cssi/SciSciGPT-SciSciNet huggingface dataset:
Antidepressant use late in pregnancy and risk of persistent pulmonary hypertension of the newborn.

Importance The association between selective serotonin reuptake inhibitor (SSRI) antidepressant use during pregnancy and risk of persistent pulmonary hypertension of the newborn (PPHN) has been controversial since the US Food and Drug Administration issued a public health advisory in 2006. Objective To examine the risk of PPHN associated with exposure to different antidepressant medication classes late in pregnancy. Design and Setting Cohort study nested in the 2000-2010 Medicaid Analytic eXtract for 46 US states and Washington, DC. Last follow-up date was December 31, 2010. Participants A total of 3 789 330 pregnant women enrolled in Medicaid from 2 months or fewer after the date of last menstrual period through at least 1 month after delivery. The source cohort was restricted to women with a depression diagnosis and logistic regression analysis with propensity score adjustment applied to control for potential confounders. Exposures for Observational Studies SSRI and non-SSRI monotherapy use during the 90 days before delivery vs no use. Main Outcomes and Measures Recorded diagnosis of PPHN during the first 30 days after delivery. Results A total of 128 950 women (3.4%) filled at least 1 prescription for antidepressants late in pregnancy: 102 179 (2.7%) used an SSRI and 26 771 (0.7%) a non-SSRI. Overall, 7630 infants not exposed to antidepressants were diagnosed with PPHN (20.8; 95% CI, 20.4-21.3 per 10 000 births) compared with 322 infants exposed to SSRIs (31.5; 95% CI, 28.3-35.2 per 10 000 births), and 78 infants exposed to non-SSRIs (29.1; 95% CI, 23.3-36.4 per 10 000 births). Associations between antidepressant use and PPHN were attenuated with increasing levels of confounding adjustment. For SSRIs, odds ratios were 1.51 (95% CI, 1.35-1.69) unadjusted and 1.10 (95% CI, 0.94-1.29) after restricting to women with depression and adjusting for the high-dimensional propensity score. For non-SSRIs, the odds ratios were 1.40 (95% CI, 1.12-1.75) and 1.02 (95% CI, 0.77-1.35), respectively. Upon restriction of the outcome to primary PPHN, the adjusted odds ratio for SSRIs was 1.28 (95% CI, 1.01-1.64) and for non-SSRIs 1.14 (95% CI, 0.74-1.74). Conclusions and Relevance Evidence from this large study of publicly insured pregnant women may be consistent with a potential increased risk of PPHN associated with maternal use of SSRIs in late pregnancy. However, the absolute risk was small, and the risk increase appears more modest than suggested in previous studies.
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks

Elicitation of probabilities is one of the most laborious tasks in building decision-theoretic models, and one that has so far received only moderate attention in decision-theoretic systems. We propose a set of user interface tools for graphical probabilistic models, focusing on two aspects of probability elicitation: (1) navigation through conditional probability tables and (2) interactive graphical assessment of discrete probability distributions. We propose two new graphical views that aid navigation in very large conditional probability tables: the CPTREE (Conditional Probability Tree) and the sCPT (shrinkable Conditional Probability Table). Based on what is known about graphical presentation of quantitative data to humans, we offer several useful enhancements to probability wheel and bar graph, including different chart styles and options that can be adapted to user preferences and needs. We present the results of a simple usability study that proves the value of the proposed tools.
Spherical Casimir Effect for a Massive Scalar Field on the Three Dimensional Ball

The zeta function regularization technique is used to study the Casimir effect for a scalar field of mass m satisfying Dirichlet boundary conditions on a spherical surface of radius a. In the case of large scalar mass, , simple analytic expressions are obtained for the zeta function and Casimir energy of the scalar field when it is confined inside the spherical surface, and when it is confined outside the spherical surface. In both cases the Casimir energy is exact up to order and contains the expected divergencies, which can be eliminated using the well established renormalization procedure for the spherical Casimir effect. The case of a scalar field present in both the interior and exterior region is also examined and, for , the zeta function, the Casimir energy, and the Casimir force are obtained. The obtained Casimir energy and force are exact up to order and respectively. In this scenario both energy and force are finite and do not need to be renormalized, and the force is found to produce an outward pressure on the spherical surface.
Applying cosine series to XML structural join size estimation

