cssi/SciSciGPT-SciSciNet huggingface dataset:
A hemagglutination-based, semi-quantitative test for point-of-care determination of SARS-CoV-2 antibody levels.

Serologic, point-of-care tests to detect antibodies against SARS-CoV-2 are an important tool in the COVID-19 pandemic. The majority of current point-of-care antibody tests developed for SARS-CoV-2 rely on lateral flow assays, but these do not offer quantitative information. To address this, we developed a novel antibody test leveraging hemagglutination, employing a dry card format currently used for typing ABO blood groups. 200 COVID-19 patient and 200 control plasma samples were reconstituted with O-negative RBCs to form whole blood and added to dried viral-antibody fusion protein, followed by a stirring step and a tilting step, 3-minute incubation, and a second tilting step. The sensitivity for the hemagglutination test, Euroimmun IgG ELISA test and RBD-based CoronaChek lateral flow assay was 87.0%, 86.5%, and 84.5%, respectively, using samples obtained from recovered COVID-19 individuals. Testing pre-pandemic samples, the hemagglutination test had a specificity of 95.5%, compared to 97.3% and 98.9% for the ELISA and CoronaChek, respectively. A distribution of agglutination strengths was observed in COVID-19 convalescent plasma samples, with the highest agglutination score (4) exhibiting significantly higher neutralizing antibody titers than weak positives (2) (p<0.0001). Strong agglutinations were observed within 1 minute of testing, and this shorter assay time also increased specificity to 98.5%. In conclusion, we developed a novel rapid, point-of-care RBC agglutination test for the detection of SARS-CoV-2 antibodies that can yield semi-quantitative information on neutralizing antibody titer in patients. The five-minute test may find use in determination of serostatus prior to vaccination, post-vaccination surveillance and travel screening.
Learning Asymmetric and Local Features in Multi-Dimensional Data through Wavelets with Recursive Partitioning.

Effective learning of asymmetric and local features in images and other data observed on multi-dimensional grids is a challenging objective critical for a wide range of image processing applications involving biomedical and natural images. It requires methods that are sensitive to local details while fast enough to handle massive numbers of images of ever increasing sizes. We introduce a probabilistic model-based framework that achieves these objectives by incorporating adaptivity into discrete wavelet transforms (DWT) through Bayesian hierarchical modeling, thereby allowing wavelet bases to adapt to the geometric structure of the data while maintaining the high computational scalability of wavelet methods---linear in the sample size (e.g., the resolution of an image). We derive a recursive representation of the Bayesian posterior model which leads to an exact message passing algorithm to complete learning and inference. While our framework is applicable to a range of problems including multi-dimensional signal processing, compression, and structural learning, we illustrate its work and evaluate its performance in the context of image reconstruction using real images from the ImageNet database, two widely used benchmark datasets, and a dataset from retinal optical coherence tomography and compare its performance to state-of-the-art methods based on basis transforms and deep learning.
Limiting fluctuations in quantum gravity to diffeomorphisms

Within the background field formalism of quantum gravity, I show that if the quantum fluctuations are limited to diffeomorphic gauge transformations rather than the physical degrees of freedom, as in conventional quantum field theory, all the quantum corrections vanish on shell and the effective action is equivalent to the classical action. In principle, the resulting theory is finite and unitary, and requires no renormalization. I also show that this is the unique parameterization that renders the path integral independent of the on-shell condition for the background field, a form of background independence. Thus, a connection is established between background independence and renormalizability and unitarity.
How Changes in Expectations of Earnings Affect the Associations of Earnings Overstatements and Audit Effort with Audit Risk and Market Price

In this study, we consider how changing expectations of earnings affect a dishonest manager’s strategy to overstate earnings and an auditor’s strategy to exert effort in a two-period setting. We model the manager type as either honest or dishonest, which allows us to differentiate audit risk from audit effort. Researchers typically assume audit effort and audit risk are negatively associated, which we find for changes in our period 2 payoff parameters, but we find the association can be positive, specifically with changes in our period 1 game parameters. Further, by dichotomizing, we show that the directional change in market price does not necessarily follow the directional change in audit effort as the prior literature suggests, because market price also adjusts for expected bias through changes in the intercept. A key finding is that when period 1 expected earnings increase, the probability that the manager is dishonest decreases, which allows the auditor to reduce audit effort. This finding suggests that observations of earnings that just meet or beat an earnings target and suspected of being managed may not be indicative of an audit failure, but indicative of an efficient allocation of effort. Finally, our multiperiod setting demonstrates that the effects from a change in the manager’s or auditor’s incentives in period 1 may reverse in period 2. Studies typically examine the contemporaneous effects of these changes on market price and/or audit risk, but fail to identify the cross-temporal effects we document in our study.
Migration, economic crisis and child growth in rural Guatemala: Insights from the Great Recession

