960 resultados para Variance.
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Objective: This study assessed 12-month service use patterns among people with psychotic disorders and sought to identify determinants of service use. Methods: As part of a large two-phase Australian study of psychotic disorders, structured interviews were conducted with a stratified random sample of adults who screened positive for psychosis. Demographic characteristics, social functioning, symptoms, mental health diagnoses, and use of psychiatric and nonpsychiatric services were assessed. Data were analyzed for 858 persons who had an ICD-10 diagnosis of a psychotic disorder and who had been hospitalized for less than six months during the previous year. Results: People with psychotic disorders had high levels of use of health services, both in absolute terms and relative to people with nonpsychotic disorders. Those with psychotic disorders were estimated to have an average of one contact with health services per week. Use of psychiatric inpatient services was associated with parenthood, higher symptom levels, recent attempts at suicide or self-harm, personal disability, medication status, and frequency of alcohol consumption. Services provided by general practitioners (family physicians) were more likely to be obtained by older people, women, people with greater availability of friends, those with fewer negative symptoms, and those whose service needs were unmet by other sources. People who were high users of health services also reported having more contact with a range of non-health agencies. Conclusions: The predictors of service use accounted for small proportions of the variance in overall use of health services. The role of general practitioners in providing and monitoring treatment programs and other psychosocial interventions needs to be acknowledged and enhanced.
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This paper presents an extension to the Rapidly-exploring Random Tree (RRT) algorithm applied to autonomous, drifting underwater vehicles. The proposed algorithm is able to plan paths that guarantee convergence in the presence of time-varying ocean dynamics. The method utilizes 4-Dimensional, ocean model prediction data as an evolving basis for expanding the tree from the start location to the goal. The performance of the proposed method is validated through Monte-Carlo simulations. Results illustrate the importance of the temporal variance in path execution, and demonstrate the convergence guarantee of the proposed methods.
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The Internet has been shown to positively enhance internationalisation for SMEs, but scant empirical testing limits our understanding of the explicit impact of the Internet on firm internationalisation. This paper highlights key areas where the integration of the Internet can be leveraged through Internet-related capabilities within the internationalisation of the firm. Specifically, this study investigates how Internet marketing capabilities play a role in altering international information availability, international strategic orientation, and international business network relationships. This study provides evidence, indicating that these key relationships may vary between countries. To examine these key relationships this study utilises draws from data small and medium sized enterprises (SMEs) in three export intensive markets; Australia (215 international SMEs), Chile (204 international SMEs) and Taiwan (130 international SMEs); and tests a conceptual model through structural equation modelling. Results from the data show the impact of Internet marketing capabilities in positively impacting traditional internationalisation elements, which varies between countries. That is, our findings highlight the international business network relationships in Australia and Taiwan are directly impacted by Internet marketing capabilities, but not in Chile. We offer some insight into why we see variance across comparative exporting countries in how they leverage new technological capabilities for internationalisation and firm performance.
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It is commonly perceived that variables ‘measuring’ different dimensions of teaching (construed as instructional attributes) used in student evaluation of teaching (SET) questionnaires are so highly correlated that they pose a serious multicollinearity problem for quantitative analysis including regression analysis. Using nearly 12000 individual student responses to SET questionnaires and ten key dimensions of teaching and 25 courses at various undergraduate and postgraduate levels for multiple years at a large Australian university, this paper investigates whether this is indeed the case and if so under what circumstances. This paper tests this proposition first by examining variance inflation factors (VIFs), across courses, levels and over time using individual responses; and secondly by using class averages. In the first instance, the paper finds no sustainable evidence of multicollinearity. While, there were one or two isolated cases of VIFs marginally exceeding the conservative threshold of 5, in no cases did the VIFs for any of the instructional attributes come anywhere close to the high threshold value of 10. In the second instance, however, the paper finds that the attributes are highly correlated as all the VIFs exceed 10. These findings have two implications: (a) given the ordinal nature of the data ordered probit analysis using individual student responses can be employed to quantify the impact of instructional attributes on TEVAL score; (b) Data based on class averages cannot be used for probit analysis. An illustrative exercise using level 2 undergraduate courses data suggests higher TEVAL scores depend first and foremost on improving explanation, presentation, and organization of lecture materials.
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With the increasing need to adapt to new environments, data-driven approaches have been developed to estimate terrain traversability by learning the rover’s response on the terrain based on experience. Multiple learning inputs are often used to adequately describe the various aspects of terrain traversability. In a complex learning framework, it can be difficult to identify the relevance of each learning input to the resulting estimate. This paper addresses the suitability of each learning input by systematically analyzing the impact of each input on the estimate. Sensitivity Analysis (SA) methods provide a means to measure the contribution of each learning input to the estimate variability. Using a variance-based SA method, we characterize how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We propose an approach built on Analysis of Variance (ANOVA) decomposition to examine the prediction made in a near-to-far learning framework based on multi-task GP regression. We demonstrate the approach by analyzing the impact of driving speed and terrain geometry on the prediction of the rover’s attitude and chassis configuration in a Marsanalogue terrain using our prototype rover Mawson.
