent and independent temporal dynamics. Beetle populations that exhibited greater AMP expression sensitivity to Bt density were also more likely to die from infection, while populations that exhibited higher microbe density-independent AMP expression were more likely to survive P. luminescens infection. Reduction in pathway signalling efficiency through RNAi-mediated knockdown of the imd gene reduced the magnitude of both microbe-independent and dependent responses and reduced host resistance to Bt growth, but had no net effect on host survival. This study provides a framework for understanding natural variation in the flexibility of investment in inducible immune responses and should inform theory on the contribution of nonequilibrium host-microbe dynamics to immune system evolution.
Coupled Recurrent Models for Polyphonic Music Composition

This paper introduces a novel recurrent model for music composition that is tailored to the structure of polyphonic music. We propose an efficient new conditional probabilistic factorization of musical scores, viewing a score as a collection of concurrent, coupled sequences: i.e. voices. To model the conditional distributions, we borrow ideas from both convolutional and recurrent neural models; we argue that these ideas are natural for capturing music's pitch invariances, temporal structure, and polyphony. We train models for single-voice and multi-voice composition on 2,300 scores from the KernScores dataset.
Model-Based String Stability of Adaptive Cruise Control Systems Using Field Data

This article is motivated by the lack of empirical data on the performance of commercially available Society of Automotive Engineers level one automated driving systems. To address this, a set of car following experiments are conducted to collect data from a 2015 luxury electric vehicle equipped with a commercial adaptive cruise control (ACC) system. Velocity, relative velocity, and spacing data collected during the experiments are used to calibrate an optimal velocity relative velocity car following model for both the minimum and maximum following settings. The string stability of both calibrated models is assessed, and it is determined that the best-fit models are string unstable, indicating they are not able to prevent all traffic disturbances from amplifying into phantom jams. Based on the calibrated models, we identify the consequences of the string unstable ACC system on synthetic and empirical lead vehicle disturbances, highlighting that commercial ACC platoons of moderate size can dampen some disturbances even while being string unstable. The primary contributions of this article are the development of a data-driven approach to calculate string stability of ACC systems, and the collection and interpretation of a dataset to understand the car following behavior of a commercial ACC system.
Asynchronous Single-Photon 3D Imaging

Single-photon avalanche diodes (SPADs) are becoming popular in time-of-flight depth-ranging due to their unique ability to capture individual photons with picosecond timing resolution. However, ambient light (e.g., sunlight) incident on a SPAD-based 3D camera leads to severe non-linear distortions (pileup) in the measured waveform, resulting in large depth errors. We propose asynchronous single-photon 3D imaging, a family of acquisition schemes to mitigate pileup during data acquisition itself. Asynchronous acquisition temporally misaligns SPAD measurement windows and the laser cycles through deterministically predefined or randomized offsets. Our key insight is that pileup distortions can be “averaged out” by choosing a sequence of offsets that span the entire depth range. We develop a generalized image formation model and perform theoretical analysis to explore the space of asynchronous acquisition schemes and design high-performance schemes. Our simulations and experiments demonstrate an improvement in depth accuracy of up to an order of magnitude as compared to the state-of-the-art, across a wide range of imaging scenarios, including those with high ambient flux.
Nonlinear random matrix theory for deep learning

Neural network configurations with random weights play an important role in the analysis of deep learning. They define the initial loss landscape and are closely related to kernel and random feature methods. Despite the fact that these networks are built out of random matrices, the vast and powerful machinery of random matrix theory has so far found limited success in studying them. A main obstacle in this direction is that neural networks are nonlinear, which prevents the straightforward utilization of many of the existing mathematical results. In this work, we open the door for direct applications of random matrix theory to deep learning by demonstrating that the pointwise nonlinearities typically applied in neural networks can be incorporated into a standard method of proof in random matrix theory known as the moments method. The test case for our study is the Gram matrix $Y^TY$, $Y=f(WX)$, where $W$ is a random weight matrix, $X$ is a random data matrix, and $f$ is a pointwise nonlinear activation function. We derive an explicit representation for the trace of the resolvent of this matrix, which defines its limiting spectral distribution. We apply these results to the computation of the asymptotic performance of single-layer random feature methods on a memorization task and to the analysis of the eigenvalues of the data covariance matrix as it propagates through a neural network. As a byproduct of our analysis, we identify an intriguing new class of activation functions with favorable properties.
On Restraints in End‐Point Protein–Ligand Binding Free Energy Calculations

