557 research outputs found
Implicitly estimating the cost of mental illness in Australia: a standard-of-living approach
Background
Estimating the costs of mental illness provides useful policy and managerial information to improve the quality of life of people living with a mental illness and their families.
Objective
This paper estimates the costs of mental health in Australia using the standard-of-living approach.
Methods
The cost of mental illness was estimated implicitly using a standard of living approach. We analyse data from 16 waves of the Household, Income and Labour Dynamics in Australia Survey (HILDA) using 209,871 observations. Unobserved heterogeneity was mitigated using an extended random-effects estimator.
Results
The equivalised disposable income of people with mental illness, measured by a self-reported mental health condition, needs to be 50% higher to achieve a similar living standard as those without a mental illness. The cost estimates vary considerably with measures of mental illness and standard of living. An alternative measure of mental illness using the first quintile of the SF-36 mental health score distribution resulted in an increase of estimated costs to 80% equivalised disposable income.
Conclusion
People with mental illness need to increase equivalised disposable income, which includes existing financial supports, by 50%-80% to achieve a similar level of financial satisfaction as those without a mental illness. The cost estimate can be substantially higher if the overall life satisfaction is used to proxy for standard of living
Estimating the cost of mental illness in Australia: a standard of living approach
This paper estimates the costs of mental health in Australia using the standard-of-living approach. We analyse data from the Household, Income and Labour Dynamics in Australia Survey using an extended random-effects estimator. To the best of our knowledge, this is the first study to examine the cost of mental illness in Australia using the standard of living approach with a nationally representative longitudinal data set. Results from the main specification show that people with a mental illness need to increase their equivalised disposable income by 50% to achieve a similar living standard as those without a mental illness. The cost estimates vary considerably with measures of mental illness and standard of living. An alternative measure of mental illness using the first quintile of the SF-36 mental health score distribution resulted in an increase of estimated costs to 80% equivalised disposable income
Improvement of Step Tracking Algorithm Used for Mobile Receiver System via Satellite
In the mobile communication via satellite, received systems are mounted on the mobile device such as ship, train, car or airplane. In order to receive continuous signals, received antenna system must be steered in both the azimuthal and elevation angle to track a satellite. This paper proposes the improved step-tracking algorithm using for mobile receiver system via satellite Vinasat I. This paper also presents the results of study, design and manufacture of the discrete-time controller system for the fast tracking of a satellite by applying an improved step tracking algorithm with fuzzy proportional integral derivative proportional integral derivative controller. Simulated and experimental results indicate that the system performances obtain from applying the improved step tracking algorithm and the fuzzy controller was better than traditional control systems
Groundwork-Based Research to Design Application SCC - Building a Sustainable Community for Children in Mountainous Area
Children’s clothing is a prime example of fast fashion, as their continuous growth requires frequent purchases. This not only impacts the environment but also puts financial strain on parents. Concurrently, many highland children lack essential material and educational resources, contributing to poverty in the region. To address these challenges, local authorities urgently require a sustainable solution that supports children, communities, and localities, fostering comprehensive development. The project development criteria are evaluated based on the United Nations’ 17 sustainable development goals (SDGs). Data was collected through an online survey of 50 married individuals, 162 non-married individuals, and interviews with those who have organized events for children in the highlands. Additionally, insights were obtained from three children from disadvantaged areas. The results indicate that all target groups show a keen interest in social activities for children. Parents facing difficulties accessing charities, and the lack of effective collaboration between charities and local authorities, hinders sustainable development efforts.
Keywords: children, SDG, social sustainabilty, communit
Adjusting for inflation and currency changes within health economic studies
Objectives: Within health economic studies, it is often necessary to adjust costs obtained from different time periods for inflation. Nevertheless, many studies do not report the methods used for this in sufficient detail. In this article, we outline the principal methods used to adjust for inflation, with a focus on studies relating to healthcare interventions in low- and middle-income countries. We also discuss issues relating to converting local currencies to international dollars and US or international dollars and then inflating using US inflation rates (method 1); inflating the local currency using local inflation rates and then exchanging to US100 incurred in Vietnam from 2006 to 2016 prices, the adjusted cost from the 3 methods were US172.09, and US$161.04, respectively. Conclusions: The different methods for adjusting for inflation can yield substantially different results. We make recommendations regarding the most appropriate method for various scenarios. Moving forward, it is vital that studies report the methodology they use to adjust for inflation more transparently
Design of a Front-End for Satellite Receiver
This paper focuses on the design and implementation of a front-end for a Vinasat satellite receiver with auto-searching mechanism and auto-tracking satellite. The front-end consists of a C-band low-noise block down-converter and a L-band receiver. The receiver is designed to meet the requirements about wide-band, high sensitivity, large dynamic range, low noise figure. To reduce noise figure and increase bandwidth, the C-band low-noise amplifier is designed using T-type of matching network with negative feedback and the L-band LNA is designed using cascoded techniques. The local oscillator uses a voltage controlled oscillator combine phase locked loop to reduce the phase noise and select channels. The front-end has successfully been designed and fabricated with parameters: Input frequency is C-band; sensitivity is greater than -130 dBm for C-band receiver and is greater than -110dBm for L-band receiver; output signals are AM/FM demodulation, I/Q demodulation, baseband signals
Attentive Deep Neural Networks for Legal Document Retrieval
Legal text retrieval serves as a key component in a wide range of legal text
processing tasks such as legal question answering, legal case entailment, and
statute law retrieval. The performance of legal text retrieval depends, to a
large extent, on the representation of text, both query and legal documents.
Based on good representations, a legal text retrieval model can effectively
match the query to its relevant documents. Because legal documents often
contain long articles and only some parts are relevant to queries, it is quite
a challenge for existing models to represent such documents. In this paper, we
study the use of attentive neural network-based text representation for statute
law document retrieval. We propose a general approach using deep neural
networks with attention mechanisms. Based on it, we develop two hierarchical
architectures with sparse attention to represent long sentences and articles,
and we name them Attentive CNN and Paraformer. The methods are evaluated on
datasets of different sizes and characteristics in English, Japanese, and
Vietnamese. Experimental results show that: i) Attentive neural methods
substantially outperform non-neural methods in terms of retrieval performance
across datasets and languages; ii) Pretrained transformer-based models achieve
better accuracy on small datasets at the cost of high computational complexity
while lighter weight Attentive CNN achieves better accuracy on large datasets;
and iii) Our proposed Paraformer outperforms state-of-the-art methods on COLIEE
dataset, achieving the highest recall and F2 scores in the top-N retrieval
task.Comment: Preprint version. The official version will be published in
Artificial Intelligence and Law journa
Preparation and testing of ceasium Brønsted ion-exchanged Al-SBA-15 supported heteropoly acid as heterogeneous catalyst in the fructone fragrancy synthesis
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