Complex 3D Research Articles

Gaze, Wall, and Racket: Combining Gaze and Hand-Controlled Plane for 3D Selection in Virtual Reality

Raypointing, the status-quo pointing technique for virtual reality, is challenging with many occluded and overlapping objects. In this work, we investigate how eye-tracking input can assist the gestural ray pointing in the disambiguation of targets in densely populated scenes. We explore the concept of Gaze + Plane, where the intersection between the user's gaze and a hand-controlled plane facilitates 3D position specification. In particular, two techniques are investigated: Gaze&Wall, which employs an indirect plane positioned in depth using a hand ray, and Gaze&Racket, featuring a hand-held and rotatable plane. In a first experiment, we reveal the speed-error trade-offs between Gaze + Plane techniques. In a second study, we compared the best techniques to newly designed gesture-only techniques, finding that Gaze&Wall is less error-prone and significantly faster. Our research has relevance for spatial interaction, specifically on advanced techniques for complex 3D tasks.

A Balanced Mission Planning for Multiple Unmanned Underwater Vehicles in Complex Marine Environments

The collaboration of a multiple unmanned underwater vehicles (multi-UUVs) system has attracted widespread attention in recent years, as it can overcome the limitations of a single UUV and enhance mission completion efficiency. Oriented towards patrol and exploration missions with multiple waypoints, this paper proposes a balanced mission planning strategy, aiming to improve mission quality while reducing mission time for multi-UUVs. Firstly, due to the uneven performance of the two optimization objectives, a quick initialization screening method is employed specifically for mission quality to reduce the mission space. Secondly, to ensure mission load distribution and collaboration among multi-UUVs, and ease the difficulty in solving the issues of mission allocation and route planning, a balanced bi-level mission planning method based on regional segmentation is proposed. Finally, applicable weight evaluation criteria are utilized to evaluate the feasible solution set and determine the optimal solution. The efficacy of the balanced mission planning strategy is substantiated through comprehensive numerical simulations in a complex 2D marine environment.

Comprehensive Geometric Parameterization and Computationally Eficient 3D Shape Matching Optimization of Realistic Stents

Abstract Flexible and compact shape representation schemes are essential for design optimization problems. Current shape representation schemes for coronary stent designs concern predominantly idealized or Independent Ring (IR) designs, which are outdated and only consider a small number of core design variables (such as strut width, height, and thickness) and ignore clinically critical characteristics such as the number of connectors. No reports exist on the geometry parameterization of the latest Helical Stents (HS) that have more complex designs than IR stents. Here, we present two new shape parameterization schemes to fully capture the 3D designs of contemporary IR and double-helix HS stents. We developed a 3D stent geometry builder based on 17 (IR) and 18 (HS) design variables, including strut width, thickness, height, number of connectors and rings, stent length, and strut centerline shape. The shape of the strut centerline was derived via a combination of NURBS, PARSEC, quarter circle, and straight line segments. Shape matching for complex 3D geometries, such as the contemporary stents within limited function evaluations, is not trivial and requires efficient parameterization and optimization algorithms. We used shape matching optimization with a limited function evaluation budget to test the proposed parameterization and two surrogate-assisted optimization algorithms relying on predictor believer and an expected improvement maximization formulation. The performance of these algorithms is objectively compared with a gradient-based optimization method to highlight their strengths. Our work paves the way for more realistic, full-fledged stent design optimization with structural and hemodynamic objectives in the future.

Unsupervised generative model for simulating post-operative double eyelid image.

Simulating the outcome of double eyelid surgery is a challenging task. Many existing approaches rely on complex and time-consuming 3D digital models to reconstruct facial features for simulating facial plastic surgery outcomes. Some recent research performed a simple affine transformation approach based on 2D images to simulate double eyelid surgery outcomes. However, these methods have faced challenges, such as generating unnatural simulation outcomes and requiring manual removal of masks from images. To address these issues, we have pioneered the use of an unsupervised generative model to generate post-operative double eyelid images. Firstly, we created a dataset involving pre- and post-operative 2D images of double eyelid surgery. Secondly, we proposed a novel attention-class activation map module, which was embedded in a generative adversarial model to facilitate translating a single eyelid image to a double eyelid image. This innovative module enables the generator to selectively focus on the eyelid region that differentiates between the source and target domain, while enhancing the discriminator's ability to discern differences between real and generated images. Finally, we have adjusted the adversarial consistency loss to guide the generator in preserving essential features from the source image and eliminating any masks when generating the double eyelid image. Experimental results have demonstrated the superiority of our approach over existing state-of-the-art techniques.

Phase Field Coupled Finite Deformation Plasticity Formulation of Ductile Fracture With Nonlinear Kinematic Hardening and Modified Energy Release Function

ABSTRACTA ductile damage theory is presented by coupling the covariant formulation of finite deformation plasticity with the phase field modeling of fracture, including kinematic hardening for the ductile response of the materials. A phase field coupled nonlinear kinematic hardening equation is proposed in the reference configuration having equivalent representation through the Lie derivative of the kinematic hardening tensor by push‐forward operation in the spatial configuration, thus ensuring the satisfaction of frame invariance. To capture the correct physical response of the material by the phase field evolution equation, the fracture driving function, that is, the difference between the sum of elastic and plastic energies and threshold energy, after the damage initiation is modified by an energy release controlling function, which is an empirical relation of equivalent plastic strain. In defining the energy release controlling function, well‐defined points with physical significance in the experimental load versus displacement curve are used. To simulate the response of the material in relatively large time steps, a modified staggered scheme is presented, evaluating the fracture driving and energy release controlling functions from the previous converged step and using the updated phase field variable in the weak form of the momentum balance equation. To quantify different material parameters from available experimental results in the literature, the developed phase field coupled elasto‐plastic model uses a neural network optimization procedure consisting of neural network training together with optimization in MATLAB and finite element model evaluation in Abaqus user element subroutine UEL. Model capabilities are demonstrated by simulating the crack propagation in complex 3D geometries such as the second and third Sandia Fracture Challenges.

New dietary trends and alternative proteins: the emergence of novel food allergens.

New dietary trends driven by environmental and health considerations will undoubtedly lead to the emergence of novel food allergens. Assessment of the allergenic risk of new or modified protein-containing food sources and ingredients, as well as surveillance of emerging food allergies, is then required. Developments of in silico and in vitro models apprehending protein capacity to cross-react with other homologous proteins and to induce a de novo allergic sensitization are ongoing to better integrate multiple parameters such as 3D structural information or major histocompatibility complex class II (MHC-II) presentation propensity. However, the effects of food matrices and food processing still need to be addressed in these models. Consequently, clinical and postmarket surveillance remain of critical importance to alert on emergent food allergies, which are modulated by regional dietary practices. Monitoring of the emergence of food allergens requires close collaborations between allergologists, consumers, patient associations and food safety authorities. We also need to get a consensus on an acceptable level of allergenic risk that offers the possibility to develop and market innovative and sustainable food products.

Data-Driven Sparse Sensor Placement Optimization on Wings for Flight-By-Feel: Bioinspired Approach and Application.

Flight-by-feel (FBF) is an approach to flight control that uses dispersed sensors on the wings of aircraft to detect flight state. While biological FBF systems, such as the wings of insects, often contain hundreds of strain and flow sensors, artificial systems are highly constrained by size, weight, and power (SWaP) considerations, especially for small aircraft. An optimization approach is needed to determine how many sensors are required and where they should be placed on the wing. Airflow fields can be highly nonlinear, and many local minima exist for sensor placement, meaning conventional optimization techniques are unreliable for this application. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm extracts information from a dense array of flow data using singular value decomposition and linear discriminant analysis, thereby identifying the most information-rich sparse subset of sensor locations. In this research, the SSPOP algorithm is evaluated for the placement of artificial hair sensors on a 3D delta wing model with a 45° sweep angle and a blunt leading edge. The sensor placement solution, or design point (DP), is shown to rank within the top one percent of all possible solutions by root mean square error in angle of attack prediction. This research is the first to evaluate SSPOP on a 3D model and the first to include variable length hairs for variable velocity sensitivity. A comparison of SSPOP against conventional greedy search and gradient-based optimization shows that SSPOP DP ranks nearest to optimal in over 90 percent of models and is far more robust to model variation. The successful application of SSPOP in complex 3D flows paves the way for experimental sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

