A new innovation paradigm: combining technological and social innovation

A new innovation paradigm is needed to answer the societal, economic and environmental challenges the world and companies are facing. The EU funded Horizon 2020 SPIRE Project “Coordinating Optimisation of Complex Industrial Processes” (COCOP) is combining technological and social innovation within a steel company pilot case (Sidenor). The project aims at reducing raw materials consumption (and energy and emissions reduction as well) by plant-wide optimisation of production processes based on a software solution and at the same time changing social practices. Key for COCOP is a methodology integrating technological innovation within a social innovation process of co-creation and co-development by involving (potential) users of the future software system and relevant stakeholders right from the beginning; thereby improving effectiveness and impact of the innovations and the implementation process. This involvement is instructed and measured by social key performance indicators (social KPIs) and operationalised in surveys (questionnaire and interviews) with future users, engineers and external experts (from different industry sectors not involved in the project). The article presents the results of the starting point of COCOP illustrating the future user perspective of the pilot steel company (Sidenor) contrasted by the view of external experts – seriously taking into account the interfaces between technology, human and organisation

Data Driven Performance Prediction in Steel Making

This work presents three data-driven models based on process data, to estimate different indicators related to process performance in a steel production process. The generated models allow the optimization of the process parameters to achieve optimal performance and quality levels. A new approach based on ensembles has been developed with feature selection methods and four state-of-the-art regression approximations (random forest, gradient boosting, xgboost and neural networks). The results show that the proposed approach makes the prediction more stable reducing the variance for all cases, even in one case, slightly reducing the bias. Furthermore, from the four machine learning paradigms presented, random forest is the one with the best results in a quantitative way, obtaining a coefficient of determination of 0.98 as a maximum, depending on the target sub-process.This research is supported by the European Union’s Horizon 2020 Research and Innovation Framework Programme [grant agreement No 723661; COCOP; http://www.cocop-spire.eu (accessed on 6 January 2022)]. The authors want to acknowledge the work of the whole COCOP consortium

Temporal variations in vertical cloud structure of Jupiter’s Great Red Spot, its surroundings and Oval BA from HST/WFC3 imaging

In this study, we present the evolution of the properties and vertical distribution of the hazes in Jupiter's Great Red Spot (GRS), its surroundings and Oval BA from 2015 to 2021. To retrieve the main atmospheric parameters, we model the spectral reflectivity of a number of dynamically and/or spectrally interesting regions with a radiative transfer tool that uses an optimal estimator scheme. The spectra of the selected regions are obtained from high-resolution Hubble Space Telescope Wide Field Camera 3 images that cover the spectral range from 200 to 900 nm. The a priori model atmosphere used to describe the various Jovian regions is taken from Anguiano-Arteaga et al. (2021, https://doi.org/10.1029/2021JE006996) for each corresponding area. We find that the biggest variations in the GRS occur in the optical thickness of the stratospheric and tropospheric haze layers starting in 2019 and in the mean size of the tropospheric haze particles in 2018. The absorption spectra of both hazes show little variations among the analyzed regions and years, with the stratospheric haze properties seeming compatible with the chromophore proposed by Carlson et al. (2016, https://doi.org/10.1016/j.icarus.2016.03.008). We report a color change of Oval BA from red to white during these years that, according to our models, can be mostly explained in terms of a decrease in the stratospheric haze optical depth

The effect of basketball footwear on the vertical ground reaction force during the landing phase of drop jumps

