cssi/SciSciGPT-SciSciNet huggingface dataset:
Collective Decision-Making in Ideal Networks: The Speed-Accuracy Tradeoff

We study collective decision-making in a model of human groups, with network interactions, performing two alternative choice tasks. We focus on the speed-accuracy tradeoff, i.e., the tradeoff between a quick decision and a reliable decision, for individuals in the network. We model the evidence aggregation process across the network using a coupled drift-diffusion model (DDM) and consider the free response paradigm in which individuals take their time to make the decision. We develop a reduced DDM as a decoupled approximation to the coupled DDM and characterize its efficiency. We determine high probability bounds on the error rate and the expected decision time for the reduced DDM. We show the effect of the decision-maker's location in the network on their decision-making performance under several threshold selection criteria. Finally, we extend the coupled DDM to the coupled Ornstein-Uhlenbeck model for decision-making in two alternative choice tasks with recency effects, and to the coupled race model for decision-making in multiple alternative choice tasks.
Why Repeated Criminal Opportunities Matter: A Dynamic Stochastic Analysis of Criminal Decision Making

Decision makers who confront a long sequence of criminal opportunities act differently from those who confront a single opportunity. If the sequence is long enough, people will take big chances in return for very small gains, even if the probability of detection is very great and the scale of punishment very large. Risk-neutral people will appear to love risk. Patient people will appear to discount the future heavily. For long enough sequences of future opportunities, raising the probability of detection increases the amount of crime committed rather than lowering it. Constitutional safeguards are an important deterrent to crime.
A streaming narrow-band algorithm: interactive computation and visualization of level sets

Deformable isosurfaces, implemented with level-set methods, have demonstrated a great potential in visualization and computer graphics for applications such as segmentation, surface processing, and physically-based modeling. Their usefulness has been limited, however, by their high computational cost and reliance on signi£cant parameter tuning. This paper presents a solution to these challenges by describing graphics processor (GPU) based algorithms for solving and visualizing level-set solutions at interactive rates. The proposed solution is based on a new, streaming implementation of the narrow-band algorithm. The new algorithm packs the level-set isosurface data into 2D texture memory via a multi-dimensional virtual memory system. As the level-set moves, this texture-based representation is dynamically updated via a novel GPU-to-CPU message passing scheme. By integrating the level-set solver with a real-time volume renderer, a user can visualize and intuitively steer the level-set surface as it evolves. We demonstrate the capabilities of this technology for interactive volume segmentation and visualization.
Optimization of switch keyboards

Patients with motor control difficulties often "type" on a computer using a switch keyboard to guide a scanning cursor to text elements. We show how to optimize some parts of the design of switch keyboards by casting the design problem as mixed integer programming. A new algorithm to find an optimized design solution is approximately 3600 times faster than a previous algorithm, which was also susceptible to finding a non-optimal solution. The optimization requires a model of the probability of an entry error, and we show how to build such a model from experimental data. Example optimized keyboards are demonstrated.
Enantioselective synthesis of cyclic carbamimidates via a three-component reaction of imines, terminal alkynes, and p-toluenesulfonylisocyanate using a monophosphine gold(I) catalyst

A racemic Au(I)-catalyzed three-component reaction has been developed to prepare cyclic carbamimidates from imines, terminal alkynes, and sulfonylisocyanates. This reaction exploits the carbophilic π-acidity of gold catalysts to first activate an alkyne toward deprotonation and secondly, to activate the internal alkyne generated toward intramolecular O-cyclization. Unlike similar previously reported multicomponent gold-catalyzed reactions, the stereocenter generated during the alkynylation is preserved in the product. This trait was exploited by developing an enantioselective variant, using an unusual trans-1-diphenylphosphino-2-arylsulfamidocyclohexane ligand. Moderate to excellent levels of enantioselectivity were obtained using a variety of N-arylbenzylidene anilines (41–95% ee, 18 examples).
The unintended effects of the Medicare Part D low income subsidy

Abstract Objectives Medicare Part D is the voluntary program that provides insurance for prescription drugs to 37 million US elderly. This form of public insurance is delivered exclusively through a choice-based private insurance market, where Medicare pays various types of subsidies. The objective of this paper is to analyze how the subsidy paid to low income enrollees induces insurers to distort their plan premiums. Methods Combining both an analysis of the incentives created by the different regulations and empirical evidence obtained from plan level data for the years between 2006 and 2013, the paper evaluates the presence of premium distortions associated with insurers response to the low income subsidy. Results The findings indicate that insurers cluster premiums at the value that maximizes the rents they earn on enrollees receiving the low income subsidies. Moreover, insurers use the possibility of offering multiple insurance plans to manipulate the amount of the subsidy and increase further their rents. Conclusions This study indicates the need to reform the subsidy system in Medicare Part D and offers guidance on the essential elements of the low income subsidy reform.
Dynamic optimization based reactive power planning to mitigate slow voltage recovery and short term voltage instability