As XML has become the de facto standard for data presentation and exchanging on the Web, XML query optimization has emerged as an important research issue. It is widely accepted that structural joins, which evaluate the containment (ancestor-descendant) relationships between XML elements, are important to the XML query processing. Estimating structural join size accurately and quickly thus becomes crucial to the success of XML query plan selection. In this paper, we propose to apply Cosine transform to structural join size estimation. Our approach captures structural information of XML data using mathematical functions, which are then approximated by the Cosine series. We derive a simple formula to estimate the structural join size using the Cosine series. Theoretical analyses and extensive experiments have been performed. The experimental results show that, compared with state-of-the-art IM-DA-Est method, our method is several order faster, requires less memory, and yields better or comparable estimates.
Structural Equation Modeling: Nonstandard Cases†

Model assumptions are often violated in typical data gathering conditions. This article discusses the consequences of violating model assumptions and presents strategies that can be used to cope with the violations. Keywords: nonstandard conditions; violations of assumptions; robustness
User revocation in secure adhoc networks

We focus on the problem of user revocation in secure adhoc networks. The current approach to achieve security in adhoc networks is to use a secret instantiation protocol in which, each user is given a subset of secrets from a common secret pool. To communicate securely, a pair of users use the secrets that are common to both of them. However, when users are compromised, some of these secrets are also compromised. Hence, to revoke the compromised users, the secrets known to these users need to be updated. Many group key management solutions exist for revocation of users from a group. However, due to the limitations in adhoc networks, i.e., lack of efficient broadcast mechanisms and lossy links, revocation of users is a challenging problem. In this paper, we propose a revocation algorithm that combines the secret instantiation protocols with group key management protocols. Depending on the combination of protocols used, our revocation algorithm provides deterministic or probabilistic guarantees for revocation. We illustrate our revocation algorithm by combining the square grid protocol and the logical key hierarchy protocol.
"Ciudadanos de un pueblo libre": liberalismo popular y raza en el suroccidente de Colombia en el siglo XIX

This article explores how popular classes, especially Afro-Colombians, created an alliance with the Liberal Party in the Cauca region of Colombia during the mid-nineteenth century. Afro-Caucanos negotiated with elite leaders of the party, trading their votes and service as soldiers in the civil wars of the era for a variety of social, economic and political gains, including the abolition of slavery, access to commons, the reduction of aguardiente monopolies, and obtaining the status of citizens. Afro-Caucanos also redefined citizenship, imagining a popular liberalism in distinct ways from the conceptions of Liberal elites, investing it with more powerful notions of liberty and equality. In the 1870s, the alliance began to fracture as elite Liberals refused to break the hacienda system and grant land rights to their popular supporters.
Risk-sharing and the Probability of Crises

In this paper I add heterogeneous agents and risk-sharing opportunities to a coordination game which represents deposit withdrawals from the banking system. I find that heterogeneity in risk aversion within the population amplifies the effect of the business cycle on the probability of a bank run. In particular, risk-sharing enhances the likelihood of bank runs during bad times. The novel insight is that when there is a risk-sharing motive, fundamentals drive not only individual behavior, but also which individuals are more relevant for the likelihood of a crisis. This mechanism has important consequences for the way we think about policy questions. In the paper I discuss three such implications in detail: (1) I show that a policy that facilitates access to banking for previously unbanked individuals generates externalities, and may even decrease welfare of the least risk averse group in the population. (2) I characterize the bias in the estimation of the probability of a banking crisis when heterogeneity is neglected. (3) I show how to correctly calculate the social value of deposit insurance when depositors differ in their risk aversion.
Lower bounds and parameterized approach for longest common subsequence

In this paper, different parameterized versions of the longest common subsequence (LCS) problem are extensively investigated and computational lower bound results are derived based on current research progress in parameterized computation. For example, with the number of sequences as the parameter k, the problem is unlikely to be solvable in time f(k)no(k), where n is the length of each sequence and f is any recursive function. The lower bound result is asymptotically tight in consideration of the dynamic programming approach of time O(nk). Computational lower bounds for polynomial-time approximation schemes (PTAS) for the LCS problem are also derived. It is shown that the LCS problem has no PTAS of time f(1/ e)no(1/ e) for any recursive function f, unless all SNP problems are solvable in subexponential time. Compared with former results on this problem, this result has its significance. Finally a parameterized approach for the LCS problem is discussed, which is more efficient than the dynamic programming approach, especially when applied to large scale sequences.
The Market for Retirement Products in Australia