Abstract Migration has been demonstrated by various studies to be closely linked to improvements in individual- and household-level outcomes. In this paper, rather than examining the effects of migration, we explore whether an economic shock in United States affected migrant households in rural Guatemala. Treating the Great Recession as a natural experiment affecting migrant and non-migrant households differently, we put the spotlight on the effect of the shock on child anthropometry, including longer-term indicators of height-for-age z-scores (HAZ). Panel data on children, and multiple children in households enable both double- and triple-difference estimation. In relative terms, migrant households fared much worse than non-migrant households over the period. Large advantages in child anthropometric status for the youngest children in migrant households in 2008, just prior to the crisis, were substantially diminished four years later. The findings underscore the possible fragility of the benefits of migration, particularly in the face of a substantial economic shock, and point to the potential importance of deepening social safety nets.
Tackling Small Eigen-Gaps: Fine-Grained Eigenvector Estimation and Inference Under Heteroscedastic Noise

This paper aims to address two fundamental challenges arising in eigenvector estimation and inference for a low-rank matrix from noisy observations: 1) how to estimate an unknown eigenvector when the eigen-gap (i.e. the spacing between the associated eigenvalue and the rest of the spectrum) is particularly small; 2) how to perform estimation and inference on linear functionals of an eigenvector—a sort of “fine-grained” statistical reasoning that goes far beyond the usual $\ell _{2}$ analysis. We investigate how to address these challenges in a setting where the unknown $n\times n$ matrix is symmetric and the additive noise matrix contains independent (and non-symmetric) entries. Based on eigen-decomposition of the asymmetric data matrix, we propose estimation and uncertainty quantification procedures for an unknown eigenvector, which further allow us to reason about linear functionals of an unknown eigenvector. The proposed procedures and the accompanying theory enjoy several important features: 1) distribution-free (i.e. prior knowledge about the noise distributions is not needed); 2) adaptive to heteroscedastic noise; 3) minimax optimal under Gaussian noise. Along the way, we establish valid procedures to construct confidence intervals for the unknown eigenvalues. All this is guaranteed even in the presence of a small eigen-gap (up to $O(\sqrt {n/\mathrm {poly}\log (n)}\,)$ times smaller than the requirement in prior theory), which goes significantly beyond what generic matrix perturbation theory has to offer.
Symplectic rational $G$-surfaces and equivariant symplectic cones

We give characterizations of a finite group $G$ acting symplectically on a rational surface ($\mathbb{CP}^2$ blown up at two or more points). In particular, we obtain a symplectic version of the dichotomy of $G$-conic bundles versus $G$-del Pezzo surfaces for the corresponding $G$-rational surfaces, analogous to a classical result in algebraic geometry. Besides the characterizations of the group $G$ (which is completely determined for the case of $\mathbb{CP}^2 \# N \overline{\mathbb{CP}^2}, N={2,3,4}$), we also investigate the equivariant symplectic minimality and equivariant symplectic cone of a given $G$-rational surface.
Reflection Groups and Rigidity of Quadratic Poisson Algebras

In this paper, we study the invariant theory of quadratic Poisson algebras. Let G be a finite group of the graded Poisson automorphisms of a quadratic Poisson algebra A. When the Poisson bracket of A is skew-symmetric, a Poisson version of the Shephard-Todd-Chevalley theorem is proved stating that the fixed Poisson subring AG is skew-symmetric if and only if G is generated by reflections. For many other well-known families of quadratic Poisson algebras, we show that G contains limited or even no reflections. This kind of Poisson rigidity result ensures that the corresponding fixed Poisson subring AG is not isomorphic to A as Poisson algebras unless G is trivial.
Quantifying the Tradeoff Between Energy Consumption and the Risk of Airborne Disease Transmission for Building HVAC Systems

It has been established that combinations of increased ventilation, improved filtration, and other HVAC techniques can reduce the likelihood of airborne disease transmission in buildings. However, ...
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization.

Human-designed data augmentation strategies have been replaced by automatically learned augmentation policy in the past two years. Specifically, recent work has empirically shown that the superior performance of the automated data augmentation methods stems from increasing the diversity of augmented data \cite{autoaug, randaug}. However, two factors regarding the diversity of augmented data are still missing: 1) the explicit definition (and thus measurement) of diversity and 2) the quantifiable relationship between diversity and its regularization effects. To bridge this gap, we propose a diversity measure called Variance Diversity and theoretically show that the regularization effect of data augmentation is promised by Variance Diversity. We validate in experiments that the relative gain from automated data augmentation in test accuracy is highly correlated to Variance Diversity. An unsupervised sampling-based framework, \textbf{DivAug}, is designed to directly maximize Variance Diversity and hence strengthen the regularization effect. Without requiring a separate search process, the performance gain from DivAug is comparable with the state-of-the-art method with better efficiency. Moreover, under the semi-supervised setting, our framework can further improve the performance of semi-supervised learning algorithms compared to RandAugment, making it highly applicable to real-world problems, where labeled data is scarce. The code is available at \texttt{\url{this https URL}}.
Influence of Spanwise Boundary Conditions on Slat Noise Simulations

