Miracle-dz/UniFAR-FTUs huggingface dataset:
Being the University: Liaison Persons' Reflections on Placements with Off-Site Supervision

Social work as a profession, social work practitioners and organisations, as well as social work educators are under strain due to global, economic, social and political changes and workplace pressures. Field education is recognised as pivotal in preparing social work students for professional practice. As social work practitioners, organisations and social work educators are exposed to external and internal pressures, social work practice learning with off-site supervision is becoming more prevalent. This paper reports on research that explored the experiences of key stakeholders in social work practice learning with external or, in other words, off-site supervision. This paper explores the experiences of university liaison persons who provided supported field education arrangements with off-site supervision. A range of themes have emerged, including reflections about bringing the university to the placement experience, creating student centred placement opportunities, the complexity of connecting the various players and the extra support and resources needed to support placements with off-site supervision. Findings suggest that quality learning experiences are about more than modes of supervision, that placements with off-site supervision increase the workload of liaison persons and that clear models and structures need to be developed to support emerging field education models.
Fgf16 Is Required for Specification of GABAergic Neurons and Oligodendrocytes in the Zebrafish Forebrain

Fibroblast growth factor (Fgf) signaling plays crucial roles in various developmental processes including those in the brain. We examined the role of Fgf16 in the formation of the zebrafish brain. The knockdown of fgf16 decreased cell proliferation in the forebrain and midbrain. fgf16 was also essential for development of the ventral telencephalon and diencephalon, whereas fgf16 was not required for dorsoventral patterning in the midbrain. fgf16 was additionally required for the specification and differentiation of γ–aminobutyric acid (GABA)ergic interneurons and oligodendrocytes, but not for those of glutamatergic neurons in the forebrain. Cross talk between Fgf and Hedgehog (Hh) signaling was critical for the specification of GABAergic interneurons and oligodendrocytes. The expression of fgf16 in the forebrain was down-regulated by the inhibition of Hh and Fgf19 signaling, but not by that of Fgf3/Fgf8 signaling. The fgf16 morphant phenotype was similar to that of the fgf19 morphant and embryos blocked Hh signaling. The results of the present study indicate that Fgf16 signaling, which is regulated by the downstream pathways of Hh-Fgf19 in the forebrain, is involved in forebrain development.
Mapping the similarity space of paintings: Image statistics and visual perception

What makes two images look similar? Here we test the hypothesis that perceived similarity of artwork is related to basic image statistics to which the early visual system is attuned. In two experiments, we employ multidimensional scaling (MDS) analysis of paired-image similarity ratings from observers for paintings. Two sets of images, classified as “landscapes” and “portraits/still-life”, are tested separately. For the landscapes, we find that one of the first two MDS scales of similarity is strongly correlated with a basic greyscale image statistic, whereas the other dimension can be accounted for by a semantic variable (representation of people). For portrait/still-life, the first two MDS scales of similarity are most highly correlated with semantic variables. Linear combinations of statistical and nonstatistical features achieve improved predictive values for the first two MDS scales for both sets. The statistics that play the largest role in shaping similarity judgements in our tests are the activity fraction measure of sparseness and the log-log slope of the spatial frequency amplitude spectrum. We discuss these results in the context of scene perception and in terms of efficient coding of statistical regularities in scenes.
Examination of curricula, teaching practices, and assessment through National Standards

This study examined to what degree the existing curricula, teaching practices, and assessments in 15 elementary physical education programs were aligned with the National Standards for Physical Education (NASPE, 1995) in the USA. Fifteen elementary physical education teachers voluntarily participated in this study. Data were gathered through observing 48 lessons while taking field notes, conducting 15 formal interviews with the teachers and collecting curriculum guides, unit and lesson plans and assessment sheets. The findings indicated that 12 teachers intentionally or unintentionally aligned their curriculums with the National Standards by designing an essential scope and progressive sequence for their programs. The teachers addressed Standards 1 and 2 in 35 observed lessons by providing outcome-oriented learning experiences that help students become competent in and knowledgeable about a variety of movement forms. Five teachers used assessment as an integral part of instruction to enhance the students' skill competency and knowledge acquisition. This study suggests that professional development plays a paramount role in equipping teachers with the knowledge and skills necessary for implementing the Standards in practice.
I'm not all gone, I can still speak: The experiences of younger people with dementia. An action research study

