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[EN] In this paper, we retrieve data about the frequent users of electronic commerce during the period 2011-2016 from the Spanish National Institute of Statistics. These data,coming from surveys, have intrinsic uncertainty that we describe using appropriate random variables. Then, we propose a stochastic model to study the dynamics of frequent users of electronic commerce. The goal of this paper is to solve the inverse problem that consists of determining themodel parameters as suitable parametric random variables, in such a way the model output be capable of capturing the data uncertainty, at the time instantswhere sample data are available, via adequate probability density functions. To achieve the aforementioned goal, we propose a computational procedure that involves building a nonlinear objective function, based on statistical moment measures, to be minimized using a variation of the particle swarm optimization algorithm.

The Minamata Convention on Mercury, with its objective to protect human health and the environment from the dangers of mercury (Hg), entered into force in 2017. The Convention outlines a life-cycle approach to the production, use, emissions, releases, handling, and disposal of Hg. As it moves into the implementation phase, scientific work and information are critically needed to support decision-making and management. This paper synthesizes existing knowledge and examines three areas in which researchers across the natural sciences, engineering, and social sciences can mobilize and disseminate knowledge in support of Hg abatement and the realization of the Convention’s objective: (1) uses, emissions, and releases; (2) support, awareness raising, and education; and (3) impacts and effectiveness. The paper ends with a discussion of the future of Hg science and policy. Keywords: environmental treaty implementation; mercury; minamata convention; science–policy; toxic pollution

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

[EN] In this paper, we retrieve data about the frequent users of electronic commerce during the period 2011-2016 from the Spanish National Institute of Statistics. These data,coming from surveys, have intrinsic uncertainty that we describe using appropriate random variables. Then, we propose a stochastic model to study the dynamics of frequent users of electronic commerce. The goal of this paper is to solve the inverse problem that consists of determining themodel parameters as suitable parametric random variables, in such a way the model output be capable of capturing the data uncertainty, at the time instantswhere sample data are available, via adequate probability density functions. To achieve the aforementioned goal, we propose a computational procedure that involves building a nonlinear objective function, based on statistical moment measures, to be minimized using a variation of the particle swarm optimization algorithm.

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

N ≤ 8 3-algebras have recently appeared in N-supersymmetric 3-dimensional Chern-Simons gauge theories. In our previous paper we classified linearly compact simple N = 8 n-algebras for any n ≥ 3. In the present paper we classify algebraic linearly compact simple N = 6 3-algebras over an algebraically closed field of characteristic 0, using their correspondence with simple linearly compact Lie superalgebras with a consistent short ℤ-grading, endowed with a graded conjugation. We also briey discuss N = 5 3-algebras.

Evaluation is a central and essential activity in conducting rigorous Design Science Research (DSR), yet there is surprisingly little guidance about designing the DSR evaluation activity beyond suggesting possible methods that could be used for evaluation. This paper extends the notable exception of theexisting framework of Pries-Heje et al [11] to address this problem. The paper proposes an extended DSR evaluation framework together with a DSR evaluation design method that can guide DSR researchers in choosing an appropriate strategy for evaluation of the design artifacts and design theories that form the output from DSR. The extended DSR evaluation framework asks the DSR researcher to consider (as input to the choice of the DSR evaluation strategy) contextual factors of goals, conditions, and constraints on the DSR evaluation, e.g. the type and level of desired rigor, the type of artifact, the need to support formative development of the designed artifacts, the properties of theartifact to be evaluated, and the constraints on resources available, such as time, labor, facilities, expertise, and access to research subjects. The framework and method support matching these in the first instance to one or more DSR evaluation strategies, including the choice of ex ante (prior to artifactconstruction) versus ex post evaluation (after artifact construction) and naturalistic (e.g., field setting) versus artificial evaluation (e.g., laboratory setting). Based on the recommended evaluation strategy(ies), guidance is provided concerning what methodologies might be appropriate within the chosenstrategy(ies).

