Anisotropic dynamics in a shaken granular dimer gas experiment

The dynamics, velocity fluctuations, and particle-plate interactions for a 2D granular gas of shaken, non-spherical particles are studied experimentally. The experiment consists of a horizontal plate that is vertically oscillated to drive the dynamics of macroscopic dimers, spherical pairs that are loosely connected by a rod that couple the interaction each of the spheres has with the shaking plate. The extended nature of the particles results in more than one energy-momentum transfer between the plate and each dimer per shaking cycle. This complex interaction results in anisotropic behavior for the dimer that is a function of the shaking parameters.Comment: 10 pages and 5 figure

Hidden in Plain Sight: Homeless Students In America's Public Schools

Student homelessness is on the rise, with more than 1.3 million homeless students identified during the 2013-14 school year. This is a 7 percent increase from the previous year and more than double the number of homeless students in 2006-07. As high as these numbers seem, they are almost certainly undercounts.Despite increasing numbers, these students - as well as the school liaisons and state coordinators who support them - report that student homelessness remains an invisible and extremely disruptive problem.Students experiencing homelessness struggle to stay in school, to perform well, and to form meaningful connections with peers and adults. Ultimately, they are much more likely to fall off track and eventually drop out of school more often than their non-homeless peers.This study:provides an overview of existing research on homeless students,sheds light on the challenges homeless students face and the supports they say they need to succeed,reports on the challenges adults - local liaisons and state coordinators - face in trying to help homeless students, andrecommends changes in policy and practice at the school, community, state and national level to help homeless students get on a path to adult success.This is a critical and timely topic. The recent reauthorization of the Every Student Succeeds Act (ESSA) provides many new and stronger provisions for homeless students (effective Oct. 1, 2016); requires states, district and schools for the first time to report graduation rates for homeless students (effective beginning with the 2016-17 school year); and affirms the urgency and importance of dealing with homelessness so that all children can succeed

Constructing a Bilingual Hadith Corpus Using a Segmentation Tool

This article describes the process of gathering and constructing a bilingual parallel corpus of Islamic Hadith, which is the set of narratives reporting different aspects of the prophet Muhammad’s life. The corpus data is gathered from the six canonical Hadith collections using a custom segmentation tool that automatically segments and annotates the two Hadith components with 92% accuracy. This Hadith segmenter minimises the costs of language resource creation and produces consistent results independently from previous knowledge and experiences that usually influence human annotators. The corpus includes more than 10M tokens and will be freely available via the LREC repository

Impact of Acute Supraventilation Breathing Technique on Anaerobic Swim Performance in Collegiate Swimmers

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Middlesex University’s Invisque visual analytics tool: supported by text analytics techniques from the University of Leeds

This report describes the joint entry from Middlesex University and the University of Leeds for Mini Challenge 3 for the VAST Challenge 2011. In order to address the challenge question, the primary tool we used was Middlesex University’s Interactive Visual Search and Query Environment (INVISQUE), which served as the user interface to the Mini-Challenge 3 news corpus. INVISQUE was supported by corpus text analytics from the University of Leeds, which provided additional information that was visualised on the INVISQUE user interface

Knowledge representation of the Quran through frame semantics: a corpus-based approach

In this paper, we present our in-progress research tasks for building lexical database of the verb valences in the Arabic Quran using FrameNet frames. We study the verbs in their context in the Quran, and compare that with matching frames and frame evoking verbs in the English FrameNet. We analyze the gaps and make appropriate amendments to the FrameNet by adding new frame elements and relations

An ELISA to Detect Serum Antibodies to the Salivary Gland Toxin of Ixodes holocyclus Neumann in Dogs and Rodents

The Ixodes holocyclus tick causes paralysis in up to 10,000 companion and domestic animals each year in Australia. Treatment requires the removal of the parasite and the administration of a commercial tick antiserum that is prepared from hyperimmune dogs. Each batch of this serum is initially tested for toxin-neutralising potency in a mouse bioassay that is expensive, time consuming, and subjective. With the aim of developing a rapid in vitro assay to replace the bioassay, we used a partially purified antigen prepared from I. holocyclus salivary glands to develop an ELISA to detect toxin-reactive antibodies in hyperimmune dog sera. The optimised ELISA reliably detected antibodies reactive to I. holocyclus salivary gland antigens. Parallel testing of sera with a negative control antigen prepared from the salivary glands of the nontoxic tick Rhipicephalus (Boophilus) microplus provided further evidence that we were detecting toxin-specific antibodies in the assay. Using the ELISA, we could also detect antibodies induced in rats after experimental infestation with I. holocyclus. This assay shows promise as an alternative means of assessing the potency of batches of hyperimmune dog serum and to screen for toxin-reactive monoclonal antibodies produced from immunised rodents

SCUoL at CheckThat! 2022: Fake News Detection Using Transformer-Based Models

The fifth edition of the "CheckThat! Lab" is one of the 2022 Conference and Labs of the Evaluation Forum (CLEF) and aims to evaluate advances supporting three factuality-related tasks, covering several languages. Our team (SCUoL) participated in task 3A, which concentrates on multi-class fake news detection of English news articles. This paper describes our approach, including several experiments exploring different machine learning and transformer-based models. Furthermore, we employed an additional dataset to support our proposed model. During the validation results phase, the experiments highlight the best performing machine learning classifier, which achieved cross-validation scores of over 60% for the LinearSVC compared to the pre-trained BERT model that exceeds other models in this task. While in the testing results, we obtained an F1 of approximately 0.305 compared to the other participants’ average F1 of 0.252

SCUoL at CheckThat! 2021: An AraBERT model for check-worthiness of Arabic tweets

Many people nowadays tend to explore social media to obtain news and find information about various events and activities. However, an abundance of misleading and false information is spreading every day for many purposes, dramatically impacting societies. Therefore, it is vitally important to identify false information on social media to help individuals distinguish the truth and protect communities from the harmful effects of false information. For this reason, determining which information has the priority to be scrutinized is a significant prior step that several studies have considered. In this paper, we have addressed Subtask-1A(Arabic) of CLEF2021 CheckThat! Lab. We have done that in two steps. The first involved pre-processing the provided dataset with text segmentation and tokenization. In the second step, we implemented different models on the Arabic tweets in order to binary classify them according to whether a specific tweet is worth being considered for fact-checking or not. We mainly compared two versions of the pre-trained AraBERT model with some of the traditional word encoding methods, including the Linear SVC model with TF-IDF. The results indicate that the AraBERTv2 version outperforms the other models. Consequently, we used it for our final submission, and we were ranked third among eight other participating teams