Optical IP switching a solution to dynamic lightpath establishment in disaggregated network architectures

The landscape of the telecommunications environment is constantly evolving; in terms of architecture and increasing data-rate. Ensuring that routing decisions are taken at the lowest possible layer offers the possibility of greatest data throughput. We propose using wavelengths in a DWDM scheme as dedicated channels that bypass the routing lookup in a router. The future trend of telecommunications industry is, however, toward larger numbers of interlinked competing operator networks. This in turn means there is a lack of a unified control plane to allow current networks to dynamically provision optical paths. This paper will report on the concept of optical IP switching. This concept seeks to address optical control plane issues in disaggregated networks while providing a means to dynamically provision optical paths to cater for large data flows

The in vitro and in vivo anti-tumour activity of N-AcMEL-(Fab')2 conjugates.

To increase the accessibility of drug-antibody complexes to tumours and to decrease non-specific binding via Fc receptors N-acetyl-melphalan (N-AcMEL) was conjugated to F(ab')2 fragments. These fragments were synthesised by pepsin degradation of IgG MoAb. Up to 20 molecules of N-AcMEL could be successfully coupled to each F(ab')2 fragment (compared with 25 molecules/intact IgG) with retention of both drug and antibody activity. The N-AcMEL-F(ab')2 conjugates demonstrated specific cytotoxicity in vitro however despite the absence of non specific Fc receptor binding and greater permeability when using F(ab')2 fragments, the N-AcMEL-F(ab')2 and N-AcMEL-IgG conjugates had similar anti-tumour activity in vivo. Conjugates made with whole IgG and F(ab')2 were equally effective in eradicating subcutaneous solid tumours in mice when injected intravenously. The lower immunogenicity of F(ab')2 fragments compared with whole IgG and the similar cytotoxicity of their conjugates, suggests that the F(ab')2 conjugate has greater clinical utility

Implications for telehealth for accessing education in rural areas: children with a severe chronic disease.

Children and their families who live in rural and remote areas are often disadvantaged by distance. In healthcare, this can be especially problematic. Children can suffer from a range of chronic conditions, e.g. diabetes, asthma, cardiac conditions, cystic fibrosis and others. In Australia, health services for children and families with such conditions are centred in specialist children’s hospitals in the capital cities in each state, but the burden of health care often falls to the parents and the children themselves. While rural health services do a wonderful job providing health care for these children, it is very rare to find specialist services in any rural situation. For example, children with cystic fibrosis who live in remote parts of Queensland attend specialist clinics in their local hospital twice or three times a year for routine check-ups, when the cystic fibrosis team of nurses, doctors and allied health staff from the children’s hospital in Brisbane travels to rural areas. If children become acutely ill, they might be able to be treated in the local hospital if they are not too sick, or they could be taken to the children’s hospital in Brisbane by their parents. If they are having a serious exacerbation of the illness, they will be transported there by aircraft and ambulance. Any child being sick is stressful for the family, regardless of where they live. However, if families live thousands of kilometres from the main treatment centres, scenarios described above can be common, with subsequent family disruption and emotional, social and economic costs. Telehealth is being installed in many rural and remote health services, thereby allowing country families the benefit of specialist consultation and care. However, governments and health departments are only slowly engaging with such technology. This paper presents findings of a study in Far North Queensland which examined how care was delivered to rural and remote families with children with cystic fibrosis, and how they cope. It will discuss how telehealth could improve care to such families and pose questions about why this is so slow in being implemented in Australia

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios.Comment: This revised version fixes two small typos in the published versio

Secondary literacy across the curriculum: Challenges and possibilities

This paper discusses the challenges and possibilities attendant upon successfully implementing literacy across the curriculum initiatives – or ‘school language policies’ as they have come to be known - particularly at the secondary or high school level. It provides a theoretical background to these issues, exploring previous academic discussions of school language policies, and highlights key areas of concern as well as opportunity with respect to school implementation of such policies. As such, it provides a necessary conceptual background to the subsequent papers in this special issue, which focus upon the Secondary Schools’ Literacy Initiative (SSLI) – a New Zealand funded programme that aims to establish cross-curricular language and literacy policies in secondary schools

Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

We express the mean and variance terms in a double exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the model, and whether they enter linearly or flexibly. When the variance term is null we obtain a generalized additive model, which becomes a generalized linear model if the predictors enter the mean linearly. The model is estimated using Markov chain Monte Carlo simulation and the methodology is illustrated using real and simulated data sets.Comment: 8 graphs 35 page

Will the COVID-19 pandemic transform infection prevention and control in surgery? Seeking leverage points for organizational learning

Abstract Background In response to the coronavirus disease of 2019 (COVID-19) pandemic, healthcare systems worldwide have stepped up their infection prevention and control efforts in order to reduce the spread of the infection. Behaviours, such as hand hygiene, screening and cohorting of patients, and the appropriate use of antibiotics have long been recommended in surgery, but their implementation has often been patchy. Methods The current crisis presents an opportunity to learn about how to improve infection prevention and control and surveillance (IPCS) behaviours. The improvements made were mainly informal, quick and stemming from the frontline rather than originating from formal organizational structures. The adaptations made and the expertise acquired have the potential for triggering deeper learning and to create enduring improvements in the routine identification and management of infections relating to surgery. Results This paper aims to illustrate how adopting a human factors and ergonomics perspective can provide insights into how clinical work systems have been adapted and reconfigured in order to keep patients and staff safe. Conclusion For achieving sustainable change in IPCS practices in surgery during COVID-19 and beyond we need to enhance organizational learning potentials