Post-injury fear-avoidance and confidence in readiness to return to sport in Irish collegiate athletes.

Fear avoidance and low confidence in their ability to return to sport can impede athletes' subsequent recovery and return to sport. This study aimed to identify fear avoidance and confidence in readiness to return to sport following injury in Irish collegiate athletes. Male (416) and female (256) athletes from 24 field-sport teams at one university were prospectively followed for one season.

Comparison of impact accelerations between injury-resistant and recently injured recreational runners.

Introduction/purpose: Previous injury has consistently been shown to be one of the greatest risk factors for running-related injuries (RRIs). Runners returning to participation following injury may still demonstrate injury-related mechanics (e.g.

Real-Time Anomaly Detection for an ADMM-Based Optimal Transmission Frequency Management System for IoT Devices.

In this paper, we investigate different scenarios of anomaly detection on decentralised Internet of Things (IoT) applications. Specifically, an anomaly detector is devised to detect different types of anomalies for an IoT data management system, based on the decentralised alternating direction method of multipliers (ADMM), which was proposed in our previous work. The anomaly detector only requires limited information from the IoT system, and can be operated using both a mathematical-rule-based approach and the deep learning approach proposed in the paper.

DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text.

This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments in Tamil-English, around 7000 comments in Kannada-English, and around 20,000 comments in Malayalam-English.

Spatially coherent modeling of 3D FDG-PET data for assessment of intratumoral heterogeneity and uptake gradients.

Radiomics have become invaluable for non-invasive cancer patient risk prediction, and the community now turns to exogenous assessment, e.g., from genomics, for interpretability of these agnostic analyses.

Multilingual hope speech detection in English and Dravidian languages.

Recent work on language technology has aimed to identify negative language such as hate speech and cyberbullying as well as improve offensive language detection to mediate social media platforms. Most of these systems rely on using machine learning models along with the labelled dataset. Such models have succeeded in identifying negativity and removing it from the platform deleting it.

Hope speech detection in YouTube comments.

Recent work on language technology has tried to recognize abusive language such as those containing hate speech and cyberbullying and enhance offensive language identification to moderate social media platforms. Most of these systems depend on machine learning models using a tagged dataset. Such models have been successful in detecting and eradicating negativity.

A qualitative examination of the factors affecting the adoption of injury focused wearable technologies in recreational runners.

Purpose: Understanding the perceived efficacy and ease of use of technologies will influence initial adoption and sustained utilization. The objectives of this study were to determine the metrics deemed important by runners for monitoring running-related injury (RRI) risk, and identify the facilitators and barriers to their use of injury focused wearable technologies.

Methods: A qualitative focus group study was undertaken.

Neuroergonomic assessment of developmental coordination disorder.

Until recently, neural assessments of gross motor coordination could not reliably handle active tasks, particularly in realistic environments, and offered a narrow understanding of motor-cognition. By applying a comprehensive neuroergonomic approach using optical mobile neuroimaging, we probed the neural correlates of motor functioning in young people with Developmental Coordination Disorder (DCD), a motor-learning deficit affecting 5-6% of children with lifelong complications. Neural recordings using fNIRS were collected during active ambulatory behavioral task execution from 37 Typically Developed and 48 DCD Children who performed cognitive and physical tasks in both single and dual conditions.

The fading impact of lockdowns: A data analysis of the effectiveness of Covid-19 travel restrictions during different pandemic phases.

As countries struggled with SARS-COV2 outbreaks at the beginning of 2021, many citizens found themselves in yet another period of increasing travel restrictions, if not a strict lockdown. At the same time there was concern that further restrictions would prove to be less effective due to a range of reasons including increasing pandemic fatigue or the lack of appropriate supports. In this study we investigate whether restrictions remained effective as a way to limit non-essential travel in order to curb virus transmission.

Relative and absolute reliability of shank and sacral running impact accelerations over a short- and long-term time frame.

Whilst running is hugely popular, running-related injuries (RRIs) are prevalent. High impact loading has been proposed to contribute to RRIs, with accelerometers becoming increasingly popular in estimating segmental loading for injury detection and biofeedback training. However, there is a lack of research examining the reliability of measures of impact acceleration across short- and long-term time periods, both prior to and following exerted running.

Musculoskeletal Injury in Referees That Officiate Over Ladies Gaelic Football and Camogie.

Aim Ladies Gaelic football and Camogie are leading female sports in Ireland. Referees are essential to the game, however, no research has examined injury in referees that officiate over female Gaelic games to date. Therefore, this study aims to retrospectively examine the musculoskeletal injury profile and injury prevention practices of referees that officiate over female Gaelic games.

Privacy-aware sharing and collaborative analysis of personal wellness data: Process model, domain ontology, software system and user trial.

Personal wellness data collected using wearable devices is a valuable resource, potentially containing knowledge that goes beyond what the device and its the associated software application can tell the user. However, extracting such knowledge from the data requires expertise that an average user cannot be expected to have. To overcome this problem, the data owner could collaborate with a data analysis expert; for such a collaboration to succeed, the collaborators need to be able to find one another, communicate with one another and share datasets and analysis results with one another.

