The WOOL Dialogue Platform: Enabling Interdisciplinary User-Friendly Development of Dialogue for Conversational Agents

Health coaching applications can include (embodied) conversational agents as coaches. The development of these agents requires an interdisciplinary cooperation between eHealth application developers, interaction designers and domain experts. Therefore, proper dialogue authoring tools and tools to integrate these dialogues in a conversational agent system are essential in the process of creating successful agent-based applications. However, we found no existing open source, easy-to-use authoring tools that support multidisciplinary agent development. To that end, we developed the WOOL Dialogue Platform. The WOOL Dialogue Platform provides the eHealth and conversational agent communities with an open source platform, consisting of a set of easy to use tools that facilitate virtual agent development. The platform consists of a dialogue definition language, an editor, application development libraries and a web service. To illustrate the platform’s possibilities and use in practice, we describe two use cases from EU Horizon 2020 research projects. The WOOL Dialogue Platform is an ‘easy to use, and powerful if needed’ platform for the development of conversational agent applications that is seeing a slow but steady increase in uptake in the eHealth community. Developed to support dialogue authoring for embodied conversational agents in the health coaching domain, this platform’s strong points are its ease of use and ability to let domain experts and agents technology experts work together by providing all parties with tools that support their work effectively.

Responses to digital disinformation as part of hybrid threats: a systematic review on the effects of disinformation and the effectiveness of fact-checking/debunking

The dissemination of purposely deceitful or misleading content to target audiences for political aims or economic purposes constitutes a threat to democratic societies and institutions, and is being increasingly recognized as a major security threat, particularly after evidence and allegations of hostile foreign interference in several countries surfaced in the last five years. Disinformation can also be part of hybrid threat activities. This research paper examines findings on the effects of disinformation and addresses the question of how effective counterstrategies against digital disinformation are, with the aim of assessing the impact of responses such as the exposure and disproval of disinformation content and conspiracy theories. The paper’s objective is to synthetize the main scientific findings on disinformation effects and on the effectiveness of debunking, inoculation, and forewarning strategies against digital disinformation. A mixed methodology is used, combining qualitative interpretive analysis and structured technique for evaluating scientific literature such as a systematic literature review (SLR), following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework.

The future of education equity policy in a COVID-19 world: a qualitative systematic review of lessons from education policymaking

Background: COVID-19 had a major global impact on education, prompting concerns about its unequal effects and some impetus to reboot equity strategies. Yet, policy processes exhibit major gaps between such expectations and outcomes, and similar inequalities endured for decades before the pandemic. Our objective is to establish how education researchers, drawing on policy concepts and theories, explain and seek to address this problem. Methods: A qualitative systematic review (2020-21), to identify peer reviewed research and commentary articles on education, equity, and policymaking, in specialist and general databases (ERIC, Web of Science, Scopus, Cochrane/ Social Systems Evidence). We did not apply additional quality measures. We used an immersive and inductive approach to identify key themes. We use these texts to produce a general narrative and explore how policy theory articles inform it. Results: 140 texts (109 articles included; 31 texts snowballed) provide a non-trivial reference to policymaking. Limiting inclusion to English-language produced a bias towards Global North articles. Our comparison with a review of health equity research highlights distinctive elements in education. First, education equity is ambiguous and contested, with no settled global definition or agenda (although some countries and international organisations have disproportionate influence). Second, researchers critique ‘neoliberal’ approaches that dominate policymaking at the expense of ‘social justice’. Third, more studies provide ‘bottom-up’ analysis of ‘implementation gaps’. Fourth, more studies relate inequity to ineffective policymaking to address marginalised groups. Conclusions: Few studies use policy theories to explain policymaking, but there is an education-specific literature performing a similar role. Compared to health research, there is more use of critical policy analysis to reflect on power and less focus on technical design issues. There is high certainty that current neoliberal policies are failing, but low certainty about how to challenge them successfully.

Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K’iche’

How do language learners avoid the production of verb argument structure overgeneralization errors (*The clown laughed the man c.f. The clown made the man laugh), while retaining the ability to apply such generalizations productively when appropriate? This question has long been seen as one that is both particularly central to acquisition research and particularly challenging. Focussing on causative overgeneralization errors of this type, a previous study reported a computational model that learns, on the basis of corpus data and human-derived verb-semantic-feature ratings, to predict adults’ by-verb preferences for less- versus more-transparent causative forms (e.g., * The clown laughed the man vs The clown made the man laugh) across English, Hebrew, Hindi, Japanese and K’iche Mayan. Here, we tested the ability of this model (and an expanded version with multiple hidden layers) to explain binary grammaticality judgment data from children aged 4;0-5;0, and elicited-production data from children aged 4;0-5;0 and 5;6-6;6 (N=48 per language). In general, the model successfully simulated both children’s judgment and production data, with correlations of r=0.5-0.6 and r=0.75-0.85, respectively, and also generalized to unseen verbs. Importantly, learners of all five languages showed some evidence of making the types of overgeneralization errors – in both judgments and production – previously observed in naturalistic studies of English (e.g., *I’m dancing it). Together with previous findings, the present study demonstrates that a simple learning model can explain (a) adults’ continuous judgment data, (b) children’s binary judgment data and (c) children’s production data (with no training of these datasets), and therefore constitutes a plausible mechanistic account of the acquisition of verbs’ argument structure restrictions.

