Mapping Principle Research Articles

Advanced analysis of cross-sectional properties in unbonded flexible risers with composite layers

ABSTRACT Unbonded flexible risers can undergo large deflection bending deformation, which is a key equipment for deep-sea oil and gas resource development. In this paper, firstly, a theoretical method for composite cylindrical and armour layers under axisymmetric load and bending moment is deduced by function principle and structural deformation characteristics. Then, the corresponding numerical model is established within ABAQUS/Explicit. After verified through experimental results, the axial compressive stiffness of the unbonded flexible riser with composite layers is studied. Furthermore, several related characteristics, including the corresponding tensile stiffness, bending stiffness of unbonded flexible riser and fibre proportion of composite layer are discussed. Finally, taking the bearing axial compression capacity of cylindrical layer into consideration, the compressive failure is studied.

Stability analysis of nonlinear Riemann-Liouville fractional differential equations

In this paper, we give sufficient conditions to guarantee the asymptotic stability of the zero solution to a kind of nonlinear fractional differential equations with the Riemann Liouville fractional derivative of order α∈(n-1,n) by using Krasnoselskii's fixed point theorem and the Banach contraction mapping principle in a weighted Banach space. The results obtained here extend the work of Li and Kou [6].

Interpolative Berinde Weak Cyclic Contraction Mapping Principle

Interpolative Berinde Weak Cyclic Contraction Mapping Principle

Study on the modulation mechanism of the optoelectronic properties based on common electrode metal atom adsorption on graphene/MoTe2.

The two-dimensional graphene/MoTe2 heterostructure holds extensive potential applications in optoelectronic devices, sensors, and catalysts. To expand its optical applications, this study systematically investigates the adsorption stability of metal atoms (Au, Pt, Pd, and Fe) on the graphene/MoTe2 and their influence on its optoelectronic properties employing first-principles methods. The findings indicate that after the adsorption of Au and Pd, the structure retains its direct bandgap properties, while the adsorption of Pt and Fe exhibits indirect bandgap characteristics. The work functions for all adsorbed structures are lower compared to the pristine graphene/MoTe2. The total density of states is primarily derived from the C-2p, Mo-4d, Te-5p orbitals, as well as the d and s orbitals of the adsorbed atoms. The pristine graphene/MoTe2 exhibits significant absorption in the ultraviolet range. Once graphene/MoTe2 is adsorbed by metal atoms, it can significantly enhance the optical absorption across the spectrum from infrared to ultraviolet light. These findings provide important theoretical guidance for regulating the application of graphene/MoTe2 in optoelectronics and related fields. All analyses are grounded in density functional theory first principles and computed using CASTEP. Graphene/MoTe2 consists of 4 × 4 × 1 single-layer, graphene single layer, and 3 × 3 × 1 single-layer MoTe2. To prevent interactions between neighboring unit cells, a 20Å vacuum space in the z-direction is employed. The electronic exchange-correlation interactions are treated using the Perdew-Burke-Ernzerhof functional within the framework of the generalized gradient approximation. Van der Waals (vdW) interactions are incorporated using the vdW correction function proposed by Grimme, which effectively describes vdW interactions. During the simulation, the cutoff energy for plane wave expansion is set to 420eV, and the k-point grid is set to 4 × 4 × 1. The atomic displacement convergence standard is 0.002Å, the internal stress convergence standard is 0.1GPa, and the interaction force convergence standard between atoms is 0.05eV/Å. The convergence threshold for the iteration precision is set to ensure that the total energy for each atom is not less than 2 × 10-5eV/atom.

Situational Analysis of Power in Participatory Action Research: Mapping Systemic Frameworks, Discourses, and Principles for Critical Feminist Qualitative Inquiry

In this current context, critical epistemologies, methodologies, and frameworks like Participatory Action Research (PAR), decolonial theory, and situational analysis can provide relevant tools for critical feminist social work research and praxis to expose and reenvision harmful, extractive, and privatized knowledge generation and dissemination. In this article, I describe the possibilities for using critical situational analysis to promote critical feminist social work scholarship through the interrogation of colonial forms of knowledge production, recognition of enactments of refusal and resistance, and illustrations of situational mapping from a study focused on exploring power differentials within PAR collaborations among social work faculty and community stakeholders. I then discuss possibilities to incorporate these analytic qualitative methodologies and frameworks to promote critical feminist principles for critical qualitative inquiry.

A review of RNA nanoparticles for drug/gene/protein delivery in advanced therapies: Current state and future prospects.

