REFORMED PRISONER OR PRISON REFORM?: AN ACCOUNT OF OSCAR WILDE’S CARCERAL WRITINGS (1895-1900)

The present paper aims at sifting through Oscar Wilde’s carceral/post-carceral writings: De Profundis (1905), The Ballad of Reading Gaol (1898), and The Daily Chronicle’s letters (1897-8) in order to pinpoint how Oscar Wilde’s literary voice, during incarceration, transformed from that of an aesthete, or a witty writer into an uncompromising prison reform activist, remaining actively engaged in mounting a propaganda tool against the desperate plight and hardship of the late nineteenth-century penal system, and accordingly, calling for the necessity of implementing major penal reformations as a retaliatory measure. The overriding question concerning this paper, therefore, will center on ‘How prison reformed Oscar Wilde’, and ‘How Oscar Wilde reformed prison’ from every conceivable angle to explore the fact that Oscar Wilde is worthy of consideration in the way in which he was affected in prison and solitary confinement and how he summoned strength to cope with the deprivations of prison life as well as implementing his recommendations to help reform prison, which were incorporated in the 1898 Prison Act

Effects of Root Debridement With Hand Curettes and Er:YAG Laser on Chemical Properties and Ultrastructure of Periodontally-Diseased Root Surfaces Using Spectroscopy and Scanning Electron Microscopy

Introduction: The efficacy of erbium-doped yttrium aluminum garnet (Er:YAG) laser for root debridement in comparison with curettes has been the subject of many recent investigations. Considering the possibility of chemical and ultra-structural changes in root surfaces following laser irradiation, this study sought to assess the effects of scaling and root planing (SRP) with curettes and Er:YAG laser on chemical properties and ultrastructure of root surfaces using spectroscopy and scanning electron microscopy (SEM).Methods: In this in vitro experimental study, extracted sound human single-rooted teeth (n = 50) were randomly scaled using manual curettes alone or in conjunction with Er:YAG laser at 100 and 150 mJ/pulse output energies. The weight percentages of carbon, oxygen, phosphorous and calcium remaining on the root surfaces were calculated using spectroscopy and the surface morphology of specimens was assessed under SEM. Data were analyzed using one-way analysis of variance (ANOVA).Results: No significant differences (P > 0.05) were noted in the mean carbon, oxygen, phosphorous and calcium weight percentages on root surfaces following SRP using manual curettes with and without laser irradiation at both output energies. Laser irradiation after SRP with curettes yielded rougher surfaces compared to the use of curettes alone.Conclusion: Although laser irradiation yielded rougher surfaces, root surfaces were not significantly different in terms of chemical composition following SRP using manual curettes with and without Er:YAG laser irradiation. Er:YAG laser can be safely used as an adjunct to curettes for SRP

Clasificación de unidades por el método de eficiencia cruzada corregido usando pesos óptimos en el intervalo más pequeño

Un método importante para clasificar las unidades de toma de decisiones (DMU) en el análisis envolvente de datos (DEA) es el método de eficiencia cruzada. Este estudio propone un modelo secundario multiobjetivo para calcular los pesos óptimos con la menor dispersión. En primer lugar, estos pesos se colocan en el intervalo más pequeño. En segundo lugar, la eficiencia cruzada de cada una de las otras unidades tiene la menor desviación de la eficiencia CCR de la misma unidad. Por tanto, se obtienen pesos óptimos que tienen la menor dispersión. Como resultado, se evitan en la medida de lo posible las ponderaciones óptimas cero que conducen a la trivialidad del índice relevante. Por lo tanto, utilizando la eficiencia cruzada promedio, los resultados de la clasificación serían más razonables. Utilizando el modelo propuesto para la clasificación de seis hogares de ancianos, los resultados muestran que este modelo es más preciso. Finalmente, con el fin de mejorar el desempeño del servicio de urgencias de un hospital, se utiliza el modelo propuesto para clasificar 11 escenarios definidos

Clasificación de unidades por el método de eficiencia cruzada corregido usando pesos óptimos en el intervalo más pequeño

