cssi/SciSciGPT-SciSciNet huggingface dataset:
Moment analysis of stochastic hybrid systems using semidefinite programming

Abstract This paper proposes a method based on semidefinite programming for estimating moments of stochastic hybrid systems (SHSs). The class of SHSs considered herein consists of a finite number of discrete states and a continuous state whose dynamics as well as the reset maps and transition intensities are polynomial in the continuous state. For these SHSs, the dynamics of moments evolve according to a system of linear ordinary differential equations. However, it is generally not possible to exactly solve the system since time evolution of a specific moment may depend upon moments of order higher than it. Our methodology recasts an SHS with multiple discrete modes to a single-mode SHS with algebraic constraints. We then find lower and upper bounds on a moment of interest via a semidefinite program that includes linear constraints obtained from moment dynamics and those arising from the recasting process, along with semidefinite constraints coming from the non-negativity of moment matrices. We illustrate the methodology via an example of SHS.
Cross-Scale Predictive Dictionaries

Sparse representations using data dictionaries provide an efficient model particularly for signals that do not enjoy alternate analytic sparsifying transformations. However, solving inverse problems with sparsifying dictionaries can be computationally expensive, especially when the dictionary under consideration has a large number of atoms. In this paper, we incorporate additional structure on to dictionary-based sparse representations for visual signals to enable speedups when solving sparse approximation problems. The specific structure that we endow onto sparse models is that of a multi-scale modeling where the sparse representation at each scale is constrained by the sparse representation at coarser scales. We show that this cross-scale predictive model delivers significant speedups, often in the range of $10-60\times $ , with little loss in accuracy for linear inverse problems associated with images, videos, and light fields.
Elastogranularity in binary granular mixtures

Frustration arises for a broad class of physical systems where confinement (geometric) or the presence of a perturbation (kinematic) prevents equilibration to a minimum energy state. By varying the diameter ratio and packing fraction in granular arrays surrounding a slowly elongating elastica, we characterize the resulting elastogranular interactions taking place in a transitional, amorphous medium. For low number density packings prepared with moderate to large bidispersity, we find the critical injected arclength to elicit jamming follows the same scaling law observed in monodisperse arrays. Beyond the jamming point, the elastica is seen to relax its bending energy within packings with progressively larger diameter ratios towards the shape expected when deforming within more fluid-like media.
Finite elements for elliptic problems with wild coefficients

An iterative finite element algorithm is proposed for numerically solving interface problems with strongly discontinuous coefficients. This algorithm employs finite element methods and iteratively solves smaller subproblems with good accuracy, and exchanges information at the interface to advance the iteration until convergence, following the idea of the Schwarz Alternating Method. Numerical experiments are performed to show the accuracy and efficiency of the algorithm for capturing strong discontinuities in the coefficients. They show that the accuracy of our method does not deteriorate and it converges faster as the discontinuity in the coefficients becomes worse. Numerical comparisons are made for coefficient discontinuity jumps in the order of 0, 105, 1010, 1050, and 10100.
Designing Online Courses as a Team: A Team-Based Approach Model

Unlike the traditional “lone ranger” method for online course design—a method that hinges on individual faculty efforts, expertise, and knowledge—a team-based approach (TBA) harnesses the collective intelligence of several experts to design effective online learning experiences. Using learning design (LD) as a conceptual framework, this article describes the experience of a public institution in using a team-based approach to produce a large number of online courses for degree programs. After establishing the relevance of a team-based approach, the author discusses the premises that underpin the model, in terms of process, faculty relationship, and quality assurance. Building on these premises, a cyclical backward design process is described which is intended to (1) clarify course-learning outcomes and align course content, (2) determine acceptable evidence of students' learning, and (3) plan the learning experience. The article is concluded with a few insights and lessons learned from the institutional experience.
TapirXLA: Embedding Fork-Join Parallelism into the XLA Compiler in TensorFlow Using Tapir

This work introduces TapirXLA, a replacement for TensorFlow’s XLA compiler that embeds recursive fork-join parallelism into XLA’s low-level representation of code. Machine-learning applications employ a variety of technologies to improve performance, including compiler technology. But compilers in machine-learning frameworks lack a deep understanding of parallelism, causing them to lose performance by missing optimizations on parallel computation. This work studies how Tapir, a compiler intermediate representation (IR) that embeds parallelism into a mainstream compiler IR, can be incorporated into a compiler for machine learning to remedy this problem. TapirXLA modifies the XLA compiler in TensorFlow to employ the Tapir/LLVM compiler to optimize low-level parallel computation. TapirXLA encodes the parallelism within high-level TensorFlow operations using Tapir’s representation of fork-join parallelism. Furthermore, TapirXLA exposes to the compiler implementations of linear-algebra library routines whose parallel operations are encoded using Tapir’s representation. We compared the performance of TensorFlow using TapirXLA against TensorFlow using an unmodified XLA compiler. On four neural-network benchmarks, TapirXLA speeds up the parallel running time of the network by a geometric-mean multiplicative factor of 30% to 100%, across four CPU architectures.
Between homeomorphism type and Tukey type

