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Despite the implementation of effective paediatric vaccination programmes, pertussis remains a global health problem. Disease epidemiology has changed over time, shifting towards the adolescent and adult populations. In adults, the true burden of pertussis is greatly underestimated and pertussis vaccine coverage rates are suboptimal, including individuals with chronic conditions. Here, we report the outcomes of a virtual international scientific workshop to assess the evidence on the burden of pertussis in older adults and identify potential solutions to improve uptake of pertussis vaccines. In adults, pertussis is underdiagnosed in part due to atypical or milder clinical presentation and the lack of testing and case confirmation. However, contemporary epidemiological data denoted an increase in the burden of pertussis among adolescents and adults. This might be related to a variety of reasons including the waning of immunity over time, the lack of booster vaccination, and the improved diagnostic methods that led to increased recognition of the disease in adults. Pertussis sequelae can be severe in older adults, particularly those with existing chronic medical conditions, and the vulnerability of these groups is further enhanced by low pertussis vaccine coverage. Possible measures to increase vaccine uptake include strengthening and harmonisation of immunisation guidelines, healthcare professionals taking a more active role in recommending pertussis vaccination, involvement of vaccination centres and pharmacies in the vaccination process, and improving knowledge of pertussis burden and vaccine efficacy among the general population.

First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person.This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions:Stress overload associated pathologiesMale and female healthPlanned pregnanciesPeriodontal healthEye disordersInflammatory disorders, wound healing and pain management with associated complicationsMetabolic disorders and suboptimal body weightCardiovascular pathologiesCancersStroke, particularly of unknown aetiology and in young individualsSleep medicineSports medicineImproved individual outcomes under pandemic conditions such as COVID-19.

European pharmaceutical companies have a legal requirement to provide non-promotional Medical Information (MI) services to support healthcare professionals (HCPs) who are using their medicinal products. While the industry has self-regulating bodies with established Codes of Practice, these mainly focus on promotional messaging and commercial activities. In the absence of similar frameworks for MI, such services struggle to understand how to meet HCP digital expectations, often in fear of breaching the promotional codes. This is limiting access to the wealth of non-promotional patient-focussed information held within the industry. Meanwhile, a large volume of unregulated, low-quality information can be readily found on the internet. To understand the current status, the Medical Information Leaders in Europe (MILE) industry association performed a benchmarking survey which explored the online MI service provision of 13 mid-large pharmaceutical companies across Europe. This highlighted a great diversity in approach in terms of geographical coverage and content. Visibility and access for HCPs is complex, compromising online engagement and website utilisation. This MILE position paper highlights the critical need to establish a clear governance model, which empowers pharmaceutical company MI functions to provide unbranded, non-promotional, medicinal product information sources to support HCP online information needs. It is essential to build confidence, transparency and trust by establishing a practical quality framework with principles and standards for online MI services for HCPs.

AI is considered as a rapidly advancing technological domain capable of altering every aspect of our lives and society. Many children may have used AI-assistants, and some have had the privilege of growing up with AI-assistants or AI-assisted smart devices in their homes. Educators across fields from computer science, AI, to education strongly suggest that it is crucial to help people understand the science behind AI, its limits, and potential societal impacts in our everyday lives as well as in the future. What is specifically urgent is to prepare K-12 students for their future professions, which might not currently exist, and becoming citizens capable of understanding and utilizing AI-enhanced technologies in the right way in the future so that they would not benefit some populations over others. AI4K12, a joint project between CSTA (CS Teacher Association) and AAAI (Association for Advancing Artificial Intelligence, is developing K-12 AI guidelines for teachers and students organized around the Five Big Ideas in AI which were introduced in 2019. Aligned with Computer Science Standards and the standards of the core subjects, the Five Big Ideas in AI can guide students’ learning of AI while learning computer science concepts and the concepts of other subjects. This position paper explores the idea to promote computing education, including computer science and computational thinking skills, and AI education through AI-powered educational robotics as a motivating learning tool.