Effects of Build Direction and Heat Treatment on the Defect Characterization and Fatigue Properties of Laser Powder Bed Fusion Ti6Al4V

Laser powder bed fusion (LPBF) is one of the high-precision additive manufacturing techniques for producing complex 3D components. It is well known that defects appear in additive-manufactured parts, and they deeply affect the fatigue properties; even heat treatment is performed after printing. In order to meet the safe-life design requirements of additive-manufactured aircraft structures, the effects of build direction and heat treatment on defects and fatigue properties need to be quantified. Hence, Ti6Al4V alloy samples with different build directions were designed and printed by LPBF. X-ray computed tomography was used to quantitatively analyze the defect size, the sphericity, and the defect orientation. And their effects on fatigue properties were studied. An extended effective defect size and a defect-based fatigue anisotropy evaluation process are proposed to qualify the effects of the defect size, sphericity, and defect orientation. It is shown that the build direction can affect the porosity distribution and maximum defect size, while the annealing treatment can cause the coalescence of small defects and higher porosity. The defect orientation exhibited a fluctuating trend of 0°–90°–0°–90°–0° as the volume increased. The elongated lack of fusion defects related to the build direction was the main crack source and could lead to fatigue anisotropy of LPBF Ti6Al4V.

Disentangling the Optoelectronic Behavior of Lead Iodide Governed by Two-Dimensional Electron Confinement.

We present a joint experimental and theoretical study for complete spectroscopic characterization and optoelectronic properties of lead iodide. Experimentally, we combine X-ray diffraction experiments to elucidate the structure with photoelectron spectroscopy to explore its electronic structure. Computationally, simulations are performed in the frame of density functional theory. We show that PbI2 presents a two-dimensional layered structure and exhibits a large transient photocurrent effect under visible light illumination, which are compatible with the surface photovoltage scenario. The transient photocurrent has an extremely long lifetime: when the sample is lightened with visible light, it shows very long relaxation times and, consequently, huge charge carrier diffusion lengths. We explain this anomalous behavior with the slow carrier mobility of holes and electrons caused by the 2D electron confinement in the layered material. Our results can be used as a simple model for understanding the optoelectronic properties of more complex 2D hybrid perovskites.

AI‐assisted Field Plate Design of GaN HEMT Device

AbstractGaN High Electron Mobility Transistors (HEMTs) plays a vital role in high‐power and high‐frequency electronics. Meeting the demanding performance requirements of these devices without compromising reliability is a challenging endeavor. Field Plates are employed to redistribute the electric field, minimizing the risk of device failure, especially in high‐voltage operations. While machine learning is applied to GaN device design, its application to field plate structures, known for their geometric complexity, is limited. This study introduces a novel approach to streamlining the field plate design process. It transforms complex 2D field plate structures into a concise feature space, reducing data requirements. A machine learning‐assisted design framework is proposed to optimize field plate structures and perform inverse design. This approach is not exclusive to the design of GaN HEMTs and can be extended to various semiconductor devices with field plate structures. The framework combines technology computer‐aided design (TCAD), machine learning, and optimization, streamlining the design process.

3D Polymeric Lattice Microstructure-Based Microneedle Array for Transdermal Electrochemical Biosensing.

