Physical activity, emotional stress, sleep disturbances, and daily fluctuations in chronic fatigue symptomatology

The current study explored the relationships between physical and emotional stress and the symptomatology of chronic fatigue syndrome (CFS). Fifty-four CFS patients were studied using a longitudinal design. A self-report format was used to collect daily measures of major physical (sleep disturbance and physical activity) and emotional (subjective emotional stress level) stressors, as well as measures of levels of fatigue and secondary symptoms. The variables accounted for a moderate variance at the individual and occasion levels. Sleep disturbance and emotional stress were found to be positively associated with levels of fatigue and symptomatology, whereas physical activity was found to have a negative relationship with fatigue only. The severity of fatigue and symptoms were found to fluctuate daily in relation with the variables, indicating the complex nature of the associations.

The behaviour of US stock prices : evidence from a threshold autoregressive model

This paper investigates the behaviour of US stock prices using an unrestricted two-regime threshold autoregressive (TAR) model with an autoregressive unit root. The TAR model is applied to monthly stock price (NYSE Common Stocks) data for the US for the period 1964:06 to 2003:04. Amongst our main results, we find that the US stock price is a nonlinear series that is characterized by a unit root process, consistent with the efficient market hypothesis.

Are nominal exchange rates and price levels co-integrated? new evidence from threshold autoregressive and momentum-threshold autoregressive models

The goal of this paper is to examine evidence for co-integration between nominal exchange rates for Canada, the UK, Japan, Germany, Italy and France (G6) vis-à-vis the US dollar, and the relative price ratios using monthly data over the period 1973:01 to 1997:04. Motivated by the fact that exchange rate adjustment may be asymmetric, we allowed for asymmetric adjustment in exchange rates by using the threshold autoregressive model and the momentum threshold autoregressive model. We do not find any evidence of a co-integrating relationship; hence, we fail to establish long-run purchasing power parity.

Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process

In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

Examining the dissociative basis for body image disturbances

Although dissociative symptoms have been linked with both food- and appearance-related aspects of eating disorders, the psychological mechanisms underlying these relationships remain unclear. The present study evaluated the hypothesis that the disturbances of self-identity attributed to dissociation can manifest as disturbances of body image and, in turn, undermine body-specific self-evaluations relevant to disordered eating (i.e., body comparison, body dissatisfaction, and internalization of the thin ideal). Ninety-three female university students completed self-report measures of dissociation and body-related aspects of disordered eating. In addition, the method of constant stimuli was used to experimentally derive three measures of body image disturbance: (1) accuracy of body size estimations (body image distortion), (2) ability to discriminate between different body sizes (body image sensitivity), and (3) consistency in one’s body size estimations (body image variability). The findings show that dissociation is related to symptoms of disordered eating, and that these relationships may be mediated by body image instability. Collectively, these findings support the notion that the body image attitudes and behaviours that characterize eating disorders may derive from proprioceptive deficits due to dissociation.

Energy deficiency, menstrual disturbances, and low bone mass : what do exercising Australian women know about the female athlete triad?

Purpose: Prevention of the female athlete triad is essential to protect female athletes’ health. The aim of this study was to investigate the knowledge, attitudes, and behaviors of regularly exercising adult women in Australia toward eating patterns, menstrual cycles, and bone health.
Methods: A total of 191 female exercisers, age 18–40 yr, engaging in ≥2 hr/wk of strenuous activity, completed a survey. After 11 surveys were excluded (due to incomplete answers), the 180 participants were categorized into lean-build sports (n = 82; running/ athletics, triathlon, swimming, cycling, dancing, rowing), non-lean-build sports (n = 94; basketball, netball, soccer, hockey, volleyball, tennis, trampoline, squash, Australian football), or gym/fitness activities (n = 4).
Results: Mean (± SD) training volume was 9.0 ± 5.5 hr/wk, with participants competing from local up to international level. Only 10% of respondents could name the 3 components of the female athlete triad. Regardless of reported history of stress fracture, 45% of the respondents did not think that amenorrhea (absence of menses for ≥3 months) could affect bone health, and 22% of those involved in lean-build sports would do nothing if experiencing amenorrhea (vs. 3.2% in non-lean-build sports, p = .005). Lean-build sports, history of amenorrhea, and history of stress fracture were all significantly associated with not taking action in the presence of amenorrhea (all p < .005). Conclusions: Few active Australian women are aware of the detrimental effects of menstrual dysfunction on bone health. Education programs are needed to prevent the female athlete triad and ensure that appropriate actions are taken by athletes when experiencing amenorrhea.

