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Abstract Contrary to expert readers, children learning to read have limited ability to preprocess letters in parafoveal vision. Parafoveal letters induce crowding cost: the features of neighboring letters interfere with target letter identification. We longitudinally studied the weight of parafoveal cost and benefit in two group of children (N = 42), during their first school year (Group 1) and at the end of second school year (Groupe 2). Using a novel digit-tracking method, a blurred text was presented and rendered unblurred by touching the screen, allowing the user to discover a window of visible text as the finger moved along it. We compared two conditions: (1) a large window, where crowding was enhanced by the presence of parafoveal information; (2) a small window, where crowding was suppressed by blurred parafoveal information. Finger kinematics were simultaneously recorded. We found that at the beginning of first-grade, digital fixations - brief slowing or stopping of the finger on a specific point - are significantly longer in the large compared to the small window condition, as parafoveal crowding increases text processing difficulty. This effect diminishes and disappears at the end of second-grade as reading performance improves. In the large window condition, longer digital saccades - rapid movements of the finger changing position - appear by the end of first grade suggesting that parafoveal exposure become more beneficial than harmful when children acquire basic reading skills. Our results show that in beginning readers, crowding has a cognitive cost that interfere with the speed of the learning reading process. Our findings are relevant to the field of education by showing that visual crowding in first grade should not be underestimated.

To advance wave energy devices towards commercialization, it is essential to optimize their design to enhance system performance. Additionally, a thorough economic evaluation is crucial for making these technologies competitive with other renewable energy sources. This study focuses on the techno-economic optimization of an innovative inertial system, the so-called SWINGO system, which is based on gyropendulum technology. SWINGO stands out due to its high energy efficiency in multi-directional installation sites, where wave directions vary significantly throughout the year. The study introduces the application of a multi-objective Evolutionary Algorithm (EA), specifically the Non-dominated Sorting Genetic Algorithm II (NSGA-II), to optimize the techno-economic performance of the SWINGO system. This approach aims to identify optimal design parameters that maximize energy extraction while considering economic viability. By deriving a Pareto frontier, a set of optimal devices is selected for further analysis. The performance of the SWINGO system is also compared to an alternative (mono-directional) inertial wave energy converter, the Inertial Sea Wave Energy Converter (ISWEC), to highlight the differences in techno-economic outcomes. Both systems are evaluated at two different installation sites: Pantelleria island and the North Sea in Denmark, with a focus on the directional wave scatter at each location.

The trend toward longer blades in offshore wind turbines poses a significant structural design challenge, given their flexibility and larger load variations. While the study of aeroelastic models of very long blades has gained attention in recent discussions, there is a gap in comprehensive studies examining the impact of different aeroelastic models on fatigue analysis. This study focuses on a comparative evaluation of different aeroelastic models under identical conditions, with a specific focus on multiaxial fatigue. The primary objective is to compare and assess the discrepancies in predicting the lifetime, spatial damage distribution, and critical wind speed conditions. The findings of this study highlight a substantial impact of the aeroelastic model selection on the expected lifetime, revealing durations of 23.2, 3.7, and 1.2 years for the geometrically exact beam theory, Euler-Bernoulli beam, and rigid body assumption. In contrast, the spatial distribution of fatigue damage and critical wind speed conditions remain relatively stable across the models.

Abstract We have previously shown that krill oil (KO), more efficiently than fish oil, was able to downregulate the endocannabinoid system in different tissues of obese zucker rats. We therefore aimed at investigating whether an intake of 2 g/d of either KO or menhaden oil (MO), which provides 309 mg/d of EPA/DHA 2:1 and 390 mg/d of EPA/DHA 1:1 respectively, or olive oil (OO) for four weeks, is able to modify plasma endocannabinoids in overweight and obese subjects. The results confirmed data in the literature describing increased levels of endocannabinoids in overweight and obese with respect to normo-weight subjects. KO, but not MO or OO, was able to significantly decrease 2-arachidonoylglycerol (2-AG), although only in obese subjects. In addition, the decrease of 2-AG was correlated to the plasma n-6/n-3 phospholipid long chain polyunsaturated fatty acid (LCPUFA) ratio. These data show for the first time in humans that relatively low doses of LCPUFA n-3 as KO can significantly decrease plasma 2-AG levels in obese subjects in relation to decrease of plasma phospholipid n-6/n-3 LCPUFA ratio. This effect is not linked to changes of metabolic syndrome parameters but is most likely due to a decrease of 2-AG biosynthesis caused by the replacement of 2-AG ultimate precursor, arachidonic acid, with n-3 PUFAs, as previously described in obese Zucker rats.

