Miracle-dz/UniFAR-FTUs huggingface dataset:
Preservice Physical Education Teachers' Service Learning Experiences Related to Comprehensive School Physical Activity Programming.

Purpose:The purpose of this study was to examine preservice physical education teachers’ (PPET) service learning experiences planning and implementing course assignments aligned with comprehensive school physical activity program (CSPAP) recommendations. Methods:Based on service learning principles, PPETs (N = 18) enrolled in a physical education methods class planned, implemented, and reflected on physical activity promotion events before, during, and after school for youth, staff, and parents. Data sources included focus group interviews, written reflections, field notes, and artifacts. Constant comparison techniques and triangulation guided data analysis and interpretation to identify overarching themes describing the PPETs’ successes, challenges, and lessons learned. Results:Four themes were identified: (a) outcomes with youth, parents, and staff, (b) communication, (c) planning and preparation, and (d) priorities and possibilities. Discussion/Conclusion:This study provides insight into the feasibilit.
Ischemic stroke and transient ischemic attack in young adults: risk factors, diagnostic yield, neuroimaging, and thrombolysis.

BACKGROUND Approximately 10% to 14% of ischemic strokes occur in young adults. OBJECTIVE To investigate the yield of diagnostic tests, neuroimaging findings, and treatment of ischemic strokes in young adults. DESIGN We retrospectively reviewed data from our Get with the Guidelines-Stroke database from 2005 through 2010. SETTING University hospital tertiary stroke center. PATIENTS A total of 215 consecutive inpatients aged 18 to 45 years with ischemic stroke/transient ischemic attack. The mean (SD) age was 37.5 (7) years; 51% were male. RESULTS There were high incidence rates of hypertension (20%), diabetes mellitus (11%), dyslipidemia (38%), and smoking (34%). Relevant abnormalities were shown on cerebral angiography in 136 of 203 patients, on cardiac ultrasonography in 100 of 195, on Holter monitoring in 2 of 192; and on hypercoagulable panel in 30 of 189 patients. Multiple infarcts were observed in 31% and were more prevalent in individuals younger than age 35 years. Relevant arterial lesions were frequently detected in the middle cerebral artery (23%), internal carotid artery (13%), and vertebrobasilar arteries (13%). Cardioembolic stroke occurred in 47% (including 17% with isolated patent foramen ovale), and 11% had undetermined stroke etiology. The median National Institutes of Health Stroke Scale score was 3 (interquartile range, 0-9) and 81% had good outcome at hospital discharge. Of the 29 patients receiving thrombolysis (median National Institutes of Health Stroke Scale score, 14; interquartile range, 9-17), 55% had good outcome at hospital discharge and none developed symptomatic brain hemorrhage. CONCLUSIONS This study shows the contemporary profile of ischemic stroke in young adults admitted to a tertiary stroke center. Stroke etiology can be determined in nearly 90% of patients with modern diagnostic tests. The causes are heterogeneous; however, young adults have a high rate of traditional vascular risk factors. Thrombolysis appears safe and short-term outcomes are favorable.
N-Acetylcysteine Reduces Markers of Differentiation in 3T3-L1 Adipocytes

Oxidative stress plays a critical role in the pathogenesis of diabetes, hypertension and atherosclerosis. Some authors reported that fat accumulation correlates to systemic oxidative stress in humans and mice, but the relationship of lipid production and oxidative metabolism is still unclear. In our laboratory we used 3T3-L1 preadipocytes, which are able to differentiate into mature adipocytes and accumulate lipids, as obesity model. We showed that intracellular reactive oxygen species (ROS) and antioxidant enzymes superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities increased in parallel with fat accumulation. Meanwhile N-acetylcysteine (NAC), a well known antioxidant and Glutathione (GSH) precursor, inhibited ROS levels as well as fat accumulation in a concentration-dependent manner. NAC also inhibited both adipogenic transcription factors CCAAT/enhancer binding protein beta (C/EBP β) and peroxisomal proliferator activated receptor gamma (PPAR γ) expression; we suggested that intracellular GSH content could be responsible for these effects.
Mathematical modelling and visualization of gas transport in a zeolite bed using a slice selection procedure

Summary We present the analytical solution of the equations of gas diffusion in a heterogeneous zeolite bed. The problem is handled by assuming that the bed consists of a large number of very thin layers of solid, perpendicular to the direction of propagation of the gas. Mass transfer by diffusion in such a material is determined by a system of differential equations with boundary and interface conditions. The results allow the theoretical determination of the time dependence of the concentration profiles and the inter- and intra-crystallite diffusion coefficients of a gas in each layer of the bed. A numerical application concerns the diffusion of benzene in a cylindrical bed of ZSM5 displaced vertically and rapidly, step by step, inside the NMR probe. Thus we can obtain the time dependence of the concentration of gas absorbed at the level of each slice. These coupled investigations give a better understanding of the diffusion process in this multilayer material.
Training Sparse Neural Networks