Identifying knowledge gaps for successful restorative aquaculture of Ostrea edulis: a bibliometric analysis

Background: Active restoration is necessary to enhance the recovery of Ostrea edulis reefs, which contribute to many ecosystem services. Restoration can be integrated within aquaculture practices, bringing positive environmental changes while maximising space utilisation. The restoration project MAREA (MAtchmaking Restoration Ecology and Aquaculture) aims to bring back O. edulis in the North-West Adriatic addressing the feasibility of its cultivation. Both successful restoration and sustainable aquaculture require a thorough understanding of the ecological needs, as the requirements of both activities need to be harmonized. Therefore, one of the preliminary activities before embarking on the pilot was the completion of a thorough literature review to identify research directions and gaps required for ‘restorative aquaculture’, aiming to gather the most up to date O. edulis knowledge on a global and local scale. Methods: Internet (Web of Science, Scopus, Google scholar) and physical resources (libraries) were searched for all available global and local knowledge on O. edulis. Bibliometrix was used to identify the main research topics using keywords, titles, and abstracts analyses. Studies were then manually screened and summarised to extract knowledge specific to restoration and aquaculture. Results: While restoration studies are recent, evidence for the loss of this species and potential causes (and solutions) have been discussed since the end of the 19th century. While diseases were a leading cause for reef loss, substratum limitation appears to be one of the leading limiting factors for both restoration and aquaculture of O. edulis, and was already mentioned in the early texts that were found. Conclusions: The review highlighted that restoration success and aquaculture feasibility depend upon the crucial stage of settlement. The project ‘MAREA’ will therefore increase its focus on this stage, both in terms of timing, location, and materials for settlement plates placement.

Review of the research programme on the Mortella III wreck (2010-2020, Corsica, France): A contribution to the knowledge of the Mediterranean naval architecture and material culture of the Renaissance.

The Mortella wrecks are the remains of two navi, Genoese seagoing merchant ships, sunk in 1527 in the Bay of Saint-Florent (Upper-Corsica, France) during the Seventh Italian War. A programme of archaeological excavations and historical research has been held on one of them, Mortella III, between 2010 and 2020. It has involved a multidisciplinary team around a European research project called ModernShip (Horizon 2020), whose objective is to shed light on Mediterranean shipbuilding during the Renaissance, a field still little known to this day. At the end of these 10 years, the aim of the present article is to conclude this research programme with the presentation of a scientific review that complements a recently published monograph on the Mortella III wreck. This study presents the latest results on the ship's architecture obtained during the excavation of the wreck in 2019, including a study of the wood of the framework. Finally, this article broadens our understanding of the nave presenting the results of a collaborative line of research on material culture with three studies in close connection with the ship architecture: artillery, anchors and ceramics.

Dynamic participation in local energy communities with peer-to-peer trading

Background: Energy communities and local electricity markets (e.g., as peer-to-peer trading) are on the rise due to increasingly decentralized electricity generation and favorable adjustment of the legal framework in many European countries. Methods: This work applies a bi-level optimization model for dynamic participation in peer-to-peer electricity trading to determine the optimal parameters of new participants who want to join an energy community, based on the preferences of the members of the original community (e.g., environmental, economic, or mixed preference). The upper-level problem chooses optimal parameters by minimizing an objective function that includes the prosumers' cost-saving and emission-saving preferences, while the lower level problem maximizes community welfare by optimally allocating locally generated photovoltaic (PV) electricity between members according to their willingness-to-pay. The bi-level problem is solved by transforming the lower level problem by its corresponding Karush-Kuhn-Tucker (KKT) conditions. Results: The results demonstrate that environment-oriented prosumers opt for a new prosumer with high PV capacities installed and low electricity demand, whereas profit-oriented prosumers prefer a new member with high demand but no PV system capacity, presenting a new source of income. Sensitivity analyses indicate that new prosumers' willingness-to-pay has an important influence when the community must decide between two new members. Conclusions: The added value of this work is that the proposed method can be seen as a basis for a selection process between a large number of potential new community members. Most important future work will include optimization of energy communities over the horizon several years.

