Dynamic Element Research Articles

The velar chord and dynamic integration of the gular valve in crocodylians.

Crocodylians evolved a unique gular valve that is capable of creating a water-tight seal between the oral and pharyngeal cavities, allowing the animal to safely submerge with an open mouth. The gular valve has traditionally been described as consisting of two separate parts: an active mobile ventral portion (consisting of the tongue and portions of the hyolingual apparatus) and a dorsal portion, which is a static fold on the hard palate (often termed the palatal velum). The results of the present study argue that the two portions of the gular valve are functionally integrated, not separate, and that the dorsal portion (herein the dorsal gular fold) is a dynamic element the shape and tension of which are influenced by active and passive forces. Using gross dissection, histology, and DiceCT, the present study documents a previously underscribed component of the gular valve, the velar chord, which links the hyolingual apparatus to the dorsal gular fold, functionally integrating the two halves of the gular valve. Through endoscopic videography and a variety of manipulations on living crocodylians, this study demonstrates that changes in the tension on the velar chord directly alter the shape and tension of the dorsal gular fold. The shape changes observed in the dorsal gular fold could be accommodated by a shallow depression in the ventral surface of the palatine bones, herein termed the velar fossa. The velar fossa is a prominent feature of Alligator mississippiensis and was observed in other crocodilians; however, a survey of living and fossil crocodylians demonstrated that the velar fossa is not a universal feature in this clade. Understanding the functional linkage between the dorsal and ventral portions of the gular valve has implications beyond the dive reflex of crocodylians, since active manipulation of the dorsal gular fold likely plays a role in a variety of behavioral and physiological processes such as deglutition and vocalization.

Impacts of Sea Level Rise on Danish Coastal Wetlands - a GIS-based Analysis.

Intergovernmental Panel on Climate Change (IPCC) scenarios run by an ensemble of models developed by the Coupled Model Intercomparison Project (CMIP) projects an average sea level rise (SLRs) of 0.6 to 1.2 m for the low and high emission scenarios (SSP1-1.9, SSP5-8.5), during the next century (IPCC 2021). The coastal zone will experience an increase in the flooding of terrestrial habitats and the depth of marine productive areas, with potential negative consequences for these ecosystems. The coast in Denmark is highly modified due to anthropogenic uses. Dikes, dams, and other coastal infrastructure are widespread, causing a coastal squeeze that prevents natural coastal development and inland migration of coastlines. We performed a national-scale analysis on the impacts of mean sea level rise (MSLR) in 2070 and 2120, and a 1 in 10-year storm surge water level (10SS) in 2120 MSLR for the Danish coast. Our study shows extensive permanent flooding of coastal habitats (~14%), whereas only 1.6% of urban areas will be flooded. Finally, very large agricultural areas (~191,000 ha) will be frequently flooded by 10SS if no extra protective measures are planned. With the present coastal protection structures, key habitats will be affected by permanent flooding or coastal squeeze while even larger extents will be subjected to intermittent marine flooding. About 45% (199 km2) of all Danish coastal wetlands will be permanently flooded by 2120, while areas occupied by forest, lakes and freshwater wetlands will be more frequently flooded by marine water. This study highlights the importance of including coastal habitats as dynamic elements in climate adaptation plans. Conservation and restoration of key habitats such as coastal wetlands should be prioritized in management plans. If Denmark does not change its current priorities, it may face the complete loss of coastal wetlands habitat in the 22nd century.

Hybrid Strategies for Enhancing the Multifunctionality of Smart Dynamic Molecular Crystal Materials.

