Search

"Personal, Social and Learning to Learn" was set as a Key Competence in 2018 by the Council Recommendation on Key Competences for Lifelong Learning. The "LifeComp" framework provides a common language to describe this Key Competence, which applies to all spheres of life; and can be acquired through formal, informal and non-formal education in order to help citizens thrive in the 21st century. "LifeComp" is a conceptual and non-prescriptive framework that describes nine competences in three areas (Personal, Social and Learning to Learn). The European Commission has developed "LifeComp into Action" to support educators to navigate the gap between theory and everyday pedagogical practices. It provides educational practitioners with a selection of principles, guidelines and research-based and learner-centred teaching strategies to foster the "LifeComp" competences. "LifeComp into Action" is expected to inspire educators, not only as a general guide for their teaching practices to foster socioemotional and metacognitive competences, but also as a basis from which to develop tailored strategies and practices to foster these competences. [Foreword by Anna-Maria Giannopoulou and Yves Punie.]

In this paper, a new computational topological framework for hypergraph analysis and recognition is developed. “Topology provides scale” is the principle at the core of this set of algebraic topological tools, whose fundamental notion is that of a scale-space topological model (s2-model). The scale of this parameterized sequence of algebraic hypergraphs, all having the same EulerPoincaré characteristic than the original hypergraph G, is provided by its relational topology in terms of evolution of incidence or adjacency connectivity maps. Its algebraic homological counterpart is again an s2-model, allowing the computation of new topological characteristics of G, which far exceeds current homological analytical techniques. Both scale-space algebraic dynamical systems are hypergraph isomorphic invariants. The hypergraph isomorphism problem is attacked here to demonstrate the power of the proposed framework, by proving the ability of s2-models to differentiate challenging cases that are difficult or even infeasible for state-of-the-art practical polynomial solvers. The processing, analysis, classification and learning power of the s2-model, at both combinatorial and algebraic levels, augurs positive prospects with respect to its application to physical, biological and social network analysis.

Two-neutron halo nuclei, such as 6He, 11Li or 14Be, are known to have a marked (core + n + n) three-body character, which is reflected in breakup, transfer or knockout reactions channels in nucleon-nucleon collisions. Their Borromean nature implies that the correlation between the valence halo neutrons is key to understand their properties, and their structure is also linked to spectra of the unbound core + n systems. Among other phenomena, the role of core collective excitations may be crucial to understand exotic properties such as parity inversion or shell gap quenching in the vicinity of nuclear halos and related systems. In this contribution it is shown that dineutron correlations can be succesfully probed in proton-target knockout reactions, and that core excitation may be an important ingredient for a proper understanding of experimental observations.Two-neutron halo nuclei, such as 6He, 11Li or 14Be, are known to have a marked (core + n + n) three-body character, which is reflected in breakup, transfer or knockout reactions channels in nucleon-nucleon collisions. Their Borromean nature implies that the correlation between the valence halo neutrons is key to understand their properties, and their structure is also linked to spectra of the unbound core + n systems. Among other phenomena, the role of core collective excitations may be crucial to understand exotic properties such as parity inversion or shell gap quenching in the vicinity of nuclear halos and related systems. In this contribution it is shown that dineutron correlations can be succesfully probed in proton-target knockout reactions, and that core excitation may be an important ingredient for a proper understanding of experimental observations.

The morphology of numerous nanocolumnar thin films deposited by the magnetron sputtering technique at oblique geometries and at relatively low temperatures has been analyzed for materials as different as Au, Pt, Ti, Cr, TiO₂, Al, HfN, Mo, V, WO₃ and W. Despite similar deposition conditions, two characteristic nanostructures have been identified depending on the material: a first one defined by highly tilted and symmetric nanocolumnar structures with a relatively high film density, and a second one characterized by rather vertical and asymmetric nanocolumns, with a much lower film density. With the help of a model, the two characteristic nanostructures have been linked to different growth dynamics and, specifically, to different surface relaxation mechanisms upon the incorporation of gaseous species with kinetic energies above the surface binding energy. Moreover, in the case of Ti, a smooth structural transition between the two types of growths has been found when varying the value of the power used to maintain the plasma discharge. Based on these results, the existence of different surface relaxation mechanisms is proposed, which quantitatively explains numerous experimental results under the same conceptual framework.

Access to higher education (HE) for students with disabilities has increased considerably over the last decades. Faced with this reality, universities are increasing their effort and resources to provide adequate teaching in order to ensure the retention of students with disabilities (Collins et al., 2018; Gunderson & Cumming, 2023). However, there are still difficulties, such as a lack of accessibility and adaptations in teaching methods, as well as educational resources and assessments that prevent many students with disabilities from successfully completing their studies (Packer et al., 2024; Parsons et al., 2021; Shpigelman et al., 2022). Scientific evidence shows the way forward to design university policies based on the principles of inclusive education. A large number of studies recommend that HE should maximise learning and participation and make them accessible to all students, without exception (Agarwal et al., 2022; Fernández-Batanero et al., 2022; Moriña & Orozco, 2022). Precisely, this paper aims to contribute to the knowledge about inclusive pedagogy through the voice of a group of faculty members who were identified as inclusive educators by their students with disabilities. This study shows the fundamental aspects that participants consider when designing and carrying out teaching practices that respond to the needs of all their students, including students with disabilities.

