Using word embeddings in Twitter election classification

Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification. However, the effect of the configuration used to generate the word embeddings on the classification performance has not been studied in the existing literature. In this paper, using a Twitter election classification task that aims to detect election-related tweets, we investigate the impact of the background dataset used to train the embedding models, as well as the parameters of the word embedding training process, namely the context window size, the dimensionality and the number of negative samples, on the attained classification performance. By comparing the classification results of word embedding models that have been trained using different background corpora (e.g. Wikipedia articles and Twitter microposts), we show that the background data should align with the Twitter classification dataset both in data type and time period to achieve significantly better performance compared to baselines such as SVM with TF-IDF. Moreover, by evaluating the results of word embedding models trained using various context window sizes and dimensionalities, we find that large context window and dimension sizes are preferable to improve the performance. However, the number of negative samples parameter does not significantly affect the performance of the CNN classifiers. Our experimental results also show that choosing the correct word embedding model for use with CNN leads to statistically significant improvements over various baselines such as random, SVM with TF-IDF and SVM with word embeddings. Finally, for out-of-vocabulary (OOV) words that are not available in the learned word embedding models, we show that a simple OOV strategy to randomly initialise the OOV words without any prior knowledge is sufficient to attain a good classification performance among the current OOV strategies (e.g. a random initialisation using statistics of the pre-trained word embedding models).     

The Invisible Scholar: Authors of Legal Scholarship in Criminology and Criminal Justice Journals

This study assesses the authorship of legal scholarship within 20 criminology and criminal justice (CCJ) journals from 2005 to 2015, examining trends over time and variation across journals in the prevalence of sole-authorship and the mean number of authors and identifying the most prolific authors of legal scholarship published in CCJ journals. The study thus sheds light on the extent of collaboration among CCJ legal scholars and identifies CCJ legal scholars who have remained largely invisible due to their focus on a marginalized subfield.     

The role of special schools for children with profound and multiple learning difficulties: is segregation always best?

The education of young people with profound and multiple learning difficulties continues to raise challenges and controversies. In this article, Ben Simmons, an ESRC funded PhD student and research assistant, and Phil Bayliss, programme director for the masters degree in special education and disability, both based in the School of Education and Lifelong Learning at the University of Exeter, describe their research into provision for pupils with profound and multiple learning difficulties in a special school in the south west of England. Their work, based in an interpretivist, qualitative approach, set out to illuminate issues relating to the inclusion of pupils with profound and multiple learning difficulties. The findings presented here suggest that the school, in spite of its strong reputation, struggled significantly to provide appropriate learning experiences for pupils with profound and multiple learning difficulties. Ben Simmons and Phil Bayliss discuss the need for improved staff development opportunities focused on enhancing current levels of knowledge and skills. They conclude by calling for a reappraisal of the established view that special schools necessarily provide the best learning environment for pupils with profound and multiple learning difficulties.     

Narrative accounts of US teachers' collaborative curriculum making in a physical education department

Through the use of narrative inquiry, this research study explores the collaborative curriculum making experiences of six teachers (three males; three females) in one physical education (PE) department in an urban middle school in the U.S. Collaboration; as defined in this work, this has to do with teachers’ voluntary interactions and their shared decision making in support of common goals. Where curriculum making is concerned, it refers to interactions between and among the four commonplaces of curriculum (teacher, learner, subject matter, milieu). The paper features the perspectives of the department head (female), experienced teachers (male and female) and teachers new to the profession (male and female). The narrative accounts of the individual teachers are set against the backdrop of the PE department with which they identify and within the storied history of the school in which they work. The story constellations representational form conveys the interrelatedness of the narratives and instantiates the teachers’ experiences of collaborative curriculum making. In the final analysis, this research enterprise makes a major contribution to the study of PE as well as to education generally. To date, no inquiries have focused on the collaborative curriculum making of teachers lodged in a PE department in one school context, despite collaborative curriculum making most closely reflecting how PE teachers typically approach the teaching task due to shared classrooms/gymnasiums/fields and the communal use of equipment.     