Dynamic molecular crystals are an emerging class of smart engineering materials that possess unique ability to convert external energy into mechanical motion. Moreover, they have being considered as strong candidates for dynamic elements in applications such as flexible electronic devices, artificial muscles, sensors, and soft robots. However, the inherent defects of molecular crystals like brittleness, short-life and fatigue, have significantly impeded their practical applications. Inspired by the concept of "the whole is greater than the sum of its parts" in the field of biology, building stimuli-response composites materials can be regarded as one of the ways to break through the current limitations of dynamic molecular crystals. Moreover, the hybrid materials can exhibit new functionalities that cannot be achieved by a single object. In this review, the focus was placed on the analysis and discussion of various hybrid strategies and options, as well as the functionalities of hybrid dynamic molecular crystal materials and the important practical applications of composite materials, with the introduction of photomechanical molecular crystals and flexible molecular crystals as a starting point.Moreover, the efficiency, limitations, and advantages of different hybrid methods were compared and discussed.

A comprehensive study of Z-DNA density and its evolutionary implications in birds

BackgroundZ-DNA, a left-handed helical form of DNA, plays a significant role in genomic stability and gene regulation. Its formation, associated with high GC content and repetitive sequences, is linked to genomic instability, potentially leading to large-scale deletions and contributing to phenotypic diversity and evolutionary adaptation.ResultsIn this study, we analyzed the density of Z-DNA-prone motifs of 154 avian genomes using the non-B DNA Motif Search Tool (nBMST). Our findings indicate a higher prevalence of Z-DNA motifs in promoter regions across all avian species compared to other genomic regions. A negative correlation was observed between Z-DNA density and developmental time in birds, suggesting that species with shorter developmental periods tend to have higher Z-DNA densities. This relationship implies that Z-DNA may influence the timing and regulation of development in avian species. Furthermore, Z-DNA density showed associations with traits such as body mass, egg mass, and genome size, highlighting the complex interactions between genome architecture and phenotypic characteristics. Gene Ontology (GO) analysis revealed that Z-DNA motifs are enriched in genes involved in nucleic acid binding, kinase activity, and translation regulation, suggesting a role in fine-tuning gene expression essential for cellular functions and responses to environmental changes. Additionally, the potential of Z-DNA to drive genomic instability and facilitate adaptive evolution underscores its importance in shaping phenotypic diversity.ConclusionsThis study emphasizes the role of Z-DNA as a dynamic genomic element contributing to gene regulation, genomic stability, and phenotypic diversity in avian species. Future research should experimentally validate these associations and explore the molecular mechanisms by which Z-DNA influences avian biology.

Global study of long term heart rhythm synchronization in groups.

Heart rhythm measurements over time reflect important elements of Autonomic Nervous System dynamics. Synchronization among the heart rhythms of multiple participants has been observed, but this study uses the first global dataset collected that measures synchronization at several locations across the globe continuously for multiple weeks. For 15 days, 104 participants located in California (USA), Lithuania, Saudi Arabia, New Zealand, and England underwent continuous ambulatory heart rhythm monitoring. They were not instructed to perform tasks together. Significant long-term correlations were observed across participants within the same region, for just the groups in Saudi Arabia and New Zealand. This is surprising, given that each participant has an individualized life and distinct heart rate. In a different analysis using population-mean cosinor, only in these two locations was a significant circaseptan (about 7-day) rhythm observed. It appears that weekly rhythms in these groups partially contribute to correlations, in addition to long-term movements. A hypothesis with supporting evidence is proposed to explain this, that participants in these groups were socially closer than in the other groups. It would then appear that heart rhythms synchronize over the long term due to social connectedness, even when they are not physically near each other or performing tasks together.

