cssi/SciSciGPT-SciSciNet huggingface dataset:
Strong magnetic field limit in a nonlinear Iwatsuka-type model

Abstract We study the strong magnetic field limit for a nonlinear Iwatsuka-type model, i.e. a nonlinear Schrodinger equation in two spatial dimensions with a magnetic vector potential that only depends on the x-coordinate. Using a high-frequency averaging technique, we show that this equation can be effectively described by a nonlocal nonlinear model, which is no longer dispersive. We also prove that, in this asymptotic regime, inhomogeneous nonlinearities are confined along the y-axis.
Handover Experiments with UAVs: Software Radio Tools and Experimental Research Platform

Mobility management is the key feature of cellular networks. When integrating unmanned aerial vehicles (UAVs) into cellular networks, their cell association needs to be carefully managed for coexistence with other cellular users. UAVs move in three dimensions and may traverse several cells on their flight path, and so may be subject to several handovers. In order to enable research on mobility management with UAV users, this paper describes the design, implementation, and testing methodology for handover experiments with aerial users. We leverage software-defined radios (SDRs) and implement a series of tools for preparing the experiment in the laboratory and for taking it outdoors for field testing. We use solely commercial off-the-shelf hardware, open-source software, and an experimental license to enable reproducible and scalable experiments. Our initial outdoor results with two SDR base stations connected to an open-source software core network, implementing the 4G long-term evolution protocol, and one low altitude UAV user equipment demonstrate the handover process.
Fundamental Limits to the Refractive Index of Transparent Optical Materials.

Increasing the refractive index available for optical and nanophotonic systems opens new vistas for design, for applications ranging from broadband metalenses to ultrathin photovoltaics to high-quality-factor resonators. In this work, fundamental limits to the refractive index of any material are derived, given only the underlying electron density and either the maximum allowable dispersion or the minimum bandwidth of interest. In the realm of small to modest dispersion, the bounds are closely approached and not surpassed by a wide range of natural materials, showing that nature has already nearly reached a Pareto frontier for refractive index and dispersion. Conversely, for narrow-bandwidth applications, nature does not provide the highly dispersive, high-index materials that the bounds suggest should be possible. The theory of composites to identify metal-based metamaterials that can exhibit small losses and sizeable increases in refractive index over the current best materials is used. Moreover, if the "elusive lossless metal" can be synthesized, it is shown that it would enable arbitrarily high refractive index in the high-dispersion regime, nearly achieving the bounds even at refractive indices of 100 and beyond at optical frequencies.
The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson’s disease

Astrocytes are essential cells of the central nervous system, characterized by dynamic relationships with neurons that range from functional metabolic interactions and regulation of neuronal firing activities, to the release of neurotrophic and neuroprotective factors. In Parkinson's disease (PD), dopaminergic neurons are progressively lost during the course of the disease, but the effects of PD on astrocytes and astrocyte-to-neuron communication remains largely unknown. This study focuses on the effects of the PD-related mutation LRRK2 G2019S in astrocytes generated from patient-derived induced pluripotent stem cells. We report the alteration of extracellular vesicle (EV) biogenesis in astrocytes, and we identify the abnormal accumulation of key PD-related proteins within multi vesicular bodies (MVBs). We found that dopaminergic neurons internalize astrocyte-secreted EVs and that LRRK2 G2019S EVs are abnormally enriched in neurites and fail to provide full neurotrophic support to dopaminergic neurons. Thus, dysfunctional astrocyte-to-neuron communication via altered EV biological properties may participate in the progression of PD.
A Survey on End-User Robot Programming

As robots interact with a broader range of end-users, end-user robot programming has helped democratize robot programming by empowering end-users who may not have experience in robot programming to customize robots to meet their individual contextual needs. This article surveys work on end-user robot programming, with a focus on end-user program specification. It describes the primary domains, programming phases, and design choices represented by the end-user robot programming literature. The survey concludes by highlighting open directions for further investigation to enhance and widen the reach of end-user robot programming systems.
Resonant self-force effects in extreme-mass-ratio binaries: A scalar model

Extreme-mass-ratio inspirals (EMRIs), compact binaries with small mass-ratios $\ensuremath{\epsilon}\ensuremath{\ll}1$, will be important sources for low-frequency gravitational wave detectors. Almost all EMRIs will evolve through important transient orbital $r\ensuremath{\theta}$ resonances, which will enhance or diminish their gravitational wave flux, thereby affecting the phase evolution of the waveforms at $O({\ensuremath{\epsilon}}^{1/2})$ relative to leading order. While modeling the local gravitational self-force (GSF) during resonances is essential for generating accurate EMRI waveforms, so far the full GSF has not been calculated for an $r\ensuremath{\theta}$-resonant orbit owing to computational demands of the problem. As a first step we employ a simpler model, calculating the scalar self-force (SSF) along $r\ensuremath{\theta}$-resonant geodesics in Kerr spacetime. We demonstrate two ways of calculating the $r\ensuremath{\theta}$-resonant SSF (and likely GSF), with one method leaving the radial and polar motions initially independent as if the geodesic is nonresonant. We illustrate results by calculating the SSF along geodesics defined by three $r\ensuremath{\theta}$-resonant ratios (1\ensuremath{\mathbin:}3, 1:2, 2\ensuremath{\mathbin:}3). We show how the SSF and averaged evolution of the orbital constants vary with the initial phase at which an EMRI enters resonance. We then use our SSF data to test a previously proposed integrability conjecture, which argues that conservative effects vanish at adiabatic order during resonances. We find prominent contributions from the conservative SSF to the secular evolution of the Carter constant $⟨\stackrel{\ifmmode \dot{}\else \textperiodcentered \fi{}}{\mathcal{Q}}⟩$, but these nonvanishing contributions are on the order of, or less than, the estimated uncertainties of our self-force results. The uncertainties come from residual incomplete removal of the singular field in the regularization process. Higher order regularization parameters, once available, will allow definitive tests of the integrability conjecture.
MosaicOS: A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection

Many objects do not appear frequently enough in complex scenes (e.g., certain handbags in living rooms) for training an accurate object detector, but are often found frequently by themselves (e.g., in product images). Yet, these object-centric images are not effectively leveraged for improving object detection in scene-centric images. In this paper, we propose Mosaic of Object-centric images as Scene-centric images (MosaicOS), a simple and novel framework that is surprisingly effective at tackling the challenges of long-tailed object detection. Keys to our approach are three-fold: (i) pseudo scene-centric image construction from object-centric images for mitigating domain differences, (ii) high-quality bounding box imputation using the object-centric images' class labels, and (iii) a multi-stage training procedure. On LVIS object detection (and instance segmentation), MosaicOS leads to a massive 60% (and 23%) relative improvement in average precision for rare object categories. We also show that our framework can be compatibly used with other existing approaches to achieve even further gains. Our pre-trained models are publicly available at this https URL.
Proprotein convertase subtilisin/kexin type 9 links inflammation to vascular endothelial cell dysfunction

Vascular endothelial cell (EC) dysfunction is a pathological mediator of he development, progression, and clinical manifestations of atherosclerotic disease. Inflammation is associated with EC dysfunction, but the responsible mechanisms are not well characterized. There is substantial evidence that serum proprotein convertase subtilisin/kexin type 9 (PCSK9) is increased in pro-inflammatory states and that elevated PCSK9 levels are associated with adverse cardiovascular outcomes after controlling for traditional risk factors, including low-density lipoprotein (LDL) cholesterol. Here we investigate PCSK9 as a novel link between inflammation and vascular EC dysfunction, as assessed by nitric oxide (NO) bioavailability. Tumor necrosis factor alpha (TNF-α), a pro-inflammatory cytokine, increased PCSK9 mRNA expression and PCSK9 protein levels in isolated human aortic ECs, which were accompanied by reduced total and phosphorylated endothelial nitric oxide synthase (eNOS) protein levels and NO bioavailability. Finally, genetic PCSK9 reduction utilizing a PCSK9 specific siRNA in human aortic ECs resulted in the rescue of phosphorylated eNOS protein levels and NO bioavailability. Our results demonstrate that PCSK9 is increased in human aortic ECs exposed to a pro-inflammatory stimulus and that this increase is associated with EC dysfunction. Silencing of TNFα-mediated augmentation of PCSK9 expression utilizing a small interfering RNA against PCSK9 rescued the inflammation-induced EC dysfunction. These results indicate that PCSK9 is a causal link between inflammation and EC dysfunction, a potent driver of atherosclerotic cardiovascular disease.
Brief review of recent advances in understanding dark matter and dark energy

Abstract Dark sector, constituting about 95% of the Universe, remains the subject of numerous studies. There are lots of models dealing with the cause of the effects assigned to “dark matter” and “dark energy”. This brief review is devoted to the very recent theoretical advances in these areas: only to the advances achieved in the last few years. For example, in section devoted to particle dark matter we overview recent publications on sterile neutrinos, self-interacting dark matter, dibarions (hexaquarks), dark matter from primordial “bubbles”, primordial black holes as dark matter, axions escaping from neutron stars, and dark and usual matter interacting via the fifth dimension. We also overview the second flavor of hydrogen atoms: their existence was proven by analyzing atomic experiments and is also evidenced by the latest astrophysical observations of the 21 cm spectral line from the early Universe. While discussing non-particle models of the cause of dark matter effects, we refer to modified Newtonian dynamics and modifications of the strong equivalence principles. We also consider exotic compact objects, primordial black holes, and retardation effects. Finally, we review recent studies on the cause of “dark energy effects”. Specifically, we cover two disputes that arose in 2019 and 2020 on whether the observations of supernovas, previously interpreted as the proof of the existence of dark energy, could have alternative explanations. Besides, we note a study of 2021, where dark energy is substituted by a new hypothetical type of dark matter having a magnetic-type interaction. We also refer to the recent model of a system of nonrelativistic neutral gravitating particles providing an alternative explanation of the entire dynamics of the Universe expansion – without introducing dark energy or new gravitational degrees of freedom.
Mosquito-borne disease and newborn health

