Dynamic Dimension Research Articles

Tutorials and mobile learning in higher education: Enhancing and accessibility

This comprehensive paper delves into two vital facets of contemporary higher education. The first segment investigates the transformative force of mobile learning (m-learning), elucidating its far-reaching impact on the educational landscape. Offering unprecedented flexibility and accessibility, m-learning redefines the dynamics between students and educators. The exploration navigates through potential benefits, challenges, and broader implications, providing a nuanced understanding of the evolving landscape of higher education in the digital age. The second segment focuses on the impact of active teaching in a first-year class at the National Engineering School of Carthage (ENICarthage) in Tunisia. Active teaching, recognized for engaging students in the learning process, is scrutinized for its effectiveness in enhancing theoretical understanding and graded assignment performance. This research introduces a dynamic dimension by incorporating mobile learning and tutorials as integral components of active teaching strategies. With its technological leverage, mobile learning aims to enhance student engagement, while advanced tutorials feature simulation functionality for an immersive learning experience. Through statistical analysis, the paper contributes to a nuanced comprehension of the positive influence of active teaching on academic achievements, offering practical insights into the application of active teaching methods and their potential benefits for enhancing student learning outcomes. This synthesis thus presents a holistic view of the dynamic interplay between mobile learning and active teaching in shaping the contemporary higher education landscape.

The impact of dynamic marketing capabilities on startup performance: A case of business incubators in Jordan

Dynamic marketing capabilities provide startups with the platform and market knowledge that entitle them to achieve their goals and survive the competition. The study aims to examine the impact of dynamic marketing capabilities dimensions on startups’ performance in Jordan. This quantitative study employs a questionnaire to solicit answers from respondents who are the incubates that use business incubator services. A total of 302 entrepreneurs from different incubator centers in Jordan participated in the online survey. Using the SmartPLS program version 4, structural equation modeling (PLS-SEM) was used to examine the study model. The findings indicate that startup performance is significantly impacted by dynamic marketing capabilities (β = 0.937, t = 127.2, p = >0.00). Concerning absorptive capacity, both dimensions revealed a significant impact on startup performance: potential absorptive capacity (β = 0.251, t = 7.932, p > 0.000) and realized absorptive capacity (β = 0.177, t = 5.409, p > 0.000). For knowledge management, the results for knowledge acquisition were β = 0.360, t = 11.089, p = >0.000, for knowledge dissemination, β = 0.102, t = 2.367, p = >0.018, and for responsiveness to knowledge β = 0.318, t = 6.852, p = >0.000.

Investigations on the Degradation Behavior of Processed FeMnSi-xCu Shape Memory Alloys.

A new functional Fe-30Mn-5Si-xCu (x = 1.5 and 2 wt%) biomaterial was obtained from the levitation induction melting process and evaluated as a biodegradable material. The degradation characteristics were assessed in vitro using immersion tests in simulated body fluid (SBF) at 37 ± 1 °C, evaluating mass loss, pH variation that occurred in the solution, open circuit potential (OCP), linear and cyclic potentiometry (LP and CP), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and nano-FTIR. To obtain plates as samples, the cast materials were thermo-mechanically processed by hot rolling. Dynamic mechanical analysis (DMA) was employed to evaluate the thermal properties of the smart material. Atomic force microscopy (AFM) was used to show the nanometric and microstructural changes during the hot rolling process and DMA solicitations. The type of corrosion identified was generalized corrosion, and over the first 3-5 days, an increase in mass was observed, caused by the compounds formed at the metal-solution interface. The formed compounds were identified mainly as oxides that passed into the immersion liquid. The degradation rate (DR) was obtained as a function of mass loss, sample surface area and immersion duration. The dynamic mechanical behavior and dimensions of the sample were evaluated after 14 days of immersion. The nanocompounds found on the surface after atmospheric corrosion and immersion in SBF were investigated with the Neaspec system using the nano-FTIR technique.

