Transformation Method Research Articles

ADP-based fault-tolerant consensus control for multiagent systems with irregular state constraints

This paper investigates the consensus control issue for nonlinear multiagent systems (MASs) subject to irregular state constraints and actuator faults using an adaptive dynamic programming (ADP) algorithm. Unlike the regular state constraints considered in previous studies, this paper addresses irregular state constraints that may exhibit asymmetry, time variation, and can emerge or disappear during operation. By developing a system transformation method based on one-to-one state mapping, equivalent unconstrained MASs can be obtained. Subsequently, a finite-time distributed observer is designed to estimate the state information of the leader, and the consensus control problem is transformed into the tracking control problem for each agent to ensure that actuator faults of any agent cannot affect its neighboring agents. Then, a critic-only ADP-based fault tolerant control strategy, which consists of the optimal control policy for nominal system and online fault compensation for time-varying addictive faults, is proposed to achieve optimal tracking control. To enhance the learning efficiency of critic neural networks (NNs), an improved weight learning law utilizing stored historical data is employed, ensuring the convergence of critic NN weights towards ideal values under a finite excitation condition. Finally, a practical example of multiple manipulator systems is presented to demonstrate the effectiveness of the developed control method.

Solvent-Free Synthesis of Bioactive Heterocycles

: The main emphasis of green chemistry is to reduce environmental pollution. Its main goal is to adopt a cost-effective and harmless strategy for human health and the environment. The green synthetic routes have succeeded in adopting solvent-free conditions as an effective tool for sustainability. Heterocycles are organic compounds that are widely distributed by nature. Many of them possess medicinal and pharmacological properties, as this heterocyclic moiety is found in many drugs. The solvent-free strategies for the Synthesis of bioactive heterocycles are, now-adays, regarded as an important objective. Solvent-free reactions are eco-friendly, cost-effective, and an environmentally benign route in organic transformation methods because of their effi-ciency, reduced reaction time, and high yields, thereby saving energy. This mini-review focuses on the environmentally benign solvent-free Synthesis of heterocycles and their potential pharma-cological applications.

Solving Fuzzy Delay Differential Equations using Fuzzy Elzaki Transform and Fuzzy Elzaki Decomposition Method

Objective: In this work, the fuzzy Elzaki transform and fuzzy Elzaki decomposition method are used to solve fuzzy delay differential equations. The fuzzy Elzaki decomposition method is a combination of the fuzzy Elzaki transform and Adomian decomposition method in a fuzzy environment. The use of transforms in solving differential equations makes the solution process simpler. Methodology: The fuzzy Elzaki transform is applied in the fuzzy delay differential equation. The nonlinear terms are decomposed using Adomian polynomials in a nonlinear fuzzy delay differential equation. In the transformed domain, the resulting algebraic equation is solved. The solution in the original time domain is obtained by applying the inverse Elzaki transform. Findings: The fuzzy Elzaki transform and fuzzy Elzaki decomposition method are useful for handling the complexities associated with fuzzy functions and delays in differential equations. The technique used to solve the fuzzy delay differential equation gives results with better accuracy compared to the exact solution. The applicability of the method is illustrated with numerical examples. Novelty: The Elzaki transform is a helpful tool for solving delay differential equations with discontinuities. For the resilient solution of complicated differential equations, especially those including nonlinearity and fuzzy logic, the fuzzy Elzaki decomposition approach is useful. It gives an organized way to find the solution to fuzzy delay differential equation by utilizing the advantages of both the Elzaki transform and the Adomian decomposition method in a fuzzy situation. Keywords: Triangular Fuzzy Number, Fuzzy Elzaki Transform, Adomian decomposition method, Fuzzy Elzaki decomposition method, Fuzzy Delay Differential Equations (FDDE)

Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network.

