Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct Leaf‐trait Syndromes of Evergreen and Deciduous Trees in a Seasonally Dry Tropical Forest

In seasonally dry tropical forests, tree species can be deciduous, remaining without leaves throughout the dry season, or evergreen, retaining their leaves throughout the dry season. Deciduous and evergreen trees specialize in habitats that differ in water availability (hillside and riparian forest, respectively) and in their exposure to herbivore attack (seasonal and continuous, respectively). We asked whether syndromes of leaf traits in deciduous and evergreen trees were consistent with hypothesized abiotic and biotic selective pressures in their respective habitat. We measured seven leaf traits in 19 deciduous and 11 evergreen tree species in a dry tropical forest in Western Mexico, and measured rates of herbivory on 23 of these species. We investigated the covariance of leaf traits in syndromes related to phenology and associated physiology, and to anti‐herbivory defense. We found evidence for syndromes that separated phenological strategies among four traits: toughness, water content, specific leaf area, and carbon:nitrogen (C:N) ratios. We found a trade‐off between two other traits: trichomes and latex. Overall, evergreen species exhibited lower rates of herbivory than deciduous species. Lower rates of herbivory were explained by a syndrome of higher toughness, lower water content, and higher C:N ratios, which are traits representative of evergreen trees. Phenology and trait syndromes did not exhibit significant phylogenetic signal, consistent with the hypothesis of evolutionary convergence among phenologies and associated leaf‐trait syndromes. Our results suggest that deciduous and evergreen trees could respond to differential water availability and herbivory in their respective habitats by converging on distinct leaf‐trait syndromes.
Temporal Characteristics of Response Integration Evoked by Multiple Whisker Stimulations in the Barrel Cortex of Rats

We investigated the responses of 114 cells in the barrel cortex of rats to describe the temporal characteristics of excitatory interactions among neurons serving two vibrissae. To examine these interactions, the principal whisker and one adjacent whisker in the same row were stimulated simultaneously or serially at various interstimulus intervals (ISIs). In 37% of the cells tested, combined stimulation of two whiskers exhibited response facilitation; the response to the combined stimulus was larger than the sum of the responses to stimulation of the individual whiskers. The occurrence and magnitude of the facilitation were strongly dependent on the ISI. The ISI capable of producing facilitation for a particular cell was tuned to a narrow range (mean ± SD, 5.3 ± 2.3 msec). The ISI that evoked the maximal facilitation was 1.3 ± 1.3, 3.4 ± 2.3, and 2.8 ± 4.5 msec for neurons in layers II/III, IV, and V/VI, respectively. These ISIs corresponded to the difference in latencies between the responses to the individual stimulations of the principal and adjacent whiskers. A significant response facilitation was observed in the regular-spiking cells but not in the fast-spiking cells. When the ISI was longer than the range that evoked facilitation, a suppression of the response to the second whisker stimulation was observed. Facilitation was observed predominantly in layer II/III cells (69%) and to a lesser extent in cells of layers IV (15%) and V/VI (24%). Our results suggest that, in the barrel cortex, the temporal relationships among tactile stimuli are coded by facilitatory and inhibitory interactions among neurons located in neighboring barrel columns.
Growth, Inequality and Poverty Relationships

This paper examines the causal relationship between inequality and a number of macroeconomic variables frequently found in the inequality and growth literature. These include growth, openness, wages, and liberalisation. We review the existing cross-country empirical evidence on the effects of inequality on growth and the extent to which the poorest in society benefit from economic growth. The linkage between growth, redistribution and poverty is also analysed. In the review of literature mainly empirical examples from 1990s are taken. In addition we test the conditional and unconditional relationship between inequality and growth in the post World War II period using WIDER inequality database. Regression results suggest that income inequality is declining over time. Inequality is also declining in growth of income. There is a significant regional heterogeneity in the levels and development over time. The Kuznets hypothesis represents a global U-shape relationship between inequality and growth.
Predicting Population Dynamics from the Properties of Individuals: A Cross-Level Test of Dynamic Energy Budget Theory

Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individual-based model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology.
CORRELATES AND RISK MARKERS FOR SLEEP DISTURBANCE IN CHILDREN WITH AUTISM SPECTRUM DISORDERS

ii Acknowledgements.iv Vita.v List of Tables . x List of Figures.xv Chapter 1: Introduction.1 Chapter 2: Method.37 Chapter 3: Results.76 Chapter 4: Discussion.94 References.122
Metacognition and confidence: comparing math to other academic subjects