Energy storage is acknowledged a key technology to meet the challenges posed by the energy transition. Short-term grid-connected storage, based on Li-Ion batteries, is becoming commonplace but seasonal energy storage at grid-scale will be needed for deep decarbonisation of the electrical power system. Pumped hydropower is considered to be the only mature technology for such applications, but this paper demonstrates that two-tanks molten salts systems, that are used today in commercial concentrating solar power (CSP) plants, can also be considered a mature technology that can be used at large scale for seasonal energy storage. This was established by evaluating the annual heat losses of molten salts tanks using validated models of these systems. The results show that the heat losses in a very well insulated molten salts tanks are around 1 K/day, which would result in good economic performance of the power block even if storage was required for up to months.

This paper presents an approach for integrating uncertainty information in air traffic flow management at the tactical phase. In particular, probabilistic methodologies to predict sector demand and sector congestion under adverse weather in a time horizon of 1.5 h are developed. Two sources of uncertainty are considered: the meteorological uncertainty inherent to the forecasting process and the uncertainty in the take-off time. An ensemble approach is adopted to characterize both uncertainty sources. The methodologies rely on a trajectory predictor able to generate an ensemble of 4D trajectories that provides a measure of the trajectory uncertainty, each trajectory avoiding the storm cells encountered along the way. The core of the approach is the statistical processing of the ensemble of trajectories to obtain probabilistic entry and occupancy counts of each sector and their congestion status when the counts are compared to weather-dependent capacity values. A new criterion to assess the risk of sector overload, which takes into account the uncertainty, is also defined. The results are presented for a historical situation over the Austrian airspace on a day with significant convection.

Addressing large bone segmental defects remains a profound challenge in orthopaedic surgery, demanding graft designs that mirror patient-specific defects while ensuring vascularization, osteoconduction, and structural integrity. Conventional approaches fall short in achieving this level of customization and functionality. This work leverages fuse filament fabrication (FFF) to fabricate innovative yttria stabilize zirconia graft designs that combine several strategies to tackle these multifaceted challenges. Graft designs ingeniously incorporate dense and porous structures mimicking the intricate architecture of natural bone for improved structural integrity and different ridges and protrusions to enhance the fixation. Additionally, these grafts undergo infiltration with PCL/PVA/AgNPs composite polymers, enriching biocompatibility, structural integrity, and antibacterial properties, fostering conducive conditions for optimal bone growth. Attaining printable filaments with YSZ powders below 50 nm and loads reaching 50 vol% marks a pioneering advancement in bone graft fabrication via Fused Filament Fabrication (FFF). This enabled high densification and low grain size at reduced sintering temperatures, imperative to achieve high mechanical performance. The biodegradation capacity of biopolymers in PBS and their role in the mechanical behaviour of grafts have been assessed, demonstrating the beneficial potential of the multicomponent graft proposed reaching strength values of 90–105 MPa.

El presente artículo analiza críticamente el uso extendido de los denominados Online Dispute Resolution (ODR, por sus siglas en inglés) en el ámbito procesal, para la resolución de conflictos, especialmente en materia de consumo. Explora cómo estos métodos, si bien promocionados como eficientes y accesibles, pueden socavar principios fundamentales de que rigen el proceso, como la igualdad, la legalidad y el desinterés objetivo, así como otros principios típicos de los medios autocompositivos de resolución de conflictos, como la voluntariedad. Desde la perspectiva procesal y de los derechos humanos, se cuestiona el impacto de los ODR en la igualdad de acceso a la justicia y la protección de los derechos individuales. Además, se examinan los riesgos asociados con la privatización de la resolución de disputas y la falta de supervisión y regulación adecuadas en este ámbito. Este artículo busca generar reflexión sobre las implicaciones éticas y sociales de los ODR y promover un debate sobre el equilibrio entre la eficiencia y la equidad en la resolución de conflictos en la era digital., This article critically analyzes the widespread use of so-called Online Dispute Resolution (ODR) in the procedural field for dispute resolution, especially in consumer matters. It explores how these methods, although promoted as efficient and accessible, may undermine fundamental principles governing the process, such as equality, legality and objective disinterestedness, as well as other principles typical of self-compositive means of dispute resolution, such as voluntariness. From a procedural and human rights perspective, the impact of ODR on equal access to justice and the protection of individual rights is questioned. In addition, it examines the risks associated with the privatization of dispute resolution and the lack of adequate oversight and regulation in this area. This article seeks to generate reflection on the ethical and social implications of ODR and to promote a debate on the balance between efficiency and fairness in dispute resolution in the digital age.

The sensitivity of tree growth to climate is conditioned by several variables, often intermingled, such as the origin of the forest (natural vs. artificial), tree age, tree size and tree-to-tree competition. The effect of these variables is usually inferred from average growth series obtained at the stand level, thus ignoring the differences at the individual tree level and their drivers. Our objective is to disentangle the effects of stand origin, age, size, competition and social status on the sensitivity of tree growth to climate, including the effects of extreme climatic events, such as droughts, on resistance and resilience, and also to show the advantages of using a tree-level approach. To this end, we compared four stands of Pinus sylvestris with contrasting characteristics: young afforested, young of natural origin, old afforested and old of natural origin. We analyzed differences in growth sensitivity to climate at both stand and tree levels to compare both approaches. Our results show the great complexity of the relationships of the variables considered with the sensitivity of growth to climate. All these variables are important and with strong interactions between them, which makes their effects not unidirectional and strongly dependent on the site conditions. While the stand approach hides these interactions, the tree-level approach makes it possible to analyze them in detail. In general, the sensitivity of growth to climate increases with age, diameter, afforested origin, decreasing competition and higher social status; growth resistance increases with age, decreasing diameter, afforested origin, decreasing competition and higher social status; and growth resilience increases with age, diameter, natural origin, decreasing competition and higher social status. We show the usefulness of the analysis of data at individual tree level, which, combined with the joint analysis at stand level, allows us to obtain more accurate and detailed information.

