cssi/SciSciGPT-SciSciNet huggingface dataset:
Suitability, digestibility and assimilation of various host plants of the gypsy moth Lymantria dispar L.

The development and survival of gypsy moth (Lymantria dispar) larvae is strongly influenced by the host plant upon which they feed. The most rapid development and largest pupae were produced from grey birch fed larvae. Beech and maple-fed larvae produced the smallest pupae while maple-fed larvae exhibited prolonged development. White and red oak-fed larvae exhibited development and pupal weights intermediate between the above two groups. The approximate digestibility (AD) and efficiencies of conversion of food (ECD and ECI) were generally highest among grey birchfed individuals. The utilization of the relatively closely related oak species, as reflected in AD and ECD values, differed.Leaves were examined for 14 elements. The content of each element varied among host plant species and over time. For example, nitrogen levels were highest in grey-birch and dropped over time in all host plants.
Information extraction and text summarization using linguistic knowledge acquisition

Abstract Storing and accessing texts in a conceptual format has a number of advantages over traditional document retrieval methods. A conceptual format facilitates natural language access to text information. It can support imprecise and inexact queries, conceptual information summarization, and, ultimately, document translation. The lack of extensive linguistic coverage is the major barrier to extracting useful information from large bodies of text. Current natural language processing (NLP) systems do not have rich enough lexicons to cover all the important words and phrases in extended texts. Two methods of overcoming this limitation are (1) to apply a text processing strategy that is tolerant of unknown words and gaps in linguistics knowledge, and (2) to acquire lexical information automatically from the texts. These two methods have been implemented in a prototype intelligent information retrieval system called SCISOR (System for Conceptual Information Summarization, Organization and Retrieval). This article describes the text processing, language acquisition, and summarization components of SCISOR.
Second level adaptation using multiple models

The concept of using multiple models to cope with transients which arise in adaptive systems with large parametric uncertainties was introduced in the 1990s. Both switching between multiple fixed models, and switching and tuning between fixed and adaptive models was proposed, and the stability of the resulting schemes was established. In all cases, the number of models needed is generally large, and the models used do not cooperate in any real sense. It was recently shown by the authors that if it is known a priori that the unknown plant parameter vector lies in the convex hull of a set of adaptive model parameter vectors at the initial time, it will remain in the convex hull of the parameters even as they evolve with time [1]. Later, a stability result was derived in [2] which decouples the stability and performance issues. In this paper, a new concept of second level adaptation is introduced to develop different stable strategies which improve the performance of the overall system. Simulation results are provided to illustrate the effectiveness of the proposed scheme in a rapidly time-varying environment, and are shown to be far superior to existing schemes.
Start up performance of load-commutated inverter fed synchronous machine drives

Load-commutated inverter (LCI) synchronous machine drives are common in the high power range. However, the starting performance of these systems is a concern since load-commutation cannot occur at arbitrarily low speeds. This paper compares three different starting strategies including one apparently neglected method-normal load commutation. In particular, it is shown that, depending on system parameters, it may be possible to start the system with no special provision for start up. A method to determine whether a given system can be started using load commutation is presented. >
Pulmonary vein occlusion/stenosis after pulmonary vein ablation for atrial fibrillation.

In this issue of the Journal. Ernst et al.1 report three cases of total pulmonary vein (PV) occlusion in 239 patients who underwent an ablation procedure for atrial fibrillation (AF). Patients initially were evaluated by internists and pulmonologists and underwent extensive evaluation before the diagnosis was finally made. Despite treatment with thrombolytics, glycoprotein IIb/IIIa inhibitors and anticoagulation, angioplasty, and stenting, restenosis developed. Because imaging studies after a PV ablation procedure were not routinely performed in all patients, the true incidence of PV stenosis and occlusion could not be determined. PV stenosis may be one of the most serious complications after a PV ablation procedure, as treatment options are limited and restenosis may recur after interventional procedures. Depending on the PV ablation strategy used and whether or not routine imaging studies were performed, the prevalence of PV stenosis has been reported to vary from 0% to 8%.2,3
Stochastic Mirror Descent Algorithm for L1-Regularized Risk Minimizations

L1-regularized empirical risk minimization is a popular method for feature selections. In this paper we propose a fast online algorithms for solving large-scale L1-regularized problems. The proposed stochastic mirror descent algorithm is a stochastic version of the mirror-prox method. We show that mirror descent is a unified framework of several recently proposed algorithms. Experiments on large-scale datasets demonstrate that the proposed SMD algorithm is much faster than the recently proposed truncated gradient algorithm (TG). At the same testing accuracy, SMD yields sparser solutions than TG, while at the same sparseness, SMD has a higher testing accuracy.
Dispersion of ventricular activation and refractoriness in patients with idiopathic dilated cardiomyopathy

