cssi/SciSciGPT-SciSciNet huggingface dataset:
MOB-ESP and other improvements in probability estimation

A key prerequisite to optimal reasoning under uncertainty in intelligent systems is to start with good class probability estimates. This paper improves on the current best probability estimation trees (Bagged-PETs) and also presents a new ensemble-based algorithm (MOB-ESP). Comparisons are made using several benchmark datasets and multiple metrics. These experiments show that MOB-ESP outputs significantly more accurate class probabilities than either the baseline B-PETs algorithm or the enhanced version presented here (EB-PETs). These results are based on metrics closely associated with the average accuracy of the predictions. MOB-ESP also provides much better probability rankings than B-PETs. The paper further suggests how these estimation techniques can be applied in concert with a broader category of classifiers.
On the automatic scoring of handwritten essays

Automating the task of scoring short handwritten student essays is considered. The goal is to assign scores which are comparable to those of human scorers by coupling two AI technologies: optical handwriting recognition and automated essay scoring. The test-bed is that of essays written by children in reading comprehension tests. The process involves several image-level operations: removal of pre-printed matter, segmentation of handwritten text lines and extraction of words. Recognition constraints are provided by the reading passage, the question and the answer rubric. Scoring is based on using a vector space model and machine learning of parameters from a set of human-scored samples. System performance is comparable to that of scoring based on perfect manual transcription.
Modeling potential species richness and urban buildout to identify mitigation sites along a California highway

One-foot resolution imagery is used to develop a detailed land cover map for part of Highway 99 in the San Joaquin Valley of California, US. The land cover map is used to model the probability of occurrence of 12 endangered or threatened species and as input to an urban growth model to examine the likelihood of development of every map unit. The combination of the two model predictions permits the categorization of every map unit with a potential endangered species richness index and predicted degree of development. Polygons with high potential endangered species richness were ranked according to the degree of development pressure. This planning approach is computationally intensive, but the input data are relatively easy to assemble, consisting of: a detailed, and fine-scale, land cover map; species presence locations; state-wide climate and landcover maps; a parcel ownership map; population growth projections; and a digital map of the county general plan.
Generic Network Interfaces for Plug and Play NoC Based Architecture

The emergence of the Network on chip (NoC) as a communication backbone for System on chip (SoC) based designs requires standardized interfaces for integrating IP (Intellectual Property) cores with diverse communication requirements. These interfaces have to be simple and generic for rapid plug and play implementation with minimal overhead. In this paper we describe the design and implementation of a programmable fabric based Network interface architecture. We have mapped the JPEG compression application on our architecture to demonstrate the feasibility of our design. The network interfaces seamlessly connect existing IP modules (Processor core, JPEG core, Memory core and UART core) to the NoC. The network, IP cores and the network interfaces are implemented on an FPGA device.
Making Sense of the Comprehensive Assessment

The European Central Bank (ECB) has finalized its comprehensive assessment of the solvency of the largest banks in the euro area and on October 26 disclosed the results of this assessment. In the present paper, Acharya and Steffen compare the outcomes of the ECB's assessment to their own benchmark stress tests conducted for 39 publically listed financial institutions that are also included in the ECB's regulatory review. The authors identify a negative correlation between their benchmark estimates for capital shortfalls and the regulatory capital shortfall, but a positive correlation between their benchmark estimates for losses under stress both in the banking book and in the trading book. They conclude that the regulatory stress test outcomes are potentially heavily affected by discretion of national regulators in measuring what is capital, and especially the use of risk-weighted assets in calculating the prudential capital requirement.
CVC Lite: A new implementation of the cooperating validity checker: Category B

We describe a tool called CVC Lite (CVCL), an automated theorem prover for formulas in a union of first-order theories. CVCL supports a set of theories which are useful in verification, including uninterpreted functions, arrays, records and tuples, and linear arithmetic. New features in CVCL (beyond those provided in similar previous systems) include a library API, more support for producing proofs, some heuristics for reasoning about quantifiers, and support for symbolic simulation primitives.
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes

Stochastic Gradient Descent (SGD) is one of the simplest and most popular stochastic optimization methods. While it has already been theoretically studied for decades, the classical analysis usually required non-trivial smoothness assumptions, which do not apply to many modern applications of SGD with non-smooth objective functions such as support vector machines. In this paper, we investigate the performance of SGD without such smoothness assumptions, as well as a running average scheme to convert the SGD iterates to a solution with optimal optimization accuracy. In this framework, we prove that after T rounds, the suboptimality of the last SGD iterate scales as O(log(T)/√T) for non-smooth convex objective functions, and O(log(T)/T) in the non-smooth strongly convex case. To the best of our knowledge, these are the first bounds of this kind, and almost match the minimax-optimal rates obtainable by appropriate averaging schemes. We also propose a new and simple averaging scheme, which not only attains optimal rates, but can also be easily computed on-the-fly (in contrast, the suffix averaging scheme proposed in Rakhlin et al. (2011) is not as simple to implement). Finally, we provide some experimental illustrations.
MICC: A TOOL FOR COMPUTING SHORT DISTANCES IN THE CURVE COMPLEX

