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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.

At present two growth models describe successfully the distribution of size and topological complexity in populations of dendritic trees with considerable accu- racy and simplicity, the BE model (Van Pelt et al. in J. Comp. Neurol. 387:325–340, 1997) and the S model (Van Pelt and Verwer in Bull. Math. Biol. 48:197–211, 1986). This paper discusses the mathematical basis of these models and analyzes quantita- tively the relationship between the BE model and the S model assumed in the literature by developing a new explicit equation describing the BES model (a dendritic growth model integrating the features of both preceding models; Van Pelt et al. in J. Comp. Neurol. 387:325–340, 1997). In numerous studies it is implicitly presupposed that the S model is conditionally linked to the BE model (Granato and Van Pelt in Brain Res. Dev. Brain Res. 142:223–227, 2003; Uylings and Van Pelt in Network 13:397–414, 2002; Van Pelt, Dityatev and Uylings in J. Comp. Neurol. 387:325–340, 1997; Van Pelt and Schierwagen in Math. Biosci. 188:147–155, 2004; Van Pelt and Uylings in Network. 13:261–281, 2002; Van Pelt, Van Ooyen and Uylings in Modeling Dendritic Geometry and the Development of Nerve Connections, pp 179, 2000). In this paper we prove the non-exactness of this assumption, quantify involved errors and determine the conditions under which the BE and S models can be separately used instead of the BES model, which is more exact but considerably more difficult to apply. This study leads to a novel expression describing the BE model in an analytical closed form, much more efficient than the traditional iterative equation (Van Pelt et al. in J. Comp. Neurol. 387:325–340, 1997) in many neuronal classes. Finally we propose a new algorithm in order to obtain the values of the parameters of the BE model when this growth model is matched to experimental data, and discuss its advantages and improvements over the more commonly used procedures., Ministerio de Educación (España), Depto. de Biodiversidad, Ecología y Evolución, Fac. de Óptica y Optometría, 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

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

[EN] Thanks to the improvements experienced in technology during the last few years, most especially in virtual reality systems, the number and potential of networked virtual environments or NVEs and their users have been increasing. NVEs aim to give distributed users a feeling of immersion in a virtual world and the possibility of interacting with other users or with virtual objects inside it, just like when they interact in the real world. Being able to provide that feeling and natural interactions when the users are geographically separated is one of the goals of these systems. Nevertheless, this goal is especially sensitive to different issues, such as different connections with heterogeneous throughput or particular network latencies, which can lead to consistency and synchronization problems and, thus, to a worsening of the users' quality of experience or QoE. With the purpose of solving these issues, researchers have proposed and evaluated numerous technical solutions, in fields like network architectures, data distribution and filtering, resource balancing, computing models, predictive modeling and synchronization in NVEs. This paper gathers and classifies them, summarizing their advantages and disadvantages, using a new way of classification. With the current increase in the number of NVEs and the multiple solutions proposed so far, this paper aims to become a useful tool and a starting point not only for future researchers in this field but also for those who are new to NVEs development, in which guaranteeing a good users' QoE is essential.

[EN] Thanks to the improvements experienced in technology during the last few years, most especially in virtual reality systems, the number and potential of networked virtual environments or NVEs and their users have been increasing. NVEs aim to give distributed users a feeling of immersion in a virtual world and the possibility of interacting with other users or with virtual objects inside it, just like when they interact in the real world. Being able to provide that feeling and natural interactions when the users are geographically separated is one of the goals of these systems. Nevertheless, this goal is especially sensitive to different issues, such as different connections with heterogeneous throughput or particular network latencies, which can lead to consistency and synchronization problems and, thus, to a worsening of the users' quality of experience or QoE. With the purpose of solving these issues, researchers have proposed and evaluated numerous technical solutions, in fields like network architectures, data distribution and filtering, resource balancing, computing models, predictive modeling and synchronization in NVEs. This paper gathers and classifies them, summarizing their advantages and disadvantages, using a new way of classification. With the current increase in the number of NVEs and the multiple solutions proposed so far, this paper aims to become a useful tool and a starting point not only for future researchers in this field but also for those who are new to NVEs development, in which guaranteeing a good users' QoE is essential.

