Miracle-dz/UniFAR-FTUs huggingface dataset:
Engaging children in lessons: the role of efficient and effective teachers

ABSTRACT The training of effective teachers has been one of the main aims of educational systems, in so far as it could be an important tool to improve the education performance of children and, consequently, contribute to their career progression and foster social mobility towards a more meritocratic society. The present study intends to identify these teachers by their ability to engage young students in lessons, which may reflect the capacity of their teaching practices and efficient use of available resources to increase students’ learning. We focus on 4th-grade reading and mathematics teachers in Spain – using TIMSS and PIRLS 2011 data – and we propose a 2-step procedure for this analysis: the 1st step obtains teachers’ efficiency scores, which are later employed in a 2nd step – together with teachers’ practices – to explain children’s engagement in lessons.
Haplós: Towards Technologies for and Applications of Somaesthetics

Portions of chapters 2 and 4 have been previously published in the following article: Maranan, D. S. (2015). Speculative somatics. Technoetic Arts, 13(3), 291–300. https://doi.org/10.1386/tear.13. 3. 291_1. This thesis expands on the material presented in the publication. This study was carried out in collaboration with industry partner Kin (UK).
PSC : Parallel Spectral Clustering

Spectral clustering algorithm has been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers from a scalability problem in both memory use and computational time when the size of a data set is large. To perform clustering on large data sets, we investigate two representative ways of approximating the dense similarity matrix. We compare one by sparsifying the matrix with another by the Nyström method. We then pick the strategy of sparsifying the matrix via retaining nearest neighbors and investigate its parallelization. We parallelize both memory use and computation on distributed computers. Through an empirical study on a large document data set of 193, 844 instances and a large photo data set of 2, 121, 863, we demonstrate that our parallel algorithm can effectively alleviate the scalability problem. Note to reviewers: A preliminary version of this work appears in the proceedings of ECML 2008 [29]. This journal version has made three major enhancements over the ECML version. First, we have improved PSC and this paper provides implementation details in using the Message Passing Interface (MPI) and MapReduce framework. Second, we applied PSC on a much larger data set consisting of 2, 121, 863 data instances, and report more results. Third, we discussed and compared the Nyström method for spectral clustering.
NO RETINAL EFFERENCE IN HUMANS: AN URBAN LEGEND

Visual attention involves the selective processing of sensory information. Animal model systems long ago demonstrated that such selectivity may be mediated by efferents that proceed from the brain to the eye in order to influence afferent input to the brain. However, such a mechanism seems to be absent from the literature on human visual attention. We here suggest that this omission is the result of an urban legend which holds that there are no retinal efferents in humans. We suggest that this legend exists because mammalian vision in general is degenerate relative to the ancestral vertebrate visual system that is clearly evident in birds. Further, our own work on an ideal animal model system has demonstrated that retinal efferents release neuromodulators that accelerate or delay photoreceptor responses to lights. If the same were true in humans, measurements of retinal response latencies would provide objective quantitative indicators of attention.
Do positive or negative stressful events predict the development of new brain lesions in people with multiple sclerosis?

