Complex Network Approach for Recurrence Analysis of Time Series

We propose a novel approach for analysing time series using complex network theory. We identify the recurrence matrix calculated from time series with the adjacency matrix of a complex network, and apply measures for the characterisation of complex networks to this recurrence matrix. By using the logistic map, we illustrate the potentials of these complex network measures for detecting dynamical transitions. Finally we apply the proposed approach to a marine palaeo-climate record and identify subtle changes of the climate regime.Comment: 23 pages, 7 figure

End-User Modelling

National audienceno abstrac

Contract Aware Components, 10 years after

The notion of contract aware components has been published roughly ten years ago and is now becoming mainstream in several fields where the usage of software components is seen as critical. The goal of this paper is to survey domains such as Embedded Systems or Service Oriented Architecture where the notion of contract aware components has been influential. For each of these domains we briefly describe what has been done with this idea and we discuss the remaining challenges.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Subgraphs in random networks

Understanding the subgraph distribution in random networks is important for modelling complex systems. In classic Erdos networks, which exhibit a Poissonian degree distribution, the number of appearances of a subgraph G with n nodes and g edges scales with network size as \mean{G} ~ N^{n-g}. However, many natural networks have a non-Poissonian degree distribution. Here we present approximate equations for the average number of subgraphs in an ensemble of random sparse directed networks, characterized by an arbitrary degree sequence. We find new scaling rules for the commonly occurring case of directed scale-free networks, in which the outgoing degree distribution scales as P(k) ~ k^{-\gamma}. Considering the power exponent of the degree distribution, \gamma, as a control parameter, we show that random networks exhibit transitions between three regimes. In each regime the subgraph number of appearances follows a different scaling law, \mean{G} ~ N^{\alpha}, where \alpha=n-g+s-1 for \gamma<2, \alpha=n-g+s+1-\gamma for 2<\gamma<\gamma_c, and \alpha=n-g for \gamma>\gamma_c, s is the maximal outdegree in the subgraph, and \gamma_c=s+1. We find that certain subgraphs appear much more frequently than in Erdos networks. These results are in very good agreement with numerical simulations. This has implications for detecting network motifs, subgraphs that occur in natural networks significantly more than in their randomized counterparts.Comment: 8 pages, 5 figure

Boolean Delay Equations: A simple way of looking at complex systems

Boolean Delay Equations (BDEs) are semi-discrete dynamical models with Boolean-valued variables that evolve in continuous time. Systems of BDEs can be classified into conservative or dissipative, in a manner that parallels the classification of ordinary or partial differential equations. Solutions to certain conservative BDEs exhibit growth of complexity in time. They represent therewith metaphors for biological evolution or human history. Dissipative BDEs are structurally stable and exhibit multiple equilibria and limit cycles, as well as more complex, fractal solution sets, such as Devil's staircases and ``fractal sunbursts``. All known solutions of dissipative BDEs have stationary variance. BDE systems of this type, both free and forced, have been used as highly idealized models of climate change on interannual, interdecadal and paleoclimatic time scales. BDEs are also being used as flexible, highly efficient models of colliding cascades in earthquake modeling and prediction, as well as in genetics. In this paper we review the theory of systems of BDEs and illustrate their applications to climatic and solid earth problems. The former have used small systems of BDEs, while the latter have used large networks of BDEs. We moreover introduce BDEs with an infinite number of variables distributed in space (``partial BDEs``) and discuss connections with other types of dynamical systems, including cellular automata and Boolean networks. This research-and-review paper concludes with a set of open questions.Comment: Latex, 67 pages with 15 eps figures. Revised version, in particular the discussion on partial BDEs is updated and enlarge

Challenge Demcare: management of challenging behaviour in dementia at home and in care homes:Development, evaluation and implementation of an online individualised intervention for care homes; and a cohort study of specialist community mental health care for families

