cssi/SciSciGPT-SciSciNet huggingface dataset:
Patch-Based Image Hallucination for Super Resolution With Detail Reconstruction From Similar Sample Images

Image hallucination and super-resolution have been studied for decades, and many approaches have been proposed to upsample low-resolution images using information from the images themselves, multiple example images, or large image databases. However, most of this work has focused exclusively on small magnification levels because the algorithms simply sharpen the blurry edges in the upsampled images – no actual new detail is typically reconstructed in the final result. In this paper, we present a patch-based algorithm for image hallucination which, for the first time, properly synthesizes novel high frequency detail. To do this, we pose the synthesis problem as a patch-based optimization which inserts coherent, high-frequency detail from contextually-similar images of the same physical scene/subject provided from either a personal image collection or a large online database. The resulting image is visually plausible and contains coherent high frequency information. We demonstrate the robustness of our algorithm by testing it on a large number of images and show that its performance is considerably superior to all state-of-the-art approaches, a result that is verified to be statistically significant through a randomized user study.
Captive-rearing duration may be more important than environmental enrichment for enhancing turtle head-starting success

Abstract Raising captive animals past critical mortality stages for eventual release (head-starting) is a common conservation tactic. Counterintuitively, post-release survival can be low. Post-release behavior affecting survival could be influenced by captive-rearing duration and housing conditions. Practitioners have adopted environmental enrichment to promote natural behaviors during head-starting such as raising animals in naturalistic enclosures. Enrichment might be especially beneficial for animals held in captivity long-term to prevent degradation of adaptive behaviors. Using 32 captive-born turtles (Terrapene carolina), half of which were raised in enriched enclosures, we employed a factorial design to explore how enrichment and rearing duration affected post-release growth, behavior, and survival. Six turtles in each treatment (enriched or unenriched) were head-started for nine months (cohort one). Ten turtles in each treatment were head-started for 21 months (cohort two). At the conclusion of captive-rearing, turtles in cohort two were overall larger than cohort one, but unenriched turtles were generally larger than enriched turtles within each cohort. Once released, enriched turtles grew faster than unenriched turtles in cohort two, but we otherwise found minimal evidence suggesting enrichment affected post-release survival or behavior. Cohort two dispersed farther and had generally higher active season survival than cohort one (0.50 vs. 0.33). Body mass was positively associated with daily survival probability. Our findings suggest attaining larger body sizes from longer captive-rearing periods to enable greater movement and alleviate susceptibility to predation (the primary cause of death) could be more effective than environmental enrichment alone in chelonian head-starting programs where substantial predation could hinder success.
Developmental changes in the ability to draw distinctive features of object categories

How do children’s visual concepts change across childhood, and how might these changes be reflected in their drawings? Here we investigate developmental changes in children’s ability to emphasize the relevant visual distinctions between object categories in their drawings. We collected over 13K drawings from children aged 2-10 years via a free-standing drawing station in a children’s museum. We hypothesized that older children would produce more recognizable drawings, and that this gain in recognizability would not be entirely explained by concurrent development in visuomotor control. To measure recognizability, we applied a pretrained deep convolutional neural network model to extract a high-level feature representation of all drawings, and then trained a multi-way linear classifier on these features. To measure visuomotor control, we developed an automated procedure to measure their ability to accurately trace complex shapes. We found consistent gains in the recognizability of drawings across ages that were not fully explained by children’s ability to accurately trace complex shapes. Furthermore, these gains were accompanied by an increase in how distinct different object categories were in feature space. Overall, these results demonstrate that children’s drawings include more distinctive visual features as they grow older.
Reliability Growth Testing

Reliability growth is the process by which the reliability problems of a product are identified and corrected by introducing modifications in the product design and/or manufacturing process. Accordingly, the reliability of the product grows as the product goes through successive stages of the development program. Although reliability growth generally refers to improvements in a product's reliability, a very important field where reliability growth programs can find large application is the control of industrial accidents. We discuss a number of stochastic models that are able to describe the reliability growth, either when improvement actions are introduced at failure occurrence (test-analyze-and-fix program), or when the corrective actions are delayed and implemented in block at the end of each stage. Such models are classified into continuous and discontinuous models according to the assumed behavior of the product reliability with test time. Special attention is devoted to the nonhomogeneous Poisson process with power-law intensity function, namely, the power-law process, which is the stochastic representation of the well known deterministic growth model of Duane. Keywords: reliability growth; repairable systems; TAAF programs; delayed fixes; nonhomogeneous Poisson process
High-throughput mapping of long-range neuronal projection using in situ sequencing

Understanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single-neuron resolution and high throughput, a challenging combination with conventional methods. Here, we introduce barcoded anatomy resolved by sequencing (BARseq), a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3,579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (intratelencephalic [IT], pyramidal tract-like [PT-like], and corticothalamic [CT]) of projection neurons. In depth analysis uncovered a projection type restricted almost exclusively to transcriptionally defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images

Object segmentation in three-dimensional (3-D) point clouds is a critical task for robots capable of 3-D perception. Despite the impressive performance of deep learning-based approaches on object segmentation in 2-D images, deep learning has not been applied nearly as successfully for 3-D point cloud segmentation. Deep networks generally require large amounts of labeled training data, which are readily available for 2-D images but are difficult to produce for 3-D point clouds. In this letter, we present Label Diffusion Lidar Segmentation (LDLS), a novel approach for 3-D point cloud segmentation, which leverages 2-D segmentation of an RGB image from an aligned camera to avoid the need for training on annotated 3-D data. We obtain 2-D segmentation predictions by applying Mask-RCNN to the RGB image, and then link this image to a 3-D lidar point cloud by building a graph of connections among 3-D points and 2-D pixels. This graph then directs a semi-supervised label diffusion process, where the 2-D pixels act as source nodes that diffuse object label information through the 3-D point cloud, resulting in a complete 3-D point cloud segmentation. We conduct empirical studies on the KITTI benchmark dataset and on a mobile robot, demonstrating wide applicability and superior performance of LDLS compared with the previous state of the art in 3-D point cloud segmentation, without any need for either 3-D training data or fine tuning of the 2-D image segmentation model.
Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

Abstract Eating is an essential activity of daily living (ADL) for staying healthy and living at home independently. Although numerous assistive devices have been introduced, many people with disabilities are still restricted from independent eating due to the devices’ physical or perceptual limitations. In this work, we present a new meal-assistance system and evaluations of this system with people with motor impairments. We also discuss learned lessons and design insights based on the evaluations. The meal-assistance system uses a general-purpose mobile manipulator, a Willow Garage PR2, which has the potential to serve as a versatile form of assistive technology. Our active feeding framework enables the robot to autonomously deliver food to the user’s mouth, reducing the need for head movement by the user. The user interface, visually-guided behaviors, and safety tools allow people with severe motor impairments to successfully use the system. We evaluated our system with a total of 10 able-bodied participants and 9 participants with motor impairments. Both groups of participants successfully ate various foods using the system and reported high rates of success for the system’s autonomous behaviors. In general, participants who operated the system reported that it was comfortable, safe, and easy-to-use.
Narrow Incumbent Victories and Post-Election Conflict : Evidence from the Philippines

Post-election violence is a common form of conflict, but its underlying mechanisms are not well understood. Using data from the 2007 Philippine mayoral elections, this paper provides evidence that post-election violence is particularly intense after narrow victories by incumbents. Using a density test, the study shows that incumbents were substantially more likely to win narrow victories than their challengers, a pattern consistent with electoral manipulation. There is no evidence that the increase in post-election violence is related to the incumbent's political platform or their performance in past elections. These results provide support for the notion that post-election violence is triggered by election fraud or by the failure of democratic ways of removing unpopular incumbents from office.
On the Non-existence of Short Vectors in Random Module Lattices

Recently, Lyubashevsky & Seiler (Eurocrypt 2018) showed that small polynomials in the cyclotomic ring \(\mathbb {Z}_q[X]/(X^n+1)\), where n is a power of two, are invertible under special congruence conditions on prime modulus q. This result has been used to prove certain security properties of lattice-based constructions against unbounded adversaries. Unfortunately, due to the special conditions, working over the corresponding cyclotomic ring does not allow for efficient use of the Number Theoretic Transform (NTT) algorithm for fast multiplication of polynomials and hence, the schemes become less practical.
Atomic Norm Denoising for Complex Exponentials With Unknown Waveform Modulations

Non-stationary blind super-resolution is an extension of the traditional super-resolution problem, which deals with the problem of recovering fine details from coarse measurements. The non-stationary blind super-resolution problem appears in many applications including radar imaging, 3D single-molecule microscopy, computational photography, etc. There is a growing interest in solving non-stationary blind super-resolution task with convex methods due to their robustness to noise and strong theoretical guarantees. Motivated by the recent work on atomic norm minimization in blind inverse problems, we focus here on the signal denoising problem in non-stationary blind super-resolution. In particular, we use an atomic norm regularized least-squares problem to denoise a sum of complex exponentials with unknown waveform modulations. We quantify how the mean square error depends on the noise variance and the true signal parameters. Numerical experiments are also implemented to illustrate the theoretical result.
In Vivo Renal Tubule pH in Stone-Forming Human Kidneys.

