The assessment of disability-related costs among children remains a largely under-researched subject with related questions rarely included in surveys. This paper addresses this issue through a unique mixed methods study conducted in the Philippines combining a nationally representative survey and in-depth interviews with families and health professionals. To quantify the extra costs associated with disabilities, the research used the standard of living approach, whereby expenditure levels of families with children with and without disabilities were compared in relation to different measures of living standards. The results find consistent evidence of high extra costs among households that have children with disabilities and point to health expenses as the leading source. Using an asset index as the indicator of living standards, a child with a disability is estimated to require between 40% and 80% extra expenditure to reach the same living standard of other children. However, the size of extra costs is substantially higher when the measure of the standard of living relies on a broader set of deprivations. In such cases, higher estimates of extra costs are likely to be the result of the lack of an inclusive environment. Critically, this points to the need to provide not only financial support but also inclusive services, especially in health and education.
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http://dx.doi.org/10.3390/ijerph20136304 | DOI Listing |
Sensors (Basel)
January 2025
School of Biomedical Engineering and Imaging Sciences, King's College London, London SE1 7EH, UK.
Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecting image quality and reproducibility. Robot-assisted ultrasound may provide a solution by delivering more consistent, precise, and faster scans, potentially reducing human error and healthcare costs. Effective force control is crucial in robotic ultrasound scanning to ensure consistent image quality and patient safety.
View Article and Find Full Text PDFSci Rep
January 2025
College of Mechanical Engineering, Anhui Institute of Information Technology, Wuhu, 241199, Anhui, China.
To address the challenge of accurately capturing tool wear states in small sample scenarios, this paper proposes a tool wear prediction method that combines XGBoost feature selection with a PSO-BP network. In order to solve the problem of input feature selection and parameter selection in BP neural network, a double-layer programming model of input feature and parameter selection is established, which is solved by XGBoost and PSO. Initially, vibration and cutting force signals from CNC machining are preprocessed using time-domain segmentation, Hampel filtering, and wavelet denoising.
View Article and Find Full Text PDFBioengineering (Basel)
January 2025
School of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.
Breast cancer ranks as the second most prevalent cancer globally and is the most frequently diagnosed cancer among women; therefore, early, automated, and precise detection is essential. Most AI-based techniques for breast cancer detection are complex and have high computational costs. Hence, to overcome this challenge, we have presented the innovative LightweightUNet hybrid deep learning (DL) classifier for the accurate classification of breast cancer.
View Article and Find Full Text PDFGenome Biol Evol
January 2025
Department of Molecular and Cell Biology, University of California-Merced, Merced, CA 95343.
Eukaryotic genome size varies considerably, even among closely related species. The causes of this variation are unclear, but weak selection against supposedly costly "extra" genomic sequences has been central to the debate for over 50 years. The mutational hazard hypothesis, which focuses on the increased mutation rate to null alleles in superfluous sequences, is particularly influential, though challenging to test.
View Article and Find Full Text PDFCureus
December 2024
Zebrafish Research Unit, Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed-to-be-University), Pondicherry, IND.
Low- and middle-income countries (LMICs) are increasingly challenged by the rising burden of medicolegal cases. Traditional forensic infrastructure and in vivo rodent models often have significant limitations due to high costs and ethical concerns. As a result, zebrafish () are gaining popularity as an attractive alternative model for LMICs because of their cost-effectiveness and practical advantages.
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