Value migration: digitalization of shipping as a mechanism of industry dethronement

In this conceptual paper, we review latest developments related to unmanned vessels and sketch potential scenarios that implicate with the existing maritime industry structure. On the one hand, we isolate a range of challenges that make the imminent realization of unmanned vessels seem like a rather utopian pursuit. On the other hand, we explain the reasons that may catalyse their emergence. Inspired by these opposing tensions, we highlight that the digital transformation of the shipping industry has the potential to enhance value within the industry’s ecosystem. However, we also contend that unmanned vessels -if realized- pose a very particular threat to the identity of the shipping industry as we know it. In particular, we build upon the concept of value migration and we highlight the drastic existential changes that may likely stem from a shift to non-seafarer-centric shipping. We conclude with questions that matter for industry dethronement purposes i.e., the possibility that existing industry structures may be substantially reconfigured following a removal of the seafarer as the nucleus of value creation in shipping

Reinforcement of wood with natural fibers

This paper describes an experimental programme which examines the reinforcement in flexure of timber beams with composite materials based on natural fibers in the form of fabrics made from hemp, flax, basalt and bamboo fibers. The industrial use of natural fibers has been continuously increasing since 1990s due to their advantages in terms of production costs, pollution emissions and energy consumption for production and disposal. The technique allows the reinforcement of the intrados of beams, avoiding the dismantling of the overlying part of the structure with significant savings in terms of costs and work time. The test program consists of three phases incorporating 45 beams. The bending tests on the wooden elements made it possible to measure the increase in capacity and stiffness resulting from the composite reinforcement. This was applied to beams, creating different arrangements and using different quantities (number of layers). Despite the diversity of the various tests carried out, the results obtained in some cases showed significant increases in terms of load-carrying capacity and in deflection ductility

Debatable results of surgery for lung cancer in a patient with long existing pulmonary metastases from differentiated thyroid carcinoma

Introduction: The appropriate following treatment in a patient with a new presented non-small cell lung cancer (NSCLC) and history of chronic lung metastases of thyroid origin has never been reported. In such cases, the presence of long­standing thyroid metastatic disease with proven “limited malignant potential” could be considered as a minor treatment problem justifying one’s the decision to focus on the primary lung carcinoma as the only serious threat for the patient’s life.Case report: We report the surgical treatment of a new presented NSCLC in a patient with chronic lung metastases of thyroid origin and we present all the diagnostic, staging and treatment problems.Conclusion: The therapeutic results of our surgical approach were not encouraging. This could be owed to our staging prob­lems of NSCLC and the well documented limited immunological response of such patients with multiple neoplasms

EU-NICE, Eurasian University Network for International Cooperation in Earthquakes

Despite the remarkable scientific advancements of earthquake engineering and seismology in many countries, seismic risk is still growing at a high rate in the world’s most vulnerable communities. Successful practices have shown that a community’s capacity to manage and reduce its seismic risk relies on capitalization on policies, on technology and research results. An important role is played by education, than contribute to strengthening technical curricula of future practitioners and researchers through university and higher education programmes. In recent years an increasing number of initiatives have been launched in this field at the international and global cooperation level. Cooperative international academic research and training is key to reducing the gap between advanced and more vulnerable regions. EU-NICE is a European Commission funded higher education partnership for international development cooperation with the objective to build capacity of individuals who will operate at institutions located in seismic prone Asian Countries. The project involves five European Universities, eight Asian universities and four associations and NGOs active in advanced research on seismic mitigation, disaster risk management and international development. The project consists of a comprehensive mobility scheme open to nationals from Afghanistan, Bangladesh, China, Nepal, Pakistan, Thailand, Bhutan, India, Indonesia, Malaysia, Maldives, North Korea, Philippines, and Sri Lanka who plan to enrol in school or conduct research at one of five European partner universities in Italy, Greece and Portugal. During the 2010-14 time span a total number of 104 mobilities are being involved in scientific activities at the undergraduate, masters, PhD, postdoctoral and academic-staff exchange levels. This high number of mobilities and activities is selected and designed so as to produce an overall increase of knowledge that can result in an impact on earthquake mitigation. Researchers, future policymakers and practitioners build up their curricula over a range of disciplines in the fields of engineering, seismology, disaster risk management and urban planning. Specific educational and research activities focus on earthquake risk mitigation related topics such as: anti-seismic structural design, structural engineering, advanced computer structural collapse analysis, seismology, experimental laboratory studies, international and development issues in disaster risk management, social-economical impact studies, international relations and conflict resolution

