Intricate Structures Research Articles

Rotating kiselev black holes in f(R, T) gravity

Exact solutions describing rotating black holes can provide significant opportunities for testing modified theories of gravity, which are motivated by the challenges posed by dark energy and dark matter. Starting with a spherical Kiselev black hole as a seed metric, we construct rotating Kiselev black holes within the f(R, T) gravity framework using the revised Newman-Janis algorithmthe f(R, T) gravity-motivated rotating Kiselev black holes (FRKBH) with additional parameter quintessence parameter ω and state parameter γ, apart from mass M and spin a, which encompasses, as exceptional cases, Kerr (K = 0) and effective Kerr-Newman (K = Q 2) black holes. These solutions give rise to distinct classes of black holes surrounded by fluids while considering specific values of the w for viable choices for the f(R, T) function. From the parameter space or domain of existence of black holes defined by a and γ for FKRBH, we discover that when a 1 < a < a 2, there is a critical value γ = γ E which corresponds to extreme value black holes portrayed by degenerate horizons. When a < a 1 (a > a 2), we encounter two distinct critical values γ = γ E1, γ E2 with γ E1 > γ E2 (or γ = γ E3, γ E4 with γ E3 > γ E4). We discuss the horizon and global structure of FKRBH spacetimes and examine their dependence on parameters w and γ. This exploration is motivated by the remarkable effects of f(R, T) gravity, which gives rise to diverse and intricate spacetime structures within the domain where black holes exist.

Research Progress in the Separation of Chemical Components from Essential Oils by High-Speed Countercurrent Chromatography

Essential oils (EOs) are vital secondary metabolites in plants. They have garnered substantial attention owing to their distinct flavors and desirable attributes, including potent antioxidant, antibacterial, and antitumor properties. Nevertheless, the active constituents of EOs exhibit intricate chemical structures, and conventional separation techniques are inadequate for purifying the individual chemical components from EOs. High-speed countercurrent chromatography, based on the principles of a hydrodynamic equilibrium system, has emerged as a liquid–liquid chromatographic separation method renowned for its ability to handle substantial single injection volumes and the absence of irreversible adsorption. Consequently, in recent years, this technique has been widely employed in the isolation and refinement of natural products. In this review, a comprehensive analysis is conducted, contrasting the merits and demerits of high-speed countercurrent chromatography with conventional separation methods. The solvent systems, elution modes, commonly employed detectors, and practical applications are reviewed in the context of high-speed countercurrent chromatography for essential oil separation and purification. Furthermore, this review offers a glimpse into the potential prospects of applying this technique, with the intention of serving as a valuable reference for the use of high-speed countercurrent chromatography in the purification of EOs.

3D-printed porous tantalum artificial bone scaffolds: fabrication, properties, and applications.

Porous tantalum scaffolds offer a high degree of biocompatibility and have a low friction coefficient. In addition, their biomimetic porous structure and mechanical properties, which closely resemble human bone tissue, make them a popular area of research in the field of bone defect repair. With the rapid advancement of additive manufacturing, 3D-printed porous tantalum scaffolds have increasingly emerged in recent years, offering exceptional design flexibility, as well as facilitating the fabrication of intricate geometries and complex pore structures that similar to human anatomy. This review provides a comprehensive description of the techniques, procedures, and specific parameters involved in the 3D printing of porous tantalum scaffolds. Concurrently, the review provides a summary of the mechanical properties, osteogenesis and antibacterial properties of porous tantalum scaffolds. The use of surface modification techniques and the drug carriers can enhance the characteristics of porous tantalum scaffolds. Accordingly, the review discusses the application of these porous tantalum materials in clinical settings. Multiple studies have demonstrated that 3D-printed porous tantalum scaffolds exhibit exceptional corrosion resistance, biocompatibility, and osteogenic properties. As a result, they are considered highly suitable biomaterials for repairing bone defects. Despite the rapid development of 3D-printed porous tantalum scaffolds, they still encounter challenges and issues when used as bone defect implants in clinical applications. Ultimately, a concise overview of the primary challenges faced by 3D-printed porous tantalum scaffolds is offered, and corresponding insights to promote further exploration and advancement in this domain are presented.

