7,268 research outputs found

    Acupuncture as an adjunct therapy in the treatment of depression

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    University of Technology Sydney. Faculty of Science.OBJECTIVE: The main analysis in this study assessed the effectiveness of using acupuncture as an adjunct therapy to Selective Serotonin Reuptake Inhibiting (SSRI’s) antidepressants in the treatment of Major Depressive Disorder (MDD). A secondary analysis explored if the intervention led to any differences between subjects based on sex. DESIGN: This study used a randomised, single blind, repeated measures design. A standardised acupuncture intervention was administered as an adjunct therapy to SSRI. The researchers proposed a best-fit synthesis model which upheld the integrity of the scientific method whilst maintaining the integrity of the Chinese Medicine (CM) model. Inclusion in the study required subjects to both satisfy the criteria for MDD and to present with liver qi stagnation (a CM diagnostic category). The Beck Depression Inventory and the Hamilton Rating Scale for Depressive Illness were the primary measures of depression. RESULTS: The outcomes of the study showed that those who received the acupuncture intervention experienced a statistically significant improvement in their depression scores compared to those who participated in a wait list control group who experienced no change. Analysis based on diagnostic status (DSM-IV-TR) indicated an 87.3% remission rate. An eight week follow up analysis indicated subjects were able to maintain their improvement and remain significantly less depressed than they were before receiving the intervention. The data were stratified according to sex and suggested there were few differences between females and males. Further analysis was conducted to include an anxiety scale (STAI) and a general mental health scale (SCL-90). As with the depression analysis, the subjects showed statistically significant improvement in anxiety and mental health dimension scores. This was similarly true for the female and the male subjects alike. CONCLUSION: Acupuncture may be an effective adjunct therapy to SSRIs for both females and males in treatment of MDD. In addition to this, the outcomes from this study have interesting implications within the wider context of the CM model. It would appear that in addition to the link between liver qi stagnation and depression, there is also a link to a broader spectrum of mental health dimensions

    Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate

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    Observations and models have shown that continuously degassing volcanoes have a potentially large effect on the natural background aerosol loading and the radiative state of the atmosphere. We use a global aerosol microphysics model to quantify the impact of these volcanic emissions on the cloud albedo radiative forcing under pre-industrial (PI) and present-day (PD) conditions. We find that volcanic degassing increases global annual mean cloud droplet number concentrations by 40% under PI conditions, but by only 10% under PD conditions. Consequently, volcanic degassing causes a global annual mean cloud albedo effect of −1.06 W m−2 in the PI era but only −0.56 W m−2 in the PD era. This non-equal effect is explained partly by the lower background aerosol concentrations in the PI era, but also because more aerosol particles are produced per unit of volcanic sulphur emission in the PI atmosphere. The higher sensitivity of the PI atmosphere to volcanic emissions has an important consequence for the anthropogenic cloud radiative forcing because the large uncertainty in volcanic emissions translates into an uncertainty in the PI baseline cloud radiative state. Assuming a −50/+100% uncertainty range in the volcanic sulphur flux, we estimate the annual mean anthropogenic cloud albedo forcing to lie between −1.16 W m−2 and −0.86 W m−2. Therefore, the volcanically induced uncertainty in the PI baseline cloud radiative state substantially adds to the already large uncertainty in the magnitude of the indirect radiative forcing of climate

    Testing times for dementia: a community survey identifying contemporary barriers to risk reduction and screening

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    Background: Advances in pharmacological and non-pharmacological dementia interventions may mean future dementia prevention incorporates a combination of targeted screening and lifestyle modifications. Elucidating potential barriers which may prevent community engagement with dementia prevention initiatives is important to maximise the accessibility and feasibility of these initiatives across the lifespan. Methods: Six hundred seven adults aged over 18 years completed a 54-item, multiple-choice survey exploring contemporary attitudes towards, and barriers to, dementia risk reduction and screening relative to other common health conditions. Participants were sourced from Australia’s largest, paid, data analytics service (ORIMA). Results: Finances (p =.009), poor motivation (p =.043), and time (p ≤.0001) emerged as significant perceived barriers to dementia risk reduction behaviours. Lack of time was more likely to be reported by younger, relative to older, participants (p ≤.0001), while females were more likely than males to report financial (p =.019) and motivational (p =.043) factors. Binary logistic regression revealed willingness to undertake dementia testing modalities was significantly influenced by gender (genetic testing, p =.012; saliva, p =.038, modifiable risk factors p =.003), age (cognitive testing, p ≤.0001; blood, p =.010), and socio-economic group (retinal imaging, p =.042; modifiable risk-factor screening, p =.019). Over 65% of respondents felt adequately informed about risk reduction for at least one non-dementia health condition, compared to 30.5% for dementia. Conclusions: This study found perceived barriers to dementia risk reduction behaviours, and the willingness to engage in various dementia testing modalities, was significantly associated with socio-demographic factors across the lifespan. These findings provide valuable insight regarding the accessibility and feasibility of potential methods for identifying those most at risk of developing dementia, as well as the need to better promote and support wide-scale engagement in dementia risk reduction behaviours across the lifespan

    Examining the impact of critical attributes on hard drive failure times: Multi-state models for left-truncated and right-censored semi-competing risks data