Briefing Idea of Geopolitics

Geopolitical diversity holds an undeniable allure, leading to the categorization of publications into four 'schools': neo-classical geopolitics, subversive geopolitics, non-geopolitics, and critical geopolitics, each exploring different dimensions of geopolitical dynamics. These schools distinguish themselves based on their proximity to the studied object (practical/applied or academic/reflective) and their stance toward the state system (focusing on states as principal actors or acknowledging other political actors and interests). Despite their differences, these studies collectively demonstrate a growing interest in geo-economics. Various thinkers, including Mackinder, Spykman, Collins, and Ratzel, have formulated these theories using terms like Heartland, Rimland, inland, outerland, enclave, and exclave. Notably, Bangladesh, as a developing country, is geopolitically strengthening its position in world politics.

Strategic Insights: Understanding the Interplay of Adaptability and Consistency in Multinational and National Organizations

This research delves into the intricate dynamics of organizational cultures, specifically focusing on the dimensions of adaptability and consistency. Through a comprehensive study involving 2 multinational and 2 national companies, the research analyzes key components such as creative change, customer focus, core values, agreement, and coordination and integration. The findings reveal that multinational companies exhibit significantly higher adaptability, driven particularly by strong scores in creative change and organizational learning. Although no significant disparities were identified in overall consistency scores, multinational organizations consistently demonstrated higher scores across core values, agreement, and coordination and integration. The study emphasizes the interdependence of adaptability and consistency traits, providing actionable insights for leaders aiming to foster resilient and effective organizational cultures. While the research has certain limitations, such as a reliance on self-reported data and a cross-sectional design, it lays a foundation for future explorations into the nuanced dimensions of organizational dynamics across diverse global contexts.

High-impedance arc fault modeling for distribution networks based on dynamic geometry dimension

Accurate modeling of high-impedance arc fault (HIAF) is of great significance for studying the characteristics of arc fault and suppressing its harm. In traditional arc models, the arc column is usually considered a cylindrical channel with constant length and diameter. However, the arc-burning process is susceptible to the environment. The changes in arc length and diameter present complex characteristics. Therefore, this study proposes a new HIAF model for distribution networks based on the arc's dynamic geometry dimension (DGD). First, the arc length, diameter, and field strength expressions are improved based on the classical cybernetic model. Next, an automatic parameter optimization method for the DGD model is proposed, and then this model is compared with existing advanced models. After that, the effects of the variable parameters of this model on arc characteristics are analyzed. Finally, the practical application effect of this model is tested. The experimental results show that the DGD model can accurately describe the dynamic arc development process, approximate the given arc waveform closely, and generate high-quality samples, which has certain advantages.

Fear of missing out and beyond: Unveiling theoretical dimensions in post-pandemic festival events and community engagement dynamics

This study unveils a framework, proposing that fear of missing out is fundamental to residents' support for hosting festival events. Unlike traditional definitions, we redefine FOMO as the fear of missing out on the same festival event others attend, especially relevant in the post-pandemic resurgence of physical festivals. Using FOMO as the moderator, data analysis via partial least squares of structural equation modelling from 243 respondents provided nuanced findings on how community benefits, individual benefits, new opportunities and social costs impact intention to support through dimensions of the theory of planned behaviour. This study broadens theoretical understanding by exploring community engagement dynamics through smaller-scale festivals. At the same time, this study emphasises predictive and explanatory modelling, which bridges the gap between theory and practice, enriching our understanding of residents' perspectives and advocating for a more inclusive theoretical framework in the context of post-pandemic festival events.

Higher-order networks for Business Ecosystems Computational Modeling

Ecosystems are nowadays a dominant organizational form in the digital age. But this construct lacks consensus on its empirical scope, its key theoretical features and its theoretical roots. The paper proposes an integrative framework as well as a method and a tool for calculating an ecosystem based on simplicial complexes and the HYPE platform. It concludes that a data-driven and visualization approach is needed to the study of the dynamic, emergent and adaptive dimensions of today’s platform-based ecosystems.

Modeling the Links Between Economic Growth, Socio-economic Dynamics and Environmental Dimensions: a Panel VAR Approach

Modeling the Links Between Economic Growth, Socio-economic Dynamics and Environmental Dimensions: a Panel VAR Approach

Study and analysis of geometric and dynamic dimensions of segner type jet turbines

Study and analysis of geometric and dynamic dimensions of segner type jet turbines

КОНТРОЛЬ ДИНАМИЧЕСКОГО ГАБАРИТА ТРАНСПОРТНОГО СРЕДСТВА С ПРИМЕНЕНИЕМ НЕЙРОННЫХ СЕТЕЙ

The purpose of this study is to develop a system for monitoring and informing the driver about the safe distance to the vehicle moving in front. The dynamic size of the car depends on a large number of factors and can change during one trip, lack of experience or overwork of the driver can cause non-compliance with the distance and, as a result, a traffic accident. A computer program using neural networks has been developed that allows determining the dynamic dimension of a vehicle depending on operating conditions. The results of the program calculation differ from experimental studies by no more than 3.5%.