Chapter 1. Introduction to the Albertine Rift

Continental rifting is a fundamental geological process that has been responsible for breaking supercontinents apart and opening new ocean basins throughout Earth's history and the East African Rift System (EARS) is the best active example of this happening in the world today. The Albertine Rift lies at the northern end of the Western Arm of the EARS, consisting primarily of the Lake Albert and Lake Edward basins as they pass along the border between Uganda and the Democratic Republic of Congo. This Memoir describes the key geomorphological features found in the Albertine Rift Valley at the present day, identifying the sedimentary dynamic elements that dovetail together to characterise the dominant depositional environments in these early continental rift basins. These are then used to interpret the Pliocene - Holocene sedimentary sequences, documented during geological field surveys over an eight year period, exposed around the onshore parts of the Lake Albert and Lake Edward rift valleys. Ultimately, the sedimentary dynamics of the Albertine Rift and the stacking of its three-dimensional stratigraphic architecture, is shown to beat to the rhythm of oscillating global glacial - interglacial climatic cyclicity and how this affects the Equatorial Tropics of Africa.

Modeling and Dynamic Characteristics of Tracked Vehicle Equipped with Symmetrical Suspensions Based on Multi-Body Dynamics and Discrete Element Coupling Method

For improving the adaptability of a tracked vehicle equipped with a symmetrical suspension system on complex hilly terrain, based on the coupling method of multi-body dynamics (MBD) and discrete element method (DEM), an MBD-DEM coupling model was built and verified to explore its dynamic behaviors on soil. Firstly, according to the basic parameters of the tracked vehicle equipped with a symmetrical suspension system, a corresponding MBD model was built in Recurdyn V9R4 software. Based on the Euler–Lagrange method, the mathematical structure of the symmetrical suspension system was analyzed, and a corresponding mathematical simulation model was built in Matlab2016/Simulink to verify the MBD model. Secondly, based on the DEM theory and the parameter of the soil in a hilly area, a granular pavement model was built. Then, based on the coupling method of MBD and DEM, the corresponding MBD-DEM coupling model was built. Finally, using the MBD-DEM coupling model, the dynamic behaviors of the tracked vehicle equipped with a symmetrical suspension system under horizontal condition, the climbing condition and the obstacle crossing condition were obtained and discussed. The study results show that the proposed MBD-DEM coupling model could be used effectively to analyze the dynamic characteristics of the tracked vehicle. In addition, according to the analysis of the dynamic characteristics of the proposed tracked vehicle, the tracked vehicle equipped with a symmetrical suspension presents good adaptabilities under various working conditions.

Faktor-faktor Yyng Mempengaruhi Rendahnya Motivasi Belajar Siswa

The low motivation to learn varies depending on the goals to be achieved in the learning process at school. The level of motivation can be seen from the attitude of students during teaching and learning activities. Motivation to learn can arise or change influenced by various factors. According to Dimyati & Mudjiono (2002) factors that influence learning motivation include students' ideals or aspirations, individual abilities, personal conditions, student environment, dynamic elements in the learning process, and teacher efforts in teaching. This study aims to describe: 1) Factors that influence students' low motivation to learn in terms of factors: a. students' ideals or aspirations, b. students' abilities, c. students' conditions, d. students' environmental conditions, e. dynamic elements in learning and teaching, f. teachers' efforts in teaching students. The method used in this study is quantitative with a descriptive research type. The research sample was 69 students of SMK Pariwisata Aisyiyah Padang in grades X, XI, and XII who were registered in the 2024/2025 academic year who were selected based on the Total Sampling technique. Data were obtained by distributing research instruments in the form of questionnaires on factors that influence low student learning motivation that have been tested for validity and reliability. Data were processed using the Percentage Technique. The results of this study indicate that: 1) factors that influence low student learning motivation are reviewed from the following factors: a. Student ideals or aspirations: difficulty in determining interests and talents (56.62%), b. Student abilities: difficulty focusing on processing lesson materials (47.83%), c. Student conditions: difficulty attending school due to health problems (44.93%), d. Student environmental conditions: avoid talking to deskmates (39.13%), d. Dynamic elements in learning and teaching: easily distracted by things around them that hinder the ability to focus on lesson materials (46.38%), e. Teacher efforts in teaching students: teachers do not provide good examples in learning discipline (44.93%). The implications of guidance and counseling services that can be provided are information services, individual counseling services and group counseling services.

