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In this paper, the properties of coincidence points of mappingsacting between (q1,q2)-quasimetric spaces are studied.For a pair of mappings, we obtain estimates for the distance from apoint to the coincidence points set and intersection of the respective graphs of the mappings. In addition,the stability of coincidence points is studied. A generalization ofLims lemma is obtained., №1 (2020)

Objective: Spondyloarthritis (SpA) is associated with a number of cardiovascular (CV) comorbidities. We examined the association of SpA disease duration and delay in diagnosis with CV-related conditions. Methods: Using data from the COMOSPA study, the associations between SpA disease duration and CV-related conditions were evaluated in univariable and multivariable logistic regression models. Each model examined 1 CV-related factor as dependent and “SpA disease duration” as a predictor, adjusted for relevant confounders. Results: Data from 3923 subjects (median SpA disease duration 5.1 yrs, interquartile range 1.3–11.8 yrs) were available for analysis. The main CV-related conditions were hypertension (HTN; 22.4%), ischemic heart disease (2.6%), stroke (1.3%), and diabetes mellitus (5.5%). HTN was associated with SpA disease duration in both univariable and multivariable analysis, with an OR of 1.129 (95% CI 1.072–1.189; p < 0.001) for each 5-year increase in SpA disease duration. Other factors associated with HTN were age, male sex, current body mass index, ever steroid therapy, and ever synthetic disease-modifying antirheumatic drug therapy, but not nonsteroidal antiinflammatory drugs (NSAID). In subgroup analysis, the strongest association of HTN and disease duration was seen in subjects with the axial-only SpA phenotype (OR 1.202, 95% CI 1.053–1.372) but not in those with peripheral-only SpA (OR 0.902, 95% CI 0.760–1.070). The other CV conditions were not associated with SpA disease duration. Conclusion: Duration of SpA disease in the ASAS-COMOSPA cohort is associated with higher odds of HTN, particularly in those with axial disease, but not with other CV-related conditions. The association with HTN does not appear to be related to NSAID exposure.

Selective attention enables prioritizing the most important information for differential sensory processing and decision-making. Here, we address an active debate regarding whether attention reflects a unitary phenomenon or involves the operation of dissociable sensory enhancement (perceptual sensitivity) and decisional gating (choice bias) processes. We developed a multialternative task in which participants detected and localized orientation changes in gratings at one of four spatial locations. Exogenous attention cues (high contrast flashes) preceded or followed the change events in close temporal proximity. Analysis of participants’ behavior with a multidimensional signal detection model revealed markedly distinct effects of exogenous cueing on perceptual sensitivity and choice bias. Whereas sensitivity enhancement was localized to the stimulus proximal to the exogenous cue, bias enhancement occurred even for distal stimuli in the cued hemifield. Modulations of sensitivity and bias were uncorrelated at both cued and uncued locations. Finally, exogenous cueing produced reaction time benefits only at the cued location and costs only at locations contralateral to the cue. These disparate effects of exogenous cueing on sensitivity, bias and reaction times could be parsimoniously explained within the framework of a diffusion-decision model, in which the drift rate was determined by a linear combination of sensitivity and bias at each location. Exogenous cueing effects on sensitivity and bias differed systematically from previously reported effects of endogenous cueing. We propose that the search for shared neural substrates of exogenous and endogenous attention would benefit from investigating neural correlates of their component sensory and decisional mechanisms.Significance statementWhen we voluntarily direct attention “endogenously”, we are able to better perceive stimuli at the attended location (sensitivity), and to prioritize information from that location for guiding behavioral decisions (bias). But when a salient stimulus, such as a flash of lightning, captures our attention “exogenously”, does it also produce these same effects? To answer this question, we designed a multiple alternative task in which task events occurred in close conjunction with salient exogenous cues (high contrast flashes). We discovered that exogenous attention enhanced both sensitivity and bias for cued stimuli, but each of these changes followed distinct spatial patterns across locations. Our results provide novel insights into component processes of exogenous attention and motivate the search for their neural correlates.

This paper presents exploratory research into “data-intensive development” that seeks to inductively identify issues and conceptual frameworks of relevance to big data in developing countries. It presents a case study of big data innovations in “Stelcorp”; a state electricity corporation in India. In an attempt to address losses in electricity distribution, Stelcorp has introduced new digital meters throughout the distribution network to capture big data, and organisation-wide information systems that store and process and disseminate big data.Emergent issues are identified across three domains: implementation, value and outcome. Implementation of big data has worked relatively well but technical and human challenges remain. The advent of big data has enabled some – albeit constrained – value addition in all areas of organisational operation: customer billing, fault and loss detection, performance measurement, and planning. Yet US$ tens of millions of investment in big data has brought no aggregate improvement in distribution losses or revenue collection. This can be explained by the wider outcome, with big data faltering in the face of external politics; in this case the electoral politics of electrification. Alongside this reproduction of power, the paper also reflects on the way in which big data has enabled shifts in the locus of power: from public to private sector; from labour to management; and from lower to higher levels of management.A number of conceptual frameworks emerge as having analytical power in studying big data and global development. The information value chain model helps track both implementation and value-creation of big data projects. The design-reality gap model can be used to analyse the nature and extent of barriers facing big data projects in developing countries. And models of power – resource dependency, epistemic models, and wider frameworks – are all shown as helping understand the politics of big data.