Principles Of Theory Research Articles

Research on Autonomous Underwater Vehicle Path Optimization Using a Field Theory-Guided A* Algorithm

Autonomous Underwater Vehicles (AUVs) have become indispensable tools in the fields of ocean exploration, resource exploitation, and environmental monitoring. Path planning and obstacle avoidance are crucial to improve the operational capabilities of AUVs. However, most algorithms focus only on macro-global or micro-local path planning and rarely address both problems simultaneously. This study extends the classical A* algorithm by integrating field theory principles. The resulting Field Theory Augmented A* (FT-A*) algorithm combines the constraints in the AUV’s dynamics and the threats posed by obstacles to ensure a safe navigation distance. The paths planned by the FT-A* algorithm were subsequently re-optimised in conjunction with Dubins curves, taking into account path smoothness and redundant node problems. Simulation experiments confirm that the improved algorithm can effectively help AUVs navigate safely around obstacles, which greatly improves navigation safety and increases the arithmetic power and navigation efficiency. The proposed FT-A* algorithm provides a robust solution for underwater path planning and demonstrates great practical value for AUV operation in complex marine environments.

ПРИНЯТИЕ РЕШЕНИЙ ПО ВЫБОРУ ОПТИМАЛЬНОЙ ПЛОТНОСТИ БУРОВОГО РАСТВОРА НА ОСНОВЕ ГЕОМЕХАНИЧЕСКОГО МОДЕЛИРОВАНИЯ И НЕЧЕТКОЙ ЛОГИКИ

In order to avoid various drilling problems associated with instability of the wellbore walls, lost circulation, etc., it is necessary to use the concept of a “safety window” of the drilling fluid. Calculation of the boundaries of the mud safety window makes it possible to justify the choice of mud density for safe drilling of wells. However, with all its advantages, it is impossible to accurately determine the boundaries of the “safety window” due to their blurriness, which requires the use of appropriate methods based on fuzzy logic and taking into account this type of heterogeneity. This article proposes an approach based on the application of the basic principles of fuzzy set theory to the choice of drilling mud density using the example of several fields in Azerbaijan, Russia and Kazakhstan. An equation for determining density was obtained, calculations were made using this expression for some fields, and the boundaries of the so-called “safety window” were assessed based on geomechanical studies.

Development and validation of the Child Hemophilia Treatment Experience Measure: A new observer-reported outcome measure.

The Child Hemophilia Treatment Experience Measure (Child Hemo-TEM) was developed to capture the treatment burden experience of children with haemophilia (CwH). Describe the development of this novel haemophilia-specific measure. Interviews were conducted with clinical experts, CwH and CwH's caregivers. Interviews were analysed according to adapted grounded theory principles. Based on the analysis, a preliminary measure was developed and debriefed. Psychometric analyses were performed according to an a priori analysis plan using data collected in a cross-sectional web survey and a final measure was generated. Interviews with four clinical experts, 25 CwH ages 8 to <12 years, and 25 caregivers of CwH <12 years were conducted. Concepts endorsed by ≥10% of CwH and caregivers were: adherence, ease of use, emotional impacts, physical impacts, treatment concerns, and interference with daily life. Cognitive debriefing assessments were conducted to ensure participant understanding and item relevance. Caregivers found the measure to be understandable, comprehensive, and relevant. However, several issues with CwH completing the measure were identified and it was decided to only develop an observer-reported outcome version. Data for psychometric validation was collected in a web survey (N=187). Item reduction dropped 12 items. Factor analysis generated a single, 7-item, internally consistent (α =.855) factor, which consisted of items covering all relevant a priori concepts. The majority of a priori convergent and all known groups validity hypotheses were confirmed. The study findings provide evidence that the Child Hemo-TEM is a brief, well-designed, and valid and reliable measure of haemophilia treatment burden.