While mosquito-borne diseases are currently most prevalent in mid-latitude countries, rising global temperatures could expand their range. This paper investigates whether one such disease, dengue, harms newborns. The empirical design exploits epidemiological patterns of the disease spreading. Dengue infection rates in the mother's municipality of residence which prevailed during the gestation period are instrumented with exogenous factors that determine dengue incidence in municipalities that have tight social connections to the maternal municipality. Using a large longitudinal dataset of Brazilian birth records, I find that a higher dengue rate during the third trimester of gestation has a detrimental effect on birth weight. In utero exposure to dengue also increases the probability of cesarean delivery and can lead to more serious consequences such as increased fetal and maternal mortality rates.
Uniform Complete Observability of Mass and Rotational Inertial Parameters in Adaptive Identification of Rigid-Body Plant Dynamics

This paper addresses the long-standing open problem of observability of mass and inertia plant parameters in the adaptive identification (AID) of second-order nonlinear models of 6 degree-of-freedom rigid-body dynamical systems subject to externally applied forces and moments. Although stable methods for AID of plant parameters for this class of systems, as well numerous approaches to stable model-based direct adaptive trajectory-tracking control of such systems, have been reported, these studies have been unable to prove analytically that the adaptive parameter estimates converge to the true plant parameter values. This paper reports necessary and sufficient conditions for the uniform complete observability (UCO) of 6-DOF plant inertial parameters for a stable adaptive identifier for this class of systems. When the UCO condition is satisfied, the adaptive parameter estimates are shown to converge to the true plant parameter values. To the best of our knowledge this is the first reported proof for this class of systems of UCO of plant parameters and for convergence of adaptive parameter estimates to true parameter values.We also report a numerical simulation study of this AID approach which shows that (a) the UCO condition can be met for fully-actuated plants as well as underactuated plants with the proper choice of control input and (b) convergence of adaptive parameter estimates to the true parameter values. We conjecture that this approach can be extended to include other parameters that appear rigid body plant models including parameters for drag, buoyancy, added mass, bias, and actuators.
Institutional diversity and safe drinking water provision in the United States

Abstract In the United States, community water systems are not only numerous but also diverse. Nonetheless, operational scale and public versus private ownership have dominated the understanding of safe water access, leaving underexplored many other factors related to governance. Applying insights from the Institutional Analysis and Design literature, we create and analyze a dataset of California's water systems classified into 26 structural types associated with distinct governance institutions. We document differences in the number of Safe Drinking Water Act violations among these types and demonstrate their relevance for implementing solutions targeting non-compliance. Advancing equitable access necessitates greater attention to organizational structure and institutional diversity in drinking water provision.
Leveraging technological change to address racial injustice and worker shortages in frontline care delivery

As the seemingly never-ending battle against COVID-19 soldiers on, women and POC (people of colour) constitute the overwhelming majority of troops drawn into battle. They disproportionately staff many of the frontline healthcare delivery jobs most vulnerable to SARS-CoV-2, and now its most virulent mutation, the Delta variant. These jobs include ‘enrolled’ (in the UK) or ‘licensed’ (in the USA) practical nurses (LPNs), certified nursing assistants (CNAs) and in-home carers, all of whom put themselves and their families at great personal risk for the benefit of their patients. Pandemic conditions may be a relatively new development for these workers, but the abhorrent quality of frontline healthcare jobs is not. While ‘job quality’ remains a subjective and elusive construct, we can all imagine a ‘high-quality’ bundle of economic, sociological and psychological attributes—generous or at least sufficient pay and benefits, job security and opportunities for advancement, a modicum of discretion over and interest in one’s work, and perhaps some control over one’s working time.1 2 We might even hope that over time, technological advances including smartphones and robots could somehow encourage an upward drift in the incidence of all of these sought-after ascriptions. But for decades, technology-centred automation has eroded job quality, making it easier for managers to squeeze wages and ignore poor employment conditions. Ironically, COVID-19 provides a rare opportunity. With its lead foot on the gas pedal, it accelerates workplace technological change—all while managers and policymakers sit squarely in the driver’s seat. If these sectoral leaders seize the wheel, they can steer the coach and the economy away from technology-centred automation and toward the path of work-centred technification . In fact, a recent report undertaken in the USA suggests that for all of the misery wrought by COVID-19, it could actually induce leaders—even in that fragmented system—to implement emerging technologies …
On a nonorientable analogue of the Milnor conjecture

The nonorientable 4-genus $\gamma_4(K)$ of a knot $K$ is the smallest first Betti number of any nonorientable surface properly embedded in the 4-ball, and bounding the knot $K$. We study a conjecture proposed by Batson about the value of $\gamma_4$ for torus knots, which can be seen as a nonorientable analogue of Milnor's Conjecture for the orientable 4-genus of torus knots. We prove the conjecture for many infinite families of torus knots, by relying on a lower bound for $\gamma_4$ formulated by Ozsvath, Stipsicz, and Szabo. As a side product we obtain new closed formulas for the signature of torus knots.
Expansion and additional validation of PKA17: A fast real-time and web-based pKa predictor