[EN] Thanks to the improvements experienced in technology during the last few years, most especially in virtual reality systems, the number and potential of networked virtual environments or NVEs and their users have been increasing. NVEs aim to give distributed users a feeling of immersion in a virtual world and the possibility of interacting with other users or with virtual objects inside it, just like when they interact in the real world. Being able to provide that feeling and natural interactions when the users are geographically separated is one of the goals of these systems. Nevertheless, this goal is especially sensitive to different issues, such as different connections with heterogeneous throughput or particular network latencies, which can lead to consistency and synchronization problems and, thus, to a worsening of the users' quality of experience or QoE. With the purpose of solving these issues, researchers have proposed and evaluated numerous technical solutions, in fields like network architectures, data distribution and filtering, resource balancing, computing models, predictive modeling and synchronization in NVEs. This paper gathers and classifies them, summarizing their advantages and disadvantages, using a new way of classification. With the current increase in the number of NVEs and the multiple solutions proposed so far, this paper aims to become a useful tool and a starting point not only for future researchers in this field but also for those who are new to NVEs development, in which guaranteeing a good users' QoE is essential.

In the present paper, we propose a novel neu- ral procedure for signal processing and coding based on the subthreshold oscillations and resonance of the neural membrane potential that could be used by real neurons to perform frequency spectra analysis and information cod- ing of incoming signals. Taking into account the biophys- ical properties of the neural membranes, we note that the subthreshold resonant behaviour they exhibit can be used to analyse incoming signals and represent them in the fre- quency domain. We study the reliability of the representa- tion of signals depending on the biophysical parameters of the neurons, the fault-tolerance of this coding scheme and its robustness against noise and in the presence of spikes. The principal characteristics of our system are the use of the physical phenomenon of neural resonance (rarely con- sidered in the literature for signal coding); it fits well with the biophysical parameters of most neurons that exhibit subthreshold oscillations; it is compatible with experimen- tal data; and it can be easily integrated in a more general model of information processing and coding that includes communication between neurons based on spikes., Depto. de Biodiversidad, Ecología y Evolución, Fac. de Óptica y Optometría, TRUE, pub

Researchers in sustainability science deal with increasingly complex problems that cross administrative, geographical, disciplinary, and sectoral boundaries, and are characterized by high stakes and deep uncertainties. This in turn creates methodological challenges to frame, structure, and solve complex problems in science and practice. There is a long tradition in visualizing systems as diagrams, and concept and cognitive maps, but there is insufficient differentiation and comparison between these methods and no clear umbrella term has yet been established. Against this background, we systematically review three foundational methods from different academic disciplines—causal diagrams, concept mapping, and cognitive mapping. Comparing and contrasting them, we facilitate a coherent understanding of qualitative systems mapping (QSM) as an umbrella term. We then proceed to explore the evident intersections between these methods to showcase some of the inter- and transdisciplinary opportunities and challenges crystallizing in integrated QSM approaches. Finally, we share case study insights from the food–water–biodiversity nexus in Austria and elaborate on some of the methodological nuances to data integration in QSM. Overall, with this overview paper, we lay the groundwork for a systematic, transparent, and yet flexible development and application of QSM methods to support mixed-methods research design and clear case study documentation, as well as fostering effective inter- and transdisciplinary communication in sustainability science. Further research needs to explore these QSM applications in depth across alternative sustainability science contexts, particularly with respect to efficient and rigorous protocols for knowledge and data integration vis-a-vis complex problems and transdisciplinary research processes.