Microneedles (MNs) or microneedle arrays (MNAs) are critical components of minimally invasive devices comprised of a single or a series of micro-scale projections. MNs can bypass the outermost layer of the skin and painlessly access microcirculation of the epidermis and dermis layers, attracting great interest in the development of personalized healthcare monitoring and diagnostic devices. However, MN technology has not yet reached its full potential since current micro- and nanofabrication methods do not address the need of fabricating MNs with complex surfaces to facilitate the development of clinically adequate devices. This work presents a new approach that combines 3D printing technology based on two-photon polymerization with soft lithography for cost-effective and time-saving fabrication of complex MNAs. Specifically, this method relies on printing complex 3D objects efficiently replicated into polymeric substrates via soft lithography, resulting in a free-standing polymeric lattice (PL) membrane that can be transferred onto gold-coated MNs and used for electrochemical biosensing. This platform shows excellent electrochemical performance in detecting metabolite (glucose) and protein (insulin) biomarkers with a dynamic linear range sufficient for detecting biomarkers in healthy individuals and patients. The approach holds great potential for fabricating next-generationMNs, including their transfer into clinically adequate devices.

Finite Element Analysis of Leaf Spring Fabricated Via Fused Deposition Modeling (FDM)

An introduction to fused deposition modeling, or 3D printing technology, will be given in this chapter. The basic idea of additive manufacturing and its underlying scientific theory will be presented at the outset of this chapter as a novel and emerging industrial technology. The parameters used to predict the melt deposition of polymers and their basic interactions with the structural component qualities will also be covered in this chapter. The chapter will provide a brief description of the quality features of FDM products concerning the process parameters. The additive manufacturing process will involve layering material to produce three-dimensional (3D) parts using a class of manufacturing technologies known as additive manufacturing (AM). This substance will include composite, metal, polymer, or concrete materials. A manufacturing process will need to have the following three main elements to be designated as an AM technique: making visual 3D models with computers and computer-aided design (CAD), utilizing a variety of CAD tools such as AutoCAD, SolidWorks, CATIA, and others. Some of these programs will be either closed- source or open-source. For additive manufacturing to be successful, an engineer or artist working with several computers will need to be proficient in using multiple operating systems. With these CAD tools and user experiences, it will be possible to produce a variety of complex 3D product models. The amount of material a 3D printer will take and the time it will require will be important factors influencing the additive manufacturing process.

Modelling the influence of vitamin D and probiotic supplementation on the microbiome and immune response

Abstract The intestinal microbiota play a critical role in human health and disease, maintaining metabolic and immune/inflammatory health, synthesizing essential vitamins and amino acids and maintaining intestinal barrier integrity. The aim of this paper is to develop a mathematical model to describe the complex interactions between the microbiota, vitamin D/vitamin D receptor (VDR) pathway, epithelial barrier and immune response in order to understand better the effects of supplementation with probiotics and vitamin D. This is motivated by emerging data indicating the beneficial effects of vitamin D and probiotics individually and when combined. We propose a system of ordinary differential equations determining the time evolution of intestinal bacterial populations, concentration of the VDR:1,25(OH)$_{2}$D complex in epithelial and immune cells, the epithelial barrier and the immune response. The model shows that administration of probiotics and/or vitamin D upregulates the VDR complex, which enhances barrier function and protects against intestinal inflammation. The model also suggests co-supplementation to be superior to individual supplements. We explore the effects of inflammation on the populations of commensal and pathogenic bacteria and the vitamin D/VDR pathway and discuss the value of gathering additional experimental data motivated by the modelling insights.

Microsurgical anatomy and the inner architecture of the retrocommissural portion of the hippocampal formation demonstrated through fiber microdissection.