Abstract The complex of curves C ( S g ) of a closed orientable surface of genus g ≥ 2 is the simplicial complex whose vertices, C 0 ( S g ) , are isotopy classes of essential simple closed curves in S g . Two vertices co-bound an edge of the 1-skeleton, C 1 ( S g ) , if there are disjoint representatives in S g . A metric is obtained on C 0 ( S g ) by assigning unit length to each edge of C 1 ( S g ) . Thus, the distance between two vertices, d ( v , w ) , corresponds to the length of a geodesic—a shortest edge-path between v and w in C 1 ( S g ) . In Birman et al. (2016) , the authors introduced the concept of efficient geodesics in C 1 ( S g ) and used them to give a new algorithm for computing the distance between vertices. In this note, we introduce the software package MICC (Metric in the Curve Complex), a partial implementation of the efficient geodesic algorithm. We discuss the mathematics underlying MICC and give applications. In particular, up to an action of an element of the mapping class group, we give a calculation which produces all distance 4 vertex pairs for g = 2 that intersect 12 times, the minimal number of intersections needed for this distance and genus.
Solving ptychography with a convex relaxation

Ptychography is a powerful computational imaging technique that transforms a collection of low-resolution images into a high-resolution sample reconstruction. Unfortunately, algorithms that currently solve this reconstruction problem lack stability, robustness, and theoretical guarantees. Recently, convex optimization algorithms have improved the accuracy and reliability of several related reconstruction efforts. This paper proposes a convex formulation of the ptychography problem. This formulation has no local minima, it can be solved using a wide range of algorithms, it can incorporate appropriate noise models, and it can include multiple a priori constraints. The paper considers a specific algorithm, based on low-rank factorization, whose runtime and memory usage are near-linear in the size of the output image. Experiments demonstrate that this approach offers a 25% lower background variance on average than alternating projections, the ptychographic reconstruction algorithm that is currently in widespread use.
A Probabilistic Analysis of Marker-Passing Techniques for Plan Recognition

Useless paths are a chronic problem for marker-passing techniques. We use a probabilistic analysis to justify a method for quickly identifying and rejecting useless paths. Using the same analysis, we identify key conditions and assumptions necessary for marker-passing to perform well.
SWITCH: a novel approach to ensemble learning for heterogeneous data

The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image classification, the training data are often collected from multiple sources and heterogeneous. Ensemble learning is a proven effective approach to heterogeneous data, which uses multiple classification models to capture the diverse aspects of heterogeneous data. If an ensemble can learn the relationship between different portions of data and their corresponding models, the ensemble can selectively apply models to unseen data according to the learned relationship. We propose a novel approach to enable the learning of the relationships between data and models by creating a set of 'switches' that can route a testing instance to appropriate classification models in an ensemble. Our empirical study on both real-world data and benchmark data shows that the proposed approach to ensemble learning can achieve significant performance improvement for heterogeneous data.
Improving quantum clocks via semidefinite programming

The accuracies of modern quantum logic clocks have surpassed those of standard atomic fountain clocks. These clocks also provide a greater degree of control, because before and after clock queries, we are able to apply chosen unitary operations and measurements. Here, we take advantage of these choices and present a numerical technique designed to increase the accuracy of these clocks. We use a greedy approach, minimizing the phase variance of a noisy classical oscillator with respect to a perfect frequency standard after an interrogation step; we do not optimize over successive interrogations or the probe times. We consider arbitrary prior frequency knowledge and compare clocks with varying numbers of ions and queries interlaced with unitary control. Our technique is based on the semidefinite programming formulation of quantum query complexity, a method first developed in the context of deriving algorithmic lower bounds. The application of semidefinite programming to an inherently continuous problem like that considered here requires discretization; we derive bounds on the error introduced and show that it can be made suitably small.
MISCIBILITY CALCULATIONS FOR WATER AND HYDROGEN IN GIANT PLANETS

