Intensive Time Series Research Articles

The experience sampling method as an mHealth tool to support self-monitoring, self-insight, and personalized health care in clinical practice.

The experience sampling method (ESM) builds an intensive time series of experiences and contexts in the flow of daily life, typically consisting of around 70 reports, collected at 8-10 random time points per day over a period of up to 10 days. With the advent of widespread smartphone use, ESM can be used in routine clinical practice. Multiple examples of ESM data collections across different patient groups and settings are shown and discussed, varying from an ESM evaluation of a 6-week randomized trial of mindfulness, to a twin study on emotion dynamics in daily life. Research shows that ESM-based self-monitoring and feedback can enhance resilience by strengthening the capacity to use natural rewards. Personalized trajectories of starting or stopping medication can be more easily initiated and predicted if sensitive feedback data are available in real time. In addition, personalized trajectories of symptoms, cognitive abilities, symptoms impacting on other symptoms, the capacity of the dynamic system of mental health to "bounce back" from disturbance, and patterns of environmental reactivity yield uniquely personal data to support shared decision making and prediction in clinical practice. Finally, ESM makes it possible to develop insight into previous implicit patterns of thought, experience, and behavior, particularly if rapid personalized feedback is available. ESM enhances clinical practice and research. It is empowering, providing co-ownership of the process of diagnosis, treatment evaluation, and routine outcome measurement. Blended care, based on a mix of face-to-face and ESM-based outside-the-office treatment, may reduce costs and improve outcomes.

Volatility in High-Frequency Intensive Care Mortality Time Series: Application of Univariate and Multivariate GARCH Models

Mortality time series display time-varying volatility. The utility of statistical estimators from the financial time-series paradigm, which account for this characteristic, has not been addressed for high-frequency mortality series. Using daily mean-mortality series of an exemplar intensive care unit (ICU) from the Australian and New Zealand Intensive Care Society adult patient database, joint estimation of a mean and conditional variance (volatility) model for a stationary series was undertaken via univariate autoregressive moving average (ARMA, lags (p, q)), GARCH (Generalised Autoregressive Conditional Heteroscedasticity, lags (p, q)). The temporal dynamics of the conditional variance and correlations of multiple provider series, from rural/ regional, metropolitan, tertiary and private ICUs, were estimated utilising multivariate GARCH models. For the stationary first differenced series, an asymmetric power GARCH model (lags (1, 1)) with t distribution (degrees-of- freedom, 11.6) and ARMA (7,0) for the mean-model, was the best-fitting. The four multivariate component series demonstrated varying trend mortality decline and persistent autocorrelation. Within each MGARCH series no model specification dominated. The conditional correlations were surprisingly low (<0.1) between tertiary series and substantial (0.4 - 0.6) between rural-regional and private series. The conditional-variances of both the univariate and multivariate series demonstrated a slow rate of time decline from periods of early volatility and volatility spikes.

Population Dynamics of Bulking and Foaming Bacteria in a Full-scale Wastewater Treatment Plant over Five Years.

Bulking and foaming are two notorious problems in activated sludge wastewater treatment plants (WWTPs), which are mainly associated with the excessive growth of bulking and foaming bacteria (BFB). However, studies on affecting factors of BFB in full-scale WWTPs are still limited. In this study, data sets of high-throughput sequencing (HTS) of 16S V3–V4 amplicons of 58 monthly activated sludge samples from a municipal WWTP was re-analyzed to investigate the BFB dynamics and further to study the determinative factors. The population of BFB occupied 0.6~36% (averagely 8.5% ± 7.3%) of the total bacteria and showed seasonal variations with higher abundance in winter-spring than summer-autumn. Pair-wise correlation analysis and canonical correlation analysis (CCA) showed that Gordonia sp. was positively correlated with NO2-N and negatively correlated with NO3-N, and Nostocodia limicola II Tetraspharea sp. was negatively correlated with temperature and positively correlated with NH3-N in activated sludge. Bacteria species correlated with BFB could be clustered into two negatively related modules. Moreover, with intensive time series sampling, the dominant BFB could be accurately modeled with environmental interaction network, i.e. environmental parameters and biotic interactions between BFB and related bacteria, indicating that abiotic and biotic factors were both crucial to the dynamics of BFB.

