Miracle-dz/UniFAR-FTUs huggingface dataset:
Representing valued bodies in PE: a visual inquiry with British Asian girls

Background: Status or value in sport and physical education (PE) contexts is often associated with performances of highly proficient sporting bodies, which produce hierarchies of privileged and marginalised gendered and racialised positions. This may be communicated through text and images shared within school, physical cultures and media that young people consume. Understanding how students make sense of constructions of valued bodies in PE, and how this affects their sense of self, can assist in creating spaces for young people to experience alternative narratives. Focus: The paper's aims are to explore varying ways British Asian girls visualise and make sense of themselves as active or sporting bodies, and what this means for their (dis)engagement in physical activity. Theoretical framework: This study draws on a feminist poststructuralist approach concerning the ways in which young people create multiple subject positions through negotiating or rejecting verbal and visual narratives about physical activity and girlhood. Methods: The data draws from a one-year collaborative visual ethnography conducted with 25 students aged 13–14 in a predominantly British Asian urban secondary school in the UK. In this research, student-participants were included in the data production through being asked to create photographs over a two-week period that represented their views of valued bodies in physical activity contexts in and out of school. Focus group interviews used participant-driven photo elicitation techniques to talk through the images. Findings: In this paper, two British Asian girls’ photos enabled them to talk about, analyse, and reflect on valued or sporting bodies that they saw in visual media. The girls illustrated their performances of constrained or empowered physicalities, within a physical culture that values, among girls, racialised performances of active but feminised bodies. Many girls placed their physical activity significantly in school, and saw sporting bodies as male and elite. Where students do not associate people like themselves as sporting bodies, there may be implications for their continued involvement in physical activity. At the same time, girls were physically activity outside of school despite not seeing themselves as sporty. Reflecting on the invisibility of minority ethnic women in sports media, this research suggests that greater representation may enable young minority women to see themselves and people like them as valued bodies in sport and physical activity.
Counting matchings with k unmatched vertices in planar graphs

We consider the problem of counting matchings in planar graphs. While perfect matchings in planar graphs can be counted by a classical polynomial-time algorithm [Kasteleyn 1961], the problem of counting all matchings (possibly containing unmatched vertices, also known as defects) is known to be #P-complete on planar graphs [Jerrum 1987]. To interpolate between matchings and perfect matchings, we study the parameterized problem of counting matchings with k unmatched vertices in a planar graph G, on input G and k. This setting has a natural interpretation in statistical physics, and it is a special case of counting perfect matchings in k-apex graphs (graphs that become planar after removing k vertices). Starting from a recent #W[1]-hardness proof for counting perfect matchings on k-apex graphs [Curtican and Xia 2015], we obtain: - Counting matchings with k unmatched vertices in planar graphs is #W[1]-hard. - In contrast, given a plane graph G with s distinguished faces, there is an O(2^s n^3) time algorithm for counting those matchings with k unmatched vertices such that all unmatched vertices lie on the distinguished faces. This implies an f(k,s)n^O(1) time algorithm for counting perfect matchings in k-apex graphs whose apex neighborhood is covered by s faces.
Consistency of Random Forests

Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5–32] that combines several randomized decision trees and aggregates their predictions by averaging. Despite its wide usage and outstanding practical performance, little is known about the mathematical properties of the procedure. This disparity between theory and practice originates in the difficulty to simultaneously analyze both the randomization process and the highly data-dependent tree structure. In the present paper, we take a step forward in forest exploration by proving a consistency result for Breiman's [Mach. Learn. 45 (2001) 5–32] original algorithm in the context of additive regression models. Our analysis also sheds an interesting light on how random forests can nicely adapt to sparsity. 1. Introduction. Random forests are an ensemble learning method for classification and regression that constructs a number of randomized decision trees during the training phase and predicts by averaging the results. Since its publication in the seminal paper of Breiman (2001), the procedure has become a major data analysis tool, that performs well in practice in comparison with many standard methods. What has greatly contributed to the popularity of forests is the fact that they can be applied to a wide range of prediction problems and have few parameters to tune. Aside from being simple to use, the method is generally recognized for its accuracy and its ability to deal with small sample sizes, high-dimensional feature spaces and complex data structures. The random forest methodology has been successfully involved in many practical problems, including air quality prediction (winning code of the EMC data science global hackathon in 2012, see http://www.kaggle.com/c/dsg-hackathon), chemoinformatics [Svetnik et al. (2003)], ecology [Prasad, Iverson and Liaw (2006), Cutler et al. (2007)], 3D
DOCUMENTARY AS MONTAGE