Predictive Analytics in Data Engineering: An AI Approach

Predictive analytics, as a cornerstone of data engineering, has witnessed a paradigm shift with the integration of Artificial Intelligence (AI) methodologies. This abstract provides an overview of the key themes explored in the paper titled “Predictive Analytics in Data Engineering: An AI Approach.” The paper delves into the transformative impact of AI on predictive analytics within the domain of data engineering. Traditional predictive analytics often relied on statistical models and historical data patterns to forecast future trends. The advent of AI technologies, particularly machine learning and deep learning, has revolutionized the predictive analytics landscape by enabling systems to autonomously learn and adapt from data. A central focus of the paper is the exploration of advanced AI algorithms in predictive analytics. Machine learning models, such as regression, decision trees, and ensemble methods, are examined for their efficacy in predictive modeling tasks. Additionally, the integration of deep learning architectures, known for their ability to capture intricate patterns in large datasets, is explored for enhancing predictive accuracy. The convergence of predictive analytics and AI introduces a dynamic dimension to data engineering workflows. The paper outlines how AI-driven predictive analytics not only enhances the accuracy of predictions but also automates feature extraction, identifies complex patterns, and adapts to evolving data structures. The synergy between AI and predictive analytics empowers data engineers to navigate the challenges posed by big data and unstructured datasets. Ethical considerations and interpretability in AI-driven predictive analytics are also scrutinized in the paper. As AI models become increasingly complex, ensuring transparency in decision-making processes and addressing biases are crucial for responsible deployment in real-world scenarios. The findings presented in this paper contribute to the evolving discourse on the integration of AI in predictive analytics within the realm of data engineering. By examining the practical implications, challenges, and ethical dimensions, the paper provides valuable insights for practitioners, researchers, and organizations aiming to harness the full potential of AI in predictive analytics to drive informed decision-making and innovation in data engineering workflows.

Discrepancy of social cognition between bipolar disorders and major depressive disorders.

The research landscape examining social cognition (SC) impairment in patients with major depressive disorders (MDD) and bipolar disorders (BD) is notably scarce. Presently, assessments predominantly rely on static stimuli and self-reported measures, which may not capture the dynamic dimensions of social cognition. This study aimed to validate the Chinese version of Movie Assessment of Social Cognition (MASC-CH) and to investigate whether MDD and BD exhibit distinct patterns of SC impairments, shedding light on potential differences between these two mood disorders. The study encompassed 197 participants, aged 18-65, distributed as follows: 21 BD, 20 MDD, and 156 healthy controls (HC). We focused on examining "cognitive" and "emotional" SC scores and "undermentalizing" and "overmentalizing" error patterns, with nonsocial inference as a control. Additional assessments included the Reading Mind in the Eyes Test (RMET) and the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). We also explored the association between depression severity (measured by the Hamilton Depressive Rating Scale, HDRS) and distinct SC dimensions between MDD and BD. The MASC-CH exhibited strong validity and reliability for SC assessment. In group comparisons, BD participants scored significantly lower on MASC-CH, while the MDD group scores were not significantly different from HC. Specifically, BD individuals had notably lower cognitive SC scores and made more undermentalizing and absence of mentalizing errors than MDD and HC. Additionally, a negative correlation between HDRS score and overmentalizing was observed in BD, not in the MDD. The findings indicate that depression severity scores in BD were inversely related to MASC-CH scores. In contrast, this relationship was not observed in the MDD group. These results underscore the importance of SC impairments as distinguishing characteristics of both BD and MDD. It provides valuable insights into the distinct social-cognitive profiles of both mood disorders.