The current study concentrates on the planning (sitting and sizing) of a renewable integrated energy system that incorporates power-to-hydrogen (P2H) and hydrogen-to-power (H2P) technologies within an active distribution network. This is expressed in the form of an optimization model, in which the objective function is to reduce the annual costs of construction and maintenance of integrated energy systems. The model takes into account the planning and operation model of wind, solar, and bio-waste resources, as well as hydrogen storage (a combination of P2H, H2P, and hydrogen tank), and the optimal power flow constraints of the distribution network. Electrical and hydrogen energy are administered in an integrated energy system. The modeling of the uncertainties regarding the quantity of load and renewable resources is achieved through stochastic optimization using the Unscented Transformation method. The novelties of the scheme include the sizing and placement of a combined hydrogen and power-based renewable integrated energy system, the consideration of the impacts of bio-waste units, P2H, and H2P systems on the planning of the integrated energy system and the operation of the active distribution network, and the modeling of uncertainties using the Unscented Transformation method to reduce the calculation time. The study's results demonstrate the scheme's ability to improve the technical conditions of the distribution network by considering the optimal planning of integrated energy systems. In comparison to the network power flow, the operation status of the network has been improved by approximately 23-45% through the optimal siting, sizing, and energy management of hydrogen storage equipment, as well as renewable resources in the form of integrated energy systems. In other words, optimal energy management and planning of the integrated energy systems in the distribution network has been able to reduce energy losses and voltage drop by 44.5% and 42.4% compared to the load flow studies. In this situation, peak load carrying capability has increased by about 23.7%. In addition, compared to the case of the network with renewable resources, the overvoltage has decreased by about 43.5%. Also, Unscented Transformation method has a lower calculation time than scenario-based stochastic optimization.

The interaction between a piezoelectric screw dislocation and collinear rigid lines in one-dimensional hexagonal quasicrystals

The interaction between a piezoelectric screw dislocation and collinear rigid lines in one-dimensional (1D) hexagonal quasicrystals (QCs) under anti-plane mechanical and in-plane electrical loading is analysed. Two idealized electrical assumptions, namely electrically conductive and dielectric, are considered. By using Muskhelishvilid’s complex transformation method, the explicit expressions for the field variables, the singularity of the field variables at the line tip and the force on the dislocation are obtained for a single rigid line. Based on the generalized Peach–Koehler formula, the generalized stress intensity factors and image force on dislocations in piezoelectric quasicrystal (PQC) are obtained. It is evident that the existence of phason field has an effect on image force.

OPTIMISATION OF STRATEGIES FOR WORKING WITH COUNTERPARTIES AND RISK MANAGEMENT AT UTILITY INFRASTRUCTURE ENTERPRISES

The objective of this paper is to examine and enhance strategies for managing relationships with counterparties and mitigating risks in utility infrastructure enterprises. The paper seeks to analyse contemporary approaches and challenges faced by these enterprises, offering recommendations for improving their strategies in counterparty interactions and risk management. Ultimately, the goal is to enhance operational stability, competitiveness, and sustainable development in a dynamic business environment. Methodology. The research presents a critical review and analysis of the existing risk management and counterparty strategies employed by utility infrastructure enterprises. The methodology comprises an examination of current practices, the identification of key problems, and an evaluation of modern approaches, including digital transformation, process automation, and innovative management methods. By synthesising existing research and case studies, the paper identifies the strengths and weaknesses of various strategies and recommends improvements. Results. The analysis identified several key challenges faced by utilities in managing counterparties and risks, including inadequate risk management systems, outdated business processes and poor communication. Process automation, digital transformation and improved stakeholder integration are identified in the document as critical factors for optimising operations. It also emphasises the importance of careful selection of counterparties, performance monitoring and staff development to mitigate risks and foster better partnerships. Practical implications. The recommendations set forth in the paper provide actionable strategies for utility infrastructure enterprises to optimise their management of counterparties and risks. The implementation of these strategies, including the utilisation of digital tools, enhanced internal communication and a focus on staff development, can facilitate improvements in efficiency, risk management and long-term sustainability for utility companies. These recommendations are particularly beneficial for those in managerial or decision-making roles who are seeking to navigate the complexities of a rapidly evolving business environment. Value / Originality. This paper makes a significant contribution to the field by offering a comprehensive analysis of the strategies available for optimising counterparty relations and risk management in the utility sector. The value of this approach lies in its integration of modern technological solutions with traditional risk management practices. By offering practical, research-based recommendations, the paper addresses current gaps in the literature and provides new insights into how utility enterprises can better manage both internal and external challenges.