The urgent need for mitigating climate change necessitates a transformative shift in energy production and consumption paradigms. Amidst this challenge, bioenergy emerges as a pivotal contributor to the global energy transition, offering a diverse array of solid, liquid, and gaseous fuels derived from biomass. This mini review delves into the unique potential of bioenergy innovations, particularly renewable diesel, bio jet fuel, and ethanol, to reduce greenhouse gas emissions and transform various industries. The article highlights critical technological advancements, supportive policies, and cross-sector collaboration essential for a sustainable energy transition. Specific challenges such as ensuring a consistent biomass feedstock supply, decentralizing processing units, and navigating complex regulatory frameworks are examined. Innovative solutions like decentralized biomass processing and enhanced biomass logistics are discussed as pathways to overcome these barriers. The review provides specific recommendations for near-term policies and strategies to support decentralized facilities, showcasing bioenergy’s role in achieving a sustainable future.

El Design Thinking (DT) es una metodología aplicada a la resolución de problemas que, en los últimos años, ha adquirido una gran relevancia en el ámbito universitario. El presente estudio analiza la aplicación de la metodología basada en el DT (IDEO, 2015) en alumnado de segundo curso del Grado en Educación Primaria de la Universidad de Sevilla (61,9% chicas; 38,1% chicos; M = 20,33; DT = 1,96). Los resultados del cuestionario ad hoc indican que el alumnado valoró positivamente la experiencia. Esta experiencia de innovación docente ha evidenciado la mejora del alumnado en sus capacidades creativas y de resolución de problemas fomentando la participación activa y el trabajo en equipo en la adquisición de nuevos aprendizajes.

Fast-ion loss detectors (FILDs) are crucial for analyzing fast-ion dynamics in magnetically confined fusion plasmas. A core challenge is to derive an accurate ion velocity distribution, requiring treatment of thousands of remapped camera frames for a full discharge. The ill-posed nature of this task necessitates regularization with a well-chosen regularization parameter and computationally efficient methods. In this work, we introduce the 'resolution principle,' a novel criterion for selecting the optimal regularization parameter, providing a distinction between genuine features and artefacts smaller than the diagnostic resolution in the reconstruction, thereby preventing misinterpretations. This principle, coupled with three iterative reconstruction techniques—Kaczmarz's method, coordinate descent, and Cimmino's method—demonstrates enhanced reconstruction capabilities compared to conventional methods like Tikhonov regularization. Utilizing these techniques allows rapid processing of measurements from full discharges, removing the computational bottleneck and facilitating between-discharge reconstructions. By reconstructing 6000 camera frames from an ELMy H-mode discharge at ASDEX Upgrade, we capture the temporal evolution of gyroradii and pitch angles, unveiling a direct correlation between pitch-angle behavior and changes in the toroidal magnetic field for a specific subset of lost ions accelerated by edge-localized modes (ELMs) to energies approximately twice that of the injection energy.

Early results on the plasma deposition of dielectric thin films on acoustic wave (AW) activated substrates revealed a densification pattern arisen from the focusing of plasma ions and their impact on specific areas of the piezoelectric substrate. Herein, we extend this methodology to tailor the plasma deposition of metals onto AW-activated LiNbO3 piezoelectric substrates. Our investigation reveals the tracking of the initial stages of nanoparticle (NP) formation and growth during the submonolayer deposition of silver. We elucidate the specific role of AW activation in reducing particle size, enhancing particle circularity, and retarding NP agglomeration and account for the physical phenomena making these processes differ from those occurring on non-activated substrates. We provide a comparative analysis of the results obtained under two representative plasma conditions: diode DC sputtering and magnetron sputtering. In the latter case, the AW activation gives rise to a 2D pattern of domains with different amounts of silver and a distinct size and circularity for the silver NPs. This difference was attributed to the specific characteristics of the plasma sheath formed onto the substrate in each case. The possibilities of tuning the plasmon resonance absorption of silver NPs by AW activation of the sputtering deposition process are discussed.

Introduction: Effective implementation of strategies to promote health and prevent noncommunicable illnesses requires a profound understanding of the interaction between the individual and society. This study brings to health research the consideration of psychosocial factors that influence the maintenance and change of health behaviors and conduct. From a primary care perspective, it is crucial to propose a biopsychosocial approach for the development of health promotion and self-care programs that embrace personal aptitudes as a relevant individual aspect. Objectives: To explore experiences related to personal aptitudes and personality traits that influence health behaviors and conduct, taking into account the social determinants of health, through a thematic analysis based on the capability-opportunity-motivation and behavior (COM-B) system. Methods and analysis: This qualitative research is carried out from a descriptive phenomenological perspective, based on 17 focus groups in which 156 people participated. Inductive and deductive analysis techniques were used following Lincoln and Guba’s criteria of methodological rigor. In addition to 7 different triangulations of analysts, 6 main categories were identified based on the COM-B system: psychological capacity, physical capacity, physical opportunity, social opportunity, reflective motivation, and automatic motivation. The importance of considering these factors to promote healthy behaviors was stressed. Discussion: This study examined how personal experiences related personal aptitudes and personality traits influence health behaviors and conduct in Spain. It was found that personality traits such as health literacy, self-efficacy, activation, and self-determination can influence the adoption of healthy behaviors. Likewise, the need for control, overthinking, and ambivalence made it impossible. Furthermore, social determinants of health and interpersonal relationships also play an important role.