This paper describes the Greek hoteliers’ attitudes about energy initiatives and their implementation to their facilities. The aim of this paper is to demonstrate the interaction between the users’ behaviour and the way energy is consumed in Greek hotels in a long-term period. This paper is part of a wider research project that explores the energy consumption in several Greek hotels. Through interviews with open-ended questions, their responses reveal their opinions and the level of information they have on the existing legislation-Greek and European- on energy use in buildings. Further than that, two scenarios are developed, using the Long Range Energy Alternative Planning software (LEAP). Each one of them exhibits different findings proposing significant but easy to apply alterations to hotels. The first one is the Business as Usual scenario, and it is developed based on the current trends in energy use in hotels. The second is the Policy scenario which is developed based on the existing legislative framework, Greek and EU.

This paper reports research findings of a corrosion sensing project for applying the electromechanical impedance method for paint coating damage detection. A piezoceramic patch attached to a structure can excite micro and local structural vibration when an alternating or random low voltage signal is applied. The resistance of the structure to the vibration excitation can be measured in terms of the electromechanical impedance. When a structure is damaged the impedance will change. This has been used for structural damage detection. The application of the impedance method for paint coating damage detection is a new exploration. In this paper, the impedance method is first introduced and then research findings on the feasibility of paint coating damage detection by the method is both theoretically and experimentally studied and results discussed.

In this paper, we present a real-time obstacle detection system for the mobility improvement for the visually impaired using a handheld Smartphone. Though there are many existing assistants for the visually impaired, there is not a single one that is low cost, ultra-portable, nonintrusive and able to detect the low-height objects on the floor. This paper proposes a system to detect any objects attached to the floor regardless of their height. Unlike some existing systems where only histogram or edge information is used, the proposed system combines both cues and overcomes some limitations of existing systems. The obstacles on the floor in front of the user can be reliably detected in real time using the proposed system implemented on a Smartphone. The proposed system has been tested in different types of floor conditions and a field trial on five blind participants has been conducted. The experimental results demonstrate its reliability in comparison to existing systems.

Several approaches for data interoperation identified by Karp have been implemented for biological databases. We extend Karp's approach for interoperation not only to protein databases but also to knowledge bases and other information sources. This paper outlines algebra for protein data source composition based on our existing work of Protein Ontology (PO). In this paper we consider the case of establishing correspondence between various protein data sources using semantic relationships over the conceptual framework of PO. Here we provide specific set of relationships over PO framework to cover data semantics for integrating data information from diverse protein data sources. These relationships help in defining semantic query algebra for PO to efficiently reason and query the instance store.

Object-Oriented (OO) conceptual modelling offers the power in describing and modelling real-word data semantics and their inter-relationships in a form that is precise and comprehensible to users [1]. Conversely, XML [2] is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems and databases. With the increased reliance on such self-describing, schema-based, semi-structured data language/(s), there exists a requirement to model, design, and manipulate XML data and the associated semantics at a higher level of abstraction than at the instance level.However, existing Object-Oriented conceptual modelling languages provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints, while most semi-structured schema languages lack the ability to provide higher levels of abstraction (such as conceptual models) that are easily understood by humans. To this end, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we use XML view as a case in point and proposed to model engineering. In this paper, we use XML views as a case in point and propose to model dynamic properties of a layered XML view model [3] using eXtensible Semantic (XSemantic) nets.In data molding, we can group the existing view models into four categories, namely [3]; (a) classical (or relational) views, (b) Object-Oriented (OO) views, (c) semi-structured (namely XML) view models [4-6, 3] and (d) view models for Semantic Web. Here, we focus only on view models for XML

The growing development of web-based reputation systems in the 21st century will have a powerful social and economic impact on both business entities and individual customers, because it makes transparent quality assessment on products and services to achieve customer assurance in the distributed web-based Reputation Systems. The web-based reputation systems will be the foundation for web intelligence in the future. Trust and Reputation help capture business intelligence through establishing customer trust relationships, learning consumer behaviour, capturing market reaction on products and services, disseminating customer feedback, buyers' opinions and end-user recommendations. It also reveals dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviours, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behaviour, sales, reputation of sellers, providers, products and services. Given the importance of reputation in this paper, we propose ontology for reputation. In the business world we can consider the reputation of a product or the reputation of a service or the reputation of an agent. In this paper we propose ontology for these entities that can help us unravel the components and conceptualise the components of reputation of each of the entities.

