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Keywords = genetic circuit design

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22 pages, 1536 KB  
Review
Unlocking MSC Potential: Metabolic Reprogramming via Synthetic Biology Approaches
by Natalia Trufanova, Oleh Trufanov and Oleksandr Petrenko
SynBio 2025, 3(3), 13; https://doi.org/10.3390/synbio3030013 - 17 Sep 2025
Viewed by 262
Abstract
Metabolic engineering of mesenchymal stem/stromal cells (MSCs) represents a compelling frontier for advanced cellular therapies, enabling the precise tuning of their biological outputs. This feature paper examines the critical role of engineered culture microenvironments, specifically 3D platforms, hypoxic preconditioning, and other priming approaches, [...] Read more.
Metabolic engineering of mesenchymal stem/stromal cells (MSCs) represents a compelling frontier for advanced cellular therapies, enabling the precise tuning of their biological outputs. This feature paper examines the critical role of engineered culture microenvironments, specifically 3D platforms, hypoxic preconditioning, and other priming approaches, which are synthetic biology strategies used to guide and optimize MSC metabolic states for desired functional outcomes. We show that these non-genetic approaches can significantly enhance MSC survival, immunomodulatory capacity, and regenerative potential by shifting their metabolism toward a more glycolytic phenotype. Furthermore, we propose a new paradigm of “designer” MSCs, which are programmed with synthetic circuits to sense and respond to the physiological cues of an injured microenvironment. This approach promises to transform regenerative medicine from an inconsistent field into a precise, predictable, and highly effective therapeutic discipline. Full article
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23 pages, 4098 KB  
Article
Modeling of the Dynamic Characteristics for a High-Load Magnetorheological Fluid-Elastomer Isolator
by Yu Tao, Wenhao Chen, Feifei Liu and Ruijie Han
Actuators 2025, 14(9), 442; https://doi.org/10.3390/act14090442 - 5 Sep 2025
Viewed by 266
Abstract
To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and [...] Read more.
To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and finite element simulations, achieving effective vibration isolation within confined spaces. The dynamic performance of the isolator was experimentally evaluated using a hydraulic testing system under varying excitation amplitudes, frequencies, initial positions, and magnetic fields. Experimental results indicate that the isolator achieves a static stiffness of 3 × 106 N/m and a maximum adjustable compression load range of 105.4%. In light of the asymmetric nonlinear dynamic behavior of the isolator, an improved nine-parameter Bouc–Wen model is proposed. Parameter identification performed via a genetic algorithm demonstrates a model accuracy of 95.0%, with a minimum error reduction of 28.8% compared to the conventional Bouc–Wen model. Full article
(This article belongs to the Section Precision Actuators)
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20 pages, 3618 KB  
Review
Synthetic Gene Circuits Enable Sensing in Engineered Living Materials
by Yaxuan Cai, Yujie Wang and Shengbiao Hu
Biosensors 2025, 15(9), 556; https://doi.org/10.3390/bios15090556 - 22 Aug 2025
Viewed by 998
Abstract
Engineered living materials (ELMs) integrate living cells—such as bacteria, yeast, or mammalian cells—with synthetic matrices to create responsive, adaptive systems for sensing and actuation. Among ELMs, those endowed with sensing capabilities are gaining increasing attention for applications in environmental monitoring, biomedicine, and smart [...] Read more.