Two studies addressed student metacognition in math, measuring confidence accuracy about math performance. Underconfidence would be expected in light of pervasive math anxiety. However, one might alternatively expect overconfidence based on previous results showing overconfidence in other subject domains. Metacognitive judgments and performance were assessed for biology, literature, and mathematics tests. In Study 1, high school students took three different tests and provided estimates of their performance both before and after taking each test. In Study 2, undergraduates similarly took three shortened SAT II Subject Tests. Students were overconfident in predicting math performance, indeed showing greater overconfidence compared to other academic subjects. It appears that both overconfidence and anxiety can adversely affect metacognitive ability and can lead to math avoidance. The results have implications for educational practice and other environments that require extensive use of math.
Depth Dropout: Efficient Training of Residual Convolutional Neural Networks

Training state-of-the-art deep neural networks is computationally expensive and time consuming. In this paper we present a method that can reduce training time while at the same time maintain nearly the same accuracy as traditional training approaches. This allows for faster experimentation and better use of computational resource. Our method extends the well-known dropout technique by randomly removing entire network layers instead of individual neurons during training and hence reducing the number of expensive convolution operations needed per training iteration. We conduct experiments on object recognition using the CIFAR10 and ImageNet datasets to demonstrate the effectiveness of our approach. Our results show that we can train residual convolutional neural networks (ResNets) 17.5% faster with only 0.4% decrease in error rate or 34.1% faster with 1.3% increase in error rate compared to a baseline model. We also perform analysis on the trade-off between testing accuracy and training speedup as a function of the drop-out ratio.
De Gustibus Disputare: Hyperbolic delay discounting integrates five approaches to impulsive choice

Impulsiveness is the tendency to shift preference from a better, later option to a poorer, earlier option as the two get closer. Explanations have extrapolated from five piecemeal elements of psychology – failure of cognitive rationality, Pavlovian conditioning, force of habit, incentive salience, and long chains of secondary reward – but in doing so have created models that stretch the properties of these elements as observed in the laboratory. The models are hard to integrate with each other, much less with the utility-maximizing structure of microeconomics. The increasing prominence of addictions, particularly addictions that do not involve a substance, have confronted behavioral science with these shortcomings. I suggest that the roles of all five phenomena follow from the hyperbolic discounting of expected reward: rationality can be seen as maximizing expected discounted reward as seen at a distance, which can be approximated by making choices in bundles; Pavlovian conditioning reduces to reward learning when a very short-term rewarding effect of conditioning stimuli is factored in; ‘habit’ subsumes various kinds of reward-seeking, especially that which has been narrowed by failures of self-control; incentive salience is a kind of short-term reward; self-reward is possible – and probably common – without being secondary to inborn turnkeys, limited rather by not being occasioned so often that the appetite(s) for it fail to build up.
Research Article Factors Associated with Road Accidents among Brazilian Motorcycle Couriers

The objective of the study was to identify factors associated with reports of road accidents, among motorcycle couriers in two medium-sized municipalities in southern Brazil. A self-administered questionnaire was answered by motorcycle couriers that had worked for at least 12 months in this profession. The outcomes analyzed were reports on accidents and serious accidents over the 12 months prior to the survey. Bivariate and multivariate analyses by means of logistic regression were carried out to investigate factors that were independently associated with the outcomes. Seven hundred and fifty motorcycle couriers, of mean age 29.5 years (standard deviation = 8.1), were included in the study. Young age (18 to 24 years compared to ≥25 years, odds ratio [OR] = 1.77) speeding (OR = 1.48), and use of cell phones while driving (OR = 1.43) were factors independently associated with reports of accidents. For serious accidents, there was an association with alternation of work shifts (OR = 1.91) and speeding (OR = 1.67). The characteristics associated with accidents—personal (young age), behavioral (use of cell phones while driving and speeding), and professional (speeding and alternation of work shifts)—reveal the need to adopt wide-ranging strategies to reduce these accidents, including better work conditions for these motorcyclists.
Native Magnetic Resonance T1-Mapping Identifies Diffuse Myocardial Injury in Hypothyroidism