This paper presents an investigation into the real-time explicit co-simulation of mobile harbor cranes under hoisting operation. The system is divided into two subsystems, with Subsystem 1 representing the payload and Subsystem 2 encompassing the wire-rope system. To capture the real-time behavior of the wire ropes accurately, the ALEM (Arbitrary Lagrangian–Eulerian Modal) method is employed in this study. Using this formulation, the intricate behavior of the wire ropes, encompassing elasticity, bending effects, and dynamic influences, is rigorously considered. The dynamic equations governing the payload are solved using the Runge–Kutta4 method, while the Generalized Alpha method is utilized to solve the wire-rope system. Both the Gauss–Seidel and Jacobi methods are investigated as two coupling techniques to connect the subsystems. Additionally, the study delves into the impact of the extrapolation method and macro time step on results accuracy and efficiency. The findings demonstrate that co-simulation employing the Gauss–Seidel method and FOH (First-Order Hold) extrapolation yields optimum and accurate simulations. Moreover, the study successfully achieves real-time simulation by optimizing the wire-rope system simulation, accounting for all degrees of freedom inherent in a 3D system. Remarkably, the maximum error observed in the axial force amounts to a mere 0.6% when employing real-time simulation. These findings can hold practical value for employing the current wire-rope subsystem in the interface modeling of real-world industrial cranes.

We present a new version of the FILDSIM code (Galdon-Quíroga et al 2018 Plasma Phys. Control. Fusion60 105005), which significantly refines the modelling of the fast-ion loss detector (FILD) signal. We demonstrate that the FILD weight functions computed using this new version of FILDSIM are more accurate relative to synthetic benchmarks than those computed using the previous version. Thus, the new version enables higher-quality velocity-space sensitivity modelling and reconstructions. We validate the improvements on experimental data from discharge #75620 at TCV. Additionally, we present a novel approach for characterizing FILDs through a gross FILD measurement and a gross weight function based on the calculations from the new version of FILDSIM. We use them to characterize the TCV FILD.

Successful application of finite control set model predictive control (FCS-MPC) strategies with long prediction horizon depends on the careful design of the optimization algorithm. The conventional method involves transforming the problem to an equivalent box-constrained integer least-squares (BILS) formulation that can be solved with branch-and-bound techniques such as the sphere decoding algorithm (SDA). In this work, it is proposed to define an artificial neural network (ANN) to replace the SDA, avoiding its inherent computational variability. Similarly to practical applications of the SDA, the ANN finds an approximate solution of the underlying optimization problem. In contrast, the main benefit of the proposed approach is that it can be implemented in a low-cost microprocessing platform, greatly improving the performance in terms of resources in comparison with other advanced techniques roposed in the literature.

A collaboration of multidisciplinary experts from the European Association of Dermato-Oncology, the European Dermatology Forum, the European Academy of Dermatology and Venereology, and the European Union of Medical Specialists was formed to develop European recommendations on AK diagnosis and treatment, based on current literature and expert consensus. This guideline addresses the epidemiology, diagnostics, risk stratification and treatments in immunocompetent as well as immunosuppressed patients. Actinic keratoses (AK) are potential precursors of cutaneous squamous cell carcinoma (cSCC) and display typical histopathologic and immunohistochemical features of this malignancy in an early stage. They can develop into cSSC in situ and become invasive in a low percentage of cases. AK is the most frequent neoplasia in white populations, frequently occurring within a cancerous field induced by ultraviolet radiation. Since it cannot be predicted, which lesion will progress to cSCC and when treatment is usually recommended. The diagnosis of AK and field cancerization is made by clinical examination. Dermatoscopy, confocal microscopy, optical coherence tomography or line-field confocal-OCT can help in the differential diagnosis of AK and other skin neoplasms. A biopsy is indicated in clinically and/or dermatoscopically suspicious and/or treatment-refractory lesions. The choice of treatment depends on patients' and lesion characteristics. For single non-hyperkeratotic lesions, the treatment can be started upon patient's request with destructive treatments or topical treatments. For multiple lesions, field cancerization treatment is advised with topical treatments and photodynamic therapy. Preventive measures such as sun protection, self-examination and repeated field cancerization treatments of previously affected skin areas in high-risk patients are advised.

info:eu-repo/semantics/nonPublished

Background & aims: It has been reported that specific killer-cell immunoglobulin-like receptors (KIRs) and HLA genotype combinations, such as KIR2DS4/HLA-C1 with presence of KIRDL2 or KIRDL3, homozygous KIRDL3/ HLA-C1 and KIR3DL1/≥2HLA-Bw4, are strongly associated with the lack of active infection and seroconversion after exposition to hepatitis C virus (HCV). Objective: To determine whether these KIR-HLA combinations are relevant factors involved in that phenotype. Patients and methods: In this retrospective case-control study, genotype data from a genome-wide association study previously performed on low susceptibility to HCV-infection carried out on 27 high-risk HCV-eronegative (HRSN) individuals and 743 chronically infected (CI) subjects were used. HLA alleles were imputed using R package HIBAG v1.2223 and KIR genotypes were imputed using the online resource KIR*IMP v1.2.0. Results: It was possible to successfully impute at least one KIR-HLA genotype combination previously associated with the lack of infection and seroconversion after exposition to HCV in a total of 23 (85.2%) HRSN individuals and in 650 (87.5%) CI subjects. No KIR-HLA genotype combination analyzed was related to the HRSN condition. Conclusions: Our results suggest that those KIR-HLA genotype combinations are not relevant factors involved in the lack of infection and seroconversion after exposition to HCV. More studies will be needed to completely understand this phenotype.

Deficiencies in the BRCA1 tumor suppressor gene are the main cause of hereditary breast and ovarian cancer. BRCA1 is involved in the Homologous Recombination DNA repair pathway and, together with BARD1, forms a heterodimer with ubiquitin E3 activity. The relevance of the BRCA1/BARD1 ubiquitin E3 activity for tumor suppression and DNA repair remains controversial. Here, we observe that the BRCA1/BARD1 ubiquitin E3 activity is not required for Homologous Recombination or resistance to Olaparib. Using TULIP2 methodology, which enables the direct identification of E3-specific ubiquitination substrates, we identify substrates for BRCA1/BARD1. We find that PCNA is ubiquitinated by BRCA1/BARD1 in unperturbed conditions independently of RAD18. PCNA ubiquitination by BRCA1/BARD1 avoids the formation of ssDNA gaps during DNA replication and promotes continuous DNA synthesis. These results provide additional insight about the importance of BRCA1/BARD1 E3 activity in Homologous Recombination.

This work presents a detailed experimental study conducted for a range of different lay-ups using thin-ply carbon fiber reinforced polymer (CFRP) laminates. The selection of the laminates was performed relying on their level of anisotropy. The laminates vary from a quasi-isotropic (QI) laminate, which is weakly anisotropic, to a cross-ply (CP) laminate, which is strongly anisotropic. The laminates were tested in on-axis and off-axis open hole tension (OHT). The main objective was to observe the effect of the level of anisotropy of the laminate on the macroscopic failure and observed failure patterns. It is shown that, contrary to most existing observations so far, depending on the lay-up and consequently its level of anisotropy, open-hole, quasi-homogeneous thin-ply laminates do not necessarily exhibit a fiber dominated failure mode, but could develop sub-critical damage mechanisms in a large extent prior to ultimate failure, reminiscent of what is observed for standard-ply CFRP laminates.

We propose fully-distributed algorithms for Nash equilibrium seeking in aggregative games over networks. We first consider the case where local constraints are present and we design an algorithm combining, for each agent, (i) the projected pseudo-gradient descent and (ii) a tracking mechanism to locally reconstruct the aggregative variable. To handle coupling constraints arising in generalized settings, we propose another distributed algorithm based on (i) a recently emerged augmented primal-dual scheme and (ii) two tracking mechanisms to reconstruct, for each agent, both the aggregative variable and the coupling constraint satisfaction. Leveraging tools from singular perturbations analysis, we prove linear convergence to the Nash equilibrium for both schemes. Finally, we run extensive numerical simulations to confirm the effectiveness of our methods and compare them with state-of-the-art distributed equilibrium-seeking algorithms.

Direct Laser Writing (DLW) has been increasingly selected as a microfabrication route for efficient, cost-effective, high-resolution material synthesis and conversion. Concurrently, lasers participate in the patterning and assembly of functional geometries in several fields of application, of which electronics stand out. In this review, recent advances and strategies based on DLW for electronics microfabrication are surveyed and outlined, based on laser material growth strategies. First, the main DLW parameters influencing material synthesis and transformation mechanisms are summarized, aimed at selective, tailored writing of conductive and semiconducting materials. Additive and transformative DLW processing mechanisms are discussed, to open space to explore several categories of materials directly synthesized or transformed for electronics microfabrication. These include metallic conductors, metal oxides, transition metal chalcogenides and carbides, laser-induced graphene, and their mixtures. By accessing a wide range of material types, DLW-based electronic applications are explored, including processing components, energy harvesting and storage, sensing, and bioelectronics. The expanded capability of lasers to participate in multiple fabrication steps at different implementation levels, from material engineering to device processing, indicates their future applicability to next-generation electronics, where more accessible, green microfabrication approaches integrate lasers as comprehensive tools.

The integration of distributed energy resources in the power grid supposes a great challenge, considering the expected growing in the electric mobility and the renewable generation. Therefore, to support the successful deployment of these resources, energy management according to the expected behaviors of the elements of power grids is required. In this sense, the probabilistic forecasting methods are gaining acceptance, as they provide richer information than deterministic methods thanks to the consideration of expected probabilities. One of their problems is that the application of metrics for choosing the best models is not simple, depending on the objective of the type of probabilistic prediction that must be performed. In this paper, diverse types of forecasting are performed, and two possible approaches for selecting interval forecasting models are compared in a case study centered on the Smart Polygeneration Microgrid (SPM) located on the Savona Campus of University of Genova (Italy). The results show that, for the machine learning models that were tested, it is better to obtain a model for each of the different types of forecasting that are required (quantiles, and the prediction intervals) to have better-quality predictions. The average improvement on the quality of the tested prediction intervals for the three forecasted variables were a 27.40%, 7.39%, and 28.65% in their Winkler score respectively.

