Desired Pattern Research Articles

Patterning of tissue spheroids biofabricated from human fibroblasts on the surface of electrospun polyurethane matrix using 3D bioprinter

Organ printing is a computer-aided additive biofabrication of functional three-dimensional human tissue and organ constructs according to digital model using the tissue spheroids as building blocks. The fundamental biological principle of organ printing technology is a phenomenon of tissue fusion. Closely placed tissue spheroids undergo tissue fusion driven by surface tension forces. In order to ensure tissue fusion in the course of post-printing, tissue spheroids must be placed and maintained close to each other. We report here that tissue spheroids biofabricated from primary human fibroblasts could be placed and maintained on the surface of biocompatible electrospun polyurethane matrix using 3D bioprinter according to desirable pattern. The patterned tissue spheroids attach to polyurethane matrix during several hours and became completely spread during several days. Tissue constructions biofabricated by spreading of patterned tissue spheroids on the biocompatible electrospun polyurethane matrix is a novel technological platform for 3D bioprinting of human tissue and organs.

Symmetry and Graph Bi-Regularized Non-Negative Matrix Factorization for Precise Community Detection

Community is a fundamental and highly desired pattern in a Large-scale Undirected Network (LUN). Community detection is a vital issue when LUN representation learning is performed. Owing to its good scalability and interpretability, a Symmetric and Non-negative Matrix Factorization model is frequently utilized to tackle this issue. It adopts a unique Latent Factor (LF) matrix for precisely representing LUN’s symmetry, which, unfortunately, leads to a reduced LF space that decreases its representation learning ability to a target LUN. Motivated by this discovery, this study proposes a Symmetry and Graph Bi-regularized Non-negative Matrix Factorization (B-NMF) method that: a) leverages multiple LF matrices when representing LUN, thereby boosting the representation learning ability; b) constructs a symmetry regularization term that implies the equality constraint among its multiple LF matrices, thereby illustrating LUN’s intrinsic symmetry; and c) incorporates graph regularization into its learning objective, thereby illustrating LUN’s local geometry. A theoretical proof is given to theoretically validate B-NMF’s convergence ability. The regularization hyperparameters are selected by validating model modularity, thereby guaranteeing B-NMF’s practicability in addressing real application issues. Extensive experimental results on ten LUNs from real applications demonstrate that the proposed B-NMF-based community detector significantly outperforms several baseline and state-of-the-art models in achieving highly-accurate community detection results. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —LUNs are very-commonly seen in real applications like a social network system. Communities in LUNs are vital for various knowledge discovery-related applications. For accurately detecting them, a detector should guarantee its high representation learning ability to a target LUN. To do so, this paper presents a B-NMF model that is able to perform precise representation learning to LUNs, thereby achieving accurate community detection results. In comparison with conventional Symmetric and Non-negative Matrix Factorization-based community detectors, a B-NMF-based community detector enjoys its enlarged latent feature space, which ensures its higher representation ability to a target LUN. It depends on two regularization hyperparameters, which can be selected by performing grid-search on the target LUN via its modularity evaluation. This paper gives the empirical values of B-NMF’s regularization hyperparameters based on the parametersensitivity tests on the involved experimental datasets. The proposed B-NMF model is shown to be highly suitable for addressing community detection and clustering tasks on LUNs from real applications.

Polymer Patterning by Laser-Induced Multipoint Initiation of Frontal Polymerization.

Frontal polymerization (FP) is an approach for thermosetting plastics at a lower energy cost than an autoclave. The potential to generate simultaneous propagation of multiple polymerization fronts has been discussed as an exciting possibility. However, FP initiated at more than two points simultaneously has not been demonstrated. Multipoint initiation could enable both large-scale material fabrication and unique pattern generation. Here, the authors present laser-patterned photothermal heating as a method for simultaneous initiation of FP at multiple locations in a 2-D sample. Carbon black particles are mixed into liquid resin (dicyclopentadiene) to enhance absorption of light from a Ti:sapphire laser (800 nm) focused on a sample. The laser is time-shared by rapid steering among initiation points, generating polymerization using up to seven simultaneous points of initiation. This process results in the formation of both symmetric and asymmetric seam patterns resulting from the collision of fronts. The authors also present and validate a theoretical framework for predicting the seam patterns formed by front collisions. This framework allows the design of novel patterns via an inverse solution for determining the initiation points required to form a desired pattern. Future applications of this approach could enable rapid, energy-efficient manufacturing of novel composite-like patterned materials.

