cssi/SciSciGPT-SciSciNet huggingface dataset:
Robust Group Synchronization via Cycle-Edge Message Passing

We propose a general framework for solving the group synchronization problem, where we focus on the setting of adversarial or uniform corruption and sufficiently small noise. Specifically, we apply a novel message passing procedure that uses cycle consistency information in order to estimate the corruption levels of group ratios and consequently solve the synchronization problem in our setting. We first explain why the group cycle consistency information is essential for effectively solving group synchronization problems. We then establish exact recovery and linear convergence guarantees for the proposed message passing procedure under a deterministic setting with adversarial corruption. These guarantees hold as long as the ratio of corrupted cycles per edge is bounded by a reasonable constant. We also establish the stability of the proposed procedure to sub-Gaussian noise. We further establish exact recovery with high probability under a common uniform corruption model.
Sick of eating: Eco-evo-immuno dynamics of predators and their trophically acquired parasites.

When predators consume prey, they risk becoming infected with their prey's parasites, which can then establish the predator as a secondary host. A predator population's diet therefore influences what parasites it is exposed to, as has been repeatedly shown in many species such as threespine stickleback (Gasterosteus aculeatus) (more benthic-feeding individuals obtain nematodes from oligocheate prey, whereas limnetic-feeding individuals catch cestodes from copepod prey). These differing parasite encounters, in turn, determine how natural selection acts on the predator's immune system. We might therefore expect that ecoevolutionary dynamics of a predator's diet (as determined by its ecomorphology) should drive correlated evolution of its immune traits. Conversely, the predator's immunity to certain parasites might alter the relative costs and benefits of different prey, driving evolution of its ecomorphology. To evaluate the potential for ecological morphology to drive evolution of immunity, and vice versa, we use a quantitative genetics framework coupled with an ecological model of a predator and two prey species (the diet options). Our analysis reveals fundamental asymmetries in the evolution of ecomorphology and immunity. When ecomorphology rapidly evolves, it determines how immunity evolves, but not vice versa. Weak trade-offs in ecological morphology select for diet generalists despite strong immunological trade-offs, but not vice versa. Only weak immunological trade-offs can explain negative diet-infection correlations across populations. The analysis also reveals that eco-evo-immuno feedbacks destabilize population dynamics when trade-offs are sufficiently weak and heritability is sufficiently high. Collectively, these results highlight the delicate interplay between multivariate trait evolution and the dynamics of ecological communities.
U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina

Fundus photography has routinely been used to document the presence and severity of retinal degenerative diseases such as age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy (DR) in clinical practice, for which the fovea and optic disc (OD) are important retinal landmarks. However, the occurrence of lesions, drusen, and other retinal abnormalities during retinal degeneration severely complicates automatic landmark detection and segmentation. Here we propose HBA-U-Net: a U-Net backbone enriched with hierarchical bottleneck attention. The network consists of a novel bottleneck attention block that combines and refines self-attention, channel attention, and relative-position attention to highlight retinal abnormalities that may be important for fovea and OD segmentation in the degenerated retina. HBA-U-Net achieved state-of-the-art results on fovea detection across datasets and eye conditions (ADAM: Euclidean distance (ED) of 25.4 pixels, REFUGE: 32.5 pixels, IDRiD: 32.1 pixels), on OD segmentation for AMD (ADAM: Dice coefficient (DC) of 0.947), and on OD detection for DR (IDRiD: ED of 20.5 pixels). We further validated the design of our network with an ablation study. Our results suggest that HBA-U-Net may be well suited for landmark detection in the presence of a variety of retinal degenerative diseases.
Self-supervised Learning for Large-scale Item Recommendations

Large scale recommender models find most relevant items from huge catalogs, and they play a critical role in modern search and recommendation systems. To model the input space with large-vocab categorical features, a typical recommender model learns a joint embedding space through neural networks for both queries and items from user feedback data. However, with millions to billions of items in the corpus, users tend to provide feedback for a very small set of them, causing a power-law distribution. This makes the feedback data for long-tail items extremely sparse. Inspired by the recent success in self-supervised representation learning research in both computer vision and natural language understanding, we propose a multi-task self-supervised learning (SSL) framework for large-scale item recommendations. The framework is designed to tackle the label sparsity problem by learning better latent relationship of item features. Specifically, SSL improves item representation learning as well as serving as additional regularization to improve generalization. Furthermore, we propose a novel data augmentation method that utilizes feature correlations within the proposed framework. We evaluate our framework using two real-world datasets with 500M and 1B training examples respectively. Our results demonstrate the effectiveness of SSL regularization and show its superior performance over the state-of-the-art regularization techniques. We also have already launched the proposed techniques to a web-scale commercial app-to-app recommendation system, with significant improvements top-tier business metrics demonstrated in A/B experiments on live traffic. Our online results also verify our hypothesis that our framework indeed improves model performance even more on slices that lack supervision.
Cell Competition between Wild-Type and JAK2V617F Mutant Cells Prevents Disease Relapse after Stem Cell Transplantation in a Murine Model of Myeloproliferative Neoplasm