Background Stressful life events have long been suspected to contribute to multiple sclerosis (MS) disease activity. The few studies examining the relationship between stressful events and neuroimaging markers have been small and inconsistent. This study examined whether different types of stressful events and perceived stress could predict the development of brain lesions. Method This was a secondary analysis of 121 patients with MS followed for 48 weeks during a randomized controlled trial comparing stress management therapy for MS (SMT-MS) to a waitlist control (WLC). Patients underwent magnetic resonance imaging (MRI) scans every 8 weeks. Every month, patients completed an interview measure assessing stressful life events and self-report measures of perceived stress, anxiety and depressive symptoms, which were used to predict the presence of gadolinium-enhancing (Gd+) and T2 lesions on MRI scans 29–62 days later. Participants classified stressful events as positive or negative. Negative events were considered ‘major’ if they involved physical threat or threat to the patient's family structure, and ‘moderate’ otherwise. Results Positive stressful events predicted decreased risk for subsequent Gd+ lesions in the control group [odds ratio (OR) 0.53 for each additional positive stressful event, 95% confidence interval (CI) 0.30–0.91] and less risk for new or enlarging T2 lesions regardless of group assignment (OR 0.74, 95% CI 0.55–0.99). Across groups, major negative stressful events predicted Gd+ lesions (OR 1.77, 95% CI 1.18–2.64) and new or enlarging T2 lesions (OR 1.57, 95% CI 1.11–2.23) whereas moderate negative stressful events, perceived stress, anxiety and depressive symptoms did not. Conclusions Major negative stressful events predict increased risk for Gd+ and T2 lesions whereas positive stressful events predict decreased risk.
In Situ Studies and Magnetic Properties of the Cmcm Polymorph of LiCoPO4 with a Hierarchical Dumbbell-Like Morphology Synthesized by Easy Single-Step Polyol Synthesis

LiCoPO4 (LCP) exists in three different structural modifications: LCP-Pnma (olivine structure), LCP-Pn21a (KNiPO4 structure type), and LCP-Cmcm (Na2CrO4 structure type). The synthesis of the LCP-Cmcm polymorph has been reported via high pressure/temperature solid-state methods and by microwave-assisted solvothermal synthesis. Phase transitions from both LCP-Pn21a and LCP-Cmcm to LCP-Pnma upon heating indicates a metastable behavior. However, a precise study of the structural changes during the heating process and the magnetic properties of LCP-Cmcm are hitherto unknown. Herein, we present the synthesis and characterization of LCP-Cmcm via a rapid and facile soft-chemistry approach using two different kinetically controlled pathways, solvothermal and polyol syntheses, both of which only require relatively low temperatures (~200 °C). Additionally, by polyol, method a dumbbell-like morphology is obtained without the use of any additional surfactant or template. A temperature-dependent in situ powder XRD shows a transition from LCP-Cmcm at room temperature to LCP-Pnma and finally to LCP-Pn21a at 575 and 725 °C, respectively. In addition to that, the determination of the magnetic susceptibility as a function of temperature indicates a long-range antiferromagnetic order below TN = 11 K at 10 kOe and 9.1 K at 25 kOe. The magnetization curves suggests the presence of a metamagnetic transition.
Journal of Personality and Social Psychology Behavioral Activation and Inhibition in Everyday Life

Joint effects of daily events and dispositional sensitivities to cues of reward and punishment on daily positive affect (PA) and negative affect (NA) were examined in 3 diary studies. Study 1 showed that positive events were strongly related to PA but not NA, whereas negative events were strongly related to NA but not PA. Studies 2 and 3 examined how the dispositional sensitivities of independent appetitive and aversive motivational systems, the Behavioral Activation System (BAS) and the Behavioral Inhibition System (BIS), moderated these relationships. Participants in Study 2 with higher BAS sensitivity reported more PA on average; those with more sensitive BIS reported more NA. Also, BIS moderated reactions to negative events, such that higher BIS sensitivity magnified reactions to negative events. Study 3 replicated these findings and showed that BAS predisposed people to experience more positive events. Results demonstrate the value of distinguishing within-person and between-person effects to clarify the functionally independent processes by which dispositional sensitivities influence affect. Extensive research addresses the role of mood and affect in cognition and behavior. Studies of the occurrence of and fluctuations in daily affect provide a logical complement to studies of affective influences on psychological processes, because they can help identify the prevalence and impact of affect in natural experience. Studies of dally affective experience have largely focused on how events, mainly stressors, contribute to affect (e. on any given day, people experience myriad events, some positive and some negative, that influence their moods to varying degrees. The present research focused on • the role of two factors-the valence of daily events and disposi-tional sensitivities to reward and punishment-in everyday affec-five experience. We asked the general question, how do everyday events and these dispositional tendencies combine to influence day-today affect? Many studies have examined relationships among dispositions and psychological well-being (defined here in terms of daily affect; Diener & Lucas, 1999). Less, but still substantial, attention has been focused on within-person variability in daily affect. Both kinds of studies are needed. Whereas studies of dispositions provide insights into relatively stable differences among people, studies of within-person variability highlight fluctuations that are salient from people's personal perspective. Although within-person processes are generally recognized to be statistically independent of between-person processes, the conceptual difference between these levels of analysis is sometimes overlooked (Gable & Reis, 1999). Daily life may be experienced in within-person terms; that is, mood at a given moment or on …
Metastatic Hepatocarcinoma He/De Tumor Model in Rat