Neural network approaches for rumor stance detection: Simulating complex rumor propagation systems

SummaryThis research introduces a comprehensive suite of neural network models designed to tackle the challenging task of rumor stance detection within the framework of simulating complex rumor propagation systems. Our objective centers on accurately modeling the intricate structures of rumor dialogues and propagation patterns to identify user stances—whether they are in support, denial, questioning, or commenting on rumors. Unlike conventional methods that rely on simplistic keyword targeting and fail in the nuanced context of social networks, our models delve into the complexities of dialogue and propagation structures, offering a more precise and insightful analysis of rumor dynamics. In addressing the simulation and modeling of complex systems, our approach specifically focuses on the elaborate interaction networks that underpin rumor spread and reception. While our methodology does not directly engage with brain‐like computing paradigms, it reflects a similar level of sophistication in handling layered and complex information flows, analogous to cognitive processes in understanding and interpreting human communications. Employing a hierarchical attention mechanism, our models adeptly parse through multitiered dialogue sequences, effectively distinguishing between various indicators of user stances. This allows for a nuanced and detailed representation of the rumor ecosystem, significantly enhancing the accuracy of stance detection. Through rigorous testing on diverse datasets, our approach has demonstrated superior performance over existing models, thereby establishing a new benchmark in the field.

Crashworthiness capability comparison of a 3D Greek cross fractal structure additively manufactured with polyamide and thermoplastic polyurethane

Crashworthiness capability comparison of a 3D Greek cross fractal structure additively manufactured with polyamide and thermoplastic polyurethane

Characterization of ZmSnRK1 genes and their response to aphid feeding, drought and cold stress

AbstractThe SnRK1 complex in plants regulates metabolism in response to environmental stresses and glucose depletion, for stress adaptation and energy homeostasis. Through phosphorylation of various targets, SnRK1 orchestrates intricate regulatory mechanisms involved in autophagy, nutrient remobilization, and TOR activity inhibition, showcasing its pivotal role in coordinating plant metabolism and stress responses. The present study aimed to identify members of the SnRK1 gene family in the maize genome and characterize them using bioinformatics and expression analyses under aphid feeding, drought, and cold stress. The focus of the study was to conduct a comprehensive analysis towards determining gene diversity of ZmSnRK1 genes, constructing intricate 3D structures, and identifying stress-related cis-elements. Four SnRK1 genes were identified, which were named ZmSnRK1.1, ZmSnRK1.2, ZmSnRK1.3, and ZmSnRK1.4. The SnRK1 proteins were found to have a distribution of conserved motifs; however, the distinction between monocots and dicots in the phylogenetic tree was clearly demonstrated. Analysis of the promoter region revealed that the ZmSnRK1 genes contain stress-related cis-elements. Compared to the control, ZmSnRK1.3 significantly upregulated in response to aphid feeding and cold stress, while ZmSnRK1.2 showed elevated expression under drought conditions. The expression of the other two genes under these treatments was generally unperturbed. The findings of this study are poised to establish a valuable scientific foundation for future research on the roles of the SnRK1 gene family in plants, providing valuable insights for enhancing genetic resilience to stress and optimizing yield traits.

Multi-view fringe projection profilometry for surfaces with intricate structures and high dynamic range

Fringe projection profilometry plays an important role for quality control in production line. However, it is facing challenges in the measurement of objects with intricate structures and high dynamic range that involved in precision manufacturing and semiconductor packaging. In this paper, a multi-view fringe projection profilometry system, which deploys a vertical telecentric projector and four oblique tilt-shift cameras, is presented to address the “blind spots” caused by shadowing, occlusion and local specular reflection. A flexible and accurate system calibration method is proposed, in which the corrected pinhole imaging model is used to calibrate the telecentric projection, and the unified calibration is performed by bundle adjustment. Experimental results show that the 3D repeated measurement error and standard deviation are no more than 10 μm within a measurable volume of 70 × 40 × 20 mm3. Furthermore, a group of experiments prove that the developed system can achieve complete and accurate 3D measurement for high dynamic range surfaces with complex structures.