Abstract Call a compact space X pin homogeneous if every two points a , b are pin equivalent, meaning that there exists a compact space Y, a quotient map f : Y → X , and a homeomorphism g : Y → Y such that g f − 1 { a } = f − 1 { b } . We will prove a representation theorem for pin equivalence; transitivity of pin equivalence will be a corollary. Pin homogeneity is strictly weaker than homogeneity and pin equivalence is strictly stronger than Tukey equivalence. Just as with topological homogeneity, no infinite compact F-space is pin homogeneous. On the other hand, X × 2 χ ( X ) is pin homogeneous for every compact X. And there is a compact pin homogeneous space with points of different π-character.
Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes

We present new algorithms for computing and approximating bisimulation metrics in Markov Decision Processes (MDPs). Bisimulation metrics are an elegant formalism that capture behavioral equivalence between states and provide strong theoretical guarantees on differences in optimal behaviour. Unfortunately, their computation is expensive and requires a tabular representation of the states, which has thus far rendered them impractical for large problems. In this paper we present a new version of the metric that is tied to a behavior policy in an MDP, along with an analysis of its theoretical properties. We then present two new algorithms for approximating bisimulation metrics in large, deterministic MDPs. The first does so via sampling and is guaranteed to converge to the true metric. The second is a differentiable loss which allows us to learn an approximation even for continuous state MDPs, which prior to this work had not been possible.
Organization design as a competitive choice: an application to the study of innovation

This commentary reflects on how a perspective that concentrates on the role of competitive context and sees organization design as a competitive choice may inform the research stream on the link between organization design and innovation. Focusing on multiunit firms and their formal organization, I discuss the benefits of, and the need for, adopting such an approach for this research stream, in particular, and the study of organization design, in general. I conclude by outlining some implications and directions for future research.
Help me help you: Identifying and addressing barriers to child support compliance

Abstract Many custodial mothers and their children rely on child support to meet basic needs; yet, most do not receive all of the support they are owed. Understanding why some fathers do not meet their formal support obligations is important for the well-being of children in single-parent families. Research about noncustodial fathers’ compliance with formal support obligations has focused predominantly on quantitative analyses of individual, family, and structural factors affecting compliance, with a more limited body of qualitative work exploring noncustodial father perspectives. Generally missing are the perspectives of staff who work with noncustodial parents on overcoming compliance barriers. Staff provide unique and useful insights, given their vantage point from within systems and across fathers. However, staff perspectives alone are inadequate for understanding the full context of noncustodial parent experiences, as noncustodial parents possess a unique view into the child support system as customers. This article contributes to the evidence base on barriers to compliance with formal child support obligations by the sharing perspectives of staff who work with noncustodial fathers struggling to find work and pay child support on overcoming these barriers, and comparing their perspectives to those of noncustodial fathers. Data were gathered through interviews and surveys with child support, employment, and parenting staff conducted for the Child Support Noncustodial Parent Employment Demonstration, and are compared to perspectives of fathers gathered through focus groups for the same evaluation (Vogel, 2020). Results indicate five types of practical, system-based, and experiential factors contributing to noncompliance: (1) an array of barriers to employment; (2) insufficient income to meet obligations; (3) child support system-initiated barriers; (4) resistance to paying support without visitation access; and (5) prior interactions with the child support system. Findings suggest a number of policy changes that could help facilitate compliance among struggling noncustodial fathers, including: access to services to address practical barriers to work; system-level health care, child care, public infrastructure, and criminal justice reforms; administrative and statutory changes within child support to help address high burden orders, enforcement actions that impede employment, and state-owed arrearages; and providing pathways to visitation when safe and appropriate.
Multiplicative and exponential variations of orthomorphisms of cyclic groups

An orthomorphism is a permutation $\sigma$ of $\{1, \dots, n-1\}$ for which $x + \sigma(x) \mod n$ is also a permutation on $\{1, \dots, n-1\}$. Eberhard, Manners, Mrazovic, showed that the number of such orthomorphisms is $(\sqrt{e} + o(1)) \cdot \frac{n!^2}{n^n}$ for odd $n$ and zero otherwise. In this paper we prove two analogs of these results where $x+\sigma(x)$ is replaced by $x \sigma(x)$ (a "multiplicative orthomorphism") or with $x^{\sigma(x)}$ (an "exponential orthomorphism"). Namely, we show that no multiplicative orthomorphisms exist for $n > 2$ but that exponential orthomorphisms exist whenever $n$ is twice a prime $p$ such that $p-1$ is squarefree. In the latter case we then estimate the number of exponential orthomorphisms.
The role of central amygdala corticotropin-releasing factor in predator odor stress-induced avoidance behavior and escalated alcohol drinking in rats.