A hypergraph transformer method for brain disease diagnosis

ObjectiveTo address the high-order correlation modeling and fusion challenges between functional and structural brain networks.MethodThis paper proposes a hypergraph transformer method for modeling high-order correlations between functional and structural brain networks. By utilizing hypergraphs, we can effectively capture the high-order correlations within brain networks. The Transformer model provides robust feature extraction and integration capabilities that are capable of handling complex multimodal brain imaging.ResultsThe proposed method is evaluated on the ABIDE and ADNI datasets. It outperforms all the comparison methods, including traditional and graph-based methods, in diagnosing different types of brain diseases. The experimental results demonstrate its potential and application prospects in clinical practice.ConclusionThe proposed method provides new tools and insights for brain disease diagnosis, improving accuracy and aiding in understanding complex brain network relationships, thus laying a foundation for future brain science research.

Rapid parameter estimation for merging massive black hole binaries using continuous normalizing flows

Abstract Detecting the coalescences of massive black hole binaries (MBHBs) is one of the primary targets for space-based gravitational wave observatories such as laser interferometer space antenna, Taiji, and Tianqin. The fast and accurate parameter estimation of merging MBHBs is of great significance for the global fitting of all resolvable sources, as well as the astrophysical interpretation of gravitational wave signals. However, such analyses usually entail significant computational costs. To address these challenges, inspired by the latest progress in generative models, we explore the application of continuous normalizing flows (CNFs) on the parameter estimation of MBHBs. Specifically, we employ linear interpolation and trig interpolation methods to construct transport paths for training CNFs. Additionally, we creatively introduce a parameter transformation method based on the symmetry in the detector’s response function. This transformation is integrated within CNFs, allowing us to train the model using a simplified dataset, and then perform parameter estimation on more general data, hence also acting as a crucial factor in improving the training speed. In conclusion, for the first time, within a comprehensive and reasonable parameter range, we have achieved a complete and unbiased 11-dimensional rapid inference for MBHBs in the presence of astrophysical confusion noise using CNFs. In the experiments based on simulated data, our model produces posterior distributions comparable to those obtained by nested sampling.

Advancing Non-Linear PDE’s Solutions: Modified Yang Transform Method with Caputo-Fabrizio Fractional Operator

Abstract In many physical processes, nonlinear PDEs have a crucial role. This paper presents a novel approach named as Modified Yang Transform (MYT) that combines an integral transform with the decomposition technique. This approach uses Yang transform and Adomian decomposition method to solve nonlinear fractional order PDEs. Nonlinear PDEs of fractional order are considered in the Caputo-Fabrizio sense. This work presents Convergence analysis of the modified Yang transform to nonlinear fractional order PDEs. Additionally, a solution framework to solve the nonlinear PDEs is carried out and some examples are provided to highlight the application of the current method.
To illustrate how the solution operates for various fractional orders, 2D and 3D graphs are plotted. After each example, the results and discussion section is included to explain the graphs and their results.

Enhancing biological system engineering realisation through advanced feature transfer and extenics: a bionic design approach

During the process of bionic design, the discrepancies between biological systems and engineering systems often result in designers being unable to handle the knowledge involved in biological systems effectively, thereby leading to a low utilisation rate of biological knowledge. This study proposes a model for the transformation of biological systems to engineering systems on the basis of feature transfer. First, the basic system is determined according to user requirements, followed by the search for suitable biological systems and the performance of similarity analysis. Second, the element model of extenics is used to represent biological systems, and the extension analysis method is used to extend biological systems. Then, on the basis of substance-field theory in TRIZ combined with the extension transformation method, three approaches for transforming biological systems into engineering systems are proposed: no processing, forward processing, and reverse processing. After transformation, the features of the engineering system are extracted and incorporated into the basic system to complete the structural design. The container bag outlet folding device is taken as an engineering case to validate the effectiveness of the proposed model.

