Automated detection of actinic keratoses in clinical photographs

Backgroun

'Ain't it a Ripping Night': Alcoholism and the Legacies of Empire in Salman Rushdie's Midnight's Children.

In the era of decolonisation that followed the Second World War, various authors sought to engage with India and the Empire’s past anew throughout their novels, identifying medicine and illness as key parts of Imperial authority and colonial experience. Salman Rushdie’s approach to the Raj in Midnight’s Children (1981) focused on the broad sweep of colonial life, juxtaposing the political and the personal. This article argues that Rushdie explores the history of colonial India by employing alcohol and alcoholism as lenses through which to explore the cultural, political and medical legacies of Empire. Through analysis of Midnight’s Children as well as a range of medical sources related to alcohol and inebriation, it will illustrate how drinking is central to Rushdie’s approach to secular and religious identities in newly independent India, as well as a means of satirising and undermining the supposed benefit that Empire presented to India and Indians

Centralising Qualitative Research in Big Data Methods Through Algorithmic Ethnography

Responding to the challenge for qualitative researchers to claim a central place in conversations about big data, analytics, datafication, data mining and the role of algorithms, this article describes a mixed-method research partnership focused on algorithmic ethnography. In the debates about the opacity of online algorithms, qualitative researchers typically advocate for access to code. This standard discourse centralises the technical aspects of big data and networked ethnographies. Instead, this article outlines a research methodology that analyses algorithmic discourses by working alongside the technical expertise of data scientists and utilizes the affordability of big data methods to do qualitative work. The potential for qualitative research skills to investigate the underlying technical processes that frame online social interactions is proposed as a way to place how people understand the world at the centre of big data research

Computational methods in skin confocal microscopy

Interest in clinical use of reflectance confocal microscopy (RCM) has recently been increased, with its successful demonstration of effectiveness in diagnostic and surgical guidance. However, this initial success is currently limited to experienced clinicians, who adopted RCM imaging at early stages and have been using it for research and clinical screening purposes for a while. On the other hand, a majority of the new cohort of users is rather interested in using RCM mostly in clinical practice, where time pressure and strict regulations exist. The current system is manual and depends highly on the experience of the users. This typically leads to variability both in RCM image acquisition and analysis. Therefore, standardized protocols for rapid and consistent imaging as well as standardized image analysis tools to guide patient care must be developed. Beyond the medical needs for such procedures that are described in the other chapters, in this chapter, we will further look into the technical side of the problem and demonstrate how the clinical needs can be dealt with using computer-aided tools, such as computer vision and machine learning algorithms

sections_500

This file contains the complete dataset of en-face sections at a resolution of 500x500 pixels. This file contains one dataset called 'sections' - this is a three dimensional array of uint8 values. The first axis is individual sections in the dataset. The second and third axes are the rows and columns of intensity values of that section

Segmentation of skin strata in reflectance confocal microscopy depth stacks

Reflectance confocal microscopy is an emerging tool for imaging human skin, but currently requires expert human assessment. To overcome the need for human experts it is necessary to develop automated tools for automatically assessing reflectance confocal microscopy imagery

crustal fracturing field and presence of fluid as revealed by seismic anisotropy: case-histories from seismogenic areas in the Apennines

