Many global challenges cannot be addressed by one single actor alone. Achieving sustainability requires governance by state and non-state market actors to jointly realise public values and corporate goals. As a form of public-private governance, voluntary standards involving governments, non-governmental organisations and companies have gained much traction in recent years and have been in the limelight of public authorities and policymakers. From a firm perspective, sustainability standards can be a way to demonstrate that they engage in corporate social responsibility (CSR) in a credible way. To capitalise on their CSR activities, firms need to ensure their stakeholders are able to recognise and assess their CSR quality. However, because the relative observability of CSR is low and since CSR is a contested concept, information asymmetries in firm-stakeholder relationships arise. Adopting CSR standards and using these as signalling devices is a strategy for firms to reduce these information asymmetries, by revealing their true CSR quality. Against this background, this article investigates the voluntary ISO 26000 standard for social responsibility as a form of public-private governance and contends that, despite its objectives, this standard suffers from severe signalling problems. Applying signalling theory to the ISO 26000 standard, this article takes a critical stance towards this standard and argues that firms adhering to this standard may actually emit signals that compromise rather than enhance stakeholders' ability to identify and interpret firms' underlying CSR quality. Consequently, the article discusses the findings in the context of public-private governance, suggests a specification of signalling theory and identifies avenues for future research.
This paper describes experiments with a game device that was used for early detection of delays in motor skill development in primary school children. Children play a game by bi-manual manipulation of the device which continuously collects ac- celerometer data and game state data. Features of the data are used to discriminate between normal children and children with delays. This study focused on the feature selection. Three features were compared: mean squared jerk (time domain); power spectral entropy (fourier domain) and cosine similarity measure (quality of game play). The discriminatory power of the features was tested in an experiment where 28 children played games of different levels of difficulty. The results show that jerk and cosine similarity have reasonable discriminatory power to detect fine-grained motor skill development delays especially when taking the game level into account. Duration of a game level needs to be at least 30 seconds in order to achieve good classification results.
In an event related potential (ERP) experiment using written language materials only, we investigated a potential modulation of the N400 by the modality switch effect. The modality switch effect occurs when a first sentence, describing a fact grounded in one modality, is followed by a second sentence describing a second fact grounded in a different modality. For example, "A cellar is dark" (visual), was preceded by either another visual property "Ham is pink" or by a tactile property "A mitten is soft." We also investigated whether the modality switch effect occurs for false sentences ("A cellar is light"). We found that, for true sentences, the ERP at the critical word "dark" elicited a significantly greater frontal, early N400-like effect (270-370 ms) when there was a modality mismatch than when there was a modality-match. This pattern was not found for the critical word "light" in false sentences. Results similar to the frontal negativity were obtained in a late time window (500-700 ms). The obtained ERP effect is similar to one previously obtained for pictures. We conclude that in this paradigm we obtained fast access to conceptual properties for modality-matched pairs, which leads to embodiment effects similar to those previously obtained with pictorial stimuli.
LINK
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.
![I’M A.I. IMage Processing and Artificial Intelligence [Inaugurele rede]](https://publinova-harvester-content-prod.s3.amazonaws.com/thumbnails/files/previews/pdf/20241113154153921952.LS20Brochure20Professorship20CVDS20FINAL20WEB2028129-thumbnail-400x300.png)