21 research outputs found
The surprisingly large policy implications of changing retirement durations
No full textThe paper reviews evidence that suggests that, over the coming two decades, people are likely to stay in the work force at least five years longer, possibly by considerably more. The implications for policy are surprisingly large and surprisingly unrecognized. Recent trends, if extended into the future, suggest that changes of this magnitude are quite likely given a continuation of past labour market conditions. However, these past trends do not reflect new pressures that will work strongly in the direction of even shorter durations of retirement and longer durations of work. These new pressures will result from changes in labour supply and demand that will result from the baby boom generation moving into traditional retirement years in large numbers, increasing the demand for older workers. On the supply side, there will be a large in increase in the educational levels and skills of older people. The effect of market forces could be further enhanced by policy action. In other words, a five year extension of working life is the minimum that should be included in most future labour market scenarios. Delaying work-retirement transitions by even this amount would have large, positive economic and fiscal effects, significantly reducing the well-known negative effects of population ageing. They would have particularly important consequences for pension policy, with a dramatic reduction in the need for retirement savings and, particularly if accompanied by flexible work-toretirement pathways, would reduce the risk of changed income needs in old age. A range of other social benefits, including greater individual choice and well-being, also seem likely – if harder to quantify. However, as with any large social change, distributional consequences are inevitable. A few groups could be relatively worse off in a world where the norm was for work to be extended later in life. In the absence of strategy for addressing the needs of these potential losers, there may well be reluctance to take policy action, despite the likelihood of large gains for most, and on many fronts.Income replacement, pension systems, pensions, retirement, retirement age, life expectancy, older workers, aging, Canada, projections, public policy
The challenges of entering the metaverse : An experiment on the effect of extended reality on workload
No full textInformation technologies exist to enable us to either do things we have not done before or do familiar things more efficiently. Metaverse (i.e. extended reality: XR) enables novel forms of engrossing telepresence, but it also may make mundate tasks more effortless. Such technologies increasingly facilitate our work, education, healthcare, consumption and entertainment; however, at the same time, metaverse bring a host of challenges. Therefore, we pose the question whether XR technologies, specifically Augmented Reality (AR) and Virtual Reality (VR), either increase or decrease the difficulties of carrying out everyday tasks. In the current study we conducted a 2 (AR: with vs. without) × 2 (VR: with vs. without) between-subject experiment where participants faced a shopping-related task (including navigating, movement, hand-interaction, information processing, information searching, storing, decision making, and simple calculation) to examine a proposed series of hypotheses. The NASA Task Load Index (NASA-TLX) was used to measure subjective workload when using an XR-mediated information system including six sub-dimensions of frustration, performance, effort, physical, mental, and temporal demand. The findings indicate that AR was significantly associated with overall workload, especially mental demand and effort, while VR had no significant effect on any workload sub-dimensions. There was a significant interaction effect between AR and VR on physical demand, effort, and overall workload. The results imply that the resources and cost of operating XR-mediated realities are different and higher than physical reality.© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
No full textPerilla seed meal (PSM), a byproduct of oil extraction from Perilla frutescens L. seeds, is rich in protein (24.26–42.85%) and holds potential as an economical and sustainable animal feed. Traditional methods for assessing protein content are labor-intensive and costly. This study explores Near-Infrared Reflectance Spectroscopy (NIRS) for the rapid, precise, and non-destructive determination of PSM protein content in 126 samples. We developed and evaluated Modified Partial Least Squares (MPLS) regression and deep learning (DL) models, including 1D-CNN (Convolutional Neural Network), LSTM Long Short-Term Memory), and hybrid architectures incorporating skip connections, inception modules, and spectral derivatives. Model performance was validated externally using parameters such as RSQexternal (R-squared), bias, SEP(C) (Standard Error of Prediction), RPD (Residual Prediction Deviation), slope, SD (Standard Deviation), p-value (≥0.05), and the correlation between reference and predicted values. The 1D CNN-LSTM-Inception derivative 1 model achieved the best performance (RPD: 8.0, RSQexternal: 0.98), followed by the MPLS-based model (RPD: 4.88, RSQexternal: 0.96) and the 1D CNN derivative 1 model (RPD: 3.07, RSQexternal: 0.96). These models provide a reliable and advanced technology for the non-destructive screening of PSM protein content, thus aiding in the rapid identification and selection of superior perilla chemotypes from varied backgrounds
Hepatic Hydrothorax without Any Evidence of Ascites
No full textHepatic hydrothorax usually presents in association with ascites, but there are rare cases when it does not. This case helps to support the differential of hepatic hydrothorax in patients who have a history of liver cirrhosis, portal hypertension, and recurrent pleural effusions without ascites. We hope to support the conclusion that a patient with recurrent pleural effusions, without ascites, does not exclude gastrointestinal involvement in its etiology
Hepatic Hydrothorax without Any Evidence of Ascites
No full textHepatic hydrothorax usually presents in association with ascites, but there are rare cases when it does not. This case helps to support the differential of hepatic hydrothorax in patients who have a history of liver cirrhosis, portal hypertension, and recurrent pleural effusions without ascites. We hope to support the conclusion that a patient with recurrent pleural effusions, without ascites, does not exclude gastrointestinal involvement in its etiology
Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
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