Personality Trait Change Across a Major Global Stressor.

The current research examined three related questions in a 21-month longitudinal study of a diverse sample of U.S. participants (N = 504): (a) How did Big Five traits change during the COVID-19 pandemic? (b) What factors were associated with individual differences in trait change? and (c) How was Big Five trait change associated with downstream well-being, mental health, and physical health? On average, across the 21-month study period, conscientiousness increased slightly, and extraversion decreased slightly. Individual trajectories varied around these average trajectories, and although few factors predicted these individual differences, greater increases in conscientiousness, extraversion, and agreeableness, and greater decreases in neuroticism were associated better well-being and fewer mental and physical health symptoms. The present research provides evidence that traits can change in the context of a major global stressor and that socially desirable patterns of trait change are associated with better health.

A rapid and automated computational approach to the design of multistable soft actuators

We develop an automated computational modeling framework for rapid gradient-based design of multistable soft mechanical structures composed of non-identical bistable unit cells with appropriate geometric parameterization. This framework includes a custom isogeometric analysis-based continuum mechanics solver that is robust and end-to-end differentiable, which enables geometric and material optimization to achieve a desired multistability pattern. We apply this numerical modeling approach in two dimensions to design a variety of multistable structures, accounting for various geometric and material constraints. Our framework demonstrates consistent agreement with experimental results, and robust performance in designing for multistability, which facilities soft actuator design with high precision and reliability.

On-Demand Tunable Electrical Conductance Anisotropy in a MOF-Polymer Composite.

Property optimization through orientation control of metal-organic framework (MOF) crystals that exhibit anisotropic crystal structures continues to garner tremendous interest. Herein, an electric field is utilized to post-synthetically control the orientation of conductive layered Cu3(HHTP)2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) crystals dispersed in an electronically insulating poly(ethylene glycol) diacrylate (PEGDA) oligomer matrix. Optical and electrical measurements areperformed to investigate the impact of the electric field on the alignment of Cu3(HHTP)2 crystals and the formation of aggregated microstructures, which leads to an ≈5000-fold increase in the conductivity of the composite. Notably, the composite thin-films containing aligned Cu3(HHTP)2 crystals exhibit significant conductivity of ≈10-3Scm-1 despite the low concentration (≈1wt.%) of conductive Cu3(HHTP)2. The use of an electric field to align Cu3(HHTP)2 crystals can rapidly generate various desired patterns that exhibit on-demand tunable collective charge transport anisotropy. The findings provide valuable insights toward the manipulation and utilization of conductive MOFs with anisotropic crystal structures for various applications such as adhesive electrical interconnects and microelectronics.

Elucidating Diurnal Patterns in Touch Desire Using Social Media Data Toward Design of Haptic Applications and Displays.

Advances in haptic technology have led researchers and engineers to seek out killer applications in which users can enjoy an experience of touch in AR/VR spaces. Such applications will respond appropriately to human desire for haptic experiences (i.e., touch desire) and thus it is essential for researchers and engineers to understand the nature of people's touch desires as they arise in the course of daily life. In this study, we employed Twitter data analysis to investigate a diurnal pattern in touch desire. Our results showed that touch desire identified in and extracted from Twitter texts did reveal a diurnal pattern. Touch desire tended to be at its lowest in the morning and increased as the day progressed. The time at which it peaked varied with the specific target of touch desire. Touch desire in relation to other people and objects reached its peak at night, but touch desire in relation to animals reached its peak at noon. These results were confirmed not only by our Twitter text analysis but also by data from other social media and an online survey. In addition, we found that the diurnal pattern of touch desire for each target shows a strong correlation with that of visual desire for the same target. This suggests that the diurnal pattern of touch desire is not limited to the sense of touch but is common to other sensory desires for each target. Our findings suggest that researchers need to take the time of day into account when investigating touch desire. Our findings also offer valuable insights for developers into the design of haptic applications and displays that takes into account the timing of daily peaks in touch desire.

USULAN PERBAIKAN LAYOUT LANTAI PRODUKSI PT XYZ MENGGUNAKAN METODE ALGORITMA BLOCPLAN DAN ALGORITMA CORELAP

PT XYZ is a company that engaged in the footwear manufacturing industry. In the production process, one of tool that required is cutting dies to form the desired designs or patterns. The production process that uses cutting dies is carried out in the moldshop section. Cutting dies are made from sheet plates that are cut to size, then processed to form a pattern or design that will be used in the main production section. Several departments were placed not in accordance with the production process flow, causing delays in the delivery of cutting dies. This also causes longer material handling time and there is irregular material flow such as cross material flow and alternating flow which also results in queuing processes. For this problem, it is necessary to design a layout to produce a shorter total distance and better production flow using the BLOCPLAN Algorithm and CORELAP Algorithm methods. From the design results, the proposed layout of the BLOCPLAN Algorithm was obtained which was able to produce a total distance of 2385.5 meters per day, whereas if using the CORELAP Algorithm it was 1514.63 meters per day. Therefore, it is recommended to use the layout from the CORELAP Algorithm calculation so that it can produce an efficiency of 20.60%.

Core-shell structured tow-pregs enabled additive manufacturing of continuously reinforced thermoset composites

One of the major challenges in thermally curable polymer composite additive manufacturing is the slow curing time of thermally curable resins, coupled with a significant drop in thermoset viscosity upon heating, making the formation of complex shapes difficult. To tackle these issues, we have introduced a novel rapid composite preformation strategy called Tow-Preg Cladding (TPC). This technique involves the use of a thin and rapidly curable dual-cure resin, which combines a thermally curable resin (such as epoxy) with a fast photo-curable resin. The dual-cure resin is applied as a coating over a thermally curable resin tow-preg, enabling the formation of a rigid cladding that supports and shapes the tow-pregs into the desired geometries and patterns. The key advantage of this approach lies in the sequential formation of an interpenetrating polymer network (IPN) at the interlayer between laminates, resulting from the curing of the photocurable resin and the thermally curable resin sequentially. This IPN formation enhances interlaminar bonding in the composite, contributing to its overall strength and performance. The composites produced using this technique exhibited impressive mechanical properties, including longitudinal tensile strength of 1058.2 MPa, longitudinal tensile modulus of 74.2 GPa, flexural strength of 1080.4 MPa, and flexural modulus of 41.7 GPa. Overall, our Tow-Preg Cladding approach shows great promise in overcoming the challenges associated with thermally curable polymer composite additive manufacturing. It offers a viable solution to creating strong, shape-specific thermoset composites efficiently with enhanced mechanical properties.

Finite-time robust formation control of multiple aerial robotic vehicles with uncertainties and time-varying complex perturbations

Formation control of aerial robotic vehicles (ARVs) has a wide range of applications in the battlefield reconnaissance, medical rescue and load transportation, etc. System parameter variations and complex disturbances are inevitable in the formation control of ARVs, and the effects of them on the formation stability control of ARVs are unnegligible. This paper addresses the robust formation control problem of finite-time leader–follower for multiple ARVs suffering from parameter uncertainties and time-varying perturbations. To ensure the states (e.g. position and velocity) of all followers to converge to leader in finite time, a novel finite-time high-order sliding mode consensus control (HOSMCC) scheme is designed. To better cope with the parameter uncertainties and time-varying disturbances, improve formation control accuracy and achieve the robust formation control of finite-time leader–follower in multiple ARV systems, a new finite time high-order sliding mode formation control (HOSMFC) scheme on the basis of finite-time HOSMCC is proposed. The finite-time stability of multi-ARV formation control system is guaranteed, and the desired formation pattern of multi-ARV systems is achieved using Lyapunov stability theorem. Performance comparisons with proportional differential formation controller (PDFC) and sliding mode formation controller (SMFC) are studied on a four-ARV formation control system. The results validate the designed formation control scheme.