The impact of harmonic restraints on protein heavy atoms and ligand atoms on end-point free energy calculations is systematically characterized for 54 protein-ligand complexes. We observe that stronger restraints reduce the equilibration time and statistical inefficiency, suppress conformational sampling, influence correlation with experiment, and monotonically decrease the estimated loss of entropy upon binding, leading to stronger estimated binding free energies in most systems. A statistical estimator that reweights for the biasing potential and includes data prior to the estimated equilibration time has the highest correlation with experiment. A spring constant of 20 cal mol-1 A-2 maintains a near-native energy landscape and suppresses artifactual energy minima while minimally limiting thermal fluctuations about the crystal structure. © 2019 Wiley Periodicals, Inc.
Targeting of the Dosage-Compensated Male X-Chromosome during Early Drosophila Development

Dosage compensation, which corrects for the imbalance in X-linked gene expression between XX females and XY males, represents a model for how genes are targeted for coordinated regulation. However, the mechanism by which dosage compensation complexes identify the X chromosome during early development remains unknown because of the difficulty of sexing embryos before zygotic transcription using X- or Y-linked reporter transgenes. We used meiotic drive to sex Drosophila embryos before zygotic transcription and ChIP-seq to measure the dynamics of dosage compensation factor targeting. The Drosophila male-specific lethal dosage compensation complex (MSLc) requires the ubiquitous zinc-finger protein chromatin-linked adaptor for MSL proteins (CLAMP) to identify the X chromosome. We observe a multi-stage process in which MSLc first identifies CLAMP binding sites throughout the genome, followed by concentration at the strongest X-linked MSLc sites. We provide insight into the dynamics of binding site recognition by a large transcription complex during early development.
Components of the endocytic and recycling trafficking pathways interfere with the integrity of the Legionella-containing vacuole

Legionella pneumophila requires the Dot/Icm translocation system to replicate in a vacuolar compartment within host cells. Strains lacking the translocated substrate SdhA form a permeable vacuole during residence in the host cell, exposing bacteria to the host cytoplasm. In primary macrophages, mutants are defective for intracellular growth, with a pyroptotic cell death response mounted due to bacterial exposure to the cytosol. To understand how SdhA maintains vacuole integrity during intracellular growth, we performed high-throughput RNAi screens against host membrane trafficking genes to identify factors that antagonise vacuole integrity in the absence of SdhA. Depletion of host proteins involved in endocytic uptake and recycling resulted in enhanced intracellular growth and lower levels of permeable vacuoles surrounding the ΔsdhA mutant. Of interest were three different Rab GTPases involved in these processes: Rab11b, Rab8b and Rab5 isoforms, that when depleted resulted in enhanced vacuole integrity surrounding the sdhA mutant. Proteins regulated by these Rabs are responsible for interfering with proper vacuole membrane maintenance, as depletion of the downstream effectors EEA1, Rab11FIP1, or VAMP3 rescued vacuole integrity and intracellular growth of the sdhA mutant. To test the model that specific vesicular components associated with these effectors could act to destabilise the replication vacuole, EEA1 and Rab11FIP1 showed increased density about the sdhA mutant vacuole compared with the wild type (WT) vacuole. Depletion of Rab5 isoforms or Rab11b reduced this aberrant redistribution. These findings are consistent with SdhA interfering with both endocytic and recycling membrane trafficking events that act to destabilise vacuole integrity during infection.
Quantum theory of light in a dispersive structured linear dielectric: a macroscopic Hamiltonian tutorial treatment

These notes – intended to be self-contained and tutorial – present a direct, macroscopic approach to quantizing light inside a linear-response dielectric material when both spectral dispersion and ...
On the Nature of Discrete Space-Time: Part 1: The distance formula, relativistic time dilation and length contraction in discrete space-time

In this work, the relativistic phenomena of Lorentz-Fitzgerald contraction and time dilation are derived using a modified distance formula that is appropriate for discrete space. This new distance formula is different than the Pythagorean theorem but converges to it for distances large relative to the Planck length. First, four candidate formulas developed by different people over the last 70 years will be discussed. Three of the formulas are shown to be identical for conditions that best describe discrete space. It is shown that this new distance formula is valid for all size-scales - from the Planck length upwards - and solves two major problems historically associated with the discrete space-time (DST) model. One problem it solves is the widely believed anisotropic nature of most discrete space models. Just as commonly believed is the second problem - the incompatibility of DST's concept of an immutable atom of space and the length contraction of this atom required by special relativity. The new formula for distance in DST solves this problem. It is shown that length contraction of the atom of space does not occur for any relative velocity of two reference frames. It is also shown that time dilation of the atom of time does not occur. Also discussed is the possibility of any object being able to travel at the speed of light for specific temporal durations given by an equation derived in this work. Also discussed is a method to empirical verify the discreteness of space by studying any observed anomalies in the motion of astronomical bodies, such as differences in the bodies' inertial masses and gravitational masses. The importance of the new distance formula for causal set theory and other theories of quantum gravity is also discussed.
The Boundaries of KKLT