We present results from ab initio simulations of liquid water?hydrogen mixtures in the range from 2 to 70 GPa and from 1000 to 6000 K, covering conditions in the interiors of ice giant planets and parts of the outer envelope of gas giant planets. In addition to computing the pressure and the internal energy, we derive the Gibbs free energy by performing a thermodynamic integration. For all conditions under consideration, our simulations predict hydrogen and water to mix in all proportions. The thermodynamic behavior of the mixture can be well described with an ideal mixing approximation. We suggest that a substantial fraction of water and hydrogen in giant planets may occur in homogeneously mixed form rather than in separate layers. The extent?of mixing depends on the planet?s interior dynamics and its conditions of formation, in particular on how much hydrogen was present when icy planetesimals were delivered. Based on our results, we do not predict water?hydrogen mixtures to phase separate during any stage of the evolution of giant planets. We also show that the hydrogen content of an exoplanet is much higher if the mixed interior is assumed.
Neuronal control of locomotor handedness in Drosophila

Genetically identical individuals display variability in their physiology, morphology, and behaviors, even when reared in essentially identical environments, but there is little mechanistic understanding of the basis of such variation. Here, we investigated whether Drosophila melanogaster displays individual-to-individual variation in locomotor behaviors. We developed a new high-throughout platform capable of measuring the exploratory behavior of hundreds of individual flies simultaneously. With this approach, we find that, during exploratory walking, individual flies exhibit significant bias in their left vs. right locomotor choices, with some flies being strongly left biased or right biased. This idiosyncrasy was present in all genotypes examined, including wild-derived populations and inbred isogenic laboratory strains. The biases of individual flies persist for their lifetime and are nonheritable: i.e., mating two left-biased individuals does not yield left-biased progeny. This locomotor handedness is uncorrelated with other asymmetries, such as the handedness of gut twisting, leg-length asymmetry, and wing-folding preference. Using transgenics and mutants, we find that the magnitude of locomotor handedness is under the control of columnar neurons within the central complex, a brain region implicated in motor planning and execution. When these neurons are silenced, exploratory laterality increases, with more extreme leftiness and rightiness. This observation intriguingly implies that the brain may be able to dynamically regulate behavioral individuality.
CRITICAL ECONOMIC FACTORS FOR SUCCESS OF A BIOMASS CONVERSION PLANT FOR AGRICULTURAL RESIDUE, YARD RESIDUE AND WOOD WASTE IN FLORIDA

Abstract: This model evaluates the potential success of a cellulosic ethanol plant in Florida. Critical Economic factors of the plant were simulated to assess the ability of this project. These critical factors include the feedstock to be used, the cost of the facility, transportation costs and the discount rate for the net present value (NPV). Results and observations are presented in this paper. Introduction The US Government has encouraged research and development of an advanced biofuelsindustry to help offset the inputs of ethanol production on food produced from feed grain. These advanced biofuels, also called second generation biofuels, include cellulosic ethanol, biohydrogen, Butanol, biomethanol and others. Cellulosic ethanol production is now in the advanced stage of development and is soon to be commercialized (Ingram, 2005). There has been considered research on cellulosic ethanol production because feedstock for the biofuel can be found throughout the US from a variety of fibrous organic materials. These materials include newly developed energy crops, agricultural residue, wood residue and municipal solid waste (MSW).
Kirwan-Novikov inequalities on a manifold with boundary

We extend the Novikov Morse-type inequalities for closed 1-forms in 2 directions. First, we consider manifolds with boundary. Second, we allow a very degenerate structure of the critical set of the form, assuming only that the form is non-degenerated in the sense of Kirwan. In particular, we obtain a generalization of a result of Floer about the usual Morse inequalities on a manifold with boundary. We also obtain an equivariant version of our inequalities. Our proof is based on an application of the Witten deformation technique. The main novelty here is that we consider the neighborhood of the critical set as a manifold with a cylindrical end. This leads to a considerable simplification of the local analysis. In particular, we obtain a new analytic proof of the Morse-Bott inequalities on a closed manifold.
Optimizing classification ensembles via a genetic algorithm for a web-based educational system

Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy. Feature extraction aims to reduce the computational cost of feature measurement, increase classifier efficiency, and allow greater classification accuracy based on the process of deriving new features from the original features. This paper represents an approach for classifying students in order to predict their final grades based on features extracted from logged data in an educational web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. By weighing feature vectors representing feature importance using a Genetic Algorithm (GA) we can optimize the prediction accuracy and obtain a marked improvement over raw classification. We further show that when the number of features is few, feature weighting and transformation into a new space works efficiently compared to the feature subset selection. This approach is easily adaptable to different types of courses, different population sizes, and allows for different features to be analyzed.
Scalable Group Rekeying for Secure Multicast: A Survey

Many group key management approaches have been recently proposed for providing scalable group rekeying to support secure communications for large and dynamic groups. We give an overview of these approaches and show the research trends. Finally, we discuss some new research directions on this subject.
Performance analysis and fault tolerance of randomized routing on Clos networks