Introduction: There is evidence that patients with a history of ileostomies, who produce acidic urine and form uric acid or calcium oxalate stones, may plug some collecting ducts with calcium phosp...
Energy-aware Scheduling of Task Graphs with Imprecise Computations and End-to-end Deadlines

Imprecise computations allow scheduling algorithms developed for energy-constrained computing devices to trade off output quality with utilization of system resources. The goal of such scheduling algorithms is to utilize imprecise computations to find a feasible schedule for a given task graph while maximizing the quality of service (QoS) and satisfying a hard deadline and an energy bound. This work presents a heuristic for scheduling tasks with potentially imprecise computations, represented with directed acyclic graphs, on multiprocessor platforms. Furthermore, it presents a mixed integer linear program formulation of the same problem, which provides the optimal reference scheduling solutions, enabling evaluation of the efficacy of the proposed heuristic. Both the heuristic and mathematical program take account of potentially imprecise inputs of tasks on their output quality. Furthermore, the presented heuristic is capable of finding feasible schedules even under tight energy budgets. Through extensive experiments, it is shown that in some cases, the proposed heuristic is capable of finding the same QoS as the ones found by MILP. Furthermore, for those task graphs that MILP outperforms the proposed heuristic, QoS values obtained with the proposed heuristic are, on average, within 1.24% of the optimal solutions while improving the runtime by a factor of 100 or so. This clearly demonstrates the advantage of the proposed heuristic over the exact solution, especially for large task graphs where solving the mathematical problem is hampered by its lengthy runtime.
Behavior Identification and Prediction for a Probabilistic Risk Framework

Operation in a real world traffic requires autonomous vehicles to be able to plan their motion in complex environments (multiple moving participants). Planning through such environment requires the right search space to be provided for the trajectory or maneuver planners so that the safest motion for the ego vehicle can be identified. Given the current states of the environment and its participants, analyzing the risks based on the predicted trajectories of all the traffic participants provides the necessary search space for the planning of motion. This paper provides a fresh taxonomy of safety / risks that an autonomous vehicle should be able to handle while navigating through traffic. It provides a reference system architecture that needs to be implemented as well as describes a novel way of identifying and predicting the behaviors of the traffic participants using classic Multi Model Adaptive Estimation (MMAE). Preliminary simulation results of the implemented model are included.
Sex Differences in the Association Between Pentraxin 3 and Cognitive Decline: The Cardiovascular Health Study.

BACKGROUND The importance of systemic inflammation, measured by C-reactive protein, in cognitive decline has been demonstrated; however, the role of vascular inflammation is less understood. Pentraxin 3 (PTX3) is a novel marker of vascular inflammation. METHODS We followed adults 65 and older, free of cardiovascular disease (CVD) for up to 9 years (n = 1,547) in the Cardiovascular Health Study. We evaluated the relationship between PTX3 and change in cognitive function, measured using the Modified Mini-Mental State Examination (3MSE), and incident cognitive impairment (3MSE < 80). Mediation by CVD events, and effect modification by sex and apolipoprotein E ɛ4 allele (APOE4) were also examined. RESULTS The average decline in 3MSE was 0.77 points per year. The association between PTX3 and change in 3MSE differed between women and men (p = .02). In the adjusted model, each standard deviation higher in PTX3 was associated with a 0.20 greater decline in 3MSE score per year in women over follow-up (95% CI: -0. 37, -0.03; p = .02), compared to no change in men (β = 0.07; 95% CI: -0.08, 0.22). CVD events had a minor effect on the associations. No effect modification by APOE4 was found, although we observed the association of PTX3 and cognitive impairment in women was attenuated and nonsignificant after adjustment for APOE4. There was a paradoxical protective association between PTX3 and reduced cognitive impairment in men, even after adjustment for APOE4. CONCLUSIONS We found that vascular inflammation was significantly associated with cognitive decline in older women, but not men.
Neutral competition in a deterministically changing environment: Revisiting continuum approaches.