Short term voltage stability poses a significant threat to system stability and reliability. This paper applies dynamic VAr injection to ensure short term voltage stability following a large disturbance in a power system with high concentration of induction motor loads. Decelerating and stalling of induction motor loads is considered to be the major cause of fault induced delayed voltage recovery (FIDVR) and short term voltage stability. If system dynamics are not taken into account properly, the proposed control solution may be an expensive over design or an under design that is not capable of eliminating FIDVR problems completely. In this work, the optimal amount and locations for installing dynamic reactive resources are found by control vector parameterization (CVP), a dynamic optimization approach. The efficiency and effectiveness of this approach is improved by utilizing results from trajectory sensitivity analysis, singular value decomposition and linear programming optimization. Dynamic optimization based on CVP approach is tested in an IEEE 162-bus system and a realistic large scale utility power system.
Topological routing path search algorithm with incremental routability test

This paper describes a topological routing path search algorithm embedded in our rubber-band-based autorouter for single-layer printed circuit boards. The algorithm searches for a topological path that is guaranteed to be transformable into a physical wire satisfying design rules. Topological path search algorithms used in existing autorouters verify design rules only locally and approximately. However, it is preferable to satisfy design rules exactly in the global routing phase, especially for routing a densely wired printed circuit board. We propose a method for incrementally verifying design rules during the topological routing path search and describe several improvements to the algorithm that reduce the overhead of the routability test and suppress combinatorial explosion. We also discuss the practical feasibility of the proposed algorithm on the basis of the results of experiments using several printed circuit boards.
Observable consequences of strong coupling in theories with large distance modified gravity

In this talk, we review theories that modify gravity at cosmological distances, and show that any such theory must exhibit a strong coupling phenomenon. We show that all consistent theories that modify the dynamics of the spin-2 graviton on asymptotically flat backgrounds, automatically have this property. Due to the strong coupling effect, modification of the gravitational force is source-dependent, and for lighter sources sets in at shorter distances. This universal feature makes modified gravity theories predictive and potentially testable by precision gravitational measurements at scales much shorter than the current cosmological horizon.
Energy Dispersed Large Data Wave Maps in 2 + 1 Dimensions

In this article we consider large data Wave-Maps from \({\mathbb R^{2+1}}\) into a compact Riemannian manifold \({(\mathcal{M},g)}\), and we prove that regularity and dispersive bounds persist as long as a certain type of bulk (non-dispersive) concentration is absent. This is a companion to our concurrent article [21], which together with the present work establishes a full regularity theory for large data Wave-Maps.
Multivariate Hypergeometric Similarity Measure

We propose a similarity measure based on the multivariate hypergeometric distribution for the pairwise comparison of images and data vectors. The formulation and performance of the proposed measure are compared with other similarity measures using synthetic data. A method of piecewise approximation is also implemented to facilitate application of the proposed measure to large samples. Example applications of the proposed similarity measure are presented using mass spectrometry imaging data and gene expression microarray data. Results from synthetic and biological data indicate that the proposed measure is capable of providing meaningful discrimination between samples, and that it can be a useful tool for identifying potentially related samples in large-scale biological data sets.
Stride Search: a general algorithm for storm detection in high-resolution climate data

Abstract. This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.
"Plata o Plomo?": Bribe and Punishment in a Theory of Political Influence

We present a model where groups attempt to influence policies using both bribes (plata, Spanish for silver) and the threat of punishment (plomo, Spanish for lead). We then use it to make predictions about the quality of a country’s public officials and to understand the role of institutions granting politicians with immunity from legal prosecution. The use of punishment lowers the returns from public office and reduces the incentives of high-ability citizens to enter public life. Cheaper plomo and more resources subject to official discretion are associated with more frequent corruption and less able politicians. This predicts that violence in a country will typically go together with corruption and worse politicians. Moreover, the possibility of punishment changes the nature of the influence game, so that even cheaper plata can lower the ability of public officials. Protecting officials from accusations of corruption (immunity) will decrease the frequency of corruption if the judiciary is weak and may increase the quality of politicians. These predictions cannot emerge from a traditional model where only bribes are used. The positive evils and dangers of the representative, as of every other form of government, may be reduced to two heads: first, general ignorance and incapacity, or, to speak more moderately, insufficient mental qualifications, in the controlling body; secondly, the danger of its being under the influence of interests not identical with the general welfare of the community.
Reducing indeterminism in consultation: a cognitive model of user/librarian interactions

