cssi/SciSciGPT-SciSciNet huggingface dataset:
Using a Neural Network to Detect Anomalies Given an N-gram Profile

In order to detect unknown intrusions and runtime errors of computer programs, the cyber-security community has developed various detection techniques. Anomaly detection is an approach that is designed to profile the normal runtime behavior of computer programs in order to detect intrusions and errors as anomalous deviations from the observed normal. However, normal but unobserved behavior can trigger false positives. This limitation has significantly decreased the practical viability of anomaly detection techniques. Reported approaches to this limitation span a simple alert threshold definition to distribution models for approximating all normal behavior based on the limited observation. However, each assumption or approximation poses the potential for even greater false positive rates. This paper presents our study on how to explain the presence of anomalies using a neural network, particularly Long Short-Term Memory, independent of actual data distributions. We present and compare three anomaly detection models, and report on our experience running different types of attacks on an Apache Hypertext Transfer Protocol server. We performed a comparative study, focusing on each model’s ability to detect the onset of each attack while avoiding false positives resulting from unknown normal behavior. Our best-performing model detected the true onset of every attack with zero false positives.
Symmetry of Narayana Numbers and Rowvacuation of Root Posets

For a Weyl group W of rank r, the W-Catalan number is the number of antichains of the poset of positive roots, and the W-Narayana numbers refine the W-Catalan number by keeping track of the cardinalities of these antichains. The W-Narayana numbers are symmetric – that is, the number of antichains of cardinality k is the same as the number of cardinality . However, this symmetry is far from obvious. Panyushev posed the problem of defining an involution on root poset antichains that exhibits the symmetry of the W-Narayana numbers. Rowmotion and rowvacuation are two related operators, defined as compositions of toggles, that give a dihedral action on the set of antichains of any ranked poset. Rowmotion acting on root posets has been the subject of a significant amount of research in the recent past. We prove that for the root posets of classical types, rowvacuation is Panyushev’s desired involution.
Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments

Autonomous exploration is an essential task for unmanned aerial vehicles (UAVs) operating in unknown environments. Often, UAVs on these missions must first build a map of the environment via pure exploration and subsequently use (i.e. exploit) the generated map for downstream navigation tasks. Accomplishing these navigation tasks in two separate steps is not always possible and can potentially be disadvantageous for UAVs deployed in outdoor and dynamically changing environments. Current exploration approaches typically use a priori human-generated maps or heuristics such as frontier-based exploration. Other approaches use learning but focus only on learning policies for specific tasks and use sample inefficient random exploration or make impractical assumptions about full map availability. In this paper, we develop an adaptive exploration approach that allows for a trade off between exploration and exploitation in a single step using Deep Reinforcement Learning (DRL). We specifically focus on UAVs searching for areas of interest (AoIs) in an unknown environment. The proposed approach uses a map segmentation technique to decompose the environment map into smaller, tractable maps. DDQN and A2C algorithms are extended with a stack of LSTM layers and trained to generate optimal policies for the exploration and exploitation tasks, respectively. Then, an information gain function is repeatedly computed to determine the optimal trade-off between them. We tested our approach in 3 different tasks against 4 baselines. The results demonstrate that our proposed approach is capable of navigating through randomly generated environments and covering more AoI in less time compared to the baselines.
Effect of eliminating pre-discharge transthoracic echocardiogram on outcomes after TAVR

OBJECTIVES The aim of this study was to determine the safety of eliminating the pre-discharge transthoracic echocardiogram (TTE) on 30-day outcomes in patients undergoing transcatheter aortic valve replacement (TAVR). BACKGROUND TTE is utilized before, during, and after TAVR. Post-procedural, pre-discharge TTE assists in assessment of prosthesis function and detection of clinically significant paravalvular leak (PVL) after TAVR. METHODS Patients who underwent TAVR at Mayo Clinic from July 2018 to July 2019 were included in a prospective institutional registry. Patients undergoing TAVR prior to February 2019 received a pre-discharge TTE, while those undergoing TAVR after February 2019 did not. Both cohorts were evaluated with TTE at 30 days post-TAVR. RESULTS A total of 330 consecutive patients were included. Of these, 160 patients (age 81.1 ± 7.6) had routine pre-discharge TTE, while 170 patients (age 78.9 ± 7.5) were dismissed without routine pre-discharge TTE. Mortality at 30 days was similar between the two groups (0% and 1.2%, respectively). One episode of PVL requiring intervention (0.6%) occurred in the pre-discharge TTE group and none in the group without pre-discharge TTE at 30-day follow-up. There was a similar incidence of total composite primary and secondary adverse events between the cohort receiving a pre-discharge TTE and those without (28.1% vs. 25.3%, P = 0.56) at 30 days. The most common event was need for permanent pacemaker or ICD implantation in both groups (13.1% vs. 11.8%, P = 0.71). CONCLUSIONS Elimination of the pre-discharge TTE is safe and associated with comparable 30-day outcomes to routine pre-discharge TTE. These findings have implication for TAVR practice cost-efficiency and health care utilization.
An explicit formula for minimizing the infected peak in an SIR epidemic model when using a fixed number of complete lockdowns