Engineered living materials (ELMs) integrate living cells—such as bacteria, yeast, or mammalian cells—with synthetic matrices to create responsive, adaptive systems for sensing and actuation. Among ELMs, those endowed with sensing capabilities are gaining increasing attention for applications in environmental monitoring, biomedicine, and smart infrastructure. Central to these sensing functions are synthetic gene circuits, which enable cells to detect and respond to specific signals. This mini-review focuses on recent advances in sensing ELMs empowered by synthetic gene circuits. Here, we highlight how rationally designed genetic circuits enable living materials to sense and respond to diverse inputs—including environmental chemicals, light, heat, and mechanical loadings—via programmable signal transduction and tailored output behaviors. Input signals are classified by their source and physicochemical properties, including synthetic inducers, environmental chemicals, light, thermal, mechanical, and electrical signals. Particular emphasis is placed on the integration of genetically engineered microbial cells with hydrogels and other functional scaffolds to construct robust and tunable sensing platforms. Finally, we discuss the current challenges and future opportunities in this rapidly evolving field, providing insights to guide the rational design of next-generation sensing ELMs. Full article
(This article belongs to the Special Issue Biomaterials for Biosensing Applications—2nd Edition)
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34 pages, 3660 KB  
Review
A Guide in Synthetic Biology: Designing Genetic Circuits and Their Applications in Stem Cells
by Karim S. Elnaggar, Ola Gamal, Nouran Hesham, Sama Ayman, Nouran Mohamed, Ali Moataz, Emad M. Elzayat and Nourhan Hassan
SynBio 2025, 3(3), 11; https://doi.org/10.3390/synbio3030011 - 22 Jul 2025
Viewed by 1893
Abstract
Stem cells, unspecialized cells with regenerative and differentiation capabilities, hold immense potential in regenerative medicine, exemplified by hematopoietic stem cell transplantation. However, their clinical application faces significant limitations, including their tumorigenic risk due to uncontrolled proliferation and cellular heterogeneity. This review explores how [...] Read more.
Stem cells, unspecialized cells with regenerative and differentiation capabilities, hold immense potential in regenerative medicine, exemplified by hematopoietic stem cell transplantation. However, their clinical application faces significant limitations, including their tumorigenic risk due to uncontrolled proliferation and cellular heterogeneity. This review explores how synthetic biology, an interdisciplinary approach combining engineering and biology, offers promising solutions to these challenges. It discusses the concepts, toolkit, and advantages of synthetic biology, focusing on the design and integration of genetic circuits to program stem cell differentiation and engineer safety mechanisms like inducible suicide switches. This review comprehensively examines recent advancements in synthetic biology applications for stem cell engineering, including programmable differentiation circuits, cell reprogramming strategies, and therapeutic cell engineering approaches. We highlight specific examples of genetic circuits that have been successfully implemented in various stem cell types, from embryonic stem cells to induced pluripotent stem cells, demonstrating their potential for clinical translation. Despite these advancements, the integration of synthetic biology with mammalian cells remains complex, necessitating further research, standardized datasets, open access repositories, and interdisciplinary collaborations to build a robust framework for predicting and managing this complexity. Full article
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18 pages, 3220 KB  
Article
High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering
by William R. Gaillard, Jess Sustarich, Yuerong Li, David N. Carruthers, Kshitiz Gupta, Yan Liang, Rita Kuo, Stephen Tan, Sam Yoder, Paul D. Adams, Hector Garcia Martin, Nathan J. Hillson and Anup K. Singh
Bioengineering 2025, 12(8), 788; https://doi.org/10.3390/bioengineering12080788 - 22 Jul 2025
Viewed by 1332
Abstract
Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. [...] Read more.
Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to integrate into highly multiplexed workflows, owing to limitations in their scalability and tunability. These challenges ultimately increase the time and cost per transformation. As a result, rapidly screening genetic libraries, exploring combinatorial designs, or optimizing electroporation parameters requires extensive iterations, consuming large quantities of expensive custom-made DNA and cell lines or primary cells. To address these limitations, we have developed a High-Throughput Microfluidic Electroporation (HTME) platform that includes a 384-well electroporation plate (E-Plate) and control electronics capable of rapidly electroporating all wells in under a minute with individual control of each well. Fabricated using scalable and cost-effective printed-circuit-board (PCB) technology, the E-Plate significantly reduces consumable costs and reagent consumption by operating on nano to microliter volumes. Furthermore, individually addressable wells facilitate rapid exploration of large sets of experimental conditions to optimize electroporation for different cell types and plasmid concentrations/types. Use of the standard 384-well footprint makes the platform easily integrable into automated workflows, thereby enabling end-to-end automation. We demonstrate transformation of E. coli with pUC19 to validate the HTME’s core functionality, achieving at least a single colony forming unit in more than 99% of wells and confirming the platform’s ability to rapidly perform hundreds of electroporations with customizable conditions. This work highlights the HTME’s potential to significantly accelerate synthetic biology Design-Build-Test-Learn (DBTL) cycles by mitigating the transformation/transfection bottleneck. Full article
(This article belongs to the Section Cellular and Molecular Bioengineering)
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24 pages, 5634 KB  
Article
Research on the Coordination of Transportation Network and Ecological Corridors Based on Maxent Model and Circuit Theory in the