Hermeneutics: A Literary Interpretive Art

This thesis examines the historical traditions of hermeneutics and its potential to enhance the process of literary interpretation and understanding. The discussion draws from the historical emplotment of hermeneutics as literary theory and method presented in the Norton Anthology of Theory and Criticism with further elaboration from several other texts. The central aim of the thesis is to illuminate the challenges inherent in the literary interpretive arts by investigating select philosophical and linguistic approaches to the study and practice of literary theory and criticism embodied within the canonical works of the Anthology. The narrative begins in ancient Greece, traverses medieval and modern developments in the western literary interpretive arts and closes with a brief survey of twentieth-century writings that form a diverse mosaic of disaggregated literary theory and criticism from several perspectives. The thesis concludes with suggestions for improving the literary interpretive process and forecasts the continuing expansion of the field into new culturally informed topic areas in the decades to follow

A personalized Uncertainty Quantification framework for patient survival models: estimating individual uncertainty of patients with metastatic brain tumors in the absence of ground truth

TodevelopanovelUncertaintyQuantification (UQ) framework to estimate the uncertainty of patient survival models in the absence of ground truth, we developed and evaluated our approach based on a dataset of 1383 patients treated with stereotactic radiosurgery (SRS) for brain metastases between January 2015 and December 2020. Our motivating hypothesis is that a time-to-event prediction of a test patient on inference is more certain given a higher feature-space-similarity to patients in the training set. Therefore, the uncertainty for a particular patient-of-interest is represented by the concordance index between a patient similarity rank and a prediction similarity rank. Model uncertainty was defined as the increased percentage of the max uncertainty-constrained-AUC compared to the model AUC. We evaluated our method on multiple clinically-relevant endpoints, including time to intracranial progression (ICP), progression-free survival (PFS) after SRS, overall survival (OS), and time to ICP and/or death (ICPD), on a variety of both statistical and non-statistical models, including CoxPH, conditional survival forest (CSF), and neural multi-task linear regression (NMTLR). Our results show that all models had the lowest uncertainty on ICP (2.21%) and the highest uncertainty (17.28%) on ICPD. OS models demonstrated high variation in uncertainty performance, where NMTLR had the lowest uncertainty(1.96%)and CSF had the highest uncertainty (14.29%). In conclusion, our method can estimate the uncertainty of individual patient survival modeling results. As expected, our data empirically demonstrate that as model uncertainty measured via our technique increases, the similarity between a feature-space and its predicted outcome decreases

Plasma Dynamics

Contains research objectives and summary of research on twenty-one projects split into three sections, with four sub-sections in the second section and reports on twelve research projects.National Science Foundation (Grant ENG75-06242)U.S. Energy Research and Development Administration (Contract E(11-1)-2766)U.S. Energy Research and Development Agency (Contract E(11-1)-3070)U.S. Energy Research and Development Administration (Contract E(11-1)-3070)Research Laboratory of Electronics, M.I.T. Industrial Fellowshi

In vitro antibacterial activity and acute toxicity studies of aqueous-methanol extract of Sida rhombifolia Linn. (Malvaceae)

<p>Abstract</p> <p>Background</p> <p>Many bacteria among the Enterobacteria family are involved in infectious diseases and diarrhoea. Most of these bacteria become resistant to the most commonly used synthetic drugs in Cameroon. Natural substances seem to be an alternative to this problem. Thus the aim of this research was to investigate the <it>in vitro </it>antibacterial activity of the methanol and aqueous-methanol extracts of <it>Sida rhombifolia </it>Linn (Malvaceae) against seven pathogenic bacteria involved in diarrhoea. Acute toxicity of the most active extract was determined and major bioactive components were screened.</p> <p>Methods</p> <p>The agar disc diffusion and the agar dilution method were used for the determination of inhibition diameters and the Minimum Inhibitory Concentration (MICs) respectively. The acute toxicity study was performed according WHO protocol.</p> <p>Results</p> <p>The aqueous-methanol extract (1v:4v) was the most active with diameters of inhibition zones ranging from 8.7 - 23.6 mm, however at 200 μg/dic this activity was relatively weak compared to gentamycin. The MICs of the aqueous-methanol extract (1v:4v) varied from 49.40 to 78.30 μg/ml. <it>Salmonella dysenteriae </it>was the most sensitive (49.40 μg/ml). For the acute toxicity study, no deaths of rats were recorded. However, significant increase of some biochemical parameters such as aspartate amino-transferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP) and creatinine (CRT) were found. The phytochemical analysis of the aqueous methanol extract indicated the presence of tannins, polyphenols, alkaloids, glycosides, flavonoids and saponins</p> <p>Conclusion</p> <p>The results showed that the aqueous-methanol extract of <it>S. rhombifolia </it>exhibited moderate antibacterial activity. Some toxic effects were found when rats received more than 8 g/kg bw of extract.</p> <p><it>Antibacterial; Enterobacteria; Acute toxicity; Phytochemical analysis</it></p

A Multi-Institutional Meningioma MRI Dataset for Automated Multi-Sequence Image Segmentation

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients