Active Shape Research Articles

Influence of the COIL methodology on the development of intercultural competence and sustainability in Latin American business students

Purpose This study aims to investigate the impact of an collaborative online international learning (COIL) program on student behavioral satisfaction and community engagement, with a focus on diversity and sustainability. Explore how these changes affect students’ perceptions of the impact of these activities and their motivation to use sustainable practices in their future careers. Design/methodology/approach A combination of research methods combining qualitative and quantitative methods was adopted. Quantitative data were collected through satisfaction surveys that included Likert scale to measure various aspects of the COIL experience. Qualitative data were obtained from students’ open statements and semi-structured interviews. Analysis uses statistical and literary techniques to identify key themes and patterns in the student’s understanding. Findings Results showed overall high student satisfaction with COIL’s activities; this highlighted the positive impact of multicultural leadership and integrating sustainability into the business. Statistical analysis revealed a positive relationship between the relationship quality created by COIL and the perception of safety-related factors. In addition, students have the desire to apply the principles they have learned in their future work. Originality/value This study contributes to the understanding of sustainability education within COIL by examining three critical dimensions: the promotion of sustainable practices in future professional environments, the development of sustainability competencies and the impact of sustainability topics on students’ perceived relationship quality and safety within collaborative international projects. Through this lens, the author investigates how COIL-based activities shape students’ commitment to sustainable practices, enhancing their intercultural competence and readiness for a globalized workforce.

Ethylene vinyl acetate/copper sulphide with near-infrared light active shape memory behavior

This thesis presents the preparation of ethylene vinyl acetate (EVA)-based shape memory polymer composites (SMPC) (EVA/CuS) with near-infrared light photo-thermal response. The composites were prepared using EVA as the matrix material and copper sulphide (CuS) particles as the functional phase. The designability of SMPs was considered in the preparation of these composites. The results demonstrated that the incorporation of CuS, as a functional phase, enhanced the cross-linking degree and augmented the shape memory properties of EVA. Additionally, it served as a photo-thermal functional filler, imparting its photo-thermal properties. It can be observed that as the quantity of CuS particles incorporated into the EVA/CuS composite film increases, the photothermal conversion performance of the composite film improves, the shape fixation rate rises, and the rate of recovery of light-responsive shape memory accelerates. The temperature of the composites increased to 116.7°C in 20 s when the CuS addition was 2 wt% and the NIR light intensity was 0.5 W/cm2. At a NIR light intensity of 0.6 W/cm2, the “U” shape of the sample was restored to a straight state in 30 s, and the shape recovery rate reached 100%. In this experiment, optical near-infrared photostimulation-responsive EVA/CuS composites have been successfully prepared. These composites demonstrate the ability to achieve remote control and fast response of EVA shape memory behavior, offering a new avenue for the preparation of photo-responsive EVA-based shape memory materials.

High-fidelity metasurface holography illuminated by ultra-uniform flat-top beam generated through active wavefront shaping

High-fidelity metasurface holography illuminated by ultra-uniform flat-top beam generated through active wavefront shaping

Neural Circuit Remodeling: Mechanistic Insights from Invertebrates.

As nervous systems mature, neural circuit connections are reorganized to optimize the performance of specific functions in adults. This reorganization of connections is achieved through a remarkably conserved phase of developmental circuit remodeling that engages neuron-intrinsic and neuron-extrinsic molecular mechanisms to establish mature circuitry. Abnormalities in circuit remodeling and maturation are broadly linked with a variety of neurodevelopmental disorders, including autism spectrum disorders and schizophrenia. Here, we aim to provide an overview of recent advances in our understanding of the molecular processes that govern neural circuit remodeling and maturation. In particular, we focus on intriguing mechanistic insights gained from invertebrate systems, such as the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster. We discuss how transcriptional control mechanisms, synaptic activity, and glial engulfment shape specific aspects of circuit remodeling in worms and flies. Finally, we highlight mechanistic parallels across invertebrate and mammalian systems, and prospects for further advances in each.