Disease relapse after allogeneic stem cell transplantation is a major cause of treatment-related morbidity and mortality in patients with myeloproliferative neoplasms (MPNs). The cellular and molecular mechanisms for MPN relapse are not well understood. Here, we established a murine model of MPN relapse, in which ~ 60% of the MPN recipient mice develop disease relapse after receiving stem cell transplantation with wild-type marrow donor. Using this model, we find that impaired wild-type cell function is associated with MPN disease relapse. We also show that competition between wild-type and JAK2V617F mutant cells can modulate the immune cell composition and PD-L1 expression induced by the JAK2V617F oncogene. These results suggest that cell competition between wild-type donor cells and JAK2V617F mutant recipient cells can prevent MPN disease relapse after stem cell transplantation.
Long Short-Term Transformer for Online Action Detection

In this paper, we present Long Short-term TRansformer (LSTR), a new temporal modeling algorithm for online action detection, by employing a long- and short-term memories mechanism that is able to model prolonged sequence data. It consists of an LSTR encoder that is capable of dynamically exploiting coarse-scale historical information from an extensively long time window (e.g., 2048 long-range frames of up to 8 minutes), together with an LSTR decoder that focuses on a short time window (e.g., 32 short-range frames of 8 seconds) to model the fine-scale characterization of the ongoing event. Compared to prior work, LSTR provides an effective and efficient method to model long videos with less heuristic algorithm design. LSTR achieves significantly improved results on standard online action detection benchmarks, THUMOS'14, TVSeries, and HACS Segment, over the existing state-of-the-art approaches. Extensive empirical analysis validates the setup of the long- and short-term memories and the design choices of LSTR.
Machine-Learning Non-Conservative Dynamics for New-Physics Detection

Energy conservation is a basic physics principle, the breakdown of which often implies new physics. This paper presents a method for data-driven ``new physics'' discovery. Specifically, given a trajectory governed by unknown forces, our neural new-physics detector (NNPhD) aims to detect new physics by decomposing the force field into conservative and nonconservative components, which are represented by a Lagrangian neural network (LNN) and an unconstrained neural network, respectively, trained to minimize the force recovery error plus a constant $\ensuremath{\lambda}$ times the magnitude of the predicted nonconservative force. We show that a phase transition occurs at $\ensuremath{\lambda}=1$, universally for arbitrary forces. We demonstrate that NNPhD successfully discovers new physics in toy numerical experiments, rediscovering friction (1493) from a damped double pendulum, Neptune from Uranus' orbit (1846), and gravitational waves (2017) from an inspiraling orbit. We also show how NNPhD coupled with an integrator outperforms both an LNN and an unconstrained neural network for predicting the future of a damped double pendulum.
Credit Assignment Through Broadcasting a Global Error Vector

Backpropagation (BP) uses detailed, unit-specific feedback to train deep neural networks (DNNs) with remarkable success. That biological neural circuits appear to perform credit assignment, but cannot implement BP, implies the existence of other powerful learning algorithms. Here, we explore the extent to which a globally broadcast learning signal, coupled with local weight updates, enables training of DNNs. We present both a learning rule, called global error-vector broadcasting (GEVB), and a class of DNNs, called vectorized nonnegative networks (VNNs), in which this learning rule operates. VNNs have vector-valued units and nonnegative weights past the first layer. The GEVB learning rule generalizes three-factor Hebbian learning, updating each weight by an amount proportional to the inner product of the presynaptic activation and a globally broadcast error vector when the postsynaptic unit is active. We prove that these weight updates are matched in sign to the gradient, enabling accurate credit assignment. Moreover, at initialization, these updates are exactly proportional to the gradient in the limit of infinite network width. GEVB matches the performance of BP in VNNs, and in some cases outperforms direct feedback alignment (DFA) applied in conventional networks. Unlike DFA, GEVB successfully trains convolutional layers. Altogether, our theoretical and empirical results point to a surprisingly powerful role for a global learning signal in training DNNs.
Combined First-Principles Calculations of Electron-Electron and Electron-Phonon Self-Energies in Condensed Systems.

We present a method to efficiently combine the computation of electron-electron and electron-phonon self-energies, which enables the evaluation of electron-phonon coupling at the G0W0 level of theory for systems with hundreds of atoms. In addition, our approach, which is a generalization of a method recently proposed for molecules [J. Chem. Theory Comput.2018, 14, 6269-6275], enables the inclusion of nonadiabatic and temperature effects at no additional computational cost. We present results for diamond and defects in diamond and discuss the importance of numerically accurate G0W0 band structures to obtain robust predictions of zero point renormalization (ZPR) of band gaps, and of the inclusion of nonadiabatic effects to accurately compute the ZPR of defect states in the band gap.
Learning-based Spectrum Sensing and Access in Cognitive Radios via Approximate POMDPs