Australia introduced a mandatory retirement savings scheme in 1992. This built on pre-existing voluntary occupational plans. The new scheme has been very successful in expanding coverage and mobilizing large financial savings that are equal to close to 100 percent of GDP. However, Australia does not impose restrictions on payout options. The payout phase used to be dominated by lump sum withdrawals, which accounted for 80 percent of benefit payments as recently as 2002. But pension payments increased in recent years and now represent 45 percent of total payments. The vast majority of these pension payments take the form of term annuities and allocated annuities. The latter are similar to phased withdrawals in Chile but run for fixed terms of up to 25 years rather than for lifetime terms. The demand for life annuities and lifetime phased withdrawals is very limited. The paper discusses the factors that have shaped the pattern of demand for retirement products, including the availability of the universal age pension and the effect of clawback provisions, the impact of the high level of home ownership, and the widespread preference of retiring workers for reliance on self-annuitization. The paper also reviews the prudential regulation of superannuation funds and life insurance companies.
A Conjecture about Conserved Symmetric Tensors

We consider T(x), a tensor of arbitrary rank that is symmetric in all of its indices and conserved in the sense that the divergence on any one index vanishes. Our conjecture is that all integral moments of this tensor will vanish if the number of coordinates in that integral moment is less than the rank of the tensor. This result is proved explicitly for a number of particular cases, assuming adequate dimensionality of the Euclidean space of coordinates (x); but a general proof is lacking. Along the way, we find some neat results for certain large matrices generated by permutations. c
Service-Constrained Network Design Problems

Several practical instances of network design problems often require the network to satisfy multiple constraints. In this paper, we focus on the following problem (and its variants): find a low-cost network, under one cost function, that services every node in the graph, under another cost function, (i.e., every node of the graph is within a prespecified distance from the network). This study has important applications to the problems of optical network design and the efficient maintenance of distributed databases.
Profile of Poverty in Zambia Based on the 1991 Household Expenditure and Incomes Survey

Many government programs supported by the Government of Zambia and world donor organizations are designed to alleviate poverty. Accordingly it is important for assistance program design, implementation, and evaluation to have a clear and accurate concept of this condition and its prevalence. This paper indentifies the extent of poverty in Zambia and reports a profile of low-income households that might be used for tarteting assistance programs to the poort. The data used to extimate poverty levels come from the Zambian Household Expenditurea nd Incomes Survey (HEIS) conducted in June 1991.
Performance Evaluation of Transcoding-Enabled Streaming Media Caching System

We evaluate the performance of transcoding-enabled streaming media caching proxy system (TeC). TeC is designed for efficient delivery of rich media web contents to heterogeneous network environments and client capabilities. Depending on the connection speed and processing capability of an end user, the proxy transcodes the requested (and possibly cached) video into an appropriate format and delivers it to the user. We study the TeC performance by simulation using real traces derived from enterprise media server logs.
Mode Effect Analysis – Paper Respondents vs. Web Respondents in the 2004–05 Teacher Follow-up Survey

Mode Effect Analysis – Paper Respondents vs. Web Respondents in the 2004–05 Teacher Follow-up Survey
Approximating non-uniform sparsest cut via generalized spectra

@+ respectively, we can find a set T ⊆ V with C(T,V\T)/D(T,V\T) at most 1+e/δ times the optimal non-uniform sparsest cut value, in time 2r/(δe) poly(n) provided λr ≥ Φ*/(1 -- δ). Here λr is the r'th smallest generalized eigenvalue of the Laplacian matrices of cost and demand graphs; C(T, V\T) (resp. D(T, V\T)) is the weight of edges crossing the (T, V\T) cut in cost (resp. demand) graph and Φ* is the sparsity of the optimal cut. In words, we show that the non-uniform sparsest cut problem is easy when the generalized spectrum grows moderately fast. To the best of our knowledge, there were no results based on higher order spectra for non-uniform sparsest cut prior to this work.Even for uniform sparsest cut, the quantitative aspects of our result are somewhat stronger than previous methods. Similar results hold for other expansion measures like edge expansion, normalized cut, and conductance, with the r'th smallest eigenvalue of the normalized Laplacian playing the role of λr(G) in the latter two cases.Our proof is based on an e1-embedding of vectors from a semi-definite program from the Lasserre hierarchy. The embedded vectors are then rounded to a cut using standard threshold rounding. We hope that the ideas connecting e1-embeddings to Lasserre SDPs will find other applications. Another aspect of the analysis is the adaptation of the column selection paradigm from our earlier work on rounding Lasserre SDPs [9] to pick a set of edges rather than vertices. This feature is important in order to extend the algorithms to non-uniform sparsest cut.
Plugging side-channel leaks with timing information flow control