The Cherenkov Telescope Array and the KM3NeT neutrino telescopes are major upcoming facilities in the fields of gamma-ray and neutrino astronomy, respectively. Possible simultaneous production of rays and neutrinos in astrophysical accelerators of cosmic gamma-ray nuclei motivates a combination of their data. We assess the potential of a combined analysis of CTA and KM3NeT data to determine the contribution of hadronic emission processes in known Galactic gamma-ray emitters, comparing this result to the cases of two separate analyses. In doing so, we demonstrate the capability of GAMMAPY, an open-source software package for the analysis of gamma-ray data, to also process data from neutrino telescopes. For a selection of prototypical gamma-ray sources within our Galaxy, we obtain models for primary proton and electron spectra in the hadronic and leptonic emission scenario, respectively, by fitting published gamma-ray spectra. Using these models and instrument response functions for both detectors, we employ the GAMMAPY package to generate pseudo data sets, where we assume 200 h of CTA observations and 10 years of KM3NeT detector operation. We then apply a three-dimensional binned likelihood analysis to these data sets, separately for each instrument and jointly for both. We find that the largest benefit of the combined analysis lies in the possibility of a consistent modelling of the gamma-ray and neutrino emission. Assuming a purely leptonic scenario as input, we obtain, for the most favourable source, an average expected 68% credible interval that constrains the contribution of hadronic processes to the observed gamma-ray emission to below 15%., The KM3NeT Collaboration acknowledges the financial support of the funding agencies: Agence Nationale de la Recherche (contract ANR-15-CE31-0020), Centre National de la Recherche Scientifique (CNRS), Commission Européenne (FEDER fund and Marie Curie Program), LabEx UnivEarthS (ANR-10-LABX-0023 and ANR-18-IDEX-0001), Paris Île-de-France Region, France; Shota Rustaveli National Science Foundation of Georgia (SRNSFG, FR-22-13708), Georgia; The General Secretariat of Research and Innovation (GSRI), Greece; Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell’Università e della Ricerca (MIUR), PRIN 2017 program (Grant NAT-NET 2017W4HA7S) Italy; Ministry of Higher Education, Scientific Research and Innovation, Morocco, and the Arab Fund for Economic and Social Development, Kuwait; Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO), the Netherlands; The National Science Centre, Poland (2021/41/N/ST2/01177); National Authority for Scientific Research (ANCS), Romania; Grants PID2021-124591NB-C41, -C42, -C43 funded by MCIN/AEI/ 10.13039/501100011033 and, as appropriate, by “ERDF A way of making Europe”, by the “European Union” or by the “European Union NextGenerationEU/PRTR”, Programa de Planes Complementarios I+D+I (refs. ASFAE/2022/023, ASFAE/2022/014), Programa Prometeo (PROMETEO/2020/019) and GenT (refs. CIDEGENT/2018/034, /2019/043, /2020/049, /2021/23) of the Generalitat Valenciana, Junta de Andalucía (ref. SOMM17/6104/UGR, P18-FR-5057), EU: MSC program (ref. 101025085), Programa María Zambrano (Spanish Ministry of Universities, funded by the European Union, NextGenerationEU), Spain; The European Union’s Horizon 2020 Research and Innovation Programme (ChETEC-INFRA – Project no. 101008324). T. Unbehaun, L. Mohrmann, and S. Funk are members of the CTA Consortium. The paper has been reviewed by the CTA Consortium Speakers and Publications Office. This research has made use of the “Prod 5” CTA instrument response functions provided by the CTA Consortium a, Peer Reviewed, Article signat per 274 autors: T. Unbehaun, L. Mohrmann, S. Funk, i membres del "KM3NeT Collaboration": S. Aiello, A. Albert, S. Alves Garre, Z. Aly, A. Ambrosone, F. Ameli, M. Andre, E. Androutsou, M. Anghinolfi, M. Anguita, L. Aphecetche, M. Ardid, S. Ardid, H. Atmani, J. Aublin, C. Bagatelas, L. Bailly-Salins, B. Baret, S. Basegmez du Pree, Y. Becherini, M. Bendahman, F. Benfenati, M. Benhassi, D. M. Benoit, E. Berbee, V. Bertin, S. Biagi, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, M. Bouwhuis, C. Bozza, R. M. Bozza, H. Brânzaş, F. Bretaudeau, R. Bruijn, J. Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, D. Calvo, S. Campion, A. Capone, F. Carenini, V. Carretero, T. Cartraud, P. Castaldi, V. Cecchini, S. Celli, L. Cerisy, M. Chabab, M. Chadolias, A. Chen, S. Cherubini, T. Chiarusi, M. Circella, R. Cocimano, J. A. B. Coelho, A. Coleiro, R. Coniglione, P. Coyle, A. Creusot, A. Cruz, G. Cuttone, R. Dallier, Y. Darras, A. De Benedittis, B. De Martino, V. Decoene, R. Del Burgo, L. S. Di Mauro, I. Di Palma, A. F. Díaz, D. Diego-Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, E. Drakopoulou, D. Drouhin, R. Dvornický, T. Eberl, A. Eddymaoui, T. van Eeden, M. Eff, D. van Eijk, I. El Bojaddaini, S. El Hedri, A. Enzenhöfer, G. Ferrara, M. D. Filipović, F. Filippini, L. A. Fusco, J. Gabriel, T. Gal, J. García Méndez, A. Garcia Soto, C. Gatius Oliver, N. Geißelbrecht, H. Ghaddari, L. Gialanella, B. K. Gibson, E. Giorgio, A. Girardi, I. Goos, S. R. Gozzini, R. Gracia, K. Graf, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, J. J. Hernández-Rey, F. Huang, W. Idrissi Ibnsalih, G. Illuminati, C. W. James, M. de Jong, P. de Jong, B. J. Jung, P. Kalaczyński, O. Kalekin, U. F. Katz, N. R. Khan Chowdhury, A. Khatun, G. Kistauri, F. van der Knaap, A. Kouchner, V. Kulikovskiy, R. Kvatadze, M. Labalme, R. Lahmann, G. Larosa, C. Lastoria, A. Lazo, S. Le Stum, G. Lehaut, E. Leonora, N. Lessing, G. Levi, Membres del KM3Net: S. Aiello, A. Albert, S. Alves Garre, Z. Aly, A. Ambrosone, F. Ameli, M. Andre, E. Androutsou, M. Anghinolfi, M. Anguita, L. Aphecetche, M. Ardid, S. Ardid, H. Atmani, J. Aublin, C. Bagatelas, L. Bailly-Salins, B. Baret, S. Basegmez du Pree, Y. Becherini, M. Bendahman, F. Benfenati, M. Benhassi, D. M. Benoit, E. Berbee, V. Bertin, S. Biagi, M. Boettcher, M. Bou Cabo, J. Boumaaza, M. Bouta, M. Bouwhuis, C. Bozza, R. M. Bozza, H. Brânzaş, F. Bretaudeau, R. Bruijn, J. Brunner, R. Bruno, E. Buis, R. Buompane, J. Busto, B. Caiffi, D. Calvo, S. Campion, A. Capone, F. Carenini, V. Carretero, T. Cartraud, P. Castaldi, V. Cecchini, S. Celli, L. Cerisy, M. Chabab, M. Chadolias, A. Chen, S. Cherubini, T. Chiarusi, M. Circella, R. Cocimano, J. A. B. Coelho, A. Coleiro, R. Coniglione, P. Coyle, A. Creusot, A. Cruz, G. Cuttone, R. Dallier, Y. Darras, A. De Benedittis, B. De Martino, V. Decoene, R. Del Burgo, L. S. Di Mauro, I. Di Palma, A. F. Díaz, D. Diego-Tortosa, C. Distefano, A. Domi, C. Donzaud, D. Dornic, M. Dörr, E. Drakopoulou, D. Drouhin, R. Dvornický, T. Eberl, A. Eddymaoui, T. van Eeden, M. Eff, D. van Eijk, I. El Bojaddaini, S. El Hedri, A. Enzenhöfer, G. Ferrara, M. D. Filipović, F. Filippini, L. A. Fusco, J. Gabriel, T. Gal, J. García Méndez, A. Garcia Soto, C. Gatius Oliver, N. Geißelbrecht, H. Ghaddari, L. Gialanella, B. K. Gibson, E. Giorgio, A. Girardi, I. Goos, S. R. Gozzini, R. Gracia, K. Graf, D. Guderian, C. Guidi, B. Guillon, M. Gutiérrez, H. van Haren, A. Heijboer, A. Hekalo, L. Hennig, J. J. Hernández-Rey, F. Huang, W. Idrissi Ibnsalih, G. Illuminati, C. W. James, M. de Jong, P. de Jong, B. J. Jung, P. Kalaczyński, O. Kalekin, U. F. Katz, N. R. Khan Chowdhury, A. Khatun, G. Kistauri, F. van der Knaap, A. Kouchner, V. Kulikovskiy, R. Kvatadze, M. Labalme, R. Lahmann, G. Larosa, C. Lastoria, A. Lazo, S. Le Stum, G. Lehaut, E. Leonora, N. Lessing, G. Levi, M. Lindsey Clark, F. Longhitano, J. Majumdar, L. Malerba, J. Mańczak, A. Manfreda, Postprint (published version)