In this study we explored the experiences of younger people with dementia (age 60–67 years) using an action research methodology across three phases. Phase One involved interviews with participants (n = 8). Phases Two (n = 5) and Three (n = 4) consisted of two action research groups. Thematic analysis highlighted few difficulties commonly associated with younger people with dementia (e.g. loss of employment). Participants highlighted a need for social support from a variety of sources as well as the opportunity to develop a shared social identity and a focus on remaining strengths. The ‘action’ (Phase Three) comprised a leaflet written by participants for other people with dementia. The findings suggest there is a need for people with dementia to receive information from people who have experienced dementia and for that information to foster a sense of hope and resilience. Furthermore, the findings support the use of action research methodologies with people with dementia.
Modeling emotional context from latent semantics

In order to extract the atmosphere in media, we model the latent semantics of TV synopses and affective terms as patterns of emotional components. Using a selection of affective last.fm tags and TV-Anytime atmosphere terms as emotional buoys, we apply LSA latent semantic analysis to represent the correlation of terms and descriptions in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, we propose that this approach could be applied to automatically generate affective user preferences based on synopsis, subtitles or other textual representations associated with media.
DNN-Based Feature Extraction and Classifier Combination for Child-Directed Speech, Cold and Snoring Identification

In this study we deal with the three sub-challenges of the In-terspeech ComParE Challenge 2017, where the goal is to identify child-directed speech, speakers having a cold, and different types of snoring sounds. For the ﬁrst two sub-challenges we propose a simple, two-step feature extraction and classiﬁ-cation scheme: ﬁrst we perform frame-level classiﬁcation via Deep Neural Networks (DNNs), and then we extract utterance-level features from the DNN outputs. By utilizing these features for classiﬁcation, we were able to match the performance of the standard paralinguistic approach (which involves extracting thousands of features, many of them being completely irrelevant to the actual task). As for the Snoring Sub-Challenge, we divided the recordings into segments, and averaged out some frame-level features segment-wise, which were then used for utterance-level classiﬁcation. When combining the predictions of the proposed approaches with those got by the standard par-alinguistic approach, we managed to outperform the baseline values of the Cold and Snoring sub-challenges on the hidden test sets.
Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

Recurrent Neural Network (RNN) is one of the most popular architectures used in Natural Language Processsing (NLP) tasks because its recurrent structure is very suitable to process variable-length text. RNN can utilize distributed representations of words by first converting the tokens comprising each text into vectors, which form a matrix. And this matrix includes two dimensions: the time-step dimension and the feature vector dimension. Then most existing models usually utilize one-dimensional (1D) max pooling operation or attention-based operation only on the time-step dimension to obtain a fixed-length vector. However, the features on the feature vector dimension are not mutually independent, and simply applying 1D pooling operation over the time-step dimension independently may destroy the structure of the feature representation. On the other hand, applying two-dimensional (2D) pooling operation over the two dimensions may sample more meaningful features for sequence modeling tasks. To integrate the features on both dimensions of the matrix, this paper explores applying 2D max pooling operation to obtain a fixed-length representation of the text. This paper also utilizes 2D convolution to sample more meaningful information of the matrix. Experiments are conducted on six text classification tasks, including sentiment analysis, question classification, subjectivity classification and newsgroup classification. Compared with the state-of-the-art models, the proposed models achieve excellent performance on 4 out of 6 tasks. Specifically, one of the proposed models achieves highest accuracy on Stanford Sentiment Treebank binary classification and fine-grained classification tasks.
Amyotrophic Lateral Sclerosis With Positive Anti-Acetylcholine Receptor Antibodies. Case Report and Review of the Literature

Abstract Myasthenia gravis is a nerve–muscle junction disease, for which the most specific test is an increase in the anti-acetylcholine receptor antibodies (anti-AChR-Abs) titer. Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting both upper and lower motor neurons. Positive AChR-Ab in patients with pure ALS are exceedingly rare. We report the case of a patient with confirmed ALS and very high levels of AChR-Ab and review the literature on this topic.
Supporting Communicability with Use Case Guidelines: An Empirical Study

Recent research into use cases advocates guidance in the composition and structuring of their descriptions. For example, the CREWS research project has proposed Use Case Authoring Guidelines. As such, this paper describes an experiment, which compares the utility of use-case writing guidelines, specifically our own (CP) guidelines with those from the CREWS group. Replication of CREWS studies has indicated that use cases are improved through the application of guideline sets, but that their application is problematic. Further experimentation has focused on comparing our own (leaner) CP Rules to those of CREWS. Our pilot experiment appeared to show that the CP Rules performed as well as those from CREWS across two types of scenario or domain. We further noted from the pilot that the CP Structure Rules actually fared better for one of the scenarios. Hence, the pilot seemed to suggest that the CP Rules would perform at least as well as the CREWS Guidelines, whilst also flagging a possible need to consider the type of scenario. The experiment now described thus attempts to confirm the findings of the pilot. In some senses, this has been successful, in that we conclude the CP Structure Rules either fare as well or better than those from CREWS. However, we also note that the improved CP scores seen were for the opposite scenario to those for the pilot. Hence, whilst being gratified by the general trend of the result we also consider the issues of combining studies in this way.
Speeding up evolutionary multi-objective optimisation through diversity-based parent selection

