Skip to content

Category

data science

2,473 papers

#data science Open access Oct 2026

Modelling broiler chicken health and welfare in a changing climate

Agriculture is particularly exposed to climate change, which threatens global food security. To date, climate change impact assessments on future food availability have focussed primarily on crop production. Projections of climate change impacts on livestock are relatively rare, with productivity gains and losses yet t...

Chérie Part · 0 citations
#data science Open access Oct 2026

An investigation of incidental vocabulary learning using English online consumer electronics review with undergraduates of Computer Science (EdD TESOL)

Teaching English vocabulary explicitly is a popular method employed in language classrooms in Taiwan (Chou, 2011). Schmitt (2008) argues that both explicit and incidental learning are necessary for second language vocabulary acquisition and should be seen as complementary. It is generally considered that extensive read...

Chun-Huei Chuo · 0 citations
#data science Open access Oct 2026

What knowledge do social workers use to inform their decision regarding permanency for Looked after Children?

Accurately identifying children at risk of abuse and intervening in ways that will protect them is far from an exact science (Spratt et al. 2015; Fleming et al. 2015) and is made all the harder by the fact that social workers have no unitary knowledge base to draw on to determine their recommendations (Enosh and Bayer-...

Paul McCafferty · 0 citations
#data science Open access Oct 2026

Intervention development, process evaluation and feasibility study of a home and school positive behaviour management programme in Northern Irish pre-school settings

Background Research denotes that problematic child behaviour can impact negatively upon caregiver well-being. Decreased well-being increases use of harsh and punitive discipline measures with such measures exacerbating negative child behaviour, and; thus, negative cycles are created. Evidence suggests that intervention...

Sarah Patterson · 0 citations
#data science Open access Oct 2026

Towards real dynamics in heterogeneous catalysis using machine learning interatomic potential simulations

Heterogeneous catalysis plays a significant role in the modern chemical industry. Computational investigation has been an indispensable approach to reveal catalyst structures and catalytic reactions in the last few decades, where first-principles calculations are widely adopted. Despite the success in understanding cat...

Jiayan Xu · 0 citations
#data science Open access Oct 2026

Developing evidence-based decision making for tooth replacement in partially dentate patients

Objectives:This study aimed to evaluate the effectiveness of different tooth replacement strategies in adult patients with shortened dental arches, including survival rates of prosthodontic interventions, risk of tooth loss and impact on oral-health related quality of life (OHRQoL); to determine the most appropriate to...

Conor McLister · 0 citations
#data science Open access Oct 2026

Invasive species: fundamental and applied science

Management of invasive alien species (IAS) is notoriously difficult, with many examples of expensive, failed attempts. While there is growing consensus that prevention is better than cure, successful prevention requires user-friendly, effective methods to quantify the ecological impacts of established, emerging and fut...

James W. E. Dickey · 0 citations
#data science Open access Oct 2026

Bridging the gap between science and industry: biology, ecology and management of the European eel (Anguilla anguilla L) in Lough Neagh

Fish are among the world’s most important natural resources, providing humans with numerous ecosystem goods and services, including an annual harvest of over 100 million tonnes of wild biomass worldwide. Current evidence suggests that many fish species and stocks are under pressure. The Food and Agriculture Organizatio...

Conor V. Dolan · 0 citations
#data science Open access Oct 2026

Sterilization and post-processing of bioresorbable polymers for cardiovascular stent applications

Cardiovascular diseases are the leading cause of death globally and account for over 30% of deaths each year. Coronary artery disease, the disease of blood vessels supplying the heart, is the most common form of cardiovascular disease, and represents an increasing burden to healthcare worldwide. Bioresorbable polymer s...

Emily Marler Morra · 0 citations
#data science Open access Oct 2026

Sleep disturbances in children with cerebral palsy

Background Sleep plays a prominent role in a child’s development, health, and wellbeing. Approximately 23-46% of children with cerebral palsy (CP) have been found to experience sleep disturbances compared to 5-30% of children without CP. The impact(s) of unresolved sleep disturbances have been found to extend beyond th...

Mary-Elaine McCavert · 0 citations
#data science Open access Oct 2026

A review of psychological interventions in prison populations and exploring Adverse Childhood Experiences (ACEs) as predictors of negative outcomes in 18–25-year-olds

Two studies were completed. The first was a systematic review and meta-analysis to synthesise available quantitative literature on the effectiveness of psychological interventions for targeting co-occurring PTSD and SUD in prison populations. Four databases (Medline, Scopus, Psych INFO and Web of Science) identified N=...

Donna Redmond · 0 citations
#data science Open access Oct 2026

Planet Hunters NGTS: no planet left behind in the Next Generation Transit Survey

In this thesis, I present the Planet Hunters NGTS citizen science project. In this project, we enlist the help of members of the public to visually vet candidates from the Next Generation Transit Survey (NGTS). The aim of this project is to detect planet candidates that were missed in initial searches of these data. By...

Sean O'Brien · 0 citations

From tech blogs

See all →
Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.