When considering information security and privacy issues most of the attention has previously focussed on data protection and the privacy of personally identifiable information (PII). What is often overlooked is consideration for the operational and transactional data. Specifically, the security and privacy protection of metadata and metastructure information of computing environments has not been factored in to most methods. Metadata, or data about data, can contain many personal details about an entity. It is subject to the same risks and malicious actions personal data is exposed to. This paper presents a new perspective for information security and privacy. It is termed Meta Privacy and is concerned with the protection and privacy of information system metadata and metastructure details. We first present a formal definition for meta privacy, and then analyse the factors that encompass and influence meta privacy. In addition, we recommend some techniques for the protection of meta privacy within the information systems. Further, the paper highlights the importance of ensuring all informational elements of information systems are adequately protected from a privacy perspective.

The growing development of web-based reputation systems in the 21st century will have a powerful social and economic impact on both business entities and individual customers, because it makes transparent quality assessment on products and services to achieve customer assurance in the distributed web-based Reputation Systems. The web-based reputation systems will be the foundation for web intelligence in the future. Trust and Reputation help capture business intelligence through establishing customer trust relationships, learning consumer behaviour, capturing market reaction on products and services, disseminating customer feedback, buyers? opinions and end-user recommendations. It also reveals dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviours, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behaviour, sales, reputation of sellers, providers, products and services. Given the importance of reputation in this paper, we propose ontology for reputation. In the business world we can consider the reputation of a product or the reputation of a service or the reputation of an agent. In this paper we propose ontology for these entities that can help us unravel the components and conceptualize the components of reputation of each of the entities.

Security and privacy are two primary concerns in RFID adoption. In this paper we focus on security issues in general and data tampering in particular. Here we present a conceptual framework to detect and identify data tampering in RFID tags. The paper surveys the existing literature and proposes to add a tamper detection component in the existing RFID middleware architecture. The tamper detection component is supported by mathematical algorithm to embed and extract secret information which can be employed to detect data tampering.

[EN] Healthcare service is a critical aspect of our daily lives. Enabled by technologies such as wearable devices and wireless sensor networks, tele-health has becoming a promising new field in IT industry. Wearable devices, which detect real-time human body conditions, form body sensor networks (BSNs) for patients. In a cloud-enabled tele-health ecosystem, health data are collected by the BSN and sent to mobile devices such as smart phones and tablets. These embedded devices process the data and forward them to remote data centers. Due to the energy and time constraints of embedded systems, the effectiveness of storage systems become a critical issue. For years, memory technologies such as SRAMs and DRAMs have been widely used in computer systems. SRAMs are fast while DRAMs have high density. However, SRAMs have the disadvantage of power leakage and low density. DRAMs are slower in read and write operations. New memory technology for embedded tele-health is needed. In the paper, we propose a hybrid memory system for embedded tele-health. We combine phase-change memory PCM with flash memory to meet energy and latency requirement while reducing capital expenditure. Moreover, the data allocation and storage on server side is also a challenging problem in tele-health. Effective storage system designs are desired to efficiently store and manage health care data from users. Therefore, in the paper, we design a ecosystem for tele-health including the memory storage for embedded devices and data storage for tele-health data centers. To fully utilize the proposed ecosystem, we design several resource allocation algorithms with dynamic programming and heuristics. The experiments show that our approaches can achieve up to 30% performance enhancement compared to greedy approaches.

