Dynamic Element Research Articles

Supramolecular oligo-thymine/melamine nanobridge-driven macroscopic engineering: reprogrammable hydrogels for multi-stimuli responsive architectures

The arbitrary, modular, and reprogrammable engineering of macroscopic objects by DNA interactions remains a challenge, despite the well-established use of DNA to drive constructs at nano/micro-scale. Moreover, achieving adaptive responsiveness in assembled architectures under dynamic environmental triggers has yet to be realized. In this study, we introduce the association of oligo-thymine strands (polyT) and melamine (MA), as a low-molecular-weight cofactor, into a supramolecular DNA duplex, termed polyT-MA nanobridge. This unique nanostructure exhibits responsiveness to five external stimuli, including temperature, DNA strand, small molecule, acidic pH, and alkaline pH. The polyT-MA nanobridge is developed as the dynamic crosslinking elements for constructing multi-stimuli responsive DNA hydrogels, which exhibit physiochemical properties changes (e.g., rigidity, thermal stability) and hydrogel-to-liquid phase transitions in response to the five external triggers. Notably, the assembly of macroscopic hydrogel blocks at millimeter scale (cubes in 5 × 5 × 5 mm dimensions) into diverse architectures, e.g., linear type, cross, P-shape, T-shape, or heteromorphy, is achieved by using the non-canonical supramolecular polyT-MA nanobridges. Sequential, dynamic, and selective disassembly of polyT-MA bridged hydrogel constructs is triggered by multiple external stimuli and the rearrangement of these separated individual cubes into other architectures in LEGO styles is presented. This study provides insights into the development of advanced materials and devices with reconfigurable architectures and functionalities for intelligent nanoengineering applications.

Penerapan Metode Motion Graphic pada Video Promosi Rumah Kos Dermawan Living, Denpasar Bali

In this research, the application of the motion graphic method in making promotional videos for the Dermawan Living Boarding House in Denpasar, Bali, was explored. Motion graphics, as a visual technique that combines graphic elements, animation and text, are used to create dynamic and interesting messages. The research method involves analysing promotional videos before and after the implementation of motion graphics. Audience response, engagement level, and recall of the video are measured. The research results show that the application of motion graphics significantly increases the attractiveness of promotional videos. The use of dynamic visual elements and smooth transitions makes videos more interesting and memorable for the audience. Apart from that, motion graphics also help convey information more efficiently. In conclusion, the use of motion graphic methods in promotional videos can be an effective strategy for increasing attractiveness and communication efficiency. The practical guidance resulting from this research can help content creators optimize the use of motion graphics in promotional videos.

Video Salient Object Detection Via Multi-level Spatiotemporal Bidirectional Network Using Multi-scale Transfer Learning

Video saliency prediction aims to resemble human visual attention by identifying the most relevant and significant elements in a video frame or sequence. This task becomes notably intricate in scenarios characterized by dynamic elements such as rapid motion, occlusions, blur, background variations, and nonrigid deformations. Therefore, the inherent complexity of human visual attention behavior during dynamic scenes necessitates the assessment of both temporal and spatial data. Existing video saliency frameworks often falter under such conditions, and relying solely on image saliency models neglects crucial temporal information in videos. This study presents a new Video Salient Object Detection via Multi-level Spatiotemporal Bidirectional Network using Multi-scale Transfer Learning (MSB-Net) to address the problem of identifying significant objects in videos. The proposed MSB-Net achieves notable results for a given sequence of frames by employing multi-scale transfer learning with an encoder and decoder approach to acquire knowledge and saliency map attributes spatially and temporally. The proposed MSB-Net model has bidirectional LSTM (Long Short-Term Memory) and CNN (Convolutional Neural Network) components. The VGG16 (Video Geometry Group) and VGG19 architectures extract multi-scale features from the input video frames. Evaluation of diverse datasets, namely DAVIS-T, SegTrack-V2, ViSal, VOS-T, and DAVSOD-T, demonstrates the model's effectiveness, outperforming other competitive models based on parameters such as MAE, F-measure, and S-measure.

