Miracle-dz/UniFAR-FTUs huggingface dataset:
Growing Citizens: Students’ Social Emotional Learning via School Gardens

The importance of social and emotional learning in the life of a student is now being recognized as a factor for academic and life success. How a garden can help in the promotion of skills related to social and emotional learning will provide further justification for the implementation of gardens in schools. The purpose of this exploratory, interpretivist qualitative study, with data collected from a purposive sample of educators involved in classroom-based education within schools, was to explore the social and emotional practices of primary grade students (kindergarten through grade five). The sample size consisted of 14 educators who were located across six schools located throughout Southwestern Ontario. Participants included vice principals, special education resource room teachers (SERR), classroom teachers, and early childhood educators (ECE). All participants worked with grades kindergarten through five, respectively, in urban elementary schools. Qualitative data consisted of participant interviews that were recorded and later transcribed, educators’ observations and field notes, and my own personal field notes. Through conclusions drawn from this case study it was, demonstrated that gardening experiences benefitted most students, but in particular, those students who have diverse needs. Further results demonstrated that the social and emotional skills related to collaboration with others and interpersonal conflict resolution between students increased when students were involved in gardens and gardening experiences. Connected to the results of this study are recommendations for an examination of policies related to school gardens for Boards of Education and recommendations to educators to think of school gardens as being able to provide an opportunity for a variety of learning
The Persistence of Social Groups. II

IN many cases the structure of the group is from the beginning adjusted to such alternation between functions immediately discharged by the group and those that are performed by an organ. Thus in stock companies, the technical management of which is committed to directors, while the stockholders in general meeting may either remove the directors or prescribe conditions which the latter may be either indisposed or incompetent to adopt for themselves. Small associations which are accustomed either to manage their affairs through a president or a committee are usually so arranged that these organs either voluntarily or involuntarily surrender their powers so soon as they cease to be equal to the burden or the responsibility of their functions. Every revolution which deposes a political government from power and gives back legislation and administration to the immediate initiative of the elements belongs in this sociological form. It follows as a matter of course that not every group can adapt itself to such reversion of type. In very large groups, or in those that live under very complicated conditions, the assumption of administrative functions by the group directly is a simple impossibility. The structure of organs is not to be recalled, and their flexibility and vital interdependence with the elements can at most show themselves in the ability of the elements to change the persons who at a given moment compose the organ, and replace them with more suitable persons. Nevertheless it is continually happening, even in cases of rather high sociological development, that the group power flows back from the organs to its original source, though this may be but a process of transition to the formation of new organs. The Episcopal church in the United States was at the disadvantage of being without a bishop until the end of the last century, because the mother
Estimating surface carbon fluxes based on a local ensemble transform Kalman filter with a short assimilation window and a long observation window: an observing system simulation experiment test in GEOS-Chem 10.1

Abstract. We developed a carbon data assimilation system to estimate surface carbon fluxes using the local ensemble transform Kalman filter (LETKF) and atmospheric transport model GEOS-Chem driven by the MERRA-1 reanalysis of the meteorological field based on the Goddard Earth Observing System model, version 5 (GEOS-5). This assimilation system is inspired by the method of Kang et al. (2011, 2012), who estimated the surface carbon fluxes in an observing system simulation experiment (OSSE) as evolving parameters in the assimilation of the atmospheric CO2, using a short assimilation window of 6 h. They included the assimilation of the standard meteorological variables, so that the ensemble provided a measure of the uncertainty in the CO2 transport. After introducing new techniques such as “variable localization”, and increased observation weights near the surface, they obtained accurate surface carbon fluxes at grid-point resolution. We developed a new version of the local ensemble transform Kalman filter related to the “running-in-place” (RIP) method used to accelerate the spin-up of ensemble Kalman filter (EnKF) data assimilation (Kalnay and Yang, 2010; Wang et al., 2013; Yang et al., 2012). Like RIP, the new assimilation system uses the “no cost smoothing” algorithm for the LETKF (Kalnay et al., 2007b), which allows shifting the Kalman filter solution forward or backward within an assimilation window at no cost. In the new scheme a long “observation window” (e.g., 7 d or longer) is used to create a LETKF ensemble at 7 d. Then, the RIP smoother is used to obtain an accurate final analysis at 1 d. This new approach has the advantage of being based on a short assimilation window, which makes it more accurate, and of having been exposed to the future 7 d observations, which improves the analysis and accelerates the spin-up. The assimilation and observation windows are then shifted forward by 1 d, and the process is repeated. This reduces significantly the analysis error, suggesting that the newly developed assimilation method can be used with other Earth system models, especially in order to make greater use of observations in conjunction with models.
Training End Users: Assessing the Effectiveness of Multimedia CBT