Can detection and prediction models for Alzheimer’s Disease be applied to Prodromal Parkinson’s Disease using explainable artificial intelligence? A brief report on Digital Neuro Signatures.

Parkinson's disease (PD) is the fastest growing neurodegeneration and has a prediagnostic phase with a lot of challenges to identify clinical and laboratory biomarkers for those in the earliest stages or those 'at risk'. Despite the current research effort, further progress in this field hinges on the more effective application of digital biomarker and artificial intelligence applications at the prediagnostic stages of PD. It is of the highest importance to stratify such prediagnostic subjects that seem to have the most neuroprotective benefit from drugs. However, current initiatives to identify individuals at risk or in the earliest stages that might be candidates for future clinical trials are still challenging due to the limited accuracy and explainability of existing prediagnostic detection and progression prediction solutions. In this brief paper, we report on a novel digital neuro signature (DNS) for prodromal-PD based on selected digital biomarkers previously discovered on preclinical Alzheimer's disease. (AD). Our preliminary results demonstrated a standard DNS signature for both preclinical AD and prodromal PD, containing a ranked selection of features. This novel DNS signature was rapidly repurposed out of 793 digital biomarker features and selected the top 20 digital biomarkers that are predictive and could detect both the biological signature of preclinical AD and the biological mechanism of a-synucleinopathy in prodromal PD. The resulting model can provide physicians with a pool of patients potentially eligible for therapy and comes along with information about the importance of the digital biomarkers that are predictive, based on SHapley Additive exPlanations (SHAP). Similar initiatives could clarify the stage before and around diagnosis, enabling the field to push into unchartered territory at the earliest stages of the disease.

Drone-based electromagnetic survey system for geophysical applications

Geophysical electromagnetic (EM) methods are used in geological mapping, mineral exploration, groundwater studies and geotechnical investigations. Airborne EM methods have the benefit of avoiding terrain obstacles such as lakes, rivers, swamps, and ravines. Compared to manned aircrafts, drones or unmanned aerial vehicles (UAVs) have benefits of their own. Drone-based surveys are versatile, fast to deploy, economical and ecologically more friendly. Presently, magnetic surveying is the only geophysical method that is routinely conducted with drones. The modest maximum payload limit of drones imposes severe restrictions on the applicability of other methods including EM and radiometric methods, for example. Finnish company, Radai Ltd has been developing Louhi, a novel drone-based frequency-domain EM survey system, in an EU funded Horizon 2020 project NEXT – New Exploration Technologies. The EM system has two operation options – the first uses a large loop on the ground as an EM source and the other uses a small portable EM transmitter loop. Both systems utilize a stand-alone and light-weight three-component EM receiver that can be towed by a drone. This article presents the theoretical background of the EM methods, the solution developed by Radai Ltd, the current version of the EM device, and results from field and flight tests that demonstrate the applicability of the drone-based EM system under development.

Assessment of the efficacy of SARS-CoV-2 vaccines in non-human primate studies: a systematic review

Background: The outbreak of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the rapid and successful development of vaccines to help mitigate the effect of COVID-19 and circulation of the virus. Vaccine efficacy is often defined as capacity of vaccines to prevent (severe) disease. However, the efficacy to prevent transmission or infectiousness is equally important at a population level. This is not routinely assessed in clinical trials. Preclinical vaccine trials provide a wealth of information about the presence and persistence of viruses in different anatomical sites. Methods: We systematically reviewed all available preclinical SARS-CoV-2 candidate vaccine studies where non-human primates were challenged after vaccination (PROSPERO registration: CRD42021231199). We extracted the underlying data, and recalculated the reduction in viral shedding. We summarized the efficacy of vaccines to reduce viral RNA shedding after challenge by standardizing and stratifying the results by different anatomical sites and diagnostic methods. We considered shedding of viral RNA as a proxy measure for infectiousness. Results: We found a marked heterogeneity between the studies in the experimental design and the assessment of the outcomes. The best performing vaccine candidate per study caused only low (6 out of 12 studies), or moderate (5 out of 12) reduction of viral genomic RNA, and low (5 out of 11 studies) or moderate (3 out of 11 studies) reduction of subgenomic RNA in the upper respiratory tract, as assessed with nasal samples. Conclusions: Since most of the tested vaccines only triggered a low or moderate reduction of viral RNA in the upper respiratory tract, we need to consider that most SARS-CoV-2 vaccines that protect against disease might not fully protect against infectiousness and vaccinated individuals might still contribute to SARS-CoV-2 transmission. Careful assessment of secondary attack rates from vaccinated individuals is warranted. Standardization in design and reporting of preclinical trials is necessary.