Improving quality of mother-infant relationship and infant attachment in socioeconomically deprived community in South Africa: randomised controlled trial

Objective To assess the efficacy of an intervention designed to improve the mother-infant relationship and security of infant attachment in a South African peri-urban settlement with marked adverse socioeconomic circumstances. Design Randomised controlled trial. Setting Khayelitsha, a peri-urban settlement in South Africa. Participants 449 pregnant women. Interventions The intervention was delivered from late pregnancy and for six months postpartum. Women were visited in their homes by previously untrained lay community workers who provided support and guidance in parenting. The purpose of the intervention was to promote sensitive and responsive parenting and secure infant attachment to the mother. Women in the control group received no therapeutic input from the research team. Main outcome measures Primary outcomes: quality of mother-infant interactions at six and 12 months postpartum; infant attachment security at 18 months. Secondary outcome: maternal depression at six and 12 months. Results The intervention was associated with significant benefit to the mother-infant relationship. At both six and 12 months, compared with control mothers, mothers in the intervention group were significantly more sensitive (6 months: mean difference=0.77 (SD 0.37), t=2.10, P<0.05, d=0.24; 12 months: mean difference=0.42 (0.18), t=-2.04, P<0.05, d=0.26) and less intrusive (6 months: mean difference=0.68 (0.36), t=2.28, P<0.05, d=0.26; 12 months: mean difference=-1.76 (0.86), t=2.28, P<0.05, d=0.24) in their interactions with their infants. The intervention was also associated with a higher rate of secure infant attachments at 18 months (116/156 (74%) v 102/162 (63%); Wald=4.74, odds ratio=1.70, P<0.05). Although the prevalence of maternal depressive disorder was not significantly reduced, the intervention had a benefit in terms of maternal depressed mood at six months (z=2.05, P=0.04) on the Edinburgh postnatal depression scale). Conclusions The intervention, delivered by local lay women, had a significant positive impact on the quality of the mother-infant relationship and on security of infant attachment, factors known to predict favourable child development. If these effects persist, and if they are replicated, this intervention holds considerable promise for use in the developing world. Trial registration Current Controlled Trials ISRCTN25664149.

Parallel and distributed computing with Java

The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

The SAFEE on-board threat detection system

Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.

Modeling the effects of node heterogeneity on the performance of a real grid application

The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.

Modeling the effects of node heterogeneity on the performance of grid applications

The performance benefit when using grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effects of synchronization overheads, mainly due to the high variability in the execution times of the different tasks, which, in turn, is accentuated by the large heterogeneity of grid nodes. In this paper we design hierarchical, queuing network performance models able to accurately analyze grid architectures and applications. Thanks to the model results, we introduce a new allocation policy based on a combination between task partitioning and task replication. The models are used to study two real applications and to evaluate the performance benefits obtained with allocation policies based on task replication.

Generalized honeycomb torus is Hamiltonian

Generalized honeycomb torus is a candidate for interconnection network architectures, which includes honeycomb torus, honeycomb rectangular torus, and honeycomb parallelogramic torus as special cases. Existence of Hamiltonian cycle is a basic requirement for interconnection networks since it helps map a "token ring" parallel algorithm onto the associated network in an efficient way. Cho and Hsu [Inform. Process. Lett. 86 (4) (2003) 185-190] speculated that every generalized honeycomb torus is Hamiltonian. In this paper, we have proved this conjecture. (C) 2004 Elsevier B.V. All rights reserved.

Distributed acceleration of mobile radio network optimisation algorithms

The past decade has witnessed explosive growth of mobile subscribers and services. With the purpose of providing better-swifter-cheaper services, radio network optimisation plays a crucial role but faces enormous challenges. The concept of Dynamic Network Optimisation (DNO), therefore, has been introduced to optimally and continuously adjust network configurations, in response to changes in network conditions and traffic. However, the realization of DNO has been seriously hindered by the bottleneck of optimisation speed performance. An advanced distributed parallel solution is presented in this paper, as to bridge the gap by accelerating the sophisticated proprietary network optimisation algorithm, while maintaining the optimisation quality and numerical consistency. The ariesoACP product from Arieso Ltd serves as the main platform for acceleration. This solution has been prototyped, implemented and tested. Real-project based results exhibit a high scalability and substantial acceleration at an average speed-up of 2.5, 4.9 and 6.1 on a distributed 5-core, 9-core and 16-core system, respectively. This significantly outperforms other parallel solutions such as multi-threading. Furthermore, augmented optimisation outcome, alongside high correctness and self-consistency, have also been fulfilled. Overall, this is a breakthrough towards the realization of DNO.