The slat noise from the 30P/30N high-lift system is being investigated through computational fluid dynamics simulations with the OVERFLOW code in conjunction with a Ffowcs Williams-Hawkings acoustics solver. In the present study, two different spanwise grids are being used to investigate the effect of the spanwise extent and periodicity on the near-field unsteady structures and radiated noise. The baseline grid with periodic boundary conditions has a short span equal to 1/9th of the stowed chord, whereas the other, longer span grid adds stretched grids on both sides of the core, baseline grid to allow inviscid surface boundary conditions at both ends. The results indicate that the near-field mean statistics obtained using the two grids are similar to each other, as are the directivity and spectral shapes of the radiated noise. However, periodicity forces all acoustic waves with less than one wavelength across the span to be two-dimensional, without any variation in the span. The spanwise coherence of the acoustic waves is what is needed to make estimates of the noise that would be radiated from realistic span lengths. Simulations with periodic conditions need spans of at least six slat chords to allow spanwise variation in the low-frequencies associated with the peak of broadband slat noise. Even then, the full influence of the periodicity is unclear, so employing grids with a fine, central region and highly stretched meshes that go to slip walls may be a more efficient means of capturing the spanwise decorrelation of low-frequency acoustic phenomena.
A Front-End for Dense Monocular SLAM using a Learned Outlier Mask Prior

Recent achievements in depth prediction from a single RGB image have powered the new research area of combining convolutional neural networks (CNNs) with classical simultaneous localization and mapping (SLAM) algorithms. The depth prediction from a CNN provides a reasonable initial point in the optimization process in the traditional SLAM algorithms, while the SLAM algorithms further improve the CNN prediction online. However, most of the current CNN-SLAM approaches have only taken advantage of the depth prediction but not yet other products from a CNN. In this work, we explore the use of the outlier mask, a by-product from unsupervised learning of depth from video, as a prior in a classical probability model for depth estimate fusion to step up the outlier-resistant tracking performance of a SLAM front-end. On the other hand, some of the previous CNN-SLAM work builds on feature-based sparse SLAM methods, wasting the per-pixel dense prediction from a CNN. In contrast to these sparse methods, we devise a dense CNN-assisted SLAM frontend that is implementable with TensorFlow and evaluate it on both indoor and outdoor datasets.
Statistical Correlation Between Quantum Entanglement and Spin–Orbit Coupling in Crossed Beam Molecular Dynamics

Non-classical features like interference is already being harnessed to control the output of chemical reactions. However quantum entanglement which is an equally enigmatic many-body quantum correlation can also be used as a powerful resource yet have eluded explicit attention. In this report, we propose an experimental scheme under the crossed beam molecular dynamical setup, with the F+HD reaction, aiming to study the possible influence of entanglement within reactant pairs on the angular features of the product distribution. The aforesaid reaction has garnered interest recently as an unusual horseshoe shape pattern in the product (HF) distribution was observed, which has been attributed to the coupling of spin and orbital degrees of freedom. We propose an experimental scheme aiming to study the possible influence of entanglement on the necessity for the inclusion of such spin-orbit characteristics, under circumstances wherein the existence of entanglement and spin-orbit interaction is simultaneously detectable. We further numerically simulate the attainable results highlighting specific patterns corresponding to various possibilities. Such studies if extended can provide unforeseen mechanistic insight in analogous reactions too from the lens of quantum information.
The Democratizing Effects of Search Engine Use: On Chance Exposures and Organizational Hubs

In this paper I highlight two implications of the widespread use of search engines, which are often overlooked by commentators. In the first part of the paper I argue that search engines are conducive to unplanned exposures to diverse and even opposing views. In the second part I argue that search engines indirectly contribute to emergent political organization, since they allow large numbers of people to locate and access organizational hubs of collective action. I conclude by pointing to the democratic significance of these properties.
Towards Democratizing Modeling at Scale

We use AI techniques to create a modeling environment that makes sophisticated models accessible to non-experts. Our AI framework for Model INTegration (MINT) assists users to explore scenarios, which MINT can run in a local environment or at scale in a supercomputing facility. We are using MINT with hydrology, agriculture, and drought models for food security.
Quantifying Intrinsic Value of Information of Trajectories

A trajectory, defined as a sequence of location measurements, contains valuable information about movements of an individual. Its value of information (VOI) may change depending on the specific application. However, in a variety of applications, knowing the intrinsic VOI of a trajectory is important to guide other subsequent tasks or decisions. This work aims to find a principled framework to quantify the intrinsic VOI of trajectories from the owner's perspective. This is a challenging problem because an appropriate framework needs to take into account various characteristics of the trajectory, prior knowledge, and different types of trajectory degradation. We propose a framework based on information gain (IG) as a principled approach to solve this problem. Our IG framework transforms a trajectory with discrete-time measurements to a canonical representation, i.e., continuous in time with continuous mean and variance estimates, and then quantifies the reduction of uncertainty about the locations of the owner over a period of time as the VOI of the trajectory. Qualitative and extensive quantitative evaluation show that the IG framework is capable of effectively capturing important characteristics contributing to the VOI of trajectories.
Density-based binning of gene clusters to infer function or evolutionary history using GeneGrouper.