Nanotechnology involves the utilization of materials with exceptional properties at the nanoscale. Over the past few years, nanotechnologies have demonstrated significant potential in improving human health, particularly in medical treatments. The self-assembly characteristic of RNA is a highly effective method for designing and constructing nanostructures using a combination of biological, chemical, and physical techniques from different fields. There is great potential for the application of RNA nanotechnology in therapeutics. This review explores various nano-based drug delivery systems and their unique features through the impressive progress of the RNA field and their significant therapeutic promises due to their unique performance in the COVID-19 pandemic. However, a significant hurdle in fully harnessing the power of RNA drugs lies in effectively delivering RNA to precise organs and tissues, a critical factor for achieving therapeutic effectiveness, minimizing side effects, and optimizing treatment outcomes. There have been many efforts to pursue targeting, but the clinical translation of RNA drugs has been hindered by the lack of clear guidelines and shared understanding. A comprehensive understanding of various principles is essential to develop vaccines using nucleic acids and nanomedicine successfully. These include mechanisms of immune responses, functions of nucleic acids, nanotechnology, and vaccinations. Regarding this matter, the aim of this review is to revisit the fundamental principles of the immune system's function, vaccination, nanotechnology, and drug delivery in relation to the creation and manufacturing of vaccines utilizing nanotechnology and nucleic acids. RNA drugs have demonstrated significant potential in treating a wide range of diseases in both clinical and preclinical research. One of the reasons is their capacity to regulate gene expression and manage protein production efficiently. Different methods, like modifying chemicals, connecting ligands, and utilizing nanotechnology, have been essential in enabling the effective use of RNA-based treatments in medical environments. The article reviews stimuli-responsive nanotechnologies for RNA delivery and their potential in RNA medicines. It emphasizes the notable benefits of these technologies in improving the effectiveness of RNA and targeting specific cells and organs. This review offers a comprehensive analysis of different RNA drugs and how they work to produce therapeutic benefits. Recent progress in using RNA-based drugs, especially mRNA treatments, has shown that targeted delivery methods work well in medical treatments.

Reviving functionalism: Applying translation-oriented text analysis to synthetic text (editing)

This paper investigates the potential application of translation-relevant text analysis. Rooted in the functionalist approach and Skopos theory, the translation-relevant text analysis is seen as instrumental in translation education for assessing the quality of synthetic text output for translation purposes (MT and/or AI) and improving (post-)editing performance relating to said output. Despite recent advancements in machine translation and the partially self-professed potential of AI models, accurately conveying the intended function of the target text remains a challenge in professional translation practices. This paper argues that salvaging functionalist theory can benefit both translator education and, ultimately, professional translation practices. To support this argument, three use cases are presented in which the key principles of functionalism and Skopos theory are applied to develop critical text analysis skills necessary for handling and editing synthetic text. Keywords: Functionalism, Translation Technology, Machine Translation, Generative Artificial Intelligence, Post-editing

On solution of non-linear FDE under tempered Ψ−Caputo derivative for the first-order and three-point boundary conditions

In this article, the existence and uniqueness of solutions for non-linear fractional differential equation with Tempered Ψ−Caputo derivative with three-point boundary conditions were studied. The existence and uniqueness of the solution were proved by applying the Banach contraction mapping principle and Schaefer’s fixed point theorem.

On Solving Linear Complementarity Problem using Principal Pivoting Method

Objectives: A rudimentary framework called the linear complementarity problem (LCP) describes a wide range of real-world scenarios in which equilibrium conditions must be met while adhering to constraints. Methods: This study presents the Principal Pivoting Method (PPM), a novel method for solving linear Complementarity problems. PPM is a viable substitute for addressing large-scale complementarity problems. It is a powerful method for handling large-scale challenge circumstances while addressing LCPs. The PPM uses a principle-based pivoting strategy to navigate the solution space. It terminates in a finite number of iterations. It deals with degenerate cases. Findings: Under specific hypotheses, the PPM is guaranteed to converge to a solution if one exists. PPM's pivoting methods account for its numerical stability. In this paper, the process is analyzed using real-life scenarios. The algorithm goes with initialization, iteration, and termination. To ensure numerical stability, a pivot element is selected. Update the basis matrix through pivotal operations. The iterations show how well the algorithm goes perfectly without causing any wrongdoing. Using this method, the solution is obtained accurately in a smaller number of iterations. Novelty: A novelty of the work is finding a solution to a real-life application problem using this method. The comparison of my research work with the existing research work is a novel approach to illustrate the Principal Pivoting method in practical applications. Here, the crisp values are converted into intuitionistic triangular fuzzy numbers for analyzing data in real-life scenarios. This is a novel way to attempt a newly considered problem, which is taken as fuzzy coefficients transforming into a linear complementarity problem. Fuzzy arithmetic operations on the Function principle are utilized. The numerical trials proved the efficacy of the suggested algorithm. Keywords: Fuzzy Linear Complementarity Problem (FLCP), Principle Pivoting Method (PPM), Intuitionistic Fuzzy set (IFS), Triangular Intuitionistic Fuzzy Number (TIFN)