[EN] Healthcare service is a critical aspect of our daily lives. Enabled by technologies such as wearable devices and wireless sensor networks, tele-health has becoming a promising new field in IT industry. Wearable devices, which detect real-time human body conditions, form body sensor networks (BSNs) for patients. In a cloud-enabled tele-health ecosystem, health data are collected by the BSN and sent to mobile devices such as smart phones and tablets. These embedded devices process the data and forward them to remote data centers. Due to the energy and time constraints of embedded systems, the effectiveness of storage systems become a critical issue. For years, memory technologies such as SRAMs and DRAMs have been widely used in computer systems. SRAMs are fast while DRAMs have high density. However, SRAMs have the disadvantage of power leakage and low density. DRAMs are slower in read and write operations. New memory technology for embedded tele-health is needed. In the paper, we propose a hybrid memory system for embedded tele-health. We combine phase-change memory PCM with flash memory to meet energy and latency requirement while reducing capital expenditure. Moreover, the data allocation and storage on server side is also a challenging problem in tele-health. Effective storage system designs are desired to efficiently store and manage health care data from users. Therefore, in the paper, we design a ecosystem for tele-health including the memory storage for embedded devices and data storage for tele-health data centers. To fully utilize the proposed ecosystem, we design several resource allocation algorithms with dynamic programming and heuristics. The experiments show that our approaches can achieve up to 30% performance enhancement compared to greedy approaches.

This paper investigates whether changes in Generally Accepted Accounting Principles (GAAP) affect corporate investment decisions. Using a sample containing forty nine changes in GAAP, I find that changes in accounting rules affect investment decisions. I then examine two mechanisms through which changes in GAAP affect investment. First, I find that changes in GAAP affect investment, particularly R&D expenditures, when firms have financial covenants that are affected by changes in GAAP. Second, I find evidence suggesting that the process of complying with some changes in GAAP alters managers’ information sets and consequently changes their investment decisions, particularly their capital and R&D expenditures and, to a weaker extent, their acquistion expenditures. This paper contributes to the literature on the real effects of accounting by providing evidence that accounting rules affect investment decisions even when the rule change does not concern the measurement and reporting of investment, and by documenting specific mechanisms through which the relation manifests.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

[EN] In wireless ad hoc networks, neighbor discovery is necessary as an initial step. In this work we present LECDH (Low Energy Collision Detection Hello), an energy-aware randomized handshake-based neighbor discovery protocol for static environments. We carried out simulations through Castalia 3.2 simulator and compared LECDH with an existing protocol EAH (Energy Aware Hello) used as reference. We conclude that the proposal outperforms the reference protocol both in one-hop and multi-hop environments in terms of Energy consumption, Discovery time, Number of discovered neighbors, Throughput, and Discoveries per packet sent, for high duty cycles. Moreover, for low number of nodes in LECDH, as the duty cycle is reduced the performance is better according to all 5 metrics in both environments. Overall, we found that our proposal follows more realistic assumptions and still allows nodes to succeed at discovering all their neighbors almost with probability 1. Moreover, a qualitative comparison of the reference solution and our proposal is included in this paper.

[EN] In recent years, SenticNet and OntoSenticNet have represented important developments in the novel interdisciplinary field of research known as sentic computing, enabling the development of a variety of Sentic applications. In this paper, we propose an extension of the OntoSenticNet ontology, named DomainSenticNet, and contribute an unsupervised methodology to support the development of domain-aware Sentic applications. We developed an unsupervised methodology that, for each concept in OntoSenticNet, mines semantically related concepts from WordNet and Probase knowledge bases and computes domain distributional information from the entire collection of Kickstarter domain-specific crowdfunding campaigns. Subsequently, we applied DomainSenticNet to a prototype tool for Kickstarter campaign authoring and success prediction, demonstrating an improvement in the interpretability of sentiment intensities. DomainSenticNet is an extension of the OntoSenticNet ontology that integrates each of the 100,000 concepts included in OntoSenticNet with a set of semantically related concepts and domain distributional information. The defined unsupervised methodology is highly replicable and can be easily adapted to build similar domain-aware resources from different domain corpora and external knowledge bases. Used in combination with OntoSenticNet, DomainSenticNet may favor the development of novel hybrid aspect-based sentiment analysis systems and support further research on sentic computing in domain-aware applications.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