An Overview of Mathematical Methods Applied in the Biomechanics of Foot and Ankle–Foot Orthosis Models

Ankle–foot orthoses (AFOs) constitute medical instruments designed for patients exhibiting pathological gait patterns, notably stemming from conditions such as stroke, with the primary objective of providing support and facilitating rehabilitation. The present research endeavors to conduct a comprehensive review of extant scholarly literature focusing on mathematical techniques employed for the examination of AFO models. The overarching aim is to gain deeper insights into the biomechanical intricacies underlying these ankle–foot orthosis models from a mathematical perspective, while concurrently aiming to advance novel models within the domain. Utilizing a specified set of keywords and their configurations, a systematic search was conducted across notable academic databases, including ISI Web of Knowledge, Google Scholar, Scopus, and PubMed. Subsequently, a total of 23 articles were meticulously selected for in-depth review. These scholarly contributions collectively shed light on the utilization of nonlinear optimization techniques within the context of ankle–foot orthoses (AFOs), specifically within the framework of fully Cartesian coordinates, encompassing both kinematic and dynamic dimensions. Furthermore, an exploration of a two-degree-of-freedom AFO design tailored for robotic rehabilitation, which takes into account the interplay between foot and orthosis models, is delineated. Notably, the review article underscores the incorporation of shape memory alloy (SMA) elements in AFOs and overviews the constitutive elastic, viscoelastic, and hyperelastic models. This comprehensive synthesis of research findings stands to provide valuable insights for orthotists and engineers, enabling them to gain a mathematical understanding of the biomechanical principles underpinning AFO models and fostering the development of innovative AFO designs.

Exploring dimensions of anti-corruption agencies (in the example of Central Asia)

This scientific article delves into the multifaceted realm of anti-corruption agencies in Central Asian nations, examining the dynamic dimensions that shape their effectiveness and impact. Against the backdrop of the region‘s unique socio-political landscape, we investigate the structural frameworks, legal mechanisms, and operational strategies employed by anti-corruption agencies to combat corruption. Drawing upon a comprehensive analysis of institutional designs and regulatory environments, our study illuminates the challenges and opportunities faced by these agencies. The implementation of anti-corruption reforms diverges across Central Asian nations, with different government bodies tasked with these responsibilities. Kazakhstan, for instance, employs a specialized body with significant powers, whereas in Turkmenistan, the prosecutor‘s office assumes a pivotal role. The article underscores the critical need to scrutinize the effectiveness of these bodies. Furthermore, our research incorporates case studies from select Central Asian nations, providing nuanced insights into the contextual variations of anti-corruption endeavors. By navigating the complex landscape of anti-corruption initiatives in Central Asia, this article contributes to a deeper understanding of the challenges and prospects for combating corruption in the region.

Johann Adam Möhler’s Dynamic Ecclesiology

Along with Kant’s sapere aude, the Enlightenment brought about a certain kind of rigidity as though everything could only be understood by way of logical reasoning through a set of inflexible procedures. When the Church was understood within this movement, it lost its dynamic and organic dimension. Romanticism, as the counter movement of the Enlightenment, brough new inspiration as to how one should do ecclesiology. Möhler took the chance. His ecclesiology is influenced by romanticism without being too abstract. His ecclesiology is exemplary of a creative ecclesiology that can manage various tensions due to different ways of understanding the nature of the Church.

A new Meso-Scale coarse-filter indicator for the Canadian boreal forest

Forest management planning and management agencies in Canada have been moving towards an ecosystem-based management (EBM) approach that honours whole ecosystem dynamics over all time and space scales. As part of this evolution, provincial, national, and international agencies have added coarse filter indicators to represent pre-industrial, or ‘natural’ range of variation (NRV) ecosystem conditions as ecologically defendable baselines. The intent was to balance the more traditional species specific (i.e., fine filter) approach to sustainability with a more holistic (i.e., coarse scale) model of ecosystem dynamics. The development and acceptance of coarse filter indicators has been neither linear nor straightforward. One of the more important assumptions inherent in an NRV strategy is that it captures relevant, meaningful patterns at the most appropriate scales in a practical way. To test this assumption, I used a spatially explicit simulation model to compare landscapes created under pre-industrial conditions with those created using four different thresholds of disturbance size commonly used today in boreal Canada. The results suggest that even a 10,000 ha upper size limit create significantly higher levels of homogeneity and fragmentation at intermediate spatial scales relative to pre-industrial landscape patterns. Towards developing a new, more robust coarse filter indicator, the net area burned at four grid sizes over 10 and 20 years was calculated for natural wildfire data from northern Saskatchewan. The results suggest that wildfire tends to cluster at all scales due largely to the influence of large infrequent wildfires. In contrast, data from two forest management areas in Alberta summarized at the same scales confirm that harvesting activity tends to spread out evenly across the landscape. Based on these findings, the NRV data was then refined to capture; 1) the percentage of grid cells where high disturbance levels occur (WHEREs – or WHERE you are) and the proportion where no disturbance occurs (WYNs – or Where You are Not). The WHERE-WYN indicator is unique in that it specifically integrates time as a dimension of landscape dynamics. It is also easily understood and calculated, corresponds directly to management activities, has NRV equivalents, and applicable to most of boreal Canada. Augmenting the current suite of coarse filter indicator with the WHERE-WYN combination addresses a critical gap in our NRV toolkit and will ultimately help create more sustainable landscapes.