We consider the conundrum of generating de Sitter space from higher-dimensional geometry, with particular attention to KKLT-type constructions arXiv:hep-th/0301240 and their 5d implications. We show that even in the probe approximation with small $g_s$, a consistent higher-dimensional solution requires a deformation of a modulus field playing the role of a Goldberger-Wise stabilizing field in Randall-Sundrum type geometries that occurs through a shift in a the throat length. We identify the light radion field that sets the length of the throat, whose origin is the dynamical conifold deformation parameter. By analyzing the theory as a 5d model of mismatched branes in AdS5 space with a GW stabilization mechanism, we show how energy (and supersymmetry breaking) is transferred to both the IR and UV regions of the throat to generate a consistent 4d de Sitter sliced geometry. This should help resolve some of the recent apparent paradoxes in explicit higher-dimensional constructions. Moreover, the radion gives insight into the potential for the previously identified ``conifold instability". We argue that this instability would be a destabilization of the potential for the radion in KKLT, which can occur when the perturbation is too large. If indeed $\sqrt{g_s}M$ is too small, the radion would enter on its runaway direction and the conifold deformation would shrink to zero size. It is difficult to satisfy the required bound and a) maintain a hierarchy in the simpler CY manifolds and b) complete the cosmological phase transition into the stabilized throat, We also discuss the implications of this type of setup for supersymmetry breaking, and how multiple throats can introduce hierarchies of supersymmetry breaking masses, even in an anomaly-mediated scenario. In an appendix we consider general compactification constraints.
Detecting circular RNA from high-throughput sequence data with de Bruijn graph.

Circular RNA is a type of non-coding RNA, which has a circular structure. Many circular RNAs are stable and contain exons, but are not translated into proteins. Circular RNA has important functions in gene regulation and plays an important role in some human diseases. Several biological methods, such as RNase R treatment, have been developed to identify circular RNA. Multiple bioinformatics tools have also been developed for circular RNA detection with high-throughput sequence data. In this paper, we present circDBG, a new method for circular RNA detection with de Bruijn graph. We conduct various experiments to evaluate the performance of CircDBG based on both simulated and real data. Our results show that CircDBG finds more reliable circRNA with low bias, has more efficiency in running time, and performs better in balancing accuracy and sensitivity than existing methods. As a byproduct, we also introduce a new method to classify circular RNAs based on reads alignment. Finally, we report a potential chimeric circular RNA that is found by CircDBG based on real sequence data. CircDBG can be downloaded from https://github.com/lxwgcool/CircDBG. We develop a new method called CircDBG for circular RNA detection, which is based on de Bruijn graph. We conduct extensive experiments and demonstrate CircDBG outperforms existing tools, especially in saving running time, reducing bias and improving capability of balancing accuracy and sensitivity. We also introduce a new method to classify circular RNAs and report a potential case of chimeric circular RNA.
Characterizing Multiphoton Excitation Using Time-Resolved X-ray Scattering

Using femtosecond x-ray scattering, experiments reveal the ultrafast and ultrasmall motion of molecular iodine in response to intense laser radiation, showing that femtosecond x rays are a powerful tool for studying laser-matter interactions.
Membrane Proteins Have Distinct Fast Internal Motion and Residual Conformational Entropy.

The internal motions of integral membrane proteins have largely eluded comprehensive experimental characterization. Here the fast side-chain dynamics of the α-helical sensory rhodopsin II and the β-barrel outer membrane protein W have been investigated in lipid bilayers and detergent micelles by solution NMR relaxation techniques. Despite their differing topologies, both proteins have a similar distribution of methyl-bearing side-chain motion that is largely independent of membrane mimetic. The methyl-bearing side chains of both proteins are, on average, more dynamic in the ps-ns timescale than any soluble protein characterized to date. Accordingly, both proteins retain an extraordinary residual conformational entropy in the folded state, which provides a counterbalance to the absence of the hydrophobic effect. Furthermore, the high conformational entropy could greatly influence the thermodynamics underlying membrane-protein functions, including ligand binding, allostery, and signaling.
Mandatory Social Distancing Associated With Increased Doubling Time: An Example Using Hyperlocal Data.