We sought to evaluate the electrophysiologic substrate for ventricular arrhythmias and sudden cardiac death in patients with idiopathic dilated cardiomyopathy. When compared with controls, patients with cardiomyopathy had prolonged activation times, increased dispersion of activation and recovery, and prolonged duration of monophasic action potential recordings at 70%, but not at 90%, of repolarization.
A Global Optimization Approach for Electrical Machine Designs

Optimization techniques have been widely applied to the design of electric machines. Traditional approaches, however, are only effective to find the local optima. This paper reports an engineering project that concerns the global optimization issues of electrical machine design. An advanced mathematical method, the filled function method (FFM), is adapted to seek the global minimum of the multi-modal model of electrical machines. Detailed analysis is presented for the configuration of the FFM in a constrained environment, construction of the algorithm, and implementation of the software. Results of the numerical experiments shows that the effectiveness of the proposed approach.
Exploiting the Monthly Data Flow in Structural Forecasting

This paper develops a framework that allows us to combine the tools provided by structural models for economic interpretation and policy analysis with those of reduced-form models designed for nowcasting. We show how to map a quarterly dynamic stochastic general equilibrium (DSGE) model into a higher frequency (monthly) version that maintains the same economic restrictions. Moreover, we show how to augment the monthly DSGE with auxiliary data that can enhance the analysis and the predictive accuracy in now-casting and forecasting. Our empirical results show that both the monthly version of the DSGE and the auxiliary variables offer help in real time for identifying the drivers of the dynamics of the economy.
Distribution automation using microcomputer technology

Abstract The development of microcomputers has resulted in numerous applications in the areas of power system protection, control, and data acquisition. Micros are currently being used for communications processors in remote terminal units and in sequence of events recorders. They provide a degree of “intelligence” and flexibility previously unknown. Future applications include their use as dedicated control modules in substation automation schemes and as replacements for traditional protective relays. The combined advantages of low cost and high performance will result in widespread use in power system applications.
A sequential Monte Carlo filter for joint linear/nonlinear state estimation with application to DS-CDMA

A sequential Monte Carlo filter is considered which combines previously developed sequential importance sampling (SIS) techniques for conditional linear Gaussian models with measurement linearization for construction of approximate simulation densities. The resulting sequential Monte Carlo Kalman filter (SMC-KF) consists of a bank of conventional Kalman filters individually tuned to sampled trajectories of the nonlinear state variables. Sampling is according to a Gaussian distribution, with mean and covariance determined by extended Kalman filter-type equations. The SMC-KF is then applied to joint delay and multipath channel estimation in direct-sequence code-division multiple access (DS-CDMA). A combined analytical/simulation technique is employed to compare performance of the SMC-KF and a previously derived extended Kalman filter (EKF)-based DS-CDMA channel estimator.
Action Learning Research: A Systematic Review and Conceptual Framework

Despite considerable interest in action learning, no systematic investigation of action learning literature has been reported. Two purposes of this study are (a) to systematically access and examine recent empirical studies on action learning and related themes using Garrard’s Matrix Method for reviewing literature (the review of the literature covered an 8-year period from 2000 to 2007; 50 studies have been selected based on the search criteria) and (b) based on Revans’s proposition regarding the need for a conceptual and practical balance between action and learning, to categorize empirical studies into action-oriented, learning-oriented, and balanced action learning. Studies selected from the systematic literature review process are highlighted, and Revans’s balance issue and the quality of select studies are discussed. A conceptual framework for the future studies of action learning, key concluding themes, and the limitations of the study are also articulated.
Data-driven equivalence checking

We present a data driven algorithm for equivalence checking of two loops. The algorithm infers simulation relations using data from test runs. Once a candidate simulation relation has been obtained, off-the-shelf SMT solvers are used to check whether the simulation relation actually holds. The algorithm is sound: insufficient data will cause the proof to fail. We demonstrate a prototype implementation, called DDEC, of our algorithm, which is the first sound equivalence checker for loops written in x86 assembly.
Evaluation of memory system extensions

A traditional memory system for a uniprocessor consists of one or two levels of cache, a main memory and a backing store. One can extend such a memory sys tem by adding inexpensive but slower memories into the memory hierarchy. This paper uses an experimental approach to evaluate two methods of extending a memory system: direct and caching. The direct method adds the slower memory into the memory hierarchy by putting it at the same level as the main memory, allowing the CPU to access the slower memories directly; whereas the caching method puts the slower memory between the main memory and the backing store, using the main memory as a cache for the slower memory. We have implemented both approaches and our experiments indicate that applications with very large data structures can benefit significantly using an extended memory system, and that the direct approach outperforms the caching approach in memory-bound applications.
Real-time mobility tracking algorithms for cellular networks based on Kalman filtering