In information facilities such as libraries, finding documents that are relevant to a user query is difficult because of the indeterminism involved in the process by which documents are indexed, and the latitude users have in choosing terms to express a query on a particular topic. Reference librarians play an important support role in coping with this indeterminism, focusing user queries through an interactive dialog. Based on thirty detailed observations of user/librarian interactions obtained through a field experiment, we have developed a computational model designed to simulate the reference librarian. The consultation includes two phases. The first is handle search, where the user's rough problem statement and a user stereotyping imposed by the librarian are med in determining the appropriate tools (handles). The second phase is document search, involving the search for documents within a chosen handle. We are collaborating with the university library for putting our model to use as an intelligent assistant for an online retrieval system.
Sunk Investments Lead to Unpredictable Prices

We study transactions that require investments before trading in a com- petitive market, when forward contracts fixing the transaction price are absent. We show that, despite the market being perfectly competitive and subject to arbitrarily little uncertainty, the inability to jointly determine investment levels and prices may make it impossible for buyers and sellers to predict the prices at which they will trade, leading to inefficient levels of investment and trade. (JEL D40, D50) Keywords: sunk investments, inefficient investments, sunspots, random prices.
THE CATALYTIC ENANTIOSELECTIVE CONSTRUCTION OF MOLECULES WITH QUATERNARY CARBON STEREOCENTERS

A long-standing challenge to synthesis can now be met through the use of new and powerful catalytic asymmetric reactions for the assembly of complex chiral molecules with quaternary stereocenters from achiral building blocks. The reaction sequence shown below is just one example discussed in this review.
14C Analysis of protein extracts from Bacillus spores.

Investigators of bioagent incidents or interdicted materials need validated, independent analytical methods that will allow them to distinguish between recently made bioagent samples versus material drawn from the archives of a historical program. Heterotrophic bacteria convert the carbon in their food sources, growth substrate or culture media, into the biomolecules they need. The F14C (fraction modern radiocarbon) of a variety of media, Bacillus spores, and separated proteins from Bacillus spores was measured by accelerator mass spectrometry (AMS). AMS precisely measures F14C values of biological materials and has been used to date the synthesis of biomaterials over the bomb pulse era (1955 to present). The F14C of Bacillus spores reflects the radiocarbon content of the media in which they were grown. In a survey of commercial media we found that the F14C value indicated that carbon sources for the media were alive within about a year of the date of manufacture and generally of terrestrial origin. Hence, bacteria and their products can be dated using their 14C signature. Bacillus spore samples were generated onsite with defined media and carbon free purification and also obtained from archived material. Using mechanical lysis and a variety of washes with carbon free acids and bases, contaminant carbon was removed from soluble proteins to enable accurate 14C bomb-pulse dating. Since media is contemporary, 14C bomb-pulse dating of isolated soluble proteins can be used to distinguish between historical archives of bioagents and those produced from recent media.
Electrodynamics: A consequence of nonlinear realizations of the Lorentz group

Extensions from the representations of the Lorentz group to include local nonlinear diagonal transformations is sufficient to generate, via the covariant derivative, the interaction of minimal coupling. These diagonal realizations are characterized by six functions φ which must satisfy a system of transformation equations. Inequivalent categories of solutions for the φ give rise to different electromagnetic fields. The Dirac monopole and Coulomb potentials follow directly from two different categories of these nonlinear realizations. Within this theory, charge becomes simply the nonlinear counterpart of intrinsic spin for aparticular nonlinear realization of the Lorentz group. Charge is thus placed on equal footing with intrinsic spin in the sense that both phenomena can be described as consequences of our space-time symmetry. Other solutions for the six φ exist, including a spinor. We briefly discuss the possibility that with these other solutions, these realizations could represent some other basic properties of elementary particles.
The radial velocity signature of tides raised in stars hosting exoplanets