The aim of this study is to select among potential tumor models that could be suitable to follow the metastatic spead of tumor cells. 18FDG-PET tumor diagnostic test has been adapted to investigate tumor growth in vivo in local and metastatic rat models. Materials and Methods. The expression of glucose transporters was traced by immunohistological analysis, followed by the uptake of 18FDG and visualized by MiniPET scanner. After s.c. administration of hepatocarcinoma (He/De) cells intensive local tumor growth and 18FDG uptake were measured. Results: Whole body 18FDG-PET imaging supported by histological analysis have shown that subcutaneously growing tumors did not project metastases to other sites from the injected area. To avoid local tumor formation i.v. injection was chosen, but did not improve the safety of tumor cell administration. Tumor formation after i.v. injection took a longer time than after s.c. administration. Tumors upon i.v. generation were smaller and detectable in liver and lung, but not in other organs or tissues. iii) Subrenally implanted He/De cells spread from the retroperitoneal primary tumor of the kidney to thoracal paratymic lymph nodes (PTNs). The spread from primary site to metastatic tumors in PTNs was confirmed by post mortem surgery and histological examinations. Conclusion: Among the three methods applied: a) Local s.c. administration of tumor cells generated local tumors unsuitable to study metastasis. b) Intravenous administration causing unpredicatable location of tumor formation is not regarded a reliable metastatic tumor model. c) Subreanal implantation model proved to be a suitable model to follow the metastatic process in rats.
Diffusion of Multiple Information: On Information Resilience and the Power of Segregation

We introduce two pieces of information, denoted memes, into a diffusion process in which memes are transmitted when individuals meet and forgotten at an exogenous rate. At most one meme can be transmitted at a meeting, which introduces opportunity costs in the process. Individuals differ according to which meme they find more interesting, and that is the one they transmit if they face a choice. We find that both memes survive under the same parameter values, and that relative interest is the main determinant in the number of people informed of a meme in the long run. We apply our framework to analyze the impact of segregation and find that segregation leads to polarization. Segregation also reduces the overall number of people informed in the long run. Our final set of results shows that agents are more likely to prefer segregation if their information preferences are more extreme, if they have few social contacts, or if they prefer a meme that is preferred by only a small fraction of the population
Origin of Solar Torsional Oscillations

Helioseismology has revealed many details of solar differential rotation and its time variation, known as torsional oscillations. So far there is no generally accepted theoretical explanation for torsional oscillations, even though a close relation to the solar activity cycle is evident. On the theoretical side, nonkinematic dynamo models (including the Lorentz force feedback on differential rotation) have been used to explain torsional oscillations. In this paper we use a slightly different approach by forcing torsional oscillations in a mean field differential rotation model. Our aim is not a fully self-consistent model, but rather to point out a few general properties of torsional oscillations, and their possible origins, that are independent from a particular dynamo model. We find that the poleward-propagating high-latitude branch of the torsional oscillations can be explained as a response of the coupled differential rotation/meridional flow system to periodic forcing in midlatitudes of either mechanical (Lorentz force) or thermal nature. The speed of the poleward propagation sets constraints on the value of the turbulent viscosity in the solar convection zone to be less than 3 × 108 m2 s-1. We also show that the equatorward-propagating low-latitude branch is most likely not a consequence of mechanical forcing (Lorentz force) alone, but rather of thermal origin due to the Taylor-Proudman theorem.
Stepwise increase in the prevalence of isolated systolic hypertension with the stages of chronic kidney disease.

