Miracle-dz/UniFAR-FTUs huggingface dataset:
Does brain activity stem from high-dimensional chaotic dynamics? Evidence from the human electroencephalogram, cat cerebral cortex and artificial neuronal networks

Nonlinear time series analyses have suggested that the human electroencephalogram (EEG) may share statistical and dynamical properties with chaotic systems. During slow-wave sleep or pathological states like epilepsy, correlation dimension measurements display low values, while in awake and attentive subjects, there is not such low dimensionality, and the EEG is more similar to a stochastic variable. We briefly review these results and contrast them with recordings in cat cerebral cortex, as well as with theoretical models. In awake or sleeping cats, recordings with microelectrodes inserted in cortex show that global variables such as local field potentials (local EEG) are similar to the human EEG. However, in both cases, neuronal discharges are highly irregular and exponentially distributed, similar to Poisson stochastic processes. To attempt reconcile these results, we investigate models of randomly-connected networks of integrate-and-fire neurons, and also contrast global (averaged) variables, with neuronal activity. The network displays different states, such as "synchronous regular" (SR) or "asynchronous irregular" (AI) states. In SR states, the global variables display coherent behavior with low dimensionality, while in AI states, the global activity is high-dimensionally chaotic with exponentially distributed neuronal discharges, similar to awake cats. Scale-dependent Lyapunov exponents and epsilon-entropies show that the seemingly stochastic nature at small scales (neurons) can coexist with more coherent behavior at larger scales (averages). Thus, we suggest that brain activity obeys similar scheme, with seemingly stochastic dynamics at small scales (neurons), while large scales (EEG) display more coherent behavior or high-dimensional chaos.
Foal Monocyte-Derived Dendritic Cells Become Activated upon Rhodococcus equi Infection

ABSTRACT Susceptibility of foals to Rhodococcus equi pneumonia is exclusive to the first few months of life. The objective of this study was to investigate the immediate immunologic response of foal and adult horse antigen-presenting cells (APCs) upon infection with R. equi. We measured the activation of the antigen-presenting major histocompatibility complex (MHC) class II molecule, costimulatory molecules CD40 and CD86, the cytokine interleukin-12 (IL-12), and the transcriptional factor interferon regulatory factor 1 (IRF-1) in monocyte-derived macrophages (mMOs) and dendritic cells (mDCs) of adult horses and foals of different ages (from birth to 3 months of age) infected with virulent R. equi or its avirulent, plasmid-cured derivative. Infection with virulent or avirulent R. equi induced (P ≤ 0.01) the expression of IL-12p35 and IL-12p40 mRNAs in foal mMOs and mDCs at different ages. This response was likely mediated by the higher (P = 0.008) expression of IRF-1 in foal mDCs at birth than in adult horse mDCs. R. equi infection promoted comparable expression of costimulatory molecules CD86 and CD40 in foal and adult horse cells. The cytokine and costimulatory response by foal mDCs was not accompanied by robust MHC class II molecule expression. These data suggest that foal APCs detect the presence of R. equi and respond with the expression of the Th1-inducing cytokine IL-12. Nevertheless, there seems to be a limitation to MHC class II molecule expression which we hypothesize may compromise the efficient priming of naïve effector cells in early life.
SumTime-Mousam: Configurable marine weather forecast generator

Numerical weather prediction (NWP) models produce time series data of basic weather parameters which human forecasters use as guidance while writing textual forecasts. Our studies of humans writing textual weather forecasts led us to build S UM T IME -M OUSAM , a text generator that produces textual marine weather forecasts for offshore oilrig applications. S UM T IME -M OUSAM separates control and processing. As a result of this forecasters can tailor the output text using control data derived from end user profiles. In this paper we describe the design and the implementation details of S UM T IME -M OUSAM which is currently being used by our industrial collaborator. Output from our system is post-edited by forecasters before communicating it to the end-users. We also briefly describe an evaluation of our system using the post-edit data.
Photocatalytic Removal of Microcystin-LR by Advanced WO3-Based Nanoparticles under Simulated Solar Light