Beside universality and very low latency, Youssef's randomized self-routing algorithms [25] have high tolerance for multiple faults and more strikingly have the potential for fault tolerance without diagnosis. In this paper we study the performance of Youssef's routing algorithms for faulty Clos networks in the presence of multiple faults in multiple columns with and without fault detection. We show that with fault detection and diagnosis, randomized routing algorithms provide scalable, very efficient and fault tolerant routing mechanisms. Without fault detection and diagnosis, randomized routing provides good fault tolerance for faulty switches in either the first or the second column. The delays become large for faults in the third column or for faults in more than one column. In conclusion, randomized routing enables the system to run without periodic fault detection/diagnosis, and if and when the performance degrades beyond a certain threshold, diagnosis can be performed to improve the routing performance.
Research in spirituality, religion, and work: Walking the line between relevance and legitimacy

While spirituality and religion in work (SRW) as an inquiry field has been gaining interest in the popular press, it has only recently been recognized by the academic community. Consequently, its relevance to important research and its legitimacy in contributing scholarly work is not ensured. Part of the problem is that many SRW concepts resist being tested with “approved” positivist research models. This paper explores the tension between relevance and legitimacy, focusing on research methods, models, and traditions that may serve both well. It suggests that many methodologies and traditions that support such work already exist. It discusses some of these methods and offers operational blueprints for alternative forms of excellent research. It argues that combining such methodological underpinnings with experimental models and new forms of data representation allows for scholarly work to emerge, thus facilitating SRW's desire to stay true to important research questions while respecting sound research traditions.
Agents in Electronic Commerce: Component Technologies for Automated Negotiation and Coalition Formation

Automated negotiation and coalition formation among self-interested agents are playing an increasingly important role in electronic commerce. Such agents cannot be coordinated by externally imposing their strategies. Instead the interaction protocols have to be designed so that each agent is motivated to follow the strategy that the protocol designer wants it to follow. This paper reviews six component technologies that we have developed for making such interactions less manipulable and more efficient in terms of the computational processes and the outcomes: 1. OCSM-contracts in marginal cost based contracting, 2. leveled commitment contracts, 3. anytime coalition structure generation with worst case guarantees, 4. trading off computation cost against optimization quality within each coalition, 5. distributing search among insincere agents, and 6. unenforced contract execution. Each of these technologies represents a different way of battling self-interest and combinatorial complexity simultaneously. This is a key battle when multi-agent systems move into large-scale open settings.
Measurements of Agricultural Productivity and Efficiency Gains from NAFTA

The primary objective of this study is to empirically determine whether North American Free Trade Agreement (NAFTA) has contributed to increased agricultural productivity in any of its member countries. Implementation of the NAFTA began on January 1, 1994. This agreement removed most barriers to trade and investment among the United States, Canada, and Mexico, in which all non-tariff barriers to agricultural trade between these countries were eliminated. Data Envelopment Analysis (DEA) and the Malmquist Productivity Index were used to estimate the total factor productivity change, technical change, and efficiency change of agricultural production for each NAFTA country. Then, using time series data, the efficiency changes in countries were compared to determine whether NAFTA has been beneficial to the agricultural sector of a member country. , Total factor productivity, technical change, and efficiency change of agricultural production in NAFTA countries were analyzed for the period 1980-2007, and then a comparison between pre- and post-NAFTA periods was also made. In the analysis, aggregate agricultural production was used as the output, and five variables were considered as the inputs, which included: land, labor, capital, fertilizer and livestock. The results revealed that the average annual total factor productivity increased by 1.6 percent during the 1980-2007 period for NAFTA countries, mainly coming from technical change. Total factor productivity did not change obviously during the pre-NAFTA period. In contrast, it increased by 2.7 percent due to technical improvements in post-NAFTA period. Consequently, it is noticeable that compared to the pre-NAFTA period, the countries especially Mexico performed better by achieving higher levels of productivity in agricultural production.
Through the Pruneyard Coherently: Resolving the Collision of Private Property Rights and Nonemployee Union Access Claims