The documentary work of Malaysian director Amir Muhammad is characterised by the montage-like style of his films. This article will consider Amir's The year of living vicariously through Walter Benjamin's notion of montage found in The arcades project. The year of living vicariously is based on a variety of interviews carried out by Amir in 2004 on the set of the Indonesian film Gie. The interviews are with the cast and crew of the film and the film itself is organised around a split screen. In addition to the continuous simultaneity of the split screen, often the film situates the production of the past (in the filming of Gie) juxtaposed to anxieties of the present. In the interviews and stories presented by Amir a number of ambivalent themes emerge, including the future role and power of the military, the role of corruption in Indonesian politics, the unresolved questions and politics surrounding 30 September Movement (G30S), apathy, or consumption. I will argue that this film provides a limited yet insightful account of the ambivalence of post-authoritarian Indonesia and in doing so it highlights the potential for montage to serve as the foundation for new forms of documentary.
Cost-effectiveness of treatments for major depression in primary care practice.

BACKGROUND This study augments a randomized controlled trial to analyze the cost-effectiveness of 2 standardized treatments for major depression relative to each other and to the "usual care" provided by primary care physicians. METHODS A randomized controlled trial was conducted in which primary care patients meeting DSM-III-R criteria for current major depression were assigned to pharmacotherapy (where nortriptyline hydrochloride was given) or interpersonal psychotherapy provided in a standardized framework or a primary physician's usual care. Two outcome measures, depression-free days and quality-adjusted days, were developed using information on depressive symptoms over time. The costs of care were calculated. Cost-effectiveness ratios comparing the incremental outcomes with the incremental costs for the different treatments were estimated. Sensitivity analyses were performed. RESULTS In terms of both economic costs and quality-of-life outcomes, patients assigned to the pharmacotherapy group did slightly better than those assigned to interpersonal psychotherapy. Both standardized therapies provided better outcomes than primary physician's usual care, but each consumed more resources. No meaningful cost-offsets were found. The incremental direct cost per additional depression-free day for pharmacotherapy relative to usual care ranges from $12.66 to $16.87 which translates to direct cost per quality-adjusted year gained from $11270 to $19510. CONCLUSIONS Standardized treatments for depression lead to better outcomes than usual care but also lead to higher costs. However, the estimates of the cost per quality-of-life year gained for standardized pharmacotherapy are comparable with those found for other treatments provided in routine practice.
Exploring the nature of the P300 in normal hearing adults in response to filtered words

The present study explored the nature of the auditory P300 in response to filtered words in ten normal hearing adults. P300 waveforms were elicited by a classic oddball paradigm, and recorded using a net of 128 electrodes (HydroCel Geodesic Sensor Net 128 1.0.). P300 waveforms from central, parietal, temporal right and temporal left regions were selected for data collection. P300 latencies and amplitudes for the largest deflection distinguishing responses to filtered from unfiltered words between 248 and 652 ms post stimuli were collected from each electrode in each region and these values were averaged obtain electrode group values. All filtered versions of the word successfully elicited P300 waveforms at all four recording locations in the form of large, vertex-positive deflections, which differed significantly (p<0.05) compared to the electrophysiological responses to the unfiltered stimulus. However, among the responses to the different filtered versions of the stimulus the overall tendency was that statistical differences could not be seen, neither in terms of amplitudes or latencies. The lack of substantial change in the P300 waveforms elicited by the different filtered versions of the stimulus word suggests the use of the P300 as a measure of filtered word performance is limited to the detection of a filtered version of a word and not the degree
A Longitudinal Approach to Assessing Urban and Suburban Children’s Exposure to Pyrethroid Pesticides

We conducted a longitudinal study to assess the exposure of 23 elementary school–age children to pyrethroid pesticides, using urinary pyrethroid metabolites as exposure biomarkers. We substituted most of the children’s conventional diets with organic food items for 5 consecutive days and collected two daily spot urine samples, first morning and before bedtime voids, throughout the 15-day study period. We analyzed urine samples for five common pyrethroid metabolites. We found an association between the parents’ self-reported pyrethroid use in the residential environment and elevated pyrethroid metabolite levels found in their children’s urine. Children were also exposed to pyrethroids through their conventional diets, although the magnitude was smaller than for the residential exposure. Children’s ages appear to be significantly associated with pyrethroids exposure, which is likely attributed to the use of pyrethroids around the premises or in the facilities where older children engaged in the outdoor activities. We conclude that residential pesticide use represents the most important risk factor for children’s exposure to pyrethroid insecticides. Because of the wide use of pyrethroids in the United States, the findings of this study are important for both children’s pesticide exposure assessment and environmental public health.
Tensor based multichannel reconstruction for breast tumours identification from DCE-MRIs