We propose two algorithms for real-time tracking of the location and dynamic motion of a mobile station in a cellular network using the pilot signal strengths from neighboring base stations. The underlying mobility model is based on a dynamic linear system driven by a discrete command process that determines the mobile station's acceleration. The command process is modeled as a semi-Markov process over a finite set of acceleration levels. The first algorithm consists of an averaging filter for processing pilot signal, strength measurements and two Kalman filters, one to estimate the discrete command process and the other to estimate the mobility state. The second algorithm employs a single Kalman filter without prefiltering and is able to track a mobile station even when a limited set of pilot signal measurements is available. Both of the proposed tracking algorithms can be used to predict future mobility behavior, which can be, useful in resource allocation applications. Our numerical results show that the proposed tracking algorithms perform accurately over a wide range of mobility parameter values.
Time, Cost and Environmental Impact Analysis on Construction Operations

Environmentally conscious construction has been a subject of research for decades. Even though construction literature involves plenty of studies that emphasize the importance of environmental impact during the construction phase of a project, most of them were not focused on better understanding the relationship among project performance criteria in construction especially including environmental impact. Due to the multi-objectives nature of construction projects and the lack of understanding of such relationship, it is important to have a method for construction professionals to select optimal construction solutions when environmental impact is considered as an additional performance criterion. This paper presents a framework to determine optimal solutions based on project time, cost and environment impact (TCEI). Life cycle assessment was applied to the evaluation of environmental impact in terms of global warming potential (GWP). Genetic algorithms were used for time, cost and environmental impact optimization. A case of study was used to illustrate the application of the framework. Such framework can be applied to the planning of construction projects.
Increasing homicide rates and linoleic acid consumption among five Western countries, 1961-2000.

Clinical intervention trials and animal studies indicate that increasing dietary intakes of long chain n−3 FA or reducing linoleic acid intake may reduce aggressive and violent behaviors. Here we examine if economic measures of greater n−6 consumption across time and countries correlate with greater risk of homicide. Linoleic acid available for human consumption was calculated from World Health Organization disappearance data for 12 major seed oils in the food supply for the years 1961 to 2000 in Argentina, Australia, Canada, the United Kingdom, and the United States (US). Homicide mortality rates, adjusted for age, were obtained from the central judicial authority of each country. Apparent linoleic acid intake from seed oil sources ranged from 0.29 en% (percentage of daily food energy) (Australia 1962) to 8.3 en% (US 1990s). Greater apparent consumption of linoleic acid correlated with higher rates of homicide mortality over a 20-fold range (0.51–10.2/100,000) across countries and time in an exponential growth regression model (r=0.94, F=567, P<0.00001). Within each country, correlations between greater linoleic acid disappearance and homicide mortality over time were significant in linear regression models. Randomized controlled trials are needed to determine if reducing high intakes of linoleic acid by seed oils with alternative compositions can reduce the risk of violent behaviors. These dietary interventions merit exploration as relatively cost-effective measures for reducing the pandemic of violence in Western societies, just as dietary interventions are reducing cardiovascular mortality. Low linoleate diets may prevent behavioral maladies that correctional institutions, social service programs, and mental health providers intend to treat.
Modeling Weekly Truck Rates for Perishables

The transportation literature reveals several studies that attempt to model freight rates. These efforts are important as they provide insight into rate determinants and consequently assist firms in planning, provide input into transportation policy debates, and are of use in transportation and commodity research. In such studies, freight-rate variations typically are explained by differences in commodity types, competition from alternative modes, and distance (Perkins; Benishay and Whitaker; Binkley and Harrar; Ferguson and Glorfeld; Boles; Miklius). However, when shippers must rely on one mode to ship a very limited mix of goods to one or a few destinations, this approach is of little use in explaining rate variations. The produce industry is a case in point. (This abstract was borrowed from another version of this item.)
Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website

