Dynamic Element Research Articles

Exploring the influence of subjective thermal perception on electroencephalogram characteristics based on prior thermal experience

Achieving thermal comfort for occupants in a dynamic environment that reflects their previous thermal experiences is essential for enhancing satisfaction. Current models do not fully consider these dynamic elements, thus limiting advancements in occupants' thermal comfort. This study aims to delineate the characteristics of electroencephalogram (EEG) responses aligned with subjective thermal perception in various thermal environment scenarios, inclusive of past thermal experiences. It focuses on identifying EEG indices, brain regions, and temporal markers that can distinguish between different thermal perceptions. The study involves sixteen male participants who undergo three thermal experience scenarios: predicted mean vote (PMV) 0 → PMV +2, PMV +2 → PMV –2, and PMV -2 → PMV +2. Our results highlight the sensitivity of the F3 channel in the left frontal lobe to thermal environments. The study identifies a pivotal time frame of 6 min after the experiment's start as significant for differentiating thermal perception groups. Additionally, it reveals that the EEG indices reacting to thermal changes vary depending on the participants' previous thermal experiences. These findings indicate that physiological signals, particularly EEG responses, can serve as effective biomarkers for distinguishing thermal perceptions in diverse thermal experience scenarios. This research emphasizes the need to integrate a variety of thermal environment scenarios, considering previous thermal experiences, into personal comfort models for more effective and tailored thermal comfort solutions.

Connecting Solar Wind Velocity Spikes Measured by Solar Orbiter and Coronal Brightenings Observed by SDO

The Parker Solar Probe's discovery that magnetic switchbacks and velocity spikes in the young solar wind are abundant has prompted intensive research into their origin(s) and formation mechanism(s) in the solar atmosphere. Recent studies, based on in situ measurements and numerical simulations, argue that velocity spikes are produced through interchange magnetic reconnection. Our work studies the relationship between interplanetary velocity spikes and coronal brightenings induced by changes in the photospheric magnetic field. Our analysis focuses on the characteristic periodicities of velocity spikes detected by the Proton Alpha Sensor on the Solar Orbiter during its fifth perihelion pass. Throughout the time period analyzed here, we estimate their origin along the boundary of a coronal hole. Around the boundary region, we identify periodic variations in coronal brightening activity observed by the Atmospheric Imaging Assembly onboard the Solar Dynamics Observatory. The spectral characteristics of the time series of in situ velocity spikes, remote coronal brightenings, and remote photospheric magnetic flux exhibit correspondence in their periodicities. Therefore, we suggest that the localized small-scale magnetic flux within coronal holes fuels a magnetic reconnection process that can be observed as slight brightness augmentations and outward fluctuations or jets. These dynamic elements may act as mediators, bonding magnetic reconnection with the genesis of velocity spikes and magnetic switchbacks.

Modeling and Control of an MR-Safe Pneumatic Radial Inflow Motor and Encoder (PRIME).

Magnetic resonance (MR) conditional actuators and encoders are the key components for MR-guided robotic systems. In this article, we present the modeling and control of our MR-safe pneumatic radial inflow motor and encoder. A comprehensive model is developed that considers the primary dynamic elements of the system, including: 1) motor dynamics, 2) pneumatic transmission line dynamics, and 3) valve dynamics. After model validation, we present a simplified third order model that facilitates design of a first order sliding mode controller (TO-SMC). Finally, the motor hardware is tested in a 7T MRI. No image distortion or artifacts were observed. We posit the MR-safe motor and dynamic model will lower the entry barriers for researchers interested in MR-guided robots and promote wider adoption of MR-guided robotic systems.