Evaluation of an Infinite-Level Inverter Operation Powered by a DC–DC Converter in Open and Closed Loop

This paper evaluates the open- and closed-loop DC–DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite-level stepped sinusoidal voltage. Adding a cascade controller to the DC–DC converter should reduce the settling time and increase the number of levels in the output voltage waveform; it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling through a single-phase bridge inverter energized from a BUCK converter. Trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller to explore its capabilities in power electronics applications. A digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, i.e., 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast, the speed error remains small, and there is no need for a controller. A digital controller requires processing time, and although in theory it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.

Advanced Hybrid Neural Networks for Accurate Recognition of the Extended Alphabet and Dynamic Signs in Mexican Sign Language (MSL)

The Mexican deaf community primarily uses Mexican Sign Language (MSL) for communication, but significant barriers arise when interacting with hearing individuals unfamiliar with the language. Learning MSL requires a substantial commitment of at least 18 months, which is often impractical for many hearing people. To address this gap, we present an MSL-to-Spanish translation system that facilitates communication through a spelling-based approach, enabling deaf individuals to convey any idea while simplifying the AI’s task by limiting the number of signs to be recognized. Unlike previous systems that focus exclusively on static signs for individual letters, our solution incorporates dynamic signs, such as “k”, “rr”, and “ll”, to better capture the nuances of MSL and enhance expressiveness. The proposed Hybrid Neural Network-based algorithm integrates these dynamic elements effectively, achieving an F1 score of 90.91%, precision of 91.25%, recall of 91.05%, and accuracy of 91.09% in the extended alphabet classification. These results demonstrate the system’s potential to improve accessibility and inclusivity for the Mexican deaf community.

The impact of preceding convection on the development of Medicane Ianos and the sensitivity to sea surface temperature

Abstract. Medicane Ianos in September 2020 was one of the strongest medicanes observed in the last 25 years. It was, like other medicanes, a very intense cyclone evolving from a baroclinic mid-latitude low into a tropical-like cyclone with an axisymmetric warm core. The dynamical elements necessary to improve the predictability of Ianos are explored with the use of simulations with the Met Office Unified Model (MetUM) at 2.2 km grid spacing for five different initialisation times, from 4 to 2 d before Ianos's landfall. Simulations are also performed with the sea surface temperature (SST) uniformly increased and decreased by 2 K from analysis to explore the impact of enhanced and reduced sea surface fluxes on Ianos's evolution. All the simulations with +2 K SST are able to simulate Medicane Ianos, albeit too intensely. The simulations with control SST initialised at the two earliest times fail to capture intense preceding precipitation events at the right locations and the subsequent development of Ianos. Amongst the simulations with −2 K SST, only the one initialised at the latest time develops the medicane. Links between sea surface fluxes and upper-level baroclinic processes are investigated. We find three elements that are important for Ianos's development. First, an area of low-valued potential vorticity (PV), termed a “low-PV bubble”, formed within a trough above where Ianos developed; diabatic heating associated with a preceding precipitation event triggered a balanced divergent flow in the upper levels, which contributed to the creation and maintenance of this low-PV bubble as shown by results from a semi-geostrophic inversion tool. Second, a quasi-geostrophic ascent was forced by middle and upper levels during Ianos's cyclogenesis. It is partially associated with the geostrophic vorticity advection, which is enhanced by the growth and advection of the low-PV bubble. Third, diabatic heating dominated by deep convection formed a vertical PV tower during Ianos's intensification and continued to produce diabatically induced divergent outflow aloft, thus sustaining Ianos’s development. Simulations missing any of these three elements do not develop Medicane Ianos. Our results imply the novel finding that preceding convection was essential for the subsequent development of Ianos, highlighting the importance of the interactions between near-surface small-scale diabatic processes and the upper-level quasi-geostrophic flow. A warmer SST strengthens the processes and thus enables Ianos to be predicted in simulations initiated at the earlier times.

