A Learning Framework for Morphological Operators using Counter-Harmonic Mean

We present a novel framework for learning morphological operators using counter-harmonic mean. It combines concepts from morphology and convolutional neural networks. A thorough experimental validation analyzes basic morphological operators dilation and erosion, opening and closing, as well as the much more complex top-hat transform, for which we report a real-world application from the steel industry. Using online learning and stochastic gradient descent, our system learns both the structuring element and the composition of operators. It scales well to large datasets and online settings.Comment: Submitted to ISMM'1

The Intentional Use of Service Recovery Strategies to Influence Consumer Emotion, Cognition and Behaviour

Service recovery strategies have been identified as a critical factor in the success of. service organizations. This study develops a conceptual frame work to investigate how specific service recovery strategies influence the emotional, cognitive and negative behavioural responses of . consumers., as well as how emotion and cognition influence negative behavior. Understanding the impact of specific service recovery strategies will allow service providers' to more deliberately and intentionally engage in strategies that result in positive organizational outcomes. This study was conducted using a 2 x 2 between-subjects quasi-experimental design. The results suggest that service recovery has a significant impact on emotion, cognition and negative behavior. Similarly, satisfaction, negative emotion and positive emotion all influence negative behavior but distributive justice has no effect

Customer emotions in service failure and recovery encounters

Emotions play a significant role in the workplace, and considerable attention has been given to the study of employee emotions. Customers also play a central function in organizations, but much less is known about customer emotions. This chapter reviews the growing literature on customer emotions in employee–customer interfaces with a focus on service failure and recovery encounters, where emotions are heightened. It highlights emerging themes and key findings, addresses the measurement, modeling, and management of customer emotions, and identifies future research streams. Attention is given to emotional contagion, relationships between affective and cognitive processes, customer anger, customer rage, and individual differences

Erratum: Unexplored therapeutic opportunities in the human genome (Nature reviews. Drug discovery (2018) 17 5 (317-332))

This corrects the article DOI: 10.1038/nrd.2018.14

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Facile and systematic access to the least-coordinating WCA [(R^FO)₃Al–F–Al(OR^F)₃]− and its more Lewis-basic brother [F–Al(OR^F)₃]− (RF = C(CF₃)₃)

By reaction of the Lewis acid Me3Si–F–Al(ORF)3 with a series of [PF6]− salts, gaseous PF5 and Me3Si–F are liberated and salts of the anion [F–Al(ORF)3]− ([f–al]−; RF = C(CF3)3) can be obtained. By addition of another equivalent of Me3Si–F–Al(ORF)3 to [f–al]−, gaseous Me3Si–F is released and salts of the least coordinating anion [(RFO)3Al–F–Al(ORF)3]− ([al–f–al]−) are formed. Both procedures work for a series of synthetically useful cations including Ag+, [NO]+, [Ph3C]+ and in very clean reactions with 5 g batch sizes giving excellent yields typically exceeding 90%. In addition, the synthesis of Me3Si–F–Al(ORF)3 has been optimized and scaled up to 85 g batches in an one-pot procedure. These anions could previously only be obtained by difficult to control decomposition reactions of [Al(ORF)4]− or by halide abstraction reactions with Me3Si–F–Al(ORF)3, generating relatively large countercations that are unsuited for further use as universal starting materials. Especially [al–f–al]− is of interest for the stabilization of reactive cations, since it is even weaker coordinating than [Al(ORF)4]− and more stable against strong electrophiles. This bridged anion can be seen as an adduct of [f–al]− and Al(ORF)3. Thus, it is similarly Lewis acidic as BF3 and eventually reacts with nucleophiles (Nu) from the reaction environment to yield Nu–Al(ORF)3 and [f–al]−. This prevents working with [al–f–al]− salts in ethereal or other donor solvents. By contrast, the [f–al]− anion is no longer Lewis acidic and may therefore be used for reactions involving stronger nucleophiles than the [al–f–al]− anion can withstand. Subsequently it may be transformed into the [al–f–al]− salt by simple addition of one equivalent of Me3Si–F–Al(ORF)3