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We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.
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This study examined the combined influence of six positive psychology variables (optimism, hope, self-efficacy, grit, gratitude, and subjective life satisfaction), termed covitality, in relation to buffering individuals against anxiety symptoms. In addition, the influence of self-deception was examined to test whether this construct had an influence on the reporting of these positive psychology variables. A total of 268 individuals (203 females and 65 males) with a mean age of 22.2 years (SD = 7.4 years) from one Queensland university took part in the study. The participants completed an online questionnaire, which included a battery of positive psychological measures, plus a measure of anxiety and self-deception. The results indicated that the covitality constructs had a moderation effect on anxiety. In a regression analysis, the six covitality constructs explained an additional 24.5% of the variance in anxiety, after controlling for self-deception. Further analyses revealed that those higher in self-deception scored higher in self-efficacy and all positive covitality measures and lower in anxiety, than those lower in self-deception. These findings illustrate the importance of considering the role that self-deception might play in the reporting of positive psychology variables.
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Stochastic modelling is critical in GNSS data processing. Currently, GNSS data processing commonly relies on the empirical stochastic model which may not reflect the actual data quality or noise characteristics. This paper examines the real-time GNSS observation noise estimation methods enabling to determine the observation variance from single receiver data stream. The methods involve three steps: forming linear combination, handling the ionosphere and ambiguity bias and variance estimation. Two distinguished ways are applied to overcome the ionosphere and ambiguity biases, known as the time differenced method and polynomial prediction method respectively. The real time variance estimation methods are compared with the zero-baseline and short-baseline methods. The proposed method only requires single receiver observation, thus applicable to both differenced and un-differenced data processing modes. However, the methods may be subject to the normal ionosphere conditions and low autocorrelation GNSS receivers. Experimental results also indicate the proposed method can result on more realistic parameter precision.
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Do the political values of the general public form a coherent system? What might be the source of coherence? We view political values as expressions, in the political domain, of more basic personal values. Basic personal values (e.g., security, achievement, benevolence, hedonism) are organized on a circular continuum that reflects their conflicting and compatible motivations. We theorize that this circular motivational structure also gives coherence to political values. We assess this theorizing with data from 15 countries, using eight core political values (e.g., free enterprise, law and order) and ten basic personal values. We specify the underlying basic values expected to promote or oppose each political value. We offer different hypotheses for the 12 non-communist and three post-communist countries studied, where the political context suggests different meanings of a basic or political value. Correlation and regression analyses support almost all hypotheses. Moreover, basic values account for substantially more variance in political values than age, gender, education, and income. Multidimensional scaling analyses demonstrate graphically how the circular motivational continuum of basic personal values structures relations among core political values. This study strengthens the assumption that individual differences in basic personal values play a critical role in political thought.
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Purpose – In structural, earthquake and aeronautical engineering and mechanical vibration, the solution of dynamic equations for a structure subjected to dynamic loading leads to a high order system of differential equations. The numerical methods are usually used for integration when either there is dealing with discrete data or there is no analytical solution for the equations. Since the numerical methods with more accuracy and stability give more accurate results in structural responses, there is a need to improve the existing methods or develop new ones. The paper aims to discuss these issues. Design/methodology/approach – In this paper, a new time integration method is proposed mathematically and numerically, which is accordingly applied to single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems. Finally, the results are compared to the existing methods such as Newmark’s method and closed form solution. Findings – It is concluded that, in the proposed method, the data variance of each set of structural responses such as displacement, velocity, or acceleration in different time steps is less than those in Newmark’s method, and the proposed method is more accurate and stable than Newmark’s method and is capable of analyzing the structure at fewer numbers of iteration or computation cycles, hence less time-consuming. Originality/value – A new mathematical and numerical time integration method is proposed for the computation of structural responses with higher accuracy and stability, lower data variance, and fewer numbers of iterations for computational cycles.
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This study aimed at presenting the intra-tester reliability of the static load bearing exercises (LBEs) performed by individuals with transfemoral amputation (TFA) fitted with an osseointegrated implant to stimulate the bone remodelling process. There is a need for a better understanding of the implementation of these exercises particularly the reliability. The intra-tester reliability is discussed with a particular emphasis on inter-load prescribed, inter-axis and inter-component reliabilities as well as the effect of body weight normalisation. Eleven unilateral TFAs fitted with an OPRA implant performed five trials in four loading conditions. The forces and moments on the three axes of the implant were measured directly with an instrumented pylon including a six-channel transducer. Reliability of loading variables was assessed using intraclass correlation coefficients (ICCs) and percentage standard error of measurement values (%SEMs). The ICCs of all variables were above 0.9 and the %SEM values ranged between 0 and 87%. This study showed a high between-participants’ variance highlighting the lack of loading consistency typical of symptomatic population as well as a high reliability between the loading sessions indicating a plausible correct repetition of the LBE by the participants. However, these outcomes must be understood within the framework of the proposed experimental protocol.