This paper presents a stochastic optimization approach for the operational management of sustainable energy districts and polygeneration microgrids. Stochastic operation optimization allows for an uncertain approach to deal with imprecise variables. A new approach is here presented for generating scenarios based on Ant Colony Optimization (ACO) to assess the uncertainties related to inexact data, renewable energy sources and power demand. In fact, due to the uncertainties related to forecasting loads and renewables, it is necessary to analyze the probability of occurrence of the prediction and the different scenarios that could be faced. Then, based on the generated scenarios and probabilities, a scenario-based two-stage stochastic optimization approach has been formulated to optimize the operation strategies of the various technologies and solve the unit commitment problem under uncertainty. The developed models have been applied to the Savona Campus Smart Polygeneration Microgrid, and historical data from 2018 have been used.

Large edge localised modes (ELMs) would cause an unacceptable reduction of material lifetime in future large tokamaks due to the significant amount of energy expelled from the magnetically confined region towards the plasma facing components. Thoroughly validated modelling of regimes devoid of large ELMs is crucial as it may then provide predictive insights prior to tokamak operation and design. This paper describes recent efforts pursued with the non-linear extended MHD code JOREK in the modelling of three scenarios without large ELMs: quiescent H-mode (QH-mode), quasi-continuous exhaust regime (QCE regime), and the enhanced D-alpha H-mode (EDA H-mode). For each of these regimes, the non-linear dynamics observed in the simulations are detailed and compared to experimental observations of the underlying instabilities of each regime (edge harmonic oscillation for QH-mode, small ELMs for QCE regime, and quasi-coherent mode for EDA H-mode). For QH-mode, the kink-peeling mode is found to govern the dynamics and a transition to a large ELM is obtained above the same density threshold as in the modelled experiment. For the QCE regime and EDA H-mode, resistive peeling–ballooning modes dominate and pedestal fluctuation frequencies correspond well to experimental observations. The dominant mechanisms for the excitation and suppression of these instabilities are presented and their influence on simulation dynamics is shown. Finally, predictive simulations of edge instabilities at different values of plasma resistivity in a 4.60 MA scenario with low edge safety factor in JT-60SA are presented.

This study addresses the optimization issues of a Parabolic Trough (PT) power plant by retrofitting it with a photovoltaic (PV) plant to find the optimal configuration for already operational Concentrated Solar Power (CSP) plants. A simulation tool based on Modelica and OpenModelica has been developed to analyze and optimize the performance of CSP/PV hybrid plants under several grid limitation scenarios, one of which includes an electrical heater to utilize the PV surplus, considering the impact of hybridization on their overall performance and therefore also on their economic viability. The results obtained provide clear insights into how different configurations of CSP and PV plants interact and how certain variables, such as the PV ratio and thermal storage size, influence the overall performance of the hybrid plant.

Not ageing in place is an increasing reality for many older Europeans. For several decades societies have applied different care models in developing initiatives to provide safe and age-friendly spaces. This article presents the community care model implemented by the Italian service provider ISRAA in Treviso (Italy) in one of its nursing homes and senior cohousing projects. The aim of our study was to analyse this senior community care model and find out how residents have responded to it. Participants were both the older adult residents in the two ISRAA facilities and professionals responsible for their social attention. A qualitative methodology was used: questionnaire, interviews, and focus groups with professionals and care facility residents. Results reveal the care philosophy implemented, residents’ experiences, the main barriers to creating a community, and how this model could be improved by following community development principles, with the older people’s help, participation, and engagement. The conclusions highlight the importance of applying principles of self-determination and social inclusion in a preventive care model for the senior community. In addition, a key factor in promoting community development is for professionals to act as community development practitioners and to allow older adults to be part of the change.

How does a plant detect the changing seasons and make important developmental decisions accordingly? How do they incorporate daylength information into their routine physiological processes?Photoperiodism, or the capacity to measure the daylength, is a crucial aspect of plant development that helps plants determine the best time of the year to make vital decisions, such as flowering. The protein CONSTANS (CO) constitutes the central regulator of this sensing mechanism, not only activating florigen production in the leaves but also participating in many physiological aspects in which seasonality is important. Recent discoveries place CO in the center of a gene network that can determine the length of the day and confer seasonal input to aspects of plant development and physiology as important as senescence, seed size, or circadian rhythms. In this review, we discuss the importance of CO protein structure, function, and evolutionary mechanisms that embryophytes have developed to incorporate annual information into their physiology.

Background: We plan a scoping review aimed to synthesize what is known about the use of sensory-driven body illusion (BI) interventions for understanding and treating body image disturbance (BID) in people diagnosed with clinical eating disorders (EDs) and people with subclinical ED symptomatology. Our study will provide an outline of the current literature, identify gaps within the literature, and suggest novel directions for future research. Methods/design: The scoping review process will be guided by the methodological framework of Arksey and O’Malley, subsequent recommendations by Levac et al., and the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols Extension for Scoping Reviews guidelines. The following electronic databases will be systematically searched: MEDLINE (via PubMed), Web of Science, PsycINFO, and Scopus. Furthermore, to identify additional studies, we will use a search engine such as Google Scholar, and for grey literature, we will include Proquest for Dissertations and Theses. A search strategy has been identified and agreed upon by the research team in conjunction with a research librarian. Two researchers will screen the titles and abstracts independently and then assess the full text of the selected citations for the inclusion criteria. A third reviewer will be involved in cases of disagreement. Data will be extracted, collated, and charted to summarize all the relevant methods, outcomes, and key findings in the articles. Discussion: A better understanding of this topic will aid in the development and refinement of current treatments aimed at treating BID in people with EDs. Implications and recommendations for research, policy, and practice in the context of the ED community will be discussed.

In this study, we examined the metabolic and gut microbiome responses to paraquat (PQ) in male Wistar rats, focusing on oxidative stress effects. Rats received a single intraperitoneal injection of PQ at 15 and 30 mg/kg, and various oxidative stress parameters (i.e., MDA, SOD, ROS, 8-isoprostanes) were assessed after three days. To explore the omic profile, GC-qTOF and UHPLC-qTOF were performed to assess the plasma metabolome; 1H-NMR was used to assess the urine metabolome; and shotgun metagenomics sequencing was performed to study the gut microbiome. Our results revealed reductions in body weight and tissue changes, particularly in the liver, were observed, suggesting a systemic effect of PQ. Elevated lipid peroxidation and reactive oxygen species levels in the liver and plasma indicated the induction of oxidative stress. Metabolic profiling revealed changes in the tricarboxylic acid cycle, accumulation of ketone body, and altered levels of key metabolites, such as 3-hydroxybutyric acid and serine, suggesting intricate links between energy metabolism and redox reactions. Plasma metabolomic analysis revealed alterations in mitochondrial metabolism, nicotinamide metabolism, and tryptophan degradation. The gut microbiome showed shifts, with higher PQ doses influencing microbial populations (e.g., Escherichia coli and Akkermansia muciniphila) and metagenomic functions (pyruvate metabolism, fermentation, nucleotide and amino acid biosynthesis). Overall, this study provides comprehensive insights into the complex interplay between PQ exposure, metabolic responses, and gut microbiome dynamics. These findings enhance our understanding of the mechanisms behind oxidative stress-induced metabolic alterations and underscore the connections between xenobiotic exposure, gut microbiota, and host metabolism.

Deep Eutectic Solvents (DESs) have appeared in recent years as an appealing alternative to classical organic solvents, due to their valuable environmental properties. In addition, these compounds, formed by the combination of one hydrogen bond donor with a hydrogen bond acceptor at a defined stoichiometric ratio, present other valuable activities not only as a reaction medium. DESs can also be employed as catalysts through hydrogen-bond interactions in different chemical transformations, thus substituting hazardous reagents and solvents. The search for novel and more environmentally friendly catalysts is an area of interest of pharmaceutical chemists, and therefore, the efforts made in the application of DESs as catalysts in the synthesis of APIs or its precursors are described, focusing mainly on condensations, nucleophilic additions to carbonyl moieties, and multicomponent reactions.

Finite-element-models are usually employed to simulate the behaviour of historical constructions. However, despite the high complexity of these numerical models, there are always discrepancies between the actual behaviour of the structure and the numerical predictions obtained. In order to improve their performance, an updating process can be implemented. According to this process, the value of the most relevant physical parameters of the model is adjusted to better mimic the actual behaviour of the structure. For this purpose, the actual structural behaviour is usually characterized via its experimental modal properties (natural frequencies and associated vibration modes). For practical engineering applications, the maximum likelihood method is normally considered to cope with this problem, due to its easy implementation together with an understandable interpretation of the updating results. However, the complexity of these numerical models makes unfeasible the practical implementation of the process due to the simulation time required for its computation. In order to shed some light to this problem, a new combinative computational algorithm is proposed herein. Additionally, the performance of the proposal has been assessed successfully via two applications: (i) a validation example, the model updating of a laboratory footbridge, in which the practical implementation of the algorithm has been described in detail; and (ii) a case-study, the model updating of a complex historical construction, in which the main advantage of the proposal has been highlighted, a clear reduction of the simulation time required to solve the updating problem without compromising the accuracy of the solution obtained.

The high penetration of renewable energy sources (RES) interfaced with power electronics together with new nonlinear loads pose new challenges in the grid operation. In fact, power systems with reduced inertia and high harmonic distortion will be common in a near future. Recently, the grid-forming operation of voltage source converters (VSCs) has emerged to address these challenges, mimicking the contribution of synchronous generators to the system inertia. In addition, these grid-connected VSCs can be used at the same time for reducing the harmonic distortion by applying active filtering techniques. However, these harmonic compensation algorithms can generate VSC overloading. This paper proposes a method for dynamically adjusting the individual virtual impedance of the filtered harmonics to prevent the power converter overcurrent. For this purpose, the value of each harmonic virtual impedance is modified according to a priority which can be set by the final user according to the established power quality standard. The paper includes a theoretical stability analysis of the controller and experimental results to validate the proposed algorithm.