Elementary phenomena, body disturbances and symptom formation in ordinary psychosis

In my research, I examined body phenomena in psychosis by exploring onset, triggering events and stabilisation in psychosis. I concluded that body disturbances can be important indicators for the onset of psychosis and, that these disturbances provide a framework for better understanding the recovery from psychosis, particularly in schizophrenia.

An extended multivariate autoregressive framework for EEG-based information flow analysis of a brain network

Recently effective connectivity studies have gained significant attention among the neuroscience community as Electroencephalography (EEG) data with a high time resolution can give us a wider understanding of the information flow within the brain. Among other tools used in effective connectivity analysis Granger Causality (GC) has found a prominent place. The GC analysis, based on strictly causal multivariate autoregressive (MVAR) models does not account for the instantaneous interactions among the sources. If instantaneous interactions are present, GC based on strictly causal MVAR will lead to erroneous conclusions on the underlying information flow. Thus, the work presented in this paper applies an extended MVAR (eMVAR) model that accounts for the zero lag interactions. We propose a constrained adaptive Kalman filter (CAKF) approach for the eMVAR model identification and demonstrate that this approach performs better than the short time windowing-based adaptive estimation when applied to information flow analysis.

Inferring activity budgets in wild animals to estimate the consequences of disturbances

Activity budgets can provide a direct link to an animal's bioenergetic budget and is thus a valuable unit of measure when assessing human-induced nonlethal effects on wildlife conservation status. However, activity budget inference can be challenging for species that are difficult to observe and require multiple observational variables. Here, we assessed whether whalewatching boat interactions could affect the activity budgets of minke whales (Balaenoptera acutorostrata). We used a stepwise modeling approach to quantitatively record, identify, and assign activity states to continuous behavioral time series data, to estimate activity budgets. First, we used multiple behavioral variables, recorded from continuous visual observations of individual animals, to quantitatively identify and define behavioral types. Activity states were then assigned to each sampling unit, using a combination of hidden and observed states. Three activity states were identified: nonfeeding, foraging, and surface feeding (SF). From the resulting time series of activity states, transition probability matrices were estimated using first-order Markov chains. We then simulated time series of activity states, using Monte Carlo methods based on the transition probability matrices, to obtain activity budgets, accounting for heterogeneity in state duration. Whalewatching interactions reduced the time whales spend foraging and SF, potentially resulting in an overall decrease in energy intake of 42%. This modeling approach thus provides a means to link short-term behavioral changes resulting from human disturbance to potential long-term bioenergetic consequences in animals. It also provides an analytical framework applicable to other species when direct observations of activity states are not possible.

ε-bounded state estimation for time-delay systems with bounded disturbances

A new problem on ε-bounded functional state estimation for time-delay systems with unknown bounded disturbances is studied in this paper. In the presence of unknown bounded disturbances, the common assumption regarding the observers matching condition is no longer required. In this regard, instead of achieving asymptotic convergence for the observer error, the error is now required to converge exponentially within a ball with a small radius ε > 0. This means that the estimate converges exponentially within an ε-bound of the true value. A general observer that utilises multiple-delayed output and input information is proposed. Sufficient conditions for the existence of the proposed observer are first given. We then employ an extended Lyapunov-Krasovskii functional which combines the delay-decomposition technique with a triple-integral term to study the ε-convergence problem of the observer error system. Moreover, the obtained results are shown to be more effective than the existing results for the cases with no disturbances and/or no time delay. Three numerical examples are given to illustrate the obtained results.