Sensor-Based Innovations in Petrol Adulteration Detection: A Comprehensive Review

Fuel adulteration is a persistent problem that has serious repercussions for engine performance, economic stability, and environmental sustainability. Maintaining fuel quality and guaranteeing adherence to legal requirements depend on the ability to detect adulteration in petrol. Sensorbased detection systems provide a sophisticated, effective, and real-time substitute for conventional detection techniques like chemical analysis and physical inspection, which are frequently laborious, non-portable, and resource-intensive. The utilization of sensor technologies in gasoline adulteration detection is the main topic of this review, with a focus on load cell and dielectric constant sensors in particular. Dielectric constant sensors, which have a high sensitivity and dependability, use variations in the electrical characteristics of fuel mixes to identify the presence of adulterants. By measuring weight and density changes, load cell sensors, on the other hand, make it possible to identify density differences brought on by adulteration. When combined, these sensors offer a strong foundation for precise and effective adulteration detection. The principles of functioning of these sensors, their incorporation into detecting systems, and the performance metrics—such as sensitivity, accuracy, portability, and cost-efficiency—that characterize their efficacy are all examined in this study. Recent developments in sensor technologies that have enhanced real-time monitoring and decreased system complexity are also highlighted. In addition, the research highlights important issues that need to be resolved to improve the realistic implementation of these systems, including scalability, environmental adaptation, and integration with IoT frameworks

Theoretical system of levels of constructing vehicle movement of ground urban electric transport vehicle

Digitalization of the transport industry and the use of artificial intelligence technologies in the automation of control of its main processes determine the need to search for new approaches to the description of electrical complexes and systems of transport purpose, their internal and external system properties. The public ground urban electric transport system is considered as a complex process of conversion, transmission and use of electrical energy and information in the electrical complex of urban electric transport, manifested in the organization of controlled movement of vehicles in specific conditions of production tasks and technology of passenger transportation. Based on the synergetic description of the properties, principles of organization and functioning of a complex production and technical system of urban electric transport, the controlled movement of vehicles has been presented as a multilevel technological process implemented by the electrical complex of urban electric transport. It has been proved that the basis of this process, formed by 5 hierarchically arranged levels, each of which provides a separate specific task of building the movement of vehicles, is the implementation of algorithms of traction electrical equipment. A theoretical system of levels of vehicle motion construction as a multilevel process has been formulated, mathematical models of each level have been identified, and sets of conditions characterizing "external" and "internal" "order parameters" defining hierarchical interlevel interrelations have been determined. The results of the work may be of interest to the developers of control systems of autonomous vehicles and driver assistance systems during the selection and justification of algorithms for the effective control of the electrical complex of traction electrical equipment of urban electric transport.

An Extended Fitts’ Law Model for Hand Interaction Evaluation in Virtual Reality: Accounting for Spatial Variables in 3D Space and the Arm Fatigue Influence

Fitts’ law is a standard tool for assessing user performance and interaction device effectiveness in human-computer interaction (HCI). However, it disregards spatial variables in 3D space and arm fatigue impacts. To address these limitations in evaluating hand interaction performance in virtual reality (VR), a target pointing and acquisition experiment was conducted in which two mapping principles of hand movements (translation, angular rotation) and two interaction methods (hand controller, freehand) were compared. The results indicated that (1) in target acquisition, azimuth and inclination angles exhibited a sinusoidal relationship with hand movement time (MT); (2) arm fatigue significantly affected MT, demonstrating an exponential relationship with task duration; (3) in the case of translational movement mapping, freehand interaction exhibited less influence from fatigue compared to controller interaction; while (4) in the angular rotation mapping case, controller pointing demonstrated greater stability, with fewer declines in efficiency than freehand pointing. Based on the findings, new model formulations were developed to accommodate varying conditions.

The biogenesis and regulation of animal microRNAs.