Optimization of ultrasound-mediated DNA transfer for bacteria and preservation of frozen competent cells.

Plasmid transformation is widely applicable in gene expression and modification. As an efficient, non-invasive, and gentle method of transformation, ultrasonic transformation provides a novel approach for strain modification. This research presents new strategies for enhancing transformation efficiency and lays the groundwork for expanding the utilization of ultrasonic transformation.

Static and Transient Response Analysis of Arbitrary Laminated Composite and Sandwich Shells by the FSDT Meshless Method

This paper, for the first time, presents a novel meshless method based on the first-order shear deformation theory (FSDT) and moving-least squares (MLS) approximation to carry out static and transient response analysis on arbitrary laminated and sandwich shell structures. The novelty of the method lies in the implementation of MLS in the curvilinear shell formulation, and the derivation of meshless governing equations on the static and transient response of arbitrary laminated and sandwich shells according to the principle of minimum potential energy and Hamilton’s principle, respectively. The concept of a Convected coordinate system is adopted to deal with arbitrary curvilinear surfaces. Both the position and displacement vectors of shells are approximated by MLS, which is conceptually the same procedure as that in the isoparametric finite element method (FEM). The numerical integration of the stiffness matrices is conducted by the simple Gaussian integral in the Convected coordinate system. Because the moving-least squares (MLS) approximation does not satisfy the Kronecker delta condition, the full transformation method is used to modify the meshless governing equations. Numerical examples are calculated to investigate the static and transient response analysis of laminated and sandwich structures with different geometrical shell shapes, including square plates, spherical shells, doubly-curved shells, and cylindrical shells. The numerical tests show that the proposed method is reliable, and robust and produces accurate results compared to the analytical and numerical solutions taken from the previous literature.

HoloLume: Point-of-Application Holographic Imaging Solution

Abstract Digital holographic imaging has emerged as a label-free, non-invasive, and powerful tool, offering a transformative method for the real-time investigation of morphology, density, and other physical and mechanical features of biological and non-biological samples. The rapid development of these portable, economical imaging systems for clinical/non-clinical setups, especially in remote areas, is of great interest. These systems are early point-of-care applications in diagnosis, research, education, and training. This article reports a general-purpose, fully automated portable imaging tool, "HoloLume," that offers high-resolution 3D imaging that facilitates the comprehensive understanding and analysis of different biological/non-biological samples. The proposed microscopic system HoloLume realizes the interferogram generation of samples using common-path optics configuration with Fresnel biprism, and its motorized stage precisely scans the whole sample with a step of 3.87 μm for quick identification of the region of interest, which makes sure a time-efficient and robust analysis. The prototype, assembled from off-the-shelf components, costs approximately USD 1700 and weighs around 3 kg. To validate and verify the performance of the HoloLume microscope, we have conducted experiments on both non-biological and biological samples. Thus, its non-invasive nature, high temporal stability, and economical lightweight prototyping make it an ideal choice for hands-on learning and quantitative analysis, reducing the need for time-consuming sample preparation and conventionally expensive microscopic systems. Furthermore, the adaptability of the proposed imaging tool to remote environments ensures wider accessibility and its easy integration with other imaging modalities enables the user to gain insight into advanced research and diagnostics.

