Applying spatial reasoning to topographical data with a grounded geographical ontology

Grounding an ontology upon geographical data has been pro- posed as a method of handling the vagueness in the domain more effectively. In order to do this, we require methods of reasoning about the spatial relations between the regions within the data. This stage can be computationally expensive, as we require information on the location of points in relation to each other. This paper illustrates how using knowledge about regions allows us to reduce the computation required in an efficient and easy to understand manner. Further, we show how this system can be implemented in co-ordination with segmented data to reason abou

What works where and how for uptake and impact of artificial intelligence in pathology: Review of theories for a realist evaluation

YesThere is increasing interest in the use of artificial intelligence (AI) in pathology to increase accuracy and efficiency. To date, studies of clinicians' perceptions of AI have found only moderate acceptability, suggesting the need for further research regarding how to integrate it into clinical practice. The aim of the study was to determine contextual factors that may support or constrain the uptake of AI in pathology. To go beyond a simple listing of barriers and facilitators, we drew on the approach of realist evaluation and undertook a review of the literature to elicit stakeholders' theories of how, for whom, and in what circumstances AI can provide benefit in pathology. Searches were designed by an information specialist and peer-reviewed by a second information specialist. Searches were run on the arXiv.org repository, MEDLINE, and the Health Management Information Consortium, with additional searches undertaken on a range of websites to identify gray literature. In line with a realist approach, we also made use of relevant theory. Included documents were indexed in NVivo 12, using codes to capture different contexts, mechanisms, and outcomes that could affect the introduction of AI in pathology. Coded data were used to produce narrative summaries of each of the identified contexts, mechanisms, and outcomes, which were then translated into theories in the form of context-mechanism-outcome configurations. A total of 101 relevant documents were identified. Our analysis indicates that the benefits that can be achieved will vary according to the size and nature of the pathology department's workload and the extent to which pathologists work collaboratively; the major perceived benefit for specialist centers is in reducing workload. For uptake of AI, pathologists' trust is essential. Existing theories suggest that if pathologists are able to "make sense" of AI, engage in the adoption process, receive support in adapting their work processes, and can identify potential benefits to its introduction, it is more likely to be accepted. For uptake of AI in pathology, for all but the most simple quantitative tasks, measures will be required that either increase confidence in the system or provide users with an understanding of the performance of the system. For specialist centers, efforts should focus on reducing workload rather than increasing accuracy. Designers also need to give careful thought to usability and how AI is integrated into pathologists' workflow

Self-repair ability of evolved self-assembling systems in cellular automata

Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair

Quantized spin waves in the metallic state of magnetoresistive manganites

High resolution spin waves measurements have been carried out in ferromagnetic (F) La(1-x)(Sr,Ca)xMnO3 with x(Sr)=0.15, 0.175, 0.2, 0.3 and x(Ca)=0.3. In all q-directions, close to the zone boundary, the spin wave spectra consist of several energy levels, with the same values in the metallic and the x\approx 1/8 ranges. Mainly the intensity varies, jumping from the lower energy levels determined in the x\approx 1/8 range to the higher energy ones observed in the metallic state. On the basis of a quantitative agreement found for x(Sr)=0.15 in a model of ordered 2D clusters, the spin wave anomalies of the metallic state can be interpreted in terms of quantized spin waves within the same 2D clusters, embedded in a 3D matrix.Comment: 4 pages, 5 figure

Characterization of rare spontaneous human immunodeficiency virus viral controllers attending a national United Kingdom clinical service using a combination of serology and molecular diagnostic assays

BACKGROUND: We report outcomes and novel characterization of a unique cohort of 42 individuals with persistently indeterminate human immunodeficiency virus (HIV) status, the majority of whom are HIV viral controllers. METHODS: Eligible individuals had indeterminate or positive HIV serology, but persistently undetectable HIV ribonucleic acid (RNA) by commercial assays and were not taking antiretroviral therapy (ART). Routine investigations included HIV Western blot, HIV viral load, qualitative HIV-1 deoxyribonucleic acid (DNA), coinfection screen, and T-cell quantification. Research assays included T-cell activation, ART measurement, single-copy assays detecting HIV-1 RNA and DNA, and plasma cytokine quantification. Human immunodeficiency virus seropositivity was defined as ≥3 bands on Western blot; molecular positivity was defined as detection of HIV RNA or DNA. RESULTS: Human immunodeficiency virus infection was excluded in 10 of 42 referrals, remained unconfirmed in 2 of 42, and was confirmed in 30 of 42, who were identified as HIV elite controllers (ECs), normal CD4 T-cell counts (median 820/mL, range 805-1336), and normal CD4/CD8 ratio (median 1.8, range 1.2-1.9). Elite controllers had a median duration of elite control of 6 years (interquartile range = 4-14). Antiretroviral therapy was undetected in all 23 subjects tested. Two distinct categories of ECs were identified: molecular positive (n = 20) and molecular negative (n = 10). CONCLUSIONS: Human immunodeficiency virus status was resolved for 95% of referrals with the majority diagnosed as EC. The clinical significance of the 2 molecular categories among ECs requires further investigation