An important method for ranking of decision making units (DMUs) in data envelopment analysis (DEA) is cross-efficiency method. This study proposes a secondary multi-objective model for calculating optimal weights with least dispersion. Firstly, these weights are placed in the smallest interval. Secondly, the cross-efficiency of each of the other units has the least deviation from the CCR efficiency of the same unit. Therefore, optimal weights are obtained which have the least dispersion. As result, the zero optimal weights which lead to the triviality of the relevant index, are avoided as far as possible. Hence, using the average cross-efficiency, the results of the ranking would be more reasonable. Using the proposed model for ranking of six nursing homes, the results show that this model is more accurate. Finally, in order to improve performance of the emergency department of a hospital, the proposed model is used to rank 11 defined scenarios.Un método importante para clasificar las unidades de toma de decisiones (DMU) en el análisis envolvente de datos (DEA) es el método de eficiencia cruzada. Este estudio propone un modelo secundario multiobjetivo para calcular los pesos óptimos con la menor dispersión. En primer lugar, estos pesos se colocan en el intervalo más pequeño. En segundo lugar, la eficiencia cruzada de cada una de las otras unidades tiene la menor desviación de la eficiencia CCR de la misma unidad. Por tanto, se obtienen pesos óptimos que tienen la menor dispersión. Como resultado, se evitan en la medida de lo posible las ponderaciones óptimas cero que conducen a la trivialidad del índice relevante. Por lo tanto, utilizando la eficiencia cruzada promedio, los resultados de la clasificación serían más razonables. Utilizando el modelo propuesto para la clasificación de seis hogares de ancianos, los resultados muestran que este modelo es más preciso. Finalmente, con el fin de mejorar el desempeño del servicio de urgencias de un hospital, se utiliza el modelo propuesto para clasificar 11 escenarios definidos

Clasificación de unidades por el método de eficiencia cruzada corregido usando pesos óptimos en el intervalo más pequeño

An important method for ranking of decision making units (DMUs) in data envelopment analysis (DEA) is cross-efficiency method. This study proposes a secondary multi-objective model for calculating optimal weights with least dispersion. Firstly, these weights are placed in the smallest interval. Secondly, the cross-efficiency of each of the other units has the least deviation from the CCR efficiency of the same unit. Therefore, optimal weights are obtained which have the least dispersion. As result, the zero optimal weights which lead to the triviality of the relevant index, are avoided as far as possible. Hence, using the average cross-efficiency, the results of the ranking would be more reasonable. Using the proposed model for ranking of six nursing homes, the results show that this model is more accurate. Finally, in order to improve performance of the emergency department of a hospital, the proposed model is used to rank 11 defined scenarios.Un método importante para clasificar las unidades de toma de decisiones (DMU) en el análisis envolvente de datos (DEA) es el método de eficiencia cruzada. Este estudio propone un modelo secundario multiobjetivo para calcular los pesos óptimos con la menor dispersión. En primer lugar, estos pesos se colocan en el intervalo más pequeño. En segundo lugar, la eficiencia cruzada de cada una de las otras unidades tiene la menor desviación de la eficiencia CCR de la misma unidad. Por tanto, se obtienen pesos óptimos que tienen la menor dispersión. Como resultado, se evitan en la medida de lo posible las ponderaciones óptimas cero que conducen a la trivialidad del índice relevante. Por lo tanto, utilizando la eficiencia cruzada promedio, los resultados de la clasificación serían más razonables. Utilizando el modelo propuesto para la clasificación de seis hogares de ancianos, los resultados muestran que este modelo es más preciso. Finalmente, con el fin de mejorar el desempeño del servicio de urgencias de un hospital, se utiliza el modelo propuesto para clasificar 11 escenarios definidos

Study of Helicobacter pylori genotype status in cows, sheep, goats and human beings

BACKGROUND: Helicobacter pylori is one of the most controversial bacteria in the world causing diverse gastrointestinal diseases. The transmission way of this bacterium still remains unknown. The possibility of zoonotic transmission of H. pylori has been suggested, but is not proven in nonprimate reservoirs. In the current survey, we investigate the presence of H. pylori in cow, sheep and goat stomach, determine the bacterium virulence factors and finally compare the human H. pylori virulence factors and animals in order to examine whether H. pylori might be transmitted from these animals to human beings. METHODS: This cross- sectional study was performed on 800 gastric biopsy specimens of cows, sheep, goats and human beings. The PCR assays was performed to detection of H. pylori, vacA and cagA genes. The PCR products of Ruminant’s samples with positive H. pylori were subjected to DNA sequencing analysis. Statistical tests were applied for data analysis. RESULTS: Overall 6 (3%) cows, 32 (16%) sheep and 164 (82%) human beings specimens were confirmed to be H. pylori positive; however we were not able to detect this bacterium in all 200 goat samples. The vacA s1a/m1a was the predominant H. pylori genotype in all three kinds of studied population. There was 3.4–8.4% variability and 92.9-98.5% homology between sheep and human samples. CONCLUSIONS: Considering the high sequence homology among DNA of H. pylori isolated from sheep and human, our data suggest that sheep may act as a reservoir for H. pylori and in the some extent share the ancestral host for the bacteria with human

