The problem of over-medicalisation: How AOD disease models perpetuate inequity for young people with multiple disadvantage.

Young people who experience multiple disadvantage have been identified as some of the most marginalised and under-serviced people in the alcohol and other drug (AOD) system. In this paper, we draw on a range of research evidence to argue that one of the challenges in responding appropriately to the needs of these young people are models of care which seek to ameliorate 'illness' rather than promote wellness. While disease approaches have some important benefits, overly-medicalised AOD treatment responses also have negative impacts. We argue that disease models rest on understandings of substance use as an individual enterprise and thereby pay insufficient attention to the material disadvantage that shape young people's substance use, creating feelings of shame, failure and a reluctance to return to care if they continue to use. Additionally we draw on literature that shows how disease models construe young people's substance use as compulsive, perpetuating deficit views of them as irrational and failing to account for the specific meanings that young people themselves give to their substance use. By focusing on clinical solutions rather than material and relational ones, medicalised treatment responses perpetuate inequity: they benefit young people whose resources and normative values align with the treatments offered by disease models, but are much less helpful to those who are under-resourced,. We suggest that alternative approaches can be found in First Nations models of care and youth programs that attend to social, cultural, and material wellbeing, making living well the focus of treatment rather than illness amelioration.

Mixed anaerobic thoracic empyema: the first report of Filifactor alocis causing extra-oral disease.

We report on a case of bilateral lung consolidation and thoracic empyema caused by the periodontal pathogens Filifactor alocis and Campylobacter rectus in a patient with chronic dysphagia. This is the first report of Filifactor alocis causing infection at an extra-oral site.

Variable rate vector quantization for medical image compression.

Three techniques for variable-rate vector quantizer design are applied to medical images. The first two are extensions of an algorithm for optimal pruning in tree-structured classification and regression due to Breiman et al. The code design algorithms find subtrees of a given tree-structured vector quantizer (TSVQ), each one optimal in that it has the lowest average distortion of all subtrees of the TSVQ with the same or lesser average rate. Since the resulting subtrees have variable depth, natural variable-rate coders result. The third technique is a joint optimization of a vector quantizer and a noiseless variable-rate code. This technique is relatively complex but it has the potential to yield the highest performance of all three techniques.

Tree-structured vector quantization of CT chest scans: image quality and diagnostic accuracy.

The authors apply a lossy compression algorithm to medical images, and quantify the quality of the images by the diagnostic performance of radiologists, as well as by traditional signal-to-noise ratios and subjective ratings. The authors' study is unlike previous studies of the effects of lossy compression in that they consider nonbinary detection tasks, simulate actual diagnostic practice instead of using paired tests or confidence rankings, use statistical methods that are more appropriate for nonbinary clinical data than are the popular receiver operating characteristic curves, and use low-complexity predictive tree-structured vector quantization for compression rather than DCT-based transform codes combined with entropy coding. The authors' diagnostic tasks are the identification of nodules (tumors) in the lungs and lymphadenopathy in the mediastinum from computerized tomography (CT) chest scans. Radiologists read both uncompressed and lossy compressed versions of images. For the image modality, compression algorithm, and diagnostic tasks the authors consider, the original 12 bit per pixel (bpp) CT image can be compressed to between 1 bpp and 2 bpp with no significant changes in diagnostic accuracy. The techniques presented here for evaluating image quality do not depend on the specific compression algorithm and are useful new methods for evaluating the benefits of any lossy image processing technique.

Effects of fish oil supplementation on apolipoprotein B100 production and lipoprotein metabolism in normolipidaemic males.

OBJECTIVE: To evaluate the effects of four weeks of fish oil supplementation on apolipoprotein B100 production and lipoprotein metabolism in normolipidaemic males. DESIGN AND SUBJECTS: Very low density lipoprotein (VLDL) apolipoprotein B100 (apoB100) kinetics in ten healthy, white males, aged 22-43 y (mean 32 y) were investigated using 13C-leucine technique and gas chromatography-mass spectrometry before and after fish oil supplementation. INTERVENTION: All subjects received 10 g (1.8 g EPA, 1.2 g DHA)/d of fish oil concentrate for four weeks. RESULTS: Fish oil supplementation resulted in a decrease of total plasma VLDL (mean +/- s.d. 1.11 +/- 0.41 vs 0.87 +/- 0.28 mmol/l, P < 0.05) and triacylglycerol concentrations (0.74 +/- 0.27) vs 0.48 +/- 0.21 mmol/l, P < 0.01). VLDL apoB100 pool size was decreased without alteration of the fractional synthetic rate but a significant decrease of apoB100 production (2.23 +/- 0.90 vs 1.54 +/- 0.52 mg/dl/h, P < 0.02). Following fish oil supplementation plasma concentrations of glucose and insulin as well as lipoprotein and hepatic lipase activities were unchanged. Fasting plasma concentrations of non-esterified fatty acid (NEFA) were decreased (0.45 +/- 0.12 vs 0.33 +/- 0.10 mmol/l, P < 0.05). CONCLUSIONS: Dietary supplementation with fish oil in healthy males results in decreased VLDL-triacylglycerol concentrations through a decrease in VLDL particle synthesis. The decrease in NEFA substrate supply also contributes.