A series of advanced WO3-based photocatalysts including CuO/WO3, Pd/WO3, and Pt/WO3 were synthesized for the photocatalytic removal of microcystin-LR (MC-LR) under simulated solar light. In the present study, Pt/WO3 exhibited the best performance for the photocatalytic degradation of MC-LR. The MC-LR degradation can be described by pseudo-first-order kinetic model. Chloride ion (Cl−) with proper concentration could enhance the MC-LR degradation. The presence of metal cations (Cu2+ and Fe3+) improved the photocatalytic degradation of MC-LR. This study suggests that Pt/WO3 photocatalytic oxidation under solar light is a promising option for the purification of water containing MC-LR.
A Multigrid Method Based on Incomplete Gaussian Elimination

In this paper we introduce and analyse a new Schur complement approximation based on incomplete Gaussian elimination. The approximate Schur complement is used to develop a multigrid method. This multigrid method has an algorithmic structure that is very similar to the algorithmic structure of classical multigrid methods. The resulting method is almost purely algebraic and has interesting properties with respect to variation in problem parameters.
Stage‐dependent feeding behavior by western tarnished plant bugs influences flower bud abscission in cotton

Unexplained variability in the relationship between the number of herbivores in a field and the amount of crop damage can arise if there is a large amount of variation among herbivore individuals in the amount of feeding damage each generates. In California, populations of the western tarnished plant bug, Lygus hesperus Knight (Heteroptera: Miridae), produce highly variable levels of damage to cotton plants (Gossypium hirsutum L.) (Malvaceae), even when found at low densities. Because L. hesperus populations are also highly variable in their overall stage structure, we hypothesize that differences in crop damage might result from varying impact by each L. hesperus stage on cotton flower buds (termed squares). Laboratory measurements of L. hesperus mouth‐parts and distance to anther sacs, a preferred feeding site, revealed that 1st−3rd instar L. hesperus nymphs will not be able to feed on anther sacs of larger squares (over 8 mm in length) but will be able to feed on squares that are most sensitive to L. hesperus damage (<7 mm). Because even the 1st instars can feed on the most sensitive ‘pinhead’ squares, size constraints do not rule out damaging effects from the youngest L. hesperus. Laboratory observations revealed that later developmental stages, and adults, spend more time feeding on cotton squares relative to 2nd and 3rd instars. In addition, a field experiment revealed no effect of 2nd instars on square retention (relative to control cages) but did reveal a significant decrease in square retention generated by adult L. hesperus (4th instar L. hesperus resulted in an intermediate level of square retention). In a final study we sampled L. hesperus stage structure and density across 38 cotton fields. Multiple regression revealed that the densities of 1st−3rd instars of L. hesperus are not correlated with anther sac damage or square retention. However, in 2 years 4th and 5th instars were positively correlated with anther sac damage and negatively correlated with square retention. In the a third year, adult L. hesperus showed correlations in the same direction, across fields and across sites within fields. Overall, these results suggest that the adults and the largest nymphs of L. hesperus (4th and 5th instars) are particularly damaging to cotton squares, with the 1st−3rd instars of L. hesperus causing little damage to plants.
COMMENTARY: Do Youth Mentoring Programs Work? A Review of the Empirical Literature