In the rapidly expanding field of e-commerce logistics, the optimisation of last-mile delivery solutions is paramount. This paper introduces a novel methodology that addresses this challenge by generating approximate Pareto fronts in a hybrid truck-drone delivery system. Specifically, we examine a generalized single truck multi- drone problem that allows multi-visit flight missions and rendezvous points distinct from launch locations. Our goal is providing decision-makers with a portfolio of optimal routing solutions that balance service time and environmental impact, criteria that are increasingly shaping decision-making in this domain. To achieve this, we introduce a bivector coding scheme inspired by flow-shop scheduling problems and implement a Simulated Annealing algorithm. This algorithm features an advanced stopping mechanism, negating the need for manual adjustments by utilizing a distinctive blend of a domination rate and a Kalman filter. Importantly, our framework employs an iterated greedy search algorithm to evolve from initial solutions towards identifying non-dominated solutions sets, which are then ranked using a hypervolume coefficient. To validate our methodology, we conduct a sensitivity analysis on two different size instances using a full factorial design of experiments. Our analysis reveals crucial insights into the impact of the number of drones, their autonomy, and their flight speed settings. From it, we conclude that it is a robust and adaptable framework for its practical application for obtaining Pareto fronts solutions among which picking the ultimate routing to be implemented.

Micro Gas Turbines are on-site generators with the potential to help the transition to a greener economy. However, their deployment into the market did not match the expectations. The Root Cause Analysis (RCA) is the methodology to uncover the highest-level causes before identifying possible solutions. This work applies the traditional approach to problem-solving, which originated as a methodology to find faults in processes. The methodology leads to an in-depth exploration of the problem and the cause–effect relationships within the microturbine and energy market. Specifically, the traditional RCA allowed for a creative and extensive approach. This study highlights the difficulty of targeting the problem from a general perspective with such tools. The process-based tools of the RCA make it challenging to represent such complex systems effectively. In this regard, the authors compare the present methodology with the Theory of Constraints, analysing benefits and obstacles. Eventually, the present methodology systematically isolated several root causes of the problem.

In the minimum-weight many-to-many point matching problem, we are given a set R of red points and a set B of blue points in the plane, of total size N, and we want to pair up each point in R to one or more points in B and vice versa so that the sum of distances between the paired points is minimized. This problem can be solved in O(N3) time by using a reduction to the minimum-weight perfect matching problem, and thus, it is not fast enough to be used for on-line systems where a large number of tunes need to be compared. Motivated by similarity problems in music theory, in this paper we study several constrained minimum-weight many-to-many point matching problems in which the allowed pairings are given by geometric restrictions, i.e., a bichromatic pair can be matched if and only if the corresponding points satisfy a specific condition of closeness. We provide algorithms to solve these constrained versions in O(N) time when the sets R and B are given ordered by abscissa.

The neutron time-of-flight facility n_TOF at CERN is a spallation source dedicated to measurements of neutron-induced reaction cross-sections of interest in nuclear technologies, astrophysics, and other applications. Since 2014, Experimental ARea 2 (EAR2) is operational and delivers a neutron fluence of neutrons per nominal proton pulse, which is 50 times higher than the one of Experimental ARea 1 (EAR1) of neutrons per pulse. The high neutron flux at EAR2 results in high counting rates in the detectors that challenged the previously existing capture detection systems. For this reason, a Segmented Total Energy Detector (sTED) has been developed to overcome the limitations in the detector’s response, by reducing the active volume per module and by using a photo-multiplier (PMT) optimized for high counting rates. This paper presents the main characteristics of the sTED, including energy and time resolution, response to -rays, and provides as well details of the use of the Pulse Height Weighting Technique (PHWT) with this detector. The sTED has been validated to perform neutron-capture cross-section measurements in EAR2 in the neutron energy range from thermal up to at least 400 keV. The detector has already been successfully used in several measurements at n_TOF EAR2.

This study evaluates the functional characteristics of the exopolysaccharide (EPS) extracts produced by various strains of Lactiplantibacillus pentosus (LPG1, 119, 13B4, and Lp13) and Lactiplantibacillus plantarum (Lp15) isolated from table olives. None of the EPS crude extracts showed cytotoxicity when administered to THP-1 human macrophage cells at dosages ranging from 6.25 to 50 mug mL-1. Many exhibited anti-inflammatory properties (reduction of pro-inflammatory cytokines TNF-alpha and IL-6 production) and antioxidant activity (reduction of ROS%) when macrophages were stimulated with Escherichia coli lipopolysaccharide. Notably, the EPS extract produced by the L. pentosus LPG1 strain had the best results corroborated by western blot immune analysis for differential expression of COX-2, Nrf-2, and HO-1 proteins, with the most significant antioxidant and anti-inflammatory response observed at a dosage of 50 mug mL-1. Chemical analysis revealed that the EPS extract produced by this strain contains a heteropolymer composed of mannose (35.45%), glucose (32.99%), arabinose (17.93%), xylose (7.48%), galactose (4.03%), rhamnose (1.34%), and fucose (0.77%). Finally, we conducted response surface methodology to model the EPS extract production by L. pentosus LPG1 considering pH (3.48-8.52), temperature (16.59-33.41 °C) and salt concentration (0.03-8.77% NaCl) as independent variables. The model identified linear effects of salt and pH and quadratic effects of salt as significant terms. The maximum EPS extract production (566 mg L-1) in a synthetic culture medium (MRS) was achieved at pH 7.5, salt 7.0%, and a temperature of 20 °C. These findings suggest the potential for novel applications for the EPS produced by L. pentosus LPG1 as nutraceutical candidates for use in human diets.