Women Fighting the Crisis: Antecedents of Women's Leadership Performance in Facing the Covid-19 Pandemic

Objective: This study aims to empirically investigate the interplay between financial literacy, entrepreneurial orientation, learning orientation, and the performance of food and beverage Micro, Small, and Medium Enterprises (MSMEs) in Bontang City, East Kalimantan Province. Method: The research, grounded in Resource-Based Theory (RBT), explores the mediation role of innovation ability in this relationship. The study encompasses 272 MSME owners as its population. Utilizing Structural Equation Modeling for data analysis. Research Findingsand Discussions: The findings show that financial literacy, entrepreneurial orientation, and learning orientation positively influence innovation capability and MSME performance. In addition, innovation capability emerges as an important mediator that bridges the impact of financial literacy, entrepreneurial orientation and learning orientation on MSME performance. The results of this study contribute to enriching the understanding of the Resource-Based Theory, highlighting that effective utilization of resources, such as financial literacy, entrepreneurial orientation, learning orientation, and innovation capability, can improve MSME performance. Research Implications: This study is a valuable reference for MSME owners in the food and beverage sector, emphasizing the importance of a proactive approach. Responding quickly to market opportunities, introducing new products to new markets, and developing a learning-oriented mindset all play an important role in driving innovation and ultimately improving MSME performance. Originality/Value: This research underscores the importance of strategic resource utilization for MSME success, in line with the principles of Resource-Based Theory. Owners of food and beverage MSMEs are encouraged to develop a proactive and learning-oriented attitude, encouraging innovation as a key driver to improve business performance.

Exploring the role of identity in pro-environmental behavior: cultural and educational influences on younger generations.

It is of paramount importance to gain an understanding of pro-environmental behavior if we are to successfully tackle the climate crisis. The existing body of research provides evidence that identity influences pro-environmental behavior. However, such research is often over-generalised and researchers are challenged to conduct robust analyses with regard to specific local, cultural and educational factors. The present study aims to investigate whether personal or social identity has a distinct effect on three different dimensions of pro-environmental behavior, using the principles of self-categorisation theory. Additionally, the study seeks to determine whether one of these two factors, the individual or the social factor, is predominant over the other. The study group consisted of cooperative students in Germany, typically a group with high professional ambitions. The data was collected in a cross-sectional survey with a total of 568 cooperative students from academic disciplines in engineering and economics. The reliability of the scales is satisfactory (ω = 0.76-0.88), and the hypotheses are tested by estimating structural equation models. Our research demonstrates that while social identity exerts a stronger influence on activist behavior than personal identity, personal identity has a more pronounced effect on consumer behavior than social identity. Nevertheless, no general statement can be made regarding the relative strength of the effects of personal and social identity on pro-environmental behavior dimensions.

A Theoretical Framework for the Development of Need for Cognition in Childhood and Adolescence.

Extensive research has highlighted the importance of Need for Cognition (NFC) in various contexts, but our understanding of its development remains limited. In particular, the current psychological literature is relatively silent regarding the factors influencing NFC development. We aim to address this gap by proposing a developmental model of NFC based on the principles of the Cognitive Adaptation Trait Theory (CATT). Through a comprehensive review of the current literature, we elucidate the potential key components contributing to the development of NFC in childhood and adolescence. Additionally, we outline several potential strategies to foster NFC development based on the key components of the model. The model aims to provide a starting point for future research on possible mechanisms underlying the development of NFC. Moving forward, future research should empirically test these hypotheses in real-world settings to enhance our understanding of NFC development and validate the suggested fostering strategies on their effectiveness.

Closing the Dissemination Gap: Accessible Toolkits for the Rapid Replication of Evidence-Informed Interventions to Improve Health Outcomes Among People with HIV.