Close-in, massive exoplanets raise significant tides in their stellar hosts. We compute the radial velocity (RV) signal due to this fluid motion in the equilibrium tide approximation. The predicted radial velocities in the observed sample of exoplanets exceed 1 m/s for 17 systems, with the largest predicted signal being � 30 m s 1 for WASP-18 b. Tidally-induced RV’s are thus detectable with present methods. Both tidal fluid flow and the epicyclic motion of a slightly eccentric orbit produce an RV signal at twice the orbital frequency. If care is not taken, the tidally induced RV may, in some cases, be confused with a finite orbital eccentricity. Indeed, WASP-18 b is reported to have an eccentric orbit with small e = 0.009 and pericenter longitude ω = π/2. Whereas such a close alignment of the orbit and line of sight to the observer requires fine tuning, this phase in the RV signal is naturally explained by the tidal velocity signature of an e = 0 orbit. Additionally, the equilibrium tide estimate for the amplitude is in rough agreement with the data. Thus the reported eccentricity for WASP-18 b is instead likely a signature of the tidally-induced RV in the stellar host. Measurement of both the orbital and tidal velocity for non-transiting planets may allow planet mass and inclination to be separately determined solely from radial velocity data. We suggest that high precision fitting of RV data should include the tidal velocity signal in those cases where it may affect the determination of orbital parameters.
Searching for Narrow Emission Lines in X-ray Spectra: Computation and Methods

The detection and quantification of narrow emission lines in X-ray spectra is a challenging statistical task. The Poisson nature of the photon counts leads to local random fluctuations in the observed spectrum that often result in excess emission in a narrow band of energy resembling a weak narrow line. From a formal statistical perspective, this leads to a (sometimes highly) multimodal likelihood. Many standard statistical procedures are based on (asymptotic) Gaussian approximations to the likelihood and simply cannot be used in such settings. Bayesian methods offer a more direct paradigm for accounting for such complicated likelihood functions, but even here multimodal likelihoods pose significant computational challenges. The new Markov chain Monte Carlo (MCMC) methods developed in 2008 by van Dyk and Park, however, are able to fully explore the complex posterior distribution of the location of a narrow line, and thus provide valid statistical inference. Even with these computational tools, standard statistical quantities such as means and standard deviations cannot adequately summarize inference and standard testing procedures cannot be used to test for emission lines. In this paper, we use new efficient MCMC algorithms to fit the location of narrow emission lines, we develop new statistical strategies for summarizing highly multimodal distributions and quantifying valid statistical inference, and we extend the method of posterior predictive p-values proposed by Protassov and coworkers to test for the presence of narrow emission lines in X-ray spectra. We illustrate and validate our methods using simulation studies and apply them to the Chandra observations of the high-redshift quasar PG 1634+706.
Two efficient and provably secure schemes for server-assisted threshold signatures

We present an algorithm which speeds scalar multiplication on a general elliptic curve by an estimated 3.8% to 8.5% over the best known general methods when using affine coordinates. This is achieved by eliminating a field multiplication when we compute 2P +Q from given points P, Q on the curve. We give applications to simultaneous multiple scalar multiplication and to the Elliptic Curve Method of factorization. We show how this improvement together with another idea can speed the computation of the Weil and Tate pairings by up to 7.8%.
Wave-equation migration in generalized coordinate systems

Month and year defended: March, 2009 Wave-equation migration using one-way wavefield extrapolation is commonly used to generate images of complex geologic structure from 3D seismic data. Most conventional wave-equation approaches restrict propagation to downward continuation, where wavefields are recursively depth extrapolated on Cartesian meshes. In practice, this approach exhibits limited high-angle accuracy and is restricted to down-going waves, which precludes using some steep-dip and all turning wave …
BRNI: Modular analysis of transcriptional regulatory programs.

Transcriptional responses often consist of regulatory modules – sets of genes with a shared expression pattern that are controlled by the same regulatory mechanisms. Previous methods allow dissecting regulatory modules from genomics data, such as expression profiles, protein-DNA binding, and promoter sequences. In cases where physical protein-DNA data are lacking, such methods are essential for the analysis of the underlying regulatory program. Here, we present a novel approach for the analysis of modular regulatory programs. Our method – Biochemical Regulatory Network Inference (BRNI) – is based on an algorithm that learns from expression data a biochemically-motivated regulatory program. It describes the expression profiles of gene modules consisting of hundreds of genes using a small number of regulators and affinity parameters. We developed an ensemble learning algorithm that ensures the robustness of the learned model. We then use the topology of the learned regulatory program to guide the discovery of a library of cis-regulatory motifs, and determined the motif compositions associated with each module. We test our method on the cell cycle regulatory program of the fission yeast. We discovered 16 coherent modules, covering diverse processes from cell division to metabolism and associated them with 18 learned regulatory elements, including both known cell-cycle regulatory elements (MCB, Ace2, PCB, ACCCT box) and novel ones, some of which are associated with G2 modules. We integrate the regulatory relations from the expression- and motif-based models into a single network, highlighting specific topologies that result in distinct dynamics of gene expression in the fission yeast cell cycle. Our approach provides a biologically-driven, principled way for deconstructing a set of genes into meaningful transcriptional modules and identifying their associated cis-regulatory programs. Our analysis sheds light on the architecture and function of the regulatory network controlling the fission yeast cell cycle, and a similar approach can be applied to the regulatory underpinnings of other modular transcriptional responses.
Atom economy. A simple Pd catalyzed addition of pronucleophiles with dienes

