cssi/SciSciGPT-SciSciNet huggingface dataset:
Reconciling findings on the employment effect of disability insurance

Over the last 25 years, the Social Security Disability Insurance Program (DI) has grown dramatically. During the same period, employment rates for men with work limitations showed substantial declines in both absolute and relative terms. While the timing of these trends suggests that the expansion of DI was a major contributor to employment decline among this group, raising questions about the targeting of disability benefits, studies using denied applicants suggest a more modest role of the DI expansion. To reconcile these findings, we decompose total employment changes into population and employment changes for three categories: DI beneficiaries, denied applicants, and non-applicants. Our results show that during the early 1990s, the growth in DI can fully explain the employment decline for men only under an extreme assumption about the employment potential of beneficiaries. For the period after the mid-1990s, we find little role for the DI program in explaining the continuing employment decline for men with work limitations. I3, J2
Averaging forecasts from VARs with uncertain instabilities

A body of recent work suggests commonly-used VAR models of output, inflation, and interest rates may be prone to instabilities. In the face of such instabilities, a variety of estimation or forecasting methods might be used to improve the accuracy of forecasts from a VAR. These methods include using different approaches to lag selection, different observation windows for estimation, (over-) differencing, intercept correction, stochastically time-varying parameters, break dating, discounted least squares, Bayesian shrinkage, and detrending of inflation and interest rates. Although each individual method could be useful, the uncertainty inherent in any single representation of instability could mean that combining forecasts from the entire range of VAR estimates will further improve forecast accuracy. Focusing on models of U.S. output, prices, and interest rates, this paper examines the effectiveness of combination in improving VAR forecasts made with real-time data. The combinations include simple averages, medians, trimmed means, and a number of weighted combinations, based on: Bates-Granger regressions, factor model estimates, regressions involving just forecast quartiles, Bayesian model averaging, and predictive least squares-based weighting. Our goal is to identify those approaches that, in real time, yield the most accurate forecasts of these variables. We use forecasts from simple univariate time series models and the Survey of Professional Forecasters as benchmarks.
Stator-averaged, rotor blade-to-blade near-wall flow in a multistage axial compressor with tip clearance variation

This paper describes the effect of tip clearance changes on the pressure at the case wall of a second-stage rotor. Wall shear distributions under the rotor tip are also presented. The results show low-pressure areas extending along the rotor suction side but lying away from the blade. Pressure contours indicate the tangential loading at the tip is lower than predicted by two-dimensional calculations; however, the predicted loading is observed between the lowest pressure's path in the passage and the blade pressure side
Weighted Superimposed Codes and Constrained Integer Compressed Sensing

We introduce a new family of codes, termed weighted superimposed codes (WSCs). This family generalizes the class of Euclidean superimposed codes (ESCs), used in multiuser identification systems. WSCs allow for discriminating all bounded, integer-valued linear combinations of real-valued codewords that satisfy prescribed norm and nonnegativity constraints. By design, WSCs are inherently noise tolerant. Therefore, these codes can be seen as special instances of robust compressed sensing schemes. The main results of the paper are lower and upper bounds on the largest achievable code rates of several classes of WSCs. These bounds suggest that, with the codeword and weighting vector constraints at hand, one can improve the code rates achievable by standard compressive sensing techniques.
Range estimation from focus using a non-frontal imaging camera

This paper is concerned with active sensing of range information from focus. It describes a new type of camera whose sensor plane is not perpendicular to the optical axis as is standard. This special imaging geometry eliminates sensor plane movement usually necessary for focusing. Camera panning, required for panoramic viewing anyway, in addition enables focusing and range estimation. Thus panning integrates the two standard mechanical actions of focusing and panning, implying range estimation is done at the speed of panning. An implementation of the proposed Non-frontal Imaging Camera (NICAM) design is described. Experiments on range estimation are also presented.
Making Profits And Providing Care: Comparing Nonprofit, For-Profit, And Government Hospitals

Three types of entities—nonprofit, for-profit, and government—own hospitals. Yet we know neither whether hospital types specialize in different medical services nor how service profitability affects specialization. In this econometric analysis of American Hospital Association data for every U.S. urban, acute care hospital (1988–2000), more than thirty services were categorized as relatively profitable, unprofitable, or variable. For-profits are most likely to offer relatively profitable medical services; government hospitals are most likely to offer relatively unprofitable services; nonprofits often fall in the middle. For-profits are also more responsive to changes in service profitability than the other two types.
Experimental study on a learning control system with bound estimation for underwater robots

Underwater robotic vehicles (URVs) have become an important tool for various underwater tasks because of their greater speed, endurance, depth capability and a lower risk factor than human divers. However, most vehicle control system designs are based on simplified vehicle models and often result in poor vehicle performance due to the nonlinear and time-varying vehicle dynamics having parameter uncertainties. This paper describes a new vehicle control system capable of learning and adapting to changes in the vehicle dynamics and parameters. This control system is compared with a conventional linear control system through extensive wet tests. Results show the learning and adapting capabilities of the presented control system.
Macroeconomic Policy and Elections in OECD Democracies

