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The application of artificial intelligence models for the fault diagnosis of marine machinery increased expeditiously within the shipping industry. This relates to the effectiveness of artificial intelligence in capturing fault patterns in marine systems that are becoming more complex and where the application of traditional methods is becoming unfeasible. However, despite these advances, the lack of fault labelling data is still a major concern due to confidentiality issues, and lack of appropriate data, for instance. In this study, a method based on histogram similarity and hierarchical clustering is proposed as an attempt to label the distinct anomalies and faults that occur in the dataset so that supervised learning can then be implemented. To validate the proposed methodology, a case study on a main engine of a tanker vessel is considered. The results indicate that the method can be a preliminary option to classify and label distinct types of faults and anomalies that may appear in the dataset, as the model achieved an accuracy of approximately 95% for the case study presented. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has emerged as a transformative technology in the fabrication of intricate structures, offering unparalleled adaptability in crafting complex geometries. Particularly noteworthy is its burgeoning significance within the realm of medical prosthetics, owing to its capacity to seamlessly replicate anatomical forms utilizing biocompatible materials. Notably, the fabrication of porous architectures stands as a cornerstone in orthopaedic prosthetic development and bone tissue engineering. Porous constructs crafted via AM exhibit meticulously adjustable pore dimensions, shapes, and porosity levels, thus rendering AM indispensable in their production. This systematic review ventures to furnish a comprehensive examination of extant research endeavours centred on the generation of porous scaffolds through additive manufacturing modalities. Its primary aim is to delineate variances among distinct techniques, materials, and structural typologies employed, with the overarching objective of scrutinizing the cutting-edge methodologies in engineering self-supported stochastic printable porous frameworks via AM, specifically for bone scaffold fabrication. Findings show that most of the structures analysed correspond to lattice structures. However, there is a strong tendency to use organic structures generated by mathematical models and printed using powder bed fusion techniques. However, no work has been found that proposes a self-supporting design for organic structures. [ABSTRACT FROM AUTHOR]

3D bioprinting involves using bioinks that combine biological and synthetic materials. The selection of the most appropriate cell-material combination for a specific application is complex, and there is a lack of consensus on the optimal conditions required. Plasma-loaded alginate and alginate/methylcellulose (Alg/MC) inks were chosen to study their viscoelastic behaviour, degree of recovery, gelation kinetics, and cell survival after printing. Selected inks showed a shear thinning behavior from shear rates as low as 0.2 s−1, and the ink composed of 3% w/v SA and 9% w/v MC was the only one showing a successful stacking and 96% recovery capacity. A 0.5 × 106 PANC-1 cell-laden bioink was extruded with an Inkredible 3D printer (Cellink) through a D = 410 μm tip conical nozzle into 6-well culture plates. Cylindrical constructs were printed and crosslinked with CaCl2. Bioinks suffered a 1.845 Pa maximum pressure at the tip that was not deleterious for cellular viability. Cell aggregates can be appreciated for the cut total length observed in confocal microscopy, indicating a good proliferation rate at different heights of the construct, and suggesting the viability of the selected bioink PANC-1/P-Alg3/MC9 for building up three-dimensional bioprinted pancreatic tumor constructs. [ABSTRACT FROM AUTHOR]

Climate change has highlighted the need to promote renewable energies. The offshore wind industry is growing exponentially because of some political strategies supported by various organizations, such as the European Union. The implementation of these strategies is commonly associated with significant investments, public acceptance, or achieving better installations and greater cumulative capacities. To ensure that offshore renewable energy projects could reach their ambitious targets, this study promotes the implementation of political strategies or planning decisions using data mining techniques and analytical tools. Strategic decisions based on real data analysis could help to achieve more suitable and optimal infrastructures. The scour phenomenon jeopardizes the operability of offshore wind farms, making it necessary to study its evolution over the years. In this work, extensive research on the scour phenomenon in offshore wind farms using real data (from the Lynn and Inner Dowsing offshore wind farms located in the UK) was performed, which revealed an evident lack of consideration of this phenomenon for data-driven decision-making processes. As a novelty, this research develops a detailed geospatial analysis of data, studying the possible autocorrelation of scour data measured from each turbine between 2011 and 2015. The conclusions obtained could be used to improve future planning tasks in offshore wind farms. [ABSTRACT FROM AUTHOR]