During the last decades, the study of seismic anisotropy has provided useful information for the interpretation and evaluation of the stress field and active crustal deformation. Seismic anisotropy can yield valuable information on upper crustal structure, fracture field, and presence of fluid-saturated rocks crossed by shear waves. Several studies worldwide demonstrate that seismic anisotropy is related to stress-aligned, filled-fluid micro-cracks (EDA model, Crampin et al., 1984b; Crampin, 1993). The seismic anisotropy is an almost ubiquitous property of the Earth and the Shear Wave Splitting is the most unambiguous indicator of anisotropy, but the automatic estimation of the splitting parameters is difficult because the effect of the anisotropy on a seismogram is a second order, not easily detectable effect. Different researchers developed automated techniques aimed to study the Shear Wave Splitting: in this study, the results of different codes are compared in order to evaluate the best method for automatic anisotropy evaluation. In the last three years, an automatic analysis code, “Anisomat+”, was developed, tested and improved to calculate the anisotropic parameters: fast polarization direction () and delay time (∂t). “Anisomat+” consists of a set of MatLab scripts able to retrieve automatically crustal anisotropy parameters from three-component seismic recordings of local earthquakes. It needs waveforms and hypocentral parameters in the format routinely archived by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The code uses horizontal component cross-correlation method: a mathematical algorithm aimed to measure the similarity of the pulse shape between two shear waves. Anisomat+ has been compared to other two automatic analysis codes (SPY and SHEBA) and tested on three zones of the Apennines (Val d’Agri, Tiber Valley and L’Aquila surroundings). It was observed that, if the number of measures is large enough, at each station the average values of the parameters (fast direction and delay time) are comparable. The main goal in developing of an automatic code was to have tool able to work on a big amount of data, in a short time, by reducing the errors due to the subjectivity. These two acquirements are very useful and are the basis to develop a quasi real-time monitoring of the anisotropic parameters. The anisotropic parameters, resulting from the automatic computation, have been interpreted to determine the fracture field geometries; for each area, I defined the dominant fast direction and the intensity of the anisotropy, interpreting these results in the light of the geological and structural setting and of two anisotropic interpretative models, proposed in the literature. In the first one, proposed by Zinke and Zoback (2000), the local stress field and cracks are aligned by tectonics phases and are not necessarily related to the presently active stress field. Therefore the anisotropic parameters variations are only space-dependent. In the second, EDA model (Crampin, 1993), and its development in the APE model (Zatsepin and Crampin, 1995) fluid-filled micro-cracks are aligned or ‘opened’ by the active stress field and the variation of the stress field might be related to the evolution of the pore pressure in time; therefore in this case the variation of the anisotropic parameters are both space- and time- dependent. I recognized that the average of fast directions, in the three selected areas, are oriented NW-SE, in agreement with the orientation of the active stress field, as suggested by the EDA model, proposed by Crampin (1993), but also, by the proposed by Zinke and Zoback model; in fact, NW-SE direction corresponds also to the strike of the main fault structures in the three study regions. The mean values of the magnitude of the normalized delay time range from 0.005 s/km to 0.007 s/km and to 0.009 s/km, respectively for the L'Aquila (AQU) area, the High Tiber Valley (ATF) and the Val d'Agri (VA), suggesting a 3-4% of crustal anisotropy (Piccinini et al., 2006). In each area are also examined the spatial and temporal distribution of anisotropic parameters, which lead to some innovative observations, listed below. o The higher values of normalized delay times have been observed in those zones where most of the seismic events occur. This aspect was further investigated, by evaluating the average seismic rate, in a time period, between years 2005 and 2010, longer than the lapse of time, analyzed in the anisotropic studies. This comparison has highlighted that the value of the normalised delay time is larger where the seismicity rate is higher. o In the Alto Tiberina Fault area the higher values of normalised delay time are not only related to the presence of a high seismicity rate but also to the presence of a tectonically doubled carbonate succession. Therefore, also the lithology, plays a important role in hosting and preserving the micro-fracture network responsible for the anisotropic field. o The observed temporal variations of anisotropic parameters, have been observed and related to the fluctuation of pore fluid pressure at depth possibly induced by different mechanisms in the different regions, for instance, changes in the water table level in Val D’Agri (Valoroso et al., GJI submitted), occurrence of the April 6th Mw=6.1 earthquake in L’Aquila (Lucente et al., 2010). Since these variations have been recognized, it is possible to affirm that the models that better fit my results, both in term of fast directions and of delay times, seems to be those proposed by Crampin (1993) and Zatsepin & Crampin (1995), respectively EDA and APE models.Università degli studi di PerugiaPublished1.11. TTC - Osservazioni e monitoraggio macrosismico del territorio nazionale3.1. Fisica dei terremoti3.2. Tettonica attiva3.8. Geofisica per l'ambienteope

Microsoft Critic Urges Break-Up

WASHINGTON (CBS.MW) -- U.S. District Court Judge Thomas Penfield Jackson\u27s scathing findings of fact in the Microsoft antitrust case cheered critics of the company that have long maintained the software giant\u27s tactics illegally crushed competitors and stifled innovation

Towards data-driven quantification of skin ageing using reflectance confocal microscopy

Introduction: Evaluation of skin ageing is a non-standardized, subjective process, with typical measures relying coarse, qualitatively defined features. Reflectance confocal microscopy depth stacks contain indicators of both chrono-ageing and photo-ageing. We hypothesize that an ageing scale could be constructed using machine learning and image analysis, creating a data-driven quantification of skin ageing without human assessment. Methods: En-face sections of reflectance confocal microscopy depth stacks from the dorsal and volar forearm of 74 participants (36/18/20 training/testing/validation) were represented using a histogram of visual features learned using unsupervised clustering of small image patches. A logistic regression classifier was trained on these histograms to differentiate between stacks from 20- to 30-year-old and 50- to 70-year-old volunteers. The probabilistic output of the logistic regression was used as the fine-grained ageing score for that stack in the testing set ranging from 0 to 1. Evaluation was performed in two ways: on the test set, the AUC was collected for the binary classification problem as well as by statistical comparison of the scores for age and body site groups. Final validation was performed by assessing the accuracy of the ageing score measurement on 20 depth stacks not used for training or evaluating the classifier. Results: The classifier effectively differentiated stacks from age groups with a test set AUC of 0.908. Mean scores were significantly different when comparing age groups (mean 0.70 vs. 0.44; t = −6.62, p = 0.0000) and also when comparing stacks from dorsal and volar body sites (mean 0.64 vs. 0.53; t = 3.12, p = 0.0062). On the final validation set, 17 out of 20 depth stacks were correctly labelled. Discussion: Despite being limited to only coarse training information in the form of example stacks from two age groups, the trained classifier was still able to effectively discriminate between younger skin and older skin. Curiously, despite being only trained with chronological age, there was still evidence for measurable differences in age scores due to sun exposure—with marked differences in scores on sun-exposed dorsal sites of some volunteers compared with less sun-exposed volar sites. These results suggest that fine-grained data-driven quantification of skin ageing is achievable.</p