The cloud model's dependence on massive parallelism and resource sharing exacerbates the security challenge of timing side-channels. Timing Information Flow Control (TIFC) is a novel adaptation of IFC techniques that may offer a way to reason about, and ultimately control, the flow of sensitive information through systems via timing channels. With TIFC, objects such as files, messages, and processes carry not just content labels describing the ownership of the object's "bits," but also timing labels describing information contained in timing events affecting the object, such as process creation/termination or message reception. With two system design tools--deterministic execution and pacing queues--TIFC enables the construction of "timing-hardened" cloud infrastructure that permits statistical multiplexing, while aggregating and rate-limiting timing information leakage between hosted computations.
ACTION OF LONGEST ELEMENT ON A HECKE ALGEBRA CELL MODULE

By a result of Mathas, the basis element Tw0 of the Hecke algebra of a finite Coxeter group acts in the canonical basis of a cell module as a permutation matrix times plus or minus a power of v. We generalize this result to the unequal parameter case. We also show that the image of Tw0 in the corresponding asymptotic Hecke algebra is given by a simple formula.
Influence of Fast Alpha Diffusion and Thermal Alpha Buildup on Tokamak Reactor Performance

The effect of fast alpha diffusion and thermal alpha accumulation on the confinement capability of a candidate Engineering Test Reactor plasma (Tokamak Ignition/Burn Experimental Reactor) in achiev...
Sampling from Determinantal Point Processes for Scalable Manifold Learning.

High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the Nystrom method. The two main challenges that arise are: (i) the landmarks selected in non-Euclidean geometries must result in a low reconstruction error, (ii) the graph constructed from sparsely sampled landmarks must approximate the manifold well. We propose to sample the landmarks from determinantal distributions on non-Euclidean spaces. Since current determinantal sampling algorithms have the same complexity as those for manifold learning, we present an efficient approximation with linear complexity. Further, we recover the local geometry after the sparsification by assigning each landmark a local covariance matrix, estimated from the original point set. The resulting neighborhood selection based on the Bhattacharyya distance improves the embedding of sparsely sampled manifolds. Our experiments show a significant performance improvement compared to state-of-the-art landmark selection techniques on synthetic and medical data.
THE EFFECTS OF BANK MERGERS ON COMMERCIAL BANK AGRICULTURAL LENDING

Regression analysis is used to estimate static and dynamic restructuring, direct and external effects of mergers from 1994 to 2001 on bank agricultural loan-to-asset ratios. Results indicate that mergers have a negative effect on agricultural loan ratios. The effect is less pronounced for smaller than larger bank mergers and more pronounced for mergers of banks affiliated with the same holding company than other merger types.
A Flow Controller for Open or Closed Conduits

General principle of flow control, utilizing non-linear resistance, is developed that is applicable to both open and closed conduits; control is definitely adjustable for discharge over its design range, and holds flow close to predetermined discharge over its head range; control is readily converted into flow meter with linear head-discharge curve and adjustable range and sensitivity.
Efficient value of information computation

One of the most useful sensitivity analysis techniques of decision analysis is the computation of value of information (or clairvoyance), the difference in value obtained by changing the decisions by which some of the uncertainties are observed. In this paper, some simple but powerful extensions to previous algorithms are introduced which allow an efficient value of information calculation on the rooted cluster tree (or strong junction tree) used to solve the original decision problem.
Insurers : Too Many, Too Few, or "Just Right"? Initial Observations on a Cross-Country Dataset of Concentration and Competition Measures

In many markets, industry and policymakers agree that there may be too many insurers. In others, the consensus is that there could be benefit from more competition. But this broad consensus is often supported by evidence that is more qualitative, anecdotal, or judgmental despite being unanimous. What is less clear, however, is how far consolidation or liberalization will go, how fast, and when it will end. This paper presents some initial observations from a cross-country data set and proposes that individual country results can be interpreted against this data set to inform expectations regarding trends in competition, concentration and consolidation, to inform analysis of the sector, for individual firm strategic planning and wider market risk assessments. A "natural level" for measures is suggested as a starting hypothesis. Further consideration is then made of the role of absolute market size, stage of market development, and differentials between life and non life segments. Analysis of the natural level, adjusted for market conditions, can then be used to develop preliminary views on current and expected market dynamics, strategic planning, and to inform policy, regulatory and supervisory priorities.
CMedPort: Intelligent Searching for Chinese Medical Information

Most information retrieval techniques have been developed for English and other Western languages. As the second largest Internet language, Chinese provides a good setting for study of how search engine techniques developed for English could be generalized for use in other languages to facilitate Internet searching and browsing in a multilingual world. This paper reviews different techniques used in search engines and proposes an integrated approach to development of a Chinese medical portal: CMedPort. The techniques integrated into CMedPort include meta-search engines, cross-regional search, summarization and categorization. A user study was conducted to compare the effectiveness, efficiency and user satisfaction of CMedPort and three major Chinese search engines. Preliminary results from the user study show that CMedPort achieves similar accuracy in searching tasks, and higher effectiveness and efficiency in browsing tasks than Openfind, a Taiwan search engine portal. We believe that the proposed approach can be used to support Chinese information seeking in Web-based digital library applications.
Effects of anharmonicity of molecular vibrations on the diffraction of electrons. Part V. Tetrahedral molecules