We have further improved and validated PKA17, our fast software for predicting pKa values of protein residues. The methodology employs coarse-grained lattice-based model of proteins. It was previou...
Do Firms Time Changes in Accounting Estimates to Manage Earnings

We investigate whether firms time their decisions to make changes in accounting estimates (CAEs) in consideration of their earnings benchmarks. Using CAE data from 2006-2018, we find that 28.1 percent of income-increasing CAEs are implemented in quarters where pre-CAE earnings are below a forecasted earnings benchmark but inclusion of the CAE effectively allows the firm to meet the benchmark. We find that income-increasing CAEs are more likely implemented when a firm’s pre-CAE earnings are further below the benchmark. We also find that firms are more likely to implement income-decreasing CAEs under two scenarios: 1) when pre-CAE earnings are relatively high, as a way to either smooth earnings or to “bury bad news,” and 2) when pre-CAE earnings are already low, as a way to take a financial “big bath” and position the firm for positive future earnings. Additionally, we present evidence that firms using CAEs to achieve an earnings benchmark face financial consequences in terms of poorer immediate stock price performance and subsequent return on assets. Our conclusions hold after performing several additional analyses, including consideration of other discretionary options, addressing endogeneity concerns and conducting falsification tests. In sum, we contribute to the earnings management literature by presenting consistent evidence that firms appear to time CAEs to meet earnings benchmarks or achieve other reporting objectives.
Approximation Algorithms for Priority Steiner Tree Problems.

In the Priority Steiner Tree (PST) problem, we are given an undirected graph \(G=(V,E)\) with a source \(s \in V\) and terminals \(T \subseteq V \setminus \{s\}\), where each terminal \(v \in T\) requires a nonnegative priority P(v). The goal is to compute a minimum weight Steiner tree containing edges of varying rates such that the path from s to each terminal v consists of edges of rate greater than or equal to P(v). The PST problem with k priorities admits a \(\min \{2 \ln |T| + 2, k\rho \}\)-approximation [Charikar et al., 2004], and is hard to approximate with ratio \(c \log \log n\) for some constant c [Chuzhoy et al., 2008]. In this paper, we first strengthen the analysis provided by [Charikar et al., 2004] for the \((2 \ln |T| + 2)\)-approximation to show an approximation ratio of \(\lceil \log _2 |T| \rceil + 1 \le 1.443 \ln |T| + 2\), then provide a very simple, parallelizable algorithm which achieves the same approximation ratio. We then consider a more difficult node-weighted version of the PST problem, and provide a \((2 \ln |T|+2)\)-approximation using extensions of the spider decomposition by [Klein & Ravi, 1995]. This is the first result for the PST problem in node-weighted graphs. Moreover, the approximation ratios for all above algorithms are tight.
Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning

Due to the broad range of applications of reinforcement learning (RL), understanding the effects of adversarial attacks against RL model is essential for the safe applications of this model. Prior works on adversarial attacks against RL mainly focus on either observation poisoning attacks or environment poisoning attacks. In this paper, we introduce a new class of attacks named action poisoning attacks, where an adversary can change the action signal selected by the agent. Compared with existing attack models, the attacker's ability in the proposed action poisoning attack model is more restricted, and hence the attack model is more practical. We study the action poisoning attack in both white-box and black-box settings. We introduce an adaptive attack scheme called LCB-H, which works for most RL agents in the black-box setting. We prove that the LCB-H attack can force any efficient RL agent, whose dynamic regret scales sublinearly with the total number of steps taken, to choose actions according to a policy selected by the attacker very frequently, with only sublinear cost. In addition, we apply LCB-H attack against a popular model-free RL algorithm: UCB-H. We show that, even in the black-box setting, by spending only logarithm cost, the proposed LCB-H attack scheme can force the UCB-H agent to choose actions according to the policy selected by the attacker very frequently.
Combining Physics-Based Modeling and Deep Learning for Ultrasound Elastography

Ultrasound elasticity images which enable the visualization of quantitative maps of tissue stiffness can be reconstructed by solving an inverse problem. Classical model-based approaches for ultrasound elastography use deterministic finite element methods (FEMs) to incorporate the governing physical laws resulting in poor performance in noisy conditions. Moreover, these approaches utilize fixed regularizers for various tissue patterns while appropriate data-adaptive priors might be required for capturing the complex spatial elasticity distribution. In this regard, we propose a joint model-based and learning-based framework for estimating the elasticity distribution by solving a regularized optimization problem. We present an integrated objective function composed of a statistical physics-based forward model and a data-driven regularizer to leverage deep neural networks for learning the underlying elasticity prior. This constrained optimization problem is solved using the gradient descent (GD) method and the gradient of regularizer is simply replaced by the residual of the trained denoiser network for having an explicit objective function with reduced computation time.
Multiple Descent: Design Your Own Generalization Curve

