A temporal relational algebra based on multiple time-lines

Background: Prior network analyses demonstrated that the death of a loved one potentially precedes specific depression symptoms, primarily loneliness, which in turn links to other depressive symptoms. In this study, we extend prior research by comparing depression symptom network structures following two types of marital disruption: bereavement versus separation. Methods: We fitted two Gaussian Graphical Models to cross-sectional data from a Swiss survey of older persons (145 bereaved, 217 separated, and 362 married controls), and compared symptom levels across bereaved and separated individuals. Results: Separated compared to widowed individuals were more likely to perceive an unfriendly environment and oneself as a failure. Both types of marital disruption were linked primarily to loneliness, from where different relations emerged to other depressive symptoms. Amongst others, loneliness had a stronger connection to perceiving oneself as a failure in separated compared to widowed individuals. Conversely, loneliness had a stronger connection to getting going in widowed individuals. Limitations: Analyses are based on cross-sectional between-subjects data, and conclusions regarding dynamic processes on the within-subjects level remain putative. Further, some of the estimated parameters in the network exhibited overlapping confidence intervals and their order needs to be interpreted with care. Replications should thus aim for studies with multiple time points and larger samples. Conclusions: The findings of this study add to a growing body of literature indicating that depressive symptom patterns depend on contextual factors. If replicated on the within-subjects level, such findings have implications for setting up patient-tailored treatment approaches in dependence of contextual factors.

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Robust Predictive Control for a Class of Multiple Time Delay Uncertain Systems with Nonlinear Disturbance

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2013.00644 ◽

2014 ◽

Vol 39 (5) ◽

pp. 644-649 ◽

Cited By ~ 7

Author(s):

Cheng-Li SU ◽

Jia-Cheng ZHAO ◽

Ping LI

Keyword(s):

Time Delay ◽

Predictive Control ◽

Uncertain Systems ◽

Multiple Time ◽

Nonlinear Disturbance ◽

Robust Predictive Control

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Oscillatory Dynamics of P53 Network With Time Delays

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207321666180601080026 ◽

2018 ◽

Vol 21 (6) ◽

pp. 411-419 ◽

Cited By ~ 2

Author(s):

Conghua Wang ◽

Fang Yan ◽

Yuan Zhang ◽

Haihong Liu ◽

Linghai Zhang

Keyword(s):

Hopf Bifurcation ◽

Cell Fate ◽

Time Delays ◽

Sustained Oscillation ◽

Multiple Time ◽

Cell Fate Decisions ◽

Oscillatory Dynamics ◽

Main Components ◽

Parameter Values ◽

P53 Network

Aims and Objective: A large number of experimental evidences report that the oscillatory dynamics of p53 would regulate the cell fate decisions. Moreover, multiple time delays are ubiquitous in gene expression which have been demonstrated to lead to important consequences on dynamics of genetic networks. Although delay-driven sustained oscillation in p53-based networks is commonplace, the precise roles of such delays during the processes are not completely known. Method: Herein, an integrated model with five basic components and two time delays for the network is developed. Using such time delays as the bifurcation parameter, the existence of Hopf bifurcation is given by analyzing the relevant characteristic equations. Moreover, the effects of such time delays are studied and the expression levels of the main components of the system are compared when taking different parameters and time delays. Result and Conclusion: The above theoretical results indicated that the transcriptional and translational delays can induce oscillation by undergoing a super-critical Hopf bifurcation. More interestingly, the length of these delays can control the amplitude and period of the oscillation. Furthermore, a certain range of model parameter values is essential for oscillation. Finally, we illustrated the main results in detail through numerical simulations.

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SOME REMARKS ON THE MULTIPLE TIME SCALES OF DIFFUSION IN MINERALS AND MELTS

10.1130/abs/2018am-323387 ◽

2018 ◽

Author(s):

Yan Liang ◽

◽

Daniele J. Cherniak ◽

Chenguang Sun

Keyword(s):

Time Scales ◽

Multiple Time Scales ◽

Multiple Time

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Physical activity levels among ovarian cancer survivors: a prospective longitudinal cohort study

International Journal of Gynecological Cancer ◽

10.1136/ijgc-2020-002107 ◽

2021 ◽

pp. ijgc-2020-002107

Author(s):

Tamara Jones ◽

Carolina Sandler ◽

Dimitrios Vagenas ◽

Monika Janda ◽

Andreas Obermair ◽

...

Keyword(s):