Background and Aim Hypothyroidism (HT) is characterized by thyroid hormone deficiencies, which can lead to diffuse myocardial interstitium lesions in patients with HT. Myocardial longitudinal relaxation time (T1) mapping is a potential diagnostic tool for quantifying diffuse myocardial injury. This study aimed to assess the usefulness of T1 mapping in identifying myocardial involvement in HT, and determine the relationship between T1 values and myocardial function. Methods A cross-sectional study was conducted with 30 untreated HT patients alongside 23 age- and sex-matched healthy controls. All subjects underwent cardiac magnetic resonance (CMR) with non-contrast (native) T1 mapping using a modified Look-Locker inversion-recovery (MOLLI) sequence to assess the native T1 values of myocardium and cardiac function. Results Native myocardial T1 values were significantly increased in HT patients, especially those with pericardial effusion (p < 0.05), compared with healthy controls. In addition, significantly reduced peak filling rate (PFR) and prolonged peak filling time (PFT) were obtained (p < 0.05) in HT patients compared with controls. Furthermore, stroke volume (SV) and cardiac index (CI) were significantly lower in HT patients than controls (all p < 0.05). Interestingly, native T1 values were negatively correlated with free triiodothyronine (FT3), PFR, SV and CI (all p < 0.05). Conclusion Diffuse myocardial injuries are common in HT patients, and increased T1 values are correlated with FT3 and cardiac function impairment. These findings indicate that T1 mapping might be useful in evaluating myocardial injuries in HT patients.
Methodologies to Study Frequency-Dependent Single Event Effects Sensitivity in Flash-Based FPGAs

Flash-based FPGAs are more and more interesting for space applications because of their robustness against Single Event Upsets (SEUs) in configuration memory. However, as Single Event Effects (SEEs) are still a concern both for user memory and the configurable logic, accurate evaluations are needed to identify mitigation techniques for securing their use in space missions. In this paper the SEE sensitivity of circuits implemented in Flash-based FPGAs is evaluated with respect to the working frequency and different routing schemes. We outline different methodologies that can be used in order to characterize SEE sensitivity, using both heavy-ions radiation experiments and analytical approaches. Experimental results detail the contributions of different SEEs as a function of operating frequency and routing on a realistic circuit.
Learning and inference using complex generative models in a spatial localization task

A large body of research has established that, under relatively simple task conditions, human observers integrate uncertain sensory information with learned prior knowledge in an approximately Bayes-optimal manner. However, in many natural tasks, observers must perform this sensory-plus-prior integration when the underlying generative model of the environment consists of multiple causes. Here we ask if the Bayes-optimal integration seen with simple tasks also applies to such natural tasks when the generative model is more complex, or whether observers rely instead on a less efficient set of heuristics that approximate ideal performance. Participants localized a “hidden” target whose position on a touch screen was sampled from a location-contingent bimodal generative model with different variances around each mode. Over repeated exposure to this task, participants learned the a priori locations of the target (i.e., the bimodal generative model), and integrated this learned knowledge with uncertain sensory information on a trial-by-trial basis in a manner consistent with the predictions of Bayes-optimal behavior. In particular, participants rapidly learned the locations of the two modes of the generative model, but the relative variances of the modes were learned much more slowly. Taken together, our results suggest that human performance in a more complex localization task, which requires the integration of sensory information with learned knowledge of a bimodal generative model, is consistent with the predictions of Bayes-optimal behavior, but involves a much longer time-course than in simpler tasks.
The World Digital Library

Abstract The World Digital Library (WDL) is a project to place online rare and unique cultural documents from libraries and other cultural institutions around the world. The WDL website, which was developed and is maintained by the Library of Congress, emphasizes multilingualism, curatorial selection and description of the content presented, and a high level of functionality.
RAW 264.7 macrophages induce apoptosis selectively in transformed fibroblasts: intercellular signaling based on reactive oxygen and nitrogen species

The rationale for this study was to determine whether macrophages induce apoptosis selectively in transformed compared with nontransformed fibroblasts and to elucidate the underlying intercellular signaling chemistry. Murine fibroblasts transformed by oncogene expression (ras, src) or methylcholanthrene treatment were sensitive for apoptosis induction by RAW 264.7 macrophages, whereas parental cells and revertants were insensitive. Moreover, RAW 264.7 macrophages induced apoptosis in normal rat kidney (NRK) fibroblasts transiently transformed by epidermal growth factor/transforming growth factor‐β. Sensitivity for intercellular apoptosis induction was based on target cell‐derived superoxide anions and effector cell‐derived peroxidase and nitric oxide (NO). Superoxide anions dismutate to hydrogen peroxide, which is converted to HOCl by the peroxidase. The interaction of HOCl with superoxide anions then generates hydroxyl radicals. In parallel, NO interacts with superoxide anions and generates apoptosis‐inducing peroxynitrite. Signaling by reactive oxygen and nitrogen species seems to represent a hitherto unrecognized signaling principle for the selective elimination of potential tumor cells by macrophages.
Parental style and gendered student performance in the South African context of accounting studies