Careful timing of nonpharmaceutical interventions such as social distancing may avoid high “second waves” of infections of COVID‐19. This article asks what should be the timing of a set of K complete‐lockdowns of prespecified lengths (such as two weeks) so as to minimize the peak of the infective compartment. Perhaps surprisingly, it is possible to give an explicit and easily computable rule for when each lockdown should commence. Simulations are used to show that the rule remains fairly accurate even if lockdowns are not perfect. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Robust & Nonlinear Control is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Reinsurance in America: Regulatory Regimes and Markets

Despite its large size and long history of insurance and insurable catastrophes and disasters, the United States of America has always lagged in the development of reinsurance companies, an industry still dominated by European and offshore domiciled reinsurers. The US experience shows that reinsurance is a necessary component of the insurance industry but the cost of reinsuring through domestically-domiciled reinsurers can be raised to prohibitive levels by inappropriate taxes and regulations, like the failure to treat reinsurers as a distinct national class in a fragmented, monoline regulatory system. High regulatory costs lead to the development of alternatives, including reinsuring overseas, through reciprocal agreements among direct writers, or via other substitutes, including market-based alternatives (ARTM) like catastrophe and death bonds and other insurance-linked securities (ILS).
The New Authoritarianism in Public Choice

Much early public choice theory focused on alleged pathologies of democratic legislatures, portraying them as irrational, manipulable, or subject to capture. Recent years have seen the emergence of...
Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits

We study the asymptotic performance of the Thompson sampling algorithm in the batched multi-armed bandit setting where the time horizon $T$ is divided into batches, and the agent is not able to observe the rewards of her actions until the end of each batch. We show that in this batched setting, Thompson sampling achieves the same asymptotic performance as in the case where instantaneous feedback is available after each action, provided that the batch sizes increase subexponentially. This result implies that Thompson sampling can maintain its performance even if it receives delayed feedback in ω(log T) batches. We further propose an adaptive batching scheme that reduces the number of batches to Θ(log T) while maintaining the same performance. Although the batched multi-armed bandit setting has been considered in several recent works, previous results rely on tailored algorithms for the batched setting, which optimize the batch structure and prioritize exploration in the beginning of the experiment to eliminate suboptimal actions. We show that Thompson sampling, on the other hand, is able to achieve a similar asymptotic performance in the batched setting without any modifications.
Detecting Attacks on IoT Devices using Featureless 1D-CNN

The generalization of deep learning has helped us, in the past, address challenges such as malware identification and anomaly detection in the network security domain. However, as effective as it is, scarcity of memory and processing power makes it difficult to perform these tasks in Internet of Things (IoT) devices. This research finds an easy way out of this bottleneck by depreciating the need for feature engineering and subsequent processing in machine learning techniques. In this study, we introduce a Featureless machine learning process to perform anomaly detection. It uses unprocessed byte streams of packets as training data. Featureless machine learning enables a low cost and low memory time-series analysis of network traffic. It benefits from eliminating the significant investment in subject matter experts and the time required for feature engineering.
Exploring Targeted Universal Adversarial Perturbations to End-to-End ASR Models

Although end-to-end automatic speech recognition (e2e ASR) models are widely deployed in many applications, there have been very few studies to understand models' robustness against adversarial perturbations. In this paper, we explore whether a targeted universal perturbation vector exists for e2e ASR models. Our goal is to find perturbations that can mislead the models to predict the given targeted transcript such as "thank you" or empty string on any input utterance. We study two different attacks, namely additive and prepending perturbations, and their performances on the state-of-the-art LAS, CTC and RNN-T models. We find that LAS is the most vulnerable to perturbations among the three models. RNN-T is more robust against additive perturbations, especially on long utterances. And CTC is robust against both additive and prepending perturbations. To attack RNN-T, we find prepending perturbation is more effective than the additive perturbation, and can mislead the models to predict the same short target on utterances of arbitrary length.
Mixing rates for Hamiltonian Monte Carlo algorithms in finite and infinite dimensions

We establish the geometric ergodicity of the preconditioned Hamiltonian Monte Carlo (HMC) algorithm defined on an infinite-dimensional Hilbert space, as developed in Beskos et al. (Stoch Process Appl 121(10):2201–2230, 2011). This algorithm can be used as a basis to sample from certain classes of target measures which are absolutely continuous with respect to a Gaussian measure. Our work addresses an open question posed in Beskos et al. (2011), and provides an alternative to a recent proof based on exact coupling techniques given in Bou-Rabee and Eberle (Two-scale coupling for preconditioned Hamiltonian Monte Carlo in infinite dimensions , 2019). The approach here establishes convergence in a suitable Wasserstein distance by using the weak Harris theorem together with a generalized coupling argument. We also show that a law of large numbers and central limit theorem can be derived as a consequence of our main convergence result. Moreover, our approach yields a novel proof of mixing rates for the classical finite-dimensional HMC algorithm. As such, the methodology we develop provides a flexible framework to tackle the rigorous convergence of other Markov Chain Monte Carlo algorithms. Additionally, we show that the scope of our result includes certain measures that arise in the Bayesian approach to inverse PDE problems, cf. Stuart (Acta Numer 19:451–559, 2010). Particularly, we verify all of the required assumptions for a certain class of inverse problems involving the recovery of a divergence free vector field from a passive scalar, Borggaard et al. (SIAM/ASA J Uncertain Quant 8(3):1036–1060, 2020).
Neuro-symbolic artificial intelligence: Current trends