Abstract Post-traumatic stress disorder (PTSD) is characterized by avoidance of trauma-associated stimuli and amygdala hyperreactivity, and is highly co-morbid with alcohol use disorder (AUD). Our lab uses a predator odor (bobcat urine) stress model that produces conditioned avoidance of an odor-paired context in a subset of rats, mirroring avoidance symptoms that manifest in some but not all humans exposed to trauma. We previously showed that after predator odor stress, Avoiders exhibit escalated operant alcohol self-administration (SA), higher aversion-resistant operant alcohol responding, hyperalgesia, and greater anxiety-like behavior compared to unstressed Controls. We also showed previously that systemic antagonism of corticotropin-releasing factor-1 receptors (CRFR1) reduced escalation of operant alcohol SA in rats not indexed for avoidance, that corticotropin-releasing factor (CRF) infusions into the central amygdala (CeA) produced conditioned place avoidance in stress-naive rats, and that intra-CeA infusion of a CRFR1 antagonist reduced hyperalgesia in Avoiders. Here, we show that avoidance behavior is persistent after repeated predator odor exposure. In addition, Avoiders showed lower weight gain than Controls after predator odor re-exposure. In the brain, higher avoidance was correlated with higher number of c-Fos + cells and CRF immunoreactivity in the CeA. Finally, we show that intra-CeA CRFR1 antagonism reversed post-stress escalation of alcohol SA and reduced avoidance behavior in Avoiders. Collectively, these findings suggest that elucidation of the mechanisms by which CRFR1-gated CeA circuits regulate avoidance behavior and alcohol SA may lead to better understanding of the neural mechanisms underlying co-morbid PTSD and AUD.
The relative importance of biotic and abiotic determinants of temporal occupancy for avian species in North America

Abstract Aim We examined the relative importance of competitor abundance and environmental variables in determining the species distributions of 175 bird species across North America. Unlike previous studies, which tend to model distributions in terms of presence and absence, we take advantage of a geographically extensive dataset of community time series to model the temporal occupancy of species at sites throughout their expected range. Location North America. Time period 2001-2015. Major taxa studied 175 bird species. Methods We calculated variation in temporal occupancy across geographic range and used variance partitioning and Bayesian hierarchical models to evaluate the relative importance of 1) the abundance of potential competitors and 2) the environment (elevation, temperature, precipitation, vegetation index) for determining temporal occupancy. We also created a null model to test whether designated competitor species predicted variation in occupancy better than non-competitor species. Results On average, the environment explained more variance in occupancy than competitor abundance, but this varied by species. For certain species, competitor abundance explained more variance than the environment. Species with larger range sizes, larger range overlap with competitors, and that occurred at higher mean temperatures had a higher proportion of variance explained by the environment than competitor abundance. The abundance of competitor species had a stronger effect on focal species occupancy than non-competitor species in the null model. Main conclusions Temporal occupancy represents a new way of describing species distributions that is complementary to presence/absence or abundance. Geographic variation in temporal occupancy was explained by both biotic and abiotic drivers, and abiotic drivers explained more variation in temporal occupancy than abundance on average. Species traits also play a role in determining whether variation in temporal occupancy is best explained by biotic or abiotic drivers. The results of our study can improve species distribution models, particularly by accounting for competitive interactions.
Tight running time lower bounds for strong inapproximability of maximum k-coverage, unique set cover and related problems (via t-wise agreement testing theorem)

We show, assuming the (randomized) Gap Exponential Time Hypothesis (Gap-ETH), that the following tasks cannot be done in T(k) · No(k)-time for any function T where N denote the input size: • [MATH HERE]-approximation for Max k-Coverage for any constant e > 0, • [MATH HERE]-approximation for k-Median (in general metrics) for any constant e > 0. • [MATH HERE]-approximation for k-Mean (in general metrics) for any constant e > 0. • Any constant factor approximation for k-Unique Set Cover, k-Nearest Codeword Problem and k-Closest Vector Problem. • (1 + Δ)-approximation for k-Minimum Distance Problem and k-Shortest Vector Problem for some Δ > 0. Since all problems considered here can be trivially solved in NO(k) time, our running time lower bounds are tight up to a constant factor in the exponent. In terms of approximation ratios, Max k-Coverage is well-known to admit polynomial-time [MATH HERE]-approximation algorithms, and, recently, it was shown that k-Median and k-Mean are approximable to within factors of [MATH HERE] and [MATH HERE] respectively in FPT time [20]; hence, our inapproximability ratios are also tight for these three problems. For the remaining problems, no non-trivial FPT approximation algorithms are known. The starting point of all our hardness results is the Label Cover problem (with projection constraints). We show that Label Cover cannot be approximated to within any constant factor in T(k) · No(k) time, where N and k denote the size of the input and the number of nodes on the side with the larger alphabet respectively. With this hardness, the above results follow immediately from known reductions. The hardness of Label Cover is in turn shown via a t-wise agreement testing theorem of the following form: given local boolean functions f1,...,fk on domains S1,...,Sk ⊆ [n], if random t functions "weakly agree" with sufficiently large probability, then we can find a global boolean function g : [n] → {0, 1} that "mostly agrees" with "many" of the local functions. We prove such a statement in the regime where S1,...,Sk are "random-looking" sets of size Θ(n/k).
Evidence for a Dichotomy in the Interior Structures of Jupiter and Saturn from Helium Phase Separation