Norm emergence is typically studied in the context of multiagent systems (MAS) where norms are implicit, and participating agents use simplistic decision-making mechanisms. These implicit norms are usually unconsciously shared and adopted through agent interaction. A norm is deemed to have emerged when a threshold or predetermined percentage of agents follow the “norm”. Conversely, in normative MAS, norms are typically explicit and agents deliberately share norms through communication or are informed about norms by an authority, following which an agent decides whether to adopt the norm or not. The decision to adopt a norm by the agent can happen immediately after recognition or when an applicable situation arises. In this paper, we make the case that, similarly, a norm has emerged in a normative MAS when a percentage of agents adopt the norm. Furthermore, we posit that agents themselves can and should be involved in norm synthesis, and hence influence the norms governing the MAS, in line with Ostrom’s eight principles. Consequently, we put forward a framework for the emergence of norms within a normative MAS, that allows participating agents to propose/request changes to the normative system, while special-purpose synthesizer agents formulate new norms or revisions in response to these requests. Synthesizers must collectively agree that the new norm or norm revision should proceed, and then finally be approved by an “Oracle”. The normative system is then modified to incorporate the norm.

Many home IoT devices suffer from poor security design and confusing interfaces, lowering the bar for successful cyberattacks. A popular approach to identify compromised IoT devices is network-based detection, in which network traffic is analyzed to fingerprint and identify such devices. However, while several network-based techniques for identifying misbehaving devices have been proposed, the role of the user in remediating IoT security incidents has been conspicuously overlooked.

In recent years, AI based on deep learning has achieved tremendous success in specialized tasks such as speech recognition, machine translation, and the detection of tumors in medical images. Despite these successes there are also some clear signs of the limitations of the current state-of-the-art in AI. For example, biases in AI-enabled face recognition and predictive policing have shown that prejudice in AI systems is a real problem that must be solved. In this position paper, we argue that current AI needs to be developed along four dimensions to become more generally applicable and trustworthy: environment, purpose, collaboration, and governance. Hybrid AI offers the potential for advancements along these four dimensions by combining two different paradigms in AI: knowledge-based reasoning and optimization, and data-driven machine learning

Threats take many forms, and understanding them in order to make organisations more cyber resilient remains challenging. Many resilience management models and standards exist. They can help enterprises recover from harmful incidents. No approach today comprehensively examines perspectives of resilience concerns. In this paper, I argue it is necessary to consider a much broader spectrum of threats and harms to better understand the complex dependencies and interactions between an enterprise (‘self’) and the environment (‘world’). This paper adapts Self-Discrepancy Theory from psychology to help establish and reason about multiple views of the ‘self’: the actual, ideal and ought enterprise, as viewed by the enterprise/risk owner and others (e.g. competitors). The paper investigates how changes in priorities and operations can affect the self (again, as viewed by the self and others). This framework does not compete with existing models and standards. Instead, the purpose of this work is to complement them by exhaustively considering different perspectives (views) of enterprises with the aim to re-contextualise resilience concerns. By using this framework, risk-owners can start making decisions with new insights, akin to: what would my opponent do in my position?; or, if I change my mission, what effect might this have on my security (and vice versa)? Viewing enterprise resilience from different perspectives is an underexplored topic in resilience and security research, and is a key motivation of this article. This is a position paper, and further studies will be necessary to provide empirical evidence of feasibility in real-world settings.

Enterprises are confronted with a highly competitive and fast-changing business environment resulting in an increasing level of cooperation between organizations. Cross-organizational processes (CBPs) aim to achieve an agreement between organizations at the process level in such an environment. An application of smart contracts and blockchain brings the unprecedented capability to execute CBPs in decentralized multi-peer environments and without central authorities to govern the workflow. However, the application of blockchain introduces various challenges due to the immutable nature of blockchain’s transaction data and the specific development and deployment life-cycle of smart contracts. In this position paper, we propose a high-level platform-independent framework for monitoring and validation of smart contracts utilizing process mining techniques. The main purpose of such a framework will be to support process engineers in the detection of nonconforming behavior, resolving detected discrepancies, and improving smart contracts.

This chapter discusses current clinical guidance for eating disorders and their relevance to boys and men experiencing eating disorders. Specifically, we assess clinical practice guidelines from the American Psychiatric Association, the National Institute for Health and Care Excellence, and the Royal Australian and New Zealand College of Psychiatrists, as well as a position paper from the Society for Adolescent Health and Medicine and a recent review article on medical management of eating disorders in adolescents. While many aspects of the current clinical guidance from these organizations are applicable to all genders, there are areas that do not effectively account for differences in eating disorder presentations in boys and men. Specifically, we summarize and provide suggestions for six major aspects of clinical guidance, including monitoring bone health, body mass index, treatment goal weight, refeeding protocols, testosterone testing, use of performance-enhancing substances, and muscle dysmorphia. Given that the evidence base to support clinical recommendations in eating disorders among boys and men is lacking, we also provide suggestions for areas of future research to strengthen the evidence base related to medical treatment in these domains.