Researchers in sustainability science deal with increasingly complex problems that cross administrative, geographical, disciplinary, and sectoral boundaries, and are characterized by high stakes and deep uncertainties. This in turn creates methodological challenges to frame, structure, and solve complex problems in science and practice. There is a long tradition in visualizing systems as diagrams, and concept and cognitive maps, but there is insufficient differentiation and comparison between these methods and no clear umbrella term has yet been established. Against this background, we systematically review three foundational methods from different academic disciplines—causal diagrams, concept mapping, and cognitive mapping. Comparing and contrasting them, we facilitate a coherent understanding of qualitative systems mapping (QSM) as an umbrella term. We then proceed to explore the evident intersections between these methods to showcase some of the inter- and transdisciplinary opportunities and challenges crystallizing in integrated QSM approaches. Finally, we share case study insights from the food–water–biodiversity nexus in Austria and elaborate on some of the methodological nuances to data integration in QSM. Overall, with this overview paper, we lay the groundwork for a systematic, transparent, and yet flexible development and application of QSM methods to support mixed-methods research design and clear case study documentation, as well as fostering effective inter- and transdisciplinary communication in sustainability science. Further research needs to explore these QSM applications in depth across alternative sustainability science contexts, particularly with respect to efficient and rigorous protocols for knowledge and data integration vis-a-vis complex problems and transdisciplinary research processes.

