Climate sensitivity uncertainty : When is good news bad?

Climate change is real and dangerous. Exactly how bad it will get, however, is uncertain. Uncertainty is particularly relevant for estimates of one of the key parameters: equilibrium climate sensitivity—how eventual temperatures will react as atmospheric carbon dioxide concentrations double. Despite significant advances in climate science and increased confidence in the accuracy of the range itself, the “likely” range has been 1.5-4.5°C for over three decades. In 2007, the Intergovernmental Panel on Climate Change (IPCC) narrowed it to 2-4.5°C, only to reverse its decision in 2013, reinstating the prior range. In addition, the 2013 IPCC report removed prior mention of 3°C as the “best estimate.” We interpret the implications of the 2013 IPCC decision to lower the bottom of the range and excise a best estimate. Intuitively, it might seem that a lower bottom would be good news. Here we ask: When might apparently good news about climate sensitivity in fact be bad news in the sense that it lowers societal wellbeing? The lowered bottom value also implies higher uncertainty about the temperature increase, a definite bad. Under reasonable assumptions, both the lowering of the lower bound and the removal of the “best estimate” may well be bad news

Cross entropy as a measure of musical contrast

We present a preliminary study of using the information theoretic concept of cross-entropy to measure musical contrast in a symbolic context, with a focus on melody. We measure cross-entropy using the Information Dynamics Of Music (IDyOM) framework. Whilst our long term aim is to understand the use of contrast in Sonata form, in this paper we take a more general perspective and look at a broad spread of Western art music of the common practice era. Our results suggest that cross-entropy has a useful role as an objective measure of contrast, but that a fuller picture will require more work

Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists. Computer-aided diagnosis systems showed potential for improving the diagnostic accuracy. In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification. Hematoxylin and eosin stained breast histology microscopy image dataset is provided as a part of the ICIAR 2018 Grand Challenge on Breast Cancer Histology Images. Our approach utilizes several deep neural network architectures and gradient boosted trees classifier. For 4-class classification task, we report 87.2% accuracy. For 2-class classification task to detect carcinomas we report 93.8% accuracy, AUC 97.3%, and sensitivity/specificity 96.5/88.0% at the high-sensitivity operating point. To our knowledge, this approach outperforms other common methods in automated histopathological image classification. The source code for our approach is made publicly available at https://github.com/alexander-rakhlin/ICIAR2018Comment: 8 pages, 4 figure

Super-resolving phase measurements with a multi-photon entangled state

Using a linear optical elements and post-selection, we construct an entangled polarization state of three photons in the same spatial mode. This state is analogous to a ``photon-number path entangled state'' and can be used for super-resolving interferometry. Measuring a birefringent phase shift, we demonstrate two- and three-fold improvements in phase resolution.Comment: 4 pages, 3 figure

Limited effect of patient and disease characteristics on compliance with hospital antimicrobial guidelines

Objective: Physicians frequently deviate from guidelines that promote prudent use of antimicrobials. We explored to what extent patient and disease characteristics were associated with compliance with guideline recommendations for three common infections. Methods: In a 1-year prospective observational study, 1,125 antimicrobial prescriptions were analysed for compliance with university hospital guidelines. Results: Compliance varied significantly between and within the groups of infections studied. Compliance was much higher for lower respiratory tract infections (LRTIs; 79%) than for sepsis (53%) and urinary tract infections (UTIs; 40%). Only predisposing illnesses and active malignancies were associated with more compliant prescribing, whereas alcohol/ intravenous drug abuse and serum creatinine levels > 130 mu mol/l were associated with less compliant prescribing. Availability of culture results had no impact on compliance with guidelines for sepsis but was associated with more compliance in UTIs and less in LRTIs. Narrowing initial broad-spectrum antimicrobial therapy to cultured pathogens was seldom practised. Most noncompliant prescribing concerned a too broad spectrum of activity when compared with guideline-recommended therapy. Conclusion: Patient characteristics had only a limited impact on compliant prescribing for a variety of reasons. Physicians seemed to practise defensive prescribing behaviour, favouring treatment success in current patients over loss of effectiveness due to resistance in future patients

A human-centered design methodology to enhance the usability, human factors, and user experience of connected health systems: a three-phase methodology.

peer-reviewedDesign processes such as human-centered design, which involve the end user throughout the product development and testing process, can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of safety and user experience. The structured and iterative nature of human-centered design can often present a challenge when design teams are faced with the necessary, rapid, product development life cycles associated with the competitive connected health industry. We wanted to derive a structured methodology that followed the principles of human-centered design that would allow designers and developers to ensure that the needs of the user are taken into account throughout the design process, while maintaining a rapid pace of development. In this paper, we present the methodology and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience of a connected health system known as the Wireless Insole for Independent and Safe Elderly Living (WIISEL) system, a system designed to continuously assess fall risk by measuring gait and balance parameters associated with fall risk. We derived a three-phase methodology. In Phase 1 we emphasized the construction of a use case document. This document can be used to detail the context of use of the system by utilizing storyboarding, paper prototypes, and mock-ups in conjunction with user interviews to gather insightful user feedback on different proposed concepts. In Phase 2 we emphasized the use of expert usability inspections such as heuristic evaluations and cognitive walkthroughs with small multidisciplinary groups to review the prototypes born out of the Phase 1 feedback. Finally, in Phase 3 we emphasized classical user testing with target end users, using various metrics to measure the user experience and improve the final prototypes. We report a successful implementation of the methodology for the design and development of a system for detecting and predicting falls in older adults. We describe in detail what testing and evaluation activities we carried out to effectively test the system and overcome usability and human factors problems. We feel this methodology can be applied to a wide variety of connected health devices and systems. We consider this a methodology that can be scaled to different-sized projects accordingly.PUBLISHEDpeer-reviewe

Acellular Pertussis Booster in Adolescents Induces Th1 and Memory CD8+ T Cell Immune Response

In a number of countries, whole cell pertussis vaccines (wcP) were replaced by acellular vaccines (aP) due to an improved reactogenicity profile. Pertussis immunization leads to specific antibody production with the help of CD4+ T cells. In earlier studies in infants and young children, wcP vaccines selectively induced a Th1 dominated immune response, whereas aP vaccines led to a Th2 biased response. To obtain data on Th1 or Th2 dominance of the immune response in adolescents receiving an aP booster immunization after a wcP or aP primary immunization, we analyzed the concentration of Th1 (IL-2, TNF-α, INF-γ) and Th2 (IL-4, IL-5, IL-10) cytokines in supernatants of lymphocyte cultures specifically stimulated with pertussis antigens. We also investigated the presence of cytotoxic T cell responses against the facultative intracellular bacterium Bordetella pertussis by quantifying pertussis-specific CD8+ T cell activation following the aP booster immunization. Here we show that the adolescent aP booster vaccination predominantly leads to a Th1 immune response based on IFNgamma secretion upon stimulation with pertussis antigen, irrespective of a prior whole cell or acellular primary vaccination. The vaccination also induces an increase in peripheral CD8+CD69+ activated pertussis-specific memory T cells four weeks after vaccination. The Th1 bias of this immune response could play a role for the decreased local reactogenicity of this adolescent aP booster immunization when compared to the preceding childhood acellular pertussis booster. Pertussis-specific CD8+ memory T cells may contribute to protection against clinical pertussis