Saturated formation containment control for a heterogeneous multi-agent system with unknown perturbations

This work addresses formation containment control for a heterogeneous multi-agent system composed of first-order (FO) and second-order (SO) agents that can be either leader or follower agents. It is assumed that unknown but bounded disturbances perturb its dynamical model. An error-based version of a generalized proportional–integral observer (GPIO) is proposed to estimate these perturbations, and saturation functions, based on position measurement and estimated velocity errors, are designed to achieve the control objective. Specifically, it is shown that the leader agents converge to a desired geometric pattern following a desired trajectory simultaneously. Furthermore, the follower agents converge to the convex hull spanned by the leaders. The result applies to a group of robots in which a directed spanning tree gives the communication topology among the leaders with a root in the main leader. At the same time, each follower receives information from at least one leader agent, and the communication is directed. Real-time experiments and a comparison with a robust control technique exhibit the excellent performance of the proposed GPIO and control strategy in achieving formation containment control.

A single immunization with core–shell structured lipopolyplex mRNA vaccine against rabies induces potent humoral immunity in mice and dogs

ABSTRACT The persistence and clinical consequences of rabies virus (RABV) infection have prompted global efforts to develop a safe and effective vaccines against rabies. mRNA vaccines represent a promising option against emerging and re-emerging infectious diseases, gaining particular interest since the outbreak of COVID-19. Herein, we report the development of a highly efficacious rabies mRNA vaccine composed of sequence-modified mRNA encoding RABV glycoprotein (RABV-G) packaged in core–shell structured lipopolyplex (LPP) nanoparticles, named LPP-mRNA-G. The bilayer structure of LPP improves protection and delivery of RABV-G mRNA and allows gradual release of mRNA molecules as the polymer degrades. The unique core–shell structured nanoparticle of LPP-mRNA-G facilitates vaccine uptake and demonstrates a desirable biodistribution pattern with low liver targeting upon intramuscular immunization. Single administration of low-dose LPP-mRNA-G in mice elicited potent humoral immune response and provided complete protection against intracerebral challenge with lethal RABV. Similarly, single immunization of low-dose LPP-mRNA-G induced high levels of virus-neutralizing antibody titers in dogs. Collectively, our data demonstrate the potential of LPP-mRNA-G as a promising next-generation rabies vaccine used in human and companion animals.

Plasmonic vortex beam emitter

Terahertz vortices prompt numerous advanced applications spanning classical and quantum communications, sensing, and chirality-based detection, owing to the inherent physical properties of terahertz waves and orbital angular momentum (OAM). Nonetheless, existing methodologies for generating terahertz vortices face challenges such as unalterable topological charges and intricate feed networks. To address these limitations, we propose a novel approach to generate multi-mode and tunable vortex beams based on chiral plasmons. Through eigenmode analysis, the uniform helical gratings are demonstrated to support chiral plasmons carrying OAM. By leveraging their vortex characteristics and introducing modulation into the periodic system, these chiral plasmons are alternatively diffracted into high-purity vortex radiations according to the Bragg law. To validate the theory, the vortex beam emitter is fabricated and measured in the microwave regime based on the modulated scheme. Experimental results confirm the emission of vortex beams with desirable phase distributions and radiation patterns. Our findings highlight the potential of chiral plasmons as seeds for tunable and compact vortex radiation, offering promising applications in tunable vortex sources.