This position paper presents preliminary findings from an ongoing systematic literature review over the usages of the ContSys standard ISO 13940 [7]. I show that the literature reveals several patterns of how “A system of concepts for the continuity of care” is understood and applied.

This position paper presents an unplugged, problem-solving-based approach for teaching computer science to children. Our approach is based on story telling, where each story consists of parallel parts, and aims at developing children’s observation and reasoning skills. The aim is to understand the global plot by identifying the interaction occurring among different characters in terms of synchronisation, collaboration and information sharing. In this sense we focus on concurrency, a very challenging computer science area, to show that children aged 7–14 can be exposed to real-life instantiations of a number of computer science concepts, understand them and even apply them in modelling and analysis contexts.

Blockchain technology presents an opportunity for industries to implement for a more transparent and sustainable business model. The fashion industry is notoriously known for its complex and opaque supply chain and its negative impact on the environment and the people involved in the processes along the fashion supply chain. To address these long-standing challenges, the integration of blockchain technology has the ability to be the solution towards an ethical supply chain network. The study contributes to the current state of the fashion supply chain and the challenges it faces, outlining what blockchain technology is and its benefits in the context of the fashion industry. It also captures consumer sentiment on the subject of sustainability and transparency in the fashion industry and the perceived use and adoption of technology.

The development and application of empathic virtual agents is rising fast in many fields, from rehabilitation to education, from mental health to personal wellbeing. The empathic agents should be developed to appropriately react to the user’s affective state, with the aim of establishing an emotional connection with him/her. We propose a position paper to shape the design of an Empathic Virtual Character to be included in an existing platform with exer-games supporting postural rehabilitation. The character will express emotions to the user with facial animations and speech statements. The character’s emotion to express will be based on the current user’s affective state, inferred by the input data. Finally, we propose a possible improvement of the developed interaction framework.

Machine Learning (ML) is increasingly deployed in complex application domains replacing human-decision making. While ML has been surprisingly successful, there are fundamental concerns in wide scale deployment without humans in the loop. A critical question is the trustworthiness of such ML systems. Although there is research towards making ML systems more trustworthy, there remain many challenges. In this position paper, we discuss the challenges and limitations of current proposals. We focus on a more adversarial approach, borrowing ideas from certification of security software with the Common Criteria. While it is unclear how to get strong trustworthy assurances for ML systems, we believe this approach can further increase the level of trust.

Producing automated vehicles (AVs) that are, and can be shown to be, safe is an ongoing challenge. This position paper draws on recent work to discuss alternative approaches to assessing AV safety, noting how AI can be a positive or negative influence it. It features suggestions to promote AV safety, drawing from practice and policy, and it ends with a speculation about a special new role for AI.

In this workshop position paper, we identify the importance of a proposed system to monitor and assess diabetic students using Internet of Things (IoT) technology and a decision support system. We survey the current studies on the application of IoT in the Saudi Arabian educational system and related work. The model of Unified Theory of Acceptance and Use of Technology will be used to specify the critical factors that affect the use of the system for diabetic students in Saudi Arabian high schools. Finally, our research is at the beginning phase, so future work will identify the academic issues of the diabetic students and factors that affect the system usage by using a mixed method approach. In addition, the proposed decision tree algorithm will be implemented and evaluated.

The research on software startups has increased lately, focusing on describing how these companies’ unique context influences development practices. The next step for research is the creation of specific practices for these companies grounded in scientific results. An obstacle in this path is which dependent variable these novel practices should improve. A natural answer is these companies’ success. This position paper reviews the literature on new ventures and startups’ success to show that telling if a startup is successful or not is a complex issue. As a solution to this problem, this paper proposes a conceptual framework, suggesting that novel practices should improve success determinants or reduce inhibitors rather than focusing on the startups’ success. Three examples illustrate the framework’s use: hypotheses engineering, microservices, and BizDev. The identification of contributors and inhibitors for success of software startups could enrich the framework and indicate possible avenues for the creation of development practices specific tailored for these companies.

Knowledge Bases (KBs) usually contain named entities. However, the majority of entities in natural language text are not named. In this position paper, we first study the nature of these entities. Then we explain how they could be represented in KBs. Finally, we discuss open challenges for adding non-named entities systematically to KBs.