BACKGROUND Public reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex. OBJECTIVE To assess interpretability of HAI data as presented on the Centers for Medicare and Medicaid Services Hospital Compare website among patients who might benefit from access to these data. METHODS We randomly selected inpatients at a large tertiary referral hospital from June to September 2014. Participants performed 4 distinct tasks comparing hypothetical HAI data for 2 hospitals, and the accuracy of their comparisons was assessed. Data were presented using the same tabular formats used by Centers for Medicare and Medicaid Services. Demographic characteristics and healthcare experience data were also collected. RESULTS Participants (N=110) correctly identified the better of 2 hospitals when given written descriptions of the HAI measure in 72% of the responses (95% CI, 66%–79%). Adding the underlying numerical data (number of infections, patient-time, and standardized infection ratio) to the written descriptions reduced correct responses to 60% (55%–66%). When the written HAI measure description was not informative (identical for both hospitals), 50% answered correctly (42%–58%). When no written HAI measure description was provided and hospitals differed by denominator for infection rate, 38% answered correctly (31%–45%). CONCLUSIONS Current public HAI data presentation methods may be inadequate. When presented with numeric HAI data, study participants incorrectly compared hospitals on the basis of HAI data in more than 40% of the responses. Research is needed to identify better ways to convey these data to the public. Infect. Control Hosp. Epidemiol. 2016;37(2):182–187
Displacement and Urban Reinvestment: A Mount Laurel Perspective

This article discusses the continuing national debate concerning the responsibility that local governments should accept when residents are forced to leave their homes as a result of reinvestment activities encouraged by the cities and funded in part with public funds. The author explains the many different forms that reinvestment displacement may take and traces the legislative and judicial response to this issue. Despite what the author refers to as a considerable amount of buck passing, the article points out resources that are being made available to combat displacement. The article highlights the Supreme Court of New Jersey opinion in the Mount Laurel case that reaffirmed the moral and legal principle that local governments must consider the housing needs of affected citizens when they use the police power to regulate land use. The article concludes by suggesting that minimizing displacement can be accomplished if cities encourage reinvestment and place a higher priority on the interest of the long term residents of reinvestment areas. The major responsibility of such a task lies with state and local government who have developed the highly sophisticated reinvestment techniques that draw heavily on their police power.
Increasing the effectiveness of benchmarking in the restaurant industry

Benchmarking has been shown to be an important activity in almost every industry. Benchmarking allows for measurable processes, systems and results to be compared (benchmarked) against those of other organisations. The foodservice industry has a variety of attributes that can be measured and compared. First, though, restaurants should be classified on the basis of attributes such as service level, average check, type of food served, availability of alcohol, and the presence or absence of entertainment, etc. This study discusses the importance of benchmarking and why a reliable classification system is needed to allow effective benchmarking to occur. It then takes an existing and newly developed system and builds on it by adding two important (and differentiating) operational characteristics. Using cluster analysis and these variables as the basis of differentiation, seven groups were discovered. Implications for practitioners and academics are discussed. A comprehensive classification system, quantitatively derived, allows restaurant practitioners and academics to have a clear way to compare and benchmark performance in various foodservice environments. This also allows the large variety of foodservice segments to differentiate between the operational and performance variances that are inherent due to the distinctions mentioned.
Renormalization of the IBA Hamiltonian for the Effects of the g Boson

The IBA Hamiltonian is renormalized in lowest order for the effects of the g boson. The renormalization of the single d boson energy e is calculated explicitly, with an application of this result to the barium isotopes.
Reachability Analysis and Deterministic Global Optimization of DAE Models

This article provides a tutorial overview of recent progress in numerical methods for the reachability analysis and deterministic global optimization of DAE models. These problems are highly interrelated, and are global problems in the sense that they concern the parametric solutions of a DAE model over a potentially large range of model parameters, rather than locally about a single value. Many techniques are available for computing such global information for functions known in closed-form (i.e., factorable functions). Two of the simplest and most flexible techniques are interval arithmetic and McCormick’s relaxation technique. The methods reviewed herein extend these techniques to functions defined as the solutions of DAE models, which are notably non-factorable. In doing so, we repeatedly exploit the idea that the factorable representations of the DAE governing equations, combined with insights from dynamical systems theory, can be used to infer global information about the DAE solutions. This concept is first used to derive methods for computing interval bounds and more general convex enclosures of the solutions of DAE models over a range of model parameters. Subsequently, these enclosures are employed in a branch-and-bound algorithm for deterministic global dynamic optimization with DAE’s embedded. The article closes with an illustrative case study in parameter estimation and some prospects for future work.
Nutritional Requirements of Camponotus Ants

It has been shown that the amount of food received by colonies of Camponotus influences imaginal stature among the workers produced (Smith, F. 1942). The following experiments were performed to see if the quality of the food received by Camponotus colonies would influence the size of the workers produced. Camponotus herculeanus subspecies pennsylvanicus DeGeer is probably both aphidicolous and entomophagous because the workers are commonly observed visiting aphids on the branches and leaves of trees. They will also readily attack and devour insect larvae that are given to them, whether in the laboratory or in the runways of their nests out-of-doors.
Phenological and Morphological Responses of Mesic and Dry Site Sources of Coastal Douglas-fir to Water Deficit