Among the challenges generated by the global climate crisis, a significant concern is the constant increase in energy demand. This leads to the need to ensure that any novel energy systems are not only renewable but also reliable in their performance. A viable solution to increase the available renewable energy mix involves tapping into the potential available in ocean waves and harvesting it via so-called wave energy converters (WECs). In this context, a relevant engineering problem relates to finding WEC design solutions that are not only optimal in terms of energy extraction but also exhibit robust behavior in spite of the harsh marine environment. Indeed, the vast majority of design optimization studies available in the state-of-the-art consider only perfect knowledge of nominal (idealized) conditions, neglecting the impact of uncertainties. This study aims to investigate the information that different robustness metrics can provide to designers regarding optimal WEC design solutions under uncertainty. The applied methodology is based on stochastic uncertainty propagation via a Monte Carlo simulation, exploiting a meta-model to reduce the computational burden. The analysis is conducted over a dataset obtained with a genetic algorithm-based optimization process for nominal WEC design. The results reveal a significant deviation in terms of robustness between the nominal Pareto set and those generated by setting different thresholds for robustness metrics, as well as between devices belonging to the same nominal Pareto frontier. This study elucidates the intrinsic need for incorporating robust optimization processes in WEC design.

Abstract Digit-tracking, a simple, calibration-free technique, has proven to be a good alternative to eye tracking in vision science. Participants view stimuli superimposed by Gaussian blur on a touchscreen interface and slide a finger across the display to locally sharpen an area the size of the foveal region just at the finger's position. Finger movements are recorded as an indicator of eye movements and attentional focus. Because of its simplicity and portability, this system has many potential applications in basic and applied research. Here we used digit-tracking to investigate visual search and replicated several known effects observed using different types of search arrays. Exploration patterns measured with digit-tracking during visual search of natural scenes were comparable to those previously reported for eye-tracking and constrained by similar saliency. Therefore, our results provide further evidence for the validity and relevance of digit-tracking for basic and applied research on vision and attention.

Floating offshore wind turbines (FOWTs) are a rapidly developing technology, but still, need to gain economic competitiveness to obtain market acceptance. The reduction of the structural cost of the floating platform represents one of the main targets to reach an optimal design in the initial design process. This paper proposes an efficient optimisation tool that could be applied to any floating wind turbine to optimise the main geometry design parameters. In this study, the OC3 spar buoy concept is considered as an example, where the stability and dynamic performance of the device are verified using hydrostatic and time-domain computations. The numerical simulations are solved using an in-house MATLAB code that uses Salome-Meca to create the mesh and obtain hydrostatic and dynamic properties of the platform, Nemoh to calculate the hydrodynamic coefficients and an aero-hydro-servo Simscape model for the time-domain simulation. The main geometry design parameters of the buoy are optimised using a genetic algorithm in combination with the Kriging surrogate model to minimise the buoy’s structural cost while ensuring the spar’s performance. The optimal design reduces the cost by two to three times the worst configuration of the design space and there is also a 25% cost reduction between the most and the least restrictive optimal cases. The optimal design results demonstrate the hydrostatic constraints’ significance over the dynamic ones as they mostly influence the feasible design area. However, the results of this work could only be specific to the design case considered, and careful consideration should be given to other types of geometries. The optimisation approach presented is particularly important as it is flexible and can be adapted to other platforms.

In this investigation, a comprehensive study was conducted on a U-shaped sloshing tank, based on reversing the classical treatment of such devices as motion stabilizers and using them instead to improve the performance of wave energy converters. The modeling encompasses a comparative analysis between a linear model and Computational Fluid Dynamics (CFD) simulations. The validation of the CFD methodology was rigorously executed via a series of experimental tests, subsequently enhancing the linear model. The refined linear model demonstrates a notable alignment with rigorously verified results, thus establishing itself as a reliable tool for advanced research, indicating promise for various applications. Furthermore, this novelty is addressed by simulating the integration of a U-tank device with a pitch-based wave energy converter, displaying a broadening of the operational bandwidth and a substantial performance improvement, raising the pitch motion of the floater to about 850% in correspondence with the new secondary peak over extended periods, effectively addressing previously identified limitations. This achievement contributes to the system’s practical relevance in marine energy conversion.