End user training is one way to increase the effectiveness of end user computing and computer-based training (CBT) using multimedia technology has been touted as an effective alternative to traditional training methods. However, there has been virtually no empirical evidence that multimedia CBT is better than, or at least as good as, other training methods. This paper reports an empirical study that compared the efficacy of multimedia CBT versus other more traditional instructional methods. Multimedia CBT was not found to be as effective as other instructional methods. This unexpected outcome indicates further research is needed into multimedia CBT and into what factors might affect the success of this method of delivering instruction.
Enterprise Risk Budgeting: Bringing Risk Management into the Financial Planning Process

Enterprise Risk Management (ERM) is a holistic, integrated approach to managing a company's risks, in contrast to the so-called "silo-approach" prevalent in many firms in which risks are managed independently of each other. Yet for all the risk exposures that are brought under the corporate umbrella in an ERM-initiative, it may be inadequate for addressing the firm’s aggregate risk in terms of the probability of failing to meet important corporate objectives, such as implementing the business plan or protecting debt covenants. In this paper we present a quantitative approach to risk management in the non-financial firm that retains the integrative, enterprise-wide mindset, yet also equips Corporate Management with the ability to evaluate financial distress-probabilities by incorporating ideas related to the concept of a firm's Economic Capital. We term such an effort Enterprise Risk Budgeting (ER-B). ER-B makes possible an ongoing re-assessment of the firm's expected financial position and overall risk profile, and in particular how these change as a result of corporate policy decisions, for example relating to capital expenditure, acquisitions, dividends, and hedging. The transparency created by such a tool increases the likelihood that Management makes sound proactive decisions with respect to its risk profile, rather than reacting to challenging circumstances once they occur. We illustrate using the experiences of Norwegian aluminium producer Norsk Hydro.
Regret Bounds for Noise-Free Cascaded Kernelized Bandits

We consider optimizing a function network in the noise-free grey-box setting with RKHS function classes, where the exact intermediate results are observable. We assume that the structure of the network is known (but not the underlying functions comprising it), and we study three types of structures: (1) chain: a cascade of scalar-valued functions, (2) multi-output chain: a cascade of vector-valued functions, and (3) feed-forward network: a fully connected feed-forward network of scalar-valued functions. We propose a sequential upper confidence bound based algorithm GPN-UCB along with a general theoretical upper bound on the cumulative regret. For the Mat\'ern kernel, we additionally propose a non-adaptive sampling based method along with its theoretical upper bound on the simple regret. We also provide algorithm-independent lower bounds on the simple regret and cumulative regret, showing that GPN-UCB is near-optimal for chains and multi-output chains in broad cases of interest.
Delay Fairness Using the Burst Assembly for Service Differentiation

Using various offset times to separate differential services is the most common form of service differentiation in optical burst switching networks. In this approach, a larger offset time is given to a higher priority burst, but it causes this burst to have a longer delay. One solution to this problem is to adjust the burst assembly time so that the buffering delay of the higher priority burst is always shorter than that of the lower priority burst. However, this adjustment causes another problem, called delay unfairness, for bursts with differential priorities that share the same path to their destination. This article proposes a new solution for delay fairness using the burst assembly.
Efficient Brain Age Prediction from 3D MRI Volumes Using 2D Projections

Using 3D CNNs on high-resolution medical volumes is very computationally demanding, especially for large datasets like UK Biobank, which aims to scan 100,000 subjects. Here, we demonstrate that using 2D CNNs on a few 2D projections (representing mean and standard deviation across axial, sagittal and coronal slices) of 3D volumes leads to reasonable test accuracy (mean absolute error of about 3.5 years) when predicting age from brain volumes. Using our approach, one training epoch with 20,324 subjects takes 20–50 s using a single GPU, which is two orders of magnitude faster than a small 3D CNN. This speedup is explained by the fact that 3D brain volumes contain a lot of redundant information, which can be efficiently compressed using 2D projections. These results are important for researchers who do not have access to expensive GPU hardware for 3D CNNs.
Exploring the role of self-efficacy beliefs and learner success in English medium instruction