Significance of magnetic field and Darcy–Forchheimer law on dynamics of non-Newtonian hybrid nanofluid flow over a spinning disc with Arrhenius activation energy and shape factor

Purpose The purpose of the study is to explore the three-dimensional heat and mass transport dynamics of the magneto-hydrodynamic non-Newtonian (Casson fluid) hybrid nanofluid flow comprised of − as nanoparticles suspended in base liquid water as it passes through a flexible spinning disc. The influence of a magnetic field, rotation parameter, porosity, Darcy−Forchheimer, Arrhenius’s activation energy, chemical reaction, Schmidt number and nanoparticle shape effects are substantial physical features of the investigation. Furthermore, the influence of hybrid nanofluid on Brownian motion and thermophoresis features has been represented using the Buongiorno model. The novelty of the work is intended to contribute to a better understanding of Casson non-Newtonian fluid boundary layer flow. Design/methodology/approach The governing mathematical equations that explain the flow and heat and mass transport phenomena for fluid domains include the Navier−Stokes equation, the thermal energy equation and the solutal concentration equations. The governing equations are expressed as partial differential equations, which are then converted into a suitable set of non-linear ordinary differential equations by using the necessary similarity variables. The ordinary differential equations are computed by combining the shooting operation with the three-stage Lobatto BVP4c technique. Findings Graphs and tables are used in the process of analysing the characteristics of velocity distributions, temperature profiles and solutal curves at varying values of the parameters, along with friction drag, heat transfer rate and Sherwood number. It has been revealed that the radial and axial velocities decrease when the Casson parameter value increases and that the rate of heat transmission is higher in hybrid nanofluids with nanoparticles in the shape of a blade. The increase in Brownian motion and thermophoresis parameters causes a rise in the temperature profile. Also, an increase in the activation energy parameter improves the solutal curve. The use of nanoparticles was shown to improve extrusion properties, the rotary heat process and biofuel generation. Originality/value All results are presented graphically and all physical quantities are computed and tabulated. The current results are compared to previous investigations and found to agree significantly with them.

Gain-Based Feedback for Shape Control of Antenna Reflectors Using Deep Q-Network Algorithm

An intelligent shape control method for antenna reflectors is proposed using gain feedback instead of displacement feedback, considering the limitations of high-precision deformation measurement on orbit. Moreover, the finite element method is used to establish an analysis model of a grid reflector with embedded piezoelectric actuators, and the antenna gain formula is derived. To solve the multidimensional control laws from a single gain dimension, an active shape control model training framework is proposed based on the deep Q-network algorithm, including the state space, action space, and reward function. Numerical simulations, with errors stemming from two typical thermal loads as the initial errors, are conducted to illustrate the effect of the proposed control method. The influence of the voltage step size on the shape control precision is analyzed, and further online training is discussed for implementing control. The results indicate that the proposed method reduces the root-mean-square (RMS) error by more than 50% The control effect of the trained control model on other error conditions does not perform as desired. However, online training can effectively solve this problem, achieving faster convergence and a significant reduction of the RMS error.

Monocular Pose and Shape Reconstruction of Vehicles in UAV imagery using a Multi-task CNN

Estimating the pose and shape of vehicles from aerial images is an important, yet challenging task. While there are many existing approaches that use stereo images from street-level perspectives to reconstruct objects in 3D, the majority of aerial configurations used for purposes like traffic surveillance are limited to monocular images. Addressing this challenge, a Convolutional Neural Network-based method is presented in this paper, which jointly performs detection, pose, type and 3D shape estimation for vehicles observed in monocular UAV imagery. For this purpose, a robust 3D object model is used following the concept of an Active Shape Model. In addition, different variants of loss functions for learning 3D shape estimation are presented, focusing on the height component, which is particularly challenging to estimate from monocular near-nadir images. We also introduce a UAV-based dataset to evaluate our model in addition to an augmented version of the publicly available Hessigheim benchmark dataset. Our method yields promising results in pose and shape estimation: utilising images with a ground sampling distance (GSD) of 3 cm, it achieves median errors of up to 4 cm in position and 3° in orientation. Additionally, it achieves root mean square (RMS) errors of \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pm 6$$\\end{document} cm in planimetry and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pm 18$$\\end{document} cm in height for keypoints defining the car shape.

Strategic Enhancement and Differential Governance: China’s Partnership Diplomacy in Latin America

This paper studies China’s partnership diplomacy and its practice in Latin America and the Caribbean (LAC). China has constructed an all-round, multi-level, and three-dimensional partnership network in LAC through three stages: strategic exploration, development, and improvement. China has implemented differential governance towards its partners, which enables active shaping and dynamic management of the partnership network. This paper categorizes the 15 partner countries into three types: pivot countries, link countries, and node countries based on their political friendliness with China, geopolitical influence, and potential for economic and trade cooperation. China’s partnerships in LAC are vital support for implementing its diplomatic strategy in the region. However, challenges to this strategy’s development include insufficient mutual support from other diplomatic means, doubts and misinterpretations of the China-Latin America partnership by some Latin American countries, and the political and identity shifts within these countries. To enhance the role of partnerships in maintaining state relations and promoting the implementation of diplomatic strategies, China has introduced new content to its partnership diplomacy in LAC.