MOTIVATION Identifying variant forms of gene clusters of interest in phylogenetically proximate and distant taxa can help to infer their evolutionary histories and functions. Conserved gene clusters may differ by only a few genes, but these small differences can in turn induce substantial phenotypes, such as by the formation of pseudogenes or insertions interrupting regulation. Particularly as microbial genomes and metagenomic assemblies become increasingly abundant, unsupervised grouping of similar, but not necessarily identical, gene clusters into consistent bins can provide a population-level understanding of their gene content variation and functional homology. RESULTS We developed GeneGrouper, a command-line tool that uses a density-based clustering method to group gene clusters into bins. GeneGrouper demonstrated high recall and precision in benchmarks for the detection of the 23-gene Salmonella enterica LT2 Pdu gene cluster and four-gene Pseudomonas aeruginosa PAO1 Mex gene cluster among 435 genomes spanning mixed taxa. In a subsequent application investigating the diversity and impact of gene-complete and -incomplete LT2 Pdu gene clusters in 1130 S. enterica genomes, GeneGrouper identified a novel, frequently occurring pduN pseudogene. When investigated in vivo, introduction of the pduN pseudogene negatively impacted microcompartment formation. We next demonstrated the versatility of GeneGrouper by clustering distant homologous gene clusters and variable gene clusters found in integrative and conjugative elements. AVAILABILITY GeneGrouper software and code are publicly available at https://pypi.org/project/GeneGrouper/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
pH-dependent interactions of Apolipophorin-III with a lipid disk

Apolipophorin-III (ApoLp-III) is required for stabilization of molecular shuttles of lipid fuels in insects and is found to contribute to the insect immune reaction. Rearrangement of its five α-hel...
Caring for an Aging Population in a Post-Pandemic World: Emerging Trends in the U.S. Older Adult Care Industry

This paper examines older adult care services during the outbreak of the COVID-19 global pandemic. Specifically, it investigates emerging developments initiated or augmented by the pandemic and dis...
Llama: A Heterogeneous & Serverless Framework for Auto-Tuning Video Analytics Pipelines

The proliferation of camera-enabled devices and large video repositories has led to a diverse set of video analytics applications. These applications rely on video pipelines, represented as DAGs of operations, to transform videos, process extracted metadata, and answer questions like, "Is this intersection congested?" The latency and resource efficiency of pipelines can be optimized using configurable knobs for each operation (e.g., sampling rate, batch size, or type of hardware used). However, determining efficient configurations is challenging because (a) the configuration search space is exponentially large, and (b) the optimal configuration depends on users' desired latency and cost targets, (c) input video contents may exercise different paths in the DAG and produce a variable amount intermediate results. Existing video analytics and processing systems leave it to the users to manually configure operations and select hardware resources. We present Llama: a heterogeneous and serverless framework for auto-tuning video pipelines. Given an end-to-end latency target, Llama optimizes for cost efficiency by (a) calculating a latency target for each operation invocation, and (b) dynamically running a cost-based optimizer to assign configurations across heterogeneous hardware that best meet the calculated per-invocation latency target. This makes the problem of auto-tuning large video pipelines tractable and allows us to handle input-dependent behavior, conditional branches in the DAG, and execution variability. We describe the algorithms in Llama and evaluate it on a cloud platform using serverless CPU and GPU resources. We show that compared to state-of-the-art cluster and serverless video analytics and processing systems, Llama achieves 7.8x lower latency and 16x cost reduction on average.
Modular Self-Supervision for Document-Level Relation Extraction

Extracting relations across large text spans has been relatively underexplored in NLP, but it is particularly important for high-value domains such as biomedicine, where obtaining high recall of the latest findings is crucial for practical applications. Compared to conventional information extraction confined to short text spans, document-level relation extraction faces additional challenges in both inference and learning. Given longer text spans, state-of-the-art neural architectures are less effective and task-specific self-supervision such as distant supervision becomes very noisy. In this paper, we propose decomposing document-level relation extraction into relation detection and argument resolution, taking inspiration from Davidsonian semantics. This enables us to incorporate explicit discourse modeling and leverage modular self-supervision for each sub-problem, which is less noise-prone and can be further refined end-to-end via variational EM. We conduct a thorough evaluation in biomedical machine reading for precision oncology, where cross-paragraph relation mentions are prevalent. Our method outperforms prior state of the art, such as multi-scale learning and graph neural networks, by over 20 absolute F1 points. The gain is particularly pronounced among the most challenging relation instances whose arguments never co-occur in a paragraph.
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network