The purpose of this paper is to test for evidence of opportunistic “political business cycles” in a large sample of 18 OECD economies. Our results can be summarized as follows: 1) We find very little evidence of pre-electoral effects on economic outcomes, in particular, on GDP growth and unemployment; 2) We see some evidence of “political monetary cycles,” that is, expansionary monetary policy in election years; 3) We also observe indications of “political budget cycles,” or “loose” fiscal policy prior to elections; 4) Inflation exhibits a post-electoral jump, which could be explained by either the pre-electoral “loose” monetary and fiscal policies and/or by an opportunistic timing of increases in publicly controlled prices, or indirect taxes.
Formation of the rare-earth peak: Gaining insight into late-time r -process dynamics

We study the formation and final structure of the rare-earth peak ($A\ensuremath{\sim}160$) of the $r$-process nucleosynthesis. Under high-entropy conditions ($Sg100{k}_{B}$), the rare-earth peak forms at late times in the $r$-process after neutron exhaustion (neutron-to-seed ratio $R=1$) as matter decays back to stability. Since rare-earth peak formation does not occur during $(n,\ensuremath{\gamma})\ensuremath{\rightleftarrows}(\ensuremath{\gamma},n)$ equilibrium it is sensitive to the strong interplay between late-time thermodynamic evolution and nuclear physics input. Depending on the conditions, the peak forms either because of the pattern of the neutron capture rates or because of the pattern of the separation energies. We analyze three nuclear data sets under different thermodynamic conditions. We find that the subtleties of each nuclear data set, including separation energies and neutron capture rates, influence not only the final shape of the peak but also when it forms. We identify the range of nuclei which are influential in rare-earth peak formation.
One-step fixed-lag smoothers for Markovian switching systems

Suboptimal approaches to the one-step fixed-lag smoothing problem for Markovian switching systems are examined in this paper. Two algorithms are developed for obtaining one-step fixed-lag smoothed estimates. The first algorithm is an approximation that considers the models over the two most recent sampling periods, while the second one considers only the models over the most recent sampling period. Simulation results are presented to compare the performances of these smoothing algorithms.
Unexpected New Chemistry of the Bis(thioimidazolyl)methanes

The synthesis of the linkage isomers of the bis(thioimidazolyl)methane family of compounds, namely CH2(N-tim)2 (1) and CH2(S-tim)2 (2) (where tim = thio(methyl)imidazolyl) has been reinvestigated in order to optimize the yields, to complete the characterization of these known compounds, and also to ascertain the effect of varying heteroatom binding on their electrochemistry. During the course of these studies, the reactive intermediate ClCH2(S-tim) (3) was isolated and characterized. The chloromethyl derivative 3 readily decomposes on warming to give the ionic compound [CH2(μ-C4H5N2S)2CH2](Cl)2 (4), which was converted to the hexafluorophosphate salt (5) and then was characterized by single-crystal X-ray diffraction. It was also shown that CH2(S-tim)2 (2) could be converted at temperatures greater than 120 °C to CH2(N-tim)2 (1) by a thermal isomerization that proceeds via the remaining possible linkage isomer CH2(S-tim)(N-tim). Electrochemical studies on 1−3 in acetonitrile reveals that each undergoes irr...
When quantum tomography goes wrong: drift of quantum sources and other errors

The principle behind quantum tomography is that a large set of observations—many samples from a 'quorum' of distinct observables—can all be explained satisfactorily as measurements on a single underlying quantum state or process. Unfortunately, this principle may not hold. When it fails, any standard tomographic estimate should be viewed skeptically. Here we propose a simple way to test for this kind of failure using the Akaike information criterion. We point out that the application of this criterion in a quantum context, while still powerful, is not as straightforward as it is in classical physics. This is especially the case when future observables differ from those constituting the quorum.
Dorsal Striatal Size, Shape, and Metabolic Rate in Never-Medicated and Previously Medicated Schizophrenics Performing a Verbal Learning Task

Background Magnetic resonance imaging and positron emission tomography were used to study the size and metabolic rate of the caudate and the putamen in 18 patients with schizophrenia (n=16) or schizo-affective disorder (n=2) and 24 age- and sex-matched control subjects. Methods The patients were either never medicated (n=7) or drug free (n=11) for a median of 3 weeks. During uptake of fludeoxyglucose F 18, all patients performed a serial verbal learning test. Positron emission tomographic and magnetic resonance imaging scans were coregistered, and the caudate and the putamen were traced on the magnetic resonance image. Results The striatum had a significantly lower relative metabolic rate in schizophrenics than in controls. Never-medicated patients had lower metabolic rates in the right putamen (ventral part of the dorsal striatum) than previously medicated patients. The caudate was significantly smaller in never-medicated patients than in controls and largest in previously medicated patients. Patients with higher relative metabolic rates in the putamen scored higher on the Abnormal Involuntary Movements Scale. Conclusions The findings are consistent with reports of striatal enlargement in previously medicated patients and size increases after neuroleptic treatment. Never-medicated patients, in contrast, had ventral striatal structures that were smaller and less active than those observed in controls and previously medicated patients.
ADD/ADHD and impaired executive function in clinical practice

