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[EN] Recent trends in waste management have initiated interest in recycled materials for sound absorption applications. The present paper studies the possibility of paper sludge to be recycled as material for sound absorption applications. Paper sludge (PS) is the water treatment waste, produced during paper production. Two different methods were studied to produce paper sludge and slaked lime composite acoustic panels for sound absorption applications at low and mid-frequencies. The sound absorption coefficient of paper sludge composite panels is measured in an impedance tube using the two-microphone method. The samples produced with different methods showed different behaviours of sound absorption. The primary method to produce showed acoustic asymmetry in the vertical direction of the samples, and it was considerably fragile as well. An improved method to produce PS composite panels was proposed in this paper. Using this method, homogenous and robust acoustic panels were obtained.

[EN] Recent trends in waste management have initiated interest in recycled materials for sound absorption applications. The present paper studies the possibility of paper sludge to be recycled as material for sound absorption applications. Paper sludge (PS) is the water treatment waste, produced during paper production. Two different methods were studied to produce paper sludge and slaked lime composite acoustic panels for sound absorption applications at low and mid-frequencies. The sound absorption coefficient of paper sludge composite panels is measured in an impedance tube using the two-microphone method. The samples produced with different methods showed different behaviours of sound absorption. The primary method to produce showed acoustic asymmetry in the vertical direction of the samples, and it was considerably fragile as well. An improved method to produce PS composite panels was proposed in this paper. Using this method, homogenous and robust acoustic panels were obtained.

In the noncereal-producing areas, there is not enough straw to supply the amount required for animal bedding. However, pulp and paper mills produce tons of wood fiber wastes, including de-inking paper sludge (DPS), in which most toxic compounds are at their detection limit. Among the detected compounds in DPS, aluminum, copper, and polycyclic aromatic hydrocarbons (PAHs) are present and were selected as model molecules. In this context, broilers were submitted to a diet containing 0, 5, and 10% of their ration as DPS. In addition, broilers and pigs were grown on de-inking paper sludge and wood shavings beddings. The presence of aluminum and copper were evaluated in blood and bones, whereas the presence of PAHs was evaluated in fat, liver, meat, and urine or blood of broilers and pigs. Animal performances were also investigated. DPS bedding did not increase aluminum or copper contents of blood or bones or PAHs in animal tissues. Animal performances and health were similar on DPS and wood shaving beddings. Using DPS as bedding material provides an integrated source of disposal of DPS and animal manure.

What is the largest cube or sphere that a given rectangular piece of paper can wrap? This natural problem, which has plagued gift-wrappers everywhere, remains very much unsolved. Here we introduce new upper and lower bounds and consolidate previous results. Though these bounds rarely match, our results significantly reduce the gap.

This volume is devoted to the most recent discoveries in mathematics and statistics. It also serves as a platform for knowledge and information exchange between experts from industrial and academic sectors. The book covers a wide range of topics, including mathematical analyses, probability, statistics, algebra, geometry, mathematical physics, wave propagation, stochastic processes, ordinary and partial differential equations, boundary value problems, linear operators, cybernetics and number and functional theory. It is a valuable resource for pure and applied mathematicians, statisticians, engineers and scientists.

This volume is devoted to the most recent discoveries in mathematics and statistics. It also serves as a platform for knowledge and information exchange between experts from industrial and academic sectors. The book covers a wide range of topics, including mathematical analyses, probability, statistics, algebra, geometry, mathematical physics, wave propagation, stochastic processes, ordinary and partial differential equations, boundary value problems, linear operators, cybernetics and number and functional theory. It is a valuable resource for pure and applied mathematicians, statisticians, engineers and scientists.

In the noncereal-producing areas, there is not enough straw to supply the amount required for animal bedding. However, pulp and paper mills produce tons of wood fiber wastes, including de-inking paper sludge (DPS), in which most toxic compounds are at their detection limit. Among the detected compounds in DPS, aluminum, copper, and polycyclic aromatic hydrocarbons (PAHs) are present and were selected as model molecules. In this context, broilers were submitted to a diet containing 0, 5, and 10% of their ration as DPS. In addition, broilers and pigs were grown on de-inking paper sludge and wood shavings beddings. The presence of aluminum and copper were evaluated in blood and bones, whereas the presence of PAHs was evaluated in fat, liver, meat, and urine or blood of broilers and pigs. Animal performances were also investigated. DPS bedding did not increase aluminum or copper contents of blood or bones or PAHs in animal tissues. Animal performances and health were similar on DPS and wood shaving beddings. Using DPS as bedding material provides an integrated source of disposal of DPS and animal manure.