A novel LEarning-based Spectrum Sensing and Access (LESSA) framework is proposed, wherein a cognitive radio (CR) learns a time-frequency correlation model underlying spectrum occupancy of licensed users (LUs) in a radio ecosystem; concurrently, it devises an approximately optimal spectrum sensing and access policy under sensing constraints. A Baum-Welch algorithm is proposed to learn a parametric Markov transition model of LUs’ spectrum occupancy based on noisy spectrum measurements. Spectrum sensing and access are cast as a Partially-Observable Markov Decision Process, approximately optimized via randomized point-based value iteration. Fragmentation, Hamming-distance state filters and Monte-Carlo methods are proposed to alleviate the inherent computational complexity, and a weighted reward metric to regulate the trade-off between CR’s throughput and interference to the LUs. Numerical evaluations demonstrate that LESSA performs within 5% of a genie-aided upper bound with foreknowledge of LUs’ spectrum occupancy, and outperforms state-of-the-art algorithms across the entire trade-off region: 71% over correlation-based clustering, 26% over Neyman-Pearson-based spectrum sensing, 6% over the Viterbi algorithm, and 9% over adaptive Deep Q-Network. LESSA is then extended to a distributed Multi-Agent setting (MA-LESSA), by proposing novel neighbor discovery and channel access rank allocation. MA-LESSA improves CRs’ throughputs by 43% over cooperative TD-SARSA, 84% over cooperative greedy distributed learning, and 3× over non-cooperative learning via g-statistics and ACKs. Finally, MA-LESSA is implemented on the DARPA SC2 platform, manifesting superior performance over competitors in a real-world TDWR-UNII WLAN emulation; its implementation feasibility is further validated on an ad-hoc distributed wireless testbed of ESP32 radios, exhibiting 96% success probability.
Mental Health and Gun Rights in Virginia: A View from the Battlefield

This article discusses my experiences representing hundreds of patients who have been involuntarily committed to a mental health facility in Virginia — a state where firearms are very much a part of the culture. Because an individual subject to involuntary commitment loses his or her rights to transport, possess, carry, or receive a firearm, I have occasionally been asked by former clients to help them with the restoration of their firearm rights after they have recovered. This article discusses some of the obstacles imposed by state and federal law that may arise during that restoration process. Perplexingly, in Virginia, an individual who signs him/herself in for voluntary admission to a mental health facility is saddled with the same firearms disability as an individual who is involuntarily committed by a court. This article argues that imposing the same firearms disability on an individual who seeks voluntary admission exposes the public to unnecessary harm because some individuals who may be inclined to seek voluntary treatment will forgo doing so if they know they will lose their firearm rights. This article argues that it would be in the best interest of the patient and the community to amend Virginia’s voluntary admission form so that individuals who seek voluntary mental health treatment are not automatically relieved of their firearm rights.
Demo abstract: A multithreaded arduino system for embedded computing

Arduino [1] is an open source platform that offers a clear and simple environment for physical computing. It is now widely used in modern robotics and Internet-of-Things (IoT) applications, due in part to its low-cost, ease of programming, and rapid prototyping capabilities. Sensors and actuators can easily be connected to the analog and digital I/O pins of an Arduino device, which features an on-board microcontroller programmed using the Arduino API.
Effects of lipolytic and antilipolytic substances on adenosine 3',5'-monophosphate levels in isolated fat cells.

Abstract The actions of certain lipolytic and antilipolytic agents were studied in isolated fat cells at the level of cyclic AMP. The following observations were made. Epinephrine (5.5 µm) produced small but significant changes in cyclic AMP levels in 10-min incubations while caffeine (1 mm) was without significant effect. In combination, epinephrine and caffeine acted synergistically, producing large increases in cyclic AMP, indicating that, as in other systems, the catecholamines act to stimulate adenyl cyclase and the methyl xanthines act to inhibit the cyclic nucleotide phosphodiesterase. Other hormones which acted to increase cyclic AMP levels in the presence of 1 mm caffeine included adrenocorticotropic hormone (ACTH), glucagon, thyroid-stimulating hormone, luteinizing hormone, norepinephrine, and the synthetic catecholamine isoproterenol. Increased levels of cyclic AMP were detectable within 30 sec after the addition of epinephrine to fat cells incubated with 1 mm caffeine and were maximal at about 6 min, after which they declined. Supramaximal epinephrine and supramaximal ACTH together did not produce greater stimulation than either agent alone, which suggested that they might act at the same location. Three compounds with antilipolytic activity were tested. Insulin decreased cyclic AMP levels in fat cells exposed to epinephrine, ACTH, or glucagon in the presence of caffeine, while the β-adrenergic blocking agent pronethalol was effective against epinephrine but not ACTH or glucagon under the experimental conditions used. Nicotinic acid decreased cyclic AMP levels in the presence of epinephrine.
Intoxication with 5,5-diphenylhydantoin (Dilantin)

A 4-year-old boy ingested between 1 and 2 Gm. of Dilantin and was hospitalized with marked ataxia, tremor, nystagmus, and hyperreflexia. The highest serum level of Dilantin was 72 μg per milliliter. The signs subsided as the serum level of the drug declined. The time required for the serum level to halve itself declined from 60 hours to 26 hours. At the high level of serum Dilantin concentration the patient had hyperglycemia with relative hypoinsulinemia. The daily excretion of parahydroxydilantin (p-HPPH), the major metabolite of Dilantin, was 115 mg. In addition, a dihydrodiol metabolite has been identified in the urine.
Transcriptional transactivation of parvovirus B19 promoters in nonpermissive human cells by adenovirus type 2.