IntroductionMentoring relationships represent one of the oldest community-based youth interventions, dating back to the genesis of the first juvenile court in Chicago during the late 1800s when probation officers provided guidance and supervision to youthful offenders in lieu of more damaging alternatives such as institutionalization (Blakeslee & Keller, 2012; Tanenhaus, 2004). Indeed, such formal interventions were rooted in the progressive era as a response to increased poverty at the hands of industrialization, immigration, and urbanization. The highly renowned Big Brothers Big Sisters of America (BBBS) mentoring program, for example, began in 1904 in New York City and today consists of over 375 agencies serving more than 210,000 youth across the United States (Blakeslee & Keller, 2012). Fiowever, not until the past two decades has a growing body of empirical literature begun to develop and mature from which to better understand the goals, operations, and outcomes of youth mentoring programs. This article summarizes the literature, beginning with a brief overview of relevant theories, followed by a summary of mentoring programs' effectiveness as derived from the empirical literature. The article continues with a short examination of vulnerable populations, problems of connecting at-risk youth with mentors, guidance for future program evaluations, best practices for mentoring programs, guidance for mentors, and an international comparison of effectiveness. The article concludes with advice pertinent to researchers, program administrators, and funding organizations. This article is designed to introduce the many complexities of youth mentoring. Readers are encouraged to seek out the various sources contained throughout for more detailed information on a given subject area.Theoretical PerspectiveYouth mentoring programs did not originate within a theoretical framework of an academic philosophy, but rather from the philanthropic aims of community advocates and social work practitioners (Dubois, Doolittle, Yates, Silverthorn, T as cited in Britner et al., 2006). Acceptance-rejection theory posits many behavioral outcomes of youth are the product of their parents'initial acceptance or rejection. Rejection, as found in various self-report studies, is associated with developmental, behavioral, and psychological problems in children, youth, and adults that may include substance abuse and delinquency (Britner et al., 2006). Acceptance, on the other hand, is associated with greater generosity, empathy, and helpfulness toward others. As such, individuals who feel accepted by their parents are more likely to have positive peer relations, higher perceptions of life satisfaction, and less psychological stress than those who perceive themselves to be rejected (Britner et al. …
The Summer Learning of Exceptional Students

The summer activities and summer learning of exceptional students—students who have an individualized education plan or who are English-language learners—are potentially important yet understudied. We analyze nationally representative survey data to fill this gap. Exceptional students are significantly less likely than their mainstream counterparts to participate in organized summer activities and summer day care but are more likely to attend summer school and to practice math with a parent. Exceptional learners make significantly greater reading gains during the summer vacation than their mainstream counterparts; however, this is true only for middle- and high-income exceptional learners. Moreover, the well-documented summer learning loss of low-income students in reading appears to be entirely driven by lower summer learning rates of low-income exceptional learners. There are no such differences in math achievement.
Coronal Emission Measures and Abundances for Moderately Active K Dwarfs Observed by Chandra

We have used Chandra to resolve the nearby 70 Oph (K0 V+K5 V) and 36 Oph (K1 V+K1 V) binary systems for the first time in X-rays. The LETG/HRC-S spectra of all four of these stars are presented and compared with an archival LETG spectrum of another moderately active K dwarf, ϵ Eri. Coronal densities are estimated from O VII line ratios and emission measure distributions are computed for all five of these stars. We see no substantial differences in coronal density or temperature among these stars, which is not surprising considering that they are all early K dwarfs with similar activity levels. However, we do see significant differences in coronal abundance patterns. Coronal abundance anomalies are generally associated with the first ionization potential (FIP) of the elements. On the Sun, low-FIP elements are enhanced in the corona relative to high-FIP elements, the so-called FIP effect. Different levels of FIP effect are seen for our stellar sample, ranging from 70 Oph A, which shows a prominent solar-like FIP effect, to 70 Oph B, which has no FIP bias at all or possibly even a weak inverse FIP effect. The strong abundance difference exhibited by the two 70 Oph stars is unexpected considering how similar these stars are in all other respects (spectral type, age, rotation period, X-ray flux). It will be difficult for any theoretical explanation for the FIP effect to explain how two stars so similar in all other respects can have coronae with different degrees of FIP bias. Finally, for the stars in our sample exhibiting a FIP effect, a curious difference from the solar version of the phenomenon is that the data seem to be more consistent with the high-FIP elements being depleted in the corona rather than with a low-FIP enhancement.
Pdx1 Is Post-Translationally Modified In vivo and Serine 61 Is the Principal Site of Phosphorylation