Despite advances in HIV care and treatment in the U.S., disparities in outcomes along the HIV care continuum persist. The widespread replication of effective and sustainable interventions that prioritize the engagement of underserved populations has been identified as a promising path to ending the HIV epidemic in the U.S. Intervention dissemination products, however, rarely provide the comprehensive and accessible information needed to replicate interventions within community settings. To bridge the divide between research and community-based implementation, the Using Evidence-informed Interventions to Improve Health Outcomes among People Living with HIV (E2i) initiative-grounded in the HIV/AIDS Bureau Implementation Science Framework-created a suite of tools to promote the rapid replication of interventions focused on transgender women, Black men who have sex with men, behavioral health integration, and identifying and addressing trauma. The resulting dissemination products are detailed and digestible multimedia toolkits that follow adult learning theory principles and align with the Template for Intervention Description and Replication criteria for adapting non-pharmacological interventions. Each E2i toolkit consists of five components: implementation guides, narrative videos of site implementation, best practice demonstration videos, interactive learning modules, and recruitment posters and brochures. Over 2 years (2022-2024), the E2i toolkit webpages amassed 7703 unique users and 17,666 pageviews. These toolkits can serve as a blueprint for designing comprehensive and accessible dissemination products for replication of HIV interventions in care settings. Dissemination products that bridge the gap between intervention research and replication in community settings are a crucial missing tool for ending the HIV epidemic.

New generalized metric based on branch length distance to compare B cell lineage trees

The B cell lineage tree encapsulates the successive phases of B cell differentiation and maturation, transitioning from hematopoietic stem cells to mature, antibody-secreting cells within the immune system. Mathematically, this lineage can be conceptualized as an evolutionary tree, where each node represents a distinct stage in B cell development, and the edges reflect the differentiation pathways. To compare these lineage trees, a rigorous mathematical metric is essential. Analyzing B cell lineage trees mathematically and quantifying changes in lineage attributes over time necessitates a comparison methodology capable of accurately assessing and measuring these changes. Addressing the intricacies of multiple B cell lineage tree comparisons, this study introduces a novel metric that enhances the precision of comparative analysis. This metric is formulated on principles of metric theory and evolutionary biology, quantifying the dissimilarities between lineage trees by measuring branch length distance and weight. By providing a framework for systematically classifying lineage trees, this metric facilitates the development of predictive models that are crucial for the creation of targeted immunotherapy and vaccines. To validate the effectiveness of this new metric, synthetic datasets that mimic the complexity and variability of real B cell lineage structures are employed. We demonstrated the ability of the new metric method to accurately capture the evolutionary nuances of B cell lineages.

Free vibration of functionally graded graphene platelets reinforced porous composite plate with a diamond-shaped hole and two cracks

This paper investigates the free vibration of the functionally graded graphene platelets reinforced porous composite (FG-GPLRPC) plate with a diamond-shaped hole and two cracks. Based on the Mindlin-Reissner plate theory and Hamilton principle, the governing equations and boundary conditions are derived. These equations are discretized using the generalized differential quadrature finite element method (GDQFEM), and the natural frequency is obtained by numerical solutions. The effects of the hole size, crack length and crack angle on the natural frequency are discussed. The results show that the natural frequency decreases with increasing crack angle and crack length.

Lattice Boltzmann Simulation of Nonequilibrium Flows Using Spectral Multiple-Relaxation-Time Collision Model

Prediction of nonequilibrium flows is critical to space flight. The present work demonstrates that the recently developed spectral multiple-relaxation-time (SMRT) lattice Boltzmann (LB) model is theoretically equivalent to Grad’s eigensystem [“Principles of the Kinetic Theory of Gases,” Thermodynamik der Gase/Thermodynamics of Gases, Springer–Verlag, Berlin, 1958, pp. 205–294], where the eigenfunctions obtained by tensor decomposition of the Hermite polynomials are also those of the linearized Boltzmann equation. Numerical results of shock structure simulation using the Maxwell molecular model agree very well with those of a high-resolution fast spectral method code up to Mach 7, provided that the relaxation times of the irreducible tensor components match their theoretical values. If a reduced set of relaxation times is used, such as in the Shakhov model and lumped-sum relaxation of Hermite modes, non-negligible discrepancies start to occur as the Mach number is raised, indicating the necessity of the fine-grained relaxation model. Together with the proven advantages of LB, the LB-SMRT scheme offers a competitive alternative for nonequilibrium flow simulation.