Abstract Environmental variation can play an important role in ecological competition by influencing the relative advantage between competing species. Here, we consider such effects by extending a classical, competitive Moran model to incorporate an environment that fluctuates periodically in time. We adapt methods from work on these classical models to investigate the effects of the magnitude and frequency of environmental fluctuations on two important population statistics: the probability of fixation and the mean time to fixation. In particular, we find that for small frequencies, the system behaves similar to a system with a constant fitness difference between the two species, and for large frequencies, the system behaves similar to a neutrally competitive model. Most interestingly, the system exhibits nontrivial behavior for intermediate frequencies. We conclude by showing that our results agree quite well with recent theoretical work on competitive models with a stochastically changing environment, and discuss how the methods we develop ease the mathematical analysis required to study such models.
RuleVis: Constructing Patterns and Rules for Rule-Based Models

We introduce RuleVis, a web-based application for defining and editing "correct-by-construction" executable rules that model biochemical functionality, which can be used to simulate the behavior of protein-protein interaction networks and other complex systems. Rule-based models involve emergent effects based on the interactions between rules, which can vary considerably with regard to the scale of a model, requiring the user to inspect and edit individual rules. RuleVis bridges the graph rewriting and systems biology research communities by providing an external visual representation of salient patterns that experts can use to determine the appropriate level of detail for a particular modeling context. We describe the visualization and interaction features available in RuleVis and provide a detailed example demonstrating how RuleVis can be used to reason about intracellular interactions.
The Toda equations and the Gromov-Witten theory of the Riemann sphere

Consequences of the Toda equations arising from the conjectural matrix model for the Riemann sphere are investigated. The Toda equations determine the Gromov–Witten descendent potential (including all genera) of the Riemann sphere from the degree 0 part. Degree 0 series computations via Hodge integrals then lead to higher-degree predictions by the Toda equations. First, closed series forms for all 1-point invariants of all genera and degrees are given. Second, degree 1 invariants are investigated with new applications to Hodge integrals. Third, a differential equation for the generating function of the classical simple Hurwitz numbers (in all genera and degrees) is found – the first such equation. All these results depend upon the conjectural Toda equations. Finally, proofs of the Toda equations in genus 0 and 1 are given.
How Do Machine Learning Algorithms Perform in Predicting Hospital Choices? Evidence from Changing Environments

Researchers have found that machine learning methods are typically better at prediction than econometric models when the choice environment is stable. We study hospital demand models, and evaluate the relative performance of machine learning algorithms when the choice environment changes substantially due to natural disasters that closed previously available hospitals. While machine learning algorithms outperform traditional econometric models in prediction, the gain they provide shrinks when patients' choice sets are more profoundly affected. We show that traditional econometric methods provide important additional information when there are major changes in the choice environment.
Adam Smith, the Competitive Process, and the Flawed Consumer Welfare Standard

Scottish economist Adam Smith wrote in 1776 that the collective buying and selling of individuals would result in the preferred allocation of society’s resources. That insight has endured and is the basis for the competition law goal of fostering and protecting the competitive process. That goal, with venerable roots on both sides of the Atlantic, has been sidetracked by emergence of the consumer welfare standard, which is now preeminent in competition law analysis. The narrow focus of the consumer welfare standard has led to confusion and misdirected decisions that do not adequately protect the competitive process. I point to confusion about who is the buyer and who is the seller in many transactions, and describe why that classification should, in any event, be irrelevant in applying competition law. When competition is distorted, the central goal of protecting the process and ensuring a preferred allocation of resources is undermined, regardless of the impact on the consumer. The proper welfare standard is unconcerned with where the harm occurs. The standard focuses on anticompetitive conduct at any level of the distribution chain and regardless of whether the anticompetitive effects are directed upstream at sellers or downstream at buyers. The symmetric standard is rooted in competition law decisions on both sides of the Atlantic; it is sound in theory and, compared to the consumer welfare standard, is easier to explain and apply. It more comfortably honors the broader goals of competition, including promoting entry, innovation, and choices for both entrepreneurs and consumers. I assess how this symmetric welfare standard would apply to mergers and classic predatory or exclusionary conduct. The standard offers hope of simplifying analysis and better serving ancillary goals of competition. Fostering and preserving efficiency, enhancing output, and maintaining low consumer prices are among the highly valued benefits of the competitive process, but they are not determinative. The focus must remain on the central goal of preserving the competitive process.
Hierarchical Distributed EV Charging Scheduling in Distribution Grids

In this paper, a hierarchical distributed method consisting of two iterative procedures is proposed for optimal electric vehicle charging scheduling (EVCS) in the distribution grids. In the proposed method, the distribution system operator (DSO) aims at reducing the grid loss while satisfying the power flow constraints. This is achieved by a consensus-based iterative procedure with the EV aggregators (Aggs) located in the grid buses. The goal of aggregaotrs, which are equipped with the battery energy storage (BES), is to reduce their electricity cost by optimal control of BES and EVs. As Aggs' optimization problem increases dimensionally by increasing the number of EVs, they solved their problem through another iterative procedure with their customers. This procedure is implementable by exploiting the mathematical properties of the problem and rewriting Aggs' optimization problem as the sharing problem, which is solved efficiently by the alternating direction method of multipliers (ADMM). To validate the performance, the proposed method is applied to IEEE-13 bus system.
Modeling of heterogeneous catalysts using simple geometry supports