Neuro-Symbolic Artificial Intelligence -- the combination of symbolic methods with methods that are based on artificial neural networks -- has a long-standing history. In this article, we provide a structured overview of current trends, by means of categorizing recent publications from key conferences. The article is meant to serve as a convenient starting point for research on the general topic.
Reduced models of unidirectional flows in compliant rectangular ducts at finite Reynolds number

Soft hydraulics, which addresses the interaction between an internal flow and a compliant conduit, is a central problem in microfluidics. We analyze Newtonian fluid flow in a rectangular duct with a soft top wall at steady state. The resulting fluid–structure interaction is formulated for both vanishing and finite flow inertia. At the leading-order in the small aspect ratio, the lubrication approximation implies that the pressure only varies in the streamwise direction. Meanwhile, the compliant wall's slenderness makes the fluid–solid interface behave like a Winkler foundation, with the displacement fully determined by the local pressure. Coupling flow and deformation and averaging across the cross section leads to a one-dimensional reduced model. In the case of vanishing flow inertia, an effective deformed channel height is defined rigorously to eliminate the spanwise dependence of the deformation. It is shown that a previously used averaged height concept is an acceptable approximation. From the one-dimensional model, a friction factor and the corresponding Poiseuille number are derived. Unlike the rigid duct case, the Poiseuille number for a compliant duct is not constant but varies in the streamwise direction. Compliance can increase the Poiseuille number by a factor of up to four. The model for finite flow inertia is obtained by assuming a parabolic vertical variation of the streamwise velocity. To satisfy the displacement constraints along the edges of the channel, weak tension is introduced in the streamwise direction to regularize the Winkler-foundation-like model. Matched asymptotic solutions of the regularized model are derived.
A society of organizations

It is a commonplace today that organizations are a key element of U.S. society and those of other industrialized nations. I argue here that the importance of large organizations in the United States is still insufficiently appreciated. The nineteenth-century industrial revolution, much of our politics and social structure, and many of the crises of the 1980s and 1990s must be reinterpreted in the light of "organizational variables." I cannot do all of this in an essay, but I lay out the argument and lightly illustrate it.
Detection of Anomalous Patterns Associated with the Impact of Medications on 30-Day Hospital Readmission Rates in Diabetes Care

Improving quality of care in diabetes requires a good understanding of variations in diabetes outcomes and related interventions. However, little is known about the impact of diabetes interventions on outcome measures at the subpopulation-level. In this study, we developed methods that combine causal inference techniques with subset scanning techniques to study the heterogeneous effects of treatments on binary health outcomes. We analyzed a diabetes dataset consisting of 70,000 initial inpatient encounters to investigate the anomalous patterns associated with the impact of 4 anti-diabetic medication classes on 30-day readmission in diabetes. We discovered anomalous subpopulations where the likelihood of readmission was up to 1.8 times higher than that of the overall population suggesting subpopulation-level heterogeneity. Identifying such subpopulations may lead to a better understanding of the heterogeneous effects of treatments and improve targeted intervention planning.
On the Underlying Drag-Reduction Mechanisms of Flow-Control Strategies in a Transitional Channel Flow: Temporal Approach

The underlying mechanisms of three different flow-control strategies on drag reduction in a channel flow are investigated by direct numerical simulations at friction Reynolds numbers ranging from 65 to 85. These strategies include the addition of long-chain polymers, the incorporation of slip surfaces, and the application of an external body force. While it has been believed that such methods lead to a skin-friction reduction by controlling near-wall flow structures, the underlying mechanisms at play are still not as clear. In this study, a temporal analysis is employed to elucidate underlying drag-reduction mechanisms among these methods. The analysis is based on the lifetime of intermittent phases represented by the active and hibernating phases of a minimal turbulent channel flow (Xi and Graham, Phys Rev Lett 2010). At a similar amount of drag reduction, the polymer and slip methods show a similar mechanism, while the body force method is different. The polymers and slip surfaces cause hibernating phases to happen more frequently, while the duration of active phases is decreased. However, the body forces cause hibernating phases to happen less frequently but prolong its duration to achieve a comparable amount of drag reduction. A possible mechanism behind the body force method is associated with its unique roller-like vortical structures formed near the wall. These structures appear to prevent interactions between inner and outer regions by which hibernating phases are prolonged. It should motivate adaptive flow-control strategies to exploit the distinct underlying mechanisms for robust control of turbulent drag at low Reynolds numbers.
ARCH: Efficient Adversarial Regularized Training with Caching

Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they need to generate a perturbation for each sample in each epoch. We propose a new adversarial regularization method ARCH (adversarial regularization with caching), where perturbations are generated and cached once every several epochs. As caching all the perturbations imposes memory usage concerns, we adopt a K-nearest neighbors-based strategy to tackle this issue. The strategy only requires caching a small amount of perturbations, without introducing additional training time. We evaluate our proposed method on a set of neural machine translation and natural language understanding tasks. We observe that ARCH significantly eases the computational burden (saves up to 70% of computational time in comparison with conventional approaches). More surprisingly, by reducing the variance of stochastic gradients, ARCH produces a notably better (in most of the tasks) or comparable model generalization. Our code is publicly available.
Online Robust Reinforcement Learning with Model Uncertainty

Robust reinforcement learning (RL) is to find a policy that optimizes the worst-case performance over an uncertainty set of MDPs. In this paper, we focus on model-free robust RL, where the uncertainty set is defined to be centering at a misspecified MDP that generates a single sample trajectory sequentially and is assumed to be unknown. We develop a sample-based approach to estimate the unknown uncertainty set and design a robust Q-learning algorithm (tabular case) and robust TDC algorithm (function approximation setting), which can be implemented in an online and incremental fashion. For the robust Q-learning algorithm, we prove that it converges to the optimal robust Q function, and for the robust TDC algorithm, we prove that it converges asymptotically to some stationary points. Unlike the results in [Roy et al., 2017], our algorithms do not need any additional conditions on the discount factor to guarantee the convergence. We further characterize the finite-time error bounds of the two algorithms and show that both the robust Q-learning and robust TDC algorithms converge as fast as their vanilla counterparts(within a constant factor). Our numerical experiments further demonstrate the robustness of our algorithms. Our approach can be readily extended to robustify many other algorithms, e.g., TD, SARSA, and other GTD algorithms.
Genome-wide approaches delineate the additive, epistatic, and pleiotropic nature of variants controlling fatty acid composition in peanut (Arachis hypogaea L.).

The fatty acid composition of seed oil is a major determinant of the flavor, shelf-life, and nutritional quality of peanuts. Major QTLs controlling high oil content, high oleic content, and low linoleic content have been characterized in several seed oil crop species. Here we employ genome-wide association approaches on a recently genotyped collection of 787 plant introduction accessions in the USDA peanut core collection, plus selected improved cultivars, to discover markers associated with the natural variation in fatty acid composition, and to explain the genetic control of fatty acid composition in seed oils. Overall, 251 single nucleotide polymorphisms (SNPs) had significant trait associations with the measured fatty acid components. Twelve SNPs were associated with two or three different traits. Of these loci with apparent pleiotropic effects, 10 were associated with both oleic (C18:1) and linoleic acid (C18:2) content at different positions in the genome. In all 10 cases, the favorable allele had an opposite effect-increasing and lowering the concentration, respectively, of oleic and linoleic acid. The other traits with pleiotropic variant control were palmitic (C16:0), behenic (C22:0), lignoceric (C24:0), gadoleic (C20:1), total saturated, and total unsaturated fatty acid content. One hundred (100) of the significantly associated SNPs were located within 1000 kbp of 55 genes with fatty acid biosynthesis functional annotations. These genes encoded, among others: ACCase carboxyl transferase subunits, and several fatty acid synthase II enzymes. With the exception of gadoleic (C20:1) and lignoceric (C24:0) acid content, which occur at relatively low abundance in cultivated peanut, all traits had significant SNP interactions exceeding a stringent Bonferroni threshold (α = 1%). We detected 7,682 pairwise SNP interactions affecting the relative abundance of fatty acid components in the seed oil. Of these, 627 SNP pairs had at least one SNP within 1000 kbp of a gene with fatty acid biosynthesis functional annotation. We evaluated 168 candidate genes underlying these SNP interactions. Functional enrichment and protein-to-protein interactions supported significant interactions (p-value < 1.0E-16) among the genes evaluated. These results show the complex nature of the biology and genes underlying the variation in seed oil fatty acid composition and contribute to an improved genotype-to-phenotype map for fatty acid variation in peanut seed oil.
BFEMP: Interpenetration-free MPM–FEM coupling with barrier contact