ABSTRACT The purpose of this study was to investigate the potentially gendered influence of experienced parental authority style on individual accounting students’ academic performance at a large South African university. Data were collected from first-year accountancy students and 953 usable responses were analysed using structural equation modelling. Tests of path invariance were also used to test the moderating influence of gender on the relationships between exposure to parenting style and student performance. Exposure to an authoritarian parental style was found to be negatively associated with student performance. Gender was found to moderate the relationship between exposure to authoritative parenting style and student performance. Experience of an authoritarian parental style was found to be associated with a host of variables representing socio-economic disadvantage. On the basis of these results, it was concluded that the influence of legacy parental style effects may be persistent for individuals who enter university for accountancy studies.
The Tracta Approach for Behaviour Analysis of Concurrent Systems

The need for modularity in the behaviour analysis of concurrent systems has been answered successfully by making reachability analysis compositional. Compositional reachability analysis (CRA) on the other hand, often exacerbates the state explosion problem; subsystem analysis leaves out information from the subsystem environment (context), which could considerably reduce the number of states allowed into its behaviour state-graph. To deal with that, we have chosen to incorporate context constraints in CRA. In the Tracta approach developed in our section, context constraints are expressed as processes in our model (we call them interface processes), that are composed with the subsystem, without a ecting the global system behaviour. Tracta supports both automatically generated and user-speci ed interfaces. It also provides an elegant way of checking violation of safety properties by the system under analysis. This work, besides introducing the main open problems in this area of research, is a detailed presentation of Tracta and its underlying theory, in their current form.
A dancing robot for rhythmic social interaction

This paper describes a robotic system that uses dance as a form of social interaction to explore the properties and importance of rhythmic movement in general social interaction. The system consists of a small creature-like robot whose movement is controlled by a rhythm-based software system. Environmental rhythms can be extracted from auditory or visual sensory stimuli, and the robot synchronizes its movement to a dominant rhythm. The system was demonstrated, and an exploratory study conducted, with children interacting with the robot in a generalized dance task. Through a behavioral analysis of videotaped interactions, we found that the robot's synchronization with the background music had an effect on children's interactive involvement with the robot. Furthermore, we observed a number of expected and unexpected styles and modalities of interactive exploration and play that inform our discussion on the next steps in the design of a socially rhythmic robotic system.
HDL and cardiovascular risk: time to call the plumber?

High-density lipoprotein cholesterol (HDL-C) has been dubbed the good cholesterol because it is thought to reflect the ability of HDL particles to remove excess cholesterol molecules from peripheral cells (including those in atherosclerotic plaques) for return to the liver. Not surprisingly, then, HDL-C has frequently been assumed to be a biomarker of HDL function, consistent with the inverse relationship in observational studies between plasma levels of HDL-C and risk of coronary artery disease. Recently, Voight et al have challenged this assumption by showing that genetically elevated HDL-C did not protect against myocardial infarction. This finding has fueled a lively discussion in the lay, scientific, and medical press about the relationship between HDL-C and HDL function, and the potential effectiveness of various HDL-C raising strategies. Epidemiological studies clearly show that levels of high-density lipoprotein cholesterol (HDL-C) are inversely associated with the risk of coronary artery disease and its thrombotic complications.1 However, in a recent study, Voight et al2 tested the hypothesis that increased plasma HDL-C is protective for myocardial infarction (MI) by examining the relationship between genetic variations associated with elevated levels of plasma HDL-C and the risk of MI.2 The major approach used was Mendelian randomization, a method developed to infer disease causality of a genetic variation.3 In the first test of the hypothesis, a loss of function single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser; minor allele frequency 2.6%) that is associated with an elevated mean plasma level of HDL-C (but no change in the plasma level of low-density lipoprotein cholesterol [LDL-C] or triglycerides) was evaluated in 20 913 MI cases and 95 407 controls. Although carriers of LIPG Asn396Ser had 0.14 mmol/L (5.5 mg/dL) higher mean plasma levels of HDL-C (with similar levels of other lipid and nonlipid risk factors for …