We developed AirTransNote, a computer-mediated classroom collaboration system. The system enables real-time note-sharing. AirTransNote manages notes written by students on paper and enables the teacher to browse through the notes or show them to the students. AirTransNote can analyze students’ answers, helping the teacher better understand their problems. The system is not meant to provide an alternative to the conventional way of instruction; rather, it is designed to enhance class interaction. We conducted a preliminary study using questionnaires and found that this system can be feasible to apply for classroom environment.

This paper concerns the Routh reduction procedure for Lagrangians systems with symmetry. It differs from the existing results on geometric Routh reduction in the fact that no regularity conditions on either the Lagrangian L or the momentum map JL are required apart from the momentum being a regular value of JL. The main results of this paper are: the description of a general Routh reduction procedure that preserves the Euler-Lagrange nature of the original system and the presentation of a presymplectic framework for Routh reduced systems. In addition, we provide a detailed description and interpretation of the Euler-Lagrange equa-tions for the reduced system. The proposed procedure includes Lagrangian systems with a non-positively definite kinetic energy metric., Depto. de Álgebra, Geometría y Topología, Fac. de Ciencias Matemáticas, Instituto de Matemática Interdisciplinar (IMI), TRUE, pub

Various security weaknesses have been identified in mobile ad-hoc networks (MANET). The paper focuses on MANET forensics whereby a third party can prove there was attack by collecting and analyzing evidence about it.The paper describes such a MANET forensics analysis method using a Bloomfilter., Lecture Notes in Computer Science

Participatory design has attracted attention as a design method in recent years. Scenario or Inclusive Design is one way to make users participate in the design process. In this paper, I report on some case studies in which the visually-impaired participated in the design process. The sighted designer worked together with the visually-impaired wearing eye masks. The visually-impaired could tell designers some problems in their lives or their demand which was difficult to express in words.

In this paper we have examined the effects of scenarios from a participatory design and cross-cultural perspective. The Scenario Exchange Project was an international workshop using scenarios. The participants were university students from Japan and Taiwan. The impetus behind this project was the practical demand for designers to correctly understand different cultures and design products and services. We confirmed that scenarios are effective techniques for bolstering participatory design. Furthermore, we have recognized that we must create new methods for describing the lifestyle and cultural background of personas.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

© 2002 Springer-Verlag London Limited. Part of the work has been performed under project CICYT TAP94-0832-C02-01. The constructive recommendations provided by the reviewers are also gratefully acknowledged., The key step in stereovision is image matching. This is carried out on the basis of selecting features, edge points, edge segments, regions, corners, etc. Once the features have been selected, a set of attributes (properties) for matching is chosen. This is a key issue in stereovision matching. This paper presents an approach for attribute selection in stereovision matching tasks based on a Probabilistic Neural Network, which allows the computation of a mean vector and a covariance matrix from which the relative importance of attributes for matching and the attribute interdependence can be derived. This is possible because the matching problem focuses on a pattern classification problem. The performance of the method is verified with a set of stereovision images and the results contrasted with a classical attribute selection method and also with the relevance concept., CICYT, Sección Deptal. de Arquitectura de Computadores y Automática (Físicas), Fac. de Ciencias Físicas, TRUE, pub

Since Arrow's main theorem showed the impossibility of a rational procedure in group decision making, many variations in restrictions and objectives have been introduced in order to find out the limits of such a negative result. But so far all those results are often presented as a proof of the great expected difficulties we always shall find pursuing a joint group decision from different individual opinions, if we pursue rational and ethical procedures. In this paper we shall review some of the alternative approaches fuzzy sets theory allows, showing among other things that the main assumption of Arrow's model, not being made explicit in his famous theorem, was its underlying binary logic (a crisp definition is implied in preferences, consistency, liberty, equality, consensus and every concept or piece of information). Moreover, we shall also point out that focusing the problem on the choice issue can be also misleading, at least when dealing with human behaviour., Depto. de Estadística e Investigación Operativa, Fac. de Ciencias Matemáticas, TRUE, pub

Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes)., Universidad Complutense, University of California, Depto. de Estadística e Investigación Operativa, Fac. de Ciencias Matemáticas, TRUE, pub

Mitigation activities, whether at the personal level relating to lifestyle or on the professional level, especially in the agriculture sector, are widely encouraged by scientists and policymakers. This research empirically analyses the association between agricultural experts’ perceptions about climate change and their intention to implement climate change mitigation. Based on survey data, individuals’ reported intention to implement personal and professional mitigation behavior is explained using a conceptual model. The structural equation modeling results suggest that the new ecological paradigm (NEP), institutional trust, and risk salience indirectly influence climate change mitigation intentions. The findings indicate that risk perception, personal efficacy, responsibility, belief in climate change occurring, and low psychological distance trigger a significantly greater intention to support personal and professional mitigation behaviors. However, the research framework is much stronger at predicting the intention to mitigate climate change in professional affairs compared to personal activities. The findings suggest that hypothetical distance factors only have a moderating effect on the relationship between higher climate change environmental values, institutional trust, risk salience, and mitigation intention. This paper analytically explores the regulating role of risk perception, hypothetical distance, personal efficacy, and responsibility between institutional trust, risk salience, and the NEP as independent concepts and intention to personal and professional mitigation behaviors as dependent variables. The findings of the study have important implications for encouraging personal and professional mitigation behaviors.

Mitigation activities, whether at the personal level relating to lifestyle or on the professional level, especially in the agriculture sector, are widely encouraged by scientists and policymakers. This research empirically analyses the association between agricultural experts’ perceptions about climate change and their intention to implement climate change mitigation. Based on survey data, individuals’ reported intention to implement personal and professional mitigation behavior is explained using a conceptual model. The structural equation modeling results suggest that the new ecological paradigm (NEP), institutional trust, and risk salience indirectly influence climate change mitigation intentions. The findings indicate that risk perception, personal efficacy, responsibility, belief in climate change occurring, and low psychological distance trigger a significantly greater intention to support personal and professional mitigation behaviors. However, the research framework is much stronger at predicting the intention to mitigate climate change in professional affairs compared to personal activities. The findings suggest that hypothetical distance factors only have a moderating effect on the relationship between higher climate change environmental values, institutional trust, risk salience, and mitigation intention. This paper analytically explores the regulating role of risk perception, hypothetical distance, personal efficacy, and responsibility between institutional trust, risk salience, and the NEP as independent concepts and intention to personal and professional mitigation behaviors as dependent variables. The findings of the study have important implications for encouraging personal and professional mitigation behaviors.

While collaborative filtering and citation analysis have been well studied for research paper recommender systems, content-based approaches typically restrict themselves to straightforward application of the vector space model. However, various types of metadata containing potentially useful information are usually available as well. Our work explores several methods to exploit this information in combination with different similarity measures.

For over a century, some economists have pointed out that upswings and down turns in economic activity (along with some key economic variables) seem to follow a surprisingly regular pattern -- a pattern sometimes labeled simply "Kondratieff long waves" in honor of the Russian economist who first rigorously described some of the phenomena leading to these changes. What might to be causes and consequences of these long-term fluctuations? What is the relationship between these so-called long waves and other structural changes, technical revolutions, financial and monetary variables? Finally, if the mechanisms of long waves can be understood, will it be possible to avoid the recurrent recessions in economic development that are as painful for the less developed countries as for the developed ones -- be they socialist or capitalist in orientation? By invitation, an international panel of distinguished scholars met in Weimar, GDR, to discuss these fascinating questions about the existence and nature of long waves. This conference was organized and sponsored jointly by the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria and the Institute of Theory, History and Organization of Science of the GDR Academy of Sciences, Berlin. A select group of 30 contributions comprise THE LONG-WAVE DEBATE, which thus represents the state of the art in the theory and empirical observation of long-term economic cycles.