Even though the aetiology of overuse injuries is multifactorial, repetitive impacts and insufficient cushioning have been pointed out as the main causes of injury. These impacts are characterized at the vertical ground reaction force by 2 peaks. The first corresponds to the landing of the forefoot (F1) and the second (F2), associated to the production of injuries. Basketball footwear, due to its design and materials, might also help cushion the impact of the foot with the ground. Nevertheless, it has not been ascertained whether this footwear reduce the impact of the foot with the ground. The aim was to determine the effect of basketball footwear on the vertical ground reaction force during the landing phase of drop jumps. Thirteen students of the University of the B. Country (age = 21.54 ± 1.12 yr; body mass = 71.83 ± 8.15 kg; height = 177 ± 7 cm) took part. They all were required to perform 3 drop landings (DL) from 30 cm (DL30) and 60 cm (DL60) high in 2 different conditions: with basketball footwear or with running footwear. Resting period between jumps was 60-90 s. We presented data from 30 cm, 2.27 ± 1.07, v (m. s-1) with basketball footwear and 2.49 ± 1.23 v (m • s-1) with the alternative one. In F2, the analysis concluded that the parameter in both, 30 cm and 60 cm, presented differences between basketball and running sport shoes (6.20 ± 1.93 vs. 5.72 ± 1.79 Bw; 9.34 ± 2.16 vs. 8.27 ± 2.07 Bw). The F2 values recorded with running shoes were lower than those recorded when wearing basketball footwear (DL30: 11.13% DL60: 11.46%). The fore and rear foot impacts and loading rate are higher when jumping from 60 cm under both conditions. The F2 was the only statistically distinctive parameter between shoe conditions from both heights with lower values for nonbasketball footwear.Aunque la etiología de las lesiones por sobreuso es multifactorial, los impactos repetidos y la amortiguación insuficiente, han sido propuestos como dos de las principales causas de lesión. Los impactos son caracterizados por la fuerza de reacción vertical del suelo en dos picos. El primero de ellos, se corresponde con el aterrizaje de la parte delantera del pie (F1) y el segundo (F2), esta mas asociado a la producción de lesiones. El calzado de baloncesto, debido a su diseño y materiales, también podría ayudar a amortiguar el impacto del pie con la tierra. Sin embargo, no ha sido averiguado aún, si este calzado reduce dicho impacto. Objetivo. El objetivo de este estudio, fue determinar que el efecto del calzado de baloncesto sobre la fuerza de reacción de la tierra en la componente vertical durante el aterrizaje. Treinta estudiantes de la Universidad del País Vasco (Edad = 21.54 ± 1.12 años; masa corporal = 71.83 ± 8.15 kg; Altura = 177 ± 7 cm) tomaron parte en este estudio. Todos ellos, realizaron 3 aterrizajes, después de ejecutar un salto drop (DL) desde 30 cm (DL30) y desde 60 cm (DL60) de altura, en 2 condiciones diferentes: con calzado de baloncesto o con calzado de running. El periodo de descanso entre saltos fue de entre 60 a 90 sg. Se presentan datos desde 30 cm de altura, 2.27 ± 1.07, v (m. s-1) con calzado de baloncesto y de 2.49 ± 1.23 v (m • s-1 ) con calzado de running. Respecto a F2, el análisis concluyó que en ambas alturas desde 30 cm y desde 60 cm, se presentaron diferencias entre las botas de baloncesto y el calzado de running (6.20 ± 1.93 vs. 5.72 ± 1.79 Bw; 9.34 ± 2.16 vs. 8.27 ± 2.07 Bw). Los valores de F2 registrados con calzado de running fueron más bajos que losregistrados con los de baloncesto (DL30: 11.13% DL60: 11.46%). Los impactos de la parte delantera y de reverso, son más altos cuando se ejecutan los saltos desde 60 cm con ambos calzados. El parámetro F2, fue el único estadísticamente distinto entre ambos calzados, desde ambas alturas de salto, con valores más bajos para el calzado de running.Embora a etiologia das lesões por sobrecarga seja multifactorial, os impactos repetidos e o amortecimento insuficiente, têm sido propostos como duas das principais causas das lesões. Os impactos são caracterizados pela força de reacção vertical ao solo em dois picos. O primeiro, corresponde à aterragem com a parte dianteiro do pé (F1) e o segundo (F2), está mais associado à ocorrência de lesões. O calçado de basquetebol, devido ao seu design e materiais, também poderia ajudar a amortecer o impacto do pé com o solo. No entanto, não se verificou ainda, se este calçado reduz o dito impacto. Objetivo: o objetivo deste estudo foi determinar o efeito do calçado de basquetebol na força de reacção no solo na componente vertical durante a aterragem. Trinta estudantes da Universidade do País Basco (idade = 21.54 ± 1.12 anos, massa corporal = 71.83 ± 8.15 kg, altura = 177 ± 7 cm) participaram neste estudo. Todos eles, realizaram três aterragens, após a execução de um salto drop (DL) desde 30 cm (DL30) e desde 60 cm (DL60) de altura, em duas situações diferentes: com calçado de basquetebol ou de corrida. O período de descanso entre saltos compreendeu-se entre os 60 e 90 seg. Os dados são apresentados a partir dos 30 cm de altura, 2.27 ± 1.07, v (m. s-1), com calçado de basquetebol e de 2.49 ± 1.23 v (m • s-1 ) com calçado de corrida. Quanto F2, a análise concluiu que, em ambos alturas de 30 cm e de 60 cm, havia diferenças entre o calçado de basquetebol e de corrida (6.20 ± 1.93 vs 5.72 ± 1,79 BW; 9.34 ± 2.16 vs 8.27 ± 2.7 pc). Os valores de F2, registados com calçado de corrida foram mais baixos que os registados com o de basquetebol (DL30: DL60% 11,13: 11,46%). Os impactos da parte dianteira e de trás, são mais elevados durante a execução de saltos de 60 cm, com ambos os calçados. O parâmetro F2, foi o único estatisticamente diferente entre os dois calçados, em ambas as alturas de salto, com valores mais baixos para o calçado de corrid

Trait anxiety is associated with attentional brain networks

Trait anxiety is a well-established risk factor for anxiety and depressive disorders, yet its neural correlates are not clearly understood. In this study, we investigated the neural correlates of trait anxiety in a large sample (n = 179) of individuals who completed the trait and state versions of the State-Trait Anxiety Inventory and underwent resting-state functional magnetic resonance imaging. We used independent component analysis to characterize individual resting-state networks (RSNs), and multiple regression analyses to assess the relationship between trait anxiety and intrinsic connectivity. Trait anxiety was significantly associated with intrinsic connectivity in different regions of three RSNs (dorsal attention network, default mode network, and auditory network) when controlling for state anxiety. These RSNs primarily support attentional processes. Notably, when state anxiety was not controlled for, a different pattern of results emerged, highlighting the importance of considering this factor in assessing the neural correlates of trait anxiety. Our findings suggest that trait anxiety is uniquely associated with resting-state brain connectivity in networks mainly supporting attentional processes. Moreover, controlling for state anxiety is crucial when assessing the neural correlates of trait anxiety. These insights may help refine current neurobiological models of anxiety and identify potential targets for neurobiologically-based interventions

Convective storms in closed cyclones in Jupiter's South Temperate Belt: (I) observations

On May 31, 2020 a short-lived convective storm appeared in one of the small cyclones of Jupiter's South Temperate Belt (STB) at planetographic latitude 30.8S. The outbreak was captured by amateur astronomer Clyde Foster in methane-band images, became widely known as Clyde's Spot, and was imaged at very high resolution by the Junocam instrument on board the Juno mission 2.5 days later. Junocam images showed a white two-lobed cyclonic system with high clouds observed in the methane-band at 890 nm. The storm evolved over a few days to become a dark feature that showed turbulence for months, presented oscillations in its drift rate, and slowly expanded, first into a Folded Filamentary Region (FFR), and later into a turbulent segment of the STB over a timescale of one year. On August 7, 2021, a new storm strikingly similar to Clyde's Spot erupted in a cyclone of the STB. The new storm exhibited first a similar transformation into a turbulent dark feature, and later transformed into a dark cyclone fully formed by January 2022. We compare the evolution into a FFR of Clyde's Spot with the formation of a FFR observed by Voyager 2 in 1979 in the South South Temperate Belt (SSTB) after a convective outburst in a cyclone that also developed a two-lobed shape. We also discuss the contemporaneous evolution of an additional cyclone of the STB, which was similar to the one were Clyde's Spot developed. This cyclone did not exhibit visible internal convective activity, and transformed from pale white in 2019, with low contrast with the environment, to dark red in 2020, and thus, was very similar to the outcome of the second storm. This cyclone became bright again in 2021 after interacting with Oval BA. We present observations of these phenomena obtained by amateur astronomers, ground-based telescopes, Hubble Space Telescope and Junocam. This study reveals that short-lived small storms that are active for only a few days can produce complex longterm changes that extend over much larger areas than those initially covered by the storms. In a second paper [In tilde urrigarro et al., 2022] we use the EPIC numerical model to simulate these storms and study moist convection in closed cyclones.We are very thankful to the large community of amateur observers operating small telescopes that submit their Jupiter observations to databases such as PVOL and ALPO-Japan. We are also grateful to two anonymous reviewers for their comments that improved the clarity of this paper. This work has been supported by Grant PID2019-109467GB-I00 funded by MCIN/AEI/10.13039/501100011033/and by Grupos Gobierno Vasco IT1366-19. PI acknowledges a PhD scholarship from Gobierno Vasco. GSO and TM were supported by NASA with funds distributed to the Jet Propulsion Laboratory, California Institute of Technology under contract 80NM0018D0004. C. J. Hansen was sup-ported by funds from NASA, USA to the Juno mission via the Planetary Science Institute. IOE was supported by a contract funded by Europlanet 2024 RI to navigate Junocam images, now available as maps in PVOL at http://pvol2.ehu.eus. Europlanet 2024 RI has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 871149. G.S. Orton, S. R. Brueshaber, T. W. Momary, K. H. Baines and E. K. Dahl were visiting Astronomers at the Infrared Telescope Facility, which is operated by the University of Hawaii under contract 80HQTR19D0030 with the National Aeronautics and Space Administration. In addition, support from NASA Juno Participating Scientist award 80NSSC19K1265 was provided to M.H. Wong. This work has used data acquired from the NASA/ESA Hubble Space Telescope (HST) , which is operated by the Association of 807 Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. These HST observations are associated with several HST observing programs: GO/DD 14661 (PI: M.H. Wong) , GO/DD 15665 (PI: I. de Pater) , GO/DD 15159 (PI: M. H. Wong) , GO/DD 15502 (PI: A. Simon) , GO/DD 14661 (PI: M. H. Wong) , GO/DD 16074 (PI: M.H. Wong) , GO/DD 16053 (PI: I. de Pater) , GO/DD 15929 (PI: A. Simon) , GO/DD 16269 (PI: A. Simon) . PlanetCam observations were collected at the Centro Astronomico Hispanico en Andalucia (CAHA) , operated jointly by the Instituto de Astrofisica de Andalucia (CSIC) and the Andalusian Universities (Junta de Andalucia) . This work was enabled by the location of the IRTF and Gemini North telescopes within the Mauakea Science Reserve, adjacent to the summit of Maunakea. We are grateful for the privilege of observing Kaawela (Jupiter) from a place that is unique in both its astronomical quality and its cultural signifi-cance. This research has made use of the USGS Integrated Software for Imagers and Spectrometers (ISIS) . Voyager 2 images were accessed through The PDS Ring-Moon Systems Nodes OPUS search service