Thermally multiplexed polymerase chain reaction

Amplification of multiple unique genetic targets using the polymerase chain reaction (PCR) is commonly required in molecular biology laboratories. Such reactions are typically performed either serially or by multiplex PCR. Serial reactions are time consuming, and multiplex PCR, while powerful and widely used, can be prone to amplification bias, PCR drift, and primer-primer interactions. We present a new thermocycling method, termed thermal multiplexing, in which a single heat source is uniformly distributed and selectively modulated for independent temperature control of an array of PCR reactions. Thermal multiplexing allows amplification of multiple targets simultaneously—each reaction segregated and performed at optimal conditions. We demonstrate the method using a microfluidic system consisting of an infrared laser thermocycler, a polymer microchip featuring 1 μl, oil-encapsulated reactions, and closed-loop pulse-width modulation control. Heat transfer modeling is used to characterize thermal performance limitations of the system. We validate the model and perform two reactions simultaneously with widely varying annealing temperatures (48 °C and 68 °C), demonstrating excellent amplification. In addition, to demonstrate microfluidic infrared PCR using clinical specimens, we successfully amplified and detected both influenza A and B from human nasopharyngeal swabs. Thermal multiplexing is scalable and applicable to challenges such as pathogen detection where patients presenting non-specific symptoms need to be efficiently screened across a viral or bacterial panel.     

Mindfulness‐Based Awareness and Compassion: Predictors of Counselor Empathy and Anxiety

Mindfulness‐based awareness and compassion were examined as predictors of empathy and anxiety among 152 master's‐level counseling interns. Results of hierarchical multiple regression analysis supported that awareness and compassion differentially contributed to explaining the variance in counselor empathy and anxiety. Implications for counselor education are discussed.     

Preschoolers modulate contrastive inferences during online language comprehension

This study examined 4- and 5-year-olds' incremental interpretation of size adjectives, focusing on whether contrastive inferences are modulated by speaker behavior. Children (N = 120, 59 females, mostly White, tested between July, 2018 and August, 2019) encountered either a conventional or unconventional speaker who labeled objects in a correspondingly typical or atypical way. Critical utterances contained size adjectives (e.g., “Look at the big duck”). With conventional speakers, gaze measures indicated that children rapidly used the adjective to differentiate members of a contrasting pair, indicating that even 4-year-olds derive contrastive inferences. With unconventional speakers, contrastive inferences were delayed in processing. The findings demonstrate that preschoolers adjust their use of pragmatic cues when presented with evidence disconfirming their default assumptions about a speaker.     

Four requirements for digital case study libraries

In education, case studies have been employed as a major pedagogical means to engage students with realistic materials and practical problems. The usefulness and success of case studies have been documented in literature. In this paper, we move the case study and its technical affordance a step further toward more authentic or realistic learning and toward communities of practice. Drawing on current intellectual achievement in education, developmental psychology and computer-supported collaborative learning, this paper proposes four requirements for interactive case study libraries, focusing on authentic learning, social interaction, resource accumulation, and communities of practice. With a usability engineering case study library as an example, we discuss design concerns derived from these requirements as well as its use in practice.     

Modern dietary guidelines for healthy pregnancy; maximising maternal and foetal outcomes and limiting excessive gestational weight gain

Abstract

Maternal dietary habits influence maternal and foetal health, representing a pathway for intervention to maximise pregnancy outcomes. Advice on energy intake is provided on a trimester basis, with no additional calories required in the first trimester and an additional 340?kcal?d^?1 and 452?kcal?d^?1 needed for the second and third trimesters. Energy intake depends on pre-gravid body mass index (BMI); underweight women are recommended an increase of 150, 200 and 300?kcal?d^?1 during the first, second and third trimester, normal weight women an increase of 0, 350 and 500?kcal?d^?1 and obese women an increase of 0, 450 and 350?kcal?day^?1. The recommendations for carbohydrate and protein intake are 175?g?d^?1 and 0.88–1.1?g?kgBM?d^?1, with no change to fat intake. The number of pre-gravid obese women is rising; therefore, we need to regulate weight in women of childbearing age and limit gestational weight gain to within the recommended ranges [overweight women 6.8–11.3?kg and obese women 5.0–9.1?kg]. This can be achieved using nutritional interventions, as dietary changes have been shown to help with gestational weight management. As pregnancy has been identified as a risk factor for the development of obesity, normal weight women should gain 11.5–16.0?kg during pregnancy. While some research has shown that dietary interventions help to regulate gestational weight gain and promote postpartum weight loss to some extent, future research is needed to provide safe and effective guidelines to maximise these effects, while benefitting maternal and foetal health.