MicroRNAs (miRNAs) are small, yet profoundly influential, non-coding RNAs that base-pair with mRNAs to induce RNA silencing. Although the basic principles of miRNA biogenesis and function have been established, recent breakthroughs have yielded important new insights into the molecular mechanisms of miRNA biogenesis. In this Review, we discuss the metazoan miRNA biogenesis pathway step-by-step, focusing on the key biogenesis machinery, including the Drosha-DGCR8 complex (Microprocessor), exportin-5, Dicer and Argonaute. We also highlight newly identified cis-acting elements and their impact on miRNA maturation, informed by advanced high-throughput and structural studies, and discuss recently discovered mechanisms of clustered miRNAprocessing, target recognition and target-directed miRNA decay (TDMD). Lastly, we explore multiple regulatory layers of miRNA biogenesis, mediated by RNA-protein interactions, miRNA tailing (uridylation or adenylation) and RNA modifications.

Performance iterative learning control on nonlinear systems for tracking varying-scale and morphologically similar targets

This paper proposes a novel three-dimensional (3D) performance iterative learning control (PILC) scheme on nonlinear systems for tracking varying-scale and morphologically similar targets. The condition and performance weighted K-nearest neighbour (KNN) and the historical database update algorithms are developed to match the historical control inputs closest to the current operating conditions, and further realise the learning process along the performance domain. The control inputs of the PILC scheme can be updated by utilising the control information obtained from the time, iteration and performance dimensions. Also, the convergence property of the proposed framework is proved via the contraction mapping principle. Finally, compared with the existing ILC works, the illustrative simulation and experimental results are presented to illustrate that the PILC scheme has better tracking performance and robustness, smaller initial error, and faster convergence speed.

Some aspects of a coupled system of nonlinear integral equations

In the present work we take a system of two integral equations and prove the existence and uniqueness of their solution. We investigate four aspects of the problem, namely, error estimation and rate of convergence of the iteration leading to the solution, Ulam-Hyers stability, well-posedness and data dependence of the solution sets. We give some new de nitions pertaining to the system we analyze here. In order to establish our results we utilize the coupled contraction mapping principle due to Bhaskar and Lakshmikantham (Nonlinear Anal. TMA 65(2006), 1379-1393) and several related results which we deduce here.

CONCEPTUAL DESIGN OF A WEARABLE TELEREHABILITATION SYSTEM FOR SEGMENTAL RESPIRATORY

In this study, it was aimed to support the patients to segmental breathing exercises in people with respiratory system disorders; easy to use, allowing for individual use. It is aimed to design a device integrated with telerehabilitation in accordance with engineering design and rehabilitation engineering design approaches. Within the scope of conceptual design, a list of requirements for the design was created. Functional structures and solution principles of the device were determined. Design variants were created and were evaluated. Structures of the final solution variant and 3D drawings of the design were created. Our design has effective and appropriate equipment that can increase the respiratory capacity of patients and contribute to rehabilitation in the home environment thanks to telerehabilitation application.

A novel proposition of radiation energy conservation in radiation dose deformation using deformable image registration

Objective. The purpose of this study is to analytically derive and validate a novel radiation energy conservation principle for dose mapping via deformable image registration (DIR).Approach. A radiation energy conservation principle for the DIR-based dose-deforming process was theoretically derived with a consideration of the volumetric Jacobian and proven using synthetic examples and a patient case. Furthermore, an energy difference error was proposed that can be used to evaluate the DIR-based dose accumulation uncertainty. For the analytical validation of the proposed energy conservation principle, a synthetic isotropic deformation was considered, and artificial deformation uncertainties were introduced. For the validation with a patient case, a ground truth set of computed tomography images and the corresponding deformation was generated. Radiation energy calculation was performed using both the ground truth deformation and another deformation with uncertainty.Main results. The suggested energy conservation principle was preserved with uncertainty-free deformation, but not with error-containing deformations using both the synthetic examples and the patient case. For a synthetic example with a tumor volume reduction of 27.1% (10% reduction in length in all directions), the energy difference error was calculated to be -29.8% and 37.2% for an over-deforming and under-deforming DIR uncertainty of 0.3 cm. The energy difference error for the patient case (tumor volume reduction of 37.6%) was 2.9% for a displacement vector field with a registration error of 2.0 ± 3.2 mm.Significance. A novel energy conservation principle for DIR-based dose deformation and the corresponding energy difference error were mathematically formulated and successfully validated using simple synthetic examples and a patient example. With a consideration of the volumetric Jacobian, this investigation proposed a radiation energy conservation principle which can be met only with uncertainty-free deformations.