Parent selection in evolutionary algorithms for multi-objective optimization is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points, while the reproduction phase involves the application of diversity mechanisms or other methods to achieve a good spread of the population along the Pareto front. We propose to refine the parent selection on evolutionary multi-objective optimization with diversity-based metrics. The aim is to focus on individuals with a high diversity contribution located in poorly explored areas of the search space, so the chances of creating new non-dominated individuals are better than in highly populated areas. We show by means of rigorous runtime analysis that the use of diversity-based parent selection mechanisms in the Simple Evolutionary Multi-objective Optimiser (SEMO) and Global SEMO for the well known bi-objective functions OneMinMax and Lotz can significantly improve their performance. Our theoretical results are accompanied by additional experiments that show a correspondence between theory and empirical results.
A Systematic Analysis of the Deracialization Concept

and Renford Reese for their prior comments. Of course, only the authors can be responsible for the analyses and interpretations presented here. We would like to especially thank Dan Orey, Jr. (1941-2006) who encouraged both of us to make the best of our education while matriculating as studendathletes at hislour alma mater, Mississippi Valley State University.
Theorising news mediations of the Zuma rape trial – citizens and subjects in collision

One of the challenges to studying the media in non-‘Western’ locations is to decide on appropriate and relevant theoretical framings for such work. Moreover in African contexts there is a call for African scholarship. In this paper I propose that two very different sets of theories are relevant to theorising the media in a southern African context. First I draw on Foucauldian understandings of governmentality and subjectivities, in spite of the fact that Foucault and his commentators make frequent reference to the ‘Western’ world and the ‘Western subject’. In addition to Foucauldian insights, I also draw on African scholar, Mamdani's theories. He argues that colonial power was effected through indirect rule to constitute people as either ‘citizen’ or ‘subject’. The bifurcated nature of the state thus proposed different sets of identities and has resulted in a particular ‘history of the present’. From a position that argues that Foucault's and Mamdani's insights are fundamental to understanding this postcolonial context and the media constructions that result, I relate them empirically to a case study of the coverage and the accompanying popular responses in the South African press of the controversial rape trial of former South African deputy president, Jacob Zuma.1 If a rights-based discourse informed much of the reporting, it did this by constituting the discourse of ethnicity (rather than the customary) as other. At the same time both patriarchal and gender rights discourses were in unequal contestation.
Analysis of Similarity based Representations on Heterogeneous Data

[ANGLES] The most common methodology of similarity based learning is the k-nearest neighbour method. But this has the disadvantage of having to store and calculate distances (similarities) for all the instances in the dataset. A more efficient methodology is to calculate similarities to only a set of chosen prototypes and use this as a new representation for learning. The current thesis deals with the implementation of these ideas using the Gower’s similarity measure for heterogeneous data. The comparison of clustering and feature selection methods for prototype selection is explored. Different methodologies are implemented in an attempt to improve the Gower’s similarity measure with the incorporation of weights for features. Novel methodologies to extract deep/higher level features from the similarity representation are proposed. The thesis provides preliminary results in these areas of research which are encouraging.
A Synthesis of Qualitative Research on Wellness-Illness

Health, disease, wellness, and illness have long been concepts central to health care disciplines. To further develop theory regarding the individual's experience of health and disease, a meta-analysis was undertaken of 112 qualitative studies from 1980 to 1991. A synthesis of qualitative research was done to derive substantive interpretations about health, disease, wellness, and illness from grounded theory, phenomenological, and ethnographic perspectives. The texts were compared and analyzed, creating new interpretations through synthesis of reciprocal translations. A dialectic model of wellness-illness was inductively derived. The process, meaning, and context inherent in the experience of health-disease are described as "living-in-the-world" of health-disease. Wellness-illness is depicted as the human experience of actual or perceived function-dysfunction. The theory emerging from this meta-analysis of qualitative research provides a synthesis of the commonalities among individual representations of health and disease.
The Arctic response to remote and local forcing of black carbon