A new methodology based on tensor algebra that uses a higher order singular value decomposition to perform three-dimensional voxel reconstruction from a series of temporal images obtained using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is proposed. Principal component analysis (PCA) is used to robustly extract the spatial and temporal image features and simultaneously de-noise the datasets. Tumour segmentation on enhanced scaled (ES) images performed using a fuzzy C-means (FCM) cluster algorithm is compared with that achieved using the proposed tensorial framework. The proposed algorithm explores the correlations between spatial and temporal features in the tumours. The multi-channel reconstruction enables improved breast tumour identification through enhanced de-noising and improved intensity consistency. The reconstructed tumours have clear and continuous boundaries; furthermore the reconstruction shows better voxel clustering in tumour regions of interest. A more homogenous intensity distribution is also observed, enabling improved image contrast between tumours and background, especially in places where fatty tissue is imaged. The fidelity of reconstruction is further evaluated on the basis of five new qualitative metrics. Results confirm the superiority of the tensorial approach. The proposed reconstruction metrics should also find future applications in the assessment of other reconstruction algorithms.
Probabilistic Model for the Gravitational Wave Signal from Merging Black Holes

Parameterised models that predict the gravitational-wave (GW) signal from merging black holes are used to extract source properties from GW observations. The majority of research in this area has focused on developing methods capable of producing highly accurate, point-estimate, predictions for the GW signal. A key element missing from every model used in the analysis of GW data is an estimate for how confident the model is in its prediction. This omission increases the risk of biased parameter estimation of source properties. Current strategies include running analyses with multiple models to measure systematic bias however, this fails to accurately reflect the true uncertainty in the models. In this work we develop a probabilistic extension to the phenomenological modelling workflow for non-spinning black holes and demonstrate that the model not only produces accurate point-estimates for the GW signal but can be used to provide well-calibrated local estimates for its uncertainty. Our analysis highlights that there is a lack of Numerical Relativity (NR) simulations available at multiple resolutions which can be used to estimate their numerical error and implore the NR community to continue to improve their estimates for the error in NR solutions published. Waveform models that are not only accurate in their point-estimate predictions but also in their error estimates are a potential way to mitigate bias in GW parameter estimation of compact binaries due to unconfident waveform model extrapolations.
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data

MOTIVATION DIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows (i) the analysis of single nucleotide polymorphism data at large number of loci, apart from microsatellite and DNA sequence data, (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X. AVAILABILITY Freely available with a detailed notice document and example projects to academic users at http://www1.montpellier. inra.fr/CBGP/diyabc CONTACT: estoup@supagro.inra.fr Supplementary information: Supplementary data are available at Bioinformatics online.
The Fourth Element

This tutorial clarifies the axiomatic definition of (v<sup>(α)</sup>; i<sup>(β)</sup>) circuit elements via a lookup table dubbed an A-pad, of admissible (v; i) signals measured via Gedanken probing circuits. The (v<sup>(α)</sup>; i<sup>(β)</sup>) elements are ordered via a complexity metric. Under this metric, the memristor emerges naturally as the fourth element, characterized by a state-dependent Ohm's law. A logical generalization to memristive devices reveals a common fingerprint consisting of a dense continuum of pinched hysteresis loops whose area decreases with the frequency ω and tends to a straight line as ω ~ ∞, for all bipolar periodic signals and for all initial conditions. This common fingerprint suggests that the term memristor be used hence-forth as a moniker for memristive devices.
Weakly supervised training for parsing Mandarin broadcast transcripts

We present a systematic investigation of applying weakly supervised co-training approaches to improve parsing performance for parsing Mandarin broadcast news (BN) and broadcast conversation (BC) transcripts, by iteratively retraining two competitive Chinese parsers from a small set of treebanked data and a large set of unlabeled data. We compare co-training to self-training, and our results show that performance using co-training is signiﬁcantly better than with self-training and both co-training and self-training with a small seed labeled corpus can improve parsing accuracy signiﬁcantly over training on the mismatching newswire treebank. We also investigate a variety of example selection approaches for co-training and ﬁnd that our proposed example selection approach based on maximizing training utility produces the best parsing accuracy. We also investigate Chinese parsing related issues including character-based parsing and word segmentation for parsing.
(Dis)Honest Information Transmission: An Experimental Analysis

