Opening up the societal debate on climate engineering: How newspaper frames are changing

The use of climate engineering or geoengineering technologies to combat climate change has been a controversial topic, even in the scientific debate. In recent studies, it has been claimed that the debate on climate engineering technologies may be closing down prematurely, with detrimental effects on the possibility of social and ethical reflection in appraising these controversial technologies. We examined the extent to which the debate on climate engineering is opening up or closing down, analyzing the diversity of English-speaking newspaper frames in the period 2006–2011. The results provide strong support for an opening of the debate, especially since 2009, given the decline of overly deterministic frames, the emergence of frames related to sociopolitical issues and an overall more balanced distribution of the various frames. This provides evidence that different perspectives are voiced in the public debate, which may enable societies to critically reflect on these emerging technologies

Visual features drive the category-specific impairments on categorization tasks in a patient with object agnosia

Object and scene recognition both require mapping of incoming sensory information to existing conceptual knowledge about the world. A notable finding in brain-damaged patients is that they may show differentially impaired performance for specific categories, such as for “living exemplars”. While numerous patients with category-specific impairments have been reported, the explanations for these deficits remain controversial. In the current study, we investigate the ability of a brain injured patient with a well-established category-specific impairment of semantic memory to perform two categorization experiments: ‘natural’ vs. ‘manmade’ scenes (experiment 1) and objects (experiment 2). Our findings show that the pattern of categorical impairment does not respect the natural versus manmade distinction. This suggests that the impairments may be better explained by differences in visual features, rather than by category membership. Using Deep Convolutional Neural Networks (DCNNs) as ‘artificial animal models’ we further explored this idea. Results indicated that DCNNs with ‘lesions’ in higher order layers showed similar response patterns, with decreased relative performance for manmade scenes (experiment 1) and natural objects (experiment 2), even though they have no semantic category knowledge, apart from a mapping between pictures and labels. Collectively, these results suggest that the direction of category-effects to a large extent depends, at least in MS′ case, on the degree of perceptual differentiation called for, and not semantic knowledge

Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia

The prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented.; We analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission.; Results show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia.; We provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control

Implicit scene segmentation in deeper convolutional neural networks

Feedforward deep convolutional neural networks (DCNNs) are matching and even surpassing human performance on object recognition. This performance suggests that activation of a loose collection of image features could support the recognition of natural object categories, without dedicated systems to solve specific visual subtasks. Recent findings in humans however, suggest that while feedforward activity may suffice for sparse scenes with isolated objects, additional visual operations ('routines') that aid the recognition process (e.g. segmentation or grouping) are needed for more complex scenes. Linking human visual processing to performance of DCNNs with increasing depth, we here explored if, how, and when object information is differentiated from the backgrounds they appear on. To this end, we controlled the information in both objects and backgrounds, as well as the relationship between them by adding noise, manipulating background congruence and systematically occluding parts of the image. Results indicated less distinction between object- and background features for more shallow networks. For those networks, we observed a benefit of training on segmented objects (as compared to unsegmented objects). Overall, deeper networks trained on natural (unsegmented) scenes seem to perform implicit 'segmentation' of the objects from their background, possibly by improved selection of relevant features

Aortic stiffness in type-1 diabetes mellitus; beware of hypertension

Cardiolog

Paroxysmal mechanical aortic valve prosthesis dysfunction: capturing the right moment

Cardiolog

Experimental reconstruction of non-stationary sound and vibration sources by means of Transient Planar Near-field Acoustic Holography

A novel algorithm called Transient Planar Near-field Acoustic Holography is presented to analyse nonstationary sound and vibration sources. The method is able to obtain the time-dependent pressure, particle velocity and intensity field at the source plane without any pre-knowledge of the source by inverse propagation of measured pressure fields. This makes it possible to analyse phenomena like transients and run-ups for all kinds of vibrating and sound radiating objects. Transient responses of thin plates are analysed to experimentally validate the performance of the algorithm. The determined velocity at the center of the plate is validated using a laser vibro-meter directed at the center of the plate and the spatial fields are qualitatively compared with theoretical mode shapes. It is shown that the algorithm is able to analyse transient responses of plates with good quantitative as well as qualitative results.</p

The Potential Added Value of Novel Hearing Therapeutics: An Early Health Economic Model for Hearing Loss

OBJECTIVE: To construct an early health economic model to assess the potential added value of novel hearing therapeutics, compared with the current standard of care. We use idiopathic sudden sensorineural hearing loss (ISSNHL) as a case example, because it is a lead indication for several emerging hearing therapeutics. METHODS: A decision analytic model was developed to assess the costs and effects of using novel hearing therapeutics for patients with ISSNHL. This was compared to the current standard of care. Input data were derived from literature searches and expert opinion. The study adopted a healthcare perspective of the UK National Health Service. Four analyses were conducted: 1) headroom, 2) scenario, 3) threshold, 4) sensitivity. RESULTS: The decision analytic model showed that novel therapeutics for ISSNHL have potential value both in terms of improved patient outcomes, as well as incremental net monetary benefit (iNMB). The base case analysis revealed an iNMB of £39,032 for novel therapeutics compared with the current standard of care. Results of the threshold and scenario analysis revealed that age of treatment and severity of ISSNHL are major determinants of iNMB for novel therapeutics. CONCLUSION: This article describes the first health economic model for novel therapeutics for hearing loss; and shows that novel hearing therapeutics can be cost-effective under NICE's cost-effectiveness threshold, with considerable room for improvement in the current standard of care. Our model can be used to inform the development of cost-effective hearing therapeutics; and help decision makers decide which therapeutics represent value for money