Abstract Replacing allylic alkylations involving allylic halides, carboxylates, etc. by the simple addition of pronucleophiles to dienes enhances efficiency of use of raw materials and reduces generation of stoichiometric by-products.
An inheritance-based technique for building simulation proofs incrementally

This paper presents a formal technique for incremental construction of system specifications, algorithm descriptions, and simulation proofs showing that algorithms meet their specifications.The technique for building specifications and algorithms incrementally allows a child specification or algorithm to inherit from its parent by two forms of incremental modification: (a) signature extension, where new actions are added to the parent, and (b) specialization (subtyping), where the child's behavior is a specialization (restriction) of the parent's behavior. The combination of signature extension and specialization provides a powerful and expressive incremental modification mechanism for introducing new types of behavior without overriding behavior of the parent; this mechanism corresponds to the subclassing for extension form of inheritance.In the case when incremental modifications are applied to both a parent specification S and a parent algorithm A, the technique allows a simulation proof showing that the child algorithm A′ implements the child specification S′ to be constructed incrementally by extending a simulation proof that algorithm A implements specification S. The new proof involves reasoning about the modifications only, without repeating the reasoning done in the original simulation proof.The paper presents the technique mathematically, in terms of automata. The technique has been used to model and verify a complex middleware system; the methodology and results of that experiment are summarized in this paper.
On using nearly-independent feature families for high precision and confidence

Consider learning tasks where the precision requirement is very high, for example a 99 % precision requirement for a video classification application. We report that when very different sources of evidence such as text, audio, and video features are available, combining the outputs of base classifiers trained on each feature type separately, aka late fusion, can substantially increase the recall of the combination at high precisions, compared to the performance of a single classifier trained on all the feature types, i.e., early fusion, or compared to the individual base classifiers. We show how the probability of a joint false-positive mistake can be less—in some cases significantly less—than the product of individual probabilities of conditional false-positive mistakes (a NoisyOR combination). Our analysis highlights a simple key criterion for this boosted precision phenomenon and justifies referring to such feature families as (nearly) independent. We assess the relevant factors for achieving high precision empirically, and explore combination techniques informed by the analysis.
A Comparative Theory of Electoral Incentives Representing the Unorganized Under PR, Plurality and Mixed-Member Electoral Systems

We expand Denzau and Munger’s 1986 model of ‘How Unorganized Interests Get Represented’ to address cross-national differences in electoral systems. We look at how individual legislators allocate their efforts to serving unorganized constituents versus organized groups. Our model shows how the optimal allocation of effort is affected by differences in nominating processes and electoral rules. Our findings include the following: (1) Closed-list proportional representation (PR) makes legislators generally more responsive to interest groups and less responsive to unorganized voters than single-member districts (SMD). (2) This difference becomes smaller as the personal component of the SMD vote diminishes. (3) Legislators elected via lists in a mixed system may be even less responsive to the unorganized than legislators in a pure list system.
Distributed processing with iAPX 186 microprocessor systems