An understanding of the complex nomenclature and 3D spatial relations between the cortical and white matter components of the retrocommissural portion of the hippocampal formation is essential for a successful outcome when performing surgery in the mediobasal temporal region. The goal of this study was to clarify the nomenclature related to the retrocommissural portion of the hippocampal formation and to provide a detailed description of its topography and inner structure from a relevant surgical perspective. This description can serve as an anatomical reference for approaching lesions in the mediobasal temporal region. Fiber microdissection was performed from the superolateral and inferior aspects on 20 previously frozen, formalin-fixed human brains. Three formalin-fixed plastinated brain specimens were then sectioned in the coronal, axial, and sagittal planes, and the relevant sections were studied. Based on its relationship with the corpus callosum, the hippocampal formation is subdivided into precommissural, supracommissural, and retrocommissural sections. The retrocommissural portion of the hippocampal formation, a structure in the mediobasal temporal region, is a component of both the floor of the temporal horn and the medial surface of the cerebral hemisphere. It includes the hippocampus (Ammon's horn and the dentate gyrus), subiculum, and related white matter fibers. Step-by-step microdissection revealed the complex ventricular and cisternal relationships of the retrocommissural portion of the hippocampal formation in the mediobasal temporal region. This further allowed clear distinction of each component of this formation in order to understand their complex reciprocal relationships that comprise a unique internal architecture and external morphology. The fiber microdissection technique provides a valuable perspective for understanding the complex structure and relations of the components of the retrocommissural portion of the hippocampal formation. This study clarifies and supplements the information presently available in the literature by offering an anatomical reference essential for differentiating the topographic diagnosis and safer surgical planning for any lesion within this formation or the mediobasal temporal region.

Simultaneous processing of both handheld biomixing and biowriting of kombucha cultured pre-crosslinked nanocellulose bioink for regeneration of irregular and multi-layered tissue defects

The nanocellulosic pellicle derived from the symbiotic culture of bacteria and yeast (Kombucha SCOBY) is an important biomaterial for 3D bioprinting in tissue engineering. However, this nanocellulosic hydrogel has a highly entangled gel network. This needs to be partially modified to improve its processability and extrusion ability for its applications in the 3D bioprinting area. To control its mechanical and biological properties for direct 3D bioprinting applications, uniform reinforcement of nanocellulose-interacting polymers and nanoparticles in such a prefabricated gel network is essential. In this study, the hydrogel network is partially hydrolyzed with organic acid and subsequently transformed into a 3D bioprintable polyelectrolyte complex with chitosan and kaolin nanoparticles without any chemical crosslinker using a handheld 3D bioprinter. This handheld bioprinter ensures homogeneity in both biomixing and bioprinting of chitosan and kaolin within the modified nanocellulose network for multi-layered bioprinted scaffolds through an extensional shear mechanism. The biomixing simulation, mechanical (static, dynamic, and cyclic), 3D bioprinting, and cellular studies confirm the homogeneous biomixing of kaolin nanoparticles and live cells in this nanocellulose-chitosan polyelectrolyte hydrogel. The combination of SCOBY-derived nanocellulose-chitosan bioink with kaolin nanoparticles and a screw-driven handheld extrusion bioprinter demonstrates a promising platform for layer-by-layer regeneration of complex tissues with homogeneous cell/particle distribution with high cell viability.

3D-Printing Functional Ceramic for One-Step Fabrication of Pd/C Catalytic Reactor

Catalysts are widely used in the chemical industry because of their environmental friendliness and low energy consumption. However, integrated fabrication of catalytic reactors (CRs) remains challenging. In this study, we propose the integrated manufacturing of a palladium-carbon (Pd/C) CR for the first time. The outer shell ink comprises Al2O3 powder and aluminum dihydrogen phosphate (AP), whereas the inner core ink consists of activated carbon powder, AP, and polymethylmethacrylate (PMMA). By integrating with the coaxial 3D printing strategy, the Pd/C CR can be freeform-designed with different core thicknesses, lengths, and shapes (W-type, L-type, and U-type). Based on this, a CR with excellent catalytic properties was further developed by loading palladium (Pd) particles. Typically, the resultant Pd/C CR with a length of 2.5 cm exhibits a catalytic efficiency of up to 97.6% after 60 min. This method of preparing Pd/C CR using coaxial 3D printing combines multimaterial 3D printing, integrated molding, and complex biomimetic structure fabrication. This offers a feasible and cost-effective solution that uses a simple fabrication process.