Abstract This paper introduces BFEMP, a new approach for monolithically coupling the Material Point Method (MPM) with the Finite Element Method (FEM) through barrier energy-based particle–mesh frictional contact using a variational time-stepping formulation. The fully implicit time integration of the coupled system is recast into a barrier-augmented unconstrained nonlinear optimization problem. A modified line-search Newton’s method is adopted to strictly prevent material points from penetrating the FEM domain, ensuring convergence and feasibility regardless of the time step size or the mesh resolutions. The proposed coupling scheme also reduces to a new approach for imposing separable frictional kinematic boundaries for MPM when all nodal displacements in the FEM domain are prescribed with Dirichlet boundary conditions. Compared to standard implicit time integration, the extra algorithmic components associated with the contact treatment only depend on simple point-segment (or point-triangle in 3D) geometric queries which robustly handle arbitrary FEM mesh boundaries represented with codimension-1 simplices. Experiments and analyses are performed to demonstrate the robustness and accuracy of the proposed method.
Transcriptomic Changes Highly Similar to Alzheimer’s Disease Are Observed in a Subpopulation of Individuals During Normal Brain Aging

Aging is a major risk factor for late-onset Alzheimer’s disease (LOAD). How aging contributes to the development of LOAD remains elusive. In this study, we examined multiple large-scale transcriptomic data from both normal aging and LOAD brains to understand the molecular interconnection between aging and LOAD. We found that shared gene expression changes between aging and LOAD are mostly seen in the hippocampal and several cortical regions. In the hippocampus, the expression of phosphoprotein, alternative splicing and cytoskeleton genes are commonly changed in both aging and AD, while synapse, ion transport, and synaptic vesicle genes are commonly down-regulated. Aging-specific changes are associated with acetylation and methylation, while LOAD-specific changes are more related to glycoprotein (both up- and down-regulations), inflammatory response (up-regulation), myelin sheath and lipoprotein (down-regulation). We also found that normal aging brain transcriptomes from relatively young donors (45-70 years old) clustered into several subgroups and some subgroups showed gene expression changes highly similar to those seen in LOAD brains. Using brain transcriptomic data from another cohort of older individuals (> 70 years), we found that samples from cognitively normal older individuals clustered with the “healthy aging” subgroup while AD samples mainly clustered with the “AD similar” subgroups. This may imply that individuals in the healthy aging subgroup will likely remain cognitively normal when they become older and vice versa. In summary, our results suggest that on the transcriptome level, aging and LOAD have strong interconnections in some brain regions in a subpopulation of cognitively normal aging individuals. This supports the theory that the initiation of LOAD occurs decades earlier than the manifestation of clinical phenotype and it may be essential to closely study the “normal brain aging” to identify the very early molecular events that may lead to LOAD development.
Family Recreation for University Faculty

(1964). Family Recreation for University Faculty. Journal of Health, Physical Education, Recreation: Vol. 35, No. 3, pp. 33-35.
A citizen privacy protection model for e-government mashup services

The Web 2.0 technologies allow dynamic content creation using syndications or mashups, extracted from diverse data sources, including government enterprise data. As a primary source of citizen data, the government has the obligation not only to make public data available for citizen access as stated in the Freedom of Information Act, but also to protect the privacy of individual citizen's records as stated in the Privacy Act. Unlike in the electronic commercial environment where the user can view the company privacy policy and indicate transaction data to be protected through opt-out mechanisms, opt-out in the mashup environment with government data is not so easy. In a mashup, a third party mashup Web application provider requests the individual's data from the government agencies through Web services. Since the data is public data not necessarily provided through an electronic interaction, individual citizens are not necessarily able to express fine-grained privacy policies on how data may be used. In addition, the government agency's privacy policy is very coarse grained, and the relative sensitivity of individual citizens is not considered. In this paper, we provide a Privacy Protection Model for Mashup Applications, using a mashup related multi-dimensional privacy protection space which includes parameters to specify mashup providers, mashup-specific operators, and mashup purposes. A personal privacy policy network is a distributed architecture where citizens can publish their individual privacy policies that can be applied to the use of their data and consulted by data providers including government agencies.
Antibody immunosuppressive therapy in solid-organ transplant

Currently, a wide variety of both polyclonal and monoclonal antibodies are being routinely utilized to prevent and treat solid organ rejection. More commonly, these agents are also administered in order to delay introduction of calcineurin inhibitors, especially in patients with already compromised renal function. While these antibody therapies dramatically reduced the incidence of acute rejection episodes and improved both short and long-term graft survival, they are also associated with an increased incidence of opportunistic infections and neoplastic complications. Therefore, effective patient management must necessarily balance these risks against the potential benefits of the therapy.
Simulation of heat transfer and air cooling in a power rectifier cabinet for generator excitation system

As an important part of the modern generator excitation system, the power rectifier cabinet accommodates the silicon-controlled rectifiers (SCRs) whose junction temperature should be kept within limit at all times. For excitation systems of 1000MW steam turbine generator and 700WM hydro generator, the required output DC current for each rectifier cabinet can be as high as 4,000A, which raises challenge for cooling design. Meanwhile, under normal operation conditions, excessive cooling wastes energy and causes frequent change of air filter due to high volume cooling air flow. In order to optimize the cooling design, the heat transfer and cooling processes are simulated for a power rectifier cabinet with 6 SCRs and using forced air cooling. First the heat generated by the SCR is calculated as a function of the rectifier cabinet output current. 3D implicit unsteady k-e turbulent model is used to simulate the air flow. The energy is coupled between the solid and the fluid (air) to reflect the heat transfer from the SCR to the heat sink and then to the cooling air. For given output current and inlet air velocity, the temperature of the SCRs, heat sinks and the cooling air is simulated; the air velocity at each location in the cabinet is also calculated. The simulation results showed good agreement with the experiment data which laid the foundation for future application of the simulation tool.
Reducing Disruptive Behavior of a Group-Home Resident with Autism and Mental Retardation