Spontaneous symmetry breaking and vortices in a tri-core nonlinear fractional waveguide

We introduce a waveguiding system composed of three linearly-coupled fractional waveguides, with a triangular (prismatic) transverse structure. It may be realized as a tri-core nonlinear optical fiber with fractional group-velocity dispersion (GVD), or, possibly, as a system of coupled Gross–Pitaevskii equations for a set of three tunnel-coupled cigar-shaped traps filled by a Bose–Einstein condensate of particles moving by Lévy flights. The analysis is focused on the phenomenon of spontaneous symmetry breaking (SSB) between components of triple solitons, and the formation and stability of vortex modes. In the self-focusing regime, we identify symmetric and asymmetric soliton states, whose structure and stability are determined by the Lévy index of the fractional GVD, the inter-core coupling strength, and the total energy, which determines the system’s nonlinearity. Bifurcation diagrams (of the supercritical type) reveal regions where SSB occurs, identifying the respective symmetric and asymmetric ground-state soliton modes. In agreement with the general principle of the SSB theory, the solitons with broken inter-component symmetry prevail with the increase of the energy in the weakly-coupled system. Three-components vortex solitons (which do not feature SSB) are studied too. Because the fractional GVD breaks the system’s Galilean invariance, we also address mobility of the vortex solitons, by applying a boost to them.

Research on the relationships between river erosion and sedimentation and energy loss in the Yangtze River Basin of China

River scour and siltation, inherently prolonged and multifaceted phenomena, profoundly impact the hydraulic conductivity and navigational safety of waterways, thereby rendering the precise forecasting of their fluctuations a paramount and unresolved challenge. This study embarks on a novel investigative trajectory by examining energy dissipation in rivers, specifically through the scrutiny of empirical hydrological records. Employing the principles of energy balance theory, this study elucidates the intricate connection between energy losses and sedimentation volumes in the upper reaches of the Yangtze River and at its confluence with the significant tributary, the Jialing River.Our findings diverge from conventional wisdom, revealing that standard metrics of energy loss, encompassing kinetic, potential, and total mechanical energies, along with momentum losses, inadequately characterize the complexity of sediment deposition processes. In contrast, we demonstrate that the loss of suspension power is a more indicative measure of sedimentation quantity. Through meticulous comparisons of various formulations for calculating suspension power, we identified a formula grounded in the concept of minimal available power dissipation in river systems that exhibits superior accuracy in correlating suspension power losses with sedimentation patterns in river sections. This formula's efficacy is further enhanced when considering aggregate suspension power dissipation under the influence of tributary inflows, enabling refined predictions of sedimentation variations along river segments. In conclusion, the insights derived from this meticulous research contribute significantly to the realm of river resource management and the pursuit of sustainable, high-quality aquatic ecosystem development.

Customizing Bayesian multivariate generalizability theory to mixed-format tests.

Mixed-format tests, which typically include dichotomous items and polytomously scored tasks, are employed to assess a wider range of knowledge and skills. Recent behavioral and educational studies have highlighted their practical importance and methodological developments, particularly within the context of multivariate generalizability theory. However, the diverse response types and complex designs of these tests pose significant analytical challenges when modeling data simultaneously. Current methods often struggle to yield reliable results, either due to the inappropriate treatment of different types of response data separately or the imposition of identical covariates across various response types. Moreover, there are few software packages or programs that offer customized solutions for modeling mixed-format tests, addressing these limitations. This tutorial provides a detailed example of using a Bayesian approach to model data collected from a mixed-format test, comprising multiple-choice questions and free-response tasks. The modeling was conducted using the Stan software within the R programming system, with Stan codes tailored to the structure of the test design, following the principles of multivariate generalizability theory. By further examining the effects of prior distributions in this example, this study demonstrates how the adaptability of Bayesian models to diverse test formats, coupled with their potential for nuanced analysis, can significantly advance the field of psychometric modeling.