In most early computer systems, large central computers, minicomputers, or microcomputers were used to perform all the necessary data processing activities in the system. The overall performance of the entire system was limited by the ability of the central CPU to bring in data, process it, and output it in some usable format. This often resulted in large data input/output bottlenecks in I/O-intensive applications where the CPU time required to service I/O functions left little time for data processing. The obvious result is a slow, nonoptimum data processing system. Now many applications are moving in the direction of simpler and easier-to-use distributed systems, where a central CPU delegates some of the processing tasks to distributed processing subsystems. Not only are costs lower with the distributed system approach, but the time needed to implement such systems is substantially less.For example, a network transaction processing system can now use numerous automatic tellers to process data at a variety of dispersed geographic locations. The tellers, or distributed nodes, can then collect, process, output, and eventually pass on necessary information to the central host computer, located at some detached location, without burdening the central computer with handling each simple transaction. The host becomes involved with an individual node only when the intelligent node requires the timely interaction. The heart of a distributed node itself must be an intelligent processing device capable of handling all the processing and I/O requirements needed by the node.The iAPX 186 is a new highly integrated 16-bit microprocessor. It combines 10 of the most common microprocessor system components onto one. The 80186 is essentially a 16-bit CPU board integrated onto a single silicon chip. By combining a limited number of peripheral support components with memory together with an iAPX 186, one can achieve a condensed, cost-effective system on one board, making the 80186 an optimal microprocessor for distributed processing nodes. This high level of integration is accomplished through an advanced HMOS II silicon gate technology. For the first time it provides a system cost saving significantly greater than that of the previous 16-bit microprocessor design alternatives. The 80186, an upgrade from the industry standard iAPX 86 and 88, offers two to three times the system throughput of a standard iAPX 86. The iAPX 186 adds 10 new instruction types to optimize existing iAPX 86 or 88 application code or streamline new iAPX 186 application code. All these hardware and software attributes make distributed processing with iAPX 186 systems a cost-effective, easy 16-bit microprocessor solution.
Terrorism and Small Groups: An Analytical Framework for Group Disruption

Terrorism scholarship has revealed the importance of small groups—both cells and leadership groups—in the proliferation of violence, yet this field remains only loosely connected to small group theory and research. There exists no systematic consideration of the role that group dynamics play in the disruption of terrorist activities. This article proposes an analytical framework for terrorist group disruption that shows how the goals and methods of counterterrorist intervention intersect with small group behavior. We use this framework to theorize how three intervention types—repression, manipulation, and persuasion—interact with group variables and processes, such as communication networks, social identities, group cohesion, and intragroup conflict. Seven theoretical propositions demonstrate how the framework can show how the direct and indirect effects of group behavior can augment or undermine counterterrorist strategies.
Generalized Random Utility Models with Multiple Types

We propose a model for demand estimation in multi-agent, differentiated product settings and present an estimation algorithm that uses reversible jump MCMC techniques to classify agents' types. Our model extends the popular setup in Berry, Levinsohn and Pakes (1995) to allow for the data-driven classification of agents' types using agent-level data. We focus on applications involving data on agents' ranking over alternatives, and present theoretical conditions that establish the identifiability of the model and uni-modality of the likelihood/posterior. Results on both real and simulated data provide support for the scalability of our approach.
Low Mach Number Modeling of Stratified Flows

Low Mach number equation sets approximate the equations of motion of a compressible fluid by filtering out the sound waves, which allows the system to evolve on the advective rather than the acoustic time scale. Depending on the degree of approximation, low Mach number models retain some subset of possible compressible effects. In this paper we give an overview of low Mach number methods for modeling stratified flows arising in astrophysics and atmospheric science as well as low Mach number reacting flows. We discuss how elements from the different fields are combined to form MAESTRO, a code for modeling low Mach number stratified flows with general equations of state, reactions and time-varying stratification.
Association between the Medicare hospice benefit and health care utilization and costs for patients with poor-prognosis cancer.

DESIGN, SETTING, AND PARTICIPANTS Matched cohort study of patients in hospice and nonhospice care using a nationally representative 20% sample of Medicare fee-for-service beneficiaries who died in 2011. Patients with poor-prognosis cancers (eg, brain, pancreatic, metastatic malignancies) enrolled in hospice before death were matched to similar patients who died without hospice care. EXPOSURES Period between hospice enrollment and death for hospice beneficiaries, and the equivalent period of nonhospice care before death for matched nonhospice patients.
Binary mask optimization for inverse lithography with partially coherent illumination

Recently, a set of generalized gradient-based optical proximity correction optimization methods have been developed to solve for the inverse lithography problem under coherent illumination. Most practical lithography systems, however, operate under partially coherent illumination. This paper focuses on developing gradient-based binary mask optimization methods that account for the inherent nonlinearities of partially coherent systems. Two nonlinear models are used in the optimization. The first relies on a Fourier representation that approximates the partially coherent system as a sum of coherent systems. The second model is based on an average coherent approximation that is computationally faster. To influence the solution patterns toward more desirable manufacturability properties, wavelet regularization is added to the optimization framework.
Market Force, Ecology, and Evolution