The disorder currently known as attention-deficit disorder (ADD) or attention-deficit/hyperactivity disorder (ADHD) is now recognized by most clinicians as a legitimate and widely prevalent disorder among children and adults. Yet there is still widespread misunderstanding as to the disorder’s nature. Many clinicians mistakenly continue to think of this as a behavior disorder characterized by hyperactivity in children and excessive restlessness or impulsivity in adults. In fact, ADD/ADHD is essentially a cognitive disorder, a developmental impairment of executive functions (EFs), the self-management system of the brain. Although EFs are complex, their impairment constitutes a syndrome that can be recognized readily in clinical practice; impaired EF involves a pattern of chronic difficulties in executing a wide variety of daily tasks. Once recognized, this disorder can be effectively treated in most cases. In this article, I describe the nature of EF impairments in ADD/ADHD and how the syndrome can be recognized and effectively treated in clinical practice. (Note: The term ADHD is used in the balance of this article to refer to both inattentive and combined subtypes.)
Batch Active Learning via Coordinated Matching

We propose a novel batch active learning method that leverages the availability of high-quality and efficient sequential active-learning policies by approximating their behavior when applied for k steps. Specifically, our algorithm uses Monte-Carlo simulation to estimate the distribution of unlabeled examples selected by a sequential policy over k steps. The algorithm then selects k examples that best matches this distribution, leading to a combinatorial optimization problem that we term "bounded coordinated matching". While we show this problem is NP-hard, we give an efficient greedy solution, which inherits approximation bounds from supermodular minimization theory. Experiments on eight benchmark datasets show that the proposed approach is highly effective.
Determination of synthetic musk compounds in sewage biosolids by gas chromatography/mass spectrometry

A review of sewage sludge regulations and land application practices by the United States National Research Council (2002) recommended development of improved analytical techniques to adequately identify and quantify new chemical contaminants, such as synthetic musk compounds in Class A sewage sludge (i.e., biosolids). This prompted the development of a rugged analytical method using gas chromatography coupled to mass spectrometry to detect this group of organic pollutants in biosolids. In this paper, the term "biosolids" is used interchangeably with "sewage sludge", which is defined in the regulations and used in the statue (Clean Water Act). Samples of Class A biosolids obtained from sewage treatment plants in Los Angeles, California, the City of Las Vegas, Nevada, and also in the form of a commercial fertilizer, were extracted using pressurized liquid extraction technique, subjected to gel permeation chromatography clean-up, and analyzed by GC/MS using the selected ion monitoring mode. The method developed has the potential to detect synthetic musk compounds in complex matrices, may provide accurate data useful in human health and environmental risk assessment, and may be useful in determining the efficacy of municipal sewage treatment plants for removing synthetic musk compounds.
An Introduction to Ensemble Methods for Data Analysis

This paper provides an introduction to ensemble statistical procedures as a special case of algorithmic methods. The discussion beings with classification and regression trees (CART) as a didactic device to introduce many of the key issues. Following the material on CART is a consideration of cross-validation, bagging, random forests and boosting. Major points are illustrated with analyses of real data.
The Polarizing Effect of Arousal on Negotiation

In this research, we examined the impact of physiological arousal on negotiation outcomes. Conventional wisdom and the prescriptive literature suggest that arousal should be minimized given its negative effect on negotiations, whereas prior research on misattribution of arousal suggests that arousal might polarize outcomes, either negatively or positively. In two experiments, we manipulated arousal and measured its effect on subjective and objective negotiation outcomes. Our results support the polarization effect. When participants had negative prior attitudes toward negotiation, arousal had a detrimental effect on outcomes, whereas when participants had positive prior attitudes toward negotiation, arousal had a beneficial effect on outcomes. These effects occurred because of the construal of arousal as negative or positive affect, respectively. Our findings have important implications not only for negotiation, but also for research on misattribution of arousal, which previously has focused on the target of evaluation, in contrast to the current research, which focused on the critical role of the perceiver.
A New Reaction Manifold for the Barton Radical Intermediates: Synthesis of N-Heterocyclic Furanosides and Pyranosides via the Formation of the C1−C2 Bond