This book stems from the effort within IIASA to explore possible "sustainable" global energy systems that might eventually replace the current "consumptive" system. In investigating the possible contributions nuclear technologies might make to a sustainable energy system, it had become clear that it is not so much particular, distinct technologies within the nuclear family that should be examined but rather particularly advantageous configurations of mutually complementary technologies. Only when one considers exploiting a whole spectrum of arrangements of fission breeders, fusion reactors, and accelerators does the true potential of nuclear power become apparent.

For over a century, some economists have pointed out that upswings and down turns in economic activity (along with some key economic variables) seem to follow a surprisingly regular pattern -- a pattern sometimes labeled simply "Kondratieff long waves" in honor of the Russian economist who first rigorously described some of the phenomena leading to these changes. What might to be causes and consequences of these long-term fluctuations? What is the relationship between these so-called long waves and other structural changes, technical revolutions, financial and monetary variables? Finally, if the mechanisms of long waves can be understood, will it be possible to avoid the recurrent recessions in economic development that are as painful for the less developed countries as for the developed ones -- be they socialist or capitalist in orientation? By invitation, an international panel of distinguished scholars met in Weimar, GDR, to discuss these fascinating questions about the existence and nature of long waves. This conference was organized and sponsored jointly by the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria and the Institute of Theory, History and Organization of Science of the GDR Academy of Sciences, Berlin. A select group of 30 contributions comprise THE LONG-WAVE DEBATE, which thus represents the state of the art in the theory and empirical observation of long-term economic cycles.

For over a century, some economists have pointed out that upswings and down turns in economic activity (along with some key economic variables) seem to follow a surprisingly regular pattern -- a pattern sometimes labeled simply "Kondratieff long waves" in honor of the Russian economist who first rigorously described some of the phenomena leading to these changes. What might to be causes and consequences of these long-term fluctuations? What is the relationship between these so-called long waves and other structural changes, technical revolutions, financial and monetary variables? Finally, if the mechanisms of long waves can be understood, will it be possible to avoid the recurrent recessions in economic development that are as painful for the less developed countries as for the developed ones -- be they socialist or capitalist in orientation? By invitation, an international panel of distinguished scholars met in Weimar, GDR, to discuss these fascinating questions about the existence and nature of long waves. This conference was organized and sponsored jointly by the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria and the Institute of Theory, History and Organization of Science of the GDR Academy of Sciences, Berlin. A select group of 30 contributions comprise THE LONG-WAVE DEBATE, which thus represents the state of the art in the theory and empirical observation of long-term economic cycles.

This book stems from the effort within IIASA to explore possible "sustainable" global energy systems that might eventually replace the current "consumptive" system. In investigating the possible contributions nuclear technologies might make to a sustainable energy system, it had become clear that it is not so much particular, distinct technologies within the nuclear family that should be examined but rather particularly advantageous configurations of mutually complementary technologies. Only when one considers exploiting a whole spectrum of arrangements of fission breeders, fusion reactors, and accelerators does the true potential of nuclear power become apparent.

[EN] The classical kinetic equation has been broadly used to describe reaction and deactivation processes in chemistry. The mathematical formulation of this deterministic nonlinear differential equation depends on reaction and deactivation rate constants. In practice, these rates must be calculated via laboratory experiments, hence involving measurement errors. Therefore, it is more realistic to treat these rates as random variables rather than deterministic constants. This leads to the randomization of the kinetic equation, and hence its solution becomes a stochastic process. In this paper we address the probabilistic analysis of a randomized kinetic model to describe reaction and deactivation by catalase of hydrogen peroxide decomposition at a given initial concentration. In the first part of the paper, we determine closed-form expressions for the probability density functions of important quantities of the aforementioned chemical process (the fractional conversion of hydrogen peroxide, the time until a fixed quantity of this fractional conversion is reached and the activity of the catalase). These expressions are obtained by taking extensive advantage of the so called Random Variable Transformation technique. In the second part, we apply the theoretical results obtained in the first part together with the principle of maximum entropy to model the hydrogen peroxide decomposition and aspergillus niger catalase deactivation using real data excerpted from the recent literature. Our results show full agreement with previous reported analysis but having as additional benefit that they provide a more complete description of both model inputs and outputs since we take into account the intrinsic uncertainties involved in modelling process

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flows within a spatially augmented Poisson interaction model. We explicitly distinguish FDI activities between three different stages of the value chain. Our results provide important insights on drivers of regional FDI activities, both from origin and destination perspectives. We moreover show that spatial dependence plays a key role in both dimensions.