BACKGROUND Hypertension is common in patients with chronic kidney disease (CKD), and isolated systolic hypertension (ISH) accounts for most patients with inadequate blood pressure (BP) control. However, it remains unclear whether the prevalence of ISH would increase with the advancement of CKD. METHODS CKD patients of stages 3, 4 and 5 were recruited (n = 324). Based on office systolic BP (SBP) and diastolic BP (DBP), they were classified into any of the four hypertensive subtypes: normotension (SBP/DBP <140/90 mmHg), isolated diastolic hypertension (IDH, SBP <140 mmHg and DBP >or=90 mmHg), ISH (SBP >or=140 mmHg and DBP <90 mmHg) and systolic-diastolic hypertension (SDH, SBP/DBP >or=140/90 mmHg). RESULTS The control rate was 45.7% at stage 3, which decreased with the advancement of CKD (control rate was 51.9%, 40.4% and 38.6% in stage 3, 4 and 5, respectively; P < 0.05). The prevalence of IDH changed from 5.0% to 5.3% and 0% from stage 3 to 4 and 5, while there was no significant change in the prevalence of SDH (15.0%, 14.9% and 15.7% at stage 3, 4 and 5, respectively). There was a stepwise increase in the prevalence of ISH with the stages of CKD (it was 28.1%, 39.4% and 45.7% in stage 3, 4 and 5, respectively). Logistic regression showed that age and CKD stages [compared with stage 3, stage 4 and 5 had 2.57 (95% CI 1.04-6.33) and 3.68 (95% CI 1.09-12.47) folds higher risk to develop ISH, respectively] were independent predictors of ISH. CONCLUSION The prevalence of ISH increased correspondingly with advanced stages of CKD, which may partially contribute to the increased cardiovascular mortality during the progress of CKD.
Ex Ante Skewness and Expected Stock Returns

We use a sample of option prices, and the method of Bakshi, Kapadia and Madan (2003), to estimate the ex ante higher moments of the underlying individual securities’ risk-neutral returns distribution. We find that individual securities’ volatility, skewness, and kurtosis are strongly related to subsequent returns. Specifically, we find a negative relation between volatility and returns in thecross-section. We also find a significant relation between skewness and returns, with more negatively (positively) skewed returns associated with subsequent higher (lower) returns, while kurtosis is positively related to subsequent returns. We analyze the extent to which these returns relations represent compensation for risk. We find evidence that, even after controlling for differences in comoments, individual securities’ skewness matters. As an application, we examine whether idiosyncratic skewness in technology stocks might explain bubble pricing in Internet stocks. However, when we combine information in the risk-neutral distribution and a stochastic discount factor to estimate the implied physical distribution of industry returns, we find little evidence that the distribution of technology stocks was positively skewed during the bubble period – in fact, these stocks have the lowest skew, and the highest estimated Sharpe ratio, of all stocks in our sample.
Bayesian Inference of Task-Based Functional Brain Connectivity Using Markov Chain Monte Carlo Methods

The study of functional networks in the brain is essential in order to gain a better insight into its diverse set of operations and to characterise the associated normal and abnormal behaviors. Present methods of analysing fMRI data to obtain functional connectivity are largely limited to approaches such as correlation, regression, and independent component analysis, which give simple point estimates. By contrast, we propose a stochastic linear model in a Bayesian setting and employ Markov chain Monte Carlo methods to approximate posterior distributions of full connectivity and covariance matrices. Through the use of a Bayesian probabilistic framework, distributional estimates of the linkage strengths are obtained as opposed to point estimates, and the uncertainty of the existence of such links is accounted for. We decompose the connectivity matrix as the Hadamard product of binary indicators and real-valued variables, and formulate an efficient joint-sampling scheme to infer them. The well-characterised somato-motor network is examined in a self-paced, right-handed finger opposition task-based experiment, while nodes from the visual network are used for contrast during the same experiment. Unlike for the visual network, significant changes in connectivity are found in the motor network during the task. Our work provides a distributional metric for functional connectivity along with causality information, and contributes to the collection of network level descriptors of brain functions.
A synthesis model for AGN evolution: supermassive black holes growth and feedback modes