Abstract Unless the skewing of radial distribution peaks is properly taken into account, diffraction analyses of gas molecules may lead to geometrically inconsistent arrays of internuclear distances. It is shown how to derive the required nonbonded skew parameter â for a tetrahedral AX 4 molecule from its potential constants in the case of an ensemble distributed among too many vibrational states to make the standard perturbation or variation methods feasible. Elements of the transformation tensor relating curvilinear coordinates S i to rectilinear coordinates S i are found and applied in a treatment using the “effective potential energy” approach of Miller. Illustrative calculations are carried out for hot CF 4 and SiF 4 molecules. It is verified that the contributions to â from nonlinear transformations and from Morse stretching deduced by a simple model in Part III of this series are in reasonably good agreement with the more rigorous contributions calculated in this research. It is shown, however, that certain other contributions are larger.
High-contrast imager for complex aperture telescopes (HiCAT): 3. first lab results with wavefront control

HiCAT is a high-contrast imaging testbed designed to provide complete solutions in wavefront sensing, control and starlight suppression with complex aperture telescopes. The pupil geometry of such observatories includes primary mirror segmentation, central obstruction, and spider vanes, which make the direct imaging of habitable worlds very challenging. The testbed alignment was completed in the summer of 2014, exceeding specifications with a total wavefront error of 12nm rms over a 18mm pupil. The installation of two deformable mirrors for wavefront control is to be completed in the winter of 2015. In this communication, we report on the first testbed results using a classical Lyot coronagraph. We also present the coronagraph design for HiCAT geometry, based on our recent development of Apodized Pupil Lyot Coronagraph (APLC) with shaped-pupil type optimizations. These new APLC-type solutions using two-dimensional shaped-pupil apodizer render the system quasi-insensitive to jitter and low-order aberrations, while improving the performance in terms of inner working angle, bandpass and contrast over a classical APLC.
The high intensity solar cell: Key to low cost photovoltaic power

The design considerations and performance characteristics of the 'high intensity' (HI) solar cell are presented. A high intensity solar system was analyzed to determine its cost effectiveness and to assess the benefits of further improving HI cell efficiency. It is shown that residential sized systems can be produced at less than $1000/kW peak electric power. Due to their superior high intensity performance characteristics compared to the conventional and VMJ cells, HI cells and light concentrators may be the key to low cost photovoltaic power.
Scaling Laws of Cognitive Networks

Opportunistic secondary spectrum usage has the potential to dramatically increase spectral efficiency and rates of a network of secondary cognitive users. In this work we consider a cognitive network: n pairs of cognitive transmitter and receiver wish to communicate simultaneously in the presence of a single primary transmitter-receiver link. We assume each cognitive transmitter-receiver pair communicates in a realistic single-hop fashion, as cognitive links are likely to be highly localized in space. We first show that under an outage constraint on the primary link's capacity, provided that the density of the cognitive users is constant, the sum-rate of the n cognitive links scales linearly with n as n ? ?. This scaling is in contrast to the sum-rate scaling of ?n seen in multi-hop ad-hoc networks. We then explore the optimal radius of the primary exclusive region: the region in which no secondary cognitive users may transmit, such that the outage constraint on the primary user is satisfied. We obtain bounds that help the design of this primary exclusive region, outside of which cognitive radios may freely transmit.
The Tully-Fisher Relation: A Numerical Simulator’s Perspective

In this brief contribution, I will outline hopes of understanding the origin of galaxy scaling relations using numerical simulations as a tool to gain understanding. The case of the Tully-Fisher relation for disk galaxies is used as a working example to illustrate the modest achievements to date and the difficult tasks ahead.
Optimizing packing fraction in granular media composed of overlapping spheres