A development cooperation Erasmus Mundus partnership for capacity building in earthquake mitigation science and higher education

Successful practices have shown that a community’s capacity to manage and reduce its seismic risk relies on capitalization on policies, on technology and research results. An important role is played by education, than contribute to strengthening technical curricula of future practitioners and researchers through university and higher education programs. EUNICE is a European Commission funded higher education partnership for international development cooperation with the objective to build capacity of individuals who will operate at institutions located in seismic prone Asian Countries. The project involves five European Universities, eight Asian universities and four associations and NGOs active in advanced research on seismic mitigation, disaster risk management and international development. The project consists of a comprehensive mobility scheme open to nationals from Afghanistan, Bangladesh, China, Nepal, Pakistan, Thailand, Bhutan, India, Indonesia, Malaysia, Maldives, North Korea, Philippines, and Sri Lanka who plan to enroll in school or conduct research at one of five European partner universities in Italy, Greece and Portugal. During the 2010-14 time span a total number of 104 mobilities are being involved in scientific activities at the undergraduate, masters, PhD, postdoctoral and academic-staff exchange levels. Researchers, future policymakers and practitioners build up their curricula over a range of disciplines in the fields of earthquake engineering, seismology, disaster risk management and urban planning

Entropic Interactions in Suspensions of Semi-Flexible Rods: Short-Range Effects of Flexibility

We compute the entropic interactions between two colloidal spheres immersed in a dilute suspension of semi-flexible rods. Our model treats the semi-flexible rod as a bent rod at fixed angle, set by the rod contour and persistence lengths. The entropic forces arising from this additional rotational degree of freedom are captured quantitatively by the model, and account for observations at short range in a recent experiment. Global fits to the interaction potential data suggest the persistence length of fd-virus is about two to three times smaller than the commonly used value of $2.2 \mu {m}$.Comment: 4 pages, 5 figures, submitted to PRE rapid communication