We present a comprehensive synthesis model for the active galactic nuclei (AGN) evolution and the growth of supermassive black hole (SMBH) in the Universe. We assume that black holes accrete in just three distinct physical states, or 'modes': at low Eddington ratio, only a radiatively inefficient, kinetically dominated mode is allowed [low kinetic (LK)]; at high Eddington ratio, instead, AGN may display both a purely radiative [radio quiet, high radiative (HR)] and a kinetic [radio loud, high kinetic (HK)] mode. We solve the continuity equation for the black hole mass function using the locally determined one as a boundary condition, and the hard X-ray luminosity function as tracer of the AGN growth rate distribution, supplemented with a luminosity-dependent bolometric correction and an absorbing column distribution. Differently from most previous semi-analytic and numerical models for black hole growth, we do not assume any specific distribution of Eddington ratios, rather we determine it empirically by coupling the mass and luminosity functions and a set of fundamental relations between observables in the three accretion modes. SMBH always show a very broad accretion rate distribution, and we discuss the profound consequences of this fact for our understanding of observed AGN fractions in galaxies, as well as for the empirical determination of SMBH mass functions with large surveys. We confirm previous results and clearly demonstrate that, at least for z≤ 1.5, SMBH mass function evolves antihierarchically, i.e. the most massive holes grew earlier and faster than less massive ones. For the first time, we find hints of a reversal of such a downsizing behaviour at redshifts above the peak of the black hole accretion rate density (z ≈2). We also derive tight constraints on the (mass-weighted) average radiative efficiency of AGN: under the simplifying assumption that the mass density of both high redshift (z ∼5) and 'wandering' black holes ejected from galactic nuclei after merger events are negligible compared to the local mass density, we find that 0.065 0.07, where ξ 0 is the local SMBH mass density in units of 4.3 x 10 5 M ⊙ Mpc -3 . We trace the cosmological evolution of the kinetic luminosity function of AGN, and find that the overall efficiency of SMBH in converting accreted rest mass energy into kinetic power, e kin , ranges between e kin ≃ (3-5) x 10 -3 , depending on the choice of the radio core luminosity function. Such a 'kinetic efficiency' varies however strongly with SMBH mass and redshift, being maximal for very massive holes at late times, as required for the AGN feedback by many galaxy formation models in cosmological contexts.
An empirical study of the naive Bayes classifier

The naive Bayes classiﬁer greatly simplify learning by assuming that features are independent given class. Although independence is generally a poor assumption, in practice naive Bayes often competes well with more sophisticated classiﬁers. Our broad goal is to understand the data characteristics which affect the performance of naive Bayes. Our approach uses Monte Carlo simulations that allow a systematic study of classiﬁcation accuracy for several classes of randomly generated problems. We analyze the impact of the distribution entropy on the classiﬁcation error, showing that low-entropy feature distributions yield good performance of naive Bayes. We also demonstrate that naive Bayes works well for certain nearly-functional feature dependencies, thus reaching its best performance in two opposite cases: completely independent features (as expected) and functionally dependent features (which is surprising). Another surprising result is that the accuracy of naive Bayes is not directly correlated with the degree of feature dependencies measured as the class-conditional mutual information between the features. Instead, a better predictor of naive Bayes accuracy is the amount of information about the class that is lost because of the independence assumption.
An adaptive subdivision technique for the approximation of attractors and invariant measures: proof of convergence

We prove convergence of a recently introduced adaptive multilevel algorithm for the efficient computation of invariant measures and attractors of dynamical systems. The proof works in the context of (sufficiently regular) stochastic processes and essentially shows that the discretization of phase space leads to a small random perturbation of the original process. A generalized version of a lemma of Khasminskii then gives the desired result.