What particle shape will generate the highest packing fraction when randomly poured into a container? In order to explore and navigate the enormous search space efficiently, we pair molecular dynamics simulations with artificial evolution. Arbitrary particle shape is represented by a set of overlapping spheres of varying diameter, enabling us to approximate smooth surfaces with a resolution proportional to the number of spheres included. We discover a family of planar triangular particles, whose packing fraction of ϕ ∼ 0.73 is among the highest experimental results for disordered packings of frictionless particles. We investigate how ϕ depends on the arrangement of spheres comprising an individual particle and on the smoothness of the surface. We validate the simulations with experiments using 3D-printed copies of the simplest member of the family, a planar particle consisting of three overlapping spheres with identical radius. Direct experimental comparison with 3D-printed aspherical ellipsoids demonstrates that the triangular particles pack exceedingly well not only in the limit of large system size but also when confined to small containers.
Inverse Design of Horizontal Axis Wind Turbine Blades Using a Vortex Line Method

A new inverse design process for horizontal axis wind turbine blades is developed to account for three-dimensional blade features such as non-planar wing tip. The multidimensional Newton iteration method combined with a vortex line method is used to provide blade geometry parameters given desired aerodynamic behaviors such as lift coefficient and axial induction. The Jacobian matrix is visualized to show the effect of the change of the blade twist and chord on the change of the aerodynamic behaviors. The method is validated for a canonical straight blade with uniform lift coefficient and axial induction distributions. The results show an excellent agreement with those obtained by PROPID, which is a blade element momentum theory-based inverse design code. The National Renewable Energy Laboratory Phase VI blade is used to validate the method for a straight blade with non-uniform distributions of the lift coefficient and axial induction. The method is also applied successfully to a non-straight blade design with a non-planar wing tip. A noticeable change in the twist and chord for this non-straight blade is seen compared with a straight blade. Finally, the inverse design code is used to make a large rotor blade, and the power output generated by this blade is computed. Copyright © 2014 John Wiley & Sons, Ltd.
Thermal modeling of cryogenic accelerator structures

A software package has been created for examining the thermal behavior of cryogenic particle accelerator structures. It models the steady state heat flows in waveguides and beampipes while in operation, treating both diffuse and specular infrared reflection. The programs runs effectively on small computers, since only a few simple geometries are treated, and the output display options are limited. Overall accuracy for simple test cases is on the order of a few percent, but on short structures with very wide apertures the errors can be up to 10%. An analysis of radiative heat load in the B-factory cavity is presented, and thermal management strategies for the input waveguide are discussed. >
Fast bidirectional probability estimation in Markov models

We develop a new bidirectional algorithm for estimating Markov chain multi-step transition probabilities: given a Markov chain, we want to estimate the probability of hitting a given target state in l steps after starting from a given source distribution. Given the target state t, we use a (reverse) local power iteration to construct an 'expanded target distribution', which has the same mean as the quantity we want to estimate, but a smaller variance - this can then be sampled efficiently by a Monte Carlo algorithm. Our method extends to any Markov chain on a discrete (finite or countable) state-space, and can be extended to compute functions of multi-step transition probabilities such as PageRank, graph diffusions, hitting/return times, etc. Our main result is that in 'sparse' Markov Chains - wherein the number of transitions between states is comparable to the number of states -the running time of our algorithm for a uniform-random target node is order-wise smaller than Monte Carlo and power iteration based algorithms; in particular, our method can estimate a probability p using only O(1/√p) running time.
Asymptotic Density and the Asymptotics of Partition Functions

Let A be a set of positive integers with gcd (A) = 1, and let p A (n) be the partition function of A. Let c 0 = π√2/3. If A has lower asymptotic density α and upper asymptotic density β, then lim inf log p A (n)/c 0 √n ≧ √α and lim sup log p A (n)/c 0 √n ≦ √β. In particular, if A has asymptotic density α > 0, then log p A (n) ∼ c0√αn. Conversely, if α > 0 and log p A (n) ∼ c 0 √αn, then the set A has asymptotic density α.
Why multi-stakeholder groups succeed and fail

Anti-corruption initiatives increasingly use multi-stakeholder groups, comprised of representatives from government, private sector, and civil society organizations, to drive implementation at the local level and serve as a force for transparency. In theory, the multi-stakeholder groups ideal is quite appealing -- each stakeholder has its own interest in the initiative and contributes its unique capacities. In practice, many multi-stakeholder groups have fallen short of expectations. This paper considers two separate but related questions. First, what are the unique barriers to implementation facing multi-stakeholder groups? Second, what policy measures can be taken to improve the likelihood that multi-stakeholder groups will succeed? The authors use existing research in political science and economics to develop a multi-level framework that accounts for the"nested nature"of multi-stakeholder groups. The framework is then applied to experiences of MSGs from the Construction Sector Transparency Initiative, a new pilot program that aims to promote transparency in construction through the release of material project information. The evidence shows that the barriers facing multi-stakeholder groups are substantial, but once the level (individual incentives, organizational dynamics, country context, or international pressures) of the challenge confronting a multi-stakeholder group is identified, the specific barrier, its root causes, and appropriate solutions can be identified. More broadly, the Construction Sector Transparency Initiative experiences suggest that multi-stakeholder groups are best used as a means of promoting dialogue and building consensus, not as the locus of policy implementation and oversight.
Learning mixtures of DAG models