In this position paper we argue that the best way to overcome the notorious knowledge bottleneck in AI is using lifelong learning by social intelligent agents. Keys to this capability are deep language understanding, dialog interaction, sufficiently broad-coverage and fine-grain knowledge bases to bootstrap the learning process, and the agent’s operation within a comprehensive cognitive architecture.

In this position paper, we discuss the introduction of spatial verification techniques in an application scenario from smart stations, viz. analysing the user experience with respect to the lighting conditions of station areas. This is a case study in industrial projects. We discuss three challenging use cases for the application of spatial model checking in this setting. First, we envision how to use the spatial model checker VoxLogicA, which can analyse both 2D and 3D voxel-based maps, to explore the areas that users can visit in a station area and to characterise them with respect to their illumination conditions. This is aimed at monitoring a smart station. We also ideate statistical spatio-temporal model checking of the design of energy-saving protocols, exploiting the modelling of user preferences. Finally, we discuss the idea of quantifying the impact of design changes, based on the logs of smart stations, to identify and measure the incidence of undesired events (e.g. non-illuminated platforms where a train is passing by) before and after each change.

Pedagogical conversational agents (PCA) aimed at offering personalized support could greatly enhance the student experience by adapting their support to the student’s learning needs and habits. But, as they become more autonomous, there is a greater need to consider the potential moral consequences of their choices and to take into consideration an holistic view of students. In face-to-face setting, the individual and holistic understanding that human teachers can have about their students and classrooms is key in ensuring that the teachers’ decisions strive for the best learning experience. However, furnishing PCAs with such a holistic understanding of complex dimensions that often involve relations between multiple elements poses a challenge. Furthermore, ethical aspects should also be considered in order to avoid decisions that can lead to discriminatory and unfair collateral results and end up favouring certain students over others; therefore, the PCA should be aware of how decisions aimed at satisfying certain needs could negatively affect other dimensions. The current position paper states the need to furnish PCAs with ethical awareness and discusses the nature of ethical dilemmas in the context of PCAs in online learning environments. Through this discussion, the paper proposes some first steps towards the design of ethically-aware PCAs.

Online Social Networks (OSNs) are very popular and widely adopted by the vast majority of Internet users across the globe. Recent scandals on the abuse of users’ personal information via these platforms have raised serious concerns about the trustworthiness of OSN service providers. The unprecedented collection of personal data by OSN service providers poses one of the greatest threats to users’ privacy and their right to be left alone. The recent approval of the GDPR (General Data Protection Regulation) presents OSN service providers with great compliance challenges. A set of new data protection requirements are imposed on data controllers (OSN service providers) by GDPR that offer greater control to data subjects (OSN users) over their personal data. This position paper investigates the link between GDPR provisions and the use of blockchain technology for solving the consent management problem in online social networks. We also describe challenges and opportunities in designing a GDPR-compliant consent management mechanism for online social networks. Key characteristics of blockchain technology that facilitate regulatory compliance were identified. The legal and technological state of play of the blockchain-GDPR relationship is reviewed and possible ways to reconcile blockchain technology with the GDPR requirements are demonstrated. This paper opens up new research directions on the use of the disruptive innovation of blockchain to achieve regulatory compliance in the application domain of online social networks.

This position paper introduces a Smart Innovation Environment for experimentation related to digital transformation projects, for the consolidation of a proposed "Digital Engineer" skill profile (with a business-oriented facet labelled as "Digital Innovator"). In the Internet of Things era, this profile implies the ability to perform both digital design and engineering activities, to semantically bridge multiple layers of abstraction and specificity - from business analysis down to cyber-physical engineering. In the paper's proposal, this integration is enabled by conceptual modelling methods and interoperable modelling tools, tailored to support the creation of Digital Twins for innovative digital business models. The architecture of the proposed environment is guided by a Design Research perspective - i.e., it is a treatment to an education "design problem" regarding the Digital Engineer skill profile in the IoT era. The proposed environment encompasses workspaces and toolkits are currently evaluated in "innovation corners" deployed across the OMiLAB ecosystem.

This position paper connects the areas and communities of abstract argumentation and attack-defence trees in the area of security. Both areas deal with attacks, defence and support and both areas rely on applications dealing with human aggressive activities. The unifying idea we use in this paper is to regard arguments as AND-OR attack trees as proposed by Schneier in the security domain. The core model, which is acceptable for both communities, is a pair \((\mathbf{S},\twoheadrightarrow )\), where S is a set of attack trees (the “arguments”) and \(\twoheadrightarrow \) is a binary relation on attack trees (the “attack” relation). This leads us to the notion of an attack-defence framework, which provides an argumentation-based semantics for attack-defence trees and more general attack-defence graphs.

