Learning to segment when experts disagree

Recent years have seen an increasing use of supervised learning methods for segmentation tasks. However, the predictive performance of these algorithms depend on the quality of labels, especially in medical image domain, where both the annotation cost and inter-observer variability are high. In a typical annotation collection process, different clinical experts provide their estimates of the “true” segmentation labels under the influence of their levels of expertise and biases. Treating these noisy labels blindly as the ground truth can adversely affect the performance of supervised segmentation models. In this work, we present a neural network architecture for jointly learning, from noisy observations alone, both the reliability of individual annotators and the true segmentation label distributions. The separation of the annotators’ characteristics and true segmentation label is achieved by encouraging the estimated annotators to be maximally unreliable while achieving high fidelity with the training data. Our method can also be viewed as a translation of STAPLE, an established label aggregation framework proposed in Warfield et al. [1] to the supervised learning paradigm. We demonstrate first on a generic segmentation task using MNIST data and then adapt for usage with MRI scans of multiple sclerosis (MS) patients for lesion labelling. Our method shows considerable improvement over the relevant baselines on both datasets in terms of segmentation accuracy and estimation of annotator reliability, particularly when only a single label is available per image. An open-source implementation of our approach can be found at https://github.com/UCLBrain/MSLS

The APO-K2 Catalog: II. Accurate Stellar Ages for Red Giant Branch Stars across the Milky Way

We present stellar age determinations for 4661 red giant branch stars in the APO-K2 catalog, derived using mass estimates from K2 asteroseismology from the K2 Galactic Archaeology Program and elemental abundances from the Apache Point Galactic Evolution Experiment survey. Our sample includes 17 of the 19 fields observed by K2, making it one of the most comprehensive catalogs of accurate stellar ages across the Galaxy in terms of the wide range of populations spanned by its stars, enabling rigorous tests of Galactic chemical evolution models. Taking into account the selection functions of the K2 sample, the data appear to support the age−chemistry morphology of stellar populations predicted by both inside-out and late-burst scenarios. We also investigate trends in age versus stellar chemistry and Galactic position, which are consistent with previous findings. Comparisons against APOKASC-3 asteroseismic ages show agreement to within ∼3%. We also discuss offsets between our ages and spectroscopic ages. Finally, we note that ignoring the effects of α-enhancement on stellar opacity (either directly or with the Salaris metallicity correction) results in an ∼10% offset in age estimates for the most α-enhanced stars, which is an important consideration for continued tests of Galactic models with this and other asteroseismic age samples

Managing Knowledge in Policymaking and Decision Making

The combined effect of increasing problem complexity and growing demand for participation in decisions has forced policymaking and decision making in organizations to become less an analytic endeavor and more a process of "knowledge management ' This requires an intermediarv to mediate among conflicting perspectives and integrate the different forms and levels of knowledge This article describes one such approach to knowledge management that utilizes a third party to create and facilitate a temporary task organization Following a brief case example, some research resultsfrom an evaluation of six past applications of the approach are presented These results provide insight into the effective structuring and conduct of knowledge management proceduresPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68626/2/10.1177_107554708600800106.pd

Ebola GP-Specific Monoclonal Antibodies Protect Mice and Guinea Pigs from Lethal Ebola Virus Infection

Ebola virus (EBOV) causes acute hemorrhagic fever in humans and non-human primates with mortality rates up to 90%. So far there are no effective treatments available. This study evaluates the protective efficacy of 8 monoclonal antibodies (MAbs) against Ebola glycoprotein in mice and guinea pigs. Immunocompetent mice or guinea pigs were given MAbs i.p. in various doses individually or as pools of 3–4 MAbs to test their protection against a lethal challenge with mouse- or guinea pig-adapted EBOV. Each of the 8 MAbs (100 µg) protected mice from a lethal EBOV challenge when administered 1 day before or after challenge. Seven MAbs were effective 2 days post-infection (dpi), with 1 MAb demonstrating partial protection 3 dpi. In the guinea pigs each MAb showed partial protection at 1 dpi, however the mean time to death was significantly prolonged compared to the control group. Moreover, treatment with pools of 3–4 MAbs completely protected the majority of animals, while administration at 2–3 dpi achieved 50–100% protection. This data suggests that the MAbs generated are capable of protecting both animal species against lethal Ebola virus challenge. These results indicate that MAbs particularly when used as an oligoclonal set are a potential therapeutic for post-exposure treatment of EBOV infection