An optimal transformation method for inferring ocean tracer sources and sinks

Abstract. The geography of changes in the fluxes of heat, carbon, freshwater and other tracers at the sea surface is highly uncertain and is critical to our understanding of climate change and its impacts. We present a state estimation framework wherein prior estimates of boundary fluxes can be adjusted to make them consistent with the evolving ocean state. In this framework, we define a discrete set of ocean water masses distinguished by their geographical, thermodynamic and chemical properties for specific time periods. Ocean circulation then moves these water masses in geographic space. In phase space, geographically adjacent water masses are able to mix together, representing a convergence, and air–sea property fluxes move the water masses over time. We define an optimisation problem whose solution is constrained by the physically permissible bounds of changes in ocean circulation, air–sea fluxes and mixing. As a proof-of-concept implementation, we use data from a historical numerical climate model simulation with a closed heat and salinity budget. An inverse model solution is found for the evolution of temperature and salinity that is consistent with “true” air–sea heat and freshwater fluxes which are introduced as model priors. When biases are introduced into the prior fluxes, the inverse model finds a solution closer to the true fluxes. This framework, which we call the optimal transformation method, represents a modular, relatively computationally cost-effective, open-source and transparent state estimation tool that complements existing approaches.

Impact of Collaborative Nursing Care on Health Outcomes of Mental Health Day Hospital Users: A Mixed Methods Study.

Given that recovery-oriented care focuses on empowering individuals with mental health challenges, collaborative care can be an effective tool for nurses in mental health day hospitals. To deepen knowledge about the impact of collaborative nursing care for improving health outcomes of mental health day hospital users. A sequential and transformative mixed methods study was designed. In the first phase of this mixed methods study, quantitative data were collected from 144 users of mental health day hospitals. In phase two, a group of users underwent an intervention based on collaborative nursing care, through participatory action research, and qualitative data were collected. Finally, quantitative data were again collected from all users. The users who participated in the intervention group improved quantitatively in terms of the quality of the therapeutic relationship. They also improved at different stages of the recovery process, thus the qualitative results confirmed that collaborative nursing care was an essential component in their recovery process. The findings highlight the critical role of collaborative nursing care in health outcomes. The therapeutic relationship was identified as a key factor in facilitating patient empowerment. The study supports implementing collaborative nursing care models in mental health settings to enhance patient outcomes. ClinicalTrials.gov identifier: NCT04814576.

Humic Substances from Waste-Based Fertilizers for Improved Soil Fertility

This research explores how different organic waste transformation methods influence the production of humic substances (HSs) and their impact on soil quality. Using olive and orange wastes as substrates, the study compares vermicomposting, composting, and anaerobic digestion processes to determine which method produces the most humic-substance-rich products. The characterization of HSs in each product included analyses of total organic carbon (TOC), humic and fulvic acid content, humification rate, humification degree, and E4/E6 ratio, with HSs extracted using potassium hydroxide (KOH) and analyzed via Diffuse Reflectance Infrared Fourier-Transform (DRIFT) spectroscopy to assess structural complexity. The results revealed that the chemical composition of the input materials significantly influenced the transformation dynamics, with orange by-products exhibiting a higher humification rate and degree. Vermicomposting emerged as the most efficient process, producing fertilizers with superior humic content, greater microbial biodiversity, and enhanced cation exchange capacity, thus markedly improving soil quality. Composting also contributed to the stabilization of organic matter, albeit less effectively than vermicomposting. Anaerobic digestion, by contrast, resulted in products with lower levels of HSs and reduced nutrient content. Aerobic processes, particularly vermicomposting, demonstrated the most rapid and effective transformation, producing structurally complex, stable humus-like substances with pronounced benefits for soil health. These findings underscore vermicomposting as the most sustainable and efficacious approach for generating HS-rich organic fertilizers, presenting a powerful alternative to synthetic fertilizers. Furthermore, this study highlights the potential of organic waste valorization to mitigate environmental pollution and foster circular economy practices in sustainable agriculture.

Near-infrared double-layer cascaded metasurface for beam shaping

The vast applicability of collimated flat-topped beam shapers, predominantly constructed from traditional lens elements, is met with challenges when the scale is less than wavelength. Metasurfaces have an excellent ability for optical manipulation, which can provide a promising approach to flat optics. Here, a metasurface-based Gaussian beam shaper is designed to combine the transmission phase principle with geometric transformation methods, which can reshape a 1550 nm Gaussian beam into a flat-topped beam with a uniformity of 84.39%. Furthermore, a cascaded metasurface beam shaper design is proposed to address the significant divergence in the flat-topped beam obtained from the single-layer metasurface. Simulation results indicate the output beam exhibits both uniform intensity and phase distributions over a considerable transmission distance, effectively minimizing the divergence of the output beam. This research has potential applications in various fields, such as optical antennas, fiber optics, and other optical systems.