Ontologies are widely used nowadays for many different purposes and in many different contexts, like industry and research, and in domains ranging from geosciences, biology, chemistry or medicine. When used for research, ontologies should be treated as other research artefacts, such as data, software, methods, etc.; following the same principles used to make them findable, accessible, interoperable and reusable (FAIR) to others. However, in comparison to the number of guides, indicators and recommendations available for making research data FAIR, not much attention has been paid so far on how to publish ontologies following the FAIR principles. This position paper reviews the technical and social needs required to define a roadmap for generating and publishing FAIR ontologies on the Web. We analyze four initiatives for ontology publication, aligning them in a common framework for comparison. The paper concludes by opening a discussion about existing, ongoing and required initiatives and instruments to facilitate FAIR ontology sharing on the Web.

The academic performance of a higher education student can be affected by several factors and in most cases Higher Education Institutions (HEI) have programs to intervene, prevent failure or students dropping out. These include student tutoring, mentoring, recovery classes, summer school, etc. Being able to identify the borderline cases is extremely important for planning and intervening in time. This position paper reports on an ongoing project, being developed at the University of Tras-os-Montes e Alto Douro (UTAD), which uses the students’ data and artificial intelligence algorithms to create models and predict the performance of students and classes. The main objective of the IA.EDU project is to research the usage of data, artificial intelligence and data science to create artificial intelligence solutions, including models and applications, to provide predictive information that can contribute to the increase in students’ academic success and a reduction in the dropout rate, by making it possible to act proactively with the students at risk, course directors and course designers.

The AI community today has renewed concern about the social implications of the models they design, imagining the impact of deployed systems. One thrust has been to reflect on issues of fairness and explainability before the design process begins. There is increasing awareness as well of the need to engender trust from users, examining the origins of mistrust as well as the value of multiagent trust modelling solutions. In this paper, we argue that social AI efforts to date often imagine a homogenous user base and those models which do support differing solutions for users with different profiles have not yet examined one important consideration upon which trusted AI may depend: the risk profile of the user. We suggest how user risk attitudes can be integrated into approaches that try to reason about such dilemmas as sacrificing optimality for the sake of explainability. In the end, we reveal that it is challenging to be satisfying the myriad needs of users in their desire to be more comfortable accepting AI solutions and conclude that tradeoffs need to be examined and balanced. We advocate reasoning about these tradeoffs concerning user models and risk profiles, as we design the decision making algorithms of our systems.

Neural networks have many applications in safety and mission critical systems. As industrial standards in various safety-critical domains require developers of critical systems to provide safety assurance, tools and techniques must be developed that enable effective creation of safety evidence for AI systems. In this position paper, we propose the use of rules extracted from neural networks as artefacts for safety evidence. We discuss the rationale behind the use of rules and illustrate it using the MNIST dataset.

Quality outcomes in emergency surgery are achieved by knowledge and training in emergency surgery. This requires standards and KPIs which need to be measured and reported regularly.

Digital enterprises and their networks increasingly rely on advanced decision-making capabilities, however, development of decision-making models requires significant effort and is often performed independently of other digitalization activities. Additionally, dynamic nature of many decision-making problems requires rapid ramp-up of decision-making capabilities. To addresses these challenges, this position paper proposes to elaborate a method for integrated on-demand decision modeling. The method combines mathematical programming and data analytics models to create case specific models on the basis of generic decision-making models. The integrated model and its data supply pipelines are configured using enterprise models allowing for consistent and rapid model deployment. The integrated model is intended for the trusted ICT supply chain configuration problem though it can be used for solving various types of decision-making problems. The main expected results are formulation of the new type decision-making model and the method for on-demand configuration of such models.

In this position paper we introduce Reowolf: an on-going project that aims to replace the decades-old application programming interface, BSD sockets, for communication on the Internet. A novel programming interface is being implemented at the systems level that is inter-operable with existing Internet applications.

Considering the lack of consensus on the deployment of facial recognition technologies, many organizations, including public bodies, NGOs and private companies have alerted public opinion and called for a broad debate on facial recognition. We believe that such a debate is indeed necessary. However, in order to be really productive, it is essential to ensure that arguments can be expressed and confronted in a rigorous way. The main objective of this position paper is to help set the terms of this debate on a solid basis. To this aim, we present an incremental and comparative risk-analysis methodology for facial recognition systems. The methodology introduces, for a better separation of concerns, four levels of analysis: the purpose, the means, the use of facial recognition and its implementation. We discuss each of these levels and illustrate them with examples based on recent developments. Interested readers can find more details, in particular about the use of ethical matrices to facilitate the analysis, in an extended version of this position paper published as an Inria report [7].