Since the enactment of the NLRA, courts, legislatures, the National Labor Relations Board, and commentators have all confronted the issue of nonemployee union access to private property. While some United States Supreme Court decisions have stated that Babcock & Wilcox and its progeny have struck the right balance, many commentators argue and some NLRB decisions imply-that courts have too frequently engaged in constrained decisionmaking that eviscerates the goals of collective bargaining, workplace democracy, "egalitarianism" and "solidarity." Since the Pruneyard case, states increasingly have been called upon to confront poignant claims for enlarged access to private property based on freedom of expression rights. Unsurprisingly, many labor commentators, state courts, and some NLRB decisions have seized upon putative freedom of expression rights as a vehicle 1) to restrict property owners' right to exclude and 2) to enhance the "common good". To the contrary, public choice analysis indicates that the common good and the larger interest are not served by uncompensated expansions of nonemployee access. Public choice examination suggests that, as our laws and legal institutions embrace expanded nonemployee access, the likelihood of error, confusion, and incoherence rise. Moreover, since exclusive possession increases efficiency and productivity, restricting the right to exclude has a negative effect on the larger interest while, assuredly, regressively redistributing benefits in favor of a small, relatively affluent special interest group at the expense of groups such as nonunion workers, unemployed workers, consumers, and taxpayers who are relatively less affluent. This, of course, reaffirms the quintessential public choice conclusion that the "relevant difference between markets and politics does not lie in the kinds of values/interests that persons pursue but in the conditions under which they pursue their various interests.' Accordingly, restricting property owners' rights to exclude can be seen as a "blatant injustice." While it is perhaps chimerical to believe that advocates of expanded access will be concerned by this "injustice," the United States Supreme Court, by deploying a principled conception of private property rights precluding uncompensated takings of the right to exclude, can return justice, equity, and coherence to the Pruneyard, and thereby enhance the common good.
Inferring selective constraint from population genomic data suggests recent regulatory turnover in the human brain

The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely missed by searching for sequence conservation across species. Here we present an analysis based on variation data among human genomes that utilizes a supervised machine learning approach for the identification of human-specific purifying selection in the genome. Using only allele frequency information from the complete low-coverage 1000 Genomes Project data set in conjunction with a support vector machine trained from known functional and nonfunctional portions of the genome, we are able to accurately identify portions of the genome constrained by purifying selection. Our method identifies previously known human-specific gains or losses of function and uncovers many novel candidates. Candidate targets for gain and loss of function along the human lineage include numerous putative regulatory regions of genes essential for normal development of the central nervous system, including a significant enrichment of gain of function events near neurotransmitter receptor genes. These results are consistent with regulatory turnover being a key mechanism in the evolution of human-specific characteristics of brain development. Finally, we show that the majority of the genome is unconstrained by natural selection currently, in agreement with what has been estimated from phylogenetic methods but in sharp contrast to estimates based on transcriptomics or other high-throughput functional methods.
Labor Markets and Income Generation in Rural Argentina

This paper addresses three areas of the rural labor market-employment, labor wages, and agriculture producer incomes. Findings show that the poor allocate a lower share of their labor to farm sectors than the nonpoor do, but still around 70 percent work in agriculture, and the vast majority of rural workers are engaged in the informal sector. When examining nonfarm employment in rural Argentina, findings suggest that key determinants of access to employment and productivity in nonfarm activities are education, skills, land access, location, and gender. Employment analyses show that women have higher probability than men to participate in rural nonfarm activities and they are not confined to low-return employment. Moreover, workers living in poorer regions with land access are less likely to be employed in the nonfarm sector. There is strong evidence that educated people have better prospects in both the farm and nonfarm sectors, and that education is an important determinant of employment in the better-paid nonfarm activities. Labor wage analyses reveal that labor markets pay lower returns to poorer than to richer women and returns to education are increasing with increased level of completed education and income level. And nonfarm income and employment are highly correlated with gender, skills, household size, and education. This analysis also shows a rather heterogeneous impact pattern of individual characteristics across the income distribution, but education is important for all levels of income. Agricultural producer income analyses reveal that producers' income monotonically increases with land size and with completed education level, and positively correlates with road access and use of electricity, fertilizer, and irrigation. Finally, farms operated by women are slightly more productive than farms operated by men.
Exact inference in networks with discrete children of continuous parents

Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditional linear Gaussian (CLG) networks, where the conditional distribution of the continuous variables given an assignment to the discrete variables is a multivariate Gaussian. Lauritzen's extension to the clique tree algorithm can be used for exact inference in CLG networks. However, many domains include discrete variables that depend on continuous ones, and CLG networks do not allow such dependencies to be represented. In this paper, we propose the first "exact" inference algorithm for augmented CLG networks -- CLG networks augmented by allowing discrete children of continuous parents. Our algorithm is based on Lauritzen's algorithm, and is exact in a similar sense: it computes the exact distributions over the discrete nodes, and the exact first and second moments of the continuous ones, up to inaccuracies resulting from numerical integration used within the algorithm. In the special case of softmax CPDs, we show that integration can often be done efficiently, and that using the first two moments leads to a particularly accurate approximation. We show empirically that our algorithm achieves substantially higher accuracy at lower cost than previous algorithms for this task.
Plan development using local probabilistic models