Researchers in sustainability science deal with increasingly complex problems that cross administrative, geographical, disciplinary, and sectoral boundaries, and are characterized by high stakes and deep uncertainties. This in turn creates methodological challenges to frame, structure, and solve complex problems in science and practice. There is a long tradition in visualizing systems as diagrams, and concept and cognitive maps, but there is insufficient differentiation and comparison between these methods and no clear umbrella term has yet been established. Against this background, we systematically review three foundational methods from different academic disciplines—causal diagrams, concept mapping, and cognitive mapping. Comparing and contrasting them, we facilitate a coherent understanding of qualitative systems mapping (QSM) as an umbrella term. We then proceed to explore the evident intersections between these methods to showcase some of the inter- and transdisciplinary opportunities and challenges crystallizing in integrated QSM approaches. Finally, we share case study insights from the food–water–biodiversity nexus in Austria and elaborate on some of the methodological nuances to data integration in QSM. Overall, with this overview paper, we lay the groundwork for a systematic, transparent, and yet flexible development and application of QSM methods to support mixed-methods research design and clear case study documentation, as well as fostering effective inter- and transdisciplinary communication in sustainability science. Further research needs to explore these QSM applications in depth across alternative sustainability science contexts, particularly with respect to efficient and rigorous protocols for knowledge and data integration vis-a-vis complex problems and transdisciplinary research processes.

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.

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

[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.

[EN] Customer service measures are traditionally used to determine the performance or/and the control parameters of any inventory system. Among them, the fill rate is one of the most widely used in practice and is defined as the fraction of demand that is immediately met from shelf i.e. from the available on-hand stock. However, this definition itself set out several problems that lead to consider two different approaches to compute the fill rate: the traditional, which computes the fill rate in terms of units short; and the standard, which directly computes the expected satisfied demand. This paper suggest two expressions, the traditional and the standard, to compute the fill rate in the continuous reorder point, order quantity (s, Q) policy following these approaches. Experimental results shows that the traditional approach is biased since underestimate the real fill rate whereas the standard computes it accurately and therefore both approaches cannot be treated as equivalent. This paper focuses on the lost sales context and discrete distributed demands.

[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] 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] 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] 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.

It is more than 4 years since the 2030 agenda for sustainable development was adopted by the United Nations and its member states in September 2015. Several efforts are being made by member countries to contribute towards achieving the 17 Sustainable Development Goals (SDGs). The progress which had been made over time in achieving SDGs can be monitored by measuring a set of quantifiable indicators for each of the goals. It has been seen that geospatial information plays a significant role in measuring some of the targets, hence it is relevant in the implementation of SDGs and monitoring of their progress. Synoptic view and repetitive coverage of the Earth's features and phenomenon by different satellites is a powerful and propitious technological advancement. The paper reviews robustness of Earth Observation data for continuous planning, monitoring, and evaluation of SDGs. The scientific world has made commendable progress by providing geospatial data at various spatial, spectral, radiometric, and temporal resolutions enabling usage of the data for various applications. This paper also reviews the application of big data from earth observation and citizen science data to implement SDGs with a multi-disciplinary approach. It covers literature from various academic landscapes utilizing geospatial data for mapping, monitoring, and evaluating the earth's features and phenomena as it establishes the basis of its utilization for the achievement of the SDGs.