Populist autocratization and populist electoral autocracies: towards a unified conceptual framework

AbstractAlthough the research subjects of populism and autocratization studies are interconnected, the full potential of combining their focuses—the dynamic elements of political systems and institutional dimensions—into a comprehensive and systematic conceptual framework remains underexploited. This study makes a stride in this direction by reviewing and connecting these areas through the concepts of populist autocratization and populist electoral autocracies. These concepts aim to deepen our understanding of the nature of contemporary autocratization and the stability of autocracies. While the study is primarily theoretical-conceptual in nature, it also engages with methodological and operationalization considerations, and outlines a brief research agenda to demonstrate the empirical applicability of the analytical framework and lays the foundation for future research.

Advancements In Machine Learning Algorithms for Enhanced Fault Analysis and Categorization in Power Systems

With the growing number of sources, complexity, and dynamic elements of power systems that are prone to disturbance and electrical faults, conventional methods of fault detection are lagging in power system protection. Major faults are exposed to transmission lines due to several factors, such as climate change, heat, lightning strokes, sudden spikes of current and voltage etc. Protecting these lines from faults is cumbersome using traditional methods. However, with the increasing complexity of transmission lines in power systems, advanced technologies such as machine learning come into play for prior fault detection and identification. ML is becoming a popular and intelligent technique for monitoring and predicting health and diagnosing faults in transmission lines of power systems. Since ML is evolving at a faster pace and given the need for and growth of advanced technologies like ML and artificial intelligence, this paper emphasizes comparative analysis of various ML algorithms for transmission line fault analysis. Comparisons for various line faults (LL, LLG, LG, LLL, LLLG, no fault) in power systems using machine learning techniques have been done in terms of accuracy, precision, and other performance measures. The results of the accuracy of various algorithms are represented as tabulated facts in this paper. The Python programming language has been utilized over a dataset to calculate results. For each algorithm, the confusion matrix shows the accuracy of predicting faults over the testing data after training the model or algorithm on the training data. Upon completion of analysis and comparison of MLT's like LR, SVM, DT, RF, K-NN, and gradient descent for analysis of transmission line fault detection, RF and DT machine learning algorithms provided the best accuracy and results. Finally, this paper gives a brief overview of various line faults, ML algorithms accuracy for each transmission fault in a confusion matrix and tabular format and concluded the best machine learning algorithms for power system transmission line fault identification.

Conformational Dynamics, Energetics, and the Divergent Evolution of Allosteric Regulation: The Case of the Yeast MAPK Family.

Allosteric mechanisms provide finely-tuned control over signalling proteins. Proteins of the same family may share high sequence identity and structural similarity but show distinct traits of allosteric control and evolutionary divergent regulation. Revealing the determinants of such properties may be important to understand the molecular bases of different regulatory pathways. Herein, we investigate whether and how evolutionarily-divergent traits of allosteric regulation in homologous proteins can be decoded in terms of internal dynamics and interaction networks that support functionally oriented conformations. In this framework, we start from the comparative analysis of the dynamics and energetics of the yeast MAP Kinases (MAPKs) Fus3 and Kss1 in their native basins. Importantly, distinctive dynamic and energetic stabilization features emerge, which can be related to the two proteins' differential ability to be phosphorylated and engage with the allosteric activator Ste5. We then expanded our study to other evolutionarily-related MAPKs. We show that the dynamical and energetical traits defining the distinct regulatory profiles of Fus3 and Kss1 can be traced along their evolutionary tree. Overall, our approach is able to reconnect (latent) allostery with the principal elements of protein structural stabilization and dynamics, showing how allosteric regulation was encrypted in MAPKs structure well before Ste5 appearance.