[EN] The classical kinetic equation has been broadly used to describe reaction and deactivation processes in chemistry. The mathematical formulation of this deterministic nonlinear differential equation depends on reaction and deactivation rate constants. In practice, these rates must be calculated via laboratory experiments, hence involving measurement errors. Therefore, it is more realistic to treat these rates as random variables rather than deterministic constants. This leads to the randomization of the kinetic equation, and hence its solution becomes a stochastic process. In this paper we address the probabilistic analysis of a randomized kinetic model to describe reaction and deactivation by catalase of hydrogen peroxide decomposition at a given initial concentration. In the first part of the paper, we determine closed-form expressions for the probability density functions of important quantities of the aforementioned chemical process (the fractional conversion of hydrogen peroxide, the time until a fixed quantity of this fractional conversion is reached and the activity of the catalase). These expressions are obtained by taking extensive advantage of the so called Random Variable Transformation technique. In the second part, we apply the theoretical results obtained in the first part together with the principle of maximum entropy to model the hydrogen peroxide decomposition and aspergillus niger catalase deactivation using real data excerpted from the recent literature. Our results show full agreement with previous reported analysis but having as additional benefit that they provide a more complete description of both model inputs and outputs since we take into account the intrinsic uncertainties involved in modelling process

[EN] The classical kinetic equation has been broadly used to describe reaction and deactivation processes in chemistry. The mathematical formulation of this deterministic nonlinear differential equation depends on reaction and deactivation rate constants. In practice, these rates must be calculated via laboratory experiments, hence involving measurement errors. Therefore, it is more realistic to treat these rates as random variables rather than deterministic constants. This leads to the randomization of the kinetic equation, and hence its solution becomes a stochastic process. In this paper we address the probabilistic analysis of a randomized kinetic model to describe reaction and deactivation by catalase of hydrogen peroxide decomposition at a given initial concentration. In the first part of the paper, we determine closed-form expressions for the probability density functions of important quantities of the aforementioned chemical process (the fractional conversion of hydrogen peroxide, the time until a fixed quantity of this fractional conversion is reached and the activity of the catalase). These expressions are obtained by taking extensive advantage of the so called Random Variable Transformation technique. In the second part, we apply the theoretical results obtained in the first part together with the principle of maximum entropy to model the hydrogen peroxide decomposition and aspergillus niger catalase deactivation using real data excerpted from the recent literature. Our results show full agreement with previous reported analysis but having as additional benefit that they provide a more complete description of both model inputs and outputs since we take into account the intrinsic uncertainties involved in modelling process

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flows within a spatially augmented Poisson interaction model. We explicitly distinguish FDI activities between three different stages of the value chain. Our results provide important insights on drivers of regional FDI activities, both from origin and destination perspectives. We moreover show that spatial dependence plays a key role in both dimensions.

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flows within a spatially augmented Poisson interaction model. We explicitly distinguish FDI activities between three different stages of the value chain. Our results provide important insights on drivers of regional FDI activities, both from origin and destination perspectives. We moreover show that spatial dependence plays a key role in both dimensions.

This paper presents an empirical study of spatial origin and destination effects of European regional FDI dyads. Recent regional studies primarily focus on locational determinants, but ignore bilateral origin- and intervening factors, as well as associated spatial dependence. This paper fills this gap by using observations on interregional FDI flows within a spatially augmented Poisson interaction model. We explicitly distinguish FDI activities between three different stages of the value chain. Our results provide important insights on drivers of regional FDI activities, both from origin and destination perspectives. We moreover show that spatial dependence plays a key role in both dimensions.

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.

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.

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)

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.

[EN] In this paper, the most usual matrix partial orders are considered on the ring of real matrices. These orders are studied on at most index 1 matrices having nonnegative group projector by using a specific block structure. The goal of this paper is to analyze how this structure is inherited by predecessors ordered under minus, sharp, star, and one-sided orders. In addition, the case of arbitrary index (greater than 1) is also investigated by means of the cn-partial order and using the Drazin inverse.