The first radical intermediate in the thiourethane-mediated deoxygenation of an alcohol (Barton−McCombie reaction) can participate in an exo-hex-5-enyl- or exo-hept-6-enyl-type radical cyclization when a suitable radical acceptor (e.g., α,β-unsaturated ester, oxime ether, or hydrazone) is appropriately placed. Carbohydrate-derived imidazolyl and triazolyl thiourethanes with such acceptors, upon addition to excess of a good hydride donor (reverse addition), undergo efficient cyclization reactions to give N-heterocyclic furanosides, and, surprisingly even N-pyranosides. Depending on the acceptor, glycosides with either a C2-amino or a C2-carbon substituent are formed.
Investigating the robustness of adaptive Dynamic Loop Scheduling on heterogeneous computing systems

Dynamic Loop Scheduling (DLS) algorithms are a powerful approach towards improving the performance of scientific applications via load balancing. The adaptive DLS (ADLS) methods have been proven to be the most appropriate for effectively balancing such applications, due to the fact that they are designed to address highly irregular, stochastic behavior caused by algorithmic and systemic variations. To guarantee certain performance levels of such DLS methods, metrics are required to measure their robustness against various unpredictable variations of factors in the computing environment. In this paper, the focus is on investigating metrics for the robustness of two Adaptive Weighted Factoring (AWF) techniques, AWFB and AWF-C, as well as of the Adaptive Factoring (AF) technique. Two robustness metrics, called flexibility and resilience, are formulated for these techniques. We also discuss their computational complexity and give notes on their usefulness.
Alcohol: Anthropological/Archaeological Perspectives

AbstractAlcohol is a special form of embodied material culture and the most widely used psychoactive agent in the world. It has been a fundamentally important social, economic, political, and religious artifact for millennia. This review assesses trends in the anthropological engagement with alcohol during the past two decades since the Annual Review last covered this subject. It highlights the growing archaeological contributions to the field, as well as recent developments by sociocultural anthropologists and social historians. Increasing historicization has been a useful corrective to the earlier functionalist emphasis on the socially integrative role of drinking. Recent studies tend to employ a more strategic/agentive analytical framework and treat drinking through the lens of practice, politics, and gender. Moreover, alcohol has come to be seen as an important component of the political economy and a commodity centrally implicated in strategies of colonialism and postcolonial struggles over state pow...
Multiple hypothesis target tracking using merge and split of graph’s nodes

In this paper, we propose a maximum a posteriori formulation to the multiple target tracking problem. We adopt a graph representation for storing the detected regions as well as their association over time. The multiple target tracking problem is formulated as a multiple paths search in the graph. Due to the noisy foreground segmentation, an object may be represented by several foreground regions and one foreground region may corresponds to multiple objects. We introduce merge, split and mean shift operations that add new hypothesis to the measurement graph in order to be able to aggregate, split detected blobs or re-acquire objects that have not been detected during stop-and-go-motion. To make full use of the visual observations, we consider both motion and appearance likelihood. Experiments have been conducted on both indoor and outdoor data sets, and a comparison has been carried to assess the contribution of the new tracker.
Characterizing Land–Atmosphere Coupling and the Implications for Subsurface Thermodynamics

Abstract The objective of this work is to develop a Simple Land-Interface Model (SLIM) that captures the seasonal and interannual behavior of land–atmosphere coupling, as well as the subsequent subsurface temperature evolution. The model employs the one-dimensional thermal diffusion equation driven by a surface flux boundary condition. While the underlying physics is straightforward, the SLIM framework allows a qualitative understanding of the first-order controls that govern the seasonal coupling between the land and atmosphere by implicitly representing the dominant processes at the land surface. The model is used to perform a suite of experiments that demonstrate how changes in surface air temperature and coupling conditions control subsurface temperature evolution. The work presented here suggests that a collective approach employing both complex and simple models, when joined with analyses of observational data, has the potential to increase understanding of land–atmosphere coupling and the subsequen...
Global stability of internet congestion controllers with heterogeneous delays

In this paper, we study the problem of designing globally stable, scalable congestion control algorithms for the Internet. Prior work has primarily used linear stability as the criterion for such a design. Global stability has been studied only for single node, single source problems. Here, we obtain conditions for a general topology network accessed by sources with heterogeneous delays. We obtain a sufficient condition for global stability in terms of the increase/decrease parameters of the congestion control algorithm and the price functions used at the links.
Silicon Mediated Alkylations in the 9,10-Dihydroanthracene System: a Convenient Synthesis of 9,9-Dialkyl-9,10- Dihydroanthracenes.