Submarine groundwater discharge as a source of dissolved nutrients to an arid coastal embayment (La Paz, Mexico)

Submarine groundwater discharge (SGD) was investigated in the southeastern portion of La Paz Bay (Baja California, Mexico) using radon (222Rn) as a natural tracer. In the absence of permanent surface flows in this arid region, we hypothesize SGD is a major regional source of dissolved nutrients. Four spatial surveys showed higher radon and nutrient (NH4, NO3, NO2, PO4 and SiO4) values in the winter than summer lagging rainfall by 3–4 months. The surveys revealed two sites (Balandra and Merito) with a stronger radon signal. Intensive time series (12–24 h) measurements at those sites were used to estimate SGD fluxes using a radon mass balance approach. In Balandra, SGD was estimated to be 0.18 m3 m−2 day−1 and significant correlations between radon and nutrients (NO3 and SiO4) were observed. In Merito, SGD rates were estimated to be 0.10 m3 m−2 day−1 and no correlations between nutrients and 222Rn were observed. The difference between the two sites was interpreted to be related to different components dominating SGD (i.e., fresh SGD in Balandra and saline SGD in Merito). The estimated SGD-derived nutrients fluxes were 2–52, 0.04–0.94, 7–164 mmol m2 day−1 for dissolved inorganic nitrogen, phosphate, and silicate, respectively. These fluxes could explain between 5 and 20 % of the regional marine primary productivity values.

Temporal Associations Among Chronic PTSD Symptoms in U.S. Combat Veterans.

The present study examined fluctuation over time in symptoms of posttraumatic stress disorder (PTSD) among 34 combat veterans (28 with diagnosed PTSD, 6 with subclinical symptoms) assessed every 2 weeks for up to 2 years (range of assessments = 13-52). Temporal relationships were examined among four PTSD symptom clusters (reexperiencing, avoidance, emotional numbing, and hyperarousal) with particular attention to the influence of hyperarousal. Multilevel cross-lagged random coefficients autoregression for intensive time series data analyses were used to model symptom fluctuation decades after combat experiences. As anticipated, hyperarousal predicted subsequent fluctuations in the 3 other PTSD symptom clusters (reexperiencing, avoidance, emotional numbing) at subsequent 2-week intervals (rs = .45, .36, and .40, respectively). Additionally, emotional numbing influenced later reexperiencing and avoidance, and reexperiencing influenced later hyperarousal (rs = .44, .40, and .34, respectively). These findings underscore the important influence of hyperarousal. Furthermore, results indicate a bidirectional relationship between hyperarousal and reexperiencing as well as a possible chaining of symptoms (hyperarousal → emotional numbing → reexperiencing → hyperarousal) and establish potential internal, intrapersonal mechanisms for the maintenance of persistent PTSD symptoms. Results suggested that clinical interventions targeting hyperarousal and emotional numbing symptoms may hold promise for PTSD of long duration.

Tidal controls on trace gas dynamics in a seagrass meadow of the Ria Formosa lagoon (southern Portugal)

Abstract. Coastal zones are important source regions for a variety of trace gases, including halocarbons and sulfur-bearing species. While salt marshes, macroalgae and phytoplankton communities have been intensively studied, little is known about trace gas fluxes in seagrass meadows. Here we report results of a newly developed dynamic flux chamber system that can be deployed in intertidal areas over full tidal cycles allowing for highly time-resolved measurements. The fluxes of CO2, methane (CH4) and a range of volatile organic compounds (VOCs) showed a complex dynamic mediated by tide and light. In contrast to most previous studies, our data indicate significantly enhanced fluxes during tidal immersion relative to periods of air exposure. Short emission peaks occurred with onset of the feeder current at the sampling site. We suggest an overall strong effect of advective transport processes to explain the elevated fluxes during tidal immersion. Many emission estimates from tidally influenced coastal areas still rely on measurements carried out during low tide only. Hence, our results may have significant implications for budgeting trace gases in coastal areas. This dynamic flux chamber system provides intensive time series data of community respiration (at night) and net community production (during the day) of shallow coastal systems.

Building an integrated coastal ocean acidification monitoring network in the U.S.