The emergence of Deep neural networks has seen human-level performance on large scale computer vision tasks such as image classification. However these deep networks typically contain large amount of parameters due to dense matrix multiplications and convolutions. As a result, these architectures are highly memory intensive, making them less suitable for embedded vision applications. Sparse Computations are known to be much more memory efficient. In this work, we train and build neural networks which implicitly use sparse computations. We introduce additional gate variables to perform parameter selection and show that this is equivalent to using a spike-and-slab prior. We experimentally validate our method on both small and large networks which result in highly sparse neural network models.
Lectures on BRS invariance for massive boson fields

These notes correspond to lectures given at the Villa de Leyva Summer School in Colombia (July 2007). Our main purpose in this short course on BRS invariance of gauge theories is to illuminate corners of the theory left in the shade by standard treatments. The plan is as follows. First a review of Utiyama's "general gauge theory". Promptly we find a counterexample to it in the shape of the massive spin-1 Stueckelberg gauge field. This is not fancy, as the massive case is the most natural one to introduce BRS invariance in the context of free quantum fields. Mathematically speaking, the first part of the course uses Utiyama's notation, and thus has the flavour and non-intrinsic notation of standard physics textbooks. Next we deal with boson fields on Fock space and BRS invariance in connection with the existence of Krein operators; the attending rigour points are then addressed.
Analysis of Maximum Likelihood classification technique on Landsat 5 TM satellite data of tropical land covers

The aim of this paper is to carry out analysis of Maximum Likelihood (ML) on Landsat 5 TM (Thematic Mapper) satellite data of tropical land covers. ML is a supervised classification method which is based on the Bayes theorem. It makes use of a discriminant function to assign pixel to the class with the highest likelihood. Class mean vector and covariance matrix are the key inputs to the function and can be estimated from the training pixels of a particular class. In this study, we used ML to classify a diverse tropical land covers recorded from Landsat 5 TM satellite. The classification is carefully examined using visual analysis, classification accuracy, band correlation and decision boundary. The results show that the separation between mean of the classes in the decision space is to be the main factor that leads to the high classification accuracy of ML.
Singular causation

1. Singular vs. general causation In many people, caffeine causes slight muscle tremors, particularly in their hands. In general, the Caffeine → Muscle Tremors causal connection is a noisy one: someone can drink coffee and experience no hand shaking, and there are many other factors that can lead to muscle tremors. Now suppose that Jane drinks several cups of coffee and then notices that her hands are trembling; an obvious question is: did this instance of coffee drinking cause this instance of hand-trembling? Structurally similar questions arise throughout everyday life: Did this pressing of the 'k' key cause this change in the pixels on the computer monitor? Did these episodes of smoking cause this lung cancer? Did this studying cause this test score? And so on. These questions all ask about singular causation in a particular situation, in contrast with general causation across multiple cases. They are thus particularly salient in situations in which we care about that specific case, as in many legal contexts, social interactions, physical explanations of anomalous events, and more. Singular causation is cognitively challenging, as it is quite unclear how we could come to know that, say, this coffee drinking caused these muscle tremors. On the one hand, we cannot directly observe singular causation, as famously noted by David Hume (1748), but instead observe only sequences of events. One might hope that so-called causal perception (see also White, this volume) could provide a way to directly observe singular causation, but there are reasons to suspect that causal perception is not just the straightforward observation of singular causation. The particular events must instead be understood or interpreted in light of background causal knowledge. On the other hand, we cannot use statistical or other inductive inference methods to learn directly about which singular causation relations obtain because we have (by definition) only a single case. There are many different methods for inferring causal structure from observations, but those all require multiple cases, so are not directly applicable for singular causation. Moreover, even if they were usable, the causal relations across multiple situations need not perfectly track the causal relations in any particular case. For example, it is perfectly consistent for caffeine to cause shaky hands, but for these particular muscle tremors to be caused by this dose of medication, rather than the coffee that one just consumed. Judgments about singular causation require more than just knowledge of …
Robust Power Control for Heterogeneous Users in Shared Unlicensed Bands

We develop a robust formalism for power control games in unlicensed bands between two groups of users competing for the spectrum: informed-users (leaders) who have advanced capabilities to extract side-information about other users and their strategies, and uninformed-users (followers) who can only observe the aggregate interference caused by others. Such nominal leader-follower games have been previously studied in the power control literature; however, these prior works fail to capture an important aspect of such interactions: the side-information and observations made by users may be uncertain, which has an important impact on users' strategies and network performance. Thus, in this paper we propose a new, robust game-theoretic formalism and solution which takes these uncertainties into account. Specifically, each group chooses its actions by solving its respective worst-case robust optimization problems. We show how various types of uncertainties affect the social utility of each group, and identify in which deployment scenarios the social utility of the robust game is higher than that of the nominal game. Importantly, we show that robust solutions in such games are more energy efficient. Finally, our theoretical formalism, analysis and solutions are complemented by simulations.
The on-line processing of socio-emotional information in prototypical scenarios: inferences from brain potentials.