Abstract A trimethylsilyl (TMS) substituent is used to control the regiochemistry of alkylation in 9,10-dihydroanthracene (9,10-DHA) furnishing 9,9-dialkyl-10-TMS-9,10-DHAs. The TMS group is subsequently removed resulting in the first convenient synthesis of a variety of 9,9-dialkyl-9,10-DHAs in good to excellent yields.
Human activity detection from RGBD images

Being able to detect and recognize human activities is important for making personal assistant robots useful in performing assistive tasks. The challenge is to develop a system that is low-cost, reliable in unstructured home settings, and also straightforward to use. In this paper, we use a RGBD sensor (Microsoft Kinect) as the input sensor, and present learning algorithms to infer the activities. Our algorithm is based on a hierarchical maximum entropy Markov model (MEMM). It considers a person's activity as composed of a set of sub-activities, and infers the two-layered graph structure using a dynamic programming approach. We test our algorithm on detecting and recognizing twelve different activities performed by four people in different environments, such as a kitchen, a living room, an office, etc., and achieve an average performance of 84.3% when the person was seen before in the training set (and 64.2% when the person was not seen before).
GENERALIZED DUALITY AND SINGULAR STRINGS IN HIGHER DIMENSIONS

Deformations of gauged WZW actions are constructed for any pair $(G,H)$ by taking different embeddings of the gauge group $H\subset G$ as it acts on the left and right of the group element $g$. This leads to models that are dual to each other, generalizing the axial/vector duality of the two dimensional black hole manifold. The classical equations are completely solved for any pair $(G,H)$ and in particular for the anti de Sitter string based on $SO(d- 1,2)/SO(d-1,1)$ for which the normal modes are determined. Duality is demonstrated for models that have the same set of normal modes. Concentrating on $SO(2,2)/SO(2,1)$, the metric and dilaton fields of the $d=3$ string as well as some of the dual generalizations are obtained. They have curvature singularities and represent new singular solutions of Einstein's general relativity in three dimensions.
The Environment as a Factor of Production

The authors develop a model of environmental resource use in production with an empirical analysis of how electric power companies consume and bank sulfur dioxide pollution permits. The model considers emissions, fuels, and labor as variable inputs with quasi-fixed inputs of permits and capital. Incorporating information from permit markets allows the authors to distinguish between user costs and asset shadow values. Their findings indicate that firms are holding stocks of pollution permits for reasons other than short-term cost savings. The results also reveal substantial substitution possibilities between emissions, permits stocks, and other factors of production. The authors speculate that anticipated secondary markets for carbon-offset inventories related to the flexibility mechanisms of the Kyoto Protocol will have similar effects for greenhouse-gas emitting firms.
Optimal control of mixing in Stokes fluid flows

Motivated by the problem of microfluidic mixing, optimal control of advective mixing in Stokes fluid flows is considered. The velocity field is assumed to be induced by a finite set of spatially distributed force fields that can be modulated arbitrarily with time, and a passive material is advected by the flow. To quantify the degree of mixedness of a density field, we use a Sobolev space norm of negative index. We frame a finite-time optimal control problem for which we aim to find the modulation that achieves the best mixing for a fixed value of the action (the time integral of the kinetic energy of the fluid body) per unit mass. We derive the first-order necessary conditions for optimality that can be expressed as a two-point boundary value problem (TPBVP) and discuss some elementary properties that the optimal controls must satisfy. A conjugate gradient descent method is used to solve the optimal control problem and we present numerical results for two problems involving arrays of vortices. A comparison of the mixing performance shows that optimal aperiodic inputs give better results than sinusoidal inputs with the same energy.
Loss-Induced Confinement in Photonic Crystal Vertical-Cavity Surface-Emitting Lasers

Through calculations and comparison with experimental results, we verify that loss introduced by an etched photonic crystal in a vertical-cavity surface-emitting laser (VCSEL) contributes significantly to the transverse optical confinement and supported modes. The optical loss is examined theoretically using a simple waveguide model from the scalar Helmholtz equation. The modal loss of fabricated lasers is extracted from the observed spectral-mode splitting. The effect of modal loss on the slope efficiency and modal behavior is examined. The model is found to be consistent with experimental measurements, and provides a means of accurate design of single-mode photonic crystal VCSELs.
Dual vortex theory of doped Mott insulators

We present a general framework for describing the quantum phases obtained by doping paramagnetic Mott insulators on the square lattice. The undoped insulators are efficiently characterized by the projective transformations of various fields under the square lattice space group (the PSG). We show that the PSG also imposes powerful constraints on the doped system, and on the effective action for the vortex and Bogoliubov quasiparticle excitations of superconducting states. This action can also be extended across transitions to supersolid or insulating states at nonzero doping. For the case of a valence bond solid (VBS) insulator, we show that the doped system has the same PSG as that of elementary bosons with density equal to the density of electron Cooper pairs. We also discuss aspects of the action for a d-wave superconductor obtained by doping a “staggered-flux” spin liquid state.
Force-Directed graph drawing using social gravity and scaling

Force-directed layout algorithms produce graph drawings by resolving a system of emulated physical forces. We present techniques for using social gravity as an additional force in force-directed layouts, together with a scaling technique, to produce drawings of trees and forests, as well as more complex social networks. Social gravity assigns mass to vertices in proportion to their network centrality, which allows vertices that are more graph-theoretically central to be visualized in physically central locations. Scaling varies the gravitational force throughout the simulation, and reduces crossings relative to unscaled gravity. In addition to providing this algorithmic framework, we apply our algorithms to social networks produced by Mark Lombardi, and we show how social gravity can be incorporated into force-directed Lombardi-style drawings.
Distributed private heavy hitters