Since the beginning of the Industrial Revolution, the release of carbon dioxide (CO2) from industrial and agricultural activities around the world has increased the amount of CO2 in the atmosphere, leading to warming temperatures and changes in weather patterns and climate. However, a significant part of the potential atmospheric CO2 increase has been naturally mitigated as the oceans have absorbed about 30% of all of the CO2 released every year (Feely et al., 2013). This absorption has caused CO2 inventories in the ocean to increase by billions of tons, especially in the last 50 to 100 years (Sabine and Tanhua, 2010). Initially, many scientists focused on the benefits of the ocean removing this greenhouse gas from the atmosphere, until the downside became dramatically obvious in the past few decades (e.g., Feely et al., 2004, 2009; Orr et al., 2005; Fabry et al., 2008; Doney et al., 2009). Observations made by hundreds of scientists at thousands of locations have unambiguously shown that CO2 absorbed by the ocean is changing the fundamental chemistry of the seawater through a process called Ocean Acidification (OA; e.g., Caldeira and Wickett, 2003, 2005; Feely et al., 2009; Mathis et al., 2011). When CO2 is absorbed by seawater, chemical reactions occur that reduce seawater pH and saturation states of biologically important calcium carbonate minerals, such as calcite and aragonite, which are the essential building blocks for the skeletons and shells of many marine organisms. Prior to mankind’s release of CO2 into the environment, most areas of the surface ocean were supersaturated with respect to calcium carbonate minerals. This supersaturation means that there was abundant material for calcifying organisms to build their skeletons and shells. Since then, the pH of surface ocean waters has fallen by an average of 0.1 pH units, which represents a 30% increase in seawater acidity (e.g., Feely et al., 2009; Byrne et al., 2010). Future predictions indicate that if the oceans continue to absorb CO2 based on business-as-usual emission scenarios, they will be 150% more acidic by the end of this century. This scenario would lead to pH levels that the oceans have not experienced for more than 20 million years (Honisch et al., 2012), when CO2 levels were naturally very high in the atmosphere and marine calcifying species such as coral reefs, crabs, and oysters were severely limited in their geographic range or completely non-existent (Portner et al., 2004; Payne and Clapham, 2012). The problem of OA is particularly disconcerting for coastal areas where nearly all ocean-based economic and subsistence activities occur within a few hundred kilometers of shore (Cooley and Doney, 2009). These areas are already under threat from multiple stressors, such as overfishing, pollution, and hypoxia brought on by eutrophication (Portner, 2012; Whittman and Portner, 2013). On a local scale, the combined effects from OA and other natural and anthropogenic processes have already led to failures in hatcheries that rear larval shellfish (e.g., Barton et al., 2012) and caused the degradation and destruction of some planktonic shells (e.g., Bednarsek et al., 2012). While direct organismal impacts have been limited to date, over 1 billion people derive 100% of their protein supply directly from the ocean. Although there is a great deal of variability in organismal responses, even within the same groups, several commercial and subsistence species have shown a low tolerance to OA conditions that are already present at certain times of the year (Kroeker et al., 2013; Whittman and Portner, 2013) and will only worsen in the coming decades. Given the variability in ecosystem responses to OA, there will likely be both winners and losers throughout the marine environment. In the U.S., fisheries from the Bering Sea to the Gulf of Maine are at risk from this potentially looming stressor. There is a critical need for intensive time series measurements and repeat hydrographic cruises in high productivity coastal and estuarine systems, as CO2 and carbonate ion concentrations in these waters can vary substantially on time scales from hours to decades due to tides, photosynthesis, terrestrial inputs, and ocean circulation patterns. Domain Editor-in-Chief Jody W. Deming, University of Washington

Parallel computing strategies in the analysis of the inhibiting effect of price limits on futures prices

ABSTRACTIn futures markets with price limits, trading halts are triggered by limit hits. Limit hits are rarely observed, perhaps because traders avoid bid‐ask quotes that cause them. If this explanation is true, futures prices would cluster in a narrow region close to the limits. We test this empirically for currency futures contracts and find results consistent with the explanation. The tests require calculations of all combinations of a computationally intensive time series, which are extremely time consuming on a sequential machine and hence limit the practicality of the analysis. Consequently, we investigate parallel computing strategies in partitioning the datasets and solving them in parallel on a high‐end Beowulf cluster. We discuss two different partitioning strategies of the given datasets on the cluster and elaborate the results. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Is the Looming Maladaptive Cognitive Style a Central Mechanism in the (Generalized) Anxiety–(Major) Depression Comorbidity: An Intra-Individual, Time Series Study

The authors examined the unfolding of anxiety-depression comorbidity while emphasizing its multifaceted and intra-individual nature. An intensive time series design was employed, whereby three young adult patients with diagnosed comorbid Generalized Anxiety Disorder (GAD) and Major Depression Disorder (MDD) were followed daily for a period of 6 months. Daily reports included affective states, cognitive vulnerability, and symptoms of depression and anxiety. The Looming Maladaptive Style (LMS), pertaining to the tendency to generate mental scenarios of potentially threatening situations as rapidly rising in risk, prospectively predicted anxiety, depression, and hopelessness, a dimension of depressive vulnerability. Effects of anxiety and depression on cognitive vulnerability were also documented. Findings suggest that LMS confers vulnerability to emotional disorders, broadly defined, and emphasize the need to include an intra-individual analysis for the purpose of elucidating the nature of psychopathologica...