La variation genetique des reponses morphologiques et phenologiques au deficit hydrique est decrite pour des semis descendants de 4 sources cotieres de Douglas provenant de stations cotieres et interieures de l'Oregon. Ces populations different pour toutes les caracteristiques etudiees et ces differences refletent une adaptation a l'environnement de la source. Une analyse discriminante canonique a ete utilisee pour determiner les variables refletant le mieux les differences entre les descendants des populations cotieres et interieures. Les consequences sur la selection des genotypes convenant aux milieux secs est etudiee
Inhibition of Vascular Endothelial Growth Factor Receptor 2 Exacerbates Loss of Lower Motor Neurons and Axons during Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) and its animal model experimental autoimmune encephalomyelitis (EAE) are inflammatory demyelinating and neurodegenerative diseases in the central nervous system (CNS). It is believed that MS and EAE are initiated by autoreactive T lymphocytes that recognize myelin antigens; however, the mechanisms responsible for neurodegeneration in these diseases remain elusive. Data indicate that vascular endothelial growth factor A (VEGF-A) plays a role in the development of MS and EAE. Interestingly, VEGF-A is regarded as a neurotrophic factor in the CNS that promotes neuron survival and neurogenesis in various neurodegenerative diseases by activating VEGF receptor 2 (VEGFR2). In this study, we sought to explore the role of the VEGF-A/VEGFR2 signaling in neurodegeneration in MS and EAE. We showed that the expression of VEGF-A was decreased in the spinal cord during EAE and that VEGFR2 was activated in lower motor neurons in the spinal cord of EAE mice. Interestingly, we found that treatment with SU5416, a selective VEGFR2 inhibitor, starting after the onset of EAE clinical symptoms exacerbated lower motor neuron loss and axon loss in the lumbar spinal cord of mice undergoing EAE, but did not alter Purkinje neuron loss in the cerebellum or upper motor neuron loss in the cerebral cortex. Moreover, SU5416 treatment had a minimal effect on EAE clinical symptoms as well as inflammation, demyelination, and oligodendrocyte loss in the lumbar spinal cord. These results imply the protective effects of the VEGF-A/VEGFR2 signaling on lower motor neurons and axons in the spinal cord in MS and EAE.
Entertainment-Education Narrative Versus Nonnarrative Interventions to Educate and Motivate Latinas to Engage in Mammography Screening:

Background. The evidence is limited comparing the effects of entertainment-education (E-E) narrative versus nonnarrative interventions to educate and motivate Latinas to engage in mammography screening. Aims. This study compared an E-E narrative intervention to two nonnarrative interventions’ effects among Latinas on breast cancer knowledge and motivation, as measured by changes in self-efficacy, behavioral norms, and behavioral intentions to engage in mammography screening. Method. A sample of 141 Spanish-speaking Latinas was randomly assigned to one of three arms: an E-E narrative video, a nonnarrative educational video, and printed educational materials. Using a repeated measures design, the influence of the E-E narrative on pretest to posttest measures was assessed and compared to the influence of the other two interventions. Results. The E-E narrative and nonnarrative interventions significantly increased Latinas’ breast cancer knowledge, mammography self-efficacy, and behavioral norms from pretest t...
Design, Characterization, and Application of a Field-Programmable Thermal Emulation Platform

This paper presents an on-chip digitally programmable thermal coupling emulation framework, referred to as the field-programmable thermal emulator (FPTE), for online characterization of power pattern, time-varying thermal field, and associated changes in the electrical characteristics of the transistors. A test chip was designed in 130-nm CMOS to validate the test structure. The measurement results demonstrated the ability of FPTE to emulate various power patterns and capture the effects on temperature and circuit performance. The test chip is used to explore and identify thermal coupling. The potential application of FPTE moves beyond thermal package tests and is capable of being used as chip-level thermal condition prediction and management infrastructure.
Probing of Thermo-Acoustic Transients in Materials Using EUV Radiation

The first application of EUV high-harmonic light to probe the nonlinear optical photoacoustic response of a sample is reported. This will enable measurements of thermal and acoustic transients in materials with sub-100nm resolution and wavelength.
Development of a Fuzzy Logic Control System in Matlab for an Air Impingement Oven

The Stein Lab Oven is an air impingement oven used for research at the University of Arkansas on the elimination of pathogens such as Salmonella, Listeria monocytogenes and Escherichia coli from ready-to-eat beef and poultry products. This oven allows for control over cooking time, cooking temperature, humidity and airflow. During research the oven is operated at desired constant temperature, humidity and airflow values, but the temperature and humidity values deviate from the desired values when disturbances occur, such as when raw product is brought into the oven. A fuzzy logic control system is developed to maintain constant temperature and humidity values and quickly recover from disturbances to the oven. A model of the oven is developed in Matlab to facilitate the modeling, design, testing and verification of the fuzzy logic controller in Matlab.
Managing community managers: social labor, feminized skills, and professionalization