In financial markets an excess of buying tends to drive prices up, and an excess of selling tends to drive them down. This is called market impact. Based on a simplified model for market making, it is possible to derive a unique functional form for market impact. This can be used to formulate a nonequilibrium theory for price formation. Commonly used trading strategies such as value investing and trend following induce characteristic dynamics in the price. Although there is a tendency for self-fulfilling prophesies, this is not always the case; in particular, many value investing strategies fail to make prices reflect values. When there is a diversity of preceived values, nonlinear strategies give rise to excess volatility. Many market phenomena such as trends and temporal correlations in volume and volatility have simple explanations. The theory is both simple and experimentally testable. Under this theory there is an emphasis on the interrelationships of strategies that makes it natural to regard a market as a financial ecology. A variety of examples show how diversity emerges autmatically as new stategies exploit the inefficiencies of old strategies. This results in capital reallocations that evolve on longer timescales, and cause apparent nonstationarities on shorter timescales. The drive toward market efficiency can be studied in the dynamical context of pattern evolution. The evolution of the capital of a strategy is analogous to the evolution of the population of a biolgoical species. Several different arguments suggest that the timescale for market efficiency is years to decades.
Do gamma-ray burst sources repeat?

Following the discovery by Quashnock & Lamb of an apparent excess of γ-ray burst pairs with small angular separations, we reanalyse the angular distribution of the bursts in the BATSE catalogue. We find that, in addition to an excess of close pairs, there is also a comparable excess of antipodal bursts, i.e. pairs of bursts separated by about 180° in the sky. Both excesses are moderately significant. Quashnock & Lamb argue that the excess of burst pairs with small angular separations is evidence that many bursts repeat, but obviously this hypothesis cannot explain the excess of antipodal coincidences. Since the two excesses have similar characteristics, and since we cannot think of any physical model of bursts that can produce antipodal pairs, we suggest that both excesses may be due to some unknown selection effect
Iridium-Catalyzed Enantioselective Hydrogenation of Cyclic Imines

A catalytic complex made from [Ir(COD)Cl] 2 [di-μ-chloro-bis(1,5-cyclooctadiene)di-iridium(I)] precursor and (S,S)-f-Binaphane ((R,R)-1,1'-bis{(R)-4,5-dihydro-3H-dinaphtho[1,2-c:2',1'-e]-phosphepino}ferrocene) ligand effectively catalyzed the enantioselective hydrogenation of cyclic imines with high reactivity and good enantioselectivity.
Gate Sizing for Cell-Library-Based Designs

With increasing time-to-market pressure and shortening semiconductor product cycles, more and more chips are being designed with library-based methodologies. In spite of this shift, the problem of discrete gate sizing has received significantly less attention than its continuous counterpart. On the other hand, cell sizes of many realistic libraries are sparse, for example, geometrically spaced, which makes the nearest rounding approach inapplicable as large timing violations may be introduced. Therefore, it is highly desirable to design an effective algorithm to handle this discrete gate-sizing problem. Such an algorithm is proposed in this paper. The algorithm is a continuous-solution-guided dynamic-programming-like approach. A set of novel techniques, such as locality-sensitive-hashing-based solution pruning, is also proposed to accelerate the algorithm. Our experimental results demonstrate that 1) the nearest rounding approach often leads to large timing violations and 2) compared to the well-known Coudert's approach, the new algorithm saves up to 21% in area cost while still satisfying the timing constraint.
Implicit learning of ignored visual context

Humans process a visual display more efficiently when they encounter it for a second time, showing learning of the display. This study tests whether implicit learning of complex visual contexts depends on attention. Subjects searched for a white target among black and white distractors. When the locations of the target and the attended set (white distractors) were repeated, search speed was enhanced, but when the locations of the target and the ignored set (black distractors) were repeated, search speed was unaffected. This suggests that the expression of learning depends on attention. However, during the transfer test, when the previously ignored set now was attended, it immediately facilitated performance. In contrast, when the previously attended set now was ignored, it no longer enhanced search speed. We conclude that the expression of visual implicit learning depends on attention but that latent learning of repeated information does not.
A Parametric Design Study of an Electrochemical Sensor