It is more than 4 years since the 2030 agenda for sustainable development was adopted by the United Nations and its member states in September 2015. Several efforts are being made by member countries to contribute towards achieving the 17 Sustainable Development Goals (SDGs). The progress which had been made over time in achieving SDGs can be monitored by measuring a set of quantifiable indicators for each of the goals. It has been seen that geospatial information plays a significant role in measuring some of the targets, hence it is relevant in the implementation of SDGs and monitoring of their progress. Synoptic view and repetitive coverage of the Earth's features and phenomenon by different satellites is a powerful and propitious technological advancement. The paper reviews robustness of Earth Observation data for continuous planning, monitoring, and evaluation of SDGs. The scientific world has made commendable progress by providing geospatial data at various spatial, spectral, radiometric, and temporal resolutions enabling usage of the data for various applications. This paper also reviews the application of big data from earth observation and citizen science data to implement SDGs with a multi-disciplinary approach. It covers literature from various academic landscapes utilizing geospatial data for mapping, monitoring, and evaluating the earth's features and phenomena as it establishes the basis of its utilization for the achievement of the SDGs.

It is more than 4 years since the 2030 agenda for sustainable development was adopted by the United Nations and its member states in September 2015. Several efforts are being made by member countries to contribute towards achieving the 17 Sustainable Development Goals (SDGs). The progress which had been made over time in achieving SDGs can be monitored by measuring a set of quantifiable indicators for each of the goals. It has been seen that geospatial information plays a significant role in measuring some of the targets, hence it is relevant in the implementation of SDGs and monitoring of their progress. Synoptic view and repetitive coverage of the Earth's features and phenomenon by different satellites is a powerful and propitious technological advancement. The paper reviews robustness of Earth Observation data for continuous planning, monitoring, and evaluation of SDGs. The scientific world has made commendable progress by providing geospatial data at various spatial, spectral, radiometric, and temporal resolutions enabling usage of the data for various applications. This paper also reviews the application of big data from earth observation and citizen science data to implement SDGs with a multi-disciplinary approach. It covers literature from various academic landscapes utilizing geospatial data for mapping, monitoring, and evaluating the earth's features and phenomena as it establishes the basis of its utilization for the achievement of the SDGs.

[EN] Recommender Systems support a broad range of domains, each with peculiarities that recommendation algorithms must consider to produce appropriate suggestions. In the paper, we bring attention to a little-studied scenario related to the news domain: recommendations catering to media journalists. Based on the particular needs inherent to a newsroom, the authors introduce SJORS, a wire news Recommender System that takes into account the activities of each journalist as well as other critical factors that arise in this particular domain, such as wire news recency. Given the nature of the items recommended, SJORS deals with the inherent ambiguity of natural language by exploiting different semantic techniques and technologies. The authors have conducted several experiments in a media company, which validated the performance and applicability of the system. Outcomes emerging from this work could be extended to other domains of interest, such as online stores, streaming platforms, or digital libraries, to name a few.

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.

© 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

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.

[EN] In a recent paper, a conformable fractional Newton-type method was proposed for solving nonlinear equations. This method involves a lower computational cost compared to other fractional iterative methods. Indeed, the theoretical order of convergence is held in practice, and it presents a better numerical behaviour than fractional Newton-type methods formerly proposed, even compared to classical Newton-Raphson method. In this work, we design a generalization of this method for solving nonlinear systems by using a new conformable fractional Jacobian matrix, and a suitable conformable Taylor power series; and it is compared with classical Newton's scheme. The necessary concepts and results are stated in order to design this method. Convergence analysis is made and a quadratic order of convergence is obtained, as in classical Newton's method. Numerical tests are made, and the Approximated Computational Order of Convergence (ACOC) supports the theory. Also, the proposed scheme shows good stability properties observed by means of convergence planes.

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.

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.

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.

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.

[EN] In a recent paper, a conformable fractional Newton-type method was proposed for solving nonlinear equations. This method involves a lower computational cost compared to other fractional iterative methods. Indeed, the theoretical order of convergence is held in practice, and it presents a better numerical behaviour than fractional Newton-type methods formerly proposed, even compared to classical Newton-Raphson method. In this work, we design a generalization of this method for solving nonlinear systems by using a new conformable fractional Jacobian matrix, and a suitable conformable Taylor power series; and it is compared with classical Newton's scheme. The necessary concepts and results are stated in order to design this method. Convergence analysis is made and a quadratic order of convergence is obtained, as in classical Newton's method. Numerical tests are made, and the Approximated Computational Order of Convergence (ACOC) supports the theory. Also, the proposed scheme shows good stability properties observed by means of convergence planes.