Minimum cross-entropy pattern classification and cluster analysis.

This paper considers the problem of classifying an input vector of measurements by a nearest neighbor rule applied to a fixed set of vectors. The fixed vectors are sometimes called characteristic feature vectors, codewords, cluster centers, models, reproductions, etc. The nearest neighbor rule considered uses a non-Euclidean information-theoretic distortion measure that is not a metric, but that nevertheless leads to a classification method that is optimal in a well-defined sense and is also computationally attractive. Furthermore, the distortion measure results in a simple method of computing cluster centroids. Our approach is based on the minimization of cross-entropy (also called discrimination information, directed divergence, K-L number), and can be viewed as a refinement of a general classification method due to Kullback. The refinement exploits special properties of cross-entropy that hold when the probability densities involved happen to be minimum cross-entropy densities. The approach is a generalization of a recently developed speech coding technique called speech coding by vector quantization.

Context-based multiscale classification of document images using wavelet coefficient distributions.

In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as well as fast classification overall-and its use of accumulated context information for improving classification accuracy.

Subband-coded image reconstruction for lossy packet networks.

Transmission of digital subband-coded images over lossy packet networks presents a reconstruction problem at the decoder. This paper presents two techniques for reconstruction of lost subband coefficients, one for low-frequency coefficients and one for high-frequency coefficients. The low-frequency reconstruction algorithm is based on inherent properties of the hierarchical subband decomposition. To maintain smoothness and exploit the high intraband correlation, a cubic interpolative surface is fit to known coefficients to interpolate lost coefficients. Accurate edge placement, crucial for visual quality, is achieved by adapting the interpolation grid in both the horizontal and vertical directions as determined by the edges present. An edge model is used to characterize the adaptation, and a quantitative analysis of this model demonstrates that edges can be identified by simply examining the high-frequency bands, without requiring any additional processing of the low-frequency band. High-frequency reconstruction is performed using linear interpolation, which provides good visual performance as well as maintains properties required for edge placement in the low-frequency reconstruction algorithm. The complete algorithm performs well on loss of single coefficients, vectors, and small blocks, and is therefore applicable to a variety of source coding techniques.

Vector quantization of image subbands: a survey.

Subband and wavelet decompositions are powerful tools in image coding because of their decorrelating effects on image pixels, the concentration of energy in a few coefficients, their multirate/multiresolution framework, and their frequency splitting, which allows for efficient coding matched to the statistics of each frequency band and to the characteristics of the human visual system. Vector quantization (VQ) provides a means of converting the decomposed signal into bits in a manner that takes advantage of remaining inter and intraband correlation as well as of the more flexible partitions of higher dimensional vector spaces. Since 1988, a growing body of research has examined the use of VQ for subband/wavelet transform coefficients. We present a survey of these methods.

Weighted universal image compression.

We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB.

JPEG-compliant perceptual coding for a grayscale image printing pipeline.

We describe a procedure by which Joint Photographic Experts Group (JPEG) compression may be customized for gray-scale images that are to be compressed before they are scaled, halftoned, and printed. Our technique maintains 100% compatibility with the JPEG standard, and is applicable with all scaling and halftoning methods. The JPEG quantization table is designed using frequency-domain characteristics of the scaling and halftoning operations, as well as the frequency sensitivity of the human visual system. In addition, the Huffman tables are optimized for low-rate coding. Compression artifacts are significantly reduced because they are masked by the halftoning patterns, and pushed into frequency bands where the eye is less sensitive. We describe how the frequency-domain effects of scaling and halftoning may be measured, and how to account for those effects in an iterative design procedure for the JPEG quantization table. We also present experimental results suggesting that the customized JPEG encoder typically maintains "near visually lossless" image quality at rates below 0.5 b/pixel (with reference to the number of pixels in the original image) when it is used with bilinear interpolation and either error diffusion or ordered dithering. Based on these results, we believe that in terms of the achieved bit rate, the performance of our encoder is typically at least 20% better than that of a JPEG encoder using the suggested baseline tables.

Bayes risk weighted vector quantization with posterior estimation for image compression and classification.