Generating virtual environments to allow increased access to the built environment

The problems encountered by individuals with disabilities when accessing large public buildings is described and a solution based on the generation of virtual models of the built environment is proposed. These models are superimposed on a control network infrastructure, currently utilised in intelligent building applications such as lighting, heating and access control. The use of control network architectures facilitates the creation of distributed models that closely mirror both the physical and control properties of the environment. The model of the environment is kept local to the installation which allows the virtual representation of a large building to be decomposed into an interconnecting series of smaller models. This paper describes two methods of interacting with the virtual model, firstly a two dimensional aural representation that can be used as the basis of a portable navigational device. Secondly an augmented reality called DAMOCLES that overlays additional information on a user’s normal field of view. The provision of virtual environments offers new possibilities in the man-machine interface so that intuitive access to network based services and control functions can be given to a user.

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological selforganization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modelling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.

Improving quality of mother-infant relationship and infant attachment in socioeconomically deprived community in South Africa: randomised controlled trail

Objective To assess the efficacy of an intervention designed to improve the mother-infant relationship and security of infant attachment in a South African peri-urban settlement with marked adverse socioeconomic circumstances. Design Randomised controlled trial. Setting Khayelitsha, a peri-urban settlement in South Africa. Participants 449 pregnant women. Interventions The intervention was delivered from late pregnancy and for six months postpartum. Women were visited in their homes by previously untrained lay community workers who provided support and guidance in parenting. The purpose of the intervention was to promote sensitive and responsive parenting and secure infant attachment to the mother. Women in the control group received no therapeutic input from the research team. Main outcome measures Primary outcomes: quality of mother-infant interactions at six and 12 months postpartum; infant attachment security at 18 months. Secondary outcome: maternal depression at six and 12 months. Results The intervention was associated with significant benefit to the mother-infant relationship. At both six and 12 months, compared with control mothers, mothers in the intervention group were significantly more sensitive (6 months: mean difference=0.77 (SD 0.37), t=2.10, P<0.05, d=0.24; 12 months: mean difference=0.42 (0.18), t=−2.04 , P<0.05, d=0.26) and less intrusive (6 months: mean difference=0.68 (0.36), t=2.28, P<0.05, d=0.26; 12 months: mean difference=−1.76 (0.86), t=2.28 , P<0.05, d=0.24) in their interactions with their infants. The intervention was also associated with a higher rate of secure infant attachments at 18 months (116/156 (74%) v 102/162 (63%); Wald=4.74, odds ratio=1.70, P<0.05). Although the prevalence of maternal depressive disorder was not significantly reduced, the intervention had a benefit in terms of maternal depressed mood at six months (z=2.05, P=0.04) on the Edinburgh postnatal depression scale). Conclusions The intervention, delivered by local lay women, had a significant positive impact on the quality of the mother-infant relationship and on security of infant attachment, factors known to predict favourable child development. If these effects persist, and if they are replicated, this intervention holds considerable promise for use in the developing world.

Inertia in Japanese organizations: knowledge management routines and failure to innovate

This paper argues that features of Japanese organizations, previously held to be the foundations of innovation, change and flexibility, can equally be significant barriers to change, innovation and adaptation in turbulent economic environments. This paper draws on two in-depth case studies of Japanese organizations. It shows how, in both cases, these firms displayed specific weaknesses in the ways in which they integrate and bundle knowledge, in particular around their research and development (R&D) functions. Despite the adoption of strategies of technological innovation and internationalization, the data suggest that the pursuit of both strategies is beset by barriers of inertia. Embedded internal network connections and knowledge-sharing routines between central R&D and other divisions are inappropriate for the revised strategy. Existing external connections, with preferred suppliers and customers within keiretsu structures, and close relationships with existing R&D partners retard these firms' strategic flexibility. With a limited variety of latent routines, knowledge, capabilities and agency to draw on when needed, these firms have limited organizational responsiveness and high levels of path-dependency.

Attention through self-synchronisation in the spiking neuron stochastic diffusion network

The paper discusses ensemble behaviour in the Spiking Neuron Stochastic Diffusion Network, SNSDN, a novel network exploring biologically plausible information processing based on higher order temporal coding. SNSDN was proposed as an alternative solution to the binding problem [1]. SNSDN operation resembles Stochastic Diffusin on Search, SDS, a non-deterministic search algorithm able to rapidly locate the best instantiation of a target pattern within a noisy search space ([3], [5]). In SNSDN, relevant information is encoded in the length of interspike intervals. Although every neuron operates in its own time, ‘attention’ to a pattern in the search space results in self-synchronised activity of a large population of neurons. When multiple patterns are present in the search space, ‘switching of at- tention’ results in a change of the synchronous activity. The qualitative effect of attention on the synchronicity of spiking behaviour in both time and frequency domain will be discussed.