This paper explores the generalization loss of linear regression in variably parameterized families of models, both under-parameterized and over-parameterized. We show that the generalization curve can have an arbitrary number of peaks, and moreover, locations of those peaks can be explicitly controlled. Our results highlight the fact that both classical U-shaped generalization curve and the recently observed double descent curve are not intrinsic properties of the model family. Instead, their emergence is due to the interaction between the properties of the data and the inductive biases of learning algorithms.
Dijet impact factor in DIS at next-to-leading order in the Color Glass Condensate

We compute the next-to-leading order impact factor for inclusive dijet production in deeply inelastic electron-nucleus scattering at small xBj. Our computation, performed in the framework of the Color Glass Condensate effective field theory, includes all real and virtual contributions in the gluon shock wave background of all-twist lightlike Wilson line correlators. We demonstrate explicitly that the rapidity evolution of these correlators, to leading logarithmic accuracy, is described by the JIMWLK Hamiltonian. When combined with the next-to-leading order JIMWLK Hamiltonian, our results for the impact factor improve the accuracy of the inclusive dijet cross-section to $$ \mathcal{O} $$ ( $$ {\alpha}_s^2 $$ ln(xf /xBj)), where xf is a rapidity factorization scale. These results are an essential ingredient in assessing the discovery potential of inclusive dijets to uncover the physics of gluon saturation at the Electron-Ion Collider.
Association of Glucagon-like Peptide 1 Analogs and Agonists Administered for Obesity with Weight Loss and Adverse Events: A Systematic Review and Network Meta-analysis

ABSTRACT Background Comparative effectiveness of 7 glucagon-like peptide 1 (GLP-1) agents on weight loss (WL) in obesity remains unknown. Methods We performed a systematic review, network meta-analysis (NMA) utilizing the following data sources: MEDLINE, EMBASE, Scopus, Cochrane Central and clinical trial registries, from inception to March 2, 2021. The prespecified criteria for study inclusion were randomized clinical trials (RCTs) of ≥12 weeks' duration. The data appraisal and extraction were performed by two investigators independently, using the published reports. The main outcomes and statistical methods were weight loss over placebo (WLOP) and adverse events (AEs) among GLP-1 agents using random-effects NMA (frequentist approach); relative ranking using surface under the cumulative ranking (SUCRA) method and certainty of evidence using grading of recommendations, assessment, development and evaluations (GRADE). Findings 64 RCTs (from 2004 to 2021) included 27018 patients (median of age, 55.1 years old; 57.4% women; baseline weight 94.8kg and BMI 33.0kg/m2; trial duration 26 weeks). Direct meta-analysis showed significant WLOP with: -1.44kg (95% CI, -2.14 to -0.74) with dulaglutide ≥1.5 mg; -1.82kg (-2.42 to -1.23) with exenatide immediate release (IR); -2.20kg (-4.31 to -0.08) with exenatide extended release (ER); -3.20kg (-6.53 to 0.15) with efpeglenatide; -2.72kg (-3.35 to -2.09) with liraglutide ≤1.8mg; -4.49kg (-5.26 to -3.72) with liraglutide >1.8mg; -0.62kg (-1.22 to -0.02) with lixisenatide; -4.33kg (-5.71 to -3.00) with semaglutide SQ 1.8mg (SUCRAs 100, 86.1, 82.8 respectively). Highest SUCRAs for discontinuation due to AEs were with taspoglutide and liraglutide >1.8mg. Risk of bias was high or unclear for random sequence generation (29.7%), allocation concealment (26.6%), and incomplete outcome data (26.6%). Heterogeneity (I2 >50%) in WL and AEs reflected magnitude, not direction of effect.
A Rapid in Vitro Assay for Detecting Phorbol Ester-Like Tumor Promoters

We are developing a rapid in vitro assay for detecting compounds with phorbol ester-like tumor promotion activity. This assay is based on the potentiation of the cytotoxic effect of ouabain by phorbol esters such as Tetra-O-decanoyl, 13-phorbol acetate (TPA) and 3-O-tetradecanoy ingenol (3TI). Ouabain is a specific inhibitor of the Na+, K+ -ATPase, a plasma membrane enzyme responsible for the active maintenance of the sodium and potassium gradients across the cell membrane.
Risk of Domestic Violence after Natural Disaster: Teaching Research and Statistics through the Use of a Participatory Action Research Model.

This paper describes the use of a participatory action research model to teach undergraduate social work research and statistics. Strategies of the model include (1) integration with social work education, (2) policy analysis, (3) literature review, (4) collaboration with practitioners, (5) collaboration with the target population through qualitative research, (6) quantitative study, (7) ongoing social action efforts, and (8) evaluation. An example is used of a project addressing a community problem with increased domestic violence during recovery from natural disaster.
Designing appointment system templates with operational performance targets

We investigate characteristics of outpatient appointment templates that provide fair and controlled patient waiting experiences. Using an inverse-simulation application, we establish successive patients’ designated arrival times based on the previous patient’s finish time distribution and a universal targeted wait time set by the provider. This approach results in a template where each patient’s probability of waiting longer than a threshold duration is uniform across all patients. Through investigation of various no-show probabilities and service time distributions, we show that the template designs that achieve wait time uniformity across different patient and service environments have generalizable characteristics. Based on these characteristics, we proceed to design practitioner-oriented heuristics that create rounded interval times for implementation which yield robust performance outcomes. Results suggest that such schedules consist of appointment intervals that differ from average service times, mo...
Allies or Commitment Devices? A Model of Appointments to the Federal Reserve