Comprehensive analysis of the effect of structural parameters on erosion wear, structural stress, and deformation of high-pressure double-elbow in shale-gas fracturing

In field hydraulic fracturing operation of shale gas development, the high pressure and large displacement liquid-particle two-phase fracturing fluid can be forced to change direction many times through high-pressure double-elbow, and be transported from the outlet pipeline of the fracturing pump to the main pipeline. The high-pressure double-elbow is prone to be affected by erosion wear and Fluid-Structure Interaction (FSI), resulting in perforation and fracture, posing a potential safety threat to field operation. In this study, we conducted the erosion wear experiments on 35CrMo steel used for high-pressure double-elbow in shale-gas fracturing. The erosion rates under different impact angles and flow velocities were obtained, and proposed a novel model of erosion prediction for high-pressure double-elbow. Then the numerical investigation was employed to conduct a comprehensive analysis of erosion wear, structural stress and deformation by the coupling of Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA). The effects of structural parameters such as connection straight pipe length, pipe inner diameter and fluid turning direction were discussed. The results indicate that with the increase of connection straight pipe length, the flow erosion decreases first then varies little, and the deformation gradually increases. Slight erosion wear but large structural stress and deformation in major inner diameter pipe. And the minimum degree of erosion and flow-induced deformation present with the fluid turning direction of double-elbow as 0°. The study can provide references for the design, installation and detection of high-pressure double-elbow and ensure safety in the process of shale gas fracturing.

Application of Multibody Dynamics and Bonded-Particle GPU Discrete Element Method in Modelling of a Gyratory Crusher

The gyratory crusher is one of the most important mineral processing assets in the comminution circuit, and its production performance directly impacts the circuit throughput. Due to its higher energy utilisation rate for rock breakage than semi-autogenous (SAG/AG) milling, it is a common practice in operations to promote and optimise primary crushing before the downstream capacity can be enhanced. This study aims to develop a discrete element modelling (DEM) and multibody dynamics (MBD) cosimulation framework to optimise the performance of the gyratory crusher. An MBD model was initially established to simulate the gyratory crusher’s drivetrain system. A GPU-based DEM was also developed with a parallel bond model incorporated to simulate the particle breakage behaviour. Coupling of the MBD and GPU-based DEM resulted in a cosimulation framework based on the Function Mock-up Interface. An industrial-scale gyratory crusher was selected to test the developed numerical framework, and results indicated that the developed method was capable of modelling normal and choked working conditions. The outcome of this study enabled more realistic gyratory crusher improvement and optimisation strategies for enhanced production.

Bio-Based Epoxy Vitrimers with Excellent Properties of Self-Healing, Recyclability, and Welding.

The development of more recyclable materials is a key requirement for a transition towards a more circular economy. Thanks to exchange reactions, vitrimer, an attractive alternative for recyclable materials, is an innovative class of polymers that is able to change its topology without decreasing its connectivity. In this work, a bisphenol compound (VP) was prepared from saturated cardanol, i.e., 3-pentadecylphenol and vanillyl alcohol. Then, VP was epoxidized to obtain epoxide (VPGE). Finally, VPGE and citric acid (CA) were polymerized in the presence of catalyst TBD to prepare a fully bio-based vitrimer based on transesterification. The results from differential scanning calorimetry (DSC) showed that the VPGE/CA system could be crosslinked at around 163 °C. The cardanol-derived vitrimers had good network rearrangement properties. Meanwhile, because of the dynamic structural elements in the network, the material was endowed with excellent self-healing, welding, and recyclability.

Nacre-mimetic alternating architecture of Ag[sbnd]SnO2 contact: Highly-efficient synergistic enhancement of in-situ self-repairing erosion resistance and naturally evolving impact resistance

Synergistically enhancing the erosion and impact resistance of contacts poses a significant challenge for cutting-edge electrical equipment. Fortunately, mollusk shells in nature have evolved effective strategies to construct microstructures with superior erosion and impact resistance. Inspired by the structure of nacre, AgSnO2 contact material with hierarchical architectures has been designed and fabricated. The mechanistic link between microstructural evolution and dynamic erosion is studied through experiments combined with Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) simulations. Results show that the reconstructed SnO2 skeleton endowed with a highly continuous and anisotropic ‘flowering'-like structure forms a continuous interpenetrating network with Ag, optimizing the conductive pathways on the molten pool surface. Additionally, the Ag-rich regions in the deeper layers on both sides of the molten pool offers a stable ‘nutrient-supply’ for the continuous ‘flowering’ reconstruction of the skeleton, exhibiting excellent in-situ self-repairing erosion resistance. Benefiting from this synergistic strategy, this skeleton is reconstructed based on its natural structure, which further disperses the stress and deformation concentration while inhibiting interfacial debonding, thereby reducing the formation of cracks and significantly enhancing the impact resistance. This work is expected to breakthrough erosion and impact resistance in extreme condition electrical contact materials through biomimetic microstructure design.