We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple search-and-score algorithms are infeasible for a variety of problems, and introduce a feasible approach in which parameter and structure search is interleaved and expected data is treated as real data. Our approach can be viewed as a combination of (1) the Cheeseman-Stutz asymptotic approximation for model posterior probability and (2) the Expectation-Maximization algorithm. We evaluate our procedure for selecting among MDAGs on synthetic and real examples.
Evaluating cloud tuning in a climate model with satellite observations

[1] This study examines the validity of a tunable cloud parameter, the threshold particle radius triggering the warm rain formation, in a climate model. Alternate values of the model's particular parameter within uncertainty have been shown to produce severely different historical temperature trends due to differing magnitude of aerosol indirect forcing. Three different threshold radii are evaluated against satellite observations in terms of the statistics depicting microphysical process signatures of the warm rain formation. The results show that the simulated temperature trend best matches to observed trend when the model adopts the threshold radius that worst reproduces satellite‒observed microphysical statistics and vice versa. This inconsistency between the “bottom‒up” process‒based constraint and the “top‒down” temperature trend constraint implies the presence of compensating errors in the model.
Improved tag set design and multiplexing algorithms for universal arrays

In this paper we address two optimization problems arising in the design of genomic assays based on universal tag arrays. First, we address the universal array tag set design problem. For this problem, we extend previous formulations to incorporate antitag-to-antitag hybridization constraints in addition to constraints on antitag-to-tag hybridization specificity, establish a constructive upper bound on the maximum number of tags satisfying the extended constraints, and propose a simple greedy tag selection algorithm. Second, we give methods for improving the multiplexing rate in large-scale genomic assays by combining primer selection with tag assignment. Experimental results on simulated data show that this integrated optimization leads to reductions of up to 50% in the number of required arrays.
Leveraging one-class SVM and semantic analysis to detect anomalous content

Experiments were conducted to test several hypotheses on methods for improving document classification for the malicious insider threat problem within the Intelligence Community. Bag-of-words (BOW) representations of documents were compared to Natural Language Processing (NLP) based representations in both the typical and one-class classification problems using the Support Vector Machine algorithm. Results show that the NLP features significantly improved classifier performance over the BOW approach both in terms of precision and recall, while using many fewer features. The one-class algorithm using NLP features demonstrated robustness when tested on new domains.
Action networks: a framework for reasoning about actions and change under uncertainty

This work proposes action networks as a semantically well founded framework for reasoning about actions and change under uncertainty. Action networks add two primitives to probabilistic causal networks: controllable variables and persistent variables. Controllable variables allow the representation of actions as directly setting the value of specific events in the domain, subject to preconditions. Persistent variables provide a canonical model of persistence according to which both the state of a variable and the causal mechanism dictating its value persist over time unless intervened upon by an action (or its consequences). Action networks also allow different methods for quantifying the uncertainty in causal relationships, which go beyond traditional probabilistic quantification. This paper describes both recent results and work in progress.
Management of information technology using analytic hierarchy process

Information technology (IT) outsourcing has become a common practice among firms who are doing everything possible to stay alive in today's highly competitive business environment. Since some types of information technology services can be used to enhance the firm's competitive position in the industry, firms are faced with the difficult task of deciding which services should be outsourced. In this paper, Analytic Hierarchy Process is proposed as a tool that can effectively handle the complex, qualitative decision variables involved in IT outsourcing decision making. Numerical examples are used to demonstrate that the attributes of this tool can be used to improve the decision quality.
The additionality impact of a matching grant program for small firms : experimental evidence from Yemen

Matching grants are one of the most common types of private sector development programs used in developing countries. But government subsidies to private firms can be controversial. A key question is that of additionality: do these programs get firms to undertake innovative activities that they would not otherwise do, or merely subsidize activities that would take place anyway? Randomized controlled trials can provide the counterfactual needed to answer this question, but efforts to experiment with matching grant programs have often failed. This paper uses a randomized controlled trial of a matching grant program for firms in the Republic of Yemen to demonstrate the feasibility of conducting experiments with well-designed programs, and to measure the additionality impact. In the first year, the matching grant is found to have led to more product innovation, firms upgrading their accounting systems, marketing more, making more capital investments, and being more likely to report their sales grew.
Exposing hidden alternative backbone conformations in X-ray crystallography using qFit

Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechain conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Overall, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.
Is Tobacco a Drug? Administrative Agencies as Common Law Courts

Professor Cass Sunstein argues that the FDA has the authority to regulate tobacco products. He considers the text of the Federal Food, Drug, and Cosmetic Act, which supports the FDA assertion, and the context of its enactment, which argues against the FDA. He resolves the tension between text and context in favor of FDA jurisdiction by turning to the emerging role of administrative agencies. In modern government, he contends, administrative agencies have become America's common law courts, with the power to adapt statutory regimes to new facts and new values when the underlying statute is ambiguous. Professor Sunstein's Article, like the other pieces in this volume, was written after the United States District Court for the Middle District of North Carolina decided Coyne Beahm v. FDA, but before a three judge panel of the United States Court of Appeals for the Fourth Circuit reversed that decision in Brown & Williamson Tobacco Corp. v. FDA. In Coyne Beahm, the District Court held that the Federal Food, Drug, and Cosmetic Act authorized the FDA to regulate tobacco products, but not tobacco advertising. The Fourth Circuit rejected the District Court's jurisdictional ruling and invalidated the FDA's regulations in their entirety. The Clinton Administration has since requested an en banc rehearing before the Fourth Circuit.
Nahm sums, stability and the colored Jones polynomial

Nahm sums are q-series of a special hypergeometric type that appear in character formulas in the conformal field theory, and give rise to elements of the Bloch group, and have interesting modularity properties. In our paper, we show how Nahm sums arise naturally in the quantum knot theory - we prove the stability of the coefficients of the colored Jones polynomial of an alternating link and present a Nahm sum formula for the resulting power series, defined in terms of a reduced diagram of the alternating link. The Nahm sum formula comes with a computer implementation, illustrated in numerous examples of proven or conjectural identities among q-series. Primary 57N10; Secondary 57M25.
Weighing the Facts A Systematic Review of Expected Patterns of Weight Loss in Full-Term, Breastfed Infants

All breastfeeding infants lose some weight in the early days of life. Conventionally, 5% to 7% loss of birth weight has been accepted as the normal and expected amount of weight loss before infants begin to gain weight steadily. When infants lose more than 7% of their birth weight, breastfeeding adequacy is sometimes questioned and formula supplementation is often given. Despite the fact that 5% to 7% is well known and commonly cited, little reliable evidence exists that supports use of this figure as a guide to practice. A systematic review of studies that focused on infant weight loss was conducted. The main objective was to determine the mean amount of weight loss for healthy, full-term exclusively breastfed infants after birth. One previous review and 9 primary studies published since 2008 were examined. The reported mean infant weight loss ranged widely among studies from 3.79% to 8.6%. The point at which most infants have lost the most amount of weight occurs 2 to 4 days after birth. Close examination of the studies, however, revealed significant methodological flaws in the research. Study limitations commonly included gaps in data collection, lack of documented feeding type, sample groups that lacked adequate numbers of exclusively breastfed infants, and the exclusion of breastfed infants who lost the most weight. Well-designed clinical studies that address these limitations are needed.
What is the Evidence for the Color Glass Condensate

I introduce the concept of the Color Glass Condensate. I review data from HERA and RHIC which suggest that such a universal form of matter has been found.
A method for modeling discontinuities in a microwave coaxial transmission line

A methodology for modeling discontinuities in a coaxial transmission line is presented. The method uses a non-linear least squares fit program to optimize the fit between a theoretical model and experimental data. When the method was applied for modeling discontinuities in a damaged S-band antenna cable, excellent agreement was obtained. >
Un-Straightening Boaz in Ruth Scholarship

Scholarly interpretations of Boaz’s sexuality in the book of Ruth largely assume that Boaz experiences sexual desires for Ruth specifically and for women generally. This essay will highlight the heterosexual bias that has commonly framed scholarly interpretations of Boaz and that imposes heterosexual attraction into the text. This essay illustrates that Boaz’s sexuality, far from an obvious aspect of the text, is largely produced through interpretive imagination. Although some scholars have questioned Ruth’s sexuality and her relationship with Naomi, Boaz’s sexuality has largely remained under-analyzed, leaving in place the assumption that the text is clear about his desires for women.
The character degree ratio and composition factors of a finite group

For a finite non-abelian group \(G\) let \({\mathrm {rat}}(G)\) denote the largest ratio of degrees of two nonlinear irreducible characters of \(G\). We prove that the number of non-abelian composition factors of \(G\) is bounded above by \(1.8\ln ({\mathrm {rat}}(G))+1.3\).