How does urban landscape pattern affect ecosystem health? Insights from a spatiotemporal analysis of 212 major cities in China

Healthy ecosystems are the foundation of sustainable urbanization. While scientists have long understood the ecological benefits of healthy landscapes, there is still limited understanding of how urban landscape patterns affect ecosystem health. To fill this gap, we systematically investigated the spatiotemporal relationships between different urban landscape patterns and ecosystem health in 212 major cities in China from 2000 to 2020 using Geographically and Temporally Weighted Regression. Results show that cities with poor ecosystem health are mainly concentrated in central-eastern China and show a long-term trend of degradation. There is spatial and temporal variability in how landscape patterns drive ecosystem health changes. The size, density, and perimeter of urban patches, along with the degree of interspersion between urban land covers with other land covers, are more important for ecosystem health than other spatial pattern measures, but these patterns also have greater temporal variation. Over the past two decades, the negative impacts of urban area growth have diminished in cities in lower-lying plains areas, but remain a major cause of local ecological degradation. The ecological health of mountain cities is more sensitive to changes in the shape and spatial arrangement of urban patches because of the intertwined distribution of natural ecosystems and urban land that often characterize these cities. This work not only confirms the advantages of spatiotemporal analytical thinking in the study of driving mechanisms of ecosystem health but also provides important guidelines for creating desirable landscape patterns for sustainable urban development.

Spherical formation control of mobile target by multi-agent systems with collision avoidance: A limit-cycle-based design approach

This paper focuses on the control of spherical formation for multi-agent systems with double-integrator dynamics in three-dimensional space. To achieve the desired formation pattern on a spherical surface, N agents must be distributed evenly around a target. Based on the information gathered about the target and its immediate neighbors, all agents can either remain stationary or rotate around the target at the same velocity on a spherical surface while the target moves in three-dimensional space. A decoupled control method with limit cycle oscillator characteristics is explored to achieve the desired formation geometric pattern. Accordingly, three subproblems are proposed to achieve the spherical formation more effectively. The first subproblem, target-spherical-surface, requires the agents to converge on a specified spherical surface with the target as its center. The second subproblem, target-circling, requires the agents to follow three prescribed orthometric circular orbits on the spherical surface to avoid collisions while moving. The final subproblem is distributed-adjustment, which involves agents to maintaining a prescribed angular distance from their immediate neighbors while remaining relatively stationary or rotating around the target. By addressing the first two sub-problems simultaneously, the agents can be guided to the desired position. The properties of the limit-cycle-based spherical formation controller are analyzed theoretically, and its effectiveness is demonstrated through numerical simulations.

Contributed Session I: Towards General Video Percepts Cone-by-Cone.

We aim to reprogram visual perception through an Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO) Display, using a GPU renderer that rasterizes a target color image or video into cone-by-cone single-wavelength laser light pulses ("microdoses"). We imaged and tracked at ~ 2° eccentricity a 0.9° x 0.9° field of view of the retina in 840 nm. Stimulated in 543 nm, all resolved, spectrally classified cones receive microdoses of varying intensities. The renderer updates for each AOSLO frame (30 frames / sec) an underlying stimulation image buffer, encoding a desired color percept pattern that takes into account the cone locations, cone spectral sensitivity to the 543 nm stimulation light, and the corresponding color percept pixel values. Within one frame, the buffer gets pixelated strip-by-strip at 1 kHz into actual world-fixed microdose intensity values, each centered on a cone within that strip at that instant. The resulting frame of microdoses visually occupies the whole raster view. We showed multiple color percepts to a cone-classified subject, with logging data. The subject saw spatially-varying colors, e.g. a red box moving on a green canvas - these percepts validated the accuracy of the prototype. These initial prototyping experiments allude to the potential of presenting general percepts to a cone-classified subject, at cone-level accuracy in a fully programmable way. The technology allows us to probe neural plasticity and towards generation of novel percepts.

The effect of the spatial variation of the evaporative flux on the deposition from a thin sessile droplet