India has committed to reducing the emissions intensity of GDP by 33-35% from the 2005 level by 2030 in alignment with objectives of the Paris Agreement. This will require a significant reduction in greenhouse gas (GHG) emissions from the food and land-use sector. In this paper, we construct three potential pathways for India to achieve its emissions target by 2050 involving moderate ambitions of mitigation action (BAU), moderate ambitions combined with achieving healthy diets (BAU + NIN), and high levels of mitigation action inclusive of healthy diets (SUSTAINABLE). Using an integrated accounting tool, the FABLE Calculator, that harmonizes various socioeconomic and biophysical data, we project these pathways under the conditions of cross-country balanced trade flows. Results from the projections show that the demand for cereals will increase by 2050, leading to increased GHG emissions under BAU. Under the SUSTAINABLE pathways, GHG emissions will decrease over the same period due to reduced demand for cereals, whereas significant crop productivity and harvest intensity gains would lead to increased crop production. The exercise reveals the indispensability of healthy diets, improved crop, and livestock productivity, and net-zero deforestation in achieving India's mid-century emission targets from the agriculture sector.

India has committed to reducing the emissions intensity of GDP by 33-35% from the 2005 level by 2030 in alignment with objectives of the Paris Agreement. This will require a significant reduction in greenhouse gas (GHG) emissions from the food and land-use sector. In this paper, we construct three potential pathways for India to achieve its emissions target by 2050 involving moderate ambitions of mitigation action (BAU), moderate ambitions combined with achieving healthy diets (BAU + NIN), and high levels of mitigation action inclusive of healthy diets (SUSTAINABLE). Using an integrated accounting tool, the FABLE Calculator, that harmonizes various socioeconomic and biophysical data, we project these pathways under the conditions of cross-country balanced trade flows. Results from the projections show that the demand for cereals will increase by 2050, leading to increased GHG emissions under BAU. Under the SUSTAINABLE pathways, GHG emissions will decrease over the same period due to reduced demand for cereals, whereas significant crop productivity and harvest intensity gains would lead to increased crop production. The exercise reveals the indispensability of healthy diets, improved crop, and livestock productivity, and net-zero deforestation in achieving India's mid-century emission targets from the agriculture sector.

The KM3NeT research infrastructure is under construction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at GeV–PeV neutrinos. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given, Postprint (published version)

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe.

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe.

The next generation of water Cherenkov neutrino telescopes in the Mediterranean Sea are under construction offshore France (KM3NeT/ORCA) and Sicily (KM3NeT/ARCA). The KM3NeT/ORCA detector features an energy detection threshold which allows to collect atmospheric neutrinos to study flavour oscillation. This paper reports the KM3NeT/ORCA sensitivity to this phenomenon. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4s if the true ordering is normal and 2.3s if inverted, after 3 years of data taking. The precision to measure ¿m2 32 and ¿23 were also estimated and found to be 85.10-6 eV2 and ( +1.9 -3.1)¿ for normal neutrino mass ordering and, 75.10-6 eV2 and ( +2.0 -7.0)¿ for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude ¿t event rate variations larger than 20% at 3s level., Peer Reviewed, Postprint (published version)

Let S be a set of n points in ℝd and let t>1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O(log n) times the length of a minimum spanning tree for S. The algorithm has running time O(n logd n). Applying recent results of Das, Narasimhan and Salowe to this t-spanner gives an O(n logd n) time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n 2) time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given., Let S be a set of n points in R(d) and let t > 1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O (log n) times the length of a minimum spanning tree for S. The algorithm has running time O (n log(d) n). Applying recent results of Das, Narasimhan, and Salowe to this t-spanner gives an O(n log(d) n)-time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n(2))-time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given.

Let S be a set of n points in ℝd and let t>1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O(log n) times the length of a minimum spanning tree for S. The algorithm has running time O(n logd n). Applying recent results of Das, Narasimhan and Salowe to this t-spanner gives an O(n logd n) time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n 2) time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given., Let S be a set of n points in R(d) and let t > 1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O (log n) times the length of a minimum spanning tree for S. The algorithm has running time O (n log(d) n). Applying recent results of Das, Narasimhan, and Salowe to this t-spanner gives an O(n log(d) n)-time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n(2))-time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given.