Ecological carrying capacity assessment incorporating ecosystem service flows

Ecological carrying capacity focuses on the limits of human development, serving as a policy instrument for guiding regional sustainable development. Regional space exhibits openness and dynamics. Nonetheless, ecological carrying capacity assessments seldom account for the potential influence of dynamic elements. The endeavor to integrate ecosystem service flows into ecological carrying capacity assessment represents an innovative approach to address this issue. This paper reviews multiple methods of assessing ecological carrying capacity and highlights the deficiencies in representing dynamic elements. Subsequently, the research progress in ecosystem service flows is examined, encompassing connotations, features, and models. Based on common theories, intermediary linkages, and the impact of incorporating spatiotemporal dynamics, the relationship between them is analyzed. The advantages of ecosystem service flows are also elucidated, which provide explicit spatial information and integrate biophysical processes when representing dynamic elements. The framework for ecological carrying capacity assessment incorporating ecosystem service flows comprises five steps: key theory selection, objectives and scope establishment, identification of supply and demand matching and assessment of flow utility, ecosystem service flow analysis, and ecological carrying capacity assessment. In the future, the research will focus on conducting quantitative pilot projects in typical regions, removing barriers to ecosystem service flows, and developing a dynamic ecological carrying capacity assessment model that considers multiple factors.

The effects of game mechanics on user retention in using social live streaming services

PurposeSocial live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.Design/methodology/approachThis study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.FindingsThe results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.Originality/valueDriven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.

Asset Allocation Strategies: A Case Study in Mutual Fund and Inaurance Portfolios in Wallet Wealth LLP

This case study explores effective asset allocation strategies, focusing on mutual funds and insurance portfolios, with an emphasis on incorporating a de-risking factor. It underscores the importance of strategic asset allocation customised to each person’s risk profiles, Investing objectives, and temporal horizons . By utilizing mutual funds and insurance products, investors can construct diversified portfolios to mitigate risk and optimize returns. The study examines how different combinations of these instruments can enhance portfolio resilience and performance. Moreover, the integration of a de-risking factor adds a dynamic element to distribution of assets. This entails modifying the asset in the portfolio. mix depending on the state of the market and risk preferences to minimize downside risk and capture upside potential. Through historical analysis and scenario simulations, the study evaluates the efficacy of various asset allocation strategies, highlighting the benefits of incorporating a de-risking approach. It demonstrates how this strategy can protect capital during market downturns while capitalizing on growth opportunities in favorable market conditions.

A Comparative Review on Enhancing Visual Simultaneous Localization and Mapping with Deep Semantic Segmentation.

Visual simultaneous localization and mapping (VSLAM) enhances the navigation of autonomous agents in unfamiliar environments by progressively constructing maps and estimating poses. However, conventional VSLAM pipelines often exhibited degraded performance in dynamic environments featuring mobile objects. Recent research in deep learning led to notable progress in semantic segmentation, which involves assigning semantic labels to image pixels. The integration of semantic segmentation into VSLAM can effectively differentiate between static and dynamic elements in intricate scenes. This paper provided a comprehensive comparative review on leveraging semantic segmentation to improve major components of VSLAM, including visual odometry, loop closure detection, and environmental mapping. Key principles and methods for both traditional VSLAM and deep semantic segmentation were introduced. This paper presented an overview and comparative analysis of the technical implementations of semantic integration across various modules of the VSLAM pipeline. Furthermore, it examined the features and potential use cases associated with the fusion of VSLAM and semantics. It was found that the existing VSLAM model continued to face challenges related to computational complexity. Promising future research directions were identified, including efficient model design, multimodal fusion, online adaptation, dynamic scene reconstruction, and end-to-end joint optimization. This review shed light on the emerging paradigm of semantic VSLAM and how deep learning-enabled semantic reasoning could unlock new capabilities for autonomous intelligent systems to operate reliably in the real world.