We examine the comparative thermal evolution of Jupiter and Saturn, applying recent theoretical results for helium's immiscibility in fluid metallic hydrogen. The redistribution of helium in their interiors proceeds very differently for the two planets. We confirm that, based on Jupiter's atmospheric helium depletion as observed in situ by the Galileo entry probe, Jupiter's interior helium has differentiated modestly, and we present models reconciling Jupiter's helium depletion, radius, and heat flow at the solar age. Jupiter's recently revised Bond albedo implies a higher intrinsic flux for the planet, accommodating more luminosity from helium differentiation, such that mildly superadiabatic interiors can satisfy all constraints. The same phase diagram applied to the less massive Saturn predicts dramatic helium differentiation, to the degree that Saturn inevitably forms a helium-rich shell or core, an outcome previously proposed by Stevenson & Salpeter and others. The luminosity from Saturn's helium differentiation is sufficient to extend its cooling time to the solar age, even for adiabatic interiors. This model predicts Saturn's atmospheric helium to be depleted to Y = 0.07 ± 0.01, corresponding to a He/H₂ mixing ratio 0.036 ± 0.006. We also show that neon differentiation may have contributed to both planets' luminosity in the past. These results demonstrate that Jupiter and Saturn's thermal evolution can be explained self-consistently with a single physical model, and emphasize that nontrivial helium distributions should be considered in future models for Saturn's internal structure and dynamo.
Domination number of an interval catch digraph family and its use for testing uniformity

We consider a special type of interval catch digraph (ICD) for one-dimensional data in a randomized setting and propose its use for testing uniformity. These ICDs are defined with expansion and cen...
An embedded boundary approach for resolving the contribution of cable subsystems to fully coupled fluid-structure interaction

Cable subsystems characterized by long, slender, and flexible structural elements are featured in numerous engineering systems. In each of them, interaction between an individual cable and the surrounding fluid is inevitable. Such a Fluid-Structure Interaction (FSI) has received little attention in the literature, possibly due to the inherent complexity associated with fluid and structural semi-discretizations of disparate spatial dimensions. This paper proposes an embedded boundary approach for filling this gap, where the dynamics of the cable are captured by a standard finite element representation $\mathcal C$ of its centerline, while its geometry is represented by a discrete surface $\Sigma_h$ that is embedded in the fluid mesh. The proposed approach is built on master-slave kinematics between $\mathcal C$ and $\Sigma_h$, a simple algorithm for computing the motion/deformation of $\Sigma_h$ based on the dynamic state of $\mathcal C$, and an energy-conserving method for transferring to $\mathcal C$ the loads computed on $\Sigma_h$. Its effectiveness is demonstrated for two highly nonlinear applications featuring large deformations and/or motions of a cable subsystem and turbulent flows: an aerial refueling model problem, and a challenging supersonic parachute inflation problem. The proposed approach is verified using numerical data, and validated using real flight data.
A biophysical model of striatal microcircuits suggests gamma and beta oscillations interleaved at delta/theta frequencies mediate periodicity in motor control

Striatal oscillatory activity is associated with movement, reward, and decision-making, and observed in several interacting frequency bands. Local field potential recordings in rodent striatum show dopamine- and reward-dependent transitions between two states: a "spontaneous" state involving β (∼15-30 Hz) and low γ (∼40-60 Hz), and a state involving θ (∼4-8 Hz) and high γ (∼60-100 Hz) in response to dopaminergic agonism and reward. The mechanisms underlying these rhythmic dynamics, their interactions, and their functional consequences are not well understood. In this paper, we propose a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms, as well as their modulation by dopamine. Building on previous modeling and experimental work suggesting that striatal projection neurons (SPNs) are capable of generating β oscillations, we show that networks of striatal fast-spiking interneurons (FSIs) are capable of generating δ/θ (ie, 2 to 6 Hz) and γ rhythms. Under simulated low dopaminergic tone our model FSI network produces low γ band oscillations, while under high dopaminergic tone the FSI network produces high γ band activity nested within a δ/θ oscillation. SPN networks produce β rhythms in both conditions, but under high dopaminergic tone, this β oscillation is interrupted by δ/θ-periodic bursts of γ-frequency FSI inhibition. Thus, in the high dopamine state, packets of FSI γ and SPN β alternate at a δ/θ timescale. In addition to a mechanistic explanation for previously observed rhythmic interactions and transitions, our model suggests a hypothesis as to how the relationship between dopamine and rhythmicity impacts motor function. We hypothesize that high dopamine-induced periodic FSI γ-rhythmic inhibition enables switching between β-rhythmic SPN cell assemblies representing the currently active motor program, and thus that dopamine facilitates movement in part by allowing for rapid, periodic shifts in motor program execution.
Prevalence, Indications, and Outcomes of Stacked Vena Cava Filters.

Guideline indications for Inferior vena cava filter (IVCF) placement primarily include an anticoagulation contraindication. The use of IVCF placement has risen by more than 200% over a decade including the placement of a second IVCF (“stacked IVCFs”). To determine the prevalence, indications
Frequency-Domain Quantum Interference with Correlated Photons from an Integrated Microresonator.