New additive manufacturing techniques, such as melting electro-writing (MEW) or near-field electrospinning (NFES), are now used to include microfibers inside 3D printed scaffolds as FDM printers present a limited resolution in the XY axis, not making it easy to go under 100 µm without dealing with nozzle troubles. This work studies the possibility of creating reproducible microscopic internal fibers inside scaffolds printed by standard 3D printing. For this purpose, novel algorithms generating deposition routines (G-code) based on primitive geometrical figures were created by python scripts, modifying basic deposition conditions such as temperature, speed, or material flow. To evaluate the influence of these printing conditions on the creation of internal patterns at the microscopic level, an optical analysis of the printed scaffolds was carried out using a digital microscope and subsequent image analysis with ImageJ software. To conclude, the formation of heterogeneously shaped microfilaments (48 ± 12 µm, mean ± S.D.) was achieved in a standard FDM 3D Printer with the strategies developed in this work, and it was found that the optimum conditions for obtaining such microfibers were high speeds and a reduced extrusion multiplier. [ABSTRACT FROM AUTHOR]

The search of suitable combinations of stem cells, biomaterials and scaffolds manufacturing methods have become a major focus of research for bone engineering. The aim of this study was to test the potential of dental pulp stem cells to attach, proliferate, mineralize and differentiate on 3D printed polycaprolactone (PCL) scaffolds. A 100% pure Mw: 84,500 ± 1000 PCL was selected. 5 × 10 × 5 mm3 parallelepiped scaffolds were designed as a wood-pilled structure composed of 20 layers of 250 μm in height, in a non-alternate order ([0,0,0,90,90,90°]). 3D printing was made at 170 °C. Swine dental pulp stem cells (DPSCs) were extracted from lower lateral incisors of swine and cultivated until the cells reached 80% confluence. The third passage was used for seeding on the scaffolds. Phenotype of cells was determined by flow Cytometry. Live and dead, Alamar blue™, von Kossa and alizarin red staining assays were performed. Scaffolds with 290 + 30 μm strand diameter, 938 ± 80 μm pores in the axial direction and 689 ± 13 μm pores in the lateral direction were manufactured. Together, cell viability tests, von Kossa and Alizarin red staining indicate the ability of the printed scaffolds to support DPSCs attachment, proliferation and enable differentiation followed by mineralization. The selected material-processing technique-cell line (PCL-3D printing-DPSCs) triplet can be though to be used for further modelling and preclinical experiments in bone engineering studies. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) techniques are becoming the approaches of choice for the construction of scaffolds in tissue engineering. However, the development of 3D printing in this field brings unique challenges, which must be accounted for in the design of experiments. The common printing process parameters must be considered as important factors in the design and quality of final 3D-printed products. In this work, we study the influence of some parameters in the design and fabrication of PCL scaffolds, such as the number and orientation of layers, but also others of "hidden" importance, such as the cooling down rate while printing, or the position of the starting point in each layer. These factors can have an important impact oin the final porosity and mechanical performance of the scaffolds. A pure polycaprolactone filament was used. Three different configurations were selected for the design of the internal structure of the scaffolds: a solid one with alternate layers (solid) (0°, 90°), a porous one with 30% infill and alternate layers (ALT) (0°, 90°) and a non-alternated configuration consisting in printing three piled layers before changing the orientation (n-ALT) (0°, 0°, 0°, 90°, 90°, 90°). The nozzle temperature was set to 172 °C for printing and the build plate to 40 °C. Strand diameters of 361 ± 26 µm for room temperature cooling down and of 290 ± 30 µm for forced cooling down, were obtained. A compression elastic modulus of 2.12 ± 0.31 MPa for n-ALT and 8.58 ± 0.14 MPa for ALT scaffolds were obtained. The cooling down rate has been observed as an important parameter for the final characteristics of the scaffold. [ABSTRACT FROM AUTHOR]