Direct Ink Writing on a Rotating Mandrel - Additive Lathe Micro-Manufacturing

Abstract Among the promising techniques within Additive Manufacturing (AM), Direct Ink Writing (DIW) stands out for its ability to work with a wide range of materials, including polymers, ceramics, glass, metals, and cement. However, DIW encounters a significant challenge in creating complex tubular structures, such as vascular scaffolds with micro scale features. To address this challenge, our research investigates a novel method known as Additive Lathe Direct Ink Writing (AL-DIW). AL-DIW entails the precise dispensing of ink onto a rotating mandrel to fabricate intricate hollow tubular structures with overhanging geometries. In this research, we present a series of test cases involving tubular structures, comprising straight-line patterns, curved line designs, and complex stent configurations, to underscore the efficacy of this technique in crafting hollow tubular geometries with micro-scale features. This study not only highlights the capabilities of AL-DIW but also contributes to the broader advancement of additive manufacturing techniques for various applications.

Higher Dimensional Leibniz-Rinehart Algebras

In this article, we delve into the realm of higher dimensional Leibniz-Rinehart algebras, exploring the intricate structures of Leibniz algebroids and their applications. By generalizing the concept of Lie algebroids and incorporating a Leibniz rule for the anchor map, the study sheds light on the fundamental principles underlying connections and underscores their significance. Through a comprehensive analysis of Leibniz-Rinehart algebras, this study paves the way for advancements and applications, offering a deeper understanding of the intricate relationship between algebraic and geometric structures.

Exploring the Influence of Cation and Halide Substitution in the Structure and Optical Properties of CH3NH3NiCl3 Perovskite.

This manuscript details a comprehensive investigation into the synthesis, structural characterization, thermal stability, and optical properties of nickel-containing hybrid perovskites, namely CH3NH3NiCl3, CsNiCl3, and CH3NH3NiBrCl2. The focal point of this study is to unravel the intricate crystal structures, thermal behaviors, and optical characteristics of these materials, thereby elucidating their potential application in energy conversion and storage technologies. X-ray powder diffraction measurements confirm that CH3NH3NiCl3 adopts a crystal structure within the Cmcm space group, while CsNiCl3 is organized in the P63/mmc space group, as reported previously. Such structural diversity underscores the complex nature of these perovskites and their potential for tailored applications. Thermal analysis further reveals the stability of CH3NH3NiCl3 and CH3NH3NiBrCl2, which begin to decompose at 260 °C and 295 °C, respectively. The optical absorption properties of these perovskites studied by UV-VIS-NIR spectroscopy revealed the bands characteristic of Ni2+ ions in an octahedral environment. Notably, these absorption bands exhibit subtle shifts upon bromide substitution, suggesting that optical properties can be finely tuned through halide modification. Such tunability is paramount for the design and development of materials with specific optical requirements. By offering a detailed examination of these properties, the study lays the groundwork for future advancements in material science, particularly in the development of innovative materials for sustainable energy technologies.

Applications of Cryogenic Electron Microscopy in Characterizing Electrochemical Materials and Interfaces

Cryogenic electron microscopy (cryo-EM) has emerged as a pivotal technology in materials science, particularly in characterizing electrochemical materials and interfaces. This paper delves into the recent advancements and applications of cryo-EM, underscoring its significance in understanding the intricate structures and mechanisms of materials sensitive to air and electron beams, such as lithium-ion battery electrodes. Cryo-EM's ability to capture materials in a near-natural state using vitreous ice and its compatibility with advanced imaging techniques like cryo-electron energy loss spectroscopy (cryo-EELS), cryo-electron tomography (cryo-ET), and cryo-focused ion beam (cryo-FIB) enhances our understanding of quantum and energy materials. This research will discuss the revolutionary impact of cryo-EM in areas like energy conservation and conversion, highlighting its role in visualizing sensitive materials and electrochemical reaction processes. This research addresses the need for comprehensive discussions on the characterization of quantum and energy materials through cryo-EM and related techniques, offering a thorough overview of recent advancements in this rapidly evolving field.

CompleteDT: Point cloud completion with information-perception transformers

In this work, we propose a novel point cloud completion network, called CompleteDT. To fully capture the 3D geometric structure of point clouds, we introduce an Information-Perception Transformer (IPT) that can simultaneously capture local features and global geometric relations. CompleteDT comprises a Feature Encoder, Query Generator, and Query Decoder. Feature Encoder extracts local features from multi-resolution point clouds to capture intricate geometrical structures. Query Generator uses the proposed IPT, utilizing the Point Local Attention (PLA) and Point Global Attention (PGA) modules, to learn local features and global correlations, and generate query features that represent predicted point clouds. The PLA captures local information within local points by adaptively measuring weights of neighboring points, while PGA adapts multi-head self-attention by transforming it into a layer-by-layer form where each head learns global features in a high-dimensional space of different dimensions. By dense connections, the module allows for direct information exchange between each head and facilitates the capture of long global correlations. By combining the strengths of both PLA and PGA, the IPT can fully leverage local and global features to facilitate CompleteDT to complete point clouds. Lastly, the query features undergo refining to generate a complete point cloud through the Query Decoder. Our experimental results demonstrate that CompleteDT outperforms current state-of-the-art methods, effectively learning from incomplete inputs and predicting complete outputs.