Research on Reactivity-Equivalent Physical Transformation Method for Double Heterogeneity in Pressurized Water Reactors Based on Machine Learning

Traditional computational methods for pressurized water reactors are unable to handle dispersed fuel particles as the double heterogeneity and the direct volumetric homogenization can result in significant errors. In contrast, reactivity-equivalent physical transformation techniques offer high precision for addressing the double heterogeneity introduced by dispersed fuel particles. This approach converts the double heterogeneity problem into a single heterogeneity problem, which is then subsequently investigated by using the conventional pressurized water reactor computational procedure. However, it is currently empirical and takes a lot of time to obtain the right k∞. In this paper, we train the RPT model by using the existing dataset of plate-dispersed fuel and rod-dispersed fuel by a machine learning method based on a linear regression model, and we then use the new data to make predictions and derive the corresponding similarity ratios. The burnup verification, density verification, fission rate verification, and neutron energy spectrum analysis are calculated through the OpenMC program. For plate-type fuel elements, the method maintains an accuracy within 200 pcm during depletion, with deviations in the 235U density and 235U fission rate within 0.1% and neutron energy spectrum errors within 6%. For rod-type fuel elements, the method maintains an accuracy within 100 pcm during depletion, with deviations in 235U and 239Pu density within 1.5% and neutron energy spectrum errors within 1%. The numerical validation indicates that the reactivity-equivalent physical transformation method based on the linear regression model not only greatly improves the computational efficiency, but also ensures a very high accuracy to deal with double heterogeneity in nuclear reactors.

Study Of Tandem Rotor Dual Wake Interaction With Downstream Stator Under Unsteady Numerical Approach

Abstract This paper highlights the intricate rotor-stator interaction between a tandem bladed rotor and a single-bladed stator in the light of unsteady numerical simulations. A low speed tandem bladed compressor stage has been conceptualized and experimentally validated against targeted performance goal. With the evident pressure rise capability of the tandem bladed compressor stage, it becomes obligatory to investigate the rotorstator interaction owing to its dominant effect on overall stage performance. The multi-passage rotor-stator unsteady simulations have been performed using blade transformation methods in ANSYS CFX. Due to the presence of two highly loaded rotor blades, the tandem rotor exhibits peculiar rotorstator interaction in terms of multiple wake impingement on the stator. Incorporating tandem blading on the rotor instead of the stator (which is more common) constricts the design envelope in terms of choice of blade axial overlap and percentage pitch. The variation of aerodynamic loading from hub to tip for both the rotor blades results in spanwise varying wake strength. The initially distinct wake structures merge resulting into a thicker wake. Additionally, the rotor blades are highly loaded in the tip region which results in the complex interaction between end-wall boundary layer and tip leakage flow. Cumulatively, these conditions constitute a challenging aerodynamic field for the downstream stator. The study focuses on the qualitative interaction between the rotor wakes and blockage with the downstream stator and put forwards some aspects of the tandem rotor-single stator stage design especially for core compressors of aero engine application.

Podophyllotoxin and Aryltetralin Lignans: Methods for the Synthesis of Rings A, B, C, D

Podophyllotoxin, its derivatives and structural analogues are an extensive group of aryl-tetralin-lignans of interest in pharmacology due to their promising anticancer and antitumor activity. The synthesis methods that have been proposed to date seek to resolve synthetic, stereochemical, pharmacodynamic and environmental aspects. In this review we have updated and brought together different classifications of lignan and podophyllotoxin synthesis. Transformation methods focus on the strategies used to form or functionalize rings A, B, C and D, as well as the configuration of the system of four stereogenic centers that fuse rings C and D.