Little is known about the time course of the mechanisms involved in the on-line processing of socio-emotional information. We used event-related brain potentials (ERPs) to investigate this issue using vignettes that described prototypical, social scenarios. An initial sentence established the social context and the following target sentence ended with a critical word that informed the reader of the character's socio-emotional response to the situation. Critical words that mismatched rather than matched with a character's expected feelings elicited a larger ERP negativity (N400) ~200-500 ms after word onset, followed by a larger frontal positivity. Dipole source modeling results indicated that an anterior temporal lobe source accounted for the N400-like effect, which we attribute to the increased demands of integrating general knowledge about social situations (e.g. scripts) with personal- and context-specific information. An additional mediofrontal source contributed to the later ERP effect and presumably reflects high-level mindreading functions. Together, these findings indicate that readers rapidly infer and evaluate on-line a character's likely socio-emotional response based on the prototypical information provided by the text.
Peer Victimization in Children With Obsessive–Compulsive Disorder: Relations With Symptoms of Psychopathology

This study examined the frequency of peer victimization and psychological symptom correlates among youth with obsessive-compulsive disorder (OCD). The Schwartz Peer Victimization Scale, Children's Depression Inventory, and Asher Loneliness Scale were administered to 52 children and adolescents diagnosed with OCD. The child's parent or guardian completed the Child Behavior Checklist, and a trained clinician administered the Children's Yale-Brown Obsessive–Compulsive Scale (CY– BOCS). Fifty-two healthy controls and 52 children with Type 1 diabetes (T1D) who were administered the Schwartz Peer Victimization Scale as part of another study were included for comparison purposes. Greater rates of peer victimization were reported in youth with OCD relative to healthy controls and children with Type 1 diabetes (T1D). Peer victimization in the OCD sample was positively related to loneliness, child-reported depression, parent-reported internalizing and externalizing symptoms, and clinician-rated OCD severity. Peer victimization fully mediated the relation between OCD severity and both depression and parent reports of child externalizing behaviors and partially mediated the relation between OCD severity and loneliness. Recognition of the magnitude of the problem and contribution problematic peer relations may play in comorbid psychological conditions is important for clinicians who see children with OCD.
INHIBITION OF MOVEMENT OF TRITON-DEMEMBRANATED SEA-URCHIN SPERM FLAGELLA BY Mg 2 + , ATP 4-, ADP AND P ,

Three distinct patterns of inhibition of MgATP"-activated flagellar motility have been found by measuring the motility of Triton-demembranated sea-urchin spermatozoa beating with their heads attached to a glass surface. Inhibition of beat frequency by the reaction products, ADP and P,, is competitive with the normal substrate, MgATP", and the inhibitory effects are similar to a reduction in MgATP" concentration. Inhibition of beat frequency by ATP'" is competitive with MgATP", but is accompanied by an inhibition of bending, as measured by the angle between the straight regions on either side of a bend, which is not seen when MgATP" concentration is reduced. Inhibition of beat frequency by Mg is not competitive with MgATP-, and is accompanied by an increase in bend angle, so that there is no change in the rate of sliding between flagellar tubules. These differences suggest unexpected complexity of dynein ATPase action in flagella. The beat frequencies of both swimming and attached spermatozoa show a linear double reciprocal dependence on MgATP~ concentration, with identical slopes. The calculated sliding velocities between tubules also give linear relationships, but the slopes are different, suggesting that beat frequency may be the more fundamental dependent variable in this system.
Sunshine Trading : Flashes of Trading Intent at the NASDAQ

We use the introduction and the subsequent removal of the flash order facility (an actionable indication of interest, IOI) from the NASDAQ as a natural experiment to investigate the impact of voluntary disclosure of trading intent on market quality. We find that flash orders significantly improve liquidity in the NASDAQ. In addition, overall market quality improves substantially when the flash functionality is introduced and deteriorates when it is removed. One explanation for our findings is that flash orders are placed by less informed traders and fulfill their role as an advertisement of uninformed liquidity needs. They successfully attract responses from liquidity providers immediately after the announcement is placed, thus lowering the risk-bearing cost for the overall market. Our study is important in understanding the impact of voluntary disclosure, in guiding future market design choices, and in the current debate on dark pools and IOIs.
The roles of hippocampal and neocortical learning mechanisms in the human brain