The pathogenic human parvovirus B19 contains a promoter at map unit 6 (B19p6) of the viral genome, expression from which is largely restricted to human cells in the erythroid lineage, whereas a putative promoter at map unit 44 (B19p44) is inactive during a natural viral infection. Although nonerythroid human cells, such as HeLa and KB, allow expression from the B19p6 promoter but not from the B19p44 promoter following DNA-mediated transfection, little expression from the B19p6 promoter occurs following recombinant virus infection (S. Ponnazhagan, X.-S. Wang, M.J. Woody, F. Luo, L.Y. Kang, M.L. Nallari, N.C. Munshi, S.Z. Zhou, and A. Srivastava, submitted for publication). However, significant expression from the B19p6 promoter as well as the B19p44 promoter could be detected in a human 293 cells line that expresses the adenovirus early gene products, suggesting that coinfection with adenovirus might mediate transcriptional transactivation of the B19 promoters in nonpermissive cells. Expression of the firefly luciferase reporter gene from the B19 promoters was evaluated either following plasmid transfection or following infection with the recombinant adeno-associated virus type 2 vectors. Both B19p6 and B19p44 promoters could be transactivated by coinfection with adenovirus in nonpermissive human cells, although the extent of transactivation of the B19p44 promoter was significantly lower than that of the B19p6 promoter. Expression of the adenovirus E1A proteins was necessary and sufficient for the observed transactivation of the B19 promoters. These studies further illustrate that the underlying molecular mechanisms of transactivation of parvovirus promoters in general by the adenovirus early proteins have similarities with those of the well-documented transactivation of the adeno-associated virus type 2 promoters.
CCR2 MEDIATES CONVENTIONAL DENDRITIC CELL RECRUITMENT AND THE FORMATION OF BRONCHOVASCULAR MONONUCLEAR CELL INFILTRATES IN THE LUNGS OF MICE INFECTED WITH CRYPTOCOCCUS NEOFORMANS

Pulmonary clearance of the encapsulated yeast Cryptococcus neoformans requires the development of T1-type immunity. CCR2-deficient mice infected with C. neoformans develop a non-protective T2 immune response and persistent infection. The mechanisms responsible for this aberrant response are unknown. The objective of this study was to define the number, phenotype, and microanatomic location of dendritic cells (DC) residing within the lung of CCR2 +/+ or CCR2 −/− mice throughout a time course following infection with C. neoformans . Results demonstrate the CCR2-mediated recruitment of conventional DC expressing modest amounts of costimulatory molecules. DC recruitment was preceded by the up-regulation in the lung of the CCR2 ligands CCL2 and CCL7. Colocalization of numerous DC and CD4 + T cells within bronchovascular infiltrates coincided with increased expression of IL-12 and IFN-γ. By contrast, in the absence of CCR2, DC recruitment was markedly impaired, bronchovascular infiltrates were diminished, and mice developed features of T2 responses, including bronchovascular collagen deposition and IL-4 production. Our results demonstrate that CCR2 is required for the recruitment of large numbers of conventional DC to bronchovascular infiltrates in mice mounting a T1 immune response against a fungal pathogen. These findings shed new insight into the mechanism(s) by which DC recruitment alters T cell polarization in response to an infectious challenge within the lung.
High-temperature superconductivity: Research enters a new phase

Copper-oxide superconductors were discovered over a decade ago, but the high value of their superconducting transition temperature,Tc, has remained a mystery. A new tool for measuring the long-range phase coherence — essential for superconductivity — of high-Tcmaterials may provide a route to the answer.
High-Achieving Black Students, Biculturalism, and Out-of-School STEM Learning Experiences: Exploring Some Unintended Consequences.

In this article, the author discusses the complex challenges of high-achieving Black students who are successful in becoming immersed in predominately White STEM (science, technology, engineering, and mathematics) spaces and how such immersion can exacerbate their experiences of racial stereotyping and other forms of racial bias. The author illustrates these complex racialized experiences through the story of Maurice, a high-achieving high school mathematics student who successfully negotiated the White spaces he occupied yet did not indicate interest in pursuing a STEM-related career. Although Maurice developed sophisticated bicultural competencies that allowed STEM professionals and educators to view him positively, he decided that compromising his own racial, cultural, and individual identities to pursue a STEM college major and career was too costly. The discussion in general highlights how racial and ethnic stereotyping which is endemic throughout STEM education and careers can push mathematically competent Black students out of the STEM pipeline prematurely.
Numerical simulation of turbulent drag reduction using micro-bubbles