A ±0.15 °C (3σ) Inaccuracy CMOS Smart Temperature Sensor from −40 °C to 125 °C with a 10 ms Conversion Time-Leveraging an Adaptative Decimation Filter in 65 nm CMOS Technology

This paper presents the design and implementation of a highly accurate smart temperature sensor designed in 65 nm CMOS technology. The sensor exhibits a ±0.15 °C (3σ) error across a wide temperature range from −40 °C to 125 °C, catering to diverse application needs. Leveraging advanced CMOS technology, the sensor employs an adaptive decimation filter that allows us to control the conversion time, ensuring that the accuracy of the conversion is maintained even in challenging conditions. The proposed sensor architecture integrates advanced techniques for temperature sensing for improved accuracy and reliability. Through meticulous circuit design and the usage of dynamic element matching, chopping, and calibration/trimming, the sensor demonstrates exceptional performance characteristics, making it suitable for various industrial, automotive, and consumer electronics applications demanding high precision temperature monitoring.

Impact of sediment uniformity from steep tributary on transport in main Channels: A CFD-DEM study

During flash flood events, a prominent size segregation phenomenon often occurs in the mixture of sediment particles of varying diameters moving with the floodwaters. However, the impact of the inherent inhomogeneity of the sediment on its transport process continues to be unclear. This study evaluates the sorting phenomenon in the transport behavior of flood-impacted, loosely deposited sediment particles originating from steep tributary feeders in mountain channels. To achieve this objective, a computational framework integrating Computational Fluid Dynamics and Discrete Element Method (CFD-DEM) was utilized to directly simulate the detailed paths of all particles. After validating the CFD-DEM model, we investigated the influence of the sediment particles’ coefficient of uniformity (Cu) on sediment transport characteristics. The results suggest that under different Cu values, coarse particles initially accelerate rapidly but later slow down and converge to a consistent speed, whereas fine particles demonstrate a more uniform speed increase and eventually maintain a constant velocity. With rising Cu, the peak degree of sorting between coarse and fine particles first increases and then stabilizes. The temporal variation of the dimensionless sediment transport rate of any sediment component at a given section can be represented using a modified dual-branch Weibull function. The overall transport process can be determined through linear superposition based on mass proportion. Additionally, we found that the heterogeneous characteristics of the sediment provide a mode of overall sediment transport where fine particles roll at the bottom, while coarse particles slide and saltate at the top, leading to reduced frictional dissipation in the movement of coarse particles. This phenomenon is commonly observed in mountain flood channels with slopes less than 60 degrees. These findings bolster the explanation for the poor application of existing sediment transport rate formulas in flash flood channels.

Unraveling the Roles of Switching and Relaxation Times in Volatile Electrochemical Memristors to Mimic Neuromorphic Dynamical Features

AbstractComputing through ensembles of interacting dynamical elements is the next frontier of the diverse field of neuromorphic computing. Spiking neural networks are one of the possible examples. Computation through dynamics and through time requires the development of novel technologies for devices with rich dynamics. Among the various candidates, the most promising ones are volatile electrochemical memristive systems that switch from high to low resistance state by voltage application and self‐recover the high resistance state after a tunable relaxation time. Such devices can perform a wide variety of computational primitives. However, a clear comprehensive picture of their possible dynamics and their physical interpretation is still missing. In the present manuscript, prototypical electrochemical silver/silicon oxide/platinum (Ag/SiOx/Pt) memristive devices are characterized to identify dynamical aspects, like integrative effects and stochastic switching. Integrative effects are evidenced both in high and low resistance states, associated to wake‐up phase and cumulative switching. All the dynamical aspects are related to characteristic switching times and relaxation times, and with reference to the electrochemical and physical processes involved in device operation. The various dynamical aspects are linked to short‐term memory effects and basic temporal processing functions based on paired‐pulse effects that are relevant for neuromorphic applications.