In this paper, we give efficient algorithms and lower bounds for solving the heavy hitters problem while preserving differential privacy in the fully distributed local model. In this model, there are n parties, each of which possesses a single element from a universe of size N. The heavy hitters problem is to find the identity of the most common element shared amongst the n parties. In the local model, there is no trusted database administrator, and so the algorithm must interact with each of the n parties separately, using a differentially private protocol. We give tight information-theoretic upper and lower bounds on the accuracy to which this problem can be solved in the local model (giving a separation between the local model and the more common centralized model of privacy), as well as computationally efficient algorithms even in the case where the data universe N may be exponentially large.
Computing classic closeness centrality, at scale

Closeness centrality, first considered by Bavelas (1948), is an importance measure of a node in a network which is based on the distances from the node to all other nodes. The classic definition, proposed by Bavelas (1950), Beauchamp (1965), and Sabidussi (1966), is (the inverse of) the average distance to all other nodes.We propose the first highly scalable (near linear-time processing and linear space overhead) algorithm for estimating, within a small relative error, the classic closeness centralities of all nodes in the graph. Our algorithm applies to undirected graphs, as well as for centrality computed with respect to round-trip distances in directed graphs.For directed graphs, we also propose an efficient algorithm that approximates generalizations of classic closeness centrality to outbound and inbound centralities. Although it does not provide worst-case theoretical approximation guarantees, it is designed to perform well on real networks.We perform extensive experiments on large networks, demonstrating high scalability and accuracy.
Nonlinear Aeroelasticity and Flight Dynamics of High-Altitude Long-Endurance Aircraft

High-Altitude Long-Endurance (HALE) aircraft have wings with high aspect ratios. During operations of these aircraft, the wings can undergo large de∞ections. These large de∞ections can change the natural frequencies of the wing which, in turn, can produce noticeable changes in its aeroelastic behavior. This behavior can be accounted for only by using a rigorous nonlinear aeroelastic analysis. Results are obtained from such an analysis for aeroelastic behavior as well as overall ∞ight dynamic characteristics of a complete aircraft model representative of HALE aircraft. When the nonlinear ∞exibility efiects are taken into account in the calculation of trim and ∞ight dynamics characteristics, the predicted aeroelastic behavior of the complete aircraft turns out to be very difierent from what it would be without such efiects. The overall ∞ight dynamic characteristics of the aircraft also change due to wing ∞exibility. For example, the results show that the trim solution as well as the short-period and phugoid modes are afiected by wing ∞exibility.
Tourette's syndrome.

Summary As our knowledge of Gilles de la Tourette's syndrome increases, so does our appreciation for the pathogenic complexity of this disorder and the challenges associated with its treatment. Advances in the neurosciences have led to new models of pathogenesis, whereas clinical studies have reinvigorated early hypotheses. The interdependent roles of genes and environment in disease formation have yet to be fully elucidated. Results of epidemiological studies have prompted debate on how best to characterise and diagnose this disorder. Absence of ideal anti-tic drugs, combined with knowledge that uncomplicated cases of childhood Tourette's syndrome frequently have a favourable outcome, has led to striking changes in care and treatment of patients. This seminar focuses on these changing views and offers a new perspective on our understanding of the pathogenesis of Tourette's syndrome and on principles for treatment of patients with this disorder.
Do U.S. Marketing Orders Have Much Market Power? An Examination of the Almond Board of California.

This paper tests the conventional wisdom that U.S. marketing orders act as profit-maximizing cartels. The paper analyzes the marketing order for U.S. almonds in both the domestic and export markets. Such a case study is relevant to all U.S. marketing orders because the size and scope of the U.S. almond industry on the world market, and the legal authority of the almond marketing order makes it a likely prospect for exhibiting true cartel behavior. The authors find that the market power exerted by the Almond Board of California's reserve setting is significantly less than would be expected from a profit-maximizing cartel.
Observer-based control of piecewise-affine systems

This paper presents a new synthesis method for both state and dynamic output feedback control of a class of hybrid systems called piecewise-affine (PWA) systems. The synthesis procedure delivers stabilizing controllers that can be proven to give either asymptotic or exponential convergence rates. The synthesis method builds on existing PWA stability analysis tools by transforming the design into a closed-loop analysis problem wherein the controller parameters are unknown. More specifically, the proposed technique formulates the search for a piecewise-quadratic control Lyapunov function and a piecewise-affine control law as an optimization problem subject to linear constraints and a bilinear matrix inequality. The linear constraints in the synthesis guarantee that sliding modes are not generated at the switching. The resulting optimization problem is known to be hard, but suboptimal solutions can be obtained using the three iterative algorithms presented in the paper. The new synthesis technique allows con...
Association between Intraoperative Blood Transfusion and Mortality and Morbidity in Patients Undergoing Noncardiac Surgery