СМЫСЛООБРАЗОВАНИЕ В ТЕКСТАХ КУЛЬТУРЫ ПОСРЕДСТВОМ ИНТЕРТЕКСТУАЛЬНОСТИ

In the article, intertextuality is considered as a technique of meaning formation in cultural texts that carry a semantic load. The process of meaning formation in cultural texts is considered in various humanities from different approaches, the techniques of meaning formation are substantiated. The concept of intertextual meaning formation in cultural texts is proposed, based on a dialogue between texts mediated by human consciousness on the basis of existing connections, historically conditioned or stipulated by the author himself. In the process of interaction of cultural texts, new semantic constructs, semantic spheres are formed. The principles of intertextual meaning formation are highlighted, among which: the principle of dialogicity, the principle of misinterpretation, the principle of functionality. The concept of intertextual meaning formation is based on the interpretation (understanding) of the text of culture. The author formulates the concept of «marginal meaning of the text of culture», by which he understands the products of meaning formation obtained as a result of the interaction of cultural texts based on intertextual connections that arise at the boundaries of these texts. Intertextual sense formation is considered as a process of formation of value meanings as a result of the emergence of semantic structures derived from activity, unfolding in a certain context, as a result of intertextual communication, as a result of connecting new objects to the existing system of semantic connections.

Disentangling the response of species diversity, forest structure, and environmental drivers to aboveground biomass in the tropical forests of Western Ghats, India

Tropical forests are crucial to the global carbon cycle, but a significant knowledge gap in the precise distribution patterns of forest aboveground biomass (AGB) hinders our ability to formulate effective conservation efforts. A key unresolved issue is the lack of understanding of how forest AGB interacts with biotic and abiotic factors on large spatial scale. To address this, we used Structural Equation Modeling to disentangle the direct and indirect effects of environmental, anthropogenic, structural diversity species diversity and edaphic factors on AGB of trees, lianas and regenerating communities using the data from 96 1-ha plots in the central Western Ghats biodiversity hotspot, India. We hypothesized that the effect of structural attributes overrides AGB distribution, with relative contributions varying among plant communities. The landscape-level mean AGB was 245.12 ± 19.74 Mg ha−1, with SEM explaining 68–85 % of variations across the three vegetation communities. Structural diversity emerged as the primary mediator of the positive effects of taxonomic diversity on AGB in the regeneration community, whereas canopy cover and stem density linked diversity to AGB in adult tree and liana communities. Further, AGB showed a positive association with soil organic carbon in adult tree and regeneration communities, underscoring the significance of belowground resource availability on AGB. The results indicate that structural features were consistently the strongest AGB predictors at all levels of data aggregation, indicating the predominant role of niche complementarity and efficient space utilization in driving AGB, albeit differently across the plant communities. Our study emphasizes the importance of maintaining high structural features and managing taxonomic diversity while promoting soil fertility and minimizing disturbances to support AGB in tropical forests. We recommend testing the effects of predictor variables on biomass of vegetation communities independently to better understand the ecological principles of forest functioning.

Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic-assisted total knee arthroplasty.

Predictive models help determine predictive factors necessary to improve functional outcomes after total knee arthroplasty (TKA). However, no study has assessed predictive models for functional outcomes after TKA based on the new concepts of personalised surgery and new technologies. This study aimed to develop and evaluate predictive modelling approaches to predict the achievement of minimal clinically important difference (MCID) in patient-reported outcome measures (PROMs) 1 year after TKA. Four hundred thirty robotic-assisted TKAs were analysed in this retrospective study. The mean age was 67.9 ± 7.9 years; the mean body mass index (BMI) was 32.0 ± 6.8 kg/m2. The following PROMs were collected preoperatively and 1-year postoperatively: knee injury and osteoarthritis outcome score for joint replacement, Western Ontario and McMaster Universities osteoarthritis index (WOMAC) Function, WOMAC Pain. Demographic data, preoperative CT scan, implant size, implant position on the robotic system and characteristics of the joint replacement procedure were selected as predictive variables. Four machine learning algorithms were trained to predict the MCID status at 1-year post-TKA for each PROM survey. 'No MCID' was chosen as the target. Models were evaluated by class discrimination (F1-score) and area under the receiver operating characteristic curve (ROC-AUC). The best-performing model was ridge logistic regression for WOMAC Function (area under the curve [AUC] = 0.80, F1 = 0.48, sensitivity = 0.79, specificity = 0.62). Variables most strongly contributing to not achieving MCID status were preoperative PROMs, high BMI and femoral resection depth (posterior and distal), supporting functional positioning principles. Conversely, variables contributing to a positive outcome (achieving MCID) were medial/lateral alignment of the tibial component, whether the procedure was an outpatient surgery and whether the patient received managed Medicare insurance. The most predictive variables included preoperative PROMs, BMI and surgical planning. The surgical predictive variables were valgus femoral alignment and femoral rotation, reflecting the benefits of personalised surgery. Including surgical variables in predictive models for functional outcomes after TKA should guide clinical and surgical decision-making for every patient. Level III.