A High-Speed Dynamic Element Matching Decoder With Integrated Background Calibration Control

A High-Speed Dynamic Element Matching Decoder With Integrated Background Calibration Control

Artificial Intelligence Scene Creation with Virtual Technology for the DigitalFilm

Artificial Intelligence-based scene creation leverages advanced algorithms to generate realistic and immersive environments for various applications, including gaming, virtual reality, and simulations. By utilizing techniques such as procedural generation, deep learning, and computer vision, these systems can automatically create complex landscapes, detailed textures, and dynamic elements that respond to user interactions. This not only enhances the user experience but also significantly reduces the time and effort required for manual scene design, enabling developers to focus on creativity and innovation. In the realm of digital media production, the quest for lifelike scenes and efficient evaluation methodologies has led to the exploration of novel techniques. This paper investigates the synergy between point estimation and artificial intelligence (AI) in advancing digital scene creation and evaluation. Through comprehensive simulations and analyses, we assess the effectiveness of point estimation in quantifying scene attributes such as visual realism, dynamic interactivity, physical accuracy, and artistic expression. Additionally, we delve into the utilization of AI algorithms for automating scene classification, thereby streamlining decision-making processes and optimizing resource allocation in production workflows. Through comprehensive simulations and analyses, we assess the effectiveness of point estimation in quantifying scene attributes such as visual realism (mean score: 0.85), dynamic interactivity (mean score: 0.72), physical accuracy (mean score: 0.93), and artistic expression (mean score: 0.65).

Investigation of higher-order springing of a ship in regular waves by experimental analysis and two-way CFD-FEA coupled method

In this paper, the higher-order springing phenomenon is addressed for a segmented barge ship model through experimental and numerical measures. An efficient in-house two-way coupled numerical solver between Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is developed and validated against experimental results. The coupling method is based on a domain-separated approach and necessitates the resolution of individual boundary value problems in distinct domains. To ensure convergence within these individual domains, an implicit numerical scheme is employed and further facilitated exchange of variables for coupling. The current approach emphasizes the overall convergence between two solvers, maintaining a strongly coupled setup to comprehensively address fluid-structure interaction phenomena, including added mass and damping effects. A series of tank tests were conducted first to measure the wave-induced sectional loads and motions, during which the springing responses to very high-order harmonics of wave load were observed. By comparing the numerical prediction with the tank test results for rigid body motion and flexible vertical bending moment (VBM), the proposed numerical method demonstrated agreement with experimental results, affirming its validity and robustness. Finally, the springing response up to 14th order harmonics is discussed and investigated.

Image-based chip detection during turning

This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algorithm carries out initial image preprocessing and edge detection, followed by background subtraction to isolate dynamic elements and filtering based on the size of the objects. Pre-determined masks are applied to eliminate overlaps with existing workspace objects, based on the tool’s trajectory. The research validates that the applied technique effectively recognizes chips in both face and straight turning. Specific filtering techniques improve the algorithm’s capability to detect even smaller chips, and it substantially reduces false alarms, laying the groundwork for long, continuous chip detection systems.

Preparing remote states for genuine quantum networks

Quantum networks typically comprise quantum channels, repeaters, and end nodes. Remote state preparation (RSP) allows one end node to prepare the states of the other end nodes remotely. While quantum discord has recently been recognized as necessary for RSP, it does not guarantee the practical implementation of RSP in quantum networks surpasses any classical method. Herein, we theoretically introduce and experimentally study a quantum resource that we call the RSP capability. This resource validates all the static and dynamic elements required to enable genuine quantum networks where the RSP’s implementation can outperform any classical emulation of entanglement- and qubit-unitaries-free strategies, including the static resources of Einstein-Podolsky-Rosen pairs and the dynamic resources of quantum channels and repeaters. Our experiment measures the RSP capability to demonstrate the transition between classical and nonclassical RSP depending on the photon-pair qualities. It shows that quantum discord does not confirm a nonclassical RSP, but the RSP capability does. These results help reveal the quantum advantages that emerge when networking RSP is in play.