From impression to expression: How warmth and competence in relaxing and challenging activities shape pleasure and eWOM

AbstractThis research investigates how aligning service providers' warmth and competence with the nature of leisure activities (relaxing vs. challenging) influences pleasure and electronic word‐of‐mouth (eWOM) sharing. Through a series of five studies, including secondary data analysis (Study 1), scenario‐based experiments (Studies 2a, 3, 4, and 5), and observation of actual eWOM behavior (Study 2b), we demonstrate that the alignment between service judgments and activity type (i.e., warmth in relaxing activities and competence in challenging activities) enhances positive eWOM sharing, with this effect being mediated by the pleasure derived from the service experience. Our findings contribute to the theoretical understanding of the cognitive and affective antecedents of eWOM. We extend the stereotype content model to the eWOM research, identifying activity type as a novel boundary condition. We recommend that managers tailor their impression management strategies to the type of activity offered. For relaxing activities, emphasize warmth‐related attributes, while for challenging activities, highlight competence‐related attributes—both approaches can enhance customer pleasure and encourage positive eWOM sharing.

Plateau zokor disturbance enhances soil bacterial diversity and reduces network complexity

Rodent disturbances are considered as the key factors that affect grassland ecological restoration worldwide. Although the impact of rodent disturbances on plant diversity and ecosystem functions has been extensively studied, our understanding of how such activities shape soil bacterial community networks and their functional roles remains limited. In this study, we employed 16S rRNA sequencing to investigate soil bacterial communities between undisturbed alpine meadow and zokor mounds at different successional stages. Additionally, we analyzed the co-occurrence networks and potential functions within the alpine meadow ecosystem. The results revealed that (1) the disturbance by plateau zokors altered the soil bacterial community structure, increased bacterial diversity and reduced network complexity. Also, there were synergistic interactions among key species in the soil bacterial co-occurrence network; (2) soil organic carbon (SOC) and total nitrogen (TN) were identified as the key environmental variables that shape soil bacterial communities; (3) functional predictions based on FAPROTAX indicated that the disturbance by plateau zokors significantly affected the functional groups involved in carbon (C) and nitrogen (N) cycling. Overall, these findings significantly enhance our understanding of how small mammal activities influence the soil nutrient cycling and bacterial community in the Qinghai-Tibet Plateau (QTP) alpine meadow.

Active shape programming drives Drosophila wing disc eversion.

How complex 3D tissue shape emerges during animal development remains an important open question in biology and biophysics. Here, we discover a mechanism for 3D epithelial shape change based on active, in-plane cellular events that is analogous to inanimate "shape programmable" materials, which undergo blueprinted 3D shape transformations from in-plane gradients of spontaneous strains. We study eversion of the Drosophila wing disc pouch, when the epithelium transforms from a dome into a curved fold, quantifying 3D tissue shape changes and mapping spatial patterns of cellular behaviors on the evolving geometry using cellular topology. Using a physical model inspired by shape programming, we find that active cell rearrangements are the major contributor to pouch eversion and validate this conclusion using a knockdown of MyoVI, which reduces rearrangements and disrupts morphogenesis. This work shows that shape programming is a mechanism for animal tissue morphogenesis and suggests that patterns in nature could present design strategies for shape-programmable materials.

Larvicidal, bactericidal, antioxidant, hypoglycemic effects and anti-proliferative activity of phyto-synthesized Ag-ZnO nanocomposites using Eranthemum roseum (Vahl) R.Br. leaf extract against Aedes aegypti and Culex quinquefasciatus mosquito vectors