Knowledge-dominated and data-driven rigid-flexible coupling dynamics for rotating flexible structure

Solving a rigid–flexible coupling nonlinear dynamic equation necessitates updating dynamic quantities in each time step, which is the main factor that hampers computational efficiency. Therefore, this study develops an innovative framework that combines knowledge-based and data-driven solutions, for which a data-driven numerical integration (DDNI) method is established to update the mass matrix and load vector. The DDNI model is obtained from offline training based on a deep neural network model and is embedded in the floating frame of reference formulation for online simulation of rigid–flexible coupling problems. As benchmark cases, planar and curved shell structures are analyzed, and the results show that the DDNI method exhibits excellent performance in terms of accuracy and adaptability. In particular, compared to a fully numeric integration (FNI) scheme, the DDNI method shows significantly improved efficiency, surpassing that of commercial software. These noteworthy characteristics aid the investigation of intricate structures in engineering problems. We utilize the developed DDNI method in a rigid–flexible coupling analysis of a manipulator, which shows that it is highly time-efficient, approximately 20 times faster than the FNI scheme, while producing results that are consistent with those of experiments.

Big surgeons don't need big incisions: Minimally invasive surgery and use of robotics in Otolaryngology: A Narrative Review.

Minimally invasive surgery (MIS) and robotics have revolutionized the field of Otolaryngology. MIS and robotics have reshaped traditional otolaryngological practices, offering patients a multitude of benefits. Reduced incision sizes and tissue manipulation minimize postoperative pain and discomfort, while also improving cosmetic outcomes. MIS has facilitated enhanced visualization and access to intricate anatomical structures, enabling the treatment of previously inaccessible lesions. MIS procedures also offer shorter hospital stays, reduced blood loss, and faster healing times whilst enhancing patient satisfaction and overall quality of life The ongoing progress in minimally invasive approaches solidifies their role as a cornerstone in modern Otolaryngology, and surgeons navigating this transformative landscape must embrace the learning curve associated with these advanced techniques, recognizing the potential for improved patient outcomes. This article explores the transformative impact of MIS and robotics on the diverse branches of Otolaryngology, highlighting the technological advancements that have enabled these techniques to flourish.

Optix regulates nanomorphology of butterfly scales primarily via its effects on pigmentation

Previous studies have shown that Optix regulates lower lamina thickness and the type of pigment that is produced in wing scales of a few butterfly species. However, the role of Optix in regulating pigment production across species, and in regulating additional aspects of scale morphology remains to be investigated. By combining microspectrophotometry, scanning electron microscopy, and focused ion beam technology on wild-type and Optix Bicyclus anynana crispants, we show that Optix regulates the production of orange pigments (ommochromes), represses the production of brown pigments (melanins), and regulates the morphology of the lower and upper surface of orange scales. Our findings suggest a conserved role of Optix as a switch gene that activates ommochrome and represses melanin synthesis across butterflies. By comparing these effects with other mutations, where only melanin is removed from scales, we propose that pigmentary changes, alone, affect the way that chitin polymerizes within a scale, changing lower lamina thickness as well as multiple intricate structures of the upper surface.

DNA-Based Replication of Programmable Colloidal Assemblies.

Nature uses replication to amplify the information necessary for the intricate structures vital for life. Despite some successes with pure nucleotide structures, constructing synthetic microscale systems capable of replication remains largely out of reach. Here, a functioning strategy is shown for the replication of microscale particle assemblies using DNA-coated colloids. By positioning DNA-functionalized colloids using capillary forces and embedding them into a polymer layer, programmable sequences of patchy particles are created that act as a primer and offer precise binding of complementary particles from suspension. The strings of complementary colloids are cross-linked, released from the primer, and purified via flow cytometric sorting to achieve a purity of up to 81% of the replicated sequences. The replication of strings of up to five colloids and non-linear shapes is demonstrated with particles of different sizes and materials. Furthermore, a pathway for exponential self-replication is outlined, including preliminary data that shows the transfer of patches and binding of a second-generation of assemblies fromsuspension.