Frequency encoding of quantum information together with fiber and integrated photonic technologies can significantly reduce the complexity and resource requirements for realizing all-photonic quantum networks. The key challenge for such frequency domain processing of single photons is to realize coherent and selective interactions between quantum optical fields of different frequencies over a range of bandwidths. Here, we report frequency-domain Hong-Ou-Mandel interference with spectrally distinct photons generated from a chip-based microresonator. We use four-wave mixing to implement an active ``frequency beam splitter'' and achieve interference visibilities of $0.95\ifmmode\pm\else\textpm\fi{}0.02$. Our work establishes four-wave mixing as a tool for selective high-fidelity two-photon operations in the frequency domain which, combined with integrated single-photon sources, provides a building block for frequency-multiplexed photonic quantum networks.
Matrix Completion with Selective Sampling

Matrix completion is a classical problem in data science wherein one attempts to reconstruct a low-rank matrix while only observing some subset of the entries. Previous authors have phrased this problem as a nuclear norm minimization problem. Almost all previous work assumes no explicit structure of the matrix and uses uniform sampling to decide the observed entries. We suggest methods for selective sampling in the case where we have some knowledge about the structure of the matrix and are allowed to design the observation set.
Rapid fabrication of collagen bundles mimicking tumor-associated collagen architectures

Abstract Stromal collagen is upregulated surrounding a solid tumor and presents as dense, thick, linearized, and aligned bundles. The collagen bundles are continually remodeled during tumor progression, and their orientation with respect to the tumor boundary has been correlated with invasive state. Currently, reconstituted-collagen gels are the standard in vitro tumor cell-extracellular matrix interaction model. The reticular, dense, and isotropic nanofiber (~900 nm-diameter, on average) gels do not, however, recapitulate the in vivo structural features of collagen bundling and alignment. Here, we present a rapid and simple method to fabricate bundles of collagen type I, whose average thickness may be varied between about 4 μm and 9 μm dependent upon diluent temperature and ionic strength. The durability and versatility of the collagen bundles was demonstrated with their incorporation into two in vitro models where the thickness and alignment of the collagen bundles resembled various in vivo arrangements. First, collagen bundles aligned by a microfluidic device elicited cancer cell contact guidance and enhanced their directional migration. Second, the presence of the collagen bundles in a bio-inert agarose hydrogel was shown to provide a route for cancer cell outgrowth. The unique structural features of the collagen bundles advance the physiological relevance of in vitro collagen-based tumor models for accurately capturing tumor cell-extracellular matrix interactions. Statement of significance Collagen in the tumor microenvironment is upregulated and remodeled into dense, thick, and aligned bundles that are associated with invasive state. Current collagen-based in vitro models are based on reticular, isotropic nanofiber gels that do not fully recapitulate in vivo tumor stromal collagen. We present a simple and robust method of rapidly fabricating cell-scale collagen bundles that better mimic the remodeled collagen surrounding a tumor. Interacting with the bundles, cancer cells exhibited drastically different phenotypic behaviors, compared to nanofiber scaffolds. This work reveals the importance of microscale architecture of in vitro tumor models. The collagen bundles provide physiologically relevant collagen morphologies that may be easily incorporated into existing models of tumor cell-extracellular matrix interactions.
The Legal Framework Governing Corporal Punishment

Every state recognizes a limited parental privilege to use corporal punishment. This privilege applies in both criminal cases and civil child-protection proceedings. This short article describes th...
ACETAMINOPHEN ACCUMULATION IN PEDIATRIC PATIENTS AFTER REPEATED THERAPEUTIC DOSES

Acetaminophen is commonly used to control fever but little is known about its kinetics in infants and children after repeated doses. Twenty-one patients (age 0.5-6.4 yrs) with fever received acetaminophen elixir at a dose of 72-90 mg/kg/day given in divided doses as 12-15 mg/kg every 4 hr or 24-30 mg/kg every 8 hr. Multiple blood samples were collected and analyzed by HPLC after the first dose and/or at steady-state (1-3 days of therapy). Maximum acetaminophen serum concentration ranged from 10.2-19.6 μg/ml in patients on every 4 hr schedule and 13.9-40.1 μg/ml in those on every 8 hr schedule. Area under the serum concentration-time curve (AUC) normalized for dose/kg averaged 0.209 (ml/min/kg)−1 and elimination half-life averaged 2.3 hr. In 10 patients, total normalized AUC averaged 0.181 and 0.202 (ml/min/kg)−1 after the first dose and at steady-state, respectively (p<0.05). Five patients showed a 13.2-43 5% increase and one had a 10.4% decrease in AUC; four had <6% change in the AUC. There was no evidence of hepatotoxicity. These data suggest that acetaminophen may accumulate after repeated therapeutic doses in children with fever.
Portfolio Choice with Sustainable Spending: A Model of Reaching for Yield

Abstract We show that reaching for yield—a tendency to take more risk when the real interest rate declines while the risk premium remains constant—results from imposing a sustainable spending constraint on an otherwise standard infinitely lived investor with power utility. When the interest rate is initially low, reaching for yield intensifies. The sustainable spending constraint also affects the response of risk-taking to a change in the risk premium, which can even change sign. In a variant of the model where the sustainable spending constraint is formulated in nominal terms, low inflation also encourages risk-taking.
AimB Is a Small Protein Regulator of Cell Size and MreB Assembly.

