Heavier-than-water silicone oil mixture as a long-term tamponade agent:A pilot study

Purpose: To evaluate the tamponade effect on the retina of a heavier-than-water silicone oil mixture and to compare it with the effect of silicone oil. Methods: Prospective, non-randomised, comparative pilot study. Phakic/pseudophakic patients with retinal detachment undergoing vitrectomy with Densiron 68 or silicone oil were recruited. The 'separation volume', defined as the relative volume of the space between intraocular tamponade agent and retina, was estimated using magnetic resonance imaging in both groups and compared. Results: Nine participants were included; 4 received silicone oil and 5 Densiron 68. The mean separation volume was statistically significantly larger in the silicone oil group (0.477 ± 0.419 cm ) than in the Densiron group (0.042 ± 0.013 cm ; p = 0.014). Conclusions: In this study Densiron achieved an excellent tamponade effect in the retina. © 2011 S. Karger AG, Basel.

An optimisation of Gaussian mixture models for integer processing units

This paper investigates sub-integer implementations of the adaptive Gaussian mixture model (GMM) for background/foreground segmentation to allow the deployment of the method on low cost/low power processors that lack Floating Point Unit (FPU). We propose two novel integer computer arithmetic techniques to update Gaussian parameters. Specifically, the mean value and the variance of each Gaussian are updated by a redefined and generalised "round'' operation that emulates the original updating rules for a large set of learning rates. Weights are represented by counters that are updated following stochastic rules to allow a wider range of learning rates and the weight trend is approximated by a line or a staircase. We demonstrate that the memory footprint and computational cost of GMM are significantly reduced, without significantly affecting the performance of background/foreground segmentation.

Fast Convergence of Regularised Region-based Mixture of Gaussians for Dynamic Background Modelling

The momentum term has long been used in machine learning algorithms, especially back-propagation, to improve their speed of convergence. In this paper, we derive an expression to prove the O(1/k2) convergence rate of the online gradient method, with momentum type updates, when the individual gradients are constrained by a growth condition. We then apply these type of updates to video background modelling by using it in the update equations of the Region-based Mixture of Gaussians algorithm. Extensive evaluations are performed on both simulated data, as well as challenging real world scenarios with dynamic backgrounds, to show that these regularised updates help the mixtures converge faster than the conventional approach and consequently improve the algorithm’s performance.

Region-based Mixture of Gaussians Modelling for Foreground Detection in Dynamic Scenes

One of the most widely used techniques in computer vision for foreground detection is to model each background pixel as a Mixture of Gaussians (MoG). While this is effective for a static camera with a fixed or a slowly varying background, it fails to handle any fast, dynamic movement in the background. In this paper, we propose a generalised framework, called region-based MoG (RMoG), that takes into consideration neighbouring pixels while generating the model of the observed scene. The model equations are derived from Expectation Maximisation theory for batch mode, and stochastic approximation is used for online mode updates. We evaluate our region-based approach against ten sequences containing dynamic backgrounds, and show that the region-based approach provides a performance improvement over the traditional single pixel MoG. For feature and region sizes that are equal, the effect of increasing the learning rate is to reduce both true and false positives. Comparison with four state-of-the art approaches shows that RMoG outperforms the others in reducing false positives whilst still maintaining reasonable foreground definition. Lastly, using the ChangeDetection (CDNet 2014) benchmark, we evaluated RMoG against numerous surveillance scenes and found it to amongst the leading performers for dynamic background scenes, whilst providing comparable performance for other commonly occurring surveillance scenes.

A Conditional Approach for Modelling Patient Re-admissions in Hospital using a mixture of Coxian phase-type distributions incorporating Bayes Theorem

The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.

The welfare implications of large litter size in the domestic pig I:Biologica factors

Increasing litter size has long been a goal of pig breeders and producers, and may have implications for pig (Sus scrofa domesticus) welfare. This paper reviews the scientific evidence on biological factors affecting sow and piglet welfare in relation to large litter size. It is concluded that, in a number of ways, large litter size is a risk factor for decreased animal welfare in pig production. Increased litter size is associated with increased piglet mortality, which is likely to be associated with significant negative animal welfare impacts. In surviving piglets, many of the causes of mortality can also occur in non-lethal forms that cause suffering. Intense teat competition may increase the likelihood that some piglets do not gain adequate access to milk, causing starvation in the short term and possibly long-term detriments to health. Also, increased litter size leads to more piglets with low birth weight which is associated with a variety of negative long-term effects. Finally, increased production pressure placed on sows bearing large litters may produce health and welfare concerns for the sow. However, possible biological approaches to mitigating health and welfare issues associated with large litters are being implemented. An important mitigation strategy is genetic selection encompassing traits that promote piglet survival, vitality and growth. Sow nutrition and the minimisation of stress during gestation could also contribute to improving outcomes in terms of piglet welfare. Awareness of the possible negative welfare consequences of large litter size in pigs should lead to further active measures being taken to mitigate the mentioned effects. © 2013 Universities Federation for Animal Welfare.

The welfare implications of large litter size in the domestic pig II:Management factors

Increasing litter size has long been a goal of pig (Sus scrofa domesticus) breeders and producers in many countries. Whilst this has economic and environmental benefits for the pig industry, there are also implications for pig welfare. Certain management interventions are used when litter size routinely exceeds the ability of individual sows to successfully rear all the piglets (ie viable piglets outnumber functional teats). Such interventions include: tooth reduction; split suckling; cross-fostering; use of nurse sow systems and early weaning, including split weaning; and use of artificial rearing systems. These practices raise welfare questions for both the piglets and sow and are described and discussed in this review. In addition, possible management approaches which might mitigate health and welfare issues associated with large litters are identified. These include early intervention to provide increased care for vulnerable neonates and improvements to farrowing accommodation to mitigate negative effects, particularly for nurse sows. An important concept is that management at all stages of the reproductive cycle, not simply in the farrowing accommodation, can impact on piglet outcomes. For example, poor stockhandling at earlier stages of the reproductive cycle can create fearful animals with increased likelihood of showing poor maternal behaviour. Benefits of good sow and litter management, including positive human-animal relationships, are discussed. Such practices apply to all production situations, not just those involving large litters. However, given that interventions for large litters involve increased handling of piglets and increased interaction with sows, there are likely to be even greater benefits for management of hyper-prolific herds. © 2013 Universities Federation for Animal Welfare.

Effects of mixture of nanoparticles under different salinity in the clams Ruditapes philippinarum and Ruditapes decussatus

Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidadde do Algarve, 2015

Selection and combination of biomarkers to control and prevent the risk of occupational exposure to the mixture of lead, arsenic and manganese

Tese de doutoramento, Farmácia (Toxicologia), Universidade de Lisboa, Faculdade de Farmácia, 2014

Anthropogenic impacts in the deep sea of the Azores : fishing and litter

Tese de Doutoramento em Ciências do Mar, especialidade em Ecologia Marinha.

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.