Classification and compression play important roles in communicating digital information. Their combination is useful in many applications, including the detection of abnormalities in compressed medical images. In view of the similarities of compression and low-level classification, it is not surprising that there are many similar methods for their design. Because some of these methods are useful for designing vector quantizers, it seems natural that vector quantization (VQ) is explored for the combined goal. We investigate several VQ-based algorithms that seek to minimize both the distortion of compressed images and errors in classifying their pixel blocks. These algorithms are investigated with both full search and tree-structured codes. We emphasize a nonparametric technique that minimizes both error measures simultaneously by incorporating a Bayes risk component into the distortion measure used for the design and encoding. We introduce a tree-structured posterior estimator to produce the class posterior probabilities required for the Bayes risk computation in this design. For two different image sources, we demonstrate that this system provides superior classification while maintaining compression close or superior to that of several other VQ-based designs, including Kohonen's (1992) "learning vector quantizer" and a sequential quantizer/classifier design.

The examination and recording of the occlusion: why and how.

Before presenting 'how' the examination and recording of the occlusion may be achieved, some attempt should be made to justify 'why' it is necessary. It may appear to be a strange way of justifying the need to examine the patient's occlusion, but this will initially involve a study of the influences of mandibular movements.

What is occlusion?

The aim of this series of papers is to explore the role of occlusion in dental practice. The range of opinion in the dental profession as to the importance of occlusion is enormous. It is very important that the profession in general and practising dentists in particular have a balanced view of occlusion. This is more important than every patient having a balanced occlusion. The fact that the study of occlusion is characterised by extremes makes it confusing and possibly difficult for individual dentists to find a philosophy which is in line with contemporary good practice supported by evidence from practice-based research.

Good occlusal practice in simple restorative dentistry.

Many theories and philosophies of occlusion have been developed. 1-12 The difficulty in scientifically validating the various approaches to providing an occlusion is that an 'occlusion' can only be judged against the reaction it may or may not produce in a tissue system (eg dental, alveolar, periodontal or articulatory). Because of this, the various theories and philosophies are essentially untested and so lack the scientific validity necessary to make them 'rules'. Often authors will present their own firmly held opinions as 'rules'. This does not mean that these approaches are to be ignored; they are, after all, the distillation of the clinical experience of many different operators over many years. But they are empirical. In developing these guidelines the authors have unashamedly drawn on this body of perceived wisdom, but we would also like to involve and challenge the reader by asking basic questions, and by applying a common sense approach to a subject that can be submerged under a sea of dictate and dogma.

Good occlusal practice in removable prosthodontics.

The loss of teeth may result in patients experiencing problems of a functional, aesthetic and psychological nature. This section addresses the very important subject of occlusal considerations for partial and complete dentures. The occlusion is particularly important given the bearing that occlusal factors have, especially on edentulous patients.

Good occlusal practice in advanced restorative dentistry.

In most patients the existing occlusal scheme will be functional, comfortable and cosmetic; and so if a tooth or teeth need to be restored, the most appropriate way to provide the restoration(s) would be to adopt a 'conformative' approach: that is to provide treatment within the existing envelope of static and dynamic occlusal relationships. There will, however, be situations where the conformative approach cannot be adopted, and this section aims to describe what is 'Good Occlusal Practice' in these circumstances.

Orthodontics and occlusion.

The discipline of orthodontics is directed towards alteration of the occlusion of the teeth and the relationships of the jaws. It is therefore somewhat surprising to find that there is little scientific evidence to support any of the concepts that suggest occlusal goals for orthodontic treatment. Most of the current concepts of orthodontic treatment are based upon personal opinion and retrospective studies. Nevertheless, an attempt is made here to provide a guide to the relationship of orthodontics and the occlusion that is evidence based. Where the evidence is weak, these areas have been highlighted.

Internal consistency of three tests from the Halstead-Reitan neuropsychological battery for older children.

The internal consistency of three neuropsychological tests was examined in a sample of 334 referred children (9-14 years of age). Coefficient alpha was calculated to estimate reliability on the Seashore Rhythm Test (SRT), two forms of the Speech Sounds Perception Test (SSPT), and the Aphasia Screening Test (AST). The standard SSPT appears to have relatively good internal consistency with an average coefficient of.81. The average coefficient for the abbreviated form of the SSPT was considerably lower (i.e.,.73), highlighting the superiority of the standard form in clinical practice. Internal consistency of the SRT was relatively low (i.e.,. 67). This level of reliability may be acceptable in group research and for component tests, but is marginal for independent clinical use. Coefficient alpha for the AST was moderate (i.e.,.77), suggesting adequate reliability for a screening test. These reliability estimates are compared to those obtained in previous studies using these tests in adult samples and with other tests commonly used with children.