Fractional Second-Grade Fluid Flow over a Semi-Infinite Plate by Constructing the Absorbing Boundary Condition

The modified second-grade fluid flow across a plate of semi-infinite extent, which is initiated by the plate’s movement, is considered herein. The relaxation parameters and fractional parameters are introduced to express the generalized constitutive relation. A convolution-based absorbing boundary condition (ABC) is developed based on the artificial boundary method (ABM), addressing issues related to the semi-infinite boundary. We adopt the finite difference method (FDM) for deriving the numerical solution by employing the L1 scheme to approximate the fractional derivative. To confirm the precision of this method, a source term is added to establish an exact solution for verification purposes. A comparative evaluation of the ABC versus the direct truncated boundary condition (DTBC) is conducted, with their effectiveness and soundness being visually scrutinized and assessed. This study investigates the impact of the motion of plates at different fluid flow velocities, focusing on the effects of dynamic elements influencing flow mechanisms and velocity. This research’s primary conclusion is that a higher fractional parameter correlates with the fluid flow. As relaxation parameters decrease, the delay effect intensifies and the fluid velocity decreases.

Overcoming Fear and Improving Public Speaking Skills through Adaptive VR Training

This paper examines the effectiveness of virtual reality (VR) in training public speaking skills. The fear of public speaking (FPS) is a common problem that can have a significant impact on an individual’s professional and personal life. Traditional therapies for public speaking anxiety have been shown to be effective, but there is growing interest in the use of VR as an alternative or supplement to these therapies. This study aims to investigate the VR medium in improving public speaking skills and to explore the potential mechanisms underlying this effect. A framework was developed with the aim to investigate the possibility of improving public speaking skills through VR. Key features of this framework include the ability to adjust the audience size and alter the dimensions of the room. Additionally, it allows for the modification of initial audience behaviors. One of the innovative aspects is the inclusion of an evolving attention span in the virtual audience, adding a dynamic element to the VR experience. The framework excels in tracking various metrics in real time and has the audience react dynamically based on them. These metrics include movement and voice parameters. The system is designed to present this data as immediate feedback to the user, but also as a summary after a presentation has concluded. After an extensive two-phased testing, the results are discussed. These findings suggest that VR can be an effective means for improving public speaking skills and potentially helping in alleviating fear of public speaking.

Modelling Strategies in Sports

This paper presents a model that examines sports teams’ strategic choices about the extent of offense/defense to adopt in competing with other teams. The mathematical formulation adopted permits the derivation of a team’s optimal strategy under different game scenarios (current score and time left to play), and team characteristics (playing at home or away, and each team’s quality). A novel feature of the model is that teams can choose a strategy at several moments in the game, thereby incorporating a comprehensive dynamic element. The National Hockey League is used as an application. Optimal coaching behavior is derived in this setting, and the impact of rule changes is assessed. The study found that removing the overtime period, disproportionally increasing the rewards for a win, or removing the point that is currently awarded to the team that loses the shootout at the end of overtime, would all lead to the adoption of more offensive strategies during the game. That outcome is aligned with higher fan interest and team revenue.

Enhanced Unmanned Aerial Vehicle Localization in Dynamic Environments Using Monocular Simultaneous Localization and Mapping and Object Tracking

This work proposes an innovative approach to enhance the localization of unmanned aerial vehicles (UAVs) in dynamic environments. The methodology integrates a sophisticated object-tracking algorithm to augment the established simultaneous localization and mapping (ORB-SLAM) framework, utilizing only a monocular camera setup. Moving objects are detected by harnessing the power of YOLOv4, and a specialized Kalman filter is employed for tracking. The algorithm is integrated into the ORB-SLAM framework to improve UAV pose estimation by correcting the impact of moving elements and effectively removing features connected to dynamic elements from the ORB-SLAM process. Finally, the results obtained are recorded using the TUM RGB-D dataset. The results demonstrate that the proposed algorithm can effectively enhance the accuracy of pose estimation and exhibits high accuracy and robustness in real dynamic scenes.

Revolutionary 3D Design with AI

The 3D design delves into the creation and deployment of an innovative web experience that seamlessly merges Artificial Intelligence (AI) technology and captivating 3D visuals within a React-based framework. It demonstrates the utilization of AI algorithms for enhancing user interactivity, personalization, and the creation of dynamic 3D elements, fostering a captivating user experience. Embark on a transformative journey into the heart of fashion's evolution, this unveils a paradigm-shifting collaboration between Artificial Intelligence (AI) and 3D cloth design, heralding a new era of creativity and innovation within the fashion industry. This explores the fusion of Artificial Intelligence (AI) with 3D cloth design, revolutionizing the fashion industry's creative landscape. Integrating AI into cloth design processes allows for swift ideation, realistic simulations, and diverse fabric explorations, empowering designers to redefine fashion concepts efficiently. Key Words: AI,3D, Design.