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Opsins are ancient molecules that enable animal vision by coupling to a vitamin-derived chromophore to form lightsensitive photopigments. The primary drivers of evolutionary diversification in opsins are thought to be visual tasks related to spectral sensitivity and color vision. Typically, only a few opsin amino acid sites affect photopigment spectral sensitivity. We show that opsin genes of the North American butterfly Limenitis arthemis have diversified along a latitudinal cline, consistent with natural selection due to environmental factors. We sequenced single nucleotide(SNP) polymorphisms in the coding regions of the ultraviolet (UVRh), blue (BRh), and long-wavelength (LWRh) opsin genes from ten butterfly populations along the eastern United States and found that a majority of opsin SNPs showed significant clinal variation. Outlier detection and analysis of molecular variance indicated that many SNPs are under balancing selection and show significant population structure. This contrasts with what we found by analysing SNPs in the wingless and EF-1 alpha loci, and from neutral amplified fragment length polymorphisms, which show no evidence of significant locus-specific or genome-wide structure among populations. Using a combination of functional genetic and physiological approaches, including expression in cell culture, transgenic Drosophila, UV-visible spectroscopy, and optophysiology, we show that key BRh opsin SNPs that vary clinally have almost no effect on spectral sensitivity. Our results suggest that opsin diversification in this butterfly is more consistent with natural selection unrelated to spectral tuning. Some of the clinally varying SNPs may instead play a role in regulating opsin gene expression levels or the thermostability of the opsin protein. Lastly, we discuss the possibility that insect opsins might have important, yet-to-be elucidated, adaptive functions in mediating animal responses to abiotic factors, such as temperature or photoperiod.
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BACKGROUND There are significant disparities in cancer outcomes between Indigenous and non-Indigenous Australians. Identifying the unmet supportive care needs of Indigenous Australians with cancer is imperative to improve their cancer care. The purpose of this study was to test the psychometric properties of a supportive care needs assessment tool for Indigenous Australian (SCNAT-IP) cancer patients. METHODS The SCNAT-IP was administered to 248 Indigenous Australians diagnosed with a range of cancer types and stages, and received treatment in one of four Queensland hospitals. All 39 items were assessed for ceiling and floor effects and analysed using exploratory factor analysis (EFA) to determine construct validity. Identified factors were assessed for internal consistency and convergent validity to validated psychosocial tools. RESULTS EFA revealed a four-factor structure (physical and psychological, hospital care, information and communication, and practical and cultural needs) explaining 51% of the variance. Internal consistency of four subscales was good, with Cronbach Alpha reliability coefficients ranging from 0.70-0.89. Convergent validity was supported by significant correlations between the SCNAT-IP with the Distress Thermometer (r=0.60, p<0.001), and The Cancer Worry Chart (r=0.58, p<0.001) and a moderately strong negative correlation with Assessment of Quality of Life questionnaire (r=-0.56, p<0.001). CONCLUSION These data provide initial support for the SCNAT-IP a measure of multiple supportive care needs domains specific to Indigenous Australian cancer patients undergoing treatment.
Predicting intentions and behaviours in populations with or at-risk of diabetes: A systematic review
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Purpose To systematically review the Theory of Planned Behaviour studies predicting self-care intentions and behaviours in populations with and at-risk of diabetes. Methods A systematic review using six electronic databases was conducted in 2013. A standardised protocol was used for appraisal. Studies eligibility included a measure of behaviour for healthy eating, physical activity, glucose monitoring, medication use (ii) the TPB variables (iii) the TPB tested in populations with diabetes or at-risk. Results Sixteen studies were appraised for testing the utility of the TPB. Studies included cross-sectional (n=7); prospective (n=5) and randomised control trials (n=4). Intention (18% – 76%) was the most predictive construct for all behaviours. Explained variance for intentions were similar across cross-sectional (28 -76%); prospective (28 -73%); and RCT studies (18 - 63%). RCTs (18 - 43%) provided slightly stronger evidence for predicting behaviour. Conclusions Few studies tested predictability of the TPB in populations with or at-risk of diabetes. This review highlighted differences in the predictive utility of the TPB suggesting that the model is behaviour and population specific. Findings on key determinants of specific behaviours contribute to a better understanding of mechanisms of behaviour change and are useful in designing targeted behavioural interventions for different diabetes populations.
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In this study, the authors pay particular attention to mistreatment directed toward an organizational member from fellow workgroup members. The study contributes to the growing body of literature that examines the mistreatment of employees in the workplace. The authors propose that mistreatment by the workgroup would contribute to feelings of rejection, over and above mistreatment by the supervisor. In addition, the authors tested the mediating role of perceived rejection between workgroup mistreatment and affective outcomes such as depression and organization-based self-esteem. Part-time working participants (N = 142) took part in the study, which required them to complete a questionnaire on workplace behaviors. Results indicated that workgroup mistreatment contributed additional variance to perceived rejection over and above supervisory mistreatment when predicting depression and organization-based self-esteem. The results also indicated that perceived rejection mediates the relationship between mistreatment and affective outcomes. Results are discussed and implications for research and practice are considered.