We present a model of executive-legislative bargaining over appointments to independent central banks in the face of an uncertain economy with strategic economic actors. The model highlights the contrast between two idealized views of Federal Reserve appointments. In one view, all politicians prefer to appoint conservatively biased central bankers to overcome credible commitment problems that arise in monetary policy. In the other, politicians prefer to appoint allies, and appointments are well described by the spatial model used to describe appointments to other agencies. Both ideals are limiting cases of our model, which depend on the level of economic uncertainty. When economic uncertainty is extremely low, politicians prefer very conservative appointments. When economic uncertainty increases, politicians' prefer central bank appointees closer to their own ideal points. In the typical case, the results are somewhere in between: equilibrium appointments move in the direction of politician's preferences but with a moderate conservative bias.
The thermocapillary migration of a droplet with insoluble surfactant: II. General case

Abstract The steady thermocapillary migration of a drop, in the presence of an insoluble surfactant, is treated theoretically under conditions of negligible convective transport of momentum and energy in the bulk phases. Gravitational effects are included for completeness. The objective of the work is the calculation of the migration velocity of the drop as well as surfactant and interfacial velocity distributions on the drop surface. In Part I, the problem was solved analytically in the limit of nondiffusing surfactant, giving rise to a stagnant cap model. In the present article, diffusion of surfactant on the drop surface is permitted. In this case, the theoretical problem is reduced to the solution of a nonlinear ordinary differential equation describing surfactant conservation on the drop surface. However, the solution has to be accomplished using numerical means in general. Asymptotic approximations are obtained for the field variables as well as the migration velocity in the limit of very small and very large surface Peclet numbers. Also, a first-order correction is developed for small values of the elasticity number. The utility of these approximations is established by comparison with the numerical results.
Association of the virD2 protein with the 5' end of T strands in Agrobacterium tumefaciens.

Abstract The soil bacterium Agrobacterium tumefaciens can incite tumors in many dicotyledonous plants by transferring a portion (T-DNA) of its Ti plasmid into susceptible plant cells. The T-DNA is flanked by border sequences that serve as recognition sites for specific cleavage by an endonuclease that comprises two virD-encoded proteins (VirD1 and VirD2). After cleavage, both double-stranded, nicked T-DNA molecules and single-stranded T-DNA molecules (T strands) were present. We have determined that a protein is tightly associated with, and probably covalently attached to, the 5' end of the T strands. Analysis of deletion derivatives in Escherichia coli, immunoprecipitation, and a procedure combining immunoblot and nucleic acid hybridization data identified this protein as the gene product of virD2.
Packaging of high reliability couplers

The increased amount of telephony and computer data traffic over single optical fiber lines and the desire to reduce redundancy to decrease capital cost have led to an increased need for high reliability components both in terrestrial and submarine markets. The authors describe a multiclad coupler process which has been used to develop ultra-high reliability couplers suitable for undersea applications. A new packaging process using a new low expansion composite wrap and LCP housing was required to achieve the optical and mechanical stability required. Extensive thermal and mechanical tests of the couplers and packaging materials predict excellent performance over the planned 27 year lifetime of these components. >
ENCLAVES IN TERRITORIAL WATERS

(1965). ENCLAVES IN TERRITORIAL WATERS. The Professional Geographer: Vol. 17, No. 1, pp. 19-19.
Bcl-2 Regulates Nonapoptotic Signal Transduction: Inhibition of c-Jun N-terminal Kinase (JNK) Activation by IL-1β and Hydrogen Peroxide

Abstract We have explored the role of bcl-2 as a potential modulator of intracellular signal transduction. Stable expression of bcl-2 in fibroblasts inhibited the activation of the c-jun amino terminal kinase (JNK) by the nonapoptotic cytokine interleukin-1β (IL-1β). This effect appeared to be selective for JNK activation as bcl-2 did not appear to alter other aspects of IL-1β signal transduction. Similarly, bcl-2 did not inhibit all activators of JNK as it had no effect on JNK activation by the protein synthesis inhibitor anisomycin. Treatment with nonlethal concentrations of H 2 O 2 , which resulted in the simultaneous stimulation of mitogen-activated protein kinase (MAPK) and JNK, demonstrated that bcl-2 appeared to alter the balance of activation of these two kinase cascades. The pathway by which bcl-2 inhibits JNK activation is demonstrated to be independent of the rac1 GTPase. In contrast, the reduction in JNK activity in cells expressing bcl-2 can be restored by costimulation with a calcium ionophore. This suggests that bcl-2 can regulate certain nonapoptotic signaling pathways. Such results therefore expand the functions of bcl-2 and may have important implication in the understanding of the role of this protein in a variety of human diseases.
Intracellular localization of β-aspartate kinase in spinach (spinacea oleracea)