Data-driven methods for physics-based character control using reinforcement learning have been successfully applied to generate high-quality motions. However, existing approaches typically rely on Gaussian distributions to represent the action policy, which can prematurely commit to suboptimal actions when solving high-dimensional continuous control problems for highly-articulated characters. In this paper, to improve the learning performance of physics-based character controllers, we propose a framework that considers a particle-based action policy as a substitute for Gaussian policies. We exploit particle filtering to dynamically explore and discretize the action space, and track the posterior policy represented as a mixture distribution. The resulting policy can replace the unimodal Gaussian policy which has been the staple for character control problems, without changing the underlying model architecture of the reinforcement learning algorithm used to perform policy optimization. We demonstrate the applicability of our approach on various motion capture imitation tasks. Baselines using our particle-based policies achieve better imitation performance and speed of convergence as compared to corresponding implementations using Gaussians, and are more robust to external perturbations during character control. Related code is available at: https://motion-lab.github.io/PFPN.
Adaptable Agent Populations via a Generative Model of Policies

In the natural world, life has found innumerable ways to survive and often thrive. Between and even within species, each individual is in some manner unique, and this diversity lends adaptability and robustness to life. In this work, we aim to learn a space of diverse and high-reward policies on any given environment. To this end, we introduce a generative model of policies, which maps a low-dimensional latent space to an agent policy space. Our method enables learning an entire population of agent policies, without requiring the use of separate policy parameters. Just as real world populations can adapt and evolve via natural selection, our method is able to adapt to changes in our environment solely by selecting for policies in latent space. We test our generative model's capabilities in a variety of environments, including an open-ended grid-world and a two-player soccer environment. Code, visualizations, and additional experiments can be found at https://kennyderek.github.io/adap/.
Coalgebraic tools for randomness-conserving protocols

Abstract We propose a coalgebraic model for constructing and reasoning about state-based protocols that implement efficient reductions among random processes. We provide basic tools that allow efficient protocols to be constructed in a compositional way and analyzed in terms of the tradeoff between state and loss of entropy. We show how to use these tools to construct various entropy-conserving reductions between processes.
The transfinite element method for modeling MMIC devices

A numerical procedure called the transfinite element-method is used in conjunction with the planar waveguide model to analyze MMIC devices. By using analytic basis functions together with finite-element approximation functions in a variational technique, the transfinite-element method determines the fields and scattering parameters for a wide variety of stripline and microstrip devices. With minor modification, the method can be applied to waveguide junctions, treating singular points in the junctions very efficiently. Calculations are shown for a rectangular-waveguide two-slot 20-dB coupler, stripline band-elimination filter, and several microstrip discontinuity problems. Good agreement of the numerical results with published values demonstrates the validity of the procedure. >
Growth and Integration

This annual conference is a global gathering of the world's leading scholars and practitioners. Among the attendees are participants from developing countries, think tanks, NGOs, and international institutions. These papers concern issues like growth an integration, financial reforms, economic development, trade and development, and investment climate.
Quartz glass pressure vessels for hydrothermal studies

Sealed quartz glass tubes used as pressure vessels in low pressure-temperature experiments in silica- saturated systems
Accuracy of near-surface aerosol extinction determined from columnar aerosol optical depth measurements in Reno, NV, USA

The aim of the present work is a detailed analysis of aerosol columnar optical depth as a tool to determine near-surface aerosol extinction in Reno, Nevada, USA, during the summer of 2012. Ground and columnar aerosol optical properties were obtained by use of in situ Photoacoustic and Integrated Nephelometer and Cimel CE-318 Sun photometer instruments, respectively. Both techniques showed that seasonal weather changes and fire plumes had enormous influence on local aerosol optics. The apparent optical height followed the shape but not magnitude of the development of the convective boundary layer when fire conditions were not present. Back trajectory analysis demonstrated that a local flow known as the Washoe Zephyr circulation often induced aerosol transport from Northern California over the Sierra Nevada Mountains that increased the aerosol optical depth at 500 nm during afternoons when compared with mornings. Aerosol fine mode fraction indicated that afternoon aerosols in June and July and fire plumes in August were dominated by submicron particles, suggesting upwind urban plume biogenically enhanced evolution toward substantial secondary aerosol formation. This fine particle optical depth was inferred to be beyond the surface, thereby complicating use of remote sensing measurements for near-ground aerosol extinction measurements. It is likely that coarse mode depletes fine mode aerosol near the surface by coagulation and condensation of precursor gases.
The Malleable Use of History in Substantive Due Process Jurisprudence: How the "Deeply Rooted" Test Should Not Be a Barrier to Finding the Defense of Marriage Act Unconstitutional Under The Fifth Amendment's Due Process Clause