Abstract The MreB actin-like cytoskeleton assembles into dynamic polymers that coordinate cell shape in many bacteria. In contrast to most other cytoskeleton systems, few MreB-interacting proteins have been well characterized. Here, we identify a small protein from Caulobacter crescentus, an assembly inhibitor of MreB (AimB). AimB overexpression mimics inhibition of MreB polymerization, leading to increased cell width and MreB delocalization. Furthermore, aimB appears to be essential, and its depletion results in decreased cell width and increased resistance to A22, a small-molecule inhibitor of MreB assembly. Molecular dynamics simulations suggest that AimB binds MreB at its monomer-monomer protofilament interaction cleft and that this interaction is favored for C. crescentus MreB over Escherichia coli MreB because of a closer match in the degree of opening with AimB size, suggesting coevolution of AimB with MreB conformational dynamics in C. crescentus. We support this model through functional analysis of point mutants in both AimB and MreB, photo-cross-linking studies with site-specific unnatural amino acids, and species-specific activity of AimB. Together, our findings are consistent with AimB promoting MreB dynamics by inhibiting monomer-monomer assembly interactions, representing a new mechanism for regulating actin-like polymers and the first identification of a non-toxin MreB assembly inhibitor. Because AimB has only 104 amino acids and small proteins are often poorly characterized, our work suggests the possibility of more bacterial cytoskeletal regulators to be found in this class. Thus, like FtsZ and eukaryotic actin, MreB may have a rich repertoire of regulators to tune its precise assembly and dynamics.
Chapter 1 – Molecular Mechanisms of Cell Death

Cell death is a fundamental pathophysiological process and also an essential event in normal life and development. Although many stimuli cause death of cells, the mode of cell death typically follows one of two patterns. The first is necrosis, or oncosis. Oncotic necrosis is most often the result of profound metabolic disruption and is characterized by cellular swelling leading to plasma membrane rupture with release of intracellular contents. The second pattern is apoptosis, a form of programmed cell death. Apoptosis causes the orderly resorption of individual cells initiated by well-defined pathways involving activation of proteases called caspases. In contrast to necrotic cell death, which typically occurs from adenosine triphosphate (ATP) depletion, apoptosis is an ATP-requiring process. Several distinct organelles (plasma membrane, mitochondrion, nucleus, endoplasmic reticulum, lysosome) give rise to signals that induce cell death. In particular, mitochondrial permeabilization and dysfunction typically develop in both necrosis and apoptosis. In some instances, apoptosis and necrosis share signaling pathways, as occurs in programmed necrosis called necroptosis. In this way, apoptosis and necrosis can represent extreme endpoints on a phenotypic continuum of lost cell viability.
Bank Entry, Competition, and the Market for Corporate Securities Underwriting

This paper examines the competitive e!ects of commercial bank entry into the corporate debt underwriting market, particularly with respect to underwriter spreads, ex-ante yields, and market concentration. We "nd that underwriter spreads and ex-ante yields have declined signi"cantly with bank entry, consistent with the market becoming more competitive. This e!ect is strongest among the lower-rated and smaller debt issues of which banks have underwritten a relatively greater share. The early evidence also indicates that bank entry has tended to decrease market concentration. Overall, our results suggest that bank entry has had a pro-competitive e!ect. ( 1999 Elsevier Science S.A. All rights reserved. JEL classixcation: G21; G24; N22
Revisiting a QoE Assessment Architecture Six Years Later: Lessons Learned and Remaining Challenges

In 2003, we presented an architecture for a streaming video quality assessment system [1]. Six years later, many of the challenges outlined in that paper remain. This paper revisits the 2003 architecture, updates it given what we have learned in our experience thus far with developing the architecture, and discusses in detail the remaining challenges to the realization of this architecture. We conclude with suggestions for moving beyond the biggest challenges, namely cooperation among the interested parties and system scale.
Paid for looks when others are looking: CEO facial traits, compensation, and corporate visibility

Abstract Using both archival data and survey data in which participants rated the facial traits of S&P 500 CEOs, we find that CEOs perceived as more competent or attractive receive a higher salary but not higher non-salary pay, particularly for firms with higher corporate visibility (conceptualized as investor visibility, customer visibility, and media visibility). However, findings also show that the favorable perceptions of CEO facial traits do not predict firm performance. Further testing shows that externally (internally) hired CEOs are paid a salary premium for looking competent (attractive), suggesting that the salary-facial traits relation may depend on how much information is readily available about the CEO candidate’s ability when s/he is hired. Supplemental analyses provide evidence that the CEO salary-facial traits relation varies depending on CEO characteristics and firm board characteristics. Implications for the CEO labor market are discussed.
2 – EQUATIONS AND INEQUALITIES