Physical Activity ◽

Ovarian Cancer ◽

Stage Iv ◽

Multiple Time ◽

Activity Levels ◽

Prospective Longitudinal Study ◽

Physical Activity Advice ◽

Physical Activity Levels ◽

Multiple Time Points ◽

Prospective Longitudinal

ObjectivePhysical activity following cancer diagnosis is associated with improved outcomes, including potential survival benefits, yet physical activity levels among common cancer types tend to decrease following diagnosis and remain low. Physical activity levels following diagnosis of less common cancers, such as ovarian cancer, are less known. The objectives of this study were to describe physical activity levels and to explore characteristics associated with physical activity levels in women with ovarian cancer from pre-diagnosis to 2 years post-diagnosis.MethodsAs part of a prospective longitudinal study, physical activity levels of women with ovarian cancer were assessed at multiple time points between pre-diagnosis and 2 years post-diagnosis. Physical activity levels and change in physical activity were described using metabolic equivalent task hours and minutes per week, and categorically (sedentary, insufficiently, or sufficiently active). Generalized Estimating Equations were used to explore whether participant characteristics were related to physical activity levels.ResultsA total of 110 women with ovarian cancer with a median age of 62 years (range 33–88) at diagnosis were included. 53–57% of the women were sufficiently active post-diagnosis, although average physical activity levels for the cohort were below recommended levels throughout the 2-year follow-up period (120–142.5min/week). A decrease or no change in post-diagnosis physical activity was reported by 44–60% of women compared with pre-diagnosis physical activity levels. Women diagnosed with stage IV disease, those earning a lower income, those receiving chemotherapy, and those currently smoking or working were more likely to report lower physical activity levels and had increased odds of being insufficiently active or sedentary.ConclusionsInterventions providing patients with appropriate physical activity advice and support for behavior change could potentially improve physical activity levels and health outcomes.

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Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism

BMJ Paediatrics Open ◽

10.1136/bmjpo-2020-000700 ◽

2021 ◽

Vol 5 (1) ◽

pp. e000700

Author(s):

Carrie Allison ◽

Fiona E Matthews ◽

Liliana Ruta ◽

Greg Pasco ◽

Renee Soufer ◽

...

Keyword(s):

Phase 1 ◽

Autism Spectrum ◽

Population Screening ◽

Diagnostic Assessment ◽

Test Accuracy ◽

Multiple Time ◽

Phase 2 ◽

Time Points ◽

Screening Study

ObjectiveThis is a prospective population screening study for autism in toddlers aged 18–30 months old using the Quantitative Checklist for Autism in Toddlers (Q-CHAT), with follow-up at age 4.DesignObservational study.SettingLuton, Bedfordshire and Cambridgeshire in the UK.Participants13 070 toddlers registered on the Child Health Surveillance Database between March 2008 and April 2009, with follow-up at age 4; 3770 (29%) were screened for autism at 18–30 months using the Q-CHAT and the Childhood Autism Spectrum Test (CAST) at follow-up at age 4.InterventionsA stratified sample across the Q-CHAT score distribution was invited for diagnostic assessment (phase 1). The 4-year follow-up included the CAST and the Checklist for Referral (CFR). All with CAST ≥15, phase 1 diagnostic assessment or with developmental concerns on the CFR were invited for diagnostic assessment (phase 2). Standardised diagnostic assessment at both time-points was conducted to establish the test accuracy of the Q-CHAT.Main outcome measuresConsensus diagnostic outcome at phase 1 and phase 2.ResultsAt phase 1, 3770 Q-CHATs were returned (29% response) and 121 undertook diagnostic assessment, of whom 11 met the criteria for autism. All 11 screened positive on the Q-CHAT. The positive predictive value (PPV) at a cut-point of 39 was 17% (95% CI 8% to 31%). At phase 2, 2005 of 3472 CASTs and CFRs were returned (58% response). 159 underwent diagnostic assessment, including 82 assessed in phase 1. All children meeting the criteria for autism identified via the Q-CHAT at phase 1 also met the criteria at phase 2. The PPV was 28% (95% CI 15% to 46%) after phase 1 and phase 2.ConclusionsThe Q-CHAT can be used at 18–30 months to identify autism and enable accelerated referral for diagnostic assessment. The low PPV suggests that for every true positive there would, however, be ~4–5 false positives. At follow-up, new cases were identified, illustrating the need for continued surveillance and rescreening at multiple time-points using developmentally sensitive instruments. Not all children who later receive a diagnosis of autism are detectable during the toddler period.

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Extending Geodemographics Using Data Primitives: A Review and a Methodological Proposal

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10060386 ◽

2021 ◽

Vol 10 (6) ◽

pp. 386

Author(s):

Jennie Gray ◽

Lisa Buckner ◽

Alexis Comber

Keyword(s):

Social Dynamics ◽

Feature Space ◽

Social Processes ◽

Multiple Time ◽

Current State ◽

Cluster Label ◽

Static Data ◽

The Social ◽

Using Data

This paper reviews geodemographic classifications and developments in contemporary classifications. It develops a critique of current approaches and identifiea a number of key limitations. These include the problems associated with the geodemographic cluster label (few cluster members are typical or have the same properties as the cluster centre) and the failure of the static label to describe anything about the underlying neighbourhood processes and dynamics. To address these limitations, this paper proposed a data primitives approach. Data primitives are the fundamental dimensions or measurements that capture the processes of interest. They can be used to describe the current state of an area in a multivariate feature space, and states can be compared over multiple time periods for which data are available, through for example a change vector approach. In this way, emergent social processes, which may be too weak to result in a change in a cluster label, but are nonetheless important signals, can be captured. As states are updated (for example, as new data become available), inferences about different social processes can be made, as well as classification updates if required. State changes can also be used to determine neighbourhood trajectories and to predict or infer future states. A list of data primitives was suggested from a review of the mechanisms driving a number of neighbourhood-level social processes, with the aim of improving the wider understanding of the interaction of complex neighbourhood processes and their effects. A small case study was provided to illustrate the approach. In this way, the methods outlined in this paper suggest a more nuanced approach to geodemographic research, away from a focus on classifications and static data, towards approaches that capture the social dynamics experienced by neighbourhoods.

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