The Influence of Eye Gaze Direction on Consumers

Abstract: There are now static ads where the model looks at the product, as well as static ads where the model doesn't look at the product. The study's goal was to investigate how models' eye gaze directions affect consumers. This paper uses a questionnaire survey as a case study to conduct a detailed analysis. It collects data on consumers' perceived attractiveness of the product, their evaluation of the product, and their intention to purchase the product. Additionally, it discusses the impact of the model's eye gaze direction on these consumers. The model's eye gaze direction has the first influence on consumers' perceived attraction to the product. Consumers will be more attracted to the product when the model's gaze remains fixed on it. In light of this influence, this paper proposes adding dynamic elements to the advertisement to make consumers more attracted to the product. Consumers' evaluation of the product is the second influence of the model's eye gaze direction on consumers is consumers' evaluation of the product. Fixing the model's eye gaze on the product improves consumers' evaluation of it. This paper suggests that the advertisement should truly reflect the product's characteristics and advantages in light of this influence. The third effect of the model's direction of gaze on consumers is their intention to purchase the product. Focusing the model's gaze on the product enhances consumers' purchase intentions. Given this influence, this paper recommends allowing stars or models that align with the product's characteristics to represent it.

Correction: Xiong et al. Application of Multibody Dynamics and Bonded-Particle GPU Discrete Element Method in Modelling of a Gyratory Crusher. Minerals 2024, 14, 774

In the published article [...]

Damage analysis and assessment of concrete T-girder bridge based on fire scene numerical reconstruction

Fire is a sporadic disaster of concrete bridges, with diverse fire environments and complex damage mechanisms. Accurately evaluating the damage situation of concrete bridges after a fire is exceedingly challenging. This study formulates a damage analysis and assessment method based on the step-by-step and progressively deepening working principle. The method relies on fire scene numerical reconstruction and encompasses key technical aspects, including bridge detection and analysis during the fire incident, fire scene numerical reconstruction, and subsequent bridge damage assessment. Building upon these principles, the study utilizes results from the detection and analysis of the concrete T-girder bridge during a fire incident to establish Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) models for the numerical reconstruction of the fire scene. These models enable the calculation of varying temperature distributions and the evolution of the bridge under fire. Compared with the parameters obtained through the ISO834 method, the numerical reconstruction approaches not only enhances the accuracy of replicating the bridge combustion process but also enables the extraction of temperature field distribution patterns within the bridge fire space and its concrete components.

Domain adaptation for semantic segmentation of road scenes via two-stage alignment of traffic elements

Unsupervised domain adaptation has been used to reduce the domain shift, which would improve the performance of semantic segmentation on unlabeled real-world data. However, existing methodologies fall short in effectively addressing the domain shift issue prevalent in traffic scenarios, leading to less than satisfactory segmentation results. In this paper, we propose a novel domain adaptation method for semantic segmentation via unsupervised alignment of traffic elements. Firstly, we introduce a two-stage self-training framework that leverages a blended set of training samples to enhance the training process. In the first stage, we leverage generated mixup training samples as inputs within our two-stage self-training framework and have developed corresponding loss functions for both the source and target domains to direct the training process. Then, the alignment modules for dynamic and static traffic elements are designed to achieve accurate matching between the source and the target domain images. The cosine similarity maximization is applied to the alignment of dynamic traffic elements, while the prototype learning is utilized for the static traffic elements. Additionally, we present a new technique for reducing noise in pseudo labels by constructing thresholds that adjust to each class. Meanwhile, we formulate the associated target domain loss function for vacant pseudo label pixels. The experimental results demonstrate that the proposed method is superior to the existing methods on five different domain adaptation tasks, which is more applicable to semantic segmentation of road scenes.