ABSTRACT English medium instruction (EMI) is a growing phenomenon in higher education contexts across the globe, and EMI programs are expanding rapidly in Japan as part of their internationalization efforts. This paper explores the relationship between student self-beliefs and their success in an EMI course within a bilingual business program. It analyzed direct measures of content course and preparatory course performances, proficiency, and questionnaire data from 139 students completing an English-mediated International Business course at a university in Japan. These data were supplemented by interviews with seven students. Multiple linear regression analysis found L2 proficiency, preparatory course performance, and self-efficacy to predict success in the EMI course. Our qualitative findings support these results, indicating that students with stronger efficacy put forth more effort and see course activities as development opportunities. These findings highlight the need for efficacy development opportunities for students entering EMI study.
University education and transition into the labour market during the financial crisis. Spanish evidence

ABSTRACT This research using a time survival model is aimed at analysing which factors determine the time it took Spanish university graduates to find their first job during the 2009–15 period, a time framework where the Spanish economy underwent the worst effects of the financial crisis. As far as training is concerned, both the type of degree (bachelor or master) and the field of knowledge decisively influence the employability process. Other factors also contribute to significantly reduce the time to obtain the first job. Among these are studying at a private university, taking a university master’s degree and studying abroad, as well as speaking some languages and having been awarded any grant. Gender does not seem to exercise any influence.
Synthetic grammar learning: Implicit rule abstraction or explicit fragmentary knowledge? Journal of

3 experiments were designed to demonstrate that classifying new letter strings as grammatical (i.e., conforming to a set of rules called a synthetic grammar) or ungrammatical may proceed from fragmentary conscious knowledge of the bigrams constituting the grammatical strings displayed in the study phase, rather than from an unconscious structured representation of the grammar, as Reber (1989) contended. In Experiment 1, grammaticality judgments of subjects initially studying grammatical letter strings did not differ from judgments by subjects learning from a list of the bigrams making up these strings. In Experiment 2, judgments about nongrammatical strings composed of valid bigrams placed in invalid locations were extremely poor, although better than chance. In Experiment 3 the explicit knowledge of bigrams as assessed by a recognition procedure appeared sufficient to account for observed performance on a standard test of grammaticality. A widely held model of cognition endows human subjects with the ability to implicitly abstract the regularities or highlevel rules embodied in richly structured stimulus domains. Over the last 20 years, this general model has received strong empirical support in the field of artificial grammar learning from extensive work by Reber and his associates (e.g., Reber, 1967; Reber & Allen, 1978; Reber, Kassin, Lewis, & Cantor, 1980; see Reber, 1989, for a review). In a typical experiment, subjects first study a set of letter strings generated from a synthetic grammar that defines authorized letters and the permissible transitions between them. The grammar used by Reber and his associates in several experiments, which also served in Dulany, Carlson, and Dewey's (1984) and in our experiments, consisted of five letter consonants (M, R, T, X, V) and the set of transition rules shown in schematic form in Figure I. Some instances of letter strings that this grammar generates are MTTVRX, VXVT, or VXM. After studying some representative exemplars, subjects are asked to categorize new grammatical and nongrammatical letter strings. Nongrammatical items (e.g., MVRa'R) are formed from the same subset of letters, but they violate transition rules. Most subjects are able to perform this task with better-than-chance accuracy. This finding is interpreted as evidence of subjects' ability to
The Effect of Modified Audit Opinion on Debt Contracts

The purpose of this study is to examine the effect of a modified audit opinion on the debt contract (interest spread, loan size, covenant, collateral, and loan maturity). Samples of this study are credit facilities obtained by listed firms in 2013-2016 with total observations of 660. Results of this study show that in general there is limited effect of modified audit opinion on debt contract. We do not find type of modified audit opinion causes higher interest rates. Modified audit opinion has significant effect on reducing the number of financial covenants. We only find evidence that material uncertainties type of modified audit opinion causes higher general covenant. We also only find evidence of the effect of modified audit opinion on loan maturity for going concern opinion type. Modified audit opinion does not affect loan size and the possibility of the need collateral in the debt contract. The insignificant results of modified audit opinion on debt contracts maybe due to lenders in Indonesia still use soft information (relationship lending) rather than hard information.
Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer

We propose a light-weight and highly efﬁcient Joint Detection and Tracking pipeline for the task of Multi-Object Tracking using a fully-transformer architecture. It is a mod-iﬁed version of TransTrack, which overcomes the computational bottleneck associated with its design, and at the same time, achieves state-of-the-art MOTA score of 73.20%. The model design is driven by a transformer based backbone instead of CNN, which is highly scalable with the input resolution. We also propose a drop-in replacement for Feed Forward Network of transformer encoder layer, by using Butterﬂy Transform Operation to perform channel fusion and depth-wise convolution to learn spatial context within the feature maps, otherwise missing within the attention maps of the transformer. As a result of our modiﬁcations, we reduce the overall model size of TransTrack by 58.73% and the complexity by 78.72%. Therefore, we expect our design to provide novel perspectives for architecture optimization in future research related to multi-object tracking.
The Metacognitions Questionnaire and Its Derivatives in Children and Adolescents: A Systematic Review of Psychometric Properties