Maintaining sufficient levels of Pdx1 activity is a prerequisite for proper regulation of blood glucose homeostasis and beta cell function. Mice that are haploinsufficient for Pdx1 display impaired glucose tolerance and lack the ability to increase beta cell mass in response to decreased insulin signaling. Several studies have shown that post-translational modifications are regulating Pdx1 activity through intracellular localization and binding to co-factors. Understanding the signaling cues converging on Pdx1 and modulating its activity is therefore an attractive approach in diabetes treatment. We employed a novel technique called Nanofluidic Proteomic Immunoassay to characterize the post-translational profile of Pdx1. Following isoelectric focusing in nano-capillaries, this technology relies on a pan specific antibody for detection and it therefore allows the relative abundance of differently charged protein species to be examined simultaneously. In all eukaryotic cells tested we find that the Pdx1 protein separates into four distinct peaks whereas Pdx1 protein from bacteria only produces one peak. Of the four peaks in eukaryotic cells we correlate one of them to a phosphorylation Using alanine scanning and mass spectrometry we map this phosphorylation to serine 61 in both Min6 cells and in exogenous Pdx1 over-expressed in HEK293 cells. A single phosphorylation is also present in cultured islets but it remains unaffected by changes in glucose levels. It is present during embryogenesis but is not required for pancreas development.
PR ] 1 1 M ay 2 00 4 Repulsion of an evolving surface on random walls

We consider the motion of a discrete random surface interacting by exclusion with a random wall. Two cases are considered: rarefied walls and walls of random height. The dynamics is given by the serial harness process. In the first case, we prove that the process delocalizes iff the mean number of visits to the set of sites where the wall is present by a random walk is infinite. When the surface delocalizes, bounds on its average speed are obtained. In the case of walls of random height, we study the effect of the distribution of the wall heights on the repulsion speed.
New Methods for Large-Scale Analyses of Social Identities and Stereotypes

Social identities, the labels we use to describe ourselves and others, carry with them stereotypes that have significant impacts on our social lives. Our stereotypes, sometimes without us knowing, guide our decisions on whom to talk to and whom to stay away from, whom to befriend and whom to bully, whom to treat with reverence and whom to view with disgust. Despite these impacts of identities and stereotypes on our lives, existing methods used to understand them are lacking. In this thesis, I first develop three novel computational tools that further our ability to test and utilize existing social theory on identity and stereotypes. These tools include a method to extract identities from Twitter data, a method to infer affective stereotypes from newspaper data and a method to infer both affective and semantic stereotypes from Twitter data. Case studies using these methods provide insights into Twitter data relevant to the Eric Garner and Michael Brown tragedies and both Twitter and newspaper data from the “Arab Spring”. Results from these case studies motivate the need for not only new methods for existing theory, but new social theory as well. To this end, I develop a new sociotheoretic model of identity labeling how we choose which label to apply to others in a particular situation. The model combines data, methods and theory from the social sciences and machine learning, providing an important example of the surprisingly rich interconnections between these fields.
The association between belonging and psychology graduate trainees' health

The purpose of this study was to examine the relationship between psychology graduate trainees’ sense of belonging to their training environment (school and practicum) and its association with students’ health (psychological, emotional, and physical). Participants were first to fifth year psychology graduate trainees from several institutes throughout the United States. Significant correlations were found between all health measures and several belonging measures. Support was provided for the hypothesis that stated that trainees who reported a higher sense of overall belonging to the training environment would report better overall health. Implications of the findings and suggestions for future research were discussed.
Bmc Musculoskeletal Disorders Reliability of Ashworth and Modified Ashworth Scales in Children with Spastic Cerebral Palsy