Numerical modelling of a high temperature borehole thermal energy storage system: Norway case study

Global warming is threatening life on earth. Utilising renewable energy is considered as the most effective measure to minimise anthropogenic CO2 emissions. High-temperature borehole thermal energy storage (BTES) systems have a world-wide potential to reduce energy consumption, increase energy utilisation of waste heat and provide efficient seasonal heat storage. Hybrid application of BTES and solar energy leads to net zero emissions. In this study HT-BTES is evaluated for seasonal thermal heat storage and recovery. To this end, a CMG STARS model was built and validated using the existing 100-wells BTES system in Norway. Then, the model was used to evaluate BTES thermal performance and thermal recovery efficiency. Sensitivity analysis was also conducted to study the dynamics of storage temperature in the BTES under different operating conditions, such as heat carrier flow rate, injection temperature, and charging period. Results of this case study show that the model-predicted temperatures during charging and discharging are in good agreement with the existing BTES system. In 5 years of operation, 35.5% of the heat injected into the BTES system was recovered, while the significant heat remained in the borehole region and lost to surrounding rock (64.5%). BTES was found very sensitive to flow rate, the charging period and injection temperature. Borehole depth has a minimal effect on BTES storage temperature at constant studied injection temperature.publishedVersio

Numerical Simulation of the Early Stages of Glaucoma in Human Eye

Background: The eye is one of the most vital organs of human body, and glaucoma is the second-leading cause of blindness after cataracts in the world. However, glaucoma is the leading cause of preventable blindness. The main objective of this study is to investigate intraocular pressure (IOP), stress, strain, and deformation in the retina in early stages of glaucoma. Methods: In this study, a model of the human eye is numerically investigated. The aqueous humor pressure is considered as 30, 35, and 40 mmHg and compared with normal eye pressure. The problem is considered as transient 3D and accurate. Comparison between obtained results shows that the model has been applied. Eye components are also considered with their real properties. Due to the inappreciable effects of turbulence and temperature variation, these effects have been neglected. To determine the pressure field, a two-way fluid-structure interaction is applied, and then, the results are used in a one-way fluid-structure interaction to determine the amount of stress, strain, and deformation of the retina. Results: The maximum deformation in the retina of a glaucoma patient is about 0.33 mm higher than a normal eye, the maximum stress is about 1,300 Pa higher than a normal eye, and the maximum strain is about 0.06 higher than a normal eye. Conclusion: In patients with increased IOP, the amount of deformation in the retina has increased, and the maximum deformation occurs near the optic disc in all cases. Furthermore, maximum stress and maximum strain occur at the place of maximum deformation

GOLD: Generalized Knowledge Distillation via Out-of-Distribution-Guided Language Data Generation

Knowledge distillation from LLMs is essential for the efficient deployment of language models. Prior works have proposed data generation using LLMs for preparing distilled models. We argue that generating data with LLMs is prone to sampling mainly from the center of original content distribution. This limitation hinders the distilled model from learning the true underlying data distribution and to forget the tails of the distributions (samples with lower probability). To this end, we propose GOLD, a task-agnostic data generation and knowledge distillation framework, which employs an iterative out-of-distribution-guided feedback mechanism for the LLM. As a result, the generated data improves the generalizability of distilled models. An energy-based OOD evaluation approach is also introduced to deal with noisy generated data. Our extensive experiments on 10 different classification and sequence-to-sequence tasks in NLP show that GOLD respectively outperforms prior arts and the LLM with an average improvement of 5% and 14%. We will also show that the proposed method is applicable to less explored and novel tasks. The code is available