While turbulent drag reduction through the injection of micro-bubbles into a turbulent boundary layer is well established in experiments, there is a lack of corresponding supporting evidence from direct numerical simulations. Here we report on a series of numerical simulations of small bubbles seeded in a turbulent channel flow at average volume fractions of up to 8%. These results show that even for relatively large bubbles, an initial transient drag reduction can occur as bubbles disperse into the flow. Relatively small spherical bubbles will produce a sustained level of drag reduction over time.
A Simplified Methodology for Extremely Low-Probability Rupture Prediction for PWR LBB Applications

The leak-before-break (LBB) applicability is stated in General Design Criterion 4 (GDC-4) of Title 10 of the Code of Federal Regulation Part 50 (10 CFR 50). GDC-4 requires that analyses reviewed and approved by the U.S. Nuclear Regulatory Commission (NRC) demonstrate that the probability of fluid system piping rupture is extremely low under conditions consistent with the design basis for the piping, in order that dynamic effects associated with postulated pipe ruptures in nuclear power units may be excluded from the design basis. Standard review plan 3.6.3 (SRP-3.6.3) further requires a simultaneous safety margin of two and ten on the flaw size and leak rate detectability, respectively, for deterministic analyses, believing that the very conservative and restrictive safety margins would lead to extremely low probability of fluid system piping rupture. The technology advancements of recent years make it possible to numerically quantify the probability of rupture with confidence. Planned for completion within the next six years, a long-term, large-scale assessment tool, xLPR, is currently being developed by the U.S. NRC, in cooperation with the nuclear industry, to assess the extremely low probability of rupture. The tool will include comprehensive evaluations both before and after through-wall cracks are developed in the degraded components. In this study, we are going to utilize a simplified methodology to investigate the probability of piping rupture for a postulated through-wall crack. The conditional probability, when multiplied by the probability of having a through-wall crack during the life time of plant service, produces an overall probability of piping rupture. The major quantifiable uncertainties, such as the uncertainties associated with the material tensile properties and fracture toughness, and flow-path crack morphology parameters will be modeled as correlated random variables in this paper. Efficient Dimension-Reduction methods will be applied to predict this conditional probability and the results will be compared with the Monte Carlo simulation method. As a sample application of the proposed method, the relationship between the magnitude of the conditional probabilities and the required leak rate detection capability will be established.© 2011 ASME
A precise method for the generation of standard metal salt particulates

Abstract A convenient precise method for producing standard dusts has been developed. Metal-containing particulate samples are generated by aspirating solutions containing metals or interest into an atomizer-burner employing an oxygen-acetylene flame. The particulates thus generated are collected by means of a miniature stack by conventional isokinetic sampling techniques. The particulate samples are deposited on filter tapes and are suitable for calibrating trace analytical methods. Particulate samples containing one or more metals, in any desired ratios of their concentrations, can be generated. Initial studies of particulate sizes indicate that the size range generated is in the respirable range, i.e.. 0.1-5 μm.
The (3He, d) reaction on 24Mg and 28Si at 38.5 MeV

The (3He, d) reaction at a sufficiently high energy is considered to be a reliable single-proton stripping direct reaction. The data for the low-lying states produced by this reaction on 24Mg and 28Si are compared to the predictions of the strong-coupling rotational model. The agreement with the model predictions for 25Al is quite good, both for the single-proton spectroscopic factors in that nucleus and most particularly for the excitation of 72+ states in 25Al and 29P by two-step processes.
Christopher Alexander's pattern language: an alternative exploration of space-making practices

While Christopher Alexander's pattern language has been widely accepted by building contractors and do-it-yourself homeowners, academics have often rejected it for being deterministic and authoritarian. This paper argues for a balanced re-evaluation of Alexander's work, arguing that its importance lies in its recognition that life patterns allow for unconscious cognitive relationships with space that can be discerned and actively improved. When reading A Pattern Language: Towns, Buildings, Construction (1977) and The Timeless Way of Building (1979), it becomes apparent that Alexander's aim is not just to produce diagrammatic patterns, but to provide a broad critique of the alienated modern condition. Alexander calls for a shift in knowledge that would allow for an holistic attitude wherein buildings could be experienced without conscious attention. Herein, I argue, Alexander's philosophical concerns can be more fully understood in the context of recently growing interests in philosophy, the cognitive scie...
Improvements in the likelihood ratio method for steady-state sensitivity analysis and simulation

Abstract The Likelihood Ratio (LR) method is a potentially powerful tool for performance sensitivity analysis of a stochastic system because of its wide applicability. However, the variance of the estimate from LR increases linearly with the length of the segment path, which makes steady-state performance sensitivity estimation difficult. In our previous paper we proposed using segments defined by an embedded regular Markov chain to increase the chance of finding shorting segments. The condition required on the embedded Markov chain is that the equilibrium distribution of the embedded Markov chain is independent of the parameter perturbed, which is very restrictive. In this paper, we develop an asymptotically consistent LR method using the same kind of segments without the restrictive condition. The new LR method is implemented using A -segments which are defined to be the segments between two adjacent visits to a subset of states, A . Since the restrictive condition is removed, the LR method developed in this paper is much more widely applicable, which in practice extends the scope of applications of the LR method.
Isoplanatic patch considerations for solar telescope multi-conjugate adaptive optics