A mathematical model for the effect of the spatial variation of the local evaporative flux on the evaporation of and deposition from a thin pinned particle-laden sessile droplet is formulated and solved. We then analyse the behaviour for a one-parameter family of local evaporative fluxes with the free parameter $n \, (&gt;-1)$ that exhibits qualitatively different behaviours mimicking those that can be obtained by, for example, surrounding the droplet with a bath of fluid or using a mask with one or more holes in it to achieve a desired pattern of evaporation enhancement and/or suppression. We show that when $-1&lt; n&lt;1$ (including the special cases $n=-1/2$ of diffusion-limited evaporation into an unbounded atmosphere and $n=0$ of spatially uniform evaporation), all of the particles are eventually advected to the contact line, and so the final deposit is a ring deposit at the contact line, whereas when $n&gt;1$ all of the particles are eventually advected to the centre of the droplet, and so the final deposit is at the centre of the droplet. In particular, the present work demonstrates that a singular (or even a non-zero) evaporative flux at the contact line is not an essential requirement for the formation of a ring deposit. In addition, we calculate the paths of the particles when diffusion is slower than both axial and radial advection, and show that in this regime all of the particles are captured by the descending free surface before eventually being deposited onto the substrate.

Edge-Weighted Consensus-Based Formation Control with Collision Avoidance for Mobile Robots Based on Multi-Strategy Mutation Differential Evolution

An edge-weighted consensus-based formation control strategy is presented for mobile robots. In the edge-weighted strategy, a desired formation pattern is achieved by adjusting gain weights related to the distance between robots. Moreover, the edge-weighted formation control exploits the properties of weighted graphs to allow the formation to rotate and adapt its shape to avoid collision among robots. However, formation patterns are commonly defined by biases with respect to the centroid of the consensus rather than gain weights. This work proposes to optimize the gain weights in edge-weighted graphs, given a formation pattern in terms of biases. A multi-strategy mutation differential evolution algorithm is introduced to solve the optimization problem. Simulation and real-world experiments are performed considering multi-robot systems composed of differential drive robots. Additionally, the experimental setup includes Turtlebot3® Waffle Pi robots and an OptiTrack® motion capture system for control purposes. The experimental results verify the effectiveness of the proposed approach.

Microbeam X-ray Reanalysis on Periodically Assembled Poly(β-Hydroxybutyric acid-Co-β-hydroxyvaleric acid) Tailored with Diluents.

Self-assembly of 3D interiors and iridescence properties of poly(β-hydroxybutyric acid-co-β-hydroxyvaleric acid) (PHBV) periodic crystals are examined using microcopy techniques and microbeam X-ray diffraction. Morphology of PHBV can be tailored by crystallizing in presence of poly(vinyl acetate) (PVAc) or poly(trimethylene adipate) (PTA) for displaying desired periodicity patterns. The regular alternate-layered lamellae of banded PHBV crystal aggregates, resembling the structures the natural mineral moonstone or nacre, are examined to elaborate the origin of light interference and formation mechanisms of periodic lamellar aggregation of PHBV spherulites. By using PHBV as a convenient model and the crystal diffraction data, this continuing work demonstrates unique methodology for effectively studying the periodic assembly in widely varying polymers with similar aggregates. Grating structures in periodically assembled polymer crystals can be tailored for microstructure with orderly periodicity.

Porphyrin-Based MOF Thin Film on Transparent Conducting Oxide: Investigation of Growth, Porosity and Photoelectrochemical Properties.

Synthesizing metal-organic frameworks (MOFs) composites with a controlled morphology is an important requirement to access materials of desired patterning and composition. Since the last decade, MOF growth from sacrificial metal oxide layer is increasingly developed as it represents an efficient pathway to functionalize a large number of substrates. In this study, porphyrin-based Al-PMOF thin films were grown on conductive transparent oxide substrates from sacrificial layers of ALD-deposited alumina oxide. The control of the solvent composition and the number of atomic layer deposition (ALD) cycles allow us to tune the crystallinity, morphology and thickness of the produced thin films. Photophysical studies evidence that Al-PMOF thin films present light absorption and emission properties governed by the porphyrinic linker, without any quenching upon increasing the film thickness. Al-PMOF thin films obtained through this methodology present a remarkably high optical quality both in terms of transparency and coverage. The porosity of the samples is demonstrated by ellipsometry and used for Zn(II) insertion inside the MOF thin film. The multifunctional transparent, porous and luminescent thin film grown on fluorine-doped tin oxide (FTO) is used as an electrode capable of photoinduced charge separation upon simulated sunlight irradiation.