Recent studies suggest that the Arctic temperature response to black carbon (BC) forcing depend strongly on the location of the forcing. We investigate how atmospheric BC in the mid-latitudes remotely influence the Arctic climate, and compare this with the response to atmospheric BC located in the Arctic itself. In this study, idealized climate simulations are carried out with a fully coupled Earth System Model, which includes a comprehensive treatment of aerosol microphysics. In order to determine how BC transported to the Arctic and BC sources not reaching the Arctic impact the Arctic climate, atmospheric BC concentrations are scaled up in the mid-latitudes (28–60° N) and in the Arctic (60–90° N), respectively. Estimates of the impact on the Arctic energy budget are represented by analyzing radiation fluxes at the top of the atmosphere and at the surface, surface turbulent fluxes, and meridional heat transport in the atmosphere. Our calculations show that increased BC forcing in the Arctic atmosphere reduces the surface air temperature in the Arctic with a corresponding increase in the sea-ice fraction, despite the increased planetary absorption of sunlight. The analysis indicates that this effect is due to a combination of a weakening of the northward heat transport caused by a reduction in the meridional temperature gradient and a dimming at the surface. On the other hand we find that BC forcing at the mid-latitudes warms the Arctic surface significantly and decreases the sea-ice fraction. Our model calculations indicate that atmospheric BC forcing outside the Arctic may be more important for the Arctic climate change than the forcing in the Arctic itself. These results suggest that mitigation strategies for the Arctic climate should also address BC sources in locations outside the Arctic even if they do not contribute much to BC in the Arctic.
Inferring Types for Parallel Programs

Citation for published version (APA): Martins, F. , Vasconcelos, V. T. , & Hüttel, H. (2017). Inferring types for parallel programs. In V. T. Vasconcelos , & P. Haller (Eds.), Proceedings Tenth Workshop on Programming Language Approaches to Concurrencyand Communication-cEntric Software (Vol. 246, pp. 28-36). Open Publishing Association. Electronic Proceedings in Theoretical Computer Science, EPTCS, Vol. 246 https://doi.org/10.4204/EPTCS.246. 6
A New Semantic Representation Model for the Elements of News

A novel semantic representation model based on Concepts and Knowledge Trees for the elements of news is described in this paper. The theoretical foundations about Concepts and Knowledge Trees are introduced briefly first. Then the key points of representing the semantic information of the four main news elements using the given model are explained respectively. Both advantages and disadvantages of the model are discussed from theoretical and practical view.
Relation of QT interval and QT dispersion to echocardiographic left ventricular hypertrophy and geometric pattern in hypertensive patients. The LIFE study.

Objective In hypertensive patients, left ventricular hypertrophy (LVH) predicts increased mortality, in part due to an increased incidence of sudden death. Repolarization-related arrhythmogenesis may be an important mechanism of sudden death in hypertensive patients with LVH. Increased QT interval and QT dispersion are electrocardiographic (ECG) measures of ventricular repolarization, and also risk markers for ventricular tachyarrhythmias. We assessed the relation of QT intervals and QT dispersion to echocardiographically determined left ventricular (LV) mass and geometry in a large population of hypertensive patients with ECG evidence of LVH. Methods QT intervals and QT dispersion were determined from baseline 12-lead ECGs in 577 (57% male; mean age 65 ± 7 years) participants in the LIFE study. LV mass index (LVMI) and geometric pattern were determined by echocardiography and QT interval duration and QT dispersion were assessed in relation to gender-specific LVMI quartiles. Results In both genders, increasing LVMI was associated with longer rate-adjusted QT intervals. QT dispersion measures showed a weaker association with LVMI quartiles. Both concentric and eccentric LVH were associated with increased QT interval duration and QT dispersion. These relations remained significant after controlling for relevant clinical variables. Conclusions In hypertensive patients with ECG evidence of LVH, increased LVMI and LVH are associated with a prolonged QT interval and increased QT dispersion. These findings suggest that an increased vulnerability to repolarization-related ventricular arrhythmias might in part explain the increased risk of sudden death in hypertensive patients with increased LV mass.
Stackelberg Pricing is Hard to Approximate within 2-ε

Stackelberg Pricing Games is a two-level combinatorial pricing problem studied in the Economics, Operation Research, and Computer Science communities. In this paper, we consider the decade-old shortest path version of this problem which is the first and most studied problem in this family. The game is played on a graph (representing a network) consisting of {\em fixed cost} edges and {\em pricable} or {\em variable cost} edges. The fixed cost edges already have some fixed price (representing the competitor's prices). Our task is to choose prices for the variable cost edges. After that, a client will buy the cheapest path from a node $s$ to a node $t$, using any combination of fixed cost and variable cost edges. The goal is to maximize the revenue on variable cost edges. In this paper, we show that the problem is hard to approximate within $2-\epsilon$, improving the previous \APX-hardness result by Joret [to appear in {\em Networks}]. Our technique combines the existing ideas with a new insight into the price structure and its relation to the hardness of the instances.