I compare recent site surveys for the future large 4-meter solar and 30-meter nighttime telescopes at the nearby Haleakala and Mauna Kea sites respectively. They show that the outstanding early morning image quality at the solar site corresponds indeed to that observed at the late night one at the nighttime site. That confirms the notion that daytime solar site heating only shows itself later in the morning. The nighttime survey includes observations of the refractive index structure function C n 2 (h) to high altitudes from which the radius of the isoplanatic patch (Ɵ 0 ) can be determined. At zenith (ζ = 0 0 ) it equals 2.5 arcsec at 500 nm wavelength. For the early morning (best) seeing at the solar site, which occurs at ζ sun = 75 0 and the cos 1.6 (ζ) dependence of Θ 0 ,that means an extremely small Ɵ 0 (0.26 arcsec). Such small values compromise Adaptive Optics (AO) solar correlation wavefront sensing for which areas are needed equal to about 8”× 8” I suggest options for measuring C n 2 (h), and therefore Ɵ 0 , during the day. These make use of the solar image as well as of daytime images of bright stars and planets. Some use the MASS technique on stars; some use the SHABAR technique using very large detector baselines on the Sun and shorter baselines on planets. It is suggested that these C n 2 (h) measurements are made also during regular solar observations. In that way optimal solar observations can be planned using real-time Ɵ 0 observations by image selection and optimization of the MCAO configuration.
Implementing conceptual search capability in a cloud-based feed aggregator

Modern society is producing more information at a faster pace than ever before. There is an increasing desire to use this massive amount of collected data to solve real world problems. But given the vast size of the data involved and the resource intensive nature of rapid large-data processing, the need for more advanced methodologies in this regard is increasing. This phenomenon has given rise to the term `Big Data' which references these types of data intensive problems; problems that are typically beyond the ability of traditional tools and methodologies to effectively address. This paper documents the means by which a problem of this type has been addressed using agent-oriented software engineering methodologies and commercial cloud technology. The Feed Analyzer is a conceptual search based Web feed aggregation system deployed to Microsoft's Windows Azure cloud platform. Work of the type documented within this paper will become of greater important as cloud technology is increasingly used to address these types of data intensive problems.
CDF sensitivity analysis technique for ranking influential parameters in the performance assessment of the proposed high-level waste repository at Yucca Mountain, Nevada, USA

Abstract A cumulative distribution function (CDF)-based method has been used to perform sensitivity analysis on a computer model that conducts total system performance assessment of the proposed high-level nuclear waste repository at Yucca Mountain, and to identify the most influential input parameters affecting the output of the model. The performance assessment computer model referred to as the TPA code, was recently developed by the US nuclear regulatory commission (NRC) and the center for nuclear waste regulatory analyses (CNWRA), to evaluate the performance assessments conducted by the US department of energy (DOE) in support of their license application. The model uses a probabilistic framework implemented through Monte Carlo or Latin hypercube sampling (LHS) to permit the propagation of uncertainties associated with model parameters, conceptual models, and future system states. The problem involves more than 246 uncertain parameters (also referred to as random variables) of which the ones that have significant influence on the response or the uncertainty of the response must be identified and ranked. The CDF-based approach identifies and ranks important parameters based on the sensitivity of the response CDF to the input parameter distributions. Based on a reliability sensitivity concept [AIAA Journal 32 (1994) 1717], the response CDF is defined as the integral of the joint probability-density-function of the input parameters, with a domain of integration that is defined by a subset of the samples. The sensitivity analysis does not require explicit knowledge of any specific relationship between the response and the input parameters, and the sensitivity is dependent upon the magnitude of the response. The method allows for calculating sensitivity over a wide range of the response and is not limited to the mean value.
Sulfhydryl groups of cytochrome oxidase.

1. The number ofp-chloromercuribenzoate (PCMB)-reactive sulfhydryl groups per molecule was estimated to be 2 in cytochrome oxidase based on a mininum molecular weight of 69,300 daltons [12] or about 3.2 based on a minimum molecular weight of 110,000 [10]. 2. The number of SH groups titrated in cytochrome oxidase with PCMB or with AgNO3 was the same in the absence of sodium dodecyl sulfate (SDS), while in the presence of SDS additional SH groups became available to AgNO3, but not to PCMB. 3. Removal of most of the intrinsic copper of cytochrome oxidase with ≥0.01 M NaCN (followed by passage through Sephadex G-25 to remove the copper cyanide and the excess cyanide) exposed approximately 1.5 or 2.4 additional SH groups per molecule to PCMB depending on the minimum molecular weight of the enzyme. 4. A determination of the heme of cytochrome oxidase by formation of the pyridine hemochrome revealed the same heme content as was obtained with Δɛ 605 nm (reduced minus oxidized)=7.6×103 cm−1 (g atom Fe)−1. 5. Repeated freezing and thawing or freeze-drying was found to be detrimental to this preparation of cytochrome oxidase. However, the SH groups decreased or became unavailable to PCMB approximately in direct proportion to the decrease in the heme groups.
Abnormal vitamin B6 status is associated with severity of symptoms in patients with rheumatoid arthritis