The Nexus Between Foreign Direct Investment and Economic Growth in Malaysia

In recent decades, Foreign Direct Investment (FDI) has become a significant factor in promoting economic growth. Recent years have witnessed significant discourse regarding the relationship between foreign direct investment and economic growth. This research employed the Autoregressive Distributed Lag (ARDL) methodology to analyze the long-run and short-run relationships between foreign direct investment and economic growth in Malaysia over the period from 1990 to 2022. The findings indicate that foreign direct investment has a positive impact on economic growth in both the short and long term. This aligns with the fundamental principles of endogenous growth theory, which posits that foreign direct investment enhances the transfer of skills that enrich the knowledge base of the host country in both the short and long term. The study provides policymakers with insights regarding the relationship between economic growth and foreign direct investment (FDI).

Interlayer reinforced 3D printed concrete with recycled coarse aggregate: Shear properties and enhancement methods

In reinforced 3D printed concrete structures, the shear interaction between the rebar and the 3D printed filaments influences both the performance and safety of the concrete structures during service. In this study, the shear performance of the interlayer reinforced interface (IRI) of 3D printed concrete with recycled coarse aggregates (3DPRAC) was investigated, focusing on the pore structure characteristics of the interlayer interface. An enhancement method for the IRI was proposed by varying the number of anchored rebar nails (ARNs) and comparing the results with those of 3D printed concrete with natural coarse aggregates (3DPNAC) and 3D printed mortar (3DPM). The results showed that the ARNs significantly improved the IRI shear strength of 3DPRAC. Specifically, the IRI shear strength of 3DPRAC was 6.1% lower than that of 3DPNAC but 43.6% higher than that of 3DPM. By examining the structural characteristics of the rebar-3DPRAC bonding area, a relationship between pore defects and shear strength was established. This established relationship led to the proposal of a partition model for the interlayer bonding interface. A finite element model of 3D printed concrete incorporating real pore structure characteristics was developed to analyze the stress distribution and damage characteristics of the interface under shear stress. The fracture mode induced by local pores with the crack propagation mechanism was also analyzed. Finally, a unified formula for calculating the shear strength of the 3DPRAC IRI was derived based on the principles of virtual work and plastic limit theory. This study provides theoretical support for engineering applications of 3D-printed reinforced concrete structures.

Complex Systems and Sustainable Leadership: Enhancing Resilience and Sustainability of Community-Based Social Enterprises in Soweto, South Africa

In urban South Africa, community-based social enterprises (CBSEs) face challenges at the intersection of financial and environmental sustainability and social purpose. These enterprises address social exclusion and community development within complex institutional environments. Despite increasing governmental support, CBSEs struggle with historical inequalities, resource limitations, high poverty levels, inadequate infrastructure, and complex social dynamics. These challenges contribute to a high failure rate among SMMEs, including CBSEs, which represent approximately 71% of community-level businesses. This study examines how complex system dynamics in marginalized South African suburbs impact the sustainable leadership and resilience of CBSEs. Utilizing a qualitative approach, the study conducted 15 in-depth semi-structured interviews with CBSE leaders. The findings revealed that effective leadership in CBSEs requires extraordinary abilities to traverse complexity, adapt to changes, and engage in dynamic organizational change. The key themes identified included adaptive and flexible leadership, interdependencies and network collaboration, community engagement and co-creation, continuous learning and feedback loops, policy influence and response, and resource utilization and constraints. By applying complex systems leadership theory (CSLT) and sustainable leadership principles, the research offers insights into the mechanisms enabling CBSEs to thrive in challenging environments. These findings contribute to Social Enterprise Management and Leadership Studies, providing practical implications for policymakers and practitioners to support CBSE development and sustainability in marginalized urban communities.

