CORA
Cork Open Research Archive (CORA) is UCC’s Open Access institutional repository which enables UCC researchers to make their research outputs freely available and accessible.
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Buntús Cainte – Caoga bliain ag fás
(Education Matters, 2017) Hyland, Áine; Mooney, Brian
1967 was an auspicious year for Irish education. It was the year of the introduction of free post-primary education and of free transport to post-primary schools. It was also the year of the publication of the first edition of Buntús Cainte, a graded course in Irish for beginners, written by my father, Tomás Ó Domhnalláin. Fifty years later, Buntús Cainte continues to enjoy unprecedented popularity. It has been reprinted regularly – most recently in 2017 – and millions of copies of the book have been sold since its first publication in 1967. It is probably the most popular Irish language course ever produced.
Back in the RACE: (Re)defining the role of radiation therapy in liver and gallbladder cancers
(Elsevier Inc., 2025-08-13) Barry, Aisling S.; Ashman, Jonathan B.; Jethwa, Krishan R.; Kim, Hyun; Miller, Eric D.; Tao, Randa; Wojcieszynski, Andrzej P.; Chuong, Michael D.
This Oncology Scan focuses on expanding the role of radiation therapy (RT) for primary liver and gallbladder (GB) cancers, which are complex and require specialized multidisciplinary involvement. The role of RT continues to evolve for these cancers, and enthusiasm for routine use of RT has lagged behind other loco-regional therapies. Advances in technology, including motion management, image guidance, and treatment conformality, have improved the therapeutic ratio of RT and have achieved favorable clinical outcomes, demonstrating that RT should be a standard of care for liver and GB cancers. For example, RT was recently included for the first time as a reasonable option for liver cancer in the updated 2025 European Association for the Study of the Liver clinical practice guidelines.
Protein quality in consumer products and diets
(CRC Press, 2025-07-31) Shkembi, Blerina; Huppertz, Thom
Although dietary recommendations focus primarily on quantitative protein intake, protein quality is critical to consider as well. Large differences in dietary protein intake are observed globally, with diets dominated by plant protein sources typically being poorer in quality. This can be attributed to the less favorable amino acid composition and lower digestibility of plant proteins. The latter is related both to protein structure and to the presence of anti-nutritional compounds, such as trypsin inhibitors, tannins, and phytates in some products. Food processing can also notably affect protein quality. Glycation of lysine residues in proteins, resulting from the Maillard reaction with reducing carbohydrates, can significantly reduce protein quality, whereas processing-induced denaturation and aggregation of proteins can both improve and reduce protein quality. Processing-induced inactivation of trypsin inhibitors and removal of tannins and phytates can improve protein quality, but care should be taken that such processing does not cause negative impacts via, for example, protein glycation. Overall, dietary protein quality is an intricate balance that should be considered at a consumer product level, rather than the raw material or protein ingredient level. Consideration of dietary protein quality at a meal level is essential to account for the complementarity of protein sources.
150 years of science education in Irish secondary schools
(International Council of Associations for Science Education, 2025) Hyland, Áine
This paper provides an overview of science education in Irish secondary schools over the past 150 years. It describes how the science curriculum developed over the decades as scientific discoveries were made. Until the middle of the 20th century the secondary school curriculum was biased in favour of the humanities but since the 1960s, science and technology have played a central role in Irish secondary education.
Advance ANN algorithm and research challenges for breast cancer detection and classification with evaluation Ni LabVIEW
(Institute of Electrical and Electronics Engineers (IEEE), 2025-07-15) Haider, Natasha; Jabeen Mazhar, Iqra; Haider, Shehpara; Ghazanfar, Jawaria; Muhammad Zohaib, Malik; Haider, Zarrar
Machine learning and digital image processing are hot emerging technologies which have garnered a lot attention for the past few decades because of promising results in multi fields like electronics, medical, communication and vision. Deep learning which is subclass, has been used for the classification for the natural images has gained a lot of research interest among biomedical researchers for better estimation of medical diagnosis. In this research paper, we developed and implemented a deep learning algorithms with image processing for detection of breast cancer in the early stage using by utilization of the algorithms in X-ray mammograms images during diagnosis. The information parameters include background tissues, abnormality, severity of classes, and etc. The algorithm utilized neural network for the model training and implementation performed in LabVIEW NI vision toolkit. The proposed algorithm performed better results and promising with excessive training of the images. Finally, we proposed novel research challenges and open problems in this area which requires further research and investigation by researchers.