Background: The Metacognitions Questionnaire (MCQ) and its derivatives have been instrumental in research examining the Self-Regulatory Executive Function Model in adults. Studies testing whether findings are applicable to children and adolescents have been increasing and several different measures adapting the MCQ for younger populations have been developed. The current study aimed to systematically review the psychometric properties of MCQ measures or derivatives used in young people (aged 18 or less), to help assess current findings in this population and to guide future research in this growing area of investigation. Method: Systematic searches were carried out on PubMed and PsycINFO of studies published up to June 2018. Additional studies were identified through Google Scholar and article references. Validity, reliability, range and responsiveness of measures were examined as well as analyses of age and gender differences on scores. Results: Forty-five articles were identified. The total sample consisted of 7,803 children and adolescents (6,922 non-clinical, 881 clinical) aged 7–18. Studies used one of seven versions of the questionnaire, five adapted from the MCQ for younger populations: (1) The Metacognitions Questionnaire-Adolescent version; (2) The Metacognitions Questionnaire-Child version; (3) The Metacognitions Questionnaire-Child Version-Revised; (4) The Metacognitions Questionnaire-Child-30; and (5) The Metacognitions Questionnaire-65 Positive Beliefs Scale Revised; and two adult versions used without adaptation: (1) The Metacognitions Questionnaire-30 and (2) The Cognitive Self Consciousness Scale-Expanded. The validity and reliability of the Metacognitions Questionnaire-Adolescent version had the most extensive support. Other questionnaires had either mixed psychometrics or promising initial findings but more limited data. Conclusions: It is recommended that studies using adolescents (age 12–18) consider using the Metacognitions Questionnaire-Adolescent version. Based on initial data, it is suggested studies using younger populations should consider the Metacognitions Questionnaire-Child-30 but further psychometric research into this and other measures is needed.
Bureaucratic state and health management training from a historical perspective: similarities and differences between Brazil and Spain

Resumo Este artigo descreveu o contexto historico da formacao em gestao em saude oferecida no Brasil e buscou identificar suas semelhancas e diferencas com aquela oferecida na Espanha. Adotou-se uma abordagem qualitativa da realidade e o metodo comparado foi empregado. Como fonte de dados, utilizaram-se a bibliografia cientifica, os documentos oficiais, que orientam as intervencoes no campo da formacao em gestao em saude nos dois paises, e a entrevista semiestruturada. As entrevistas foram realizadas com gestores selecionados pelo fato de estarem ocupando ou de terem ocupado cargos de gestao e que tenham participado da conformacao da politica de saude, totalizando quatro gestores brasileiros e seis espanhois. Apoiados na analise de conteudo tematica, os resultados se relacionaram com a categoria “institucionalidade” a partir dos seguintes temas: politica de saude e educacao; politica de formacao de gestores; e profissionalizacao. Identificou-se como elemento comum o fato de tanto o Brasil quanto a Espanha adotarem a protecao a saude como direito de cidadania por meio de sistemas publicos e universais de saude. A diferenca mais significativa diz respeito a cobertura populacional, alcancada na quase totalidade na Espanha no final dos anos 1990. Evidenciou-se a inexistencia de uma politica nacional de formacao de gestores nos dois paises, considerada central para a profissionalizacao da gestao em saude. Ainda que o tema da profissionalizacao esteja presente no Brasil, na Espanha assumiu contornos institucionais distintos com avancos significativos em periodo recente.
Artificial Neural Network Solver for Time-Dependent Fokker-Planck Equations

Stochastic differential equations play an important role in various applications when modeling systems that have either random perturbations or chaotic dynamics at faster time scales. The time evolution of the probability distribution of a stochastic differential equation is described by the Fokker-Planck equation, which is a second order parabolic partial differential equation. Previous work combined artificial neural network and Monte Carlo data to solve stationary Fokker-Planck equations. This paper extends this approach to time dependent Fokker-Planck equations. The focus is on the investigation of algorithms for training a neural network that has multi-scale loss functions. Additionally, a new approach for collocation point sampling is proposed. A few 1D and 2D numerical examples are demonstrated.