Self-adaptive equation embedded neural networks for traffic flow state estimation with sparse data

The data-driven approach in intelligent traffic systems has achieved successive breakthroughs, thanks to the ever-increasing volume of traffic data. Nonetheless, in practical scenarios, the collected data often contain some issues, e.g., missing values, significantly impacting the accuracy and efficiency of the algorithms. To enhance the precision of traffic estimation utilizing the sparse data, we have developed a physics-informed neural network (PINN) based algorithm in the line with the traffic flow theory and deep learning principles. In contrast to the conventional PINNs, our approach uniquely incorporates a self-adaptive macro model for mixed flow into the network's architecture, serving as an embedded source of physics information. With this algorithm, we can capture the dynamic behavior of an entire traffic flow including its spatiotemporal evolution with sparse traffic data such as initial and boundary value information. To realize the model's adaptability, we have revised the macro model by inverting its parameters and incorporating a data-driven nonlinear element, which simplifies the intricate macro model structure. The network's effectiveness has been validated through the experiments conducted on a mixed traffic flow system experiencing local agglomeration and real-world data, demonstrating its capability for precise traffic simulation, efficient traffic flow prediction, and interpretability. Our study offers a novel insight for data-driven traffic flow state estimation.

Reflections and insights on a mindfulness, acceptance, and commitment-based (MAC) intervention with complementary Self-Determination Theory (SDT) principles delivered by a coach

This paper presents a case of implementing a MAC-based intervention, empowered by SDT principles, delivered by the coach. As the MAC-based approach becomes dominant in the sport psychology field and SDT is a leading motivational approach applied to sports coaching, a 10-session program was delivered by the head coach to a group of 28 gymnasts. The intervention included psychoeducation on core MAC principles (e.g., values, acceptance, defusion) and was guided by the coach's efforts to fulfill the basic psychological needs of autonomy, competence, and relatedness. The intervention program protocol aligned with the coach's reflections are presented in each session. In conclusion, despite some constraints, this intervention framework holds potential for contributing to youth athletes' performance, well-being, and psychological development.

STUDI KAUSALITAS MOTIVASI DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN BANK MUAMALAT KCU FATMAWATI

The aim of this research is to determine the influence of work motivation and discipline on employee performance at PT Bank Muamalat KCU Fatmawati partially and simultaneously. The method used is descriptive quantitative. The sampling technique uses a saturated sampling technique from a population of 60 as samples. The method used to test and analyze the influence partially and simultaneously uses hypothesis testing (t test and f test). This study investigates the significant impact of work discipline and work motivation on employee performance. Data analysis reveals that work discipline has a substantial influence on performance, with a contribution value of 0.933. This suggests that adherence to rules and punctuality play a crucial role in enhancing employee output, as supported by reinforcement theory and time management principles. Additionally, work motivation shows a significant effect on performance, with a contribution value of 0.672, highlighting the importance of intrinsic motivation factors, such as achievement and recognition, in driving employees to excel. The findings underscore the need for a comprehensive approach in performance management, emphasizing both the establishment of strong disciplinary practices and the cultivation of high motivation levels to optimize employee performance.

Thermal performance augmentation of microchannel using curved rectangular winglet vortex generators having rectangular perforation

This article innovatively introduces the application of punched curved rectangular wing vortex generators positioned on opposing sides of a rectangular microchannel. Through a comprehensive approach combining numerical simulations and experimental investigations, the flow dynamics and heat transfer performance of these VGs under turbulent conditions are thoroughly examined. This analysis is performed in the turbulent flow regime, specifically at Reynolds number ranging from 2500 to 3500. The governing equations are solved by using SST k-ω model. To evaluate the behavior of mixed vortices, a range of key metrics is utilized, including the Nusselt number ratio, friction coefficient ratio, and thermal enhancement factor (TEF). The study encompasses variations in opening angles (θ = 0°, 5°, 10°, 15°) and pitch ratios (PR = P/H = 15, 30, 45) to determine their impact on the overall system performance. The findings reveal that the punched curved rectangular winglet VGs effectively induce mixed vortices, leading to an enhancement in local heat transfer rates. However, the presence of fluid jets hinders the formation of other vortices. Compared to a smooth tube, the maximum TEF also experiences a 26 % rise. To validate the findings, the field synergy principle and entropy generation theory was utilized.