Background: Measurement of spasticity is a difficult and unresolved problem, partly due to its complexity and the fact that there are many factors involved. In the assessment of spasticity in the pediatric disabled population, methods that are easily used in practice are ordinal scales that still lack reliability. A prospective cross-sectional observational study was planned to determine the reliability of the Ashworth Scale (AS) and the Modified Ashworth Scale (MAS) in children with spastic cerebral palsy (CP).
Remote Sea Surface Temperature Variations during ENSO: Evidence for a Tropical Atmospheric Bridge

Abstract In an El Nino event, positive SST anomalies usually appear in remote ocean basins such as the South China Sea, the Indian Ocean, and the tropical North Atlantic approximately 3 to 6 months after SST anomalies peak in the tropical Pacific. Ship data from 1952 to 1992 and satellite data from the 1980s both demonstrate that changes in atmospheric circulation accompanying El Nino induce changes in cloud cover and evaporation which, in turn, increase the net heat flux entering these remote oceans. It is postulated that this increased heat flux is responsible for the surface warming of these oceans. Specifically, over the eastern Indian Ocean and South China Sea, enhanced subsidence during El Nino reduces cloud cover and increases the solar radiation absorbed by the ocean, thereby leading to enhanced SSTs. In the tropical North Atlantic, a weakening of the trade winds during El Nino reduces surface evaporation and increases SSTs. These relationships fit the concept of an “atmospheric bridge” that conne.
EXAMINING MOTIVATIONAL SHIFTS IN MIDDLE SCHOOL: WHAT DEEPENS SCIENCE MOTIVATION AND WHAT ATTENUATES ITS DECLINE?

While motivational decline towards science is common during adolescence, this dissertation asks if there are beneficial science experiences that buffer against the loss of motivation and even promote its growth. The dissertation consists of two papers (Chapter 2 & 3) with additional analyses in Chapter 4 and a summary of findings in Chapter 5. The first paper examines whether classroom science experiences are differentially associated with motivational change and science content knowledge. Using self-reports from a sample of approximately 3,000 middle school students, this study investigates the influence of perceived science classroom experiences (student engagement & perceived success), on motivational change (fascination, values, competency belief) and content learning. Controlling for demographic information, school effects, and initial levels of motivation and content knowledge, we find that dimensions of engagement (affect, behavioral-cognitive) and perceived success are differentially associated with changes in particular motivational constructs and learning. The second paper examines one of these motivational outcomes (value) in more detail. Valuing science is associated with positive learning outcomes and is often used to motivate engagement in the sciences, but less is known about what influences its development and maintenance, particularly during the critical middle school years. Using multinomial regression applied to longitudinal data from approximately 2,600 middle-school students, I test the relationship of the perceived science experiences examined in Paper 1 (affective engagement, behavioral-cognitive engagement, & perceived success) and optional formal and optional informal experiences to changes in science utility value. Furthermore, we address whether the same factors that predict growth in science value also predict absence of decline. Overall, we find that all five factors are associated with changes in value, but some have different relationships with growth vs. decline outcomes. Chapter 4 extends these findings to examine drivers of growth and decline for fascination and competency beliefs. Together, these findings provide a more nuanced view of the factors associated with science motivation and learning (both in and out of the science classroom), as well as the practical implications for educational practice.
Verb Class Discovery from Rich Syntactic Data

Previous research has shown that syntactic features are the most informative features in automatic verb classification. We investigate their optimal characteristics by comparing a range of feature sets extracted from data where the proportion of verbal arguments and adjuncts is controlled. The data are obtained from different versions of VALEX [1] – a large SCF lexicon for English which was acquired automatically from several corpora and the Web. We evaluate the feature sets thoroughly using four supervised classifiers and one unsupervised method. The best performing feature set includes rich syntactic information about both arguments and adjuncts of verbs. When combined with our best performing classifier (a novel Gaussian classifier), it yields the promising accuracy of 64.2% in classifying 204 verbs to 17 Levin (1993) classes. We discuss the impact of our results on the state-or-art and propose avenues for future work.