Background: The impact of intraoperative erythrocyte transfusiononoutcomesofanemicpatientsundergoingnoncardiacsurgeryhasnotbeenwellcharacterized.Theobjective of this study was to examine the association between blood transfusion and mortality and morbidity in patients with severeanemia(hematocritlessthan30%)whoareexposedto one or two units of erythrocytes intraoperatively. Methods: Thiswasaretrospectiveanalysisoftheassociationof blood transfusion and 30-day mortality and 30-day morbidity in 10,100 patients undergoing general, vascular, or orthopedic surgery. We estimated separate multivariate logistic regression models for 30-day mortality and for 30-day complications. Results: Intraoperative blood transfusion was associated with an increased risk of death (odds ratio [OR], 1.29; 95% CI, 1.03–1.62). Patients receiving an intraoperative transfusion were more likely to have pulmonary, septic, wound, or thromboembolic complications, compared with patients not receiving an intraoperative transfusion. Compared with patients who were not transfused, patients receiving one or two units of erythrocytes were more likely to have pulmonary complications (OR, 1.76; 95% CI, 1.48–2.09), sepsis (OR, 1.43; 95% CI, 1.21–1.68), thromboembolic complications (OR, 1.77; 95% CI, 1.32–2.38), and wound complications (OR, 1.87; 95% CI, 1.47–2.37). Conclusions: Intraoperative blood transfusion is associated with a higher risk of mortality and morbidity in surgical patients with severe anemia. It is unknown whether this association is due to the adverse effects of blood transfusion or is, instead, the result of increased blood loss in the patients receiving blood.
An Improved Projectile Boattail

Abstract : A series of projectile boattails have shown improved aerodynamic performance over the standard conical boattail. These boattails have equal or lower drag and an improved gyroscopic stability. Their Magnus and damping characteristics appear to be satisfactory so that the projectile should be dynamically stable. Also, these boattails increase the projectile wheel base considerably, thereby decreasing the balloting in the gun tube. The improved aerodynamic performance could lead to longer ranges, longer projectiles or lower spin rates for future projectiles.
Target Detection Via Network Filtering

A method of network filtering has been proposed recently to detect the effects of certain external perturbations on the interacting members in a network. However, with large networks, the goal of detection seems a priori difficult to achieve, especially since the number of observations available often is much smaller than the number of variables describing the effects of the underlying network. Under the assumption that the network possesses a certain sparsity property, we provide a formal characterization of the accuracy with which the external effects can be detected, using a network filtering system that combines Lasso regression in a sparse simultaneous equation model with simple residual analysis. We explore the implications of the technical conditions underlying our characterization, in the context of various network topologies, and we illustrate our method using simulated data.
Tackling the infrared problem of thermal QCD

Abstract Perturbative calculations of corrections to the behavior of an ideal gas of quarks and gluons, the limit that is formally realized at infinite temperature, are obstructed by severe infrared divergences. The limits to computability that the infrared problem poses can be overcome in the framework of dimensionally reduced effective theories. Here, we give details on the evaluation of the highest pertubation coefficient needed for this setup, in the continuum.
Discovery, biological activity, synthesis and potential therapeutic utility of naturally occurring histone deacetylase inhibitors

Covering: up to 2009 A number of small-molecule natural products have been shown to inhibit the activity of histone deacetylases (HDACs). These enzymes catalyze the hydrolysis of N-acetyl lysine residues of the histone proteins that package chromosomal DNA and thereby play a vital role in mediating gene expression. HDAC inhibitors (HDACi) are potent cytotoxic agents with significant potential as anticancer therapeutics and it is currently thought that their selective activity on members of specific subclasses of the eighteen known human HDAC isoforms is important to this activity and to moderation of their toxicity. Herein, we discuss both linear and cyclic HDACi, as well as selected synthetically derived analogs.
Titan - Far-infrared and microwave remote sensing of methane clouds and organic haze

Titan's surface and plausible atmospheric thermal opacity sources, which include gaseous N2, CH4, and H2, together with CH4 clouds and organic haze, are sufficient to match available earth-based and Voyager observations of Titan's thermal emission spectrum. Dominant thermal emission sources are the surface, at greater than 1 cm wavelengths, atmospheric N2 for the 1-200 micron range, condensed and gaseous CH4 for 200-20 microns, and molecular bands and organic haze at less than 20 microns.
Highly enantioselective hydrogenation of enol acetates catalyzed by Ru-TunaPhos complexes.