Radon tracing of groundwater discharge into an Australian estuary surrounded by coastal acid sulphate soils

Summary Widespread sulphidic deposits have accumulated in tropical coastal floodplains throughout the world. Sulphidic soils oxidize when floodplains are drained for urban and agricultural development. As a result, large amounts of sulphuric acid may be released to nearby waterways. Macropores may create excellent conditions for groundwater flow in coastal acid sulphate soils (CASS). An automated radon (222Rn) measurement system was used to quantify groundwater inputs into a tidally-dominated estuary that is known to be influenced by acid discharges from CASS (Richmond River Estuary, Australia). A high resolution radon survey along a 120-km long segment of the tidal river identified two areas of preferential groundwater inputs. Intensive time series measurements in one of those areas (the Tuckean Broadwater) demonstrated that groundwater inputs are highly variable over hourly and seasonal time scales and inversely related to surface water pH. Elevated radon concentrations (up to 12 dpm/L) and low pH (as low as 3.3) were observed in surface waters at low tide a few weeks after a large rain event. These results demonstrate that acidic waters are entering the estuary via tidally-modulated groundwater flow pathways. Groundwater discharge rates into drains in the Tuckean Swamp were estimated from a dual-assumption radon mass balance to be 0.09–0.16 and 0.56–0.89 m3 s−1 during the dry and wet season, respectively (or 6–10 and 37–59 cm/day if the area is taken into account). While surface runoff increased only 2-fold in the wet season relative to the dry season, groundwater discharge rates increased ∼6-fold. Since groundwater can be a major driver of surface water quality, radon can be useful in CASS monitoring and management efforts.

&lt;sup234&lt;/sup&gt;Th measured particle export from surface waters in north-western Mediterranean: comparison of spring and autumn periods

234Th was used to quantify the short-term variability of particle dynamics and of POC export during transition periods in surface waters over the north-western Mediterranean. As a part of DYNAPROC I and II cruises, two intensive time-series of 234Th were carried out near the DYFAMED station (43° 25´N–7°51´E) during late spring (May, 1995), when the system changes towards oligotrophy, and during autumn (October, 2004), when the stratification is disturbed by wind. Particulate fluxes derived from 234Th measured in the upper water column and in drifting sediment trap showed large differences between the two situations: the flux decreased from high to low values during late spring, at the difference of the autumnal situation where the fluxes were always low. 234Th-derived POC fluxes, calculated from the 234Th238U disequilibrium in the water column and POC/234Th ratio on trapped material, and export ratios (ThE: ratio of 234Th-derived POC export to primary production) showed a large range, from 8 to 110 mgC m−2 d−1 and 3–55%; the lowest values were observed at the end of the productive period (end May) and in automn. The 234Th-derived information is in agreement with the annual variations in Mediterranean Sea productivity. From these experiments during transition periods, it is not obvious that renewal of nutrients by wind events is strong enough to sustain significant export after the end of the productive period or to initiate significant export in autumn.

Traumatic brain injury in childhood: Intensive Care time series data and outcome

Age-specific norms are necessary to determine potential secondary brain insult after head injury in children. We describe and quantify the secondary physiological derangement recorded in children of different ages following traumatic brain injury, and relate it to outcome at 12 months post-injury. Prospective time-series data (including intracranial pressure, arterial blood pressure, cerebral perfusion pressure, oxygen saturation, temperature and heart rate) downloaded from ICU monitors, were examined to identify abnormal (i.e. outside normal age-specific limits) recordings lasting more than 5 min. Cumulated total duration of derangement was calculated for each parameter and as a percentage of the time that the ICP monitor was in situ. Univariate and multivariate logistic regression modelling was used to evaluate predictors of outcome. Age-specificity allows realistic comparisons of physiological data among children. Duration of age-specific derangement of CPP was found to predict outcome (dead v. alive: p = 0.003 and Glasgow Outcome Score 1-3 v. 4-5, i.e. poor v. independent outcome p = 0.004).