Let S be a set of n points in ℝd and let t>1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O(log n) times the length of a minimum spanning tree for S. The algorithm has running time O(n logd n). Applying recent results of Das, Narasimhan and Salowe to this t-spanner gives an O(n logd n) time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n 2) time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given., Let S be a set of n points in R(d) and let t > 1 be a real number. A t-spanner for S is a graph having the points of S as its vertices such that for any pair p, q of points there is a path between them of length at most t times the Euclidean distance between p and q. An efficient implementation of a greedy algorithm is given that constructs a t-spanner having bounded degree such that the total length of all its edges is bounded by O (log n) times the length of a minimum spanning tree for S. The algorithm has running time O (n log(d) n). Applying recent results of Das, Narasimhan, and Salowe to this t-spanner gives an O(n log(d) n)-time algorithm for constructing a t-spanner having bounded degree and whose total edge length is proportional to the length of a minimum spanning tree for S. Previously, no o(n(2))-time algorithms were known for constructing a t-spanner of bounded degree. In the final part of the paper, an application to the problem of distance enumeration is given.

This paper details the design, development and evaluation of an affective tutoring system (ATS)—an e-learning system that detects and responds to the emotional states of the learner. Research into the development of ATS is an active and relatively new field, with many studies demonstrating promising results. However, there is often no practical way to apply these findings in real-world settings. The ATS described in this paper utilizes a generic affective application model to infer and appropriately respond to the learner’s affective state. This approach brings several advantages, notably the potential direct support for re-use and retrospective addition of affect sensing functionality into existing e-learning software. Skin conductivity and heart rate variability measurements were used to infer affective activation and valence. The evaluation involved an experiment in which the effectiveness of the fully functional ATS was compared with that of a non-affective version, and was conducted with 40 adult participants. The evaluation of the effectiveness of this tutoring system showed that measurable improvements in perceived learning may be obtained with a modest level of software development.

This paper details the design, development and evaluation of an affective tutoring system (ATS)—an e-learning system that detects and responds to the emotional states of the learner. Research into the development of ATS is an active and relatively new field, with many studies demonstrating promising results. However, there is often no practical way to apply these findings in real-world settings. The ATS described in this paper utilizes a generic affective application model to infer and appropriately respond to the learner’s affective state. This approach brings several advantages, notably the potential direct support for re-use and retrospective addition of affect sensing functionality into existing e-learning software. Skin conductivity and heart rate variability measurements were used to infer affective activation and valence. The evaluation involved an experiment in which the effectiveness of the fully functional ATS was compared with that of a non-affective version, and was conducted with 40 adult participants. The evaluation of the effectiveness of this tutoring system showed that measurable improvements in perceived learning may be obtained with a modest level of software development.

The Immune System is, together with Central Nervous System, one of the most important and complex unit of our organism. Despite great advances in recent years that shed light on its understanding and in the unraveling of key mechanisms behind its functions, there are still many areas of the Immune System that remain object of active research. The development of in-silico models, bridged with proper biological considerations, have recently improved the understanding of important complex systems [1,2]. In this paper, after introducing major role players and principal functions of the mammalian Immune System, we present two computational approaches to its modeling; i.e., two in-silico Immune Systems. (i) A large-scale model, with a complexity of representation of 10[superscript 6] − 10[superscript 8] cells (e.g., APC, T, B and Plasma cells) and molecules (e.g., immunocomplexes), is here presented, and its evolution in time is shown to be mimicking an important region of a real immune response. (ii) Additionally, a viral infection model, stochastic and light-weight, is here presented as well: its seamless design from biological considerations, its modularity and its fast simulation times are strength points when compared to (i). Finally we report, with the intent of moving towards the virtual lymph note, a cost-benefits comparison among Immune System models presented in this paper.

This paper characterizes the optimal way for a principal to structure a rank-order tournament in a moral hazard setting (as in Lazear and Rosen in J Polit Econ 89:841–864, 1981). We find that it is often optimal to give rewards to top performers that are smaller in magnitude than corresponding punishments to poor performers. The paper identifies four reasons why the principal might prefer to give larger rewards than punishments: (1) R is small relative to P (where R is risk aversion and P is absolute prudence); (2) the distribution of shocks to output is asymmetric and the asymmetry takes a particular form; (3) the principal faces a limited liability constraint; and (4) there is agent heterogeneity of a particular form.