A treatment package consisting of a DRO procedure, token fines, and prompted relaxation was used to reduce the agitated-disruptive behavior of a person with autism and mental retardation living in a community group home. The agitated-disruptive behaviors (cursing, hitting, kicking, throwing objects, and verbal threats) were measured during three different activities in a group home. The baseline rates of the agitated-disruptive behavior during one of these activities was relatively low, during another was moderate, and during the third was high. DRO procedures were partially implemented by a peer with Down syndrome and mental retardation during a portion of the study. Effects of the DRO procedures were as follows: During each activity an initial reduction of agitated-disruptive behavior was dependent on choosing an appropriate DRO interval, with shorter DRO intervals required during activities in which the baseline rates of the agitated-disruptive behavior were higher. Once shorter DRO intervals had been used to reduce agitated-disruptive behavior, longer DRO intervals were effective in maintaining those reductions. Reductions were maintained for up to 6 months.
Quantification of Primary Motor Pathways Using Diffusion MRI Tractography and Its Application to Predict Postoperative Motor Deficits in Children With Focal Epilepsy

As a new tool to quantify primary motor pathways and predict postoperative motor deficits in children with focal epilepsy, the present study utilized a maximum a posteriori probability (MAP) classification of diffusion weighted imaging (DWI) tractography combined with Kalman filter. DWI was performed in 31 children with intractable focal epilepsy who underwent epilepsy surgery. Three primary motor pathways associated with “finger,” “leg,“ and “face” were classified using DWI-MAP classifier and compared with the results of invasive electrical stimulation mapping (ESM) via receiver operating characteristic (ROC) curve analysis. The Kalman filter analysis was performed to generate a model to determine the probability of postoperative motor deficits as a function of the proximity between the resection margin and the finger motor pathway. The ROC curve analysis showed that the DWI-MAP achieves high accuracy up to 89% (finger), 88% (leg), 89% (face), in detecting the three motor areas within 20 mm, compared with ESM. Moreover, postoperative reduction of the fiber count of finger pathway was associated with postoperative motor deficits involving the hand. The prediction model revealed an accuracy of 92% in avoiding postoperative deficits if the distance between the resection margin and the finger motor pathway seen on preoperative DWI tractography was 19.5 mm. This study provides evidence that the DWI-MAP combined with Kalman filter can effectively identify the locations of cortical motor areas even in patients whose motor areas are difficult to identify using ESM, and also can serve as a reliable predictor for motor deficits following epilepsy surgery. Hum Brain Mapp 35:3216–3226, 2014. © 2013 Wiley Periodicals, Inc.
Muscle-related differences in mechanomyography–force relationships are model-dependent.

Introduction: In this study we examined the mechanomyographic amplitude (MMGRMS)–force relationships with log-transform and polynomial regression models for the vastus lateralis (VL), rectus femoris (RF), and first dorsal interosseous (FDI) muscles. Methods: Twelve healthy (age 23 ± 3 years) men performed isometric ramp contractions of the leg extensors and index finger from 10% to 80% of their maximal voluntary contraction (MVC) with MMG sensors positioned on the VL, RF, and FDI. Log-transform and polynomial regression models were fitted to the relationships. Results: There were differences for the a terms (intercepts) and b terms (slopes) from the log-transform model between the FDI, VL, and RF; however, there were no consistent differences identified with the polynomial regression models. Conclusions: The log-transform model quantified differences in the patterns of responses between the FDI and the leg extensors, but polynomial regression could not distinguish such differences. Muscle Nerve 49: 202–208, 2014
The effect of preoperative β-blocker use and race on long-term survival after coronary artery bypass grafting.

regression model. A total of 1,448 (62%) black and 6,094 (55%) white patients had a history of preoperative β-blocker use. Among black patients, those receiving β-blockers survived longer than those not receiving β-blockers (adjusted HR ¼ 0.77, 95% CI ¼ 0.67-0.88). The survival advantage was comparable to that observed among white patients (adjusted HR ¼ 0.88, 95% CI ¼ 0.82-0.93).
Differentiation-Dependent Interpentameric Disulfide Bond Stabilizes Native Human Papillomavirus Type 16