Abstract Purpose Patients with rheumatoid arthritis have low plasma vitamin B 6 levels and elevated plasma homocysteine responses to a methionine load. We examined whether these abnormalities are associated with clinical and biochemical indicators of disease status. Methods We performed a cross-sectional study in 37 patients who met the American College of Rheumatology criteria for rheumatoid arthritis. Vitamin B 6 status was assessed by the plasma pyridoxal 5′-phosphate level and with the homocysteine response to a methionine load test. Clinical disease activity was assessed by joint counts, the Health Assessment Questionnaire disability score, and biochemical markers of the acute phase response. Results Plasma pyridoxal 5′-phosphate levels were inversely correlated with the erythrocyte sedimentation rate ( r = −0.37, P = 0.02), C-reactive protein level ( r = −0.52, P = 0.002), disability score ( r = −0.37, P = 0.02), morning stiffness ( r = −0.38, P = 0.02), and degree of pain ( r = −0.33, P = 0.04). The increase in homocysteine levels after a methionine load correlated with the erythrocyte sedimentation rate ( r = 0.39, P = 0.02), C-reactive protein level ( r = 0.37, P = 0.03), disability score ( r = 0.37, P = 0.04), degree of pain ( r = 0.38, P = 0.02) and fatigue ( r = 0.42, P = 0.01), number of painful joints ( r = 0.43, P = 0.007), and number of swollen joints ( r = 0.32, P = 0.05). Conclusion Markers of vitamin B 6 status are associated with disease activity and severity, synovial burden, and pain in patients with rheumatoid arthritis, raising the possibility that impaired vitamin B 6 status in these patients is a result of inflammation.
Noninvasive Markers of Oxidative DNA Stress, RNA Degradation and Protein Degradation Are Differentially Correlated With Resting Metabolic Rate and Energy Intake in Children and Adolescents

Urinary excreted RNA and DNA catabolites are used as noninvasive markers for metabolic processes: 8-oxo-2'-deoxyguanosine (8-oxodG) potentially represents oxidative stress to DNA/deoxyribonucleotidetriphosphate pool, modified ribonucleoside pseudouridine (psi) originating mainly from degraded rRNA and tRNA reflects RNA turnover. Modified amino acid gamma-carboxyglutamic acid (Gla) stems from degraded proteins reflecting turnover of proteins. Aim of the present study was to investigate (44 healthy males, 3-18 y) how excretion rates of 8-oxodG, psi, and Gla are related to resting metabolic rate and energy intake. Excretion rates of 8-oxodG (pmol/kg/d), psi (micromol/kg/d), and Gla (micromol/kg/d) were significantly correlated with resting metabolic rate (kJ/kg/d): r = 0.108 (p = 0.029), 0.691 and 0.552 (p < 0.0001), respectively. Excretion rates of 8-oxodG, psi, and Gla were also significantly correlated with energy intake (kJ/kg/d): r = 0.108 (p = 0.036), 0.602 and 0.462 (p < 0.0001). 8-oxodG and Gla excretion was significantly correlated with psi excretion: r = 0.174 (p = 0.005) and 0.709 (p < 0.0001). These results indicate close relationships between whole-body RNA and protein degradation and metabolic rate. The relationship between 8-oxodG excretion and metabolic rate, however, is less strong suggesting that factors other than metabolic rate considerably affect the oxidative stress to DNA.
Ferromagnetic-resonance field shift in an exchange-biased CoO/Ni80Fe20 bilayer

The temperature dependence of the ferromagnetic resonance field shift has been investigated in a CoO/Permalloy bilayer between room temperature and 4 K. The field shift is found to consist of two components: a unidirectional exchange-bias field shift and a uniaxial anisotropic field shift. These field shifts are shown to be equal to the conventional exchange bias and anisotropy fields, provided the rigid spin rotation hypothesis is correct. We have also measured the temperature variation of the exchange bias and the magnetic anisotropy fields from hysteresis loops obtained from SQUID-magnetometry, and found incomplete agreement with the parameters obtained from the ferromagnetic resonance spectra. Analogies with spin-glass phenomena indicate that this incomplete agreement results from the breakdown of the rigid rotation model (or equivalently, the surface anisotropy model) results due to the large rotation angles encountered in a magnetic moment reversal. Notwithstanding, we show that the results of rotating the sample by 180° in the plane of the film yields changes in the resonance field shift which are in agreement with hysteresis loop parameters. A connection between results observed in exchange bias materials and those in spin-glass materials is suggested.
Total least-squares criteria in parameter identification for flight flutter testing

An investigation of parameter identification of time series models for linear dynamic structural systems using the least squares and total least-squares criteria is presented. Excitation and response time-domain data are used to parameterize autoregressive, moving average models. The method, or criteria, which is used to solve a set of overdetermine d, linear algebraic equations developed from the time-domain data affects the solution. A commonly used criteria, least squares, introduces the possibility of significant bias error hi the system parameters and leads to bias errors in the modal parameter estimates when measurement errors are present. An alternative criteria, total least squares, provides an approach that appears to significantly reduce the bias error in the parameter estimates. These methods are applied to a simple, simulated system and then to flight flutter test data with particular emphasis on accurate modal damping estimates. [A] [A'] [4'.>'
Norepinephrine-induced contractions of the rat aorta in the absence of extracellular calcium--II. Effects of calcium antagonists.

