Referral to hospital in Nepal: 4 years' experience in one rural district

Formal referral systems have been proposed as a strategy to improve access to secondary care, yet their implementation can be problematic. This paper describes data from referrals in one rural district in Nepal over a four year period. Whilst the characteristics of those patients attending hospital after referral were similar to those described in other developing countries, the rate (1.0 per 1,000 population per year) is much lower, especially when compared to estimated need. Geographical and other barriers to access to secondary care in rural Nepal are discussed

Rebuilding health care in Iraq

The effects of three wars within 25 years, a decade of international sanctions, and a brutal regime have had tragic consequences on Iraq’s health system and on the health of the Iraqi people. While the scale of these problems is becoming clearer, it has been difficult in the current security situation to know how best to respond to requests for help. A workshop organised by the International Committee of the Faculty of Public Health (FPH) in November 2003 has now addressed this very issue. This paper describes the health service needs presented at the workshop by representatives from the Department for International Development (DFID), World Health Organisation (WHO), International Non-Governmental Organisations (INGOs) and, most importantly, Iraq’s Ministry of Health. We will also consider current responses and how professional public health bodies from around the world might contribute to the development of Iraq’s health sector

Unordered Tuples in Quantum Computation

It is well known that the C*-algebra of an ordered pair of qubits is M_2 (x) M_2. What about unordered pairs? We show in detail that M_3 (+) C is the C*-algebra of an unordered pair of qubits. Then we use Schur-Weyl duality to characterize the C*-algebra of an unordered n-tuple of d-level quantum systems. Using some further elementary representation theory and number theory, we characterize the quantum cycles. We finish with a characterization of the von Neumann algebra for unordered words.Comment: In Proceedings QPL 2015, arXiv:1511.0118

Information recovery from rank-order encoded images

The time to detection of a visual stimulus by the primate eye is recorded at 100 – 150ms. This near instantaneous recognition is in spite of the considerable processing required by the several stages of the visual pathway to recognise and react to a visual scene. How this is achieved is still a matter of speculation. Rank-order codes have been proposed as a means of encoding by the primate eye in the rapid transmission of the initial burst of information from the sensory neurons to the brain. We study the efficiency of rank-order codes in encoding perceptually-important information in an image. VanRullen and Thorpe built a model of the ganglion cell layers of the retina to simulate and study the viability of rank-order as a means of encoding by retinal neurons. We validate their model and quantify the information retrieved from rank-order encoded images in terms of the visually-important information recovered. Towards this goal, we apply the ‘perceptual information preservation algorithm’, proposed by Petrovic and Xydeas after slight modification. We observe a low information recovery due to losses suffered during the rank-order encoding and decoding processes. We propose to minimise these losses to recover maximum information in minimum time from rank-order encoded images. We first maximise information recovery by using the pseudo-inverse of the filter-bank matrix to minimise losses during rankorder decoding. We then apply the biological principle of lateral inhibition to minimise losses during rank-order encoding. In doing so, we propose the Filteroverlap Correction algorithm. To test the perfomance of rank-order codes in a biologically realistic model, we design and simulate a model of the foveal-pit ganglion cells of the retina keeping close to biological parameters. We use this as a rank-order encoder and analyse its performance relative to VanRullen and Thorpe’s retinal model

Information recovery from rank-order encoded images

The work described in this paper is inspired by SpikeNET, a system developed to test the feasibility of using rank-order codes in modelling largescale networks of asynchronously spiking neurons. The rank-order code theory proposed by Thorpe concerns the encoding of information by a population of spiking neurons in the primate visual system. The theory proposes using the order of firing across a network of asynchronously firing spiking neurons as a neural code for information transmission. In this paper we aim to measure the perceptual similarity between the image input to a model retina, based on that originally designed and developed by VanRullen and Thorpe, and an image reconstructed from the rank-order encoding of the input image. We use an objective metric originally proposed by Petrovic to estimate perceptual edge preservation in image fusion which, after minor modifcations, is very much suited to our purpose. The results show that typically 75% of the edge information of the input stimulus is retained in the reconstructed image, and we show how the available information increases with successive spikes in the rank-order code

Constructed wetlands: Prediction of performance with case-based reasoning (part B)

The aim of this research was to assess the treatment efficiencies for gully pot liquor of experimental vertical- flow constructed wetland filters containing Phragmites australis (Cav.) Trin. ex Steud. (common reed) and filter media of different adsorption capacities. Six out of 12 filters received inflow water spiked with metals. For 2 years, hydrated nickel and copper nitrate were added to sieved gully pot liquor to simulate contaminated primary treated storm runoff. The findings were analyzed and discussed in a previous paper (Part A). Case-based reasoning (CBR) methods were applied to predict 5 days at 20°C N-Allylthiourea biochemical oxygen demand (BOD) and suspended solids (SS), and to demonstrate an alternative method of analyzing water quality performance indicators. The CBR method was successful in predicting if outflow concentrations were either above or below the thresholds set for water-quality variables. Relatively small case bases of approximately 60 entries are sufficient to yield relatively high predictions of compliance of at least 90% for BOD. Biochemical oxygen demand and SS are expensive to estimate, and can be cost-effectively controlled by applying CBR with the input variables turbidity and conductivity

An associative memory for the on-line recognition and prediction of temporal sequences

This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been proposed, and different sequence learning models have been analysed according to this framework. The network model is an associative memory with a separate store for the sequence context of a symbol. A sparse distributed memory is used to gain scalability. The context store combines the functionality of a neural layer with a shift register. The sensitivity of the machine to the sequence context is controllable, resulting in different characteristic behaviours. The model can store and predict on-line sequences of various types and length. Numerical simulations on the model have been carried out to determine its properties.Comment: Published in IJCNN 2005, Montreal, Canad