This special issue of Distributed Computing is based on papers that originally appeared as extended abstracts in the Proceedings of the 24th International Symposium on Distributed Computing (DISC2010), held in Cambridge, Massachusetts on August 13–15, 2010. The papers for the Special Issue were chosen by the Program Committee from the 32 regular papers presented at the Symposium, based on their quality and representation of the spectrum of topics encompassed by the Symposium. In addition to being reviewed, in preliminary form, by the Program Committee, the full papers submitted for the Special Issue were refereed according to the standard practices of Distributed Computing (due to time constrains, some papers could not appear in this volume). We thank the Members of the Editorial Board for their work in editing this issue, and the referees and the authors of these papers for their respective contributions.

In 1971, Knuth gave an O(n2)-time algorithm for the classic problem of finding an optimal binary search tree. Knuth’s algorithm works only for search trees based on 3-way comparisons, but most modern computers support only 2-way comparisons (<, ≤, =, ≥, and >). Until this paper, the problem of finding an optimal search tree using 2- way comparisons remained open — poly-time algorithms were known only for restricted variants. We solve the general case, giving (i) an O(n4)-time algorithm and (ii) an O(n log n)-time additive-3 approximation algorithm. For finding optimal binary split trees, we (iii) obtain a linear speedup and (iv) prove some previous work incorrect. © Springer-Verlag Berlin Heidelberg 2015.

This research deals with the hybridization of the two soft computing fields, which are the chaos theory and evolutionary computation. This paper aims on the investigations on the adaptive multi-chaos-driven evolutionary algorithm Differential Evolution (DE) concept. This paper is aimed at the embedding and adaptive alternating of set of two discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE. In this paper the novel adaptive concept of DE/rand/1/bin strategy driven alternately by two chaotic maps (systems) is introduced. From the previous research, it follows that very promising results were obtained through the utilization of different chaotic maps, which have unique properties with connection to DE. The idea is then to connect these two different influences to the performance of DE into the one adaptive multi-chaotic concept with automatic switching without prior knowledge of the optimization problem and without any manual setting of the "switching point". Repeated simulations were performed on the IEEE CEC 13 benchmark set. Finally, the obtained results are compared with state of the art adaptive representative jDE. © Springer International Publishing Switzerland 2015.

The isolation among physically co-located virtual machines is an important prerequisite for ensuring the security in a virtualized environment (VE). The VE should prevent from exploitation of sidechannels stemming from the usage of shared resources, being hardware or software. However, despite the presumed secure logical isolation, a possible information leakage beyond the boundaries of a virtual machine due to side-channel exploits is a key concern in the VE. Such exploits have been demonstrated in the academic world during the last years. This paper takes into consideration the side-channel attacks threat, and points out that the feasibility of a SCA strongly depends on the specific context of the execution environment. The paper proposes a framework for feasibility assessment of SCAs using cache-based exploits as an example scenario. Furthermore, we provide a proof of concept to show how the feasibility of cache-based SCAs can be assessed using the proposed approach. © Springer International Publishing Switzerland 2015.

The isolation among physically co-located virtual machines is an important prerequisite for ensuring the security in a virtualized environment (VE). The VE should prevent from exploitation of sidechannels stemming from the usage of shared resources, being hardware or software. However, despite the presumed secure logical isolation, a possible information leakage beyond the boundaries of a virtual machine due to side-channel exploits is a key concern in the VE. Such exploits have been demonstrated in the academic world during the last years. This paper takes into consideration the side-channel attacks threat, and points out that the feasibility of a SCA strongly depends on the specific context of the execution environment. The paper proposes a framework for feasibility assessment of SCAs using cache-based exploits as an example scenario. Furthermore, we provide a proof of concept to show how the feasibility of cache-based SCAs can be assessed using the proposed approach. © Springer International Publishing Switzerland 2015.

In 1971, Knuth gave an O(n2)-time algorithm for the classic problem of finding an optimal binary search tree. Knuth’s algorithm works only for search trees based on 3-way comparisons, but most modern computers support only 2-way comparisons (<, ≤, =, ≥, and >). Until this paper, the problem of finding an optimal search tree using 2- way comparisons remained open — poly-time algorithms were known only for restricted variants. We solve the general case, giving (i) an O(n4)-time algorithm and (ii) an O(n log n)-time additive-3 approximation algorithm. For finding optimal binary split trees, we (iii) obtain a linear speedup and (iv) prove some previous work incorrect. © Springer-Verlag Berlin Heidelberg 2015.