A multi-source entity-level sentiment corpus for the financial domain: the FinLin corpus.

Unlabelled: We introduce FinLin, a novel corpus containing investor reports, company reports, news articles, and microblogs from StockTwits, targeting multiple entities stemming from the automobile industry and covering a 3-month period. FinLin was annotated with a sentiment score and a relevance score in the range [- 1.0, 1.

Assessment and classification of peripheral pain in athletes: a scoping review protocol.

Pain is often presumed to be part of the sport injury experience. The time-loss definition of injury leads to under-reported athletic pain impacting performance and quality of life. Whilst research regarding the assessment and classification of back pain in athletes is emerging, little has been reported regarding how peripheral pain is assessed and classified in research and practice.

Denoising EEG Signals for Real-World BCI Applications Using GANs.

As a measure of the brain's electrical activity, electroencephalography (EEG) is the primary signal of interest for brain-computer-interfaces (BCI). BCIs offer a communication pathway between a brain and an external device, translating thought into action with suitable processing. EEG data is the most common signal source for such technologies.

Correction: Collaboration in the time of COVID: a scientometric analysis of multidisciplinary SARS-CoV-2 research.

[This corrects the article DOI: 10.1057/s41599-021-00922-7.].

TGMD-3 short version: Evidence of validity and associations with sex in Irish children.

This study examined the internal structure and evidence of validity of the Test of Gross Motor Development 3 edition (TGMD-3) in primary school aged children. Participants (n = 1608, 47% girls, age range 5-11 years, mean age 9.2 ± 2.

A Survey of Orthographic Information in Machine Translation.

Machine translation is one of the applications of natural language processing which has been explored in different languages. Recently researchers started paying attention towards machine translation for resource-poor languages and closely related languages. A widespread and underlying problem for these machine translation systems is the linguistic difference and variation in orthographic conventions which causes many issues to traditional approaches.

Estimating Exposure Risk to Guide Behaviour During the SARS-COV2 Pandemic.

The end of 2020 and the beginning of 2021 was a challenging time for many countries in Europe, as the combination of colder weather, holiday celebrations, and the emergence of more transmissible virus variants conspired to create a perfect storm for virus transmission across the continent. At the same time lockdowns appeared to be less effective than they were earlier in the pandemic. In this paper we argue that one contributing factor is that existing ways of communicating risk-case numbers, test positivity rates, hospitalisations etc.

Translational Application of 3D Bioprinting for Cartilage Tissue Engineering.

Cartilage is an avascular tissue with extremely limited self-regeneration capabilities. At present, there are no existing treatments that effectively stop the deterioration of cartilage or reverse its effects; current treatments merely relieve its symptoms and surgical intervention is required when the condition aggravates. Thus, cartilage damage remains an ongoing challenge in orthopaedics with an urgent need for improved treatment options.

Longer Disciplined Tapers Improve Marathon Performance for Recreational Runners.

For marathoners the taper refers to a period of reduced training load in the weeks before race-day. It helps runners to recover from the stresses of weeks of high-volume, high-intensity training to enhance race-day performance. The aim of this study was to analyse the taper strategies of recreational runners to determine whether particular forms of taper were more or less favorable to race-day performance.

Visualising household air pollution: Colorimetric sensor arrays for monitoring volatile organic compounds indoors.

Indoor air quality monitoring as it relates to the domestic setting is an integral part of human exposure monitoring and health risk assessment. Hence there is a great need for easy to use, fast and economical indoor air quality sensors to monitor the volatile organic compound composition of the air which is known to be significantly perturbed by the various source emissions from activities in the home. To meet this need, paper-based colorimetric sensor arrays were deployed as volatile organic compound detectors in a field study aiming to understand which activities elicit responses from these sensor arrays in household settings.

Estimation of Continuous Blood Pressure from PPG via a Federated Learning Approach.

Ischemic heart disease is the highest cause of mortality globally each year. This puts a massive strain not only on the lives of those affected, but also on the public healthcare systems. To understand the dynamics of the healthy and unhealthy heart, doctors commonly use an electrocardiogram (ECG) and blood pressure (BP) readings.

Developing On-Site Trace Level Speciation of Lead, Cadmium and Zinc by Stripping Chronopotentiometry (SCP): Fast Screening and Quantification of Total Metal Concentrations.

Electrochemical stripping techniques are interesting candidates for carrying out onsite speciation of environmentally relevant trace metals due to the existing low-cost portable instrumentation available and the low detection limits that can be achieved. In this work, we describe the initial analytical technique method development by quantifying the total metal concentrations using Stripping Chronopotentiometry (SCP). Carbon paste screen-printed electrodes were modified with thin films of mercury and used to quantify sub-nanomolar concentrations of lead and cadmium and sub-micromolar concentrations of zinc in river water.