Sleep disruption and domestic violence: exploring the interconnections between mothers and children

This paper argues that sleep disruption is both a strategy and an effect of violence and abuse which profoundly affects the lives of women and children. This paper traces the interconnections between the patterns of sleeping (not sleeping) for women and children living with and recovering from the effects of violence and abuse. It highlights the threat to the emotional and physical well-being of children and women and provides a non-pathologizing route into an exploration of one of the symptoms of trauma. It is based on a pilot study which interviewed 17 women, 14 of whom were mothers to 28 children. Mothers reported that many of their children experienced nightmares, bed-wetting, night panics and disrupted sleep patterns. Recovery of the ability to sleep was often slow and uneven with interactive effects between women and children slowing progress.

Disruption prediction at JET [Joint European Torus]

The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus), Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. Ollrien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as ?i and q? with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of assigning a disruption probability to every plasma input pattern. The second method determines the novelty of an input pattern by calculating the probability density distribution of successful plasma patterns that have been run at JET. The density distribution is represented as a mixture distribution, and its parameters arc determined using the Expectation-Maximisation method. If the dataset, used to determine the distribution parameters, covers sufficiently well the machine operational space. Then, the patterns flagged as novel can be regarded as patterns belonging to a disrupting plasma. Together with these methods, a network has been designed to predict the vertical forces, that a disruption can cause, in order to avoid that too dangerous plasma configurations are run. This network can be run before the pulse using the pre-programmed plasma configuration or on line becoming a tool that allows to stop dangerous plasma configuration. All these methods have been implemented in real time on a dual Pentium Pro based machine. The Disruption Prediction and Prevention System has shown that internal plasma parameters can be determined on-line with a good accuracy. Also the disruption detection algorithms showed promising results considering the fact that JET is an experimental machine where always new plasma configurations are tested trying to improve its performances.

Control of the endocrine pancreas by gastrointestinal peptides

This thesis concerns the mechanism through which enteral delivery of glucose results in a larger insulin response than an equivalent parenteral glucose load. Preliminary studies in which mice received a glucose solution either intragastrically or intraperitoneally confirmed this phenomenon. An important regulatory system in this respect is the entero-insular axis, through which insulin secretion is influenced by neural and endocrine communication between the gastrointestinal tract and the pancreatic islets of Langerhans. Using an in vitro system involving static incubation of isolated (by collagenase digestion) islets of Langerhans, the effect of a variety of gastrointestinal peptides on the secretion of the four main islet hormones, namely insulin, glucagon, somatostatin and pancreatic polypeptide, was studied. The gastrointestinal peptides investigated in this study were the secretin family, comprising secretin, glucagon, gastric inhibitory polypeptide (GIP), vasoactive intestinal polypeptide (VIP), peptide histidine isoleucine (PHI) and growth hormone releasing factor (GRF). Gastrin releasing peptide (GRP) was also studied. The results showed that insulin release was stimulated by all peptides studied except PHI, glucagon release was stimulated by all peptides tested, except GRF which suppressed glucagon release, somatostatin release was stimulated by GIP and GRF but suppressed by VIP, PHI, glucagon and secretin, and PP release was stimulated by GIP and GRF, but suppressed by PHI. The insulinotropic effect of GRP was investigated further. A perifusion system was used to examine the time-course of insulin release from isolated islets after stimulation with GRP. GRP was shown to be insulinotropic only in the presence of physiologically elevated glucose concentrations and both first and second phases of insulin release were augmented. There was no effect at substimulatory or very high glucose concentrations. Studies using a cultured insulin-secreting islet cell line, the RINm5F cell line, were undertaken to elucidate the intracellular mechanism of action of GRP. This peptide did not enhance insulin release via an augmentation of glucose metabolism, or via the adenylate cyclase/cyclic AMP secondary messenger system. The pattern of changes of cytosolic free calcium in response to GRP, which involved both mobilization of intracellular stores and an influx of extracellular calcium, suggested the involvement of phosphatidylinositol bisphosphate breakdown as a mediator of the effect of GRP on insulin secretion.