A study of gas transport mechanisms in shale's confined nanopores: Examining irregularity, adsorption effects, and stresses

Many difficulties and challenges have been encountered during the exploration and development of shale gas, among which high flexibility of the reservoir structure and low permeability have been the most notable problems that have restricted the efficient development of shale gas. In this paper, we have developed a fractal apparent permeability model for shale based on fractal theory that has taken into account the confinement effects. Also considering the effect of pore deformation on porosity, the defining equation of pore size under the combined effect of multiple factors is obtained, which, in turn, leads to the defining equation of dynamic fractal dimension. Due to the significant confinement effect due to the development of nanopores in shale reservoirs, the Peng–Robinson equation of state is modified using the adsorption effect, and the influence of the confinement effect on the critical properties and each permeability parameter is considered. Based on this, a shale fractal apparent permeability model coupled with slip flow, Knudsen diffusion, and surface diffusion was developed, and the model was validated with experimental data. The results revealed that the developed model was in relatively better agreement with the measured data. Furthermore, the confinement effect performed a positive role in shale's apparent permeability, with the calculated values of model permeability that considered the confinement effect was greater than the calculated values of model permeability, without the confinement effects being considered.

Changes in the semantic profile to evaluate the quality and safety of life

The purpose of the article is to highlight the specifics of changing the parameters of the semantic profile in determining the indicators of quality and safety of life. Modern civilizational development is characterized by dynamism and flexibility, which directly affects human and social life and requires new algorithms for determining the level of quality and security in both the existential and institutional, as well as in the value and functional dimensions. The purpose of the research is to determine the relationship between socio-cultural factors that have dynamic characteristics with constant constants of the semantic differential. The research methodology focuses on the use of general scientific (primarily analytical) methods and philosophical and methodological synergistic principles. The results of the study indicate that there are three formats of this interaction: changing profile parameters under the influence of socio-cultural activity; preservation of profile constants regardless of socio-cultural realities; synergistic mutual transformation of indicators of socio-cultural life and the semantic profile of its assessment. The scientific novelty of the work is focused on the introduction of a dynamic dimension to the impact assessment and measurement of the parameters of quality and safety of life using a semantic profile. Thus, the problem of quality and safety of life in both the theoretical and ideological and practice-oriented dimensions receives new mechanisms and tools for assessing and measuring the level of viability in modern civilisational progress. The semantic profile is no longer a stable format for assessing the quality and safety of life, but a dynamic method that is able to operate with variable data, transforming its own parameters.

Methodological Paradigms in Representing African Law: The Stratigraphic Approach and the Notion of Legal Pluralism

Abstract The contribution deals with the representation of African law in comparative legal literature. It aims at moving forward from an understanding of African legal systems as bounded entities, frequently dubbed “pluralistic” but too often described as derivative from western law, that is the law of the former colonial powers. The paper reacts to common representations of African law based on the “stratigraphic approach” and on the notion of legal pluralism. While remaining a valuable tool for the study of African legal systems in a structuralist fashion, the stratigraphic approach ultimately fails to capture the more dynamic dimension of legal relations and the agency of legal subjects better conveyed by the notion of legal pluralism. The notion of legal pluralism, in turn, points at the existence of plural normative orders in all legal systems, therefore it seems to have lost its specificity to post-colonial African societies. Moreover, research on legal pluralism has become progressively dominated by academic lawyers adopting a normative and theoretical approach with little regard for empirical observation of law in society.