Passed in 1996, the Defense of Marriage Act ("DOMA") clarifies "marriage" as referring exclusively to a legal union between one man and one woman as husband and wife. Paralleling the intense social debate over same-sex marriages, DOMA sparked an array of scholarly attacks on its own constitutionality. The author argues that scholarship should not overlook substantive due process jurisprudence in challenging DOMA. The U.S. Supreme Court's use of history in defining fundamental rights under substantive clue process is sufficiently flexible to accommodate same-sex marriages within the fundamental right to marriage. The Court, although emphasizing tradition and history as the roots from which fundamental rights stem, has been willing to overlook, or to selectively read, such history and traditions. The author concludes that a failure to extend fundamental right status to same-sex marriage would in fact undermine some of the Court's most notable precedents in this area of law.
Identification of Enterobacteriaceae from Washed and Unwashed Commercial Shell Eggs

To evaluate the effect of processing on the safety and quality of retail shell eggs, a storage study was conducted with unwashed and commercially washed eggs. This work demonstrated that commercial processing decreased microbial contamination of eggshells. To know which species persisted during storage on washed or unwashed eggs, Enterobacteriaceae isolates were selected and identified biochemically. For each of three replications, shell eggs were purchased from a commercial processing plant, transported back to the laboratory, and stored at 4 degrees C. Once a week for 6 weeks, 12 eggs for each treatment (washed and unwashed control) were rinsed in sterile phosphate-buffered saline. A 1-ml aliquot of each sample was plated onto violet red bile glucose agar with overlay and incubated at 37 degrees C for 24 h. Following incubation, plates were observed for colonies characteristic of the family Enterobacteriaceae. A maximum of 10 isolates per positive sample were streaked for isolation before being identified to the genus or species level using commercially available biochemical strips. Although most of the isolates from the unwashed control eggs belonged to the genera Escherichia or Enterobacter, many other genera and species were identified. These included Citrobacter, Klebsiella, Kluyvera, Pantoea, Providencia, Rahnella, Salmonella, Serratia, and Yersinia. Non-Enterobacteriaceae also recovered from the unwashed egg samples included Xanthomonas and Flavimonas. Very few washed egg samples were contaminated with any of these bacteria. These data provide useful information on the effectiveness of processing in removing microorganisms from commercial shell eggs.
Brief report: developmental change in theory of mind abilities in children with autism.

This longitudinal study investigated developmental change in theory of mind among 57 children with autism aged between 4 to 14 years at the start of the study. On an initial visit and one year later, each participant was administered a battery of tests designed to measure a broad developmental range of theory of mind abilities from early (e.g., desire) to more advanced (e.g., moral judgment) mental state understanding. Both group and individual data indicated significant developmental improvement in theory of mind ability, which was primarily related to the children's language abilities.
Association between vegetarian diets and bone health (823.2)

Low bone mineral density (BMD) is associated with an increased risk of osteoporotic fracture, and diet is considered an important modifiable risk factor linked to bone health. While vegetarian diets appear to exhibit health advantages, there is conflicting evidence regarding the effect of these diets on long-term bone health. Purpose: To compare dietary composition, protein status, and bone health in long-term omnivores (OMN) and vegetarians (VEG). Methods: Dietary intake and 24-hour urine was examined in healthy OMN (n=23) and VEG (n=46), aged 19-50 years (30.3 ± 8.0 y). Dietary status ranged from one-year to lifetime adherence. Each subject completed a 24-hour recall, administered by a trained nutritionist, to assess dietary intake and completed a 24-hour urine collection. Urinary nitrogen and calcium were measured in 24-hour urine with colorimetric enzymatic assays. After testing for normality, univariate analyses of total body BMD z-scores were controlled for body weight. Independent samples T-tests w...
Electronic Detection of Nucleic Acids: A Versatile Platform for Molecular Diagnostics

A novel platform for the electronic detection of nucleic acids on microarrays is introduced and shown to perform well as a selective detection system for applications in molecular diagnostics. A gold electrode in a printed circuit board is coated with a self-assembled monolayer (SAM) containing DNA capture probes. Unlabeled nucleic acid targets are immobilized on the surface of the SAM through sequence-specific hybridization with the DNA capture probe. A separate signaling probe, containing ferrocene-modified nucleotides and complementary to the target in the region adjoining the capture probe binding site, is held in close proximity to the SAM in a sandwich complex. The SAM allows electron transfer between the immobilized ferrocenes and the gold, while insulating the electrode from soluble redox species, including unbound signaling probes. Here, we demonstrate sequence-specific detection of amplicons after simple dilution of the reaction product into hybridization buffer. In addition, single nucleotide polymorphism discrimination is shown. A genotyping chip for the C282Y single nucleotide polymorphism associated with hereditary hemochromatosis is used to confirm the genotype of six patients' DNA. In addition, a gene expression-monitoring chip is described that surveys five genes that are differentially regulated in the cellular apoptosis response. Finally, custom modification of individual electrodes through sequence-specific hybridization demonstrates the potential of this system for infectious disease diagnostics. The versatility of the electronic detection platform makes it suitable for multiple applications in diagnostics and pharmacogenetics.
AN EVALUATION OF THE USDA FOOD SECURITY MEASURE WITH GENERALIZED LINEAR MIXED MODELS