Adrenomedullin and calcitonin gene-related peptide receptors in endocrine-related cancers:opportunities and challenges

Adrenomedullin (AM), adrenomedullin 2 (AM2/intermedin) and calcitonin gene-related peptide (CGRP) are members of the calcitonin family of peptides. They can act as growth or survival factors for a number of tumours, including those that are endocrine-related. One mechanism through which this occurs is stimulating angiogenesis and lymphangiogenesis. AM is expressed by numerous tumour types and for some cancers, plasma AM levels can be correlated with the severity of the disease. In cancer models, lowering AM content or blocking AM receptors can reduce tumour mass. AM receptors are complexes formed between a seven transmembrane protein, calcitonin receptor-like receptor and one of the two accessory proteins, receptor activity-modifying proteins (RAMPs) 2 or 3 to give the AM1 and AM2 receptors respectively. AM also has affinity at the CGRP receptor, which uses RAMP1. Unfortunately, due to a lack of selective pharmacological tools or antibodies to distinguish AM and CGRP receptors, the precise receptors and signal transduction pathways used by the peptides are often uncertain. Two other membrane proteins, RDC1 and L1/G10D (the 'ADMR'), are not currently considered to be genuine CGRP or AM receptors. In order to properly evaluate whether AM or CGRP receptor inhibition has a role in cancer therapy, it is important to identify which receptors mediate the effects of these peptides. To effectively distinguish AM1 and AM2 receptors, selective receptor antagonists need to be developed. The development of specific CGRP receptor antagonists suggests that this is now feasible.

Disruption of the interaction between PMCA2 and calcineurin triggers apoptosis and enhances paclitaxel-induced cytotoxicity in breast cancer cells

Cancer is caused by defects in the signalling mechanisms that govern cell proliferation and apoptosis. It is well known that calcium-dependent signalling pathways play a critical role in cell regulation. A tight control of calcium homeostasis by transporters and channel proteins is required to assure a proper functioning of the calcium-sensitive signal transduction pathways that regulate cell growth and apoptosis. The Plasma Membrane Calcium ATPase 2 (PMCA2) has been recently identified as a negative regulator of apoptosis that can play a significant role in cancer progression by conferring cells resistance to apoptosis. We have previously reported an inhibitory interaction between PMCA2 and the calcium-activated signalling molecule calcineurin in breast cancer cells. Here we demonstrate that disruption of the PMCA2/calcineurin interaction in a variety of human breast cancer cells results in activation of the calcineurin/NFAT pathway, up-regulation in the expression of the pro-apoptotic protein Fas Ligand, and in a concomitant loss of cell viability. Reduction in cell viability is the consequence of an increase in cell apoptosis. Impairment of the PMCA2/calcineurin interaction enhances paclitaxel-mediated cytotoxicity of breast tumoral cells. Our results suggest that therapeutic modulation of the PMCA2/calcineurin interaction might have important clinical applications to improve current treatments for breast cancer patients.

The propensity to disrupt and the disruption nucleolus of a characteristic function game

Gately [1974] recently introduced the concept of an individual player's “propensity to disrupt” a payoff vector in a three-person characteristic function game. As a generalisation of this concept we propose the “disruption nucleolus” of ann-person game. The properties and computational possibilities of this concept are analogous to those of the nucleolus itself. Two numerical examples are given.

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

The challenges of representing human behaviour in simulation models:some case examples from supply chain, evacuation modelling and rail disruption

As more of the economy moves from traditional manufacturing to the service sector, the nature of work is becoming less tangible and thus, the representation of human behaviour in models is becoming more important. Representing human behaviour and decision making in models is challenging, both in terms of capturing the essence of the processes, and also the way that those behaviours and decisions are or can be represented in the models themselves. In order to advance understanding in this area, a useful first step is to evaluate and start to classify the various types of behaviour and decision making that are required to be modelled. This talk will attempt to set out and provide an initial classification of the different types of behaviour and decision making that a modeller might want to represent in a model. Then, it will be useful to start to assess the main methods of simulation in terms of their capability in representing these various aspects. The three main simulation methods, System Dynamics, Agent Based Modelling and Discrete Event Simulation all achieve this to varying degrees. There is some evidence that all three methods can, within limits, represent the key aspects of the system being modelled. The three simulation approaches are then assessed for their suitability in modelling these various aspects. Illustration of behavioural modelling will be provided from cases in supply chain management, evacuation modelling and rail disruption.