Interpretive structural modelling of risk sources in a virtual organisation

International audienceSpeedier network decision making together with shorter time to bring items to market together with lower network operating costs all result from enhanced knowledge sharing. In addition re-use of enterprise and network knowledge resulting from improved capture means that any risk of repeating earlier project work is limited, repetition of past mistakes is reduced. Decisions are made with greater awareness of any risks involved and therefore there is likely to be a reduction in costs arising from faulty decisions and failed collaborations. While there are many advantages attaching to the use of virtual organizations (VOs) there are also challenges, including risks that have become apparent through undertaking a review of the literature. In total 13 sources of risk were found stemming from the network related risks in a VO, where the emphasis of the study was placed,. This paper contains a thorough study that will identify these threats as well as gaining a sound understanding of them by examining them one by one as they have been identified by the literature and previous studies. Subsequently, their relative importance will be analysed through the use of Structural Modeling (ISM) using information gathered in a questionnaire

Multiple agency perspective, family control, and private information abuse in an emerging economy

Using a comprehensive sample of listed companies in Hong Kong this paper investigates how family control affects private information abuses and firm performance in emerging economies. We combine research on stock market microstructure with more recent studies of multiple agency perspectives and argue that family ownership and control over the board increases the risk of private information abuse. This, in turn, has a negative impact on stock market performance. Family control is associated with an incentive to distort information disclosure to minority shareholders and obtain private benefits of control. However, the multiple agency roles of controlling families may have different governance properties in terms of investors’ perceptions of private information abuse. These findings contribute to our understanding of the conflicting evidence on the governance role of family control within a multiple agency perspectiv

Driving Innovation through Big Open Linked Data (BOLD): Exploring Antecedents using Interpretive Structural Modelling

YesInnovation is vital to find new solutions to problems, increase quality, and improve profitability. Big open linked data (BOLD) is a fledgling and rapidly evolving field that creates new opportunities for innovation. However, none of the existing literature has yet considered the interrelationships between antecedents of innovation through BOLD. This research contributes to knowledge building through utilising interpretive structural modelling to organise nineteen factors linked to innovation using BOLD identified by experts in the field. The findings show that almost all the variables fall within the linkage cluster, thus having high driving and dependence powers, demonstrating the volatility of the process. It was also found that technical infrastructure, data quality, and external pressure form the fundamental foundations for innovation through BOLD. Deriving a framework to encourage and manage innovation through BOLD offers important theoretical and practical contributions

Minimal in vivo efficacy of iminosugars in a lethal Ebola virus guinea pig model

The antiviral properties of iminosugars have been reported previously in vitro and in small animal models against Ebola virus (EBOV); however, their effects have not been tested in larger animal models such as guinea pigs. We tested the iminosugars N-butyl-deoxynojirimycin (NB-DNJ) and N-(9-methoxynonyl)-1deoxynojirimycin (MON-DNJ) for safety in uninfected animals, and for antiviral efficacy in animals infected with a lethal dose of guinea pig adapted EBOV. 1850 mg/kg/day NB-DNJ and 120 mg/kg/day MON-DNJ administered intravenously, three times daily, caused no adverse effects and were well tolerated. A pilot study treating infected animals three times within an 8 hour period was promising with 1 of 4 infected NB-DNJ treated animals surviving and the remaining three showing improved clinical signs. MON-DNJ showed no protective effects when EBOV-infected guinea pigs were treated. On histopathological examination, animals treated with NB-DNJ had reduced lesion severity in liver and spleen. However, a second study, in which NB-DNJ was administered at equally-spaced 8 hour intervals, could not confirm drug-associated benefits. Neither was any antiviral effect of iminosugars detected in an EBOV glycoprotein pseudotyped virus assay. Overall, this study provides evidence that NB-DNJ and MON-DNJ do not protect guinea pigs from a lethal EBOV-infection at the dose levels and regimens tested. However, the one surviving animal and signs of improvements in three animals of the NB-DNJ treated cohort could indicate that NB-DNJ at these levels may have a marginal beneficial effect. Future work could be focused on the development of more potent iminosugars