A Reconstruction Methodology of Dynamic Construction Site Activities in 3D Digital Twin Models Based on Camera Information

Digital twin technology significantly enhances construction site management efficiency; however, dynamically reconstructing site activities presents a considerable challenge. This study introduces a methodology that leverages camera data for the 3D reconstruction of construction site activities. The methodology was initiated using 3D scanning to meticulously reconstruct the construction scene and dynamic elements, forming a model base. It further integrates deep learning algorithms to precisely identify static and dynamic elements in obstructed environments. An enhanced semi-global block-matching algorithm was then applied to derive depth information from the imagery, facilitating accurate element localization. Finally, a near-real-time projection method was introduced that utilizes the spatial relationships among elements to dynamically incorporate models into a 3D base, enabling a multi-perspective view of site activities. Validated by simulated construction site experiments, this methodology showcased an impressive reconstruction accuracy reaching up to 95%, this underscores its significant potential in enhancing the efficiency of creating a dynamic digital twin model.

Flashforward Language Style Analysis in Bugis Song Lyrics by Selfie Yamma

The objective of this research is to examine the "flashforward" language style of Bugis music lyrics performed by Selfie Yamma, with a focus on cultural, linguistic, and musical backgrounds. Information was gathered from the lyrics of the songs collected from relevant sources. The process of data analysis included organizing the data, simplifying the data, presenting the data, and summarizing the data. The analysis findings indicate that the "flashforward" language style plays a crucial role in forming a distinct and exclusive ambiance in Bugis song lyrics. Utilizing flashforward language style in song lyrics enhances the understanding and expression of the message, providing a new perspective for interpretation. Language in Bugis culture is not only a means of communication in song lyrics; it also represents the traditional values, beliefs, and historical experiences of the Bugis people. The use of "flashforward" language in song lyrics enhances emotional and cognitive engagement with the audience by adding a dynamic and imaginative element to the interpretation.

Jazz / Pop Singing at the Crossroads of Movement and Musical elements

Research question - How can focusing on the connection between body movements and the key musical elements of rhythm, lyrics/mood, pitch and dynamics positively affect the expressiveness and vocal freedom of jazz / pop vocalists? When considering the attributes of captivating performances, jazz and pop singers often tend to underutilize their bodies on stage. This observation prompted a deeper examination of the interplay between body awareness, singing, and movements, resulting in the question “How can focusing on the connection between body movements and the key musical elements of rhythm, lyrics/mood, pitch and dynamics positively affect the expressiveness and vocal freedom of jazz / pop vocalists?” The research aims to address this question through a series of investigative stages. Firstly, the analysis of my 2023 end-of-year performance revealed a clear correlation between gestures, expressiveness and the four musical elements mentioned. Further research supported this finding and led to the development of movement-focused singing exercises, whereby vocalists sing while consciously engaging their bodies in alignment with each key musical element individually. This methodology underwent testing with six vocalists, yielding valuable empirical data. The data shows that this set of exercises can be a helpful, holistic tool in increasing expressiveness, enhancing awareness and improving embodiment while singing, as I have also experienced for myself. By sharing this research, I hope to encourage all musicians to deepen their connection with themselves, their instrument, and the audience through movement and body awareness.

Principles of an economic sociology of innovation

AbstractAlthough innovation is a core element of capitalist dynamics, it turns out that, to date, there is no coherent Economic Sociology of innovation, leaving the discipline oblivious to explaining fundamental economic dynamics. Nor has the enormous importance of novelty and innovation in current societal transitions evoked a corresponding research program in Economic Sociology, meaning that Economic Sociology struggles to grasp contemporary societal change. The article reviews the rather disparate diversity of approaches that could speak to a remedy, stepwise assembling and integrating them to establish the principles of an Economic Sociology approach to innovation. First, resonating with ‘embeddedness’ as the core paradigm of Economic Sociology, it spells out the embeddedness of innovation processes in social institutions. Next, it reviews innovation in relation to the diversity of normative, cultural‐cognitive, regulative, and relational institutions, carving out the relevance of the combination of institutions in ‘fields.’ It then determines ‘valuation’ as the overarching mechanism of how institutional frameworks interact with innovation processes. Eventually, discussing ‘institutional work’ as a major property of institutional frameworks, it raises awareness for the mechanisms of the ‘co‐evolution’ of institutions and innovations.

