Additive manufacturing (AM) is a valuable addition to engineering design by enabling complex geometries, reduced waste, and rapid prototyping. Despite these advantages, the structural integrity of 3D-printed components can be limited by several factors, such as anisotropy, porosity, and layer adhesion [1]. Adhesive bonding has gained relevance as an effective method to join 3D-printed components, offering benefits such as stress distribution, energy absorption, and compatibility with complex geometries. Adhesive bonding, unlike mechanical fastening or welding, distributes stresses more uniformly and eliminates the need to drill holes, which are required for bolted joints. In 3D-printed components, adhesives offer a versatile solution to join dissimilar materials or repair parts without inducing heat-affected zones, oppositely to welded joints. However, the effectiveness of adhesive bonding relies on parameters such as surface energy, adhesive type, and the quality of surface preparation [2]. Adhesive bonding of 3D-printed components entail difficulties such as high surface roughness, internal defects, and anisotropic properties due to layer-by-layer deposition. These factors complicate adhesion and require an additional design effort in the adhesive selection, surface treatment, and joint design.

This paper reports an experimental procedure based on the Constructal Law to reduce the noise level. The study investigates both the component level and the system level noise reduction. It is shown that at 100% load and at the second construct, a noise of 3dB will be reduced.

Keywords: Constructal; Noise Reduction; Correlations; Second Construct

The idea for the Submerge Trimaran hull concept (STR) presented on this paper it’s originated from the Nautilus System (NTLS) stabilizers for motions and currents, which is based on a 2 sides linear approximation using Keulegan-Carpenter number (KC) to obtain the roll motion damping coefficients from the roll decay test of high block coefficient vessels with bilge keels and from which it´s possible to understand that, the damping that’s rules the roll motion of high block coefficient vessels with appendages is more significant at lower oscillations amplitudes (roll decay test latest cycles), it´s mean at lower KC numbers (KC <) were the steady state flow regime is predominant and the GM_T has a linear variation in the stability curve, which however didn’t occur for larger oscillation amplitudes (roll decay test initial cycles) were highest KC numbers (KC >) are relevant (drag forces) meaning that, the action of appendages such as bilge keels is less effective in reducing roll amplitudes as results of the turbulence derived from the back and forth oscillating flow, being the main source for the energy dissipation the vessel hull form capability to generate waves. Therefore, the Submerge Trimaran hull (STR) is a NTLS variation to be applied in conventional vessels with advance velocity to obtain a reduction to the roll amplitudes by increasing the potential damping while restricting the transversal oscillation flow by doing a hull modification from a perspective that considers as a base a hull immerse in a steady state flow regime (lower KC numbers) that´s has the effect of varying the natural roll period, extending the GM_T (STR) linear variation in the transverse stability envelope for a broader range of sea state, as more external excitation energy it´s require to obtain the same conventional hull roll amplitude, as part of the main motivation for the STR hull concept development idea, which is to achieve an overall improvement to a vessel sea keeping performance to cross ocean routes efficiently with energy savings and decabornization.

Keywords: Nautilus System (NTLS); Submerge Trimaran Hull (STR); Roll Motion Control

Quantum computing is poised to transform the field of medicine, offering unprecedented possibilities in diagnostics and treatment. With its immense computational power, quantum computing can tackle medical challenges that are currently insurmountable with classical computers. This editorial explores how quantum computing can be harnessed in modern medicine, discussing its potential benefits and the obstacles that must be addressed.

Artificial intelligence (AI) is becoming a game-changer in the field of dentistry, transforming everything from diagnostics to treatment planning and patient management. With its data-driven capabilities, AI is helping dental professionals provide more accurate, efficient, and personalized care. One of the most significant applications of AI in dentistry is in diagnostic imaging. Machine learning algorithms can analyze dental X-rays, CT scans, and other imaging data with remarkable accuracy. AI systems can detect cavities, root infections, gum diseases, and even early signs of oral cancer by identifying patterns that might be difficult for the human eye to see. For example, in radiographic interpretation, AI can measure bone density and monitor changes over time, helping dentists spot issues before they become severe. Early diagnosis can lead to more effective, less invasive treatments, improving patient outcomes and reducing long-term costs. Another challenging aspect is in the field of treatment planning and predictive analytics as AI also aids in creating more precise and personalized treatment plans. By analyzing a patient’s dental history, genetics, and lifestyle factors, AI-powered systems can predict the progression of certain conditions and recommend optimal treatment plans. For instance, in orthodontics, AI-driven software is used to design custom aligners for treatments like Invisalign, predicting how teeth will move and adjusting the aligners accordingly. This process enhances the accuracy of alignments, shortens treatment times, and improves patient satisfaction. In prosthodontics and implantology, AI can assist in designing and placing dental prosthetics and implants with unparalleled accuracy. Advanced software considers various patient-specific factors, such as bone structure and tooth position, to create the most suitable fit. This helps reduce risks associated with implant failure, ensuring a higher success rate. Moreover, AI shows a promising progress in the field of robotic assistance in dental surgeries as it is paving the way for robotics in dental surgeries, bringing precision and consistency to procedures like implant placement and root canal therapy. Robots powered by AI can assist dentists by stabilizing instruments and guiding them through complex movements with minimal error.

The Fourth Industrial Revolution (Industry 4.0) represents a paradigm shift, one that transcends mere technological evolution. As researchers and practitioners, we find ourselves at the confluence of digital innovation, cyber-physical systems, and transformative societal implications. In this essay, we dissect the core tenets of Industry 4.0 and its profound significance for science and society.