Approximate models of world state transitions are necessary when building plans for complex systems operating in dynamic environments. External event probabilities can depend on state feature values as well as time spent in that particular state. We assign temporally-dependent probability functions to state transitions. These functions are used to locally compute state probabilities, which are then used to select highly probable goal paths and eliminate improbable states. This probabilistic model has been implemented in the Cooperative Intelligent Real-time Control Architecture (CIRCA), which combines an AI planner with a separate real-time system such that plans are developed, scheduled, and executed with real-time guarantees. We present flight simulation tests that demonstrate how our probabilistic model may improve CIRCA performance.
Algebra of dimension theory

The dimension algebra of graded groups is introduced. With the help of known geometric results of extension theory, this algebra induces all known results of the cohomological dimension theory. Elements of the algebra are equivalence classes dim(A) of graded groups A. There are two geometric interpretations of these equivalence classes: 1) For pointed CW complexes K and L, dim(H * (K)) = dim(H * (L)) if and only if the infinite symmetric products SP(K) and SP(L) are of the same extension type (i.e., SP(K) ∈ AE(X) iff SP(L) ∈ AE(X) for all compact X). 2) For pointed compact spaces X and Y, dim(H - *(X)) = dim(Η - *(Y)) if and only if X and Y are of the same dimension type (i.e., dim G (X) = dim G (Y) for all Abelian groups G). Dranishnikov's version of the Hurewicz Theorem in extension theory becomes dim(π*(K)) = dim(H * (K)) for all simply connected K. The concept of cohomological dimension dim A (X) of a pointed compact space X with respect to a graded group A is introduced. It turns out dim A (X) ≤ 0 iff dim A(n) (X) ≤ n for all n ∈ Z. If A and B are two positive graded groups, then dim(A) = dim(B) if and only if dim A (X) = dim B (X) for all compact X.
INTERNATIONAL BUSINESS CYCLE SYNCHRONIZATION IN HISTORICAL PERSPECTIVE

We analyze the changes in business cycle synchronization among 16 industrial countries the over the past century and a quarter, demarcated into four exchange rate regimes. We find a secular trend towards increased synchronization for much of the twentieth century that has occurred across diverse exchange rate regimes. This finding contrasts with the mixed results reported in the recent literature, which has focused on the evidence for the past 20 or 30 years. Examining the role of global shocks and shock transmission in the rising synchronization, we find that global (common) shocks generally are the dominant influence.
Failure detection and isolation in integrator networks

Detection and isolation of link failures in directed networks of LTI systems have been the focus of our previous study. Our results relate the failure of links in the network to jump discontinuities in the derivatives of the output responses of the nodes and exploit this relation to propose failure detection and isolation (FDI) techniques, accordingly. In this work, we consider these results in the context of single-integrator networked dynamics, and show that with the additional niceties of the integrator networks and the enhanced proofs, one is able to incorporate both unidirectional and bidirectional link failures in our FDI algorithms. Computer experiments with large networks and both directed and undirected topologies provide interesting insights as to the role of directionality, as well as the scalability of the proposed FDI techniques with the network size.
13. Soft X-Ray Fluorescence Spectroscopy

Publisher Summary This chapter discusses the characteristic features of soft x-ray fluorescence (SXF) spectroscopy, specialized spectrometers and detectors that have been developed for measuring very weak spectra, and some typical experimental results. X-ray fluorescence spectra are produced when x-rays are used to excite characteristic x-ray emission spectra of a particular element. Very low yields for radiative transitions in the soft x-ray spectral range made SXF impractical before the advent of powerful synchrotron sources. Consequently, the history of SXF spectroscopy is provided by the measurement of soft x-ray emission (SXE) spectra excited by energetic electrons. Soft x-rays are strongly absorbed requiring windowless operation from a source to sample to spectrometer and detector and the use of reflective optics. Normal incidence reflectance is very low, requiring the use of grazing incidence optics and the accommodation or correction of the large aberrations that this implies. The single most important constraint on SXF spectroscopy, however, is the low radiative yield, which results from the fact that holes in shallow core levels are filled more efficiently by nonradiative than by radiative processes. This fact prevented the development of intense conventional sources using e-beam excitation and limited the development of SXE spectroscopies before the advent of modern synchrotron sources. Another major advantage of photon excitation of emission spectra is that it eliminates the bremsstrahlung background radiation associated with the scattering of energetic electrons.
Approximating MAP using Local Search

MAP is the problem of finding a most probable instantiation of a set of variables in a Bayesian network, given (partial) evidence about the complement of that set. Unlike computing priors, posteriors, and MPE (a special case of MAP), the time and space complexity of MAP is not only exponential in the network treewidth, but also in a larger parameter known as the "constrained" treewidth. In practice, this means that computing MAP can be orders of magnitude more expensive than computing priors, posteriors or MPE. For this reason, MAP computations are generally avoided or approximated by practitioners. We have investigated the approximation of MAP using local search. The local search method has a space complexity which is exponential only in the network treewidth, as is the complexity of each step in the search process. Our experimental results show that local search provides a very good approximation of MAP, while requiring a small number of search steps. Practically, this means that the average case complexity of local search is often exponential only in treewidth as opposed to the constrained treewidth, making approximating MAP as efficient as other computations.
Maximal singular loci of Schubert varieties in $SL(n)/B$