The chiral disphosphines with tunable dihedral angles (TunaPhos) have been used for asymmetric hydrogenation of enol acetates and dihedral-angle-dependent enantioselectivities were observed. C2-TunaPhos has been proved to be effective for Ru-catalyzed asymmetric hydrogenation of electron-deficient and other enol acetates.
Estimating Earnings Poverty in 1939: A Comparison of Orshansky-Method and Price-Indexed Definitions of Poverty

Official poverty lines do not exist for the United States for years prior to 1959. In this paper a poverty line comparable to the seminal line is constructed for 1939 using the Orshansky method. Poverty rates are then calculated using the earnings data of the 1940 Public Use Microdata Sample of the U.S. Census. A comparison with similar work by Ross et al. (1987) demonstrates the degree to which continual price indexing of the poverty line results in inappropriate estimates. A trend of increasing incidence of poverty among female-headed households prior to 1960 is also revealed.
Inversion of multimegameter-range acoustic data for ocean temperature

Ocean sound speed (a surrogate for temperature) derived from the ray travel times obtained from acoustic transmissions may be inaccurate when the reference ocean state is inadequate for linearized inversion. When the reference (e.g., the Levitus ocean atlas) is significantly different from the "true" ocean, the reference ray paths inaccurately represent the true sampling. In addition, natural oceanic variations, such as the evolution of a summer mixed layer, can significantly change the ray sampling over time. The guiding principle for inversion is that ray travel times associated with the inverse solution must match the measured travel times. A time-dependent reference ocean can reduce both the nonlinearities and the solution uncertainties since the model variances may be assumed to be less. The Levitus ocean atlas was employed to explore the effects of nonlinearities when inverting multimegameter-range acoustic data and to find accurate inversion methods. These methods were applied to acoustic data obtained in the North Pacific during the acoustic thermometry of ocean climate (ATOC) project using an acoustic source on Pioneer Seamount off the coast of California. In order to linearize the inversions, the annual cycle was removed by referencing the measured travel times to travel times computed using the Levitus monthly ocean atlas. This linearization results in a more accurate time series of range- and depth-averaged temperatures, but the solution for range- and depth-averaged temperature is only slightly different from that using a time-independent set of rays. Standard uncertainties for the 0-1000-m depth-averaged temperature are typically /spl plusmn/0.012/spl deg/C, while the annual peak to-peak temperature variation is about 0.4/spl deg/C. Because the travel time data are inherently averaging, the time series of range- and depth averaged temperature is insensitive to different assumptions made in the forward model, such as the model parameterization, variances, wavenumber spectra, and the data uncertainties.
Networks of influence diagrams: a formalism for representing agents' beliefs and decision-making processes

This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents' beliefs and decision-making processes. NIDs are graphical structures in which agents' mental models are represented as nodes in a network; a mental model for an agent may itself use descriptions of the mental models of other agents. NIDs are demonstrated by examples, showing how they can be used to describe conflicting and cyclic belief structures, and certain forms of bounded rationality. In an opponent modeling domain, NIDs were able to outperform other computational agents whose strategies were not known in advance. NIDs are equivalent in representation to Bayesian games but they are more compact and structured than this formalism. In particular, the equilibrium definition for NIDs makes an explicit distinction between agents' optimal strategies, and how they actually behave in reality.
TacTex'13: a champion adaptive power trading agent

Sustainable energy systems of the future could no longer rely on the current paradigm that energy supply follows demand. Since many of the renewable energy resources do not produce power on demand, there is a need for new market structures that motivate sustainable behaviors by participants. The Power Trading Agent Competition(Power TAC) is a new annual competition that focuses on the design and operation of future retail power markets, specifically in smart grid environments with renewable energy production, smart metering, and autonomous agents acting on behalf of customers and retailers. It uses a rich, open-source simulation platform that is based on real-world data and state-of-the-art customer models. Its purpose is to help researchers understand the dynamics of customer and retailer decision-making, as well as the robustness of proposed market designs. This research contributes to the former, by introducing TacTex'13, the champion agent from the inaugural competition in 2013. TacTex'13 learns and adapts to the environment in which it operates, by heavily relying on reinforcement-learning and prediction methods. We formalize the complex decision-making problem that TacTex'13 faces, and approximate its solution in TacTex'13's constituent components. We examine the success of the complete agent through analysis of competition results.
When Perception is Reality: Subjective Expectations and Contracting

Over the past five years or so, applied economists have been relying increasingly on subjective perceptions to explain behavior. In Bellemare (2009a, 2009b) I elicited from landlords subjective perception of tenurial insecurity as a result of the land tenancy contract they signed with their tenant and similar subjective perception as a result of the (hypothetical) alternative contract. This paper discusses how one might explicitly incorporate subjective perceptions in applied contract theory and opens the 'black box' of subjective perceptions in this context by studying their empirical determinants.
Effective supergravity from the weakly coupled heterotic string

The motivation for Calabi-Yau-like compactifications of the weakly coupled E{sub 8} {circle_times} E{sub 8} heterotic string theory, its particle spectrum and the issue of dilaton stabilization are briefly reviewed. Modular invariant models for hidden sector condensation and supersymmetry breaking are described at the quantum level of the effective field theory. Their phenomenological and cosmological implications, including a possible origin for R-parity, are discussed.