The relevance of affective information triggers cognitive prioritisation, dictated by both the attentional load of the relevant task, and socio-emotional abilities. This dataset provides electroencephalographic (EEG) signals related to implicit emotional speech perception under low, intermediate, and high attentional demands. Demographic and behavioural data are also provided. Specific social-emotional reciprocity and verbal communication characterise Autism Spectrum Disorder (ASD) and may influence the processing of affective prosodies. Therefore, 62 children and their parents or legal guardians participated in data collection, including 31 children with high autistic traits (x̄_age=9.6-year-old, σ_age=1.5) who previously received a diagnosis of ASD by a medical specialist, and 31 typically developed children (x̄_age=10.2-year-old, σ_age=1.2). Assessments of the scope of autistic behaviours using the Autism Spectrum Rating Scales (ASRS, parent report) are provided for every child. During the experiment, children listened to task-irrelevant affective prosodies (anger, disgust, fear, happiness, neutral and sadness) while answering three visual tasks: neutral image viewing (low attentional load), one-target 4-disc Multiple Object Tracking (MOT; intermediate), one-target 8-disc MOT (high). The EEG data recorded during all three tasks and the tracking capacity (behavioural data) from MOT conditions are included in the dataset. Particularly, the tracking capacity was computed as a standardised index of attentional abilities during MOT, corrected for guessing. Beforehand, children answered the Edinburgh Handedness Inventory, and resting-state EEG activity of children was recorded for 2 minutes with eyes open. Those data are also provided. The present dataset can be used to investigate the electrophysiological correlates of implicit emotion and speech perceptions and their interaction with attentional load and autistic traits. Besides, resting-state EEG data may be used to characterise inter-individual heterogeneity at rest and, in turn, associate it with attentional capacities during MOT and with autistic behavioural patterns. Finally, tracking capacity may be useful to explore dynamic and selective attentional mechanisms under emotional constraints.

The necessity of developing more realistic artificial food requires the aggregation of different biomaterials in an ordered and controlled manner. One of the most advanced methods for this is food printers reproducing additive manufacturing processes. This study presents a fully automatized 3D food printer leveraging collaborative Cartesian and multi-ink robotic systems to create complex food structures, with materials with different rheological settings using a screw conveyor configuration with controlled motion velocity. The developed food printer followed a formal mechatronic design strategy with fully functional instrumentation and automation systems. An adaptive controller was developed and implemented to regulate the coordinated operation of booth robotic devices, which are enforced by the G-code corresponding to the target food structure, leading to the necessary resolution. This device was tested with different commercial food inks to develop structures with complex shapes. The workability of the developed printer was confirmed by examining the food samples obtained using multiple materials, including creating different three-dimensional structures of a single complex food ink and creating simple structures made of different food inks with diverse structures that could yield a synthetic tissue that reproduces synthetic meat.

This study aims to develop and validate an integrated extrusion bioprinting system that produces planar and non-planar scaffolds with embedded living material (bacteria or mammalian cells), overcoming the limitation of traditional extrusion bioprinting, where the material is deposited and cultured in planar layers. The bioprinting device was constructed by modifying a fused deposition modelling 3D printer, adapting the extrusion holder for hydrogel-bioinks, going from an 8-bit architecture to a 32-bit one andad hoc updating the firmware, increasing the processing capacity and enabling accurate deposition of material. The device performance was assessed in hydrogel 3D planar and non-planar extrusion, considering different radius of curvature to form porous scaffolds, evaluating their ability to retain the designed curved geometry and the cell viability maintaining in bacterial and mammalian cells bioinks. The viability (up to 99%) and growth of bacteria and mammalian cells embedded in the scaffolds was confirmed by confocal microscopy. The suggested bioprinting platform and procedure integrates an efficient strategy for producing hydrogel-based scaffolds, obtaining 98% resolution in planar deposition. For non-planar scaffolds, it was found that they are capable of maintaining the designed curvature even after being removed from the support, with an 88% of resolution. It is reported a novel and advanced 3D extrusion bioprinting strategy for producing curved and complex scaffolds, preserving resolution and sterile conditions, introducing in addition a methodology for direct design and generation of a g-code with continuous and smooth paths, pioneering on the 3D bioprinting of bacterial bioinks.