Additive Manufacturing of cryogenic materials

The use of pure copper and Inconel 718 as cryogenic materials has been well known in the cryogenic materials space. Despite their potential, little is known about the use of these materials in cryogenic environments regarding their ability to withstand these conditions when manufactured using Additive Manufacturing (AM) methods. AM has emerged as a promising production method due to its ability to produce complex geometries and near net-shape parts. Copper and Inconel 718 offer a wide range of uses in cryogenic applications, as Copper being highly conductive makes it ideal for electrical applications, whilst Inconel 718 serves well as an engineering material.In this paper, we demonstrate the Coldgas Spraying (CS) of copper and the Selective Laser Melting (SLM) of Inconel 718 and Scalmalloy as the AM processes of choice for each respective material. The main distinction between both processes is that CS is useful for rapid deposition of material in the range of several kg/h whereas SLM is limited to a range of several hundred g/h. However, CS can only yield bulk structures while SLM allows the production of fine and intricate structures due to the nature of their approaches.The work presented here was performed in the framework of a research project named AdHyBau. It is funded by the German government in which several partners from industry and academia seek to jointly develop a 500 kW output power electric drive for aviation applications which employs liquid hydrogen as a propellant for a fuel cell but also for advanced cooling to obtain very high power densities in the range of above 10 kW/kg.

Ultra-broadband, high absorption, polarization-insensitive microwave absorbers designed based on multi-scale fractal metasurfaces

Microwave absorbers play an essential role in radar stealth applications. However, conventional microwave absorbers are hindered by limitations such as narrow bandwidth, large size, and inadequate absorption rates. Leveraging metasurfaces presents an ideal approach for creating microwave absorbers, but metasurface-based broadband absorbers typically entail intricate structures, natural absorbing materials, or electronic components, posing challenges in terms of fabrication and expansion. Here, we numerically demonstrate a simple multi-scale fractal metasurface microwave absorber, with the full width at half-maximum of band exceeding one optical octave. By integrating the localized surface plasmon resonance absorption band and the Salisbury-Screen-type absorption band, we achieve an average absorption of 90% ranging from 11.5 GHz to 27.1 GHz. Furthermore, this absorber exhibits excellent polarization insensitivity and maintains high absorption even at large incident angles. The device, offering both broadband absorption and a straightforward structure, holds significant promise for practical applications and widespread adoption.

Additive Manufacturing of Micro-Architected Copper based on an Ion-Exchangeable Hydrogel.

Additive manufacturing (AM) of copper through laser-based processes poses challenges, primarily attributed to the high thermal conductivity and low laser absorptivity of copper powder or wire as the feedstock. Although the use of copper salts in vat photopolymerization-based AM techniques has garnered recent attention, achieving micro-architected copper with high conductivity and density has remained elusive. In this study, we present a facile and efficient process to create complex 3D micro-architected copper structures with superior electrical conductivity and hardness. The process entails the formulation of an ion-exchangeable photoresin, followed by the utilization of digital light processing (DLP) printing to sculpt 3D hydrogel scaffolds, which were transformed into Cu2+-chelated polymer frameworks (Cu-CPFs) with a high loading of Cu2+ ions through ion exchange, followed by debinding and sintering, results in the transformation of Cu-CPFs into miniaturized copper architectures. This methodology represents an efficient pathway for the creation of intricate micro-architected 3D metal structures.

Self-assembly of peptide nanocapsules by a solvent concentration gradient.

Biological systems can create materials with intricate structures and specialized functions. In comparison, precise control of structures in human-made materials has been challenging. Here we report on insect cuticle peptides that spontaneously form nanocapsules through a single-step solvent exchange process, where the concentration gradient resulting from the mixing of water and acetone drives the localization and self-assembly of the peptides into hollow nanocapsules. The underlying driving force is found to be the intrinsic affinity of the peptides for a particular solvent concentration, while the diffusion of water and acetone creates a gradient interface that triggers peptide localization and self-assembly. This gradient-mediated self-assembly offers a transformative pathway towards simple generation of drug delivery systems based on peptide nanocapsules.