This research is conducted using zinc doped silver nanocomposite on Eranthemum roseum leaf extract. E. roseum has its own medicinal properties due its bioactive compounds. Silver and Zinc also has its own medicinal properties due to its microbial properties. Our work is aimed to combine nanoparticles with plant extract to explore the medicinal properties. The synthesized Ag-ZnO NCs is characterized using X-ray powder diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDAX) and Transmission Electron Microscopy (TEM) analysis. The XRD analysis confirms the crystal nature of the Ag-ZnO NCs. The average shape of the nanocomposite was obtained using SEM as spherical, EDAX analysis confirming the presence of Ag, Zn and Oxygen and TEM conforms the oval shape of nanoparticles Antibacterial activity shows highest level of activity against K. pneumoniae and B. subtilis. DPPH Activity of Ag-ZnO NCs highest inhibition of 52.56 % while the ABTS analysis of Ag-ZnO NCs shows 54.28 %. Hypoglycemic activity α-amylase and α- glucosidase assay of Ag-ZnO NCs obtained good activity with maximum level of inhibition 63 % and 60 %. Anti-proliferative assay shows good activity against cancer causing cells in HepG2 human liver cancer line with 67.11 %. Larvicidal potential of Ag-ZnO NCs recorded good mortality rate against Aedes aegypti and Culex quinquefasciatus. This study confirms the maximum activity of Ag-ZnO NCs and acts as Larvicidal, Anti-proliferative, Antioxidant, Hypoglycemic agents.

Hybrid dynamical modeling of shape memory alloy actuators with phase kinetic equations

Shape memory alloy morphing actuators are a type of composite soft actuator with many attractive properties such as large deformation, small form factor, self-sensing ability, and physical reservoir computing potential. These actuators are composed of active shape memory alloy wires and a passive material to magnify the overall deflection. However, the dynamic modeling of these actuators is difficult due to both shape memory alloy characteristics and the nonlinearity of the passive layer. Here, a hybrid dynamical model is proposed that couples the phase kinetics and thermal modeling for the shape memory alloy with a dynamic Cosserat beam model. This hybrid model is benchmarked against experimental linear and morphing actuators resulting in a root mean squared error of 0.87 mm for the linear actuator and root mean squared error of 1.34 and 1.42 mm for the two morphing actuator configurations evaluated in this work. This model applies continuous phase kinetic equations in a comprehensive hybrid dynamical model to accurately simulate the hysteretic transition of the alloy, which is then coupled to a high deformation beam model. This work can expand the capability and design of novel morphing actuators to achieve specified dynamic characteristics for increased application in robotic fields.

Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images.

Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the position and identifying the morphological features of the vertebrae. However, detection errors may occur owing to the noise and ambiguity of images, as well as individual variations in the shape of the lumbar vertebrae. This study proposes a method to improve the robustness of landmark detection results. This method assumes that landmarks are detected by a convolutional neural network-based two-step model consisting of Pose-Net and M-Net. The model generates a heatmap response to indicate the probable landmark positions. The proposed method then corrects the landmark positions using the heatmap response and active shape model, which employs statistical information on the landmark distribution. Experiments were conducted using 3600 lumbar X-ray images, and the results showed that the landmark detection error was reduced by the proposed method. The average value of maximum errors decreased by 5.58% after applying the proposed method, which combines the outstanding image analysis capabilities of deep learning with statistical shape constraints on landmark distribution. The proposed method could also be easily integrated with other techniques to increase the robustness of landmark detection results such as CoordConv layers and non-directional part affinity field. This resulted in a further enhancement in the landmark detection performance. These advantages can improve the reliability of automatic systems used to inspect lumbar X-ray images. This will benefit both patients and medical staff by reducing medical expenses and increasing diagnostic efficiency.

Closed-loop active shape control of radial rib in umbrella antenna based on fiber-optic shape sensing

Closed-loop active shape control of radial rib in umbrella antenna based on fiber-optic shape sensing

Streams of conscious visual experience

Consciousness, a cornerstone of human cognition, is believed to arise from complex neural interactions. Traditional views have focused on localized fronto-parietal networks or broader inter-regional dynamics. In our study, we leverage advanced fMRI techniques, including the novel Functionnectome framework, to unravel the intricate relationship between brain circuits and functional activity shaping visual consciousness. Our findings underscore the importance of the superior longitudinal fasciculus within the fronto-parietal fibers, linking conscious perception with spatial neglect. Additionally, our data reveal the critical contribution of the temporo-parietal fibers and the splenium of the corpus callosum in connecting visual information with conscious representation and their verbalization. Central to these networks is the thalamus, posited as a conductor in synchronizing these interactive processes. Contrasting traditional fMRI analyses with the Functionnectome approach, our results emphasize the important explanatory power of interactive mechanisms over localized activations for visual consciousness. This research paves the way for a comprehensive understanding of consciousness, highlighting the complex network of neural connections that lead to awareness.