Background: Dementia with challenging behaviour (CB) causes significant distress for caregivers and the person with dementia. It is associated with breakdown of care at home and disruption in care homes. Challenge Demcare aimed to assist care home staff and mental health practitioners who support families at home to respond effectively to CB. Objectives: To study the management of CB in care homes (ResCare) and in family care (FamCare). Following a conceptual overview, two systematic reviews and scrutiny of clinical guidelines, we (1) developed and tested a computerised intervention; (2) conducted a cluster randomised trial (CRT) of the intervention for dementia with CB in care homes; (3) conducted a process evaluation of implementation of the intervention; and (4) conducted a longitudinal observational cohort study of the management of people with dementia with CB living at home, and their carers. Review methods: Cochrane review of randomised controlled trials; systematic meta-ethnographic review of quantitative and qualitative studies. Design: ResCare – survey, CRT, process evaluation and stakeholder consultations. FamCare – survey, longitudinal cohort study, participatory development design process and stakeholder consultations. Comparative examination of baseline levels of CB in the ResCare trial and the FamCare study participants. Settings: ResCare – 63 care homes in Yorkshire. FamCare – 33 community mental health teams for older people (CMHTsOP) in seven NHS organisations across England. Participants: ResCare – 2386 residents and 861 staff screened for eligibility; 555 residents with dementia and CB; 277 ‘other’ residents; 632 care staff; and 92 staff champions. FamCare – every new referral (n = 5360) reviewed for eligibility; 157 patients with dementia and CB, with their carer; and 26 mental health practitioners. Stakeholder consultations – initial workshops with 83 practitioners and managers from participating organisations; and 70 additional stakeholders using eight group discussions and nine individual interviews. Intervention: An online application for case-specific action plans to reduce CB in dementia, consisting of e-learning and bespoke decision support care home and family care e-tools. Main outcome measures: ResCare – survey with the Challenging Behaviour Scale; measurement of CB with the Neuropsychiatric Inventory (NPI) and medications taken from prescriptions; implementation with thematic views from participants and stakeholders. FamCare – case identification from all referrals to CMHTsOP; measurement of CB with the Revised Memory and Behaviour Problems Checklist and NPI; medications taken from prescriptions; and thematic views from stakeholders. Costs of care calculated for both settings. Comparison of the ResCare trial and FamCare study participants used the NPI, Clinical Dementia Rating and prescribed medications. Results: ResCare – training with group discussion and decision support for individualised interventions did not change practice enough to have an impact on CB in dementia. Worksite e-learning opportunities were not readily taken up by care home staff. Smaller homes with a less hierarchical management appear more ready than others to engage in innovation. FamCare – home-dwelling people with dementia and CB are referred to specialist NHS services, but treatment over 6 months, averaging nine contacts per family, had no overall impact on CB. Over 60% of people with CB had mild dementia. Families bear the majority of the care costs of dementia with CB. A care gap in the delivery of post-diagnostic help for families supporting relatives with dementia and significant CB at home has emerged. Higher levels of CB were recorded in family settings; and prescribing practices were suboptimal in both care home and family settings. Limitations: Functionality of the software was unreliable, resulting in delays. This compromised the feasibility studies and undermined delivery of the intervention in care homes. A planned FamCare CRT could not proceed because of insufficient referrals. Conclusions: A Cochrane review of individualised functional analysis-based interventions suggests that these show promise, although delivery requires a trained dementia care workforce. Like many staff training interventions, our interactive e-learning course was well received by staff when delivered in groups with facilitated discussion. Our e-learning and decision support e-tool intervention in care homes, in its current form, without ongoing review of implementation of recommended action plans, is not effective at reducing CB when compared with usual care. This may also be true for staff training in general. A shift in priorities from early diagnosis to early recognition of dementia with clinically significant CB could bridge the emerging gap and inequities of care to families. Formalised service improvements in the NHS, to co-ordinate such interventions, may stimulate better opportunities for practice models and pathways. Separate services for care homes and family care may enhance the efficiency of delivery and the quality of research on implementation into routine care. Future work: There is scope for extending functional analysis-based interventions with communication and interaction training for carers. Our clinical workbooks, video material of real-life episodes of CB and process evaluation tool resources require further testing. There is an urgent need for evaluation of interventions for home-dwelling people with dementia with clinically significant CB, delivered by trained dementia practitioners. Realist evaluation designs may illuminate how the intervention might work, and for whom, within varying service contexts

Identification of Novel Genetic Loci Associated with Thyroid Peroxidase Antibodies and Clinical Thyroid Disease

Peer reviewe

Neuropeptides, Trophic Factors, and Other Substances Providing Morphofunctional and Metabolic Protection in Experimental Models of Diabetic Retinopathy

Vision is the most important sensory modality for many species, including humans. Damage to the retina results in vision loss or even blindness. One of the most serious complications of diabetes, a disease that has seen a worldwide increase in prevalence, is diabetic retinopathy. This condition stems from consequences of pathological metabolism and develops in 75% of patients with type 1 and 50% with type 2 diabetes. The development of novel protective drugs is essential. In this review we provide a description of the disease and conclude that type 1 diabetes and type 2 diabetes lead to the same retinopathy. We evaluate existing experimental models and recent developments in finding effective compounds against this disorder. In our opinion, the best models are the long-term streptozotocin-induced diabetes and Otsuka Long-Evans Tokushima Fatty and spontaneously diabetic Torii rats, while the most promising substances are topically administered somatostatin and pigment epithelium-derived factor analogs, antivasculogenic substances, and systemic antioxidants. Future drug development should focus on these