..beta..-Aspartate kinase is a key regulatory enzyme catalyzing the first step in the aspartate pathway leading to the synthesis of lysine, threonine and methionine. As such, its presence in a particular cellular compartment or organelle would suggest that control of the aspartate pathway resides in that organelle. The present work reports results of initial efforts to demonstrate the presence of ..beta..-aspartate kinase (ATP: L-aspartate 4 phosphotransferase, EC 2.7.2.4) in organelle preparations from spinach leaf tissues.
Maximum-entropy meshfree method for incompressible media problems

A novel maximum-entropy meshfree method that we recently introduced in Ortiz et al. (2010) [1] is extended to Stokes flow in two dimensions and to three-dimensional incompressible linear elasticity. The numerical procedure is aimed to remedy two outstanding issues in meshfree methods: the development of an optimal and stable formulation for incompressible media, and an accurate cell-based numerical integration scheme to compute the weak form integrals. On using the incompressibility constraint of the standard u-p formulation, a u-based formulation is devised by nodally averaging the hydrostatic pressure around the nodes. A modified Gauss quadrature scheme is employed, which results in a correction to the stiffness matrix that alleviates integration errors in meshfree methods, and satisfies the patch test to machine accuracy. The robustness and versatility of the maximum-entropy meshfree method is demonstrated in three-dimensional computations using tetrahedral background meshes for integration. The meshfree formulation delivers optimal rates of convergence in the energy and L^2-norms. Inf-sup tests are presented to demonstrate the stability of the maximum-entropy meshfree formulation for incompressible media problems.
Evaluation of the Effect of Density on Potato Yield and Tuber Size Distribution

Potato (Solanum tuberosum) yield has been optimized for in-row spacings ranging from 15 to 40 cm depending on region, targeted market, variety, and other factors. Production goals require optimizing tuber size to maximize crop value. Our goal was to evaluate the effect of plant, stem, and tuber density on stem and tuber set, potato yield, tuber size distribution, and other quality factors. Research plots were established within a 20-ha commercial production fi eld, and analysis was done with linear and nonlinear regression. Plant density decreased with increasing in-row plant spacing. Stem density increased linearly with increasing plant density, but response differed across years. Tuber density increased to a maximum of 190 tubers m –2 in response to plant and stem density, with stem density more accurately predicting tuber set. Yield was related to plant, stem, and tuber density using nonlinear regression, more accurately predicted by stem and tuber density than by plant density. A hyperbolic model was used to predict yield with estimated maximum yield of 86 Mg ha –1 when related to stem density. Average tuber size was related to stem and tuber density using the inverse yield law and estimated maximum average tuber size of >200 g. The distribution for tuber sizes was estimated as a Weibull probability density function that predicted changes in tuber size in response to stem and tuber density. The hyperbolic model accurately predicted tuber density and yield with the added benefi t that estimated parameters have biological importance, unlike polynomial or other regression models used to predict crop yield. Modeling tuber size distribution over different stem densities provides a mechanism for future economic analysis to optimize management and conduct sensitivity analysis to determine the most important factors infl uencing crop value.
Relationships Between Linear Descriptive Type Traits and Body Measurements

Abstract Holstein cows (297) in five Virginia Institutional Breeding Project herds were evaluated subjectively by a linear scoring system and were measured objectively for related physical components of conformation. Repeatabilities for physical traits ranged from 45% (rear leg angle) to 90% (stature) with most traits exceeding 70%. Subjectively scored linear traits were generally skewed negatively with few cows scored in the lower 40% of scores for rump, side view (slope), rear legs, side view (set), strength of body, and dairy character. Multiple squared correlations for models predicting linear scores of individual cows from their related physical traits ranged from .09 to .68, with a majority between .30 and .50. Correlations for identical models, of means of linear scores and physical traits, ranged from .45 to .97, with most exceeding .70. Regressions indicated relationships between linear scores and physical traits were as expected and, in general, were homogeneous between classifiers. Changes in physical traits per point change in linear scores were small. The linear type evaluation system examined distinguished with reasonable accuracy among cows the differences in their physical components of conformation. However, improvements in the system may be possible by redescribing
Electron-gas theory of ionic crystals, including many-body effects

The electron-gas theory of ionic crystals is extended to include nonadditive (many-body) interactions arising from the simultaneous overlap of the densities of several ions. The theory is used to predict equilibrium geometries, lattice energies, and pressure-induced phase transitions for the fluorides and oxides of the alkali and alkaline earth metals. The results are in good agreement with electron-gas calculations assuming additive, two-body interactions between pairs of ions. This comparison shows that the simultaneous overlap of three or more ions has only a small effect on these crystals, and that for many purposes the simpler two-body approximation is adequate. The predictions of lattice distances and energies agree with experiment to a typical accuracy of 1 or 2%. In order to obtain this accuracy, it is necessary to calculate the electron densities for the anions in a stabilizing potential well whose size is determined self-consistently by the electrostatic potential of the crystal at the anion site. This shrinkage of the anion by the crystal is also a kind of many-body interaction, but it can be handled within the framework of an effective two-body interaction involving the stabilized anions. The corresponding cation expansion effect is also calculated, and shown to be negligible for the alkali and alkaline earth metal ions.
Striking a Balance Between Innovation and Standards: A Study of Teachers Implementing Project-Based Approaches to Teaching Science