Schubert varieties in the flag manifold SL(n)/B play a key role in our understanding of projective varieties. One important problem is to determine the locus of singular points in a variety. In 1990, Lakshmibai and Sandhya showed that the Schubert variety X w is nonsingular if and only if w avoids the patterns 4231 and 3412. They also gave a conjectural description of the singular locus of X w . In 1999, Gasharov proved one direction of their conjecture. In this paper we give an explicit combinatorial description of the irreducible components of the singular locus of the Schubert variety X w for any element w ∈ G n . In doing so, we prove both directions of the Lakshmibai-Sandhya conjecture. These irreducible components are indexed by permutations which differ from w by a cycle depending naturally on a 4231 or 3412 pattern in w. Our description of the irreducible components is computationally more efficient (O(n 6 )) than the previously best known algorithms, which were all exponential in time. Furthermore, we give simple formulas for calculating the Kazhdan-Lusztig polynomials at the maximum singular points.
Intracluster Planetary Nebulae as Probes of Intracluster Starlight

I review the progress in research on Intracluster Planetary Nebulae (IPN). Hundreds of IPN candidates have now been found in the Virgo and Fornax galaxy clusters, and searches of two nearby galaxy groups have been made. From the results thus far, approximately 10–20% of all stars in Virgo and Fornax are in an intracluster component, but there are few such stars in galaxy groups. From the spatial distribution of IPN, it appears that the intracluster stars are clustered, in agreement with tidal-stripping scenarios. In Virgo, the IPN have a large line-of-sight depth, which implies that the bulk of intracluster stars in this cluster derive from late-type galaxies and dwarfs. I also discuss other important developments in IPN research such as the detection of intracluster H II regions, a possible detection of IPN in the Coma Cluster, and future observational and theoretical developments.
Mission strategy for cometary exploration in the 1980's

A specific plan for a sequence of cometary intercept missions in the 1980's is reported. Each mission is described in detail and the supporting role of ground based cometary observations is included. Only three launches are required in the proposed mission sequence for six cometary encounters with comets Encke, Giacobini-Zinner, Borrelly and Halley. Cometary ephemerics errors are reduced to very small values because of a favorable earth-comet orbital geometry for Encke 1980, and excellent earth based sighting conditions exist for the entire 1985 mission set.
Noise threshold for a fault-tolerant two-dimensional lattice architecture

We consider a model of quantum computation in which the set of operations is limited to nearest-neighbor interactions on a 2D lattice. We model movement of qubits with noisy SWAP operations. For this architecture we design a fault-tolerant coding scheme using the concatenated [7, 1, 3] Steane code. Our scheme is potentially applicable to ion-trap and solid-state quantum technologies. We calculate a lower bound on the noise threshold for our local model using a detailed failure probability analysis. We obtain a threshold of 1.85×10-5 for the local setting, where memory error rates are one-tenth of the failure rates of gates, measurement, and preparation steps. For the analogous nonlocal setting, we obtain a noise threshold of 3.61 × 10-5. Our results thus show that the additional SWAP operations required to move qubits in the local model affect the noise threshold only moderately.
A wall-crossing formula for the signature of symplectic quotients

We use symplectic cobordisrn, and the localization result of Ginzburg, Guillemin, and Karshon to find a wall-crossing formula for the signature of regular symplectic quotients of Hamiltonian torus actions. The formula is recursive, depending ultimately on fixed point data. In the case of a circle action, we obtain a formula for the signature of singular quotients as well. We also show how formulas for the Poincar6 polynomial and the Euler characteristic (equivalernt to those of Kirwan can be expressed in the same recursive manner.
On explicit parametrisation of spectral curves for Moser-Calogero particles and its applications

The system of $N$ classical particles on the line with the Weierstrass $\wp$ function as potential is known to be completely integrable. Recently D'Hoker and Phong found a beautiful parameterization by the polynomial of degree $N$ of the space of Riemann surfaces associated with this system. In the trigonometric limit of the elliptic potential these Riemann surfaces degenerate into rational curves. The D'Hoker-Phong polynomial in the limit describes the intersection points of the rational curves. We found an explicit determinant representation of the polynomial in the trigonometric case. We consider applications of this result to the theory of Toeplitz determinants and to geometry of the spectral curves. We also prove our earlier conjecture on the asymptotic behavior of the ratio of two symplectic volumes when the number of particles tends to infinity.
Predicate Abstraction for Linked Data Structures