The application of a novel model catalyst is demonstrated in this work. In this catalyst, oxide particles of simple geometric shape are used as a catalyst support. The simple geometry facilitates observations of the dispersed phase by transmission electron microscopy. We present our results on the effect of support and pretreatment on metal particle morphology and reactivity.
Galaxies: Lighthouses in the Shoals of Dark Halos

It is anticipated from hierarchical clustering theory that there are scaling relationships between halos over a wide range of mass. Observationally it can be difficult to identify the markers that characterize these relationships because of the small numbers of visible probes and confusion from contaminants in projection. Nonetheless, in favorable circumstances it is possible to identify a very useful marker: the radius of the caustic at second turnaround. In a few favorable circumstances it is possible to identify the radius of first turnaround or zero velocity surface about a collapsed region. It will be shown that specifically the radius of second turnaround scales as anticipated over three orders of magnitude in mass from 1012 to 1015 MΘ. Halos are characterized by zones of dispersed velocities within the second turnaround caustic and zones of infall between the first and the second turnaround radii. The inner zone is populated in the majority by gas-poor morphologies and the outer zone is populated in the majority by gas-rich morphologies. The numbers of dwarfs within the inner zone is roughly constant per unit halo mass.
Packing Nearly Optimal Ramsey R(3,t) Graphs

In 1995 Kim famously proved the Ramsey bound R(3, t) ≤ ct2/logt by constructing an n-vertex graph that is triangle-free and has independence number at most $$C\,\sqrt {n\,\log \,n} $$. We extend this celebrated result, which is best possible up to the value of the constants, by approximately decomposing the complete graph Kn into a packing of such nearly optimal Ramsey R(3,t) graphs. More precisely, for any e > 0 we find an edge-disjoint collection (Gi)i of n-vertex graphs Gi ⊆ Kn such that (a) each Gi is triangle-free and has independence number at most $$C_{\epsilon} \sqrt{n \log n}$$, and (b) the union of all the Gi contains at least $$(1-\epsilon)\left(\begin{array}{l}n \\2\end{array}\right)$$ edges. Our algorithmic proof proceeds by sequentially choosing the graphs Gi via a semi-random (i.e., Rodl nibble type) variation of the triangle-free process. As an application, we prove a conjecture in Ramsey theory by Fox, Grinshpun, Liebenau, Person, and Szabo (concerning a Ramsey-type parameter introduced by Burr, Erdős, and Lovasz in 1976). Namely, denoting by sr(H) the smallest minimum degree of r-Ramsey minimal graphs for H, we close the existing logarithmic gap for H = K3 and establish that sr(K3) = Θ(r2 logr).
Integral Metaplectic Modular Categories

A braided fusion category is said to have Property F if the associated braid group representations factor through a finite group. We verify integral metaplectic modular categories have property F b...
Reproducibility in Accounting Research: Views of the Research Community

We have little knowledge about the prevalence of irreproducibility in the accounting literature. To narrow this gap, we conducted a survey among the participants of the 2019 JAR Conference on their perceptions of the frequency, causes, and consequences of irreproducible research published in accounting journals. A majority of respondents believe that irreproducibility is common in the literature, constitutes a major problem, and receives too little attention. Most have encountered irreproducibility in the work of others (although not in their own work) but chose not to pursue their failed reproduction attempts to publication. Respondents believe irreproducibility results chiefly from career or publication incentives as well as from selective reporting of results. They also believe that practices like sharing code and data combined with stronger incentives to replicate the work of others would enhance reproducibility. The views of accounting researchers are remarkably similar to those expressed in a survey by the scientific journal Nature. We conclude by discussing the implications of our findings and provide several potential paths forward for the accounting research community.
Lorentz Violation and Partons

A parton-model description of high-energy hadronic interactions in the presence of Lorentz violation is presented. This approach is used to study lepton-hadron and hadron-hadron interactions at large momentum transfer. Cross sections for deep inelastic scattering and the Drell-Yan process are calculated at first order for minimal and nonminimal Lorentz violation. Estimated bounds are placed using existing LHC and future US-based Electron-Ion Collider data.
Agrammatism and Paragrammatism: A Cortical Double Dissociation Revealed by Lesion-Symptom Mapping

The fundamental distinction of grammatical deficits in aphasia, agrammatism and paragrammatism, was made over a century ago. However, the extent to which the agrammatism/paragrammatism distinction exists independently of differences in speech fluency has not clearly been investigated. Despite much research on agrammatism, the lesion correlates of paragrammatism are essentially unknown. Lesion-symptom mapping was used to investigate the degree to which the lesion correlates of agrammatism and paragrammatism overlap or dissociate. Four expert raters assessed videos of 53 right-handed patients with aphasia following chronic left-hemisphere stroke retelling the Cinderella story. Consensus discussion determined each subject's classification with respect to grammatical deficits as Agrammatic, Paragrammatic, Both, or No Grammatical Deficit. Each subject's lesion was manually drawn on a high-resolution MRI and warped to standard space for group analyses. Lesion-symptom mapping analyses were performed in NiiStat including lesion volume as a covariate. Secondary analyses included speech rate (words per minute) as an additional covariate. Region of interest analyses identified a double dissociation between these syndromes: damage to Broca's area was significantly associated with agrammatism, p = 0.001 (but not paragrammatism, p = 0.930), while damage to the left posterior superior and middle temporal gyri was significantly associated with paragrammatism, p < 0.001 (but not agrammatism, p = 0.873). The same results obtained when regressing out the effect of speech rate, and nonoverlapping lesion distributions between the syndromes were confirmed by uncorrected whole brain analyses. Our results support a fundamental distinction between agrammatism and paragrammatism.
Anaerobic infections in children

Anaerobic bacteria commonly cause infection in children. Anaerobes are the most predominant components of the normal human skin and mucous membrane bacterial flora, and are therefore a common cause of bacterial infections of endogenous origin. Because of their fastidious nature, they are difficult to isolate from infectious sites and are often overlooked. Anaerobic infections can occur in all body sites, including the central nervous system, oral cavity, head and neck, chest, abdomen, pelvis, skin, and soft tissues. Anaerobic bacteria colonize the newborn after delivery and have been recovered from several types of neonatal infections. These include cellulitis of the site of fetal monitoring, neonatal aspiration pneumonia, bacteremia, conjunctivitis, omphalitis, and infant botulism. The lack of directing adequate therapy against these organisms may lead to clinical failures. Their isolation requires appropriate methods of collection, transportation, and cultivation of specimens. Treatment of anaerobic infection is complicated by the slow growth of these organisms, by their polymicrobial nature, and by the growing resistance of anaerobic bacteria to antimicrobials. Antimicrobial therapy is often the only form of therapy required, whereas in other cases it is an important adjunct to a surgical approach. Because anaerobic bacteria generally are recovered mixed with aerobic organisms, the choice of appropriate antimicrobial agents should provide for adequate coverage of both types of pathogens.
An Experimental Comparison of Speed Scaling Algorithms with Deadline Feasibility Constraints

We consider the first, and most well studied, speed scaling problem in the algorithmic literature: where the scheduling quality of service measure is a deadline feasibility constraint, and where the power objective is to minimize the total energy used. Four online algorithms for this problem have been proposed in the algorithmic literature. Based on the best upper bound that can be proved on the competitive ratio, the ranking of the online algorithms from best to worst is: $qOA$, $OA$, $AVR$, $BKP$. As a test case on the effectiveness of competitive analysis to predict the best online algorithm, we report on an experimental ``horse race'' between these algorithms using instances based on web server traces. Our main conclusion is that the ranking of our algorithms based on their performance in our experiments is identical to the order predicted by competitive analysis. This ranking holds over a large range of possible power functions, and even if the power objective is temperature.
Adapting control policies from simulation to reality using a pairwise loss

This paper proposes an approach to domain transfer based on a pairwise loss function that helps transfer control policies learned in simulation onto a real robot. We explore the idea in the context of a “category level” manipulation task where a control policy is learned that enables a robot to perform a mating task involving novel objects. We explore the case where depth images are used as the main form of sensor input. Our experimental results demonstrate that proposed method consistently outperforms baseline methods that train only in simulation or that combine real and simulated data in a naive way.
Functionally Effective Conscious AI Without Suffering

Insofar as consciousness has a functional role in facilitating learning and behavioral control, the builders of autonomous Artificial Intelligence (AI) systems are likely to attempt to incorporate ...
REVERSAL OF FORTUNE: GEOGRAPHY AND INSTITUTIONS IN THE MAKING OF THE MODERN WORLD INCOME DISTRIBUTION*