The development of highly sensitive biosensors for the detection of biomolecules, such as the biomarker interleukin-8 for the early detection of oral cancer, requires optimization of sensor design. To augment the performance of an electrochemical sensor, this study used a microscale, aptamer-based electrochemical sensor for detecting botulinum neurotoxin aptamer hybridization. We first used topedown lithographic processing to define the pattern of the electrodes and then used bottomeup manufacturing to modify the surface molecular properties for reducing nonspecific binding. We systemically examined the effects of the design parameters of an aptamerbased electrochemical sensor. Specifically, five key design parameters were examined: the area of the working electrode (WE), the area of the counter electrode (CE), the separation distance between the WE and CE, the overlap length between the WE and CE, and the aptamer concentration. Through an analysis of the signal and noise generated across variations of the different parameters, the significance of each parameter in sensor performance was determined. In particular, we found that the area of the WE was the only key parameter that influenced the performance of the sensor. The output signal level increased with the area of the WE and the signal-to-noise ratio was about constant in the tested range (i.e., from
Finding the origin of the Pioneer anomaly

Analysis of radio-metric tracking data from the Pioneer 10/11 spacecraft at distances between 20 and 70 astronomical units (AU) from the Sun has consistently indicated the presence of an anomalous, small, constant Doppler frequency drift. The drift can be interpreted as being due to a constant acceleration of aP = (8.74 ± 1.33) × 10−8 cm s−2 directed towards the Sun. Although it is suspected that there is a systematic origin to the effect, none has been found. As a result, the nature of this anomaly has become of growing interest. Here we present a concept for a deep-space experiment that will reveal the origin of the discovered anomaly and will also characterize its properties to an accuracy of at least two orders of magnitude below the anomaly's size. The proposed mission will not only provide a significant accuracy improvement in the search for small anomalous accelerations, it will also determine if the anomaly is due to some internal systematic or has an external origin. A number of critical requirements and design considerations for the mission are outlined and addressed. If only already existing technologies were used, the mission could be flown as early as 2010.
Strong Consistency of the Good-Turing Estimator

We consider the problem of estimating the total probability of all symbols that appear with a given frequency in a string of i.i.d. random variables with unknown distribution. We focus on the regime in which the block length is large yet no symbol appears frequently in the string. This is accomplished by allowing the distribution to change with the block length. Under a natural convergence assumption on the sequence of underlying distributions, we show that the total probabilities converge to a deterministic limit, which we characterize. We then show that the Good-Turing total probability estimator is strongly consistent.
Password Protected Smart Card and Memory Stick Authentication against Off-Line Dictionary Attacks

We study the security requirements for remote authentication with password protected smart card. In recent years, several protocols for password-based authenticated key exchange have been proposed. These protocols are used for the protection of password based authentication between a client and a remote server. In this paper, we will focus on the password based authentication between a smart card owner and smart card via an untrusted card reader. In a typical scenario, a smart card owner inserts the smart card into an untrusted card reader and input the password via the card reader in order for the smart card to carry out the process of authentication with a remote server. In this case, we want to guarantee that the card reader will not be able to impersonate the card owner in future without the smart card itself. Furthermore, the smart card could be stolen. If this happens, we want the assurance that an adversary could not use the smart card to impersonate the card owner even though the sample space of passwords may be small enough to be enumerated by an off-line adversary.
Fundamental limit of nanophotonic light-trapping in solar cells

We use a rigorous electromagnetic approach to develop a light-trapping theory, which reveals that the standard limit developed by Yablonovitch can be substantially surpassed in nanophotonic regimes, opening new avenues for highly efficient solar cells.
Active stability of the glenohumeral joint decreases in the apprehension position.

Abstract Background. Muscle forces that compress the glenohumeral joint during mid-ranges of motion may lead to increased translational forces in end-range positions, such as the apprehension position, where symptoms of anterior instability occur. Objective. The objective of this study was to quantify active stability provided by eight shoulder muscles in mid-range and end-range positions through muscle force vector analysis. Methods. Lines of action were derived from a geometric model and muscle force magnitudes were estimated with electromyography-based techniques. Resultant muscle force vectors were calculated by summing individual muscle force vectors. Results. Compared to mid-range positions, lines of action of resultant force vectors were more anteriorly directed in end-range positions compared to 15° of abduction, up to 26°. Consequently, anterior stability was lowest in the apprehension position. The magnitudes of the resultant force vectors were comparable to other studies. Based on a sensitivity analysis, lines of action of resultant force vectors vary up to 6° within the population. Conclusions. Data obtained from this model will improve conservative management, post-surgical rehabilitation, and strength training protocols. Relevance. In the apprehension position, muscle forces may promote anterior humeral head translation, predisposing the glenohumeral joint to anterior instability when other stabilizing mechanisms such as the glenohumeral capsule are not functioning normally.