We present Alias Refinement Types Art, a new approach that uses predicate-abstraction to automate the verification of correctness properties of linked data structures. While there are many techniques for checking that a heap-manipulating program adheres to its specification, they often require that the programmer annotate the behavior of each procedure, for example, in the form of loop invariants and pre- and post-conditions. We introduce a technique that lifts predicate abstraction to the heap by factoring the analysis of data structures into two orthogonal components: 1i¾?Alias Types, which reason about the physical shape of heap structures, and 2i¾?Refinement Types, which use simple predicates from an SMT decidable theory to capture the logical or semantic properties of the structures. We evaluate Art by implementing a tool that performs type inference for an imperative language, and empirically show, using a suite of data-structure benchmarks, that Art requires only 21i¾?% of the annotations needed by other state-of-the-art verification techniques.
Kenya's quest for growth stabilization and reforms - but political stability ?

Kenya has long had a reputation of being politically risky, manifested in corruption, uncertainty about policies, and the importance of political connections in doing business. Kenya began its economic liberalization in 1993. Reform picked up speed after a tightening of aid by donors on governance grounds and an attempt to re-establish credibility following the costly Goldenberg scandal uncovered in 1992. But tangible results in the shape of favorable government debt dynamics and a pick up in growth took a decade to materialize. The paper argues that the peaceful presidential election and transfer of power in December 2002 was central to the economic upswing after 2002. The subsequent decline in political risk was singled out by the private sector as an important development. The paper draws on an analysis of debt dynamics, the evolution of domestic interest rates, and the latest Investment Climate Assessment to present evidence on the criticality of low political risk in facilitating good economic outcomes after 2003. The December 2007 elections have highlighted other aspects of political risk - ethnic and social tensions with roots in inequality. The findings of this paper underline the importance of establishing a foundation for long-term political stability and social cohesion in view of the disruptions following the December 2007 elections. This process is likely to be at least as difficult and lengthy as fundamental economic policy and institutional reform.
Integrating qualitative methods into investment climate impact evaluations

Incorporating qualitative methods into the evaluation of development programs has become increasingly popular in recent years, both for the distinctive insights such approaches can bring in their own right and because of their capacity to complement the strengths -- and where necessary correct some of the weaknesses -- of quantitative approaches. Some initial work deploying mixed methods has been undertaken in the assessment of investment climate reforms, but considerable room for expansion exists. This paper summarizes some of the key principles and practices underpinning mixed methods evaluations in development, highlight some notable examples of how such work has been conducted (and the particular contributions it has made), and offers some guidelines for those seeking to increase the sophistication and utility of qualitative methods in the evaluation of investment climate reforms.
Conversion From Tacrolimus to Belatacept to Prevent the Progression of Chronic Kidney Disease in Pancreas Transplantation: Case Report of Two Patients

Belatacept is a novel immunosuppressive agent that may be used as an alternative to calcineurin inhibitors (CNI) in immunosuppression (IS) regimens. We report two cases of pancreas transplant that were switched from tacrolimus (TAC) to belatacept. Case 1: 38-year-old female with pancreas transplant alone maintained on TAC-based IS regimen whose serum creatinine (SCr) slowly deteriorated from 0.6 mg/dL at baseline to 2.2 mg/dL, 16 months posttransplant. A native kidney biopsy performed showed CNI toxicity. The patient was started on belatacept and TAC was eliminated. Case 2: 49-year-old female with simultaneous pancreas–kidney transplant, maintained on TAC-based regimen where the SCr worsened over an initial 3-month period from a baseline of 1.0 to 3.0 mg/dL. Belatacept was started and TAC was lowered. Due to persistent graft dysfunction and kidney transplant biopsy still showing changes consistent with CNI toxicity, the TAC was then discontinued. At >1 year postbelatacept and off TAC follow-up, kidney function as measured by SCr remains stable at 1.0 ± 0.2 mg/dL in both recipients. Neither patient developed rejection following the switch, and pancreas allograft function remains stable in both recipients.
How Bribery Distorts Firm Growth : Differences by Firm Attributes

How corruption affects economic performance has been studied for over a decade. Yet the lack of detailed firm-level data has limited research regarding who is carrying the real burden of corruption. This study shows that for firms in the Latin America and Caribbean region, bribery significantly distorts firm growth. Firms that pay bribes when conducting business transactions -- such as applying for permits, electricity, or water connections -- have 24 percent lower annual sales growth than firms that do not face such solicitations. Moreover, these distortions are more severe for low-revenue-generating and young firms. Using the instrumental variables method, the authors show that these results are robust to different specifications and the use of different sub-samples.