Among countries colonized by European powers during the past 500 years, those that were relatively rich in 1500 are now relatively poor. We document this reversal using data on urbanization patterns and population density, which, we argue, proxy for economic prosperity. This reversal weighs against a view that links economic development to geographic factors. Instead, we argue that the reversal ree ects changes in the institutions resulting from European colonialism. The European intervention appears to have created an “ institutional reversal” among these societies, meaning that Europeans were more likely to introduce institutions encouraging investment in regions that were previously poor. This institutional reversal accounts for the reversal in relative incomes. We provide further support for this view by documenting that the reversal in relative incomes took place during the late eighteenth and early nineteenth centuries, and resulted from societies with good institutions taking advantage of the opportunity to industrialize.
Chapter 7 – Critical Phenomena

This chapter is a review of the fundamentals of phase transitions of materials close to their critical points; this material is not normally included in thermodynamics texts. The discussion centers on the derivation of equations that specify how various physical properties of materials are altered as the critical point is reached where the two related phases become indistinguishable. This topic has been extensively explored during the last 40 years and continues to be explored; as far as can be ascertained, a survey of these recent theories is not usually included in standard textbooks.
6 – Population Dynamics

Publisher Summary Populations of insects can change dramatically in size over relatively short periods of time, given their short generation times and high reproductive rates. Predicting the effects of global change has become a major goal of research on population dynamics. Insect populations respond to changes in habitat conditions and resource quality. Their responses to current and historic environmental changes help in anticipating their responses in the future. This chapter addresses temporal patterns of abundance, factors causing or regulating population fluctuation, and models of population dynamics. It briefly discusses the population fluctuation, factors affecting population size, and models of population change. Populations of insects can fluctuate dramatically through time, with varying effects on community and ecosystem patterns and processes, as well as on the degree of crowding among members of the population. The amplitude and frequency of fluctuations distinguish irruptive populations, cyclic populations, and stable populations. Cyclic populations have stimulated the greatest interest among ecologists. The various hypotheses that have been developed to explain cyclic patterns of population fluctuation all include density-dependent regulation with a time lag that generates regular oscillations. In addition, development of population dynamics models has been useful for forecasting changes in insect abundance and effects on crop, range, and forest resources.
Leave-One-Out Approach for Matrix Completion: Primal and Dual Analysis

In this paper, we introduce a powerful technique based on Leave-One-Out analysis to the study of low-rank matrix completion problems. Using this technique, we develop a general approach for obtaining fine-grained, entrywise bounds for iterative stochastic procedures in the presence of probabilistic dependency. We demonstrate the power of this approach in analyzing two of the most important algorithms for matrix completion: (i) the non-convex approach based on Projected Gradient Descent (PGD) for a rank-constrained formulation, also known as the Singular Value Projection algorithm, and (ii) the convex relaxation approach based on nuclear norm minimization (NNM). Using this approach, we establish the first convergence guarantee for the original form of PGD without regularization or sample splitting , and in particular shows that it converges linearly in the infinity norm . For NNM, we use this approach to study a fictitious iterative procedure that arises in the dual analysis . Our results show that NNM recovers an $d$ -by- $d$ rank- $r$ matrix with $\mathcal {O}(\mu r \log (\mu r) d\log d)$ observed entries. This bound has optimal dependence on the matrix dimension and is independent of the condition number. To the best of our knowledge, none of previous sample complexity results for tractable matrix completion algorithms satisfies these two properties simultaneously.
Chapter 4 – Reproductive Systems

The physiological systems of insects provide the potential for their huge success on our planet, but their reproductive systems specifically enable that potential to be realized. Although short-lived insects have a relatively brief reproductive opportunity, they compensate with a diverse assemblage of reproductive strategies that allow prodigious numbers of offspring to be produced under a wide range of ecological circumstances. These strategies include parthenogenesis, pedogenesis, polyembryony, functional hermaphroditism, viviparity, and the more common bisexual reproduction and oviparity.
Activist monetary policy, imperfect capital mobility, and the overshooting hypothesis

Abstract The hypothesis of exchange rate overshooting is investigated in the context of a model that incorporates activist monetary policy, variable output, imperfect capital mobility, and slow price adjustment. Monetary policy which accommodates prices and/or interest rates is shown to increase the probability of undershooting. Using constrained maximum likelihood methods, the model is estimated for Germany and Japan since the advent of generalized floating in 1973. Based on the estimated parameter values, the mark exhibits overshooting while the yen is characterized by undershooting. The constraints implied by the model cannot be rejected at standard significance levels for either country.
Chapter 4 – Ion Exchange