In the game industry, community managers engage in social and emotional labor as they split their loyalties between game communities and game companies. Community managers do not fully represent the interests of one group, and their intermediary role puts particular stresses on the types of emotional labor that they are called upon to enact. Further, community managers must also participate in social labor---work that builds and exploits social connections for monetary gain. Most of this labor, however, is undervalued and in some instances is simply uncompensated "free" labor carried out by members of a fan community. Ultimately, we argue, casting the role of the community manager as a social and emotional laborer feminizes this work, monetarily devaluing it while isolating workers in these roles from the communities that they ostensibly serve.
Alarm Performance Metrics

Abstract Alarm systems are designed to annunciate to the operators the presence of abnormal conditions that require their intervention. However, present day alarm systems are improperly managed leading to alarm floods even during minor upsets and large number of standing and chattering alarms during normal and abnormal operations. Poor alarm system performance can have serious consequences with significant economic and safety impact. Re -engineering alarm systems require a systematic alarm rationalisation procedure that involves significant time and effort. While the costs involved in this redesign can be easily quantified, the benefits cannot be easily estimated. In this work a framework to estimate alarm system effectiveness by considering alarm system performance and operator performance is discussed. Based on this framework, a simple approach is proposed to estimate the impact of alarm system effectiveness on plant operating costs.
Neuromagnetic responses to tactile stimulation of the fingers: Evidence for reduced cortical inhibition for children with Autism Spectrum Disorder and children with epilepsy.

Abstract The purpose of this study was to compare somatosensory responses from a group of children with epilepsy and a group of children with autism spectrum disorder (ASD), with age matched TD controls. We hypothesized that the magnitude of the tactile “P50m” somatosensory response would be reduced in both patient groups, possibly due to reduced GABAergic signaling as has been implicated in a variety of previous animal models and in vivo human MRS studies. We observed significant (~ 25%) decreases in tactile P50m dipole moment values from the source localized tactile P50m response, both for children with epilepsy and for children with ASD. In addition, the latency of the tactile P50m peak was observed to be equivalent between TD and ASD groups but was significantly delayed in children with epilepsy by ~ 6 ms. Our data support the hypothesis of impaired GABAergic signaling in both children with ASD and children with epilepsy. Further work is needed to replicate these findings and directly relate them to both in vivo measures of GABA via e.g. magnetic resonance spectroscopy and psychophysical assessments of somatosensory function, and behavioral indices.
Why Do Large Positive Non-GAAP Earnings Adjustments Predict Abnormally High CEO Pay?

CEOs of S&P 500 firms that report high non-GAAP earnings relative to GAAP earnings receive substantial unexplained pay. Crucially, this result remains even after controlling for the level of non-GAAP and GAAP earnings. These firms are relatively poor performers (i.e., low GAAP earnings and stock returns) and have less powerful CEOs, consistent with non-GAAP earnings being used as justification when high executive pay is more likely to cause outrage. Indeed, despite the lower GAAP and return performance, these firms are more likely to beat the earnings targets specified in their compensation plans, which likely increases investors’ perceptions of core operating earnings and reduces outrage. However, while the fraction of CEO pay that seems attributable to opportunistic non-GAAP reporting is economically meaningful, it is also limited, meaning that the bulk of CEO pay likely represents reward for performance.
Growing Up Fast: Implications for Foster Youth When Independence and Early Adulthood Collide

Abstract Foster care alumni face overwhelming challenges as they transition from care to independence. Torn between their desire to be independent, yet acknowledging they need support, they struggle to find their footing. Adopting a survivor self-reliance mind-set, they set out to earn a bachelor's degree on their own. As they struggle, they compare themselves to non-foster peers who, by enlarge, have a support system enabling them a prolonged entrance to adulthood, which provides a safety net. Without a safety net, and with a focus on independence, decisions youth from foster care make, result in few alumni earning a bachelor's degree.
A symmetric positive semi-definite 3-D FDTD subgridding algorithm for arbitrary grid settings without compromising accuracy

In this work, we develop an accurate 3-D FDTD subgridding algorithm suitable for arbitrary subgrid arrangements and grid ratios. More important, the resultant numerical system is symmetric positive semi-definite in nature, and hence ensuring stability without compromising accuracy. It also permits a local time step in different grids, thus providing an efficient solution for solving multiscale problems. Numerical experiments have demonstrated the performance the proposed algorithm.
Leg stereotypy syndrome: phenomenology and prevalence