Topology, dynamics, and control of a muscle-architected soft arm

Muscular hydrostats, such as octopus arms or elephant trunks, lack bones entirely, endowing them with exceptional dexterity and reconfigurability. Key to their unmatched ability to control nearly infinite degrees of freedom is the architecture into which muscle fibers are weaved. Their arrangement is, effectively, the instantiation of a sophisticated mechanical program that mediates, and likely facilitates, the control and realization of complex, dynamic morphological reconfigurations. Here, by combining medical imaging, biomechanical data, live behavioral experiments, and numerical simulations, an octopus-inspired arm made of [Formula: see text]200 continuous muscle groups is synthesized, exposing "mechanically intelligent" design and control principles broadly pertinent to dynamics and robotics. Such principles are mathematically understood in terms of storage, transport, and conversion of topological quantities, effected into complex 3D motions via simple muscle activation templates. These are in turn composed into higher-level control strategies that, compounded by the arm's compliance, are demonstrated across challenging manipulation tasks, revealing surprising simplicity and robustness.

Cage-like micro-scaffolds fabricated by DLW method for cell investigation

This paper focuses on the use of direct laser writing method in fabricating three-dimensional biocompatible scaffolds that emulate the extracellular matrix. The interaction between HEK 293 cells and these cage-like scaffolds, particularly the effect of pore size on cell invasion, is explored in detail. Our study underscores the influence of scaffold architecture on cellular behavior and highlights the potential of direct laser writing technology in creating complex 3D scaffolds. The insights gleaned from this research could be invaluable in future applications such as tissue engineering, regenerative medicine, and drug delivery.

Effects of Leafy Flexible Vegetation on Bed‐Load Transport and Dune Geometry

AbstractThe development of sustainable river management strategies requires knowledge of the effect of vegetation on hydrodynamics and sediment transport. To date, the complex physical processes involving the combined effects of leafy flexible vegetation and mobile bedforms are not completely understood. Most sediment transport models have been developed for bare bed conditions so that their performance in the presence of leafy flexible vegetation remains unclear. On the other hand, recently developed models consider vegetated conditions but they typically account only for the presence of rigid cylinders and in some cases scour at their base. For this purpose, laboratory experiments were conducted with mobile dune bed conditions and artificial flexible plants with varying Leaf Area Index to investigate the effect of flexible vegetation on bed morphology and sediment transport. Sediment transport rates and bedform characteristics such as height, wavelength and celerity, were measured in specifically designed experimental runs. The collected data show that the presence of leafy vegetation alters bed morphology, tending to reduce the average dune wavelength and leading to the formation of complex 3D geometries. Bed‐shear‐stress‐based models for predicting sediment transport were verified to be valid under conditions of low vegetation roughness density. On the contrary, the collected data emphasize that the measured bed‐load transport rate increased in the presence of leafy flexible vegetation with higher frontal area. Recent bed‐load models for vegetated channels provide a better interpretation for dense leafy vegetation but are less effective when predominant effects related to dunes are present.

Enhancing brain image quality with 3D U-net for stripe removal in light sheet fluorescence microscopy

Light Sheet Fluorescence Microscopy (LSFM) is increasingly popular in neuroimaging for its ability to capture high-resolution 3D neural data. However, the presence of stripe noise significantly degrades image quality, particularly in complex 3D stripes with varying widths and brightness, posing challenges in neuroscience research. Existing stripe removal algorithms excel in suppressing noise and preserving details in 2D images with simple stripes but struggle with the complexity of 3D stripes. To address this, we propose a novel 3D U-net model for Stripe Removal in Light sheet fluorescence microscopy (USRL). This approach directly learns and removes stripes in 3D space across different scales, employing a dual-resolution strategy to effectively handle stripes of varying complexities. Additionally, we integrate a nonlinear mapping technique to normalize high dynamic range and unevenly distributed data before applying the stripe removal algorithm. We validate our method on diverse datasets, demonstrating substantial improvements in peak signal-to-noise ratio (PSNR) compared to existing algorithms. Moreover, our algorithm exhibits robust performance when applied to real LSFM data. Through extensive validation experiments, both on test sets and real-world data, our approach outperforms traditional methods, affirming its effectiveness in enhancing image quality. Furthermore, the adaptability of our algorithm extends beyond LSFM applications to encompass other imaging modalities. This versatility underscores its potential to enhance image usability across various research disciplines.