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    \ua9 2023 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons Ltd. The ability to predict failures in hard disk drives (HDDs) is a major objective of HDD manufacturers since avoiding unexpected failures may prevent data loss, improve service reliability, and reduce data center downtime. Most HDDs are equipped with a threshold-based monitoring system named self-monitoring, analysis and reporting technology (SMART). The system collects several performance metrics, called SMART attributes, and detects anomalies that may indicate incipient failures. SMART works as a nascent failure detection method and does not estimate the HDDs\u27 remaining useful life. We define critical attributes and critical states for hard drives using SMART attributes and fit multi-state models to the resulting semi-competing risks data. The multi-state models provide a coherent and novel way to model the failure time of a hard drive and allow us to examine the impact of critical attributes on the failure time of a hard drive. We derive dynamic predictions of conditional survival probabilities, which are adaptive to the state of the drive. Using a dataset of HDDs equipped with SMART, we find that drives are more likely to fail after entering critical states. We evaluate the predictive accuracy of the proposed models with a case study of HDDs equipped with SMART, using the time-dependent area under the receiver operating characteristic curve (AUC) and the expected prediction error (PE). The results suggest that accounting for changes in the critical attributes improves the accuracy of dynamic predictions

    Aggregation of Votes with Multiple Positions on Each Issue

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    We consider the problem of aggregating votes cast by a society on a fixed set of issues, where each member of the society may vote for one of several positions on each issue, but the combination of votes on the various issues is restricted to a set of feasible voting patterns. We require the aggregation to be supportive, i.e. for every issue jj the corresponding component fjf_j of every aggregator on every issue should satisfy fj(x1,,,xn){x1,,,xn}f_j(x_1, ,\ldots, x_n) \in \{x_1, ,\ldots, x_n\}. We prove that, in such a set-up, non-dictatorial aggregation of votes in a society of some size is possible if and only if either non-dictatorial aggregation is possible in a society of only two members or a ternary aggregator exists that either on every issue jj is a majority operation, i.e. the corresponding component satisfies fj(x,x,y)=fj(x,y,x)=fj(y,x,x)=x,x,yf_j(x,x,y) = f_j(x,y,x) = f_j(y,x,x) =x, \forall x,y, or on every issue is a minority operation, i.e. the corresponding component satisfies fj(x,x,y)=fj(x,y,x)=fj(y,x,x)=y,x,y.f_j(x,x,y) = f_j(x,y,x) = f_j(y,x,x) =y, \forall x,y. We then introduce a notion of uniformly non-dictatorial aggregator, which is defined to be an aggregator that on every issue, and when restricted to an arbitrary two-element subset of the votes for that issue, differs from all projection functions. We first give a characterization of sets of feasible voting patterns that admit a uniformly non-dictatorial aggregator. Then making use of Bulatov's dichotomy theorem for conservative constraint satisfaction problems, we connect social choice theory with combinatorial complexity by proving that if a set of feasible voting patterns XX has a uniformly non-dictatorial aggregator of some arity then the multi-sorted conservative constraint satisfaction problem on XX, in the sense introduced by Bulatov and Jeavons, with each issue representing a sort, is tractable; otherwise it is NP-complete

    On modeling player fitness in training for team sports with application to professional rugby

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    It is increasingly important for professional sports teams to monitor player fitness in order to optimize performance. Models have been put forward linking fitness in training to performance in competition but rely on regular measurements of player fitness. As formal tests for measuring player fitness are typically time-consuming and inconvenient, measurements are taken infrequently. As such, it may be challenging to accurately predict performance in competition as player fitness is unknown.Alternatively, other data, such as how the players are feeling, may be measured more regularly. This data, however, may be biased as players may answer the questions differently and these differences may dominate the data. Linear Mixed Methods and Support Vector Machines were used to estimate player fitness from available covariates at times when explicit measures of fitness are unavailable. Using data provided by Glasgow Warriors Rugby Club, a case study was used to illustrate the application and value of these models. Both models performed well with R2 values ranging from 60% to 85%, demonstrating that the models largely captured the biases introduced by individual players

    Addressing obesity in the first 1000 days in high risk infants: Systematic review.

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    Early intervention is critical for addressing the challenge of childhood obesity. Yet many preventive interventions do not target infants most at risk of future overweight or obesity. This systematic review examines interventions delivered before 2 years that aim to ameliorate excess weight gain among infants at high risk of overweight or obesity, due to sociodemographic characteristics, parental weight or health status, infant feeding or health behaviours. We searched six databases for interventions: (a) delivered before age two, (b) specifically aimed at infants at high risk of childhood obesity and (c) that reported outcomes by weight status beyond 28 days. The search identified over 27,000 titles, and 49 papers from 38 studies met inclusion criteria: 10 antenatal interventions, 16 postnatal and 12 conducted both before and after birth. Nearly all targeted infant and/or maternal nutrition. Studies varied widely in design, obesity risk factors, outcomes and quality. Overall, nine interventions of varying quality reported some evidence of significantly improved child weight trajectory, although effects tended to diminish over time. Interventions that improved weight outcomes tended to engage parents for a longer period, and most offered health professional input and support. Two studies of limited quality reported significantly worse weight outcomes in the intervention group

    A simulation study of BrachyShade, a shadow-based internal source tracking system for HDR prostate brachytherapy

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    © 2018 Commonwealth of Australia. Department of Education and Training, and Department of Industry, Innovation and Science.. This paper presents a simulation study of BrachyShade, a proposed internal source-tracking system for real time quality assurance in high dose rate prostate brachytherapy. BrachyShade consists of a set of spherical tungsten occluders located above a pixellated silicon photodetector. The source location is estimated by minimising the mean squared error between a parametric model of the shadow image and acquired images of the shadows projected on the detector plane. A novel algorithm is finally employed to correct the systemic error resulting from Compton scattering in the medium. The worst-case error obtained with BrachyShade for a 13.5 ms image acquisition is less than 1.3 mm in the most distant part of the treatment volume, while for 75% of source locations an error of less than 0.42 mm was achieved
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