Traumatic brain injury in childhood: Intensive Care time series data and outcome

Age-specific norms are necessary to determine potential secondary brain insult after head injury in children. We describe and quantify the secondary physiological derangement recorded in children of different ages following traumatic brain injury, and relate it to outcome at 12 months post-injury. Prospective time-series data (including intracranial pressure, arterial blood pressure, cerebral perfusion pressure, oxygen saturation, temperature and heart rate) downloaded from ICU monitors, were examined to identify abnormal (i.e. outside normal age-specific limits) recordings lasting more than 5 min. Cumulated total duration of derangement was calculated for each parameter and as a percentage of the time that the ICP monitor was in situ. Univariate and multivariate logistic regression modelling was used to evaluate predictors of outcome. Age-specificity allows realistic comparisons of physiological data among children. Duration of age-specific derangement of CPP was found to predict outcome (dead v. alive: p = 0.003 and Glasgow Outcome Score 1–3 v. 4–5, i.e. poor v. independent outcome p = 0.004).

Pattern Detection in Intensive Care Monitoring Time Series with Autoregressive Models: Influence of the Model Order

The detection of patterns in monitoring data of vital signs is of great importance for adequate bedside decision support in critical care. Currently used alarm systems, which are based on fixed thresholds and independency assumptions, are not satisfactory in clinical practice. Time series techniques such as AR-models consider autocorrelations within the series, which can be used for pattern recognition in the data. For practical applications in intensive care the data analysis has to be automated. An important issue is the suitable choice of the model order which is difficult to accomplish online. In a comparative case-study we analyzed 34564 univariate time series of hemodynamic variables in critically ill patients by autoregressive models of different orders and compared the results of pattern detection. AR(2)-models seem to be most suitable for the detection of clinically relevant patterns, thus affirming that treating the data as independent leads to false alarms. Moreover, using AR(2)-models affords only short estimation periods. These findings for pattern detection in intensive care data are of medical importance as they justify a preselection of a model order, easing further automated statistical online analysis.

Changing patterns of infant behavior and mother–infant interaction: Intra- and interindividual variability

Mother–infant dyads were observed weekly at their homes for a 15-month period. In this way longitudinal data about the infants’ crying, fretting/fussing, smiling and different types of physical contact with the mother were collected. The subject of this study concerns the variability and stability in macroscopic patterns of associations between these behaviors. Different types of associations were found between the behaviors, and most of them changed considerably as the infant developed. Individual differences in the nature of the associations and in the changes they underwent over time predominated, but in a limited number of cases the infants shared the same developmental trajectories of behavioral associations. The results show how the use of intensive time series designs can be advantageous in clarifying issues of long-term variability and stability in human behavior. They also support the notion of changing patterns of behavior being a normal feature of early development.

The Development of Phonological Abilities and Their Relation to Reading Acquisition

The relation between phonological abilities and reading acquisition and the interindividual variation in the development of different phonological manipulation skills were assessed for six 7-year-old Finnish nonreaders. Intensive time series data were collected by following the children for 13 months. Assessments were conducted every 4 weeks with five phonological manipulation tests. The results indicated gradual progress at the group level. However, analysis of the individual profiles indicated large interindividual variation in the rate of improvement and in the relation between different manipulation skills and reading acquisition.

Styles of interaction in low-income mother-infant dyads

Mother–infant dyads were observed weekly at their homes for a 15-month period. In this way longitudinal data about the infants’ crying, fretting/fussing, smiling and different types of physical contact with the mother were collected. The subject of this study concerns the variability and stability in macroscopic patterns of associations between these behaviors. Different types of associations were found between the behaviors, and most of them changed considerably as the infant developed. Individual differences in the nature of the associations and in the changes they underwent over time predominated, but in a limited number of cases the infants shared the same developmental trajectories of behavioral associations. The results show how the use of intensive time series designs can be advantageous in clarifying issues of long-term variability and stability in human behavior. They also support the notion of changing patterns of behavior being a normal feature of early development.

Identification and description of the momentum effect in studies of learning: An abstract science concept

AbstractSeveral studies of the validity of the intensive time series design have revealed a post‐intervention increase in the level of achievement data. This so called “momentum effect” has not been demonstrated through the application of an appropriate analysis technique. The purpose of this study was to identify and apply a technique that would adequately represent and describe such an effect if indeed it does occur, and to use that technique to study the momentum effect as it is observed in several data sets on the learning of the concept of plate tectonics. Subsequent to trials of several different analyses, a segmented straight line regression analysis was chosen and used on three different data sets. Each set revealed similar patterns of inflection points between lines with similar time intervals between inflections for those data from students with formal cognitive tendencies. These results seem to indicate that this method will indeed be useful in representing and identifying the presence and duration of the momentum effect in time series data on achievement. Since the momentum effect could be described in each of the data sets and since its presence seems a function of similar circumstances, support is given for its presence in the learning of abstract scientific concepts for formal cognitive tendency students. The results indicate that the duration of the momentum effect is related to the level of student understanding tested and the cognitive level of the learners.