In a hyperlocal analysis of doubling time of COVID-19, we found that a county that implemented mandatory social distancing and other measures to reduce spread of infection saw an earlier increase in doubling time than surrounding counties.
How best to annuitize defined contribution assets

Unlike defined benefit pensions that provide participants with steady benefits for as long as they live, 401(k) plans and Individual Retirement Accounts (IRAs) provide little guidance on how to turn accumulated assets into income. As a result, retirees have to decide how much to withdraw each year and face the risk of either spending too quickly and outliving their resources or spending too conservatively and consuming too little. Surveys of individuals’ plans and several recent studies suggest that people will not draw down their accumulations for fear that they will exhaust their money and be unable to cover end-of-life health care costs. They also must consider how to invest their savings after retirement. These are difficult decisions. Better strategies are possible that will ensure a higher level of lifetime income, reduce the likelihood that people will outlive their resources, and alleviate some of the anxiety associated with post-retirement investing. Workers could use a portion of their 401(k) and IRA assets to purchase an immediate annuity that pays a fixed amount throughout their lives, typically starting at age 65. Or they could purchase an advanced life deferred annuity (ALDA) that requires a smaller share of accumulated assets and begins payments at a later age like 85. Alternatively, they could use their assets to delay claiming Social Security – essentially purchasing an inflation-indexed annuity. Right now, none of these three options is commonly used. Very few workers choose to purchase immediate or deferred annuities (the first two options). And few retirees appear to be deferring claiming in order to receive the maximum annuity income from Social Security – most people simply retire earlier and claim immediately. Increasing annuitization in a meaningful way would require embedding annuities in 401(k) plans, with annuitization as the default. Recent proposed federal legislation, such as the SECURE Act (Setting Every Community Up for Retirement Enhancement), encourages plan sponsors to offer annuities in their plans by establishing a fiduciary safe harbor when specific statutory conditions are followed in selecting an insurance company. This legislation does not address, however, the question of defaults or the possibility of using 401(k) assets to purchase additional Social Security benefits. Moving forward on these fronts would require some consensus about the appropriate share of 401(k) assets to be annuitized and the best method for annuitizing them. To address these issues, this paper compares the level of lifetime utility generated by alternative annuitization approaches – immediate annuities, deferred annuities, and additional Social Security through delayed claiming. The analysis also tests different assumptions for the share of initial wealth that participants use to purchase these products.
Research issues for automatic assembly

ABSTRACT The research issues currently being explored world wide will be discussed. The work falls under two main headings namely, a) parts mating phenomena-quantitative descriptions of what happens when parts interact during the assembly process, the kind of information available, its quality etc. b) programmability-the capability of a machine to be taught a new task rather than being built specifically to do the task. Exploration of the parts mating question requires investigation into geometric, force-friction, and logical test characteristics of the mating process, involving the generation of and the carrying out of very precise experiments to examine hypothesis. Programmability issues include the analysis of manufactured products to determine kinds of tasks, statistics of their occurence and geometric requirements on the placing and alignment of parts; and the general economic modeling and comparison of manual assembly, assembly by special machines and assembly by programmable machines.
S1 heterocyclic thrombin inhibitors

Abstract A series of boropeptides have previously been described by Kettner et al. to be potent thrombin inhibitors. DuP 714 is a representative of this class of compounds with a K i = 0.040 nM, but this inhibitor has undesireable side effects. New and selective boronic acid thrombin inhibitors have been developed by replacing the guanidine of the boroarginine side chain with various heterocycles ranging in size and basicity.
How Crashes Develop: Intradaily Volatility and Crash Evolution

This paper explores whether affine models of volatility jumps estimated on intradaily S&P 500 futures data over 1983-2008 can capture major daily outliers such as the 1987 stock market crash. I find that intradaily jumps in futures prices are typically small, and that self-exciting but short-lived volatility spikes capture intradaily and daily returns better. Multifactor models of the evolution of diffusive variance and jump intensities improve fits substantially. The models capture the conditional distributions of daily returns reasonably well, but have difficulty capturing the evolution of daily realized variance.
YOUTH KICKER’S KNEE: LATERAL DISTAL FEMORAL HEMIPHYSEAL ARREST SECONDARY TO CHRONIC REPETITIVE MICROTRAUMA:

Background:Year-round competitive sports places the youth athlete at risk for injury from chronic repetitive stress. Various conditions have been reported secondary to overuse. Stress injuries to t...