A common framework for learning causality

[EN] Causality is a fundamental part of reasoning to model the physics of an application domain, to understand the behaviour of an agent or to identify the relationship between two entities. Causality occurs when an action is taken and may also occur when two happenings come undeniably together. The study of causal inference aims at uncovering causal dependencies among observed data and to come up with automated methods to find such dependencies. While there exist a broad range of principles and approaches involved in causal inference, in this position paper we argue that it is possible to unify different causality views under a common framework of symbolic learning.This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R. Diego Aineto is partially supported by the FPU16/03184 and Sergio Jimenez by the RYC15/18009, both programs funded by the Spanish government.Onaindia De La Rivaherrera, E.; Aineto, D.; Jiménez-Celorrio, S. (2018). A common framework for learning causality. Progress in Artificial Intelligence. 7(4):351-357. https://doi.org/10.1007/s13748-018-0151-yS35135774Aineto, D., Jiménez, S., Onaindia, E.: Learning STRIPS action models with classical planning. In: International Conference on Automated Planning and Scheduling, ICAPS-18 (2018)Amir, E., Chang, A.: Learning partially observable deterministic action models. J. Artif. Intell. Res. 33, 349–402 (2008)Asai, M., Fukunaga, A.: Classical planning in deep latent space: bridging the subsymbolic–symbolic boundary. In: National Conference on Artificial Intelligence, AAAI-18 (2018)Cresswell, S.N., McCluskey, T.L., West, M.M.: Acquiring planning domain models using LOCM. Knowl. Eng. Rev. 28(02), 195–213 (2013)Ebert-Uphoff, I.: Two applications of causal discovery in climate science. In: Workshop Case Studies of Causal Discovery with Model Search (2013)Ebert-Uphoff, I., Deng, Y.: Causal discovery from spatio-temporal data with applications to climate science. In: 13th International Conference on Machine Learning and Applications, ICMLA 2014, Detroit, MI, USA, 3–6 December 2014, pp. 606–613 (2014)Giunchiglia, E., Lee, J., Lifschitz, V., McCain, N., Turner, H.: Nonmonotonic causal theories. Artif. Intell. 153(1–2), 49–104 (2004)Halpern, J.Y., Pearl, J.: Causes and explanations: a structural-model approach. Part I: Causes. Br. J. Philos. Sci. 56(4), 843–887 (2005)Heckerman, D., Meek, C., Cooper, G.: A Bayesian approach to causal discovery. In: Jain, L.C., Holmes, D.E. (eds.) Innovations in Machine Learning. Theory and Applications, Studies in Fuzziness and Soft Computing, chapter 1, pp. 1–28. Springer, Berlin (2006)Li, J., Le, T.D., Liu, L., Liu, J., Jin, Z., Sun, B.-Y., Ma, S.: From observational studies to causal rule mining. ACM TIST 7(2), 14:1–14:27 (2016)Malinsky, D., Danks, D.: Causal discovery algorithms: a practical guide. Philos. Compass 13, e12470 (2018)McCain, N., Turner, H.: Causal theories of action and change. In: Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, AAAI 97, IAAI 97, 27–31 July 1997, Providence, Rhode Island, pp. 460–465 (1997)McCarthy, J.: Epistemological problems of artificial intelligence. In: Proceedings of the 5th International Joint Conference on Artificial Intelligence, Cambridge, MA, USA, 22–25 August 1977, pp. 1038–1044 (1977)McCarthy, J., Hayes, P.: Some philosophical problems from the standpoint of artificial intelligence. Mach. Intell. 4, 463–502 (1969)Pearl, J.: Reasoning with cause and effect. AI Mag. 23(1), 95–112 (2002)Pearl, J.: Causality: Models, Reasoning and Inference, 2nd edn. Cambridge University Press, Cambridge (2009)Spirtes, C.G.P., Scheines, R.: Causation, Prediction and Search, 2nd edn. The MIT Press, Cambridge (2001)Spirtes, P., Zhang, K.: Causal discovery and inference: concepts and recent methodological advances. Appl. Inform. 3, 3 (2016)Thielscher, M.: Ramification and causality. Artif. Intell. 89(1–2), 317–364 (1997)Triantafillou, S., Tsamardinos, I.: Constraint-based causal discovery from multiple interventions over overlapping variable sets. J. Mach. Learn. Res. 16, 2147–2205 (2015)Yang, Q., Kangheng, W., Jiang, Y.: Learning action models from plan examples using weighted MAX-SAT. Artif. Intell. 171(2–3), 107–143 (2007)Zhuo, H.H., Kambhampati, S: Action-model acquisition from noisy plan traces. In: International Joint Conference on Artificial Intelligence, IJCAI-13, pp. 2444–2450. AAAI Press (2013

Deepening democracy within Ireland's social partnership

Ireland's social partnership process, now under attack from a number of quarters, has repeatedly been charged with being 'undemocratic' in that it undermines the sovereign position of elected political representatives, with key policy formulation and decision-making taking place in fora outside the institutions of representative democracy. These critiques echo those against new forms of networked governance more globally. A key question therefore is how (and if) democracy may be deepened within social partnership or its potential successor(s). This article addresses this question by employing a post-liberal democratic framework to examine social partnership in practice, and by drawing lessons from another partnership process, Malawi's PRSP. Drawing from Malawi's experience, it is argued that democracy can be deepened within social partnership when governance deliberations and negotiations are conducted under conditions of vibrant public debate and genuine perspective-based representation, and when the communicative and discursive norms are widened to allow for such representation