Objectives To describe the phenomenology and prevalence of leg stereotypy syndrome (LSS), characterised chiefly by repetitive, rhythmical, stereotypic leg movement, especially when sitting. Methods We sought to characterise LSS in two groups of subjects: (1) general population (GP) group, defined as individuals accompanying patients during their visits to Baylor College of Medicine Parkinson’s Disease Center and Movement Disorders Clinic who are not genetically related to the patients; and (2) movement disorders (MD) group, composed of consecutive patients with diagnoses of restless legs syndrome, Parkinson’s disease, Tourette syndrome and tardive dyskinesia. Results There were 92 participants enrolled in this study; 7% of 57 individuals in the GP group and 17% of those in the MD group met the diagnostic criteria for LSS. The mean age of individuals with LSS was 44.5 (±11.9) years and mean age at onset of LSS was 17.5 (±5.7) years. In half of the individuals, the ‘shaking’ involved predominantly one leg. All had a positive family history of similar disorder and none had diurnal variation. The seven-item Leg Stereotypy Syndrome Questionnaire was developed as a screening tool to aid in differentiating LSS from other movement disorders. Conclusions LSS is a common condition, occurring in up to 7% of otherwise healthy individuals, and it is even more common in patients with hyperkinetic movement disorders. Although it phenomenologically may overlap with other stereotypic disorders, we argue that it is a distinct, familial, neurological syndrome.
Successful MitraClip for Severe Mitral Regurgitation Secondary to Papillary Muscle Rupture as a Complication of Transcatheter Aortic Valve Replacement.

An 82-year-old woman with history of hypertension, hyperlipidemia, hypothyroidism, remote breast cancer, deafness, and severe symptomatic aortic stenosis underwent transfemoral transcatheter aortic valve replacement (TAVR) with an Edwards SAPIEN S3 valve (Edwards Lifesciences, Irvine, California),
Perioperative Outcome in Geriatric Patients

Increasing number of very old patients (> 80 year old) are presenting for invasive procedures and surgeries. This review addresses perioperative outcomes after cardiac and non-cardiac surgery, in octogenarians and older patients. The overall rates of major upper abdominal cancer resections in octogenarians are increasing over time. Postoperative mortality, postoperative admission to the intensive care unit, and discharge to non-home disposition, after emergency general surgery, were strongly associated with age greater than 80 years. Though acceptable, perioperative morbidity and mortality tends to increase non-linearly after the age of 75 years in patients undergoing cardiac operations. Clinician-centric outcomes continue to dominate outcome reporting. Octogenarians have higher risk of mortality and increased rates of complications, both after cardiac and non-cardiac surgeries. Perioperative care is more resource intensive in the elderly. It is important to keep these factors in mind when contemplating interventions in very elderly individuals.
Generating predictions to aid the scientific discovery process

NGLAUBER is a system which models the scientific discovery of qualitative empirical laws. As such, it falls into the category of scientific discovery systems. However, NGLAUBER can also be viewed as a conceptual clustering system since it forms classes of objects and characterizes these classes. NGLAUBER, differs from existing scientific discovery and conceptual clustering systems in a number of ways. 1. It uses an incremental method to group objects into classes. 2. These classes are formed based on the relationships between objects rather than just the attributes of objects. 3. The system describes the relationships between classes rather than simply describing the classes. 4. Most importantly, NGLAUBER proposes experiments by predicting future data. The experiments help the system guide itself through the search for regularities in the data.
The Lehigh Valley Stroke Program: establishing a communitywide, hospital-based stroke register.

A communitywide, hospital-based stroke register has been established in the Lehigh Valley of Pennsylvania and New Jersey. The Lehigh Valley has about 600,000 inhabitants and is geographically somewhat isolated. Ninety-five percent of the people are white, and the population has an age-sex distribution like that of the United States as a whole. All patients falling into any of nine diagnostic categories of stroke or transient ischemic attack are registered on admission to a hospital, and medical, social, and demographic data are abstracted onto precoded data forms. A single neurologist assigns definitive diagnoses according to standardized criteria after reviewing all of the medical data. The stroke register provides a new and powerful tool for collecting population-based data on a large number of cases in a short time. After adjusting for demographic differences, epidemiologic studies can be carried out that may be generalizable to the entire United States. Several organizational aspects of the register and its operation are described in this report, and examples of the types of information and statistics readily calculable from the data in the register are given. The completeness of the stroke ascertainment and the large population registered also offer an excellent opportunity for any interested researcher to investigate the relationships between medical, social, and demographic conditions on the one hand and stroke risk on the other; to study the efficacy of prevention and treatment programs; and to determine health care provision requirements in a well-defined population.
Model Registration and Validation