Over the last decade, new information has been developed and collected to measure the extent of food insecurity and hunger in the United States. Common measurement of the phenomenon of hunger and food insecurity has become possible through efforts of the U.S. Department of Agriculture (USDA) to develop a set of survey questions that can be used to obtain estimates of the prevalence and severity of food insecurity. This paper takes a closer look at the measurement of food insecurity and the effect of household variables on measured food insecurity. The effects of demographic and survey-specific variables on the food insecurity/hunger scale are evaluated using a generalized linear model with mixed effects. Data come from the 1995, 1997, and 1999 Food Security Module of the Current Population Survey. The results generally validate the model currently used by the U.S. Department of Agriculture. In addition, our approach makes it possible to consider the effect of demographics and several survey design variables on food security among measurably food-insecure households. The analysis of the expanded model with the 1995 data finds results similar to those reported based on the Rasch model used by the USDA. Even though the sample size was reduced and a number of screening and questionnaire changes were introduced in 1997 and 1999, the results for those years appear mostly unchanged and confirm the robustness of the scale in measuring food insecurity. There is some evidence that interpretation of questions may vary among different demographic groups.
Segregation and Integration of Visual Channels: Layer-by-Layer Computation of ON–OFF Signals by Amacrine Cell Dendrites

The visual system analyzes images through parallel channels, and our data suggest that the first set of parallel representations of the visual world is embodied in the inner plexiform layer (IPL) of the retina, in which light-evoked excitatory inputs of the ON and OFF bipolar cells to amacrine cells (ACs) are organized in a layer-by-layer manner. Approximately 30% of ACs have narrowly monostratified dendrites in 1 of the 10 strata of the IPL, and they receive segregated bipolar cell inputs: the light-evoked excitatory cation current, Δ I C, in strata 1, 2, and 4 is OFF (predominantly mediated by the OFF bipolar cells), the current in strata 3 and 7–10 is ON (predominantly mediated by ON bipolar cells), and the current in strata 5 and 6 is ON–OFF (mediated by both ON and OFF bipolar cells). The remaining 70% of ACs have broadly monostratified, multistratified, or diffuse dendrites, and they integrate bipolar cell signals through layer-by-layer summation: ACs with dendrites ramified in multiple strata exhibit Δ I Cs that are sums of Δ I Cs of individual strata. The light-evoked inhibitory chloride current, Δ I Cl, in strata 1, 2, and 4–6 is ON–OFF (mediated predominantly by ON–OFF ACs or ON ACs plus OFF ACs), and the Δ I Cl in strata 3 and 7–10 is ON (mediated predominantly by ON ACs). This indicates that the amacrine–amacrine inhibitory synaptic circuitry in the IPL is asymmetrical in favor of the ON channels.
miR-133a alleviates cardiac autophagy by targeting AMPK in Ins2+/- diabetic mice (868.3)

Optimum level of autophagy is indispensable for survival and cellular function, and miRNA tightly regulates biological functions. In diabetic hearts, miR-133a (anti-hypertrophy and anti-fibrosis) i...
Mixing E-mail with Babel

Increasingly large numbers of people communicate today via electronic means such as email or news forums. One of the basic properties of the current electronic communication means is the identification of the end-points. However, at times it is desirable or even critical to hide the identity and/or whereabouts of the end-points (e.g., human users) involved. This paper discusses the goals and desired properties of anonymous email in general and introduces the design and salient features of Babel anonymous remailer. Babel allows email users to converse electronically while remaining anonymous with respect to each other and to other-even hostile-parties. A range of attacks and corresponding countermeasures is considered. An attempt is made to formalize and quantify certain dimensions of anonymity and untraceable communication.
Interferon Gamma Prolongs Survival of Varicella-Zoster Virus-Infected Human Neurons In Vitro

Infection of human neurons in vitro with varicella-zoster virus (VZV) at a low multiplicity of infection does not result in a cytopathic effect (CPE) within 14 days postinfection (dpi), despite production of infectious virus. We showed that by 28 dpi a CPE ultimately developed in infected neurons and that interferon gamma inhibited not only the CPE but also VZV DNA accumulation, transcription, and virus production, thereby prolonging the life of VZV-infected neurons.
Re-Envisioning The Dissertation Stage Of Doctoral Study: Traditional Mistakes With Non-Traditional Learners

Doctoral students discuss the shift from learning in isolation to collaborative learning during doctoral study. Pros and cons of learning in isolation and collaborative learning will be detailed with various types of collaboration being discussed.
The dissociation kinetics of the ethylenediaminetetrakis(methylenephosphonato) complex of europium(III)

Abstract The dissociation kinetics of the ethylenediaminetetrakis(methylenephosphonato) complex of Eu(III) have been studied in acetate buffer solutions using copper ion as a scavenger of the ligand. The rate expression contains acid independent and acid dependent terms but is independent of the copper ion concentration. The rate of reaction increases with increasing acetate buffer concentration but becomes independent of it at high concentrations. The dissociation is inhibited by protonation in contrast to the dissociation of the car☐ylate analog EuEDTA which is promoted by [H+].
Role of the bile salt surfactant sodium cholate in enhancing the aqueous dispersion stability of single-walled carbon nanotubes: a molecular dynamics simulation study.