Neural activity shaping in visual prostheses with deep learning

Objective. The visual perception provided by retinal prostheses is limited by the overlapping current spread of adjacent electrodes. This reduces the spatial resolution attainable with unipolar stimulation. Conversely, simultaneous multipolar stimulation guided by the measured neural responses—neural activity shaping (NAS)—can attenuate excessive spread of excitation allowing for more precise control over the pattern of neural activation. However, defining effective multipolar stimulus patterns is a challenging task. Previous attempts focused on analytical solutions based on an assumed linear nonlinear model of retinal response; an analytical model inversion (AMI) approach. Here, we propose a model-free solution for NAS, using artificial neural networks (ANNs) that could be trained with data acquired from the implant. Approach. Our method consists of two ANNs trained sequentially. The measurement predictor network (MPN) is trained on data from the implant and is used to predict how the retina responds to multipolar stimulation. The stimulus generator network is trained on a large dataset of natural images and uses the trained MPN to determine efficient multipolar stimulus patterns by learning its inverse model. We validate our method in silico using a realistic model of retinal response to multipolar stimulation. Main results. We show that our ANN-based NAS approach produces sharper retinal activations than the conventional unipolar stimulation strategy. As a theoretical bench-mark of optimal NAS results, we implemented AMI stimulation by inverting the model used to simulate the retina. Our ANN strategy produced equivalent results to AMI, while not being restricted to any specific type of retina model and being three orders of magnitude more computationally efficient. Significance. Our novel protocol provides a method for efficient and personalized retinal stimulation, which may improve the visual experience and quality of life of retinal prosthesis users.

Active shape control by plants in dynamic environments.

Plants are a paradigm for active shape control in response to stimuli. For instance, it is well known that a tilted plant will eventually straighten vertically, demonstrating the influence of both an external stimulus, gravity, and an internal stimulus, proprioception. These effects can be modulated when a potted plant is additionally rotated along the plant's axis, as in a rotating clinostat, leading to intricate shapes. We use a previously derived rod model to study the response of a growing plant and the joint effects of both stimuli at all rotation speeds. In the absence of rotation, we identify a universal planar shape towards which all shoots eventually converge. With rotation, we demonstrate the existence of a stable family of three-dimensional dynamic equilibria where the plant axis is fixed in space. Further, the effect of axial growth is to induce steady behaviors, such as solitary waves. Overall, this study offers insight into the complex out-of-equilibrium dynamics of a plant in three dimensions and further establishes that internal stimuli in active materials are key for robust shape control.

Retinal waves in adaptive rewiring networks orchestrate convergence and divergence in the visual system.

Spontaneous retinal wave activity shaping the visual system is a complex neurodevelopmental phenomenon. Retinal ganglion cells are the hubs through which activity diverges throughout the visual system. We consider how these divergent hubs emerge, using an adaptively rewiring neural network model. Adaptive rewiring models show in a principled way how brains could achieve their complex topologies. Modular small-world structures with rich-club effects and circuits of convergent-divergent units emerge as networks evolve, driven by their own spontaneous activity. Arbitrary nodes of an initially random model network were designated as retinal ganglion cells. They were intermittently exposed to the retinal waveform, as the network evolved through adaptive rewiring. A significant proportion of these nodes developed into divergent hubs within the characteristic complex network architecture. The proportion depends parametrically on the wave incidence rate. Higher rates increase the likelihood of hub formation, while increasing the potential of ganglion cell death. In addition, direct neighbors of designated ganglion cells differentiate like amacrine cells. The divergence observed in ganglion cells resulted in enhanced convergence downstream, suggesting that retinal waves control the formation of convergence in the lateral geniculate nuclei. We conclude that retinal waves stochastically control the distribution of converging and diverging activity in evolving complex networks.

IMPLEMENTATION OF CHARACTER FORMATION FOR STUDENTS THROUGH EXTRACURRICULAR ACTIVITY MANAGEMENT AT INTEGRATED ISLAMIC ELEMENTARY SCHOOL BANDAR LAMPUNG

Education seeks to build students' moral character and personalities as well as their ability to collaborate with others, be responsible, autonomous, and have high moral standards. It does not merely concentrate on academic success. Participating in extracurricular activities helps students develop positive character traits. Utilizing a case study methodology and a descriptive qualitative approach, this study examines how extracurricular activities shape students' personalities and how they are managed. According to the study's findings, extracurricular activities help kids grow in their social skills, leadership, feeling of accountability, self-assurance, and academic prowess. The purpose of evaluating extracurricular activities is to find out how well they help kids develop desirable character traits. It is possible to develop extracurricular activities by offering a greater range of options, encouraging student participation in the planning and execution process, training managers, and providing suitable infrastructure and facilities. Good extracurricular activity management is essential to developing students' good character traits and equipping them for life's difficulties.