An important application of machine vision is to provide a means to monitor a scene over a period of time and report changes in the content of the scene. We have developed a validation mechanism that implements the first step towards a system for detecting changes in images of aerial scenes. Validation seeks to confirm of the presence of model objects in the image. Our system uses a 3-D site model of the scene as a basis for model validation, and eventually for detecting changes and to update the site model. The validation process is implemented in three steps: resection, fine registration of the image to the model by matching of model features to image features, and validation of the objects in the model. Our system, if necessary, is aided by shadows to help validate the model. The system has been tested using a hand-generated site model and several images of a 500:1 scale model of the site, acquired form several viewpoints.
Release of Kallikrein and Tonin from the Rat Submandibular Gland

The interaction of neurotransmitters and hormones with specific receptors on the plasma membranes of cells results in enzyme secretion from exocrine glands. However, the effects of agonists on the release of kallikrein and tonin from the rat submandibular gland have not yet been evaluated systematically. The purpose of the present study was to investigate the effects of norepinephrine, isoproterenol, methacholine, and cholecystokinin on the simultaneous release of kallikrein and tonin from the rat submandibular gland. Submandibular gland slices were incubated in vitro at 37° C in a modified Krebs-Ringer medium containing 0.2% each of glucose and bovine serum albumin and bubbled with a gas mixture of 95% O2 and 5% CO2. Glandular kallikrein and tonin secreted into the incubation medium were determined by specific radioimmunoassays. Norepinephrine at 10-5M concentration increased kallikrein secretion from a control value of 7.7 ± 1.5 to 114.7 ± 26.9 ng/min/mg tissues (p<.01), and at 10-4M concentration kallikrein secretion increased to 265.9 ± 58.3 ng/min/mg tissue (p<.01). Similarly, norepinephrine at 10-5M enhanced the release of tonin from a basal rate of 4.4 ± 0.6 to 57 ±14.4 ng/min/mg tissue (p<.05), and at 10-4M the rate increased to 91.3 ± 20.0 ng/min/mg tissue (p<.01). In contrast, isoproterenol, methacholine, and cholecystokinin did not increase the secretion of kallikrein or tonin. We conclude that the secretion of kallikrein and tonin from rat submandibular glands upon sympathetic stimulation is mediated through stimulation of α-adrenoceptors only.
Signal Detection Analysis of Choice Behavior and Aging

The primary research question was whether older adults respond to the contingencies of reinforcement such that they allocate their behavior as predicted by the reinforcement contingencies and discriminative stimuli programmed by the experimenters. Six subjects, ranging in age from 62 to 74 years, participated in 15 experimental sessions. Subjects were instructed to press the “F1” key when they saw a white circle, and to press the “F12” key when they saw a red letter “A.” Responses on the F1 key were reinforced on a variable interval (VI) 30-s schedule (i.e., a VI schedule of reinforcement with 11 arithmetically spaced intervals with a mean of 30 s); F12 key responses were reinforced on a VI 60-s schedule (i.e., a VI schedule of reinforcement with 11 arithmetically spaced intervals with a mean of 60 s). Reinforcers included monetary units (10 cents) and verbal praise. Results indicated positive effects of stimulus control of behavior. Collective false alarms and miss rates represented only 0.05% of the total responses. Also, two thirds of the subjects allocated behavior consistent with the second hypothesis that a denser reinforcement schedule (i.e., the VI 30-s) would cause subjects to respond more quickly to this condition. Implications of the present results for clinical studies of Alzheimer's Disease and dementia, as well as behavior modification strategies with aging individuals, are discussed.
Deep CSI Learning for Gait Biometric Sensing and Recognition.

Gait is a person's natural walking style and a complex biological process that is unique to each person. Recently, the channel state information (CSI) of WiFi devices have been exploited to capture human gait biometrics for user identification. However, the performance of existing CSI-based gait identification systems is far from satisfactory. They can only achieve limited identification accuracy (maximum $93\%$) only for a very small group of people (i.e., between 2 to 10). To address such challenge, an end-to-end deep CSI learning system is developed, which exploits deep neural networks to automatically learn the salient gait features in CSI data that are discriminative enough to distinguish different people Firstly, the raw CSI data are sanitized through window-based denoising, mean centering and normalization. The sanitized data is then passed to a residual deep convolutional neural network (DCNN), which automatically extracts the hierarchical features of gait-signatures embedded in the CSI data. Finally, a softmax classifier utilizes the extracted features to make the final prediction about the identity of the user. In a typical indoor environment, a top-1 accuracy of $97.12 \pm 1.13\%$ is achieved for a dataset of 30 people.