Very recently, bile salt biosurfactants have been utilized extensively to disperse individual single-walled carbon nanotubes (SWNTs) in aqueous solution with high weight fractions, as well as to sort SWNTs according to their electronic properties with the aid of ultracentrifugation. To help elucidate the role of bile salts in the SWNT dispersion process, we report the first detailed large-scale all-atomistic molecular dynamics (MD) simulation study of the adsorption and surface self-assembly of a common bile salt surfactant, sodium cholate (SC), on a SWNT in aqueous solution. We find that the cholate ions wrap around the SWNT like a ring and have a small tendency to orient perpendicular to the cylindrical axis of the SWNT, a unique feature that has not been observed for conventional linear surfactants such as sodium dodecyl sulfate (SDS). In addition, we carry out a series of simulations to compute the potential of mean force (PMF) between two parallel SC-covered SWNTs as a function of the intertube separ...
Coordination Compounds of Strontium. Syntheses, Characterizations, and Crystal Structures of [Sr(u-ONc)(2)(HONc(4))]2 and Sr(5)(u(4)-O)(u(3)-ONep)(4)(u-ONep)(4)(HONep)(solv)(4) (ONc=O(2)CCH(2)CMe(3));Nep=CH(2)CMe(3); solv=tetrahydrofuran or 1-methyl-imida

Abstract We have synthesized and characterized two novel Sr compounds: [Sr(μ-ONc)2(HONc)4]2 (1, ONc ˭ O2CCH2CMe3), and Sr5(μ−O)(μ3˭ONep)4(μ˭ONep)4(HONep)(solv)4 [ONep ˭ OCH2CMe3, solv = tetrahydrofuran (THF), 2a; 1-methyl-imidazole (Melm), 2b], that demonstrate increased solubility in comparison to the commercially available Sr precursors. The two metal centers of 1 share four unidentate bridging μ-ONc ligands and complete their octahedral geometry through coordination of four monodentate terminal HONc ligands. The structural arrangement of the central core of 2a and 2b are identical, wherein four octahedral Sr atoms are arranged in a square geometry around a μ4-O ligand. An additional seven-coordinated Sr atom sits directly atop the μ4-O to form a square-pyramidal arrangement of the Sr atoms, but the apical Sr-O distance is too long to be considered a bond. In solution, compound 1 is disrupted forming a monomer but 2a and 2b retain their structures.
Drug-induced lung injury

Lung injury is an increasing cause of morbidity and mortality in patients treated with cytotoxic and noncytotoxic drugs. Prompt diagnosis is important because early drug-induced lung injury will often regress with the cessation of therapy. Diagnosis requires a high index of suspicion because infection, radiation pneumonitis, and recurrence of the underlying disease can manifest clinically and radiologically in a similar manner. Because the lungs have only a limited number of histopathologic responses to injury, including pulmonary edema/diffuse alveolar damage, NSIP, BOOP, EP, and pulmonary hemorrhage, knowledge of these manifestations and the corresponding radiologic manifestations can often be useful in suggesting a diagnosis of drug-induced lung injury. An understanding of the drugs most commonly associated with lung injury can also facilitate diagnosis.
Standoffish states: Nonliterate leviathans in Southeast Asia

Under what conditions do states strive to homogenise their populations, rendering them ‘legible’ for state-making projects? Virtually all conditions, according to James Scott's landmark treatise, The Art of Not Being Governed. Whereas Scott sees states’ appetites to standardise their populations for purposes of control and extraction as practically universal, we see this appetite as radically and fascinatingly uneven. Much as Scott sees mobile populations as ‘nonliterate’ due to their disinterest in (and not their ignorance of) the purported fruits of civilisation, we see Leviathans as frequently ‘nonliterate’ in their disinclination (and not simply their incapacity) to actively administer their subjects and territory: even in Southeast Asia, the region that has done more than any other to generate Scott's theories of state power and practice. We thus argue that the world is riddled with standoffish states, not just standardising states. Even in the zones where the potential costs of eschewing the pursuit of legibility appear highest – those containing violent insurgencies – states can prove surprisingly disinterested in pursuing centralised governance in a highly administrative manner. We highlight four alternative strategies – indirect rule, divide and conquer, militarised pacification, and forcible expulsion – that states commonly deploy to fulfil what we see as their most fundamental objective: preventing political challenges to the ruling centre.