Abstract Background Williams syndrome (WS) and Autism Spectrum Disorders (ASD) are neurodevelopmental conditions associated with atypical but opposite face-to-face interactions patterns: WS patients overly stare at others, ASD individuals escape eye contact. Whether these behaviors result from dissociable visual processes within the occipito-temporal pathways is unknown. Using high-density electroencephalography, multivariate signal processing algorithms and a protocol designed to identify and extract evoked activities sensitive to facial cues, we investigated how WS (N = 14), ASD (N = 14) and neurotypical subjects (N = 14) decode the information content of a face stimulus. Results We found two neural components in neurotypical participants, both strongest when the eye region was projected onto the subject's fovea, simulating a direct eye contact situation, and weakest over more distant regions, reaching a minimum when the focused region was outside the stimulus face. The first component peaks at 170 ms, an early signal known to be implicated in low-level face features. The second is identified later, 260 ms post-stimulus onset and is implicated in decoding salient face social cues. Remarkably, both components were found distinctly impaired and preserved in WS and ASD. In WS, we could weakly decode the 170 ms signal based on our regressor relative to facial features, probably due to their relatively poor ability to process faces’ morphology, while the late 260 ms component was highly significant. The reverse pattern was observed in ASD participants who showed neurotypical like early 170 ms evoked activity but impaired late evoked 260 ms signal. Conclusions Our study reveals a dissociation between WS and ASD patients and points at different neural origins for their social impairments.

Summary: Here, we present an optimized iDISCO+ protocol combining tissue clearing and light sheet microscopy to map the postnatal development of oxytocin and vasopressin neurons in mouse hypothalamus. We describe tissue preparation, immunostaining, clearing, and imaging. We then detail how to process the 3D cell dataset to analyze cell network using a point-based recording procedure that accurately maps neurons in the Allen brain atlas. This protocol can be applied to any neuronal population, in different brain regions and at different developmental stages.For complete details on the use and execution of this protocol, please refer to Soumier et al. (2021).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

In 2014, the Sardinian Regional Department of Hygiene, Health and Social Security promoted the Regional Prevention Plan, which embraced the protection of the population from exposure to indoor pollutants, including radon gas. The programme foresaw: the drafting of “Guidance for the construction/renovation of buildings”; radon monitoring and mapping activities during a dedicated campaign based on geological surveying; a radon health impact assessment; community involvement and a radon risks communication campaign. The objectives of the programme were focused to protect Sardinian population from radon risk, with special reference to vulnerable and susceptible subjects, spread knowledge about risks and the opportunities to reduce them. Using a Health Impact Assessment procedure, the number of attributable deaths was estimated based on radon exposure levels, also visible as preventable events by implementing preventive actions. The purpose of this article is to illustrate the activities carried out, with specific reference to the use of communication to develop each action, to understand strengths and weaknesses and the lessons to be applied in Sardinia and other areas. Monitoring and evaluation results indicate that the health of populations living in radon-exposed areas can be significantly improved by reducing exposure to radon and synergistic risk factors. It is essential to strengthen awareness-raising events using historical and acquired knowledge, and to monitor progress in order to reinforce further actions, as these schemes should be planned for the long term, with central coordination and continuous evaluation. The case of radon risk management and communication in Sardinia offers a number of suggestions and lessons learned, both for the continuation of the work that is expected to be very intense in the coming years, and for the problems that may arise in other regions and countries affected by radon risk.

To advance wave energy devices towards commercialization, it is essential to optimize their design to enhance system performance. Additionally, a thorough economic evaluation is crucial for making these technologies competitive with other renewable energy sources. This study focuses on the techno-economic optimization of an innovative inertial system, the so-called SWINGO system, which is based on gyropendulum technology. SWINGO stands out due to its high energy efficiency in multi-directional installation sites, where wave directions vary significantly throughout the year. The study introduces the application of a multi-objective Evolutionary Algorithm (EA), specifically the Non-dominated Sorting Genetic Algorithm II (NSGA-II), to optimize the techno-economic performance of the SWINGO system. This approach aims to identify optimal design parameters that maximize energy extraction while considering economic viability. By deriving a Pareto frontier, a set of optimal devices is selected for further analysis. The performance of the SWINGO system is also compared to an alternative (mono-directional) inertial wave energy converter, the Inertial Sea Wave Energy Converter (ISWEC), to highlight the differences in techno-economic outcomes. Both systems are evaluated at two different installation sites: Pantelleria island and the North Sea in Denmark, with a focus on the directional wave scatter at each location. [ABSTRACT FROM AUTHOR]