Ion exchange is poorly understood but important chemical reaction in soils, sediments, and aquifers; a process that has profound effects on the solution concentration of many ions. The ion exchange isotherm that describes the relation between solution composition and the ion exchange complex is influenced by two major factors: electrolyte concentration and ion selectivity. Electrolyte concentration affects the exchange isotherm only for asymmetric exchange reactions, the effect being proportional to the ion-charge concentration. Ion selectivity influences symmetric and asymmetric exchange reactions and arises from Coulomb interactions between the ion and the exchange site. The strength of the Coulomb interaction between ion and site is controlled by ion hydration; the hydration shell determines how closely each ion can approach the exchange site. Weakly hydrated ions that are able to shed their hydration shell can bind more strongly to the exchange site than strongly hydrated ions. As a general rule, single-adjustable-parameter exchange isotherms provide an excellent fit of the experimental exchange isotherm. In certain cases (cf. Appendix 4.F) the selectivity coefficient adopts two limiting values representing preferred interlayer hydration states and undergoes an abrupt transition between the two limiting values when the exchange complex reaches a critical value.
Detecting Stuffing of a User’s Credentials at Her Own Accounts

We propose a framework by which websites can coordinate to detect credential stuffing on individual user accounts. Our detection algorithm teases apart normal login behavior (involving password reuse, entering correct passwords into the wrong sites, etc.) from credential stuffing, by leveraging modern anomaly detection and carefully tracking suspicious logins. Websites coordinate using a novel private membership-test protocol, thereby ensuring that information about passwords is not leaked; this protocol is highly scalable, partly due to its use of cuckoo filters, and is more secure than similarly scalable alternatives in an important measure that we define. We use probabilistic model checking to estimate our credential-stuffing detection accuracy across a range of operating points. These methods might be of independent interest for their novel application of formal methods to estimate the usability impacts of our design. We show that even a minimal-infrastructure deployment of our framework should already support the combined login load experienced by the airline, hotel, retail, and consumer banking industries in the U.S.
Estimation and inference for the indirect effect in high-dimensional linear mediation models

Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in the presence of high-dimensional mediators for linear mediation models. We develop methods for both incomplete mediation, where a direct effect may exist, and complete mediation, where the direct effect is known to be absent. We prove consistency and asymptotic normality of our indirect effect estimators. Under complete mediation, where the indirect effect is equivalent to the total effect, we further prove that our approach gives a more powerful test compared to directly testing for the total effect. We confirm our theoretical results in simulations, as well as in an integrative analysis of gene expression and genotype data from a pharmacogenomic study of drug response. We present a novel analysis of gene sets to understand the molecular mechanisms of drug response, and also identify a genome-wide significant noncoding genetic variant that cannot be detected using standard analysis methods.
15 – INTERNATIONAL ECONOMICS

Publisher Summary This chapter focuses on international economics. Trade and financial flows link the nations of the world like an interconnected system of bathtubs. One country's actions disturb the entire system. Exchange rates affect the economy in many ways. A change in the exchange rate alters many prices, changes the distribution of income, and shifts aggregate demand and supply. Interest rates are important international links. The credit markets of the world are tied together by credit flows. The Eurodollars are an indication of international economic interdependence. Eurodollars are dollar-denominated accounts in foreign banks. Expansionary monetary policy forces dollar depreciation. Investment spending and net exports both rise, boosting aggregate demand. Fiscal policy is less effective. Lower investment and net export spending offset the fiscal injection. National interest rates are affected by international forces. Interest rates are important, too, because credit flows bring exchange-rate changes.
Primary Site Predicts Grade for Gastroenteropancreatic Neuroendocrine Tumors

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and abstruse neoplasms with increasing incidence and clinical relevance. The National Cancer Data Base was examined to identify GEP-NET cases from 2004 to 2013. In total, 39,454 patients diagnosed with GEP-NET were identified. Median age was 61 years. Majority was female (50.13%), white (79.49%), and had low-grade neoplasms (84.39%). On univariate analysis, age, sex, race, primary site, tumor size, and regional lymph node involvement were associated with tumor grade (P < 0.0001). On multivariate analysis, older age [odds ratio (OR) = 9.57], gender (male, OR = 1.29), and race continued to be associated with high-grade neoplasms. The primary site also remained a significant predictor of tumor grade. High-grade neoplasms were more likely to arise from the esophagus (OR = 317.75), hepatobiliary system (OR = 23.15), colorectum (OR = 14.37), ampulla of Vater (OR = 11.61), and stomach (OR = 7.84) compared with the appendix (OR = 5.41), pancreas (OR = 5.31), and small bowel (referent). The tumor grade for GEP-NETs is highly dependent on the primary site, suggesting different sites may be biologically distinct diseases. A personalized approach to GEP-NET treatment, tailored to the site of origin, is imperative.