Publisher Summary A major concern of algebra is the solution of equations. This chapter explores the answers to a few questions related to polynomial equations of the first and second degree. An equation states that two algebraic expressions are equal. The task is to find values of the unknown for which a particular equation holds true. These values are called solutions or roots of the equation, and the set of all solutions is called the solution set. The solutions of an equation depend on the number system being used. Linear inequalities play an important role in solving word problems. A solution of an inequality is a value of the unknown that satisfies the inequality, and the solution set is composed of all solutions. The chapter explains how to solve a linear inequality, that is, an inequality in which the unknown appears only in the first degree.
The Cycle of SEC4 Function in Vesicular Transport

Sec4 is a Ras-like GTP-binding protein required for exocytosis in yeast. Unlike Ras, it is the ability of Sec4 to cycle between the GTP- and GDP-bound forms rather than the absolute levels of the GTP-bound form that is critical for function. This cycle may be coupled to an observed cycle of Sec4 localization within the cell. Sec4 binds to secretory vesicles which then fuse with the plasma membrane in exocytosis. Sec4 can recycle from the plasma membrane through a soluble pool to rebind to a new round of vesicles. We have found an activity in yeast (Saccharomyces cerevisiae) comparable to that of the GDP dissociation inhibitor protein isolated from mammalian cells that releases GDP-bound Sec4 from membranes. DSS4-1, a dominant suppressor of the sec4-8 temperature-sensitive mutation, encodes a nucleotide exchange protein. The cycle of Sec4 may function to allow the assembly and subsequent disassembly of a set of proteins necessary for exocytosis. Candidates for members of this set of proteins are encoded by sec genes which show strong genetic interactions with sec4-8. Two of these (SEC8 and SEC15) encode large proteins which form a complex that is peripherally associated with the plasma membrane.
Bivariate Normal Distribution

The bivariate normal distribution is defined by its density function. The regression function of one variable on the other is given by the linear conditional mean function. The conditional variance is expressed in terms of the correlation coefficient of the variables. References to tables of the bivariate normal distribution are included. Keywords: bivariate normal; regression function; normal and multivariate normal distributions
Chapter 3 – Unconjugated hyperbilirubinaemia

Publisher Summary Unconjugated hyperbilirubinemia is characterized clinically by jaundice without bile in the urine. In unconjugated hyperbilirubinemia, the total serum bilirubin is raised with less than 15% bilirubin reported to be in the direct reacting form. It may be physiological in the newborn. It is frequently caused because of hematological causes. The genetic or familial functional disorders considered in this chapter rarely cause unconjugated hyperbilirubinemia. Very high concentrations of unconjugated bilirubin cause brain damage. The chapter discusses the clinical features and diagnosis of Crigler-Najjar syndrome Type 1 and 2, Gilbert's syndrome, Breast milk jaundice, and control of hyperbilirubinemia. It also describes a syndrome of severe persistent unconjugated hyperbilirubinemia, without hemolysis or evidence of hepatic disease that is usually complicated by the early onset of kemicterus and, frequently, death in the first year of life. With the improved treatment of jaundice in the newborn period patients now survive into adult life but remain at risk of kemicterus. The condition is inherited in an autosomal recessive fashion. Crigler-Najjar Type 2 variant of the Crigler-Najjar syndrome is characterized by a less severe non-hemolytic unconjugated hyperbiliruninemia with a serum bilirubin concentration of between 5 and 20mg/dl which falls by at least 30% when enzyme-inducing agents such as phenobarbitone are given. The disorder is inherited in an autosomal dominant fashion with variable penetrance, however, in some families inheritance may be autosomal recessive.
The Discounted Euler Equation: A Note

We present a simple model with income risk and borrowing constraints that yields a ‘discounted Euler equation’. This feature of the model mutes the extent to which news about far future real interest rates (i.e. forward guidance) affects current outcomes. We show that this simple model approximates the outcomes of a rich model with uninsurable income risk and borrowing constraints in response to a forward guidance shock. The model is simple enough to be easily incorporated into simple New Keynesian models. We illustrate this with an application to the zero lower bound.
A Unique Mouse Model of Early Life Exercise Enables Hippocampal Memory and Synaptic Plasticity.