Estudio radiativo dinámico de la gran mancha roja de Júpiter

180 p.Esta Tesis se centra en el estudio de la Gran Mancha Roja de Júpiter (GRS, por sus siglas en inglés), su entorno y el Óvalo BA. En primer lugar, se analizan desde el punto de vista dinámico las interacciones que la GRS experimentó con una serie de vórtices en 2019. Mediante este análisis, se identifican las zonas de interés para su estudio mediante modelización de transporte radiativo. Se estudiaron un total de 13 regiones para el período de tiempo comprendido entre 2015 y 2021 empleando imágenes de la cámara WFC3 del Telescopio Espacial Hubble. En concreto, se analizan las propiedades de las nieblas y nubes para niveles de presión inferiores a 1 bar. Entre otras conclusiones, encontramos un colorante compatible con el agente más prometedor en la literatura. En cuanto al Óvalo BA, el cambio de color rojizo a blanquecino entre 2018 y 2019 es explicado por nuestro modelo con una reducción en la concentración de dicho agente colorante en el óvalo. Finalmente, se presenta una exploración de las condiciones microfísicas para la generación de aerosoles en la GRS, incluyendo el desarrollo de un código unidimensional que trata el transporte vertical de partículas

A new innovation paradigm: combining technological and social innovation

A new innovation paradigm is needed to answer the societal, economic and environmental challenges the world and companies are facing. The EU funded Horizon 2020 SPIRE Project “Coordinating Optimisation of Complex Industrial Processes” (COCOP) is combining technological and social innovation within a steel company pilot case (Sidenor). The project aims at reducing raw materials consumption (and energy and emissions reduction as well) by plant-wide optimisation of production processes based on a software solution and at the same time changing social practices. Key for COCOP is a methodology integrating technological innovation within a social innovation process of co-creation and co-development by involving (potential) users of the future software system and relevant stakeholders right from the beginning; thereby improving effectiveness and impact of the innovations and the implementation process. This involvement is instructed and measured by social key performance indicators (social KPIs) and operationalised in surveys (questionnaire and interviews) with future users, engineers and external experts (from different industry sectors not involved in the project). The article presents the results of the starting point of COCOP illustrating the future user perspective of the pilot steel company (Sidenor) contrasted by the view of external experts – seriously taking into account the interfaces between technology, human and organisation

Data Driven Performance Prediction in Steel Making

This work presents three data-driven models based on process data, to estimate different indicators related to process performance in a steel production process. The generated models allow the optimization of the process parameters to achieve optimal performance and quality levels. A new approach based on ensembles has been developed with feature selection methods and four state-of-the-art regression approximations (random forest, gradient boosting, xgboost and neural networks). The results show that the proposed approach makes the prediction more stable reducing the variance for all cases, even in one case, slightly reducing the bias. Furthermore, from the four machine learning paradigms presented, random forest is the one with the best results in a quantitative way, obtaining a coefficient of determination of 0.98 as a maximum, depending on the target sub-process

Model-Based Decision Support System for Electric Arc Furnace (EAF) Online Monitoring and Control

In this work, a practical approach for a decision support system for the electric arc furnace (EAF) is presented, with real-time heat state monitoring and control set-point optimization, which has been developed within the EU-funded project REVaMP and applied at the EAF of Sidenor in Basauri, Spain. The system consists of a dynamic process model based on energy and mass balances, including thermodynamic calculations for the most important metallurgical reactions, with particular focus on the modelling of the dephosphorisation reaction, as this is a critical parameter for production of high-quality steel grades along the EAF process route. A statistical scrap characterization tool is used to estimate the scrap properties, which are critical for reliable process performance and accurate online process control. The underlying process models and control functions were validated on the basis of historical production and measurement data of a large number of heats produced at the Sidenor plant. The online implementation of the model facilitates the accurate monitoring of the process behaviour and can be applied for exact process end-point control regarding melt temperature as well as oxygen, carbon and phosphorus content. Embedded within a model predictive control concept, the model can provide useful advice to the operator to adjust the relevant set-points for energy and resource-efficient process control