In this paper, I suggest a new experimental method for measuring (dis)honest information transmission. Subjects play a variant of the dictator game in which the dictator’s decision whether to lie (either to or against his advantage) or whether to be honest, when communicating private information to a game partner, determines the division of payoffs. Using this set-up in analysing deception has some advantages: First, it allows to clearly isolate an individual’s motivation for (dis)honest behaviour from other possible sources of influence. Second, to my best knowledge this is the first experiment which investigates white lies and black lies in one single setting.
Transcriptional and posttranscriptional regulation contributes to the sex-regulated expression of two sequence-related genes at the janus locus of Drosophila melanogaster

We investigated the structure and developmental pattern of expression of two genes clustered at the janus locus, located at 99D.3R. Data obtained from genomic and cDNA sequencing and from a combination of S1 mapping and primer extension experiments indicated a very unusual organization of this locus, which appeared to be composed of two partially overlapping genes, designated janA and janB. These two genes were found to be transcribed in the same direction. janA encoded one minor and two major transcripts. The 5' end of the janB mRNA mapped within the 3' untranslated region of the janA transcribed sequence. The overlapping region was 118 bases long. Similarities observed between these two genes with respect to both peptidic sequence and intron position strongly suggested that this locus originated from the duplication of an ancestral transcription unit. However, each of the resulting genes has acquired its own specificity of expression linked to sex determination. The janB transcript was detected only in males, and its expression at the adult stage was restricted to germ line cells. The janA gene displayed a much more complex expression; one of the major mRNAs was found in both sexes and at all stages, whereas the two other janA transcripts were expressed only in males.
Antibiotic Resistance: Understanding and Responding to an Emerging Crisis

Interest in the problem of antimicrobial drug resistance was once limited to health care workers and academics. Today, the problem is widespread, and patients are acquiring drug-resistant infections for which there may be no active therapeutic agents. Antimicrobial drug–resistant infections, such as methicillin-resistant Staphylococcus aureus, have spread beyond health care settings and now cause disease, including life-threatening infections, in community settings. The goal of Antibiotic Resistance: Understanding and Responding to an Emerging Crisis by Drlica and Perlin is to explain “how human activities contribute to the problem of resistance. ” The book is intended for “farmers, hospital administrators, government regulators, health department personnel, pharmaceutical executives, and especially individual users” of antibiotics. The book is written in language that readers with a cursory understanding of biology will understand. Readers with little to no biology background can turn to helpful appendixes in the back of the book, where they will find a concise and clear introduction to the Molecules of Life and Microbial Life Forms, which provide the necessary information to tackle antibiotic resistance concepts. The subject matter was not short-changed in the authors’ effort to make it more widely accessible. This book addresses resistance problems in all types of infections: bacterial, viral, parasitic, and fungal. Chapters address diverse issues, including antibiotic drug activity, development, and use; resistance mechanisms and transmission; laboratory detection of resistance; and what we can do to avoid drug-resistant pathogens. The book’s readability is enhanced by the use of text boxes, which provide additional information such as historical antidotes that give depth to the chapter’s topic. For example, in Chapter 3, A Survey of Antibiotics, Box 3-2 recounts how a toxic formulation of sulfa drugs in the late 1937, which killed more than 100 persons, led Congress to pass the Food Drug and Cosmetic Act and to the subsequent creation of the Food and Drug Administration. In addition, each chapter ends with a Perspective section that concisely positions the chapter’s topic in the larger world of humans, animals, pathogens, and drugs. This book fulfills its intended purpose and will serve as an important resource for anyone looking for greater understanding of antibiotics and the problem of drug resistance.
Online Mining of Maximal Frequent Itemsequences from Data Streams

Mining data streams often requires real-time extraction of interesting patterns from dynamic and continuously growing data. This requirement has imposed challenges on discovering and outputting current useful patterns in an instant way, commonly referred to as online streaming data mining. In this paper, we present INSTANT, a novel algorithm that explores maximal frequent itemsequences from streaming data in an online fashion. We first provide useful operators on the lattice of itemsequential sets, and then apply them to the algorithm design of INSTANT. In comparison with the most popular methods such as close-itemset based mining algorithms, INSTANT has solid theoretical foundations to ensure that it employs more compact in-memory data structures than closed itemsequences. Experimental results show that our method can achieve better results than previous related methods in terms of both time and space efficiency.