Physical exercise is a powerful modulator of learning and memory. Mechanisms underlying the cognitive benefits of exercise are well documented in adult rodents. Exercise studies targeting postnatal periods of hippocampal maturation (specifically targeting periods of synaptic reorganization and plasticity) are lacking. We characterize a model of early-life exercise (ELE) in male and female mice designed with the goal of identifying critical periods by which exercise may have a lasting impact on hippocampal memory and synaptic plasticity. Mice freely accessed a running wheel during three postnatal periods: the 4th postnatal week (juvenile ELE, P21-27), 6th postnatal week (adolescent ELE, P35-41), or 4th-6th postnatal weeks (juvenile-adolescent ELE, P21-41). All exercise groups increased their running distances during ELE. When exposed to a subthreshold learning stimulus, juv ELE and juv-adol ELE formed lasting long-term memory for an object location memory task, whereas sedentary and adol ELE mice did not. Electrophysiological experiments revealed enhanced long-term potentiation in hippocampal CA1 in the juvenile-adolescent ELE group. I/O curves were also significantly modulated in all mice that underwent ELE. Our results suggest that early-life exercise, specifically during the 4th postnatal week, can enable hippocampal memory, synaptic plasticity, and alter hippocampal excitability when occurring during postnatal periods of hippocampal maturation.
Planar Graph Perfect Matching Is in NC

Is perfect matching in NC? That is, is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in theoretical computer science for over three decades, ever since the discovery of RNC perfect matching algorithms. Within this question, the case of planar graphs has remained an enigma: On the one hand, counting the number of perfect matchings is far harder than finding one (the former is #P-complete and the latter is in P), and on the other, for planar graphs, counting has long been known to be in NC whereas finding one has resisted a solution. In this article, we give an NC algorithm for finding a perfect matching in a planar graph. Our algorithm uses the above-stated fact about counting perfect matchings in a crucial way. Our main new idea is an NC algorithm for finding a face of the perfect matching polytope at which a set (which could be polynomially large) of conditions, involving constraints of the polytope, are simultaneously satisfied. Several other ideas are also needed, such as finding, in NC, a point in the interior of the minimum-weight face of this polytope and finding a balanced tight odd set.
Mathematics of Nested Districts: The Case of Alaska

In eight states, a “nesting rule” requires that each state Senate district be exactly composed of two adjacent state House districts. In this article, we investigate the potential impacts of these ...
Characterization of Septoria brown spot disease development and yield effects on soybean in Illinois

Brown spot, caused by Septoria glycines Hemmi, is a highly prevalent foliar disease of soybean (Glycine max (L.) Merr.). Despite its wide distribution, the development of Septoria brown spot and it...
The Bargaining and Contagion Effects of Investors in Single Family Residential Properties: The Case of Denver Colorado

We study the bargaining power of investors and the contagion effects of investor-owned single family homes on nearby property values. By controlling for the characteristics of both buyers and sellers, we find that investors tend to have more bargaining power than owner-occupiers — they purchase at lower prices and sell at higher prices, all else equal. We identify two types of investors: Professional Investors (e.g., corporations and partnerships) and Individual Investors. We find differences in the behavior of these two types of investors. For example, Individual Investors tend to invest in homes similar in terms of unobserved quality to those purchased by owner-occupiers. The tendency to buy lower quality homes is primarily attributable to Professional Investors. We also find that Professional Investors have more bargaining power than Individual Investors. For the contagion analysis, we use a repeat sales methodology and find that increasing ownership by investors in a neighborhood is associated with a small positive effect on nearby property values.
Regular Two-Distance Sets

This paper makes a deep study of regular two-distance sets. A set of unit vectors X in Euclidean space $${\mathbb {R}}^n$$ is said to be regular two-distance set if the inner product of any pair of its vectors is either $$\alpha $$ or $$\beta $$, and the number of $$\alpha $$’s (and hence $$\beta $$’s) on each row of the Gram matrix of X is the same. We present various properties of these sets as well as focus on the case where they form tight frames for the underlying space. We then give some constructions of regular two-distance sets, in particular, two-distance frames, both tight and non-tight cases. We also supply an example of a non-tight maximal two-distance frame. Connections among two-distance sets, equiangular lines, and quasi-symmetric designs are also discussed. For instance, we give a sufficient condition for constructing sets of equiangular lines from regular two-distance sets, especially from quasi-symmetric designs satisfying certain conditions.
On the Wasserstein distance between classical sequences and the Lebesgue measure

We discuss the classical problem of measuring the regularity of distribution of sets of $N$ points in $\mathbb{T}^d$. A recent line of investigation is to study the cost ($=$ mass $\times$ distance) necessary to move Dirac measures placed in these points to the uniform distribution. We show that Kronecker sequences satisfy optimal transport distance in $d \geq 3$ dimensions. This shows that for differentiable $f: \mathbb{T}^d \rightarrow \mathbb{R}$ and badly approximable vectors $\alpha \in \mathbb{R}^d$, we have $$ \ | \int_{\mathbb{T}^d} f(x) dx - \frac{1}{N} \sum_{k=1}^{N} f(k \alpha) \ | \leq c_{\alpha} \frac{ \| \nabla f\|^{(d-1)/d}_{L^{\infty}}\| \nabla f\|^{1/d}_{L^{2}} }{N^{1/d}}.$$ We note that the result is uniformly true for a sequence instead of a set. Simultaneously, it refines the classical integration error for Lipschitz functions, $\| \nabla f\|_{L^{\infty}} N^{-1/d}$. We obtain a similar improvement for numerical integration with respect to the regular grid. The main ingredient is an estimate involving Fourier coefficients of a measure; this allows for existing estimates to be conviently `recycled'. We present several open problems.