[EN] The ant colony optimization (ACO) is inspired by the behavior of real ants, and as a bioinspired method, its underlying computation is massively parallel by definition. This paper shows re-engineering strategies to migrate the ACO algorithm applied to the Traveling Salesman Problem to modern Intel-based multi- and many-core architectures in a step-by-step methodology. The paper provides detailed guidelines on how to optimize the algorithm for the intra-node (thread and vector) parallelization, showing the performance scalability along with the number of cores on different Intel architectures, reporting up to 5.5x speedup factor between the Intel Xeon Phi Knights Landing and Intel Xeon v2. Moreover, parallel efficiency is provided for all targeted architectures, finding that core load imbalance, memory bandwidth limitations, and NUMA effects on data placement are some of the key factors limiting performance. Finally, a distributed implementation is also presented, reaching up to 2.96x speedup factor when running the code on 3 nodes over the single-node counterpart version. In the latter case, the parallel efficiency is affected by the synchronization frequency, which also affects the quality of the solution found by the distributed implementation.

[EN] Augmented Reality (AR) has become a mainstream technology in the development of solutions for repair and maintenance operations. Although most of the AR solutions are still limited to specific contexts in industry, some consumer electronics companies have started to offer pre-packaged AR solutions as alternative to video-based tutorials (VT) for minor maintenance operations. In this paper, we present a comparative study of the acquired knowledge and user perception achieved with AR and VT solutions in some maintenance tasks of IT equipment. The results indicate that both systems help users to acquire knowledge in various aspects of equipment maintenance. Although no statistically significant differences were found between AR and VT solutions, users scored higher on the AR version in all cases. Moreover, the users explicitly preferred the AR version when evaluating three different usability and satisfaction criteria. For the AR version, a strong and significant correlation was found between the satisfaction and the achieved knowledge. Since the AR solution achieved similar learning results with higher usability scores than the video-based tutorials, these results suggest that AR solutions are the most effective approach to substitute the typical paper-based instructions in consumer electronics.

[EN] When a video is encoded with constant quality, the resulting bitstream will have variable bitrate due to the inherent nature of the video encoding process. This paper proposes a video Adaptive Bitrate Streaming (ABR) algorithm, called Look Ahead, which takes into account this bitrate variability in order to calculate, in real time, the appropriate quality level that minimizes the number of interruptions during the playback. The algorithm is based on the Dynamic Adaptive Streaming over HTTP (DASH) standard for on-demand video services. In fact, it has been implemented and integrated into ExoPlayer v2, the latest version of the library developed by Google to play DASH contents. The proposed algorithm is compared to the Müller and Segment Aware Rate Adaptation (SARA) algorithms as well as to the default ABR algorithm integrated into ExoPlayer. The comparison is carried out by using the most relevant parameters that affect the Quality of Experience (QoE) in video playback services, that is, number and duration of stalls, average quality of the video playback and number of representation switches. These parameters can be combined to define a QoE model. In this sense, this paper also proposes two new QoE models for the evaluation of ABR algorithms. One of them considers the bitrate of every segment of each representation, and the second is based on VMAF (Video Multimethod Assessment Fusion), a Video Quality Assessment (VQA) method developed by Netflix. The evaluations presented in the paper reflect: first, that Look Ahead outperforms the Müller, SARA and the ExoPlayer ABR algorithms in terms of number and duration of video playback stalls, with hardly decreasing the average video quality; and second, that the two QoE models proposed are more accurate than other similar models existing in the literature.

[EN] The aim of this paper is to show how the number of conjugacy classes appearing in the product of classes affect the structure of a finite group. The aim of this paper was to show several results about solvability concerning the case in which the power of a conjugacy class is a union of one or two conjugacy classes. Moreover, we show that the above conditions can be determined through the character table of the group.

[EN] In this paper, the most usual matrix partial orders are considered on the ring of real matrices. These orders are studied on at most index 1 matrices having nonnegative group projector by using a specific block structure. The goal of this paper is to analyze how this structure is inherited by predecessors ordered under minus, sharp, star, and one-sided orders. In addition, the case of arbitrary index (greater than 1) is also investigated by means of the cn-partial order and using the Drazin inverse.