This research deals with the hybridization of the two soft computing fields, which are the chaos theory and evolutionary computation. This paper aims on the investigations on the adaptive multi-chaos-driven evolutionary algorithm Differential Evolution (DE) concept. This paper is aimed at the embedding and adaptive alternating of set of two discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE. In this paper the novel adaptive concept of DE/rand/1/bin strategy driven alternately by two chaotic maps (systems) is introduced. From the previous research, it follows that very promising results were obtained through the utilization of different chaotic maps, which have unique properties with connection to DE. The idea is then to connect these two different influences to the performance of DE into the one adaptive multi-chaotic concept with automatic switching without prior knowledge of the optimization problem and without any manual setting of the "switching point". Repeated simulations were performed on the IEEE CEC 13 benchmark set. Finally, the obtained results are compared with state of the art adaptive representative jDE. © Springer International Publishing Switzerland 2015.

It is well known that the validity of the so called Lenard–Magri scheme of integrability of a bi-Hamiltonian PDE can be established if one has some precise information on the corresponding 1st variational Poisson cohomology for one of the two Hamiltonian operators. In the first part of the paper we explain how to introduce various cohomology complexes, including Lie superalgebra and Poisson cohomology complexes, and basic and reduced Lie conformal algebra and Poisson vertex algebra cohomology complexes, by making use of the corresponding universal Lie superalgebra or Lie conformal superalgebra. The most relevant are certain subcomplexes of the basic and reduced Poisson vertex algebra cohomology complexes, which we identify (non-canonically) with the generalized de Rham complex and the generalized variational complex. In the second part of the paper we compute the cohomology of the generalized de Rham complex, and, via a detailed study of the long exact sequence, we compute the cohomology of the generalized variational complex for any quasiconstant coefficient Hamiltonian operator with invertible leading coefficient. For the latter we use some differential linear algebra developed in the Appendix., National Science Foundation (U.S.), ERC (Advanced Grant)

In our recent paper “The variational Poisson cohomology” (2011) we computed the dimension of the variational Poisson cohomology H[subscript K](V) for any quasiconstant coefficient ℓ × ℓ matrix differential operator K of order N with invertible leading coefficient, provided that V is a normal algebra of differential functions over a linearly closed differential field. In the present paper we show that, for K skewadjoint, the Z -graded Lie superalgebra H[subscript K](V) is isomorphic to the finite dimensional Lie superalgebra [˜ over H](Nℓ,S) . We also prove that the subalgebra of “essential” variational Poisson cohomology, consisting of classes vanishing on the Casimirs of K, is zero. This vanishing result has applications to the theory of bi-Hamiltonian structures and their deformations. At the end of the paper we consider also the translation invariant case., National Science Foundation (U.S.)

The skewfield K(∂) of rational pseudodifferential operators over a differential field K is the skewfield of fractions of the algebra of differential operators K[∂]. In our previous paper, we showed that any H ∈ K(∂) has a minimal fractional decomposition H = AB[superscript −1] , where A,B ∈ K[∂], B ≠ 0, and any common right divisor of A and B is a non-zero element of K . Moreover, any right fractional decomposition of H is obtained by multiplying A and B on the right by the same non-zero element of K[∂] . In the present paper, we study the ring M[subscript n](K(∂)) of n × n matrices over the skewfield K(∂). We show that similarly, any H ∈ M[subscript n](K(∂)) has a minimal fractional decomposition H = AB[superscript −1], where A,B ∈ M[subscript n](K[∂]), B is non-degenerate, and any common right divisor of A and B is an invertible element of the ring M[subscript n](K[∂]). Moreover, any right fractional decomposition of H is obtained by multiplying A and B on the right by the same non-degenerate element of M[subscript n](K[∂]). We give several equivalent definitions of the minimal fractional decomposition. These results are applied to the study of maximal isotropicity property, used in the theory of Dirac structures., National Science Foundation (U.S.)