This research reports on the efforts of six middle school and high school science teachers in a public school district in New York City to balance innovative teaching methods and strategies with the New York State Learning Standards and Regents requirements. More specifically, this research examines the factors that influenced the implementation of project-based approaches to teaching and learning science. Observations of meetings and classrooms, and collection of artifacts such as curricula, project planners, demographic profiles, student work, and test results served as the primary data sources that were triangulated and related to current theory on project-based learning in science. Four teachers embraced aspects of project-based learning in science and two rejected most aspects of teaching project-based learning in science. Implications for science professional development are discussed.
Low-mass lepton pair production at large transverse momentum

We study the transverse momentum distribution of low-mass lepton pairs produced in hadronic scattering, using the perturbative QCD factorization approach. We argue that the distribution at large transverse momentum, Q{sub T}>>Q, with the pair's invariant mass Q as low as Q{approx}{lambda}{sub QCD}, can be systematically factorized into universal parton-to-lepton pair fragmentation functions, parton distributions, and perturbatively calculable partonic hard parts evaluated at a short-distance scale {approx}O(1/Q{sub T}). We introduce a model for the input lepton pair fragmentation functions at a scale {mu}{sub 0}{approx}1 GeV, which are then evolved perturbatively to scales relevant at the Relativistic Heavy Ion Collider. Using the evolved fragmentation functions, we calculate the transverse momentum distributions in hadron-hadron, hadron-nucleus, and nucleus-nucleus collisions at the Relativistic Heavy Ion Collider. We also discuss the sensitivity of the transverse momentum distribution of low-mass lepton pairs to the gluon distribution.
New Approaches to Prevent LEOPARD Syndrome-associated Cardiac Hypertrophy by Specifically Targeting Shp2-dependent Signaling

In LEOPARD syndrome (LS) patients, mutations in the protein tyrosine phosphatase Shp2 cause hypertrophic cardiomyopathy. The prohypertrophic effects of mutant Shp2 are mediated downstream by hyperactivation of mammalian target of rapamycin. Our goal was to further define the signaling cascade that is essential for the underlying pathomechanism, thus expanding the list of potential future therapeutic targets. Using cultured neonatal rat cardiomyocytes with adenoviral gene delivery and pharmacological inhibitors, we found that hypertrophy induced by a particularly aggressive LS mutation in Shp2 depends on hyperactivation of Akt and focal adhesion kinase as well as mammalian target of rapamycin. Dissecting domain-specific functions of Shp2 using double and truncation mutants, we determined that the hypertrophic effects of mutant Shp2 depend on the two SH2 domains and on an intact catalytic center. The latter finding prompted us to test the efficacy of a Shp2 inhibitor targeted directly at the catalytic pocket. This compound, PHPS1, effectively prevented mutant Shp2-induced hypertrophy. In summary, we identified three novel targets for pharmacological therapy of LS-associated cardiac hypertrophy. Of particular importance is the finding that intervention directly at the mutant Shp2 protein is effective because this would facilitate custom-tailored therapeutic approaches for patients carrying LS mutations in Shp2.
Many players in BCL-2 family affairs.

During apoptotic cell death, cellular stress signals converge at the mitochondria to induce mitochondrial outer-membrane permeabilization (MOMP) through B cell lymphoma-2 (BCL-2) family proteins and their effectors. BCL-2 proteins function through protein–protein interactions, the mechanisms and structural aspects of which are only now being uncovered. Recently, the elucidation of the dynamic features underlying their function has highlighted their structural plasticity and the consequent complex thermodynamic landscape governing their protein–protein interactions. These studies show that canonical interactions involve a conserved, hydrophobic groove, whereas non-canonical interactions function allosterically outside the groove. We review the latest structural advances in understanding the interactions and functions of mammalian BCL-2 family members, and discuss new opportunities to modulate these proteins in health and disease.
Airport Security Screening and Changing Passenger Satisfaction: An Exploratory Assessment

Since September 11, 2001, airport screening procedures in the US have been continuously evolving. For example, the passenger screening process is now trying to strike a balance between security and customer service (i.e. minimizing wait times). This balancing act has important implications not only for passenger safety, but also for the financial stability of an airline industry that is faced with volatile energy prices and sometimes burdensome labor agreements. Using data from 2002 and 2003, we estimate multinomial logit models to uncover factors that determine passenger satisfaction at security screening points. Our findings show that, while wait times at security screening points are significant determinants of passenger satisfaction, many other factors come into play. Moreover, the results show that the determinants of customer satisfaction are not stable over time. This suggests that further refinements in airport screening procedures should give careful consideration to the factors underlying passenger satisfaction, and how these might change over time, rather than focusing exclusively on minimizing wait times at passenger screening points.