Contemporary models of declarative memory state that when initially learned, all novel information is encoded by the hippocampal system before being consolidated or transformed to depend on neocortical structures subserving semantic memory. Based on observations with functional magnetic resonance imaging (fMRI), this thesis presents evidence that novel associations may be directly encoded by the semantic system in humans. While the hippocampus is often involved in information processing at the early stages of learning, the semantic system is seen to encode associative memory traces in the first instance (chapter 2). Furthermore, it is proposed that the hippocampus is not involved in learning when associative information is gradually accumulated across a series of ambiguous events. This is characteristic of cross-situational learning (xSL) which allows for the acquisition of word-object associations (i.e. nouns) during infancy. It is shown that xSL is not well accounted for by a prominent model of contextual learning - the temporal context model (chapter 3). Additionally, fMRI data suggest that neocortical structures rather than components of the hippocampal system are preferentially involved in xSL compared to traditional methods of training (chapter 4). Finally, it is suggested that rapid hippocampal learning mechanisms rely on specialised neuronal-microglial interactions. The administration of a microglial inhibitor (minocycline) was found to modulate hippocampal function and bias its use when other learning systems would have been more advantageous (chapter 5). Collectively, these findings suggest that the hippocampal system is specialised for rapidly encoding information that is explicitly provided, yet may not be recruited when associative information is collated across ambiguous events. At the same time, the neocortical semantic system may be able to learn new information at faster rates than previously thought. As such, it is hypothesised that amnestic patients may be able to acquire some forms of declarative material if presented in an appropriate manner.
Extensive Gene Remodeling in the Viral World: New Evidence for Nongradual Evolution in the Mobilome Network

Complex nongradual evolutionary processes such as gene remodeling are difficult to model, to visualize, and to investigate systematically. Despite these challenges, the creation of composite (or mosaic) genes by combination of genetic segments from unrelated gene families was established as an important adaptive phenomena in eukaryotic genomes. In contrast, almost no general studies have been conducted to quantify composite genes in viruses. Although viral genome mosaicism has been well-described, the extent of gene mosaicism and its rules of emergence remain largely unexplored. Applying methods from graph theory to inclusive similarity networks, and using data from more than 3,000 complete viral genomes, we provide the first demonstration that composite genes in viruses are 1) functionally biased, 2) involved in key aspects of the arm race between cells and viruses, and 3) can be classified into two distinct types of composite genes in all viral classes. Beyond the quantification of the widespread recombination of genes among different viruses of the same class, we also report a striking sharing of genetic information between viruses of different classes and with different nucleic acid types. This latter discovery provides novel evidence for the existence of a large and complex mobilome network, which appears partly bound by the sharing of genetic information and by the formation of composite genes between mobile entities with different genetic material. Considering that there are around 10E31 viruses on the planet, gene remodeling appears as a hugely significant way of generating and moving novel sequences between different kinds of organisms on Earth.
An Improved Proportionate Normalized Least-Mean-Square Algorithm for Broadband Multipath Channel Estimation

To make use of the sparsity property of broadband multipath wireless communication channels, we mathematically propose an lp-norm-constrained proportionate normalized least-mean-square (LP-PNLMS) sparse channel estimation algorithm. A general lp-norm is weighted by the gain matrix and is incorporated into the cost function of the proportionate normalized least-mean-square (PNLMS) algorithm. This integration is equivalent to adding a zero attractor to the iterations, by which the convergence speed and steady-state performance of the inactive taps are significantly improved. Our simulation results demonstrate that the proposed algorithm can effectively improve the estimation performance of the PNLMS-based algorithm for sparse channel estimation applications.
Why minimum wage hikes may not reduce employment

Recent research has challenged the conventional wisdom among economists that increases in the minimum wage reduce employment among low-wage workers. Although some studies continue to find negative effects, others suggest that moderately raising the minimum wage may not reduce employment. The author of this article describes and evaluates several models that may explain the controversial recent findings and proposes avenues for future research that would help determine the validity of these models. ; The author notes that if the recent findings that minimum wage increases do not always adversely affect employment are correct, economists may need to reconsider their views of how labor markets work. In addition, research on other effects of minimum wage increases is needed. For example, the distributional consequences are important, particularly if higher-skilled workers displace lower-skilled workers when the minimum wage is raised. The recent findings challenging traditional thinking about employment and the minimum wage should be taken as the starting point for a larger examination of the effects of the minimum wage rather than an end to the debate.