3D Ziyarat: Lenticularity and technologies of the moving image in material and visual piety

Images in movement and images of movement take a central place in iterations of Islamic material and visual piety. Yet the still image remains the default object of inquiry in most studies of devotional visuality. Taking movement rather than stasis as the prerequisite for engagement, many popular decorative items and technologies that share the status of “moving images” evoke the affective experience of pilgrimage. In what follows, close analysis of a repertoire of one such image technology, the lenticular print, formed through its circulation in Pakistan, provides insights into the kind of engagement expected from images whose efficacy is governed by their mobility. By testing the application of some significant theories on the phenomenology of film experience, combined with ways of understanding the forms of presence elicited by virtual pilgrimage, this essay attempts to better grasp the kinds of engagement invited by devotional objects characterized by their evocation of movement.Economic and Social Research Council ES/V011669/1 London Arts and Humanities Partnership (LAHP), an initiative of the Arts and Humanities Research Council (AHRC) AH/L503873/

Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: A comparison of new and existing tests.

Small-study effects are a common threat in systematic reviews and may indicate publication bias. Their existence is often verified by visual inspection of the funnel plot. Formal tests to assess the presence of funnel plot asymmetry typically estimate the association between the reported effect size and their standard error, the total sample size, or the inverse of the total sample size. In this paper, we demonstrate that the application of these tests may be less appropriate in meta-analysis of survival data, where censoring influences statistical significance of the hazard ratio. We subsequently propose 2 new tests that are based on the total number of observed events and adopt a multiplicative variance component. We compare the performance of the various funnel plot asymmetry tests in an extensive simulation study where we varied the true hazard ratio (0.5 to 1), the number of published trials (N=10 to 100), the degree of censoring within trials (0% to 90%), and the mechanism leading to participant dropout (noninformative versus informative). Results demonstrate that previous well-known tests for detecting funnel plot asymmetry suffer from low power or excessive type-I error rates in meta-analysis of survival data, particularly when trials are affected by participant dropout. Because our novel test (adopting estimates of the asymptotic precision as study weights) yields reasonable power and maintains appropriate type-I error rates, we recommend its use to evaluate funnel plot asymmetry in meta-analysis of survival data. The use of funnel plot asymmetry tests should, however, be avoided when there are few trials available for any meta-analysis

Predictions for high energy neutrino cross-sections from the ZEUS global PDF fits

We have updated predictions for high energy neutrino and antineutrino charged current cross-sections within the conventional DGLAP formalism of NLO QCD using a modern PDF fit to HERA data, which also accounts in a systematic way for PDF uncertainties deriving from both model uncertainties and from the experimental uncertainties of the input data sets. Furthermore the PDFs are determined using an improved treatment of heavy quark thresholds. A measurement of the neutrino cross-section much below these predictions would signal the need for extension of the conventional formalism as in BFKL resummation, or even gluon recombination effects as in the colour glass condensate model.Comment: 10 pages (RevTeX4), 6 figures; expanded discussion of additional theoretical uncertainties at low x; accepted for publication in JHE

Internal-external cross-validation helped to evaluate the generalizability of prediction models in large clustered datasets

OBJECTIVE: To illustrate how to evaluate the need of complex strategies for developing generalizable prediction models in large clustered datasets. STUDY DESIGN AND SETTING: We developed eight Cox regression models to estimate the risk of heart failure using a large population-level dataset. These models differed in the number of predictors, the functional form of the predictor effects (non-linear effects and interaction) and the estimation method (maximum likelihood and penalization). Internal-external cross-validation was used to evaluate the models' generalizability across the included general practices. RESULTS: Among 871,687 individuals from 225 general practices, 43,987 (5.5%) developed heart failure during a median follow-up time of 5.8 years. For discrimination, the simplest prediction model yielded a good concordance statistic, which was not much improved by adopting complex strategies. Between-practice heterogeneity in discrimination was similar in all models. For calibration, the simplest model performed satisfactorily. Although accounting for non-linear effects and interaction slightly improved the calibration slope, it also led to more heterogeneity in the observed/expected ratio. Similar results were found in a second case study involving patients with stroke. CONCLUSION: In large clustered datasets, prediction model studies may adopt internal-external cross-validation to evaluate the generalizability of competing models, and to identify promising modelling strategies

Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review

OBJECTIVES: Missing data is a common problem during the development, evaluation, and implementation of prediction models. Although machine learning (ML) methods are often said to be capable of circumventing missing data, it is unclear how these methods are used in medical research. We aim to find out if and how well prediction model studies using machine learning report on their handling of missing data. STUDY DESIGN AND SETTING: We systematically searched the literature on published papers between 2018 and 2019 about primary studies developing and/or validating clinical prediction models using any supervised ML methodology across medical fields. From the retrieved studies information about the amount and nature (e.g. missing completely at random, potential reasons for missingness) of missing data and the way they were handled were extracted. RESULTS: We identified 152 machine learning-based clinical prediction model studies. A substantial amount of these 152 papers did not report anything on missing data (n = 56/152). A majority (n = 96/152) reported details on the handling of missing data (e.g., methods used), though many of these (n = 46/96) did not report the amount of the missingness in the data. In these 96 papers the authors only sometimes reported possible reasons for missingness (n = 7/96) and information about missing data mechanisms (n = 8/96). The most common approach for handling missing data was deletion (n = 65/96), mostly via complete-case analysis (CCA) (n = 43/96). Very few studies used multiple imputation (n = 8/96) or built-in mechanisms such as surrogate splits (n = 7/96) that directly address missing data during the development, validation, or implementation of the prediction model. CONCLUSION: Though missing values are highly common in any type of medical research and certainly in the research based on routine healthcare data, a majority of the prediction model studies using machine learning does not report sufficient information on the presence and handling of missing data. Strategies in which patient data are simply omitted are unfortunately the most often used methods, even though it is generally advised against and well known that it likely causes bias and loss of analytical power in prediction model development and in the predictive accuracy estimates. Prediction model researchers should be much more aware of alternative methodologies to address missing data

Fast odour dynamics are encoded in the olfactory system and guide behaviour

Odours are transported in turbulent plumes, which result in rapid concentration fluctuations1,2 that contain rich information about the olfactory scenery, such as the composition and location of an odour source2,3,4. However, it is unclear whether the mammalian olfactory system can use the underlying temporal structure to extract information about the environment. Here we show that ten-millisecond odour pulse patterns produce distinct responses in olfactory receptor neurons. In operant conditioning experiments, mice discriminated temporal correlations of rapidly fluctuating odours at frequencies of up to 40 Hz. In imaging and electrophysiological recordings, such correlation information could be readily extracted from the activity of mitral and tufted cells—the output neurons of the olfactory bulb. Furthermore, temporal correlation of odour concentrations5 reliably predicted whether odorants emerged from the same or different sources in naturalistic environments with complex airflow. Experiments in which mice were trained on such tasks and probed using synthetic correlated stimuli at different frequencies suggest that mice can use the temporal structure of odours to extract information about space. Thus, the mammalian olfactory system has access to unexpectedly fast temporal features in odour stimuli. This endows animals with the capacity to overcome key behavioural challenges such as odour source separation5, figure–ground segregation6 and odour localization7 by extracting information about space from temporal odour dynamics

Alterações induzidas pelo treino de pré-época no futebol

info:eu-repo/semantics/publishedVersio

A topolographical approach to infrastructure:Political topography, topology and the port of Dar es Salaam

Economic infrastructure hubs, such as ports, are crucial sites for exploring new political geographies. In such environments, mobilities are enabled and rigidly channelled premised on the stasis of the port-as-checkpoint. Such nodes are part of an ever-growing political geography of zones that requires more attention. This article proposes a ‘topolographical’ approach – a combined heuristic drawing from political topography and topology – to comprehend more fully the transformations in the political geographies of large-scale infrastructures. The cardinal nature of the port of Dar es Salaam makes it a crucial site through which to illustrate the purchase of this framework. The topographical analysis puts forward the port of Dar as ‘archipelago of global territories’, within which heterogeneous actors claim graduated authority. Drawing on topology, the article shows what is folded into the port, constantly shaping not only who governs but, more importantly, how power and authority are exercised. It will be shown how imaginaries of the port - as gateway, seamless space, and modernity ‘from scratch’ - as much as new technological devices work to produce historically and geographically distinct political geographies, and indeed bring new ones into being