Abstract 1. 1. The rat aorta responds biphasically to norepinephrine (NE) in calcium-free medium, with the initial phasic and subsequent tonic components of the contraction being apparently mediated through mobilization of calcium from different intracellular pools. 2. 2. Membrane calcium channel blockers (verapamil, nifedipine, and SKF24260) did not affect the biphasic aortic contractions induced by NE in calcium-free medium, but reduced the response to NE in calcium-containing medium. 3. 3. Intracellular calcium antagonists (tertiary propyl and butyl methylenedioxyindenes) inhibited both phases of the NE-induced aortic contractions in calcium-free medium at concentrations which were similar to those required to inhibit NE-induced contractions in calcium-containing medium. 4. 4. These results support the concept that both components of the biphasic response of the rat aorta to NE are mediated through the mobilization of intracellular calcium when evoked in a calcium-free medium.
Bodies, Texts, and Translators: Indigenous Breast Milk and the Jesuit Exclusion of Mestizos in Late Sixteenth-Century Peru

The present article analyzes the connection between the corporeal reasons Jesuits provide to justify excluding their mestizo translators from the order in late sixteenth century Peru and the publication of the Third Lima Council's standardized translations. I argue the simultaneous Jesuit prohibition of mestizo ordination and the codification of religious translation in the Andes led to the consolidation of a marginalized, but still influential, subject position in colonial Peru occupied by non-European translators. While the hierarchy imposed by certain discriminatory ideologies marginalizes the mestizo “lengua,” a different hierarchy, that of the language specialist, invalidates some key implications of the exclusion.
The seesaw in winter temperatures between Greenland and Northern Europe. Part II: Some oceanic and atmospheric effects in middle and high latitudes

Abstract Description of the seesaw in wintertime climate between Greenland and northern Europe is continued in terms of variations in long waves, frequencies of highs and lows, zonal geostrophic winds, precipitation, sea ice and sea surface temperatures. The monthly variations in four circulation modes are described. Significant spatial correlations exist between the zonal. component of the geostrophic wind in the area of the strongest westerlies in the North Atlantic Ocean and the zonal geostrophic wind elsewhere north of 20°N in winter. Long waves 1 and 2 change substantially from one phase of the seesaw to the other at 63°N. At 45°N only wave 2 changes appreciably between phases. Large, statisticaly significant anomalies occur during and after seesaw winters in the atmosphere-ocean-ice system of the North Atlantic Ocean and its periphery, as well as in the North Pacific Ocean. Anomalies of sea surface temperature which develop during seesaw winters tend to persist through the subsequent spring and summ...
Performance of single and multiple TCP flows over high bandwidth-delay links using error correction and interleaving

This paper investigates the performance of single and multiple TCP connections sharing a bandwidth-delay link. The link employs block-based error correction codes ECC, along with interleaving which is first shown to affect the performance of a single TCP connection. We examine impact of using ECC and interleaving on multiple connections on an ideal two-state fading channel model. Results are obtained by numerical simulation of both single and multiple TCP connections over the channel. Single TCP connection results show that the delay introduced by interleaving significantly affects TCP performance on a lossy channel. Without ECC, the aggregate channel utilization of multiple instances of TCP is higher than that of a single TCP instance. We find that this advantage dissipates when significant ECC is introduced.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Standardized Experimental Testing Procedures for Low-Rise Structures

Abstract This paper reports the progress made, over an eighteen month period, by an ad hoc committee of the Structural Engineers′ Association of Southern California in the development of guidelines to be followed if consistent experimental investigations, representative of the structural performance of mixed material systems under strong seismic excitation, are to be achieved. Aspects covered include the issue of load or deflection control, the rate of load application, the pattern of repetitive load or displacement application, the number of components or systems to be tested and the interpretation of the results.
A median-voter model of economic regulation

A basic median-voter model is developed and extended to analyze issues of economic regulation and public policy outcomes. The model is used to generate comparative static results relating changes in public-policy outcomes to changes in relative group sizes, total population, information costs, and population heterogeneity. The model is also used to explore the issue of optimal group size — the size of the special-interest group that maximizes the group's per capita public policy gains. Comparative static analysis reveals how optimal group size and gains per capita are affected by changes in population heterogeneity, the size of the total population, and relative knowledge levels.
From Laboratory to Scientific Literature The Life and Death of Biomedical Research Results

This study documents the course of submission of a group of biomedical research papers to peer-reviewed journals and characterizes their quality through citation analysis for published papers and t...