This position paper suggests the existence of a plurality of “general-purpose” AGI paradigms, each specific to a domain of experience. These paradigms are studied to answer the question of which AGI will be developed first. Finally, in order to make the case for AGI based on symbolic experience, preliminary results from Semiotic AI are discussed.

A possible practical engineering approach to creation of the general artificial intelligence is considered. The choice of approach is based on modular hierarchical representation of knowledge, where each module uses its own methods of representation and knowledge processing. Work with knowledge is done by a hierarchical multi-agent system. The description of system’s individual elements and information about the current development state are given.

Nursing home culture change movement advocates for care that is less hospital-like, and more patient-centered. Despite being a step towards the good direction in providing a proper service for elderly people, considering their well-being is not easy due to a number of factors as: specific treatments with a high price; the number of involved stakeholders (e.g. patient, doctors, relatives, nursing home clerks, funding organisations, etc); or the difficulties to gather an accurate measure for the patients well-being. In current position paper we devise some potential challenges that arise in this context and we provide our insights on potential techniques to solve them by means of a framework to automate the management of well-being goals in nursing homes. Ministerio de Economía y Competitividad BELI (TIN2015-70560-R) Ministerio de Ciencia, Innovación y Universidades Horatio RTI2018-101204-B-C21

There is no doubt that teachers play a central role sparking students’ interest in physics and supporting them in learning about physics. The question is, however, what teachers need to know and, more importantly, what other qualities teachers need to possess in order to meet the demands that come with that central role. In this position paper, I will address questions about the main issues we are currently facing in physics teacher education and what can be done about it. I will argue for a stronger focus on non-cognitive qualities of teacher professional competence, their role in the organization of high-quality physics instruction and how these qualities can be developed in physics teacher education.

The aim of this paper is to provide an outline of the minimal designation of resources for emergency surgery services. Major key performance indicators are identified to facilitate the validation of a safe delivery of acute patient care. The development of emergency surgical care should not be carried out in isolation. While there is no set formats or structures of an acute surgical care delivery model worldwide, this position paper provides an outline of a framework, which summarises the key principles of the designation of resources for emergency surgery.

This position paper analyses the multidisciplinarity of cognitive research and its challenges from three perspective: the foundations of cognitive science, which draw from logic and neuroscience and their interconnections in studying human logic; computation as a means to identify mathematical patterns in human cognition, represent them symbolically and use such representations in computer emulations of human cognitive activities and possibly verify properties of such activities; education, devising and implementing learning models that exploit as well as address human cognition.

This paper offers a Talmudic norms solution to the paradox of the heap. The claim is that the paradox arises because philosophers use the wrong language to discuss it. We need a language about objects which is capable of expressing not only the declarative properties of the object (such as being a heap) but also how the object/heap was constructed. Such a view of objects comes from the Talmudic theory of mixtures.

In this position paper, our goal is to argue the need for specific software development practices to early-stage startups. In order to reach this goal, we discuss the consequences of innovative and market-driven contexts, which are two of the key elements when describing software startups. We also argue that these practices could be applied to innovative initiatives within established companies since they share similar characteristics and challenges as those from startups.

Dividing interaction logs into meaningful segments has been a core problem in supporting users in search tasks for over 20 years. Research has brought up many different definitions: from simplistic mechanical sessions to complex search missions spanning multiple days. Having meaningful segments is essential for many tasks depending on context, yet many research projects over the last years still rely on early proposals. This position paper gives a quick overview of session identification development and questions the widespread use of the industry standard.

Compared with the general population, people with intellectual disabilities have worse health, lower levels of activity, and greater barriers to participating in fitness activities. Regular physical activity has positive effects on cardiovascular and psychosocial health and thus it is important to identify effective interventions for people with intellectual disabilities in everyday settings. In this position paper we present the design and development of prototypes of game-based eHealth solutions for behaviour change and health promotion by influencing physical activity. Participatory design and agile development have been applied in this project to deliver a system based on three solutions to promote, motivate and maintain physical activity in people with intellectual disabilities: Guided in-door bicycle exercise, guided out-door exercise and guided mild workouts. All the solutions provide virtual environments and motivation features adapted to people with intellectual disabilities for better engagement.