Effects of CO2 Geosequestration on Opalinus Clay

CO2 geosequestration is an important contributor to United Nations Sustainable Development Goal 13, i.e., Climate Action, which states a global Net-Zero CO2 emissions by 2050. A potential impact of CO2 geosequestration in depleted oil and gas reservoirs is the variations in induced pressure across the caprocks, which can lead to significant local variations in CO2 saturation. A detailed understanding of the relationship between the pressure gradient across the caprock and local CO2 concentration is of utmost importance for assessing the potential of CO2 geosequestration. Achieving this through experimental techniques is extremely difficult, and thus, we employ a coupled Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) based solver to mimic sub-critical CO2 injection in Opalinus Clay under various pressure gradients across the sample. The geomechanical and multiphase flow modelling utilising Darcy Law helps evaluate local variations in CO2 concentration in Opalinus Clay. Well-validated numerical results indicate favourable sub-critical CO2 geosequestration under a positive pressure gradient across Opalinus Clay. In the absence of a positive pressure gradient, a peak CO2 concentration of 5% has been recorded, which increases substantially (above 90%) as the pressure gradient across the sample increases.

Seeing and Thinking about Urban Blue–Green Space: Monitoring Public Landscape Preferences Using Bimodal Data

Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively understand public preferences. This paper proposes a method to evaluate public landscape preference from the perspective of seeing and thinking, takes the examples of seven parks around the Dianchi Lake in Kunming, China, and analyses the social media data by using natural language processing technology and image semantic segmentation technology. The conclusions are as follows: (1) The public exhibits significantly high positive sentiments towards various UBGSs, with over 93% of comments expressed positive sentiments. (2) Differences exist in the frequency and perception of landscape features between image and text modalities. Landscape elements related to stability are perceived more in images than in text, while dynamic and experiential elements are perceived more in text than in images. (3) In both modalities, the distinctive landscape features of parks are more frequently perceived and preferred by the public. In the end, the intrinsic links between landscape elements and public sentiment and preferences are discussed, and suggestions for design and management improvements are made to consolidate their health benefits to the public.

Experimental and numerical investigation on the hydroelastic response of barge and KVLCC2 ship

In this paper, the hydroelasticity of two segmented ship models (Barge and KVLCC2) is investigated by experimental and numerical methods. A two-way Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) coupled method is adopted and further validated its accuracy against experimental results. The current approach emphasizes the overall convergence between two solvers, maintaining a strongly coupled manner to comprehensively address the fluid-structure interaction phenomenon, including the added mass effect. A series of experiments of a segmented Barge and KVLCC2 under various wave conditions were firstly conducted. The motions of the models are measured and the displacement Response Amplitude Operators (RAOs) are calculated. The CFD-FEA coupled method is demonstrated in agreement with experimental results by comparing the numerical prediction with the tank test results in terms of motion, affirming the validity and robustness. Finally, the hydroelastic response is discussed and investigated.

Evolving wormhole geometry from dark matter energy density

We analyse traversable wormholes defined by the dynamic line elements that asymptotically approach Friedmann–Robertson–Walker (FRW) universe. These dynamical wormholes is supported by the galactic dark matter as well as perfect isotropic fluid. We will discuss several evolving Lorentzian wormholes comprising with different perfect isotropic fluids in addition to various scale factors. We will speculate the various significance, features and throat energy conditions for these evolving traversable Lorentzian wormholes.

Shared and distinct electroencephalogram microstate abnormalities across schizophrenia, bipolar disorder, and depression.