Mapping the chromatin accessibility landscape of zebrafish embryogenesis at single-cell resolution by SPATAC-seq.

Currently, the dynamic accessible elements that determine regulatory programs responsible for the unique identity and function of each cell type during zebrafish embryogenesis lack detailed study. Here we present SPATAC-seq: a split-pool ligation-based assay for transposase-accessible chromatin using sequencing. Using SPATAC-seq, we profiled chromatin accessibility in more than 800,000 individual nuclei across 20 developmental stages spanning the sphere stage to the early larval protruding mouth stage. Using this chromatin accessibility map, we identified 604 cell states and inferred their developmental relationships. We also identified 959,040 candidate cis-regulatory elements (cCREs) and delineated development-specific cCREs, as well as transcription factors defining diverse cell identities. Importantly, enhancer reporter assays confirmed that the majority of tested cCREs exhibited robust enhanced green fluorescent protein expression in restricted cell types or tissues. Finally, we explored gene regulatory programs that drive pigment and notochord cell differentiation. Our work provides a valuable open resource for exploring driver regulators of cell fate decisions in zebrafish embryogenesis.

The Root Endophytic Microbiome Shifts Under Drought in High-Performing Sorghum

Plant-associated microbes contribute to crop health and resilience, potentially extending or complementing plant traits under abiotic stress. Here we tested a series of hypotheses centered on the fungal mycobiome and bacterial microbiome of field-grown sorghum ( Sorghum bicolor), an emerging model crop for drought resilience, which we cultivated under arid conditions. Overall, the sorghum mycobiome and microbiome differed in composition between the exterior and interior of plant tissues, between roots and leaves, and among sorghum genotypes. We did not observe variation in fungal and bacterial endophytes among performance classes of sorghum when water was plentiful, but the root endophytic mycobiome and microbiome both shifted markedly under water limitation, with similar shifts in composition observed among multiple plant genotypes. The root endophytic microbiome of high-performing sorghum was especially responsive to water limitation. Network analysis suggested that water limitation did not directly remodel these root endophytic microbiomes, such that interactions of the microbiome with the host plant, rather than interactions among microbes within the microbiome, may be the most dynamic element of change when water is limited. Overall, our study points to shifts in the prevalence of particular taxa under abiotic stress and suggests that high-performing lines may have distinctive features as substrates or strategies for actively recruiting diverse, abundant, and distinctive microbial communities to roots under water limitation. Such findings are important in the arid lands that frame marginal agriculture today and comprise an increasing proportion of agriculture in a changing world.

이커머스 플랫폼 상품 이미지의 표현 방법이 광고 태도에 미치는 영향

This study investigates the impact of expression methods in product images used on detailed pages in the cosmetics industry on e-commerce platforms, focusing on product type, function type, and appeal type, on advertising attitudes. The study employed a 2(product type: skincare vs. makeup) × 2(function type: still vs. motion) × 2(appeal type: rational vs. emotional) design, selecting representative products from Naver Shopping to create eight experimental stimuli. A survey was conducted with women aged 20 and older in South Korea from May 2 to 6, 2024, and a total of 44 completed questionnaires were analyzed. The results indicated that motion graphics induced higher advertising attitudes compared to still images, and emotional appeals led to higher advertising attitudes than rational appeals. This implies that dynamic elements in product images create a stronger impression on consumers, and emotional appeals enhance advertising effectiveness by evoking emotional responses. However, there was no statistically significant difference in advertising attitudes based on product type, nor were there significant interaction effects between product type, function type, and appeal type. These findings highlight the importance of dynamic images and emotional appeals in digital marketing strategies for the cosmetics industry. Future research should aim to generalize these results across diverse consumer groups and consider variables such as purchasing tendencies, skin characteristics, and age for a more comprehensive analysis. Further research in other industries is also necessary to determine if similar marketing elements yield consistent effects.