Genetic and biochemical analyses of human papillomavirus type 16 (HPV16) capsids have shown that certain conserved L1 cysteine residues are critical for capsid assembly, integrity, and maturation. Since previous studies utilized HPV capsids produced in monolayer culture-based protein expression systems, the ascribed roles for these cysteine residues were not placed in the temporal context of the natural host environment for HPV, stratifying and differentiating human tissue. Here we extend upon previous observation, that HPV16 capsids mature and become stabilized over time (10-day to 20-day) in a naturally occurring tissue-spanning redox gradient, by identifying temporal roles for individual L1 cysteine residues. Specifically, the C175S substitution severely undermined wild-type titers of the virus within both 10 and 20-day tissue, while C428S, C185S, and C175,185S substitutions severely undermined wild-type titers only within 20-day tissue. All mutations led to 20-day virions that were less stable than wild-type and failed to form L1 multimers via nonreducing SDS-PAGE. Furthermore, Optiprep-fractionated 20-day C428S, C175S, and C175,185S capsids appeared permeable to endonucleases in comparison to wild-type and C185S capsids. Exposure to an oxidizing environment failed to enhance infectious titers of any of the cysteine mutants over time as with wild-type. Introduction of these cys mutants results in failure of the virus to mature.
Molecular dynamics simulations of surface reconstruction at the edges of a crack in ruthenium aluminum

Using molecular dynamics computer simulations and interatomic potentials derived partly by Voter and Chen1 and Rifkin et al.,2 we studied the surface reconstruction taking place on free surfaces of arrays of RuAl. Surface reconstruction appears to be very important on (111) and (110) types of planes and almost nonexistent on (100) type of planes. Cracks oriented so that their crack planes were either (111) types or (110) types exhibit on their internal free surface important surface reconstruction. It is believed that this effect may have some contribution in the brittle versus ductile behavior of the crack.
Diets of Muskellunge in Northern Wisconsin Lakes

Abstract The muskellunge Esox masquinongy is an important sport fish in Wisconsin and elsewhere, but more information about its diet is needed to better understand its role in aquatic systems and its effects on other fish. Stomach contents were examined for 1,092 muskellunge (226–1,180 mm total length, TL) captured in the littoral zone from 34 Wisconsin water bodies from Jul 1991 to Oct 1994. Food occurred in 34.3% (N = 375) of the stomachs, with most (74%) containing a single item. Overall, the proportion of muskellunge with food differed significantly among seasons, with the greatest proportion occurring in fall (69.0%), followed by summer (53.5%) and then spring (25.4%). Prey items consisted of 547 fish, representing 12 families and 31 species, along with 35 nonfish items; fish composed 98% of the diet. Relative importance values of diet items varied by taxa, season, and water body, but the main food items eaten by muskellunge in each season were yellow perch Perca flavescens and white sucker Catostomo...
Design research for the living curriculum

This paper reports on design research for an on-line performance support system that provides case-based support for teaching project-based science curricula. The goal of the system is to provide teachers using PBS curricula with access to help in the form of examples of the enacted curriculum, answer common questions, and support for key teaching tasks.
Murine leukemia. Proposed role for gangliosides in immune suppression

Abstract Glycolipid-bound sialic acid levels were elevated 2 to 4-fold in the sera of two strains of mice bearing thymic lymphoma produced either spontaneously (AKR/J) or due to chemical carcinogenesis [Swiss mice injected with 5-(3,3-dimethyl-1-triazeno)imidazole-4-carboximide]. The serum glycolipid-bound sialic acid level reflected the tumor burden of the AKR/J mice during the early stages of leukemogenesis. Furthermore, the elevation was found to coincide with the ontogenesis of thymic lymphoma and not to be simply an age-dependent phenomenon. TLC analysis of Florisil column-purified gangliosides from the sera of AKR/J and Swiss mice suggested presence of gangliosides with mobilities very close to GM2 and GM3 standards respectively. On the premise that the elevated glycolipid levels in circulation might interfere with normal lymphocyte functions, the immunoinhibitory properties of exogenously added mixed gangliosides were examined on tests of in vitro correlates of the immune response. Gangliosides inhibited concanavalin A and lipopolysaccharide-induced [ 3 H ]-thymidine, [ 14 C ]-leucine and [ 3 H ]-lysine uptake by normal AKR/J mouse thymocytes and spleen cells. Mixed gangliosides also suppressed the two-way mixed lymphocyte reaction of AKR/J × Swiss and AKR/J × DBA/2 spleen cells. These and other results strongly suggest a general immunologically relevant role for gangliosides in the ontogeny of thymic lymphoma of mice.
Ionic Polymer-Metal Composites (IPMCs) as dexterous manipulators and tactile sensors for minimally invasive robotic surgery

Robot-assisted surgery provides the surgeons with new tools to perform sophisticated surgical operations in a minimally invasive manner. Small robotic end-effectors at the tip of the surgical forceps are the key advantage of robotic surgery over laparoscopic surgery and any improvement on the design of these small robots can significantly improve the overall functionality of the surgical robots. In this sense, novel bio-compatible electro-active polymeric actuators can improve the design and functionality of these robotic end-effectors particularly by introducing smaller and more flexible robotic tools. Here, we introduce the applications of IPMCs as flexible actuators with embedded tactile and force feedback sensors in minimally-invasive robotic surgery. A new design for the robotic manipulation of the organs is presented in which a two dimensional IPMC actuator is replaced with the rigid robotic distal tip. It is shown that with a customized design, IPMC actuators maintain the required dexterity for two-dimensional bending of robotic distal tip. The overall design of the robot could be considered as a hybrid robot with the combination of rigid robotic links and flexible IPMC actuator with two degrees of freedom. On the other hand with the current robotic distal tips, no tactile force feedback is available during surgery and the surgeons rely solely on vision feedback. With the proposed design of actuator, the IPMC based distal tip could be used to deliver force feedback data by using an embedded IPMC tactile sensor. Design considerations, kinematics and chemo-electro-mechanical model of the proposed actuator is presented.
MSU Tailbot: Controlling Aerial Maneuver of a Miniature-Tailed Jumping Robot

Inspired by the aerial maneuvering ability of lizards, we present the design and control of MSU (Michigan State University) tailbot—a miniature-tailed jumping robot. The robot can not only wheel on the ground, but also jump up to overcome obstacles. Moreover, once leaping into the air, it can control its body angle using an active tail to dynamically maneuver in midair for safe landings. We derive the midair dynamics equation and design controllers, such as a sliding mode controller, to stabilize the body at desired angles. To the best of our knowledge, this is the first miniature (maximum size $7.5$ cm) and lightweight ( $26.5$ g) robot that can wheel on the ground, jump to overcome obstacles, and maneuver in midair. Furthermore, tailbot is equipped with on-board energy, sensing, control, and wireless communication capabilities, enabling tetherless or autonomous operations. The robot in this paper exemplifies the integration of mechanical design, embedded system, and advanced control methods that will inspire the next-generation agile robots mimicking their biological counterparts. Moreover, it can serve as mobile sensor platforms for wireless sensor networks with many field applications.
Surface‐Enhanced Raman Scattering on Silver Nanoparticles in Different Aggregation Stages

Enhancement factors of surface-enhanced Raman scattering (SERS) are compared for crystal violet attached to 15-60-nm-sized colloidal silver particles in various aggregation stages using 830 nm and 407 nm laser excitation. Enhancement factors on the order of 10 6 -10 7 have been measured at 407 nm excitation for molecules adsorbed on spatially-isolated silver spheres exhibiting strong, sharp, single-sphere plasmon resonance at 395 nm. Extremely large SERS enhancement factors on the order of 10 14 are obtained at near infrared excitation for molecules on clusters built from colloidal particles. The SERS enhancement factor is demonstrated to be independent of the size of the clusters. The increase of SERS enhancement factors by 7-8 orders of magnitude by the formation of aggregates, as well as the extremely small density of "hot sites" exhibiting this high level of enhancement, provide further strong arguments for the electromagnetic origin of the hot spots and for strongly enhanced local optical fields as a key effect in SERS at an extremely high enhancement level.
The contribution of residual nephrons within the chronically diseased kidney to urate homeostasis in man

Abstract Forty-nine clearance studies were performed in thirty-six patients with stable chronic renal disease in order to elucidate the role of residual nephrons in the maintenance of urate homeostasis. With increasing severity of disease, plasma urate neither became elevated as soon nor did it increase to so great a degree as plasma urea nitrogen. This appeared to be at least partially explicable on the basis of a marked increase in urate excretion per nephron (UV urate : C inulin ), which was particularly striking when inulin clearance had decreased to less than 15 ml. per minute. At this level of renal function a fivefold increase in UV urate : C inulin was observed whereas the plasma urate concentration had less than doubled. Pyrazinamide, a potent inhibitor of tubular secretion of urate, was administered to all patients in order to assess the role of each component of the bidirectional transport system for urate at different stages of disease. Until the inulin clearance had decreased to less than 10 ml. per minute, an appropriate augmentation of tubular secretory rate for urate (TS ur ) was observed for any degree of hyperuricemia. Reabsorption of filtered urate remained essentially complete in patients with C inulin over 15 ml. per minute. With advanced disease, urate secretion was markedly reduced in association with a striking increase in fractional excretion of filtered urate. The latter phenomenon was of much greater quantitative significance, thus accounting for the marked increase in excretion per nephron in advanced disease. Repeat studies following the induction of normouricemia by allopurinol administration indicated that urate secretion of patients with disease, as in normal subjects, is profoundly influenced by the plasma urate level, as opposed to fractional excretion of urate, which was not predictably altered. Thus, until advanced uremia supervenes, residual nephrons of the chronically diseased kidney retain integrity of urate reabsorptive and secretory transport. When disease becomes severe, glomerulotubular imbalance evolves, permitting excretion of 45 per cent of the filtered urate. Thus, although substrate-regulated tubular secretion is the principal homeostatic mechanism for urate excretion in normal and the majority of diseased kidneys, glomerular filtration assumes this role in far advanced renal disease.