Microstates of an electroencephalogram (EEG) are canonical voltage topographies that remain quasi-stable for 90 ms, serving as the foundational elements of brain dynamics. Different changes in EEG microstates can be observed in psychiatric disorders like schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). However, the similarities and disparatenesses in whole-brain dynamics on a subsecond timescale among individuals diagnosed with SCZ, BD, and MDD are unclear. This study included 1112 participants (380 individuals diagnosed with SCZ, 330 with BD, 212 with MDD, and 190 demographically matched healthy controls [HCs]). We assembled resting-state EEG data and completed a microstate analysis of all participants using a cross-sectional design. Our research indicates that SCZ, BD, and MDD exhibit distinct patterns of transition among the four EEG microstate states (A, B, C, and D). The analysis of transition probabilities showed a higher frequency of switching from microstates A to B and from B to A in each patient group compared to the HC group, and less frequent transitions from microstates A to C and from C to A in the SCZ and MDD groups compared to the HC group. And the probability of the microstate switching from C to D and D to C in the SCZ group significantly increased compared to those in the patient and HC groups. Our findings provide crucial insights into the abnormalities involved in distributing neural assets and enabling proper transitions between different microstates in patients with major psychiatric disorders.

Using cultural-historical activity theory to describe a university-wide blended learning initiative

Institution-wide evaluations of Blended Learning implementations are rare. Even less common are evaluations that report the sociocultural context of the implementation. Recently, an Australian university in the western region of Victoria embarked on an initiative to blend all course units over a three-year period. Stemming from a rigorous analysis of reporting documents and participantresearcher observations, an attempt has been made to describe the sociocultural context of this blended learning initiative through the lens of Engestrom’s Cultural-historical Activity Theory (CHAT). This description, along with the challenges surfaced will serve as a precursor to the university-wide impact evaluation of this blended learning initiative. The objective of the analysis was to reify the complex processes, intricate relationships and dynamic environmental elements, which tend not to be captured by impact evaluations. Understanding what exactly is going on will enable the University to situate evaluation findings in the context of factors that might have helped or hampered the achievement of outcomes, and remediate process-related problems in a timely manner. Amidst the flurry of focused and coordinated blended learning activities, eight key process-related challenges emerged: Staff Capacity, Engagement, Deployment, Workload, Technological Issues, Project Management, Communication and Unit Stability. These challenges could potentially make or break ‘the Blend’ if not adequately addressed. This paper highlights the value of process evaluations for online and blended learning implementations and argues for such evaluations to be grounded in ontological realities reflected on accountability reports and observational data.

Navigating Ritual Resilience: The Interplay of Change and Continuity in the Shaolin Monastery During the COVID-19 Pandemic

The global upheaval caused by the COVID-19 pandemic introduced considerable perturbations to the religious life and ritual observances within most religious communities around the world. This article delves into the resilience and adaptability of ritual practices within the Shaolin Monastery of China during the five-month COVID-19 quarantine spanning from 23 January to 22 June, 2020. Employing ethnographic methods and grounded in anthropological theory, the study examines the interplay between ritual as a static social fact and as a dynamic, adaptable process, within the context of the Shaolin monastic life. It underlines the intricate interplay between static and dynamic elements in ritual practice, casting light on the Shaolin community’s response to the pandemic. The study discerns dichotomies responsible for the critical forces underlying complex dynamics intrinsic to the Shaolin community’s religious life, namely: religious–secular, isolation–social engagement, discipline–freedom, tradition–innovation, and individual–collective. Tracking the evolutions and consistencies within these dual relationships enabled casting light on the transformative processes that were set in motion and identifying the elements of the religious life that have undergone change and those that have remained constant. This exploration offers a unique glimpse into the mechanisms through which resilience was enacted with the strategies that enabled the community to maintain, adjust and innovate its ritual practices amidst the tribulations presented by the crisis.

Evolution of the national theory of cooperation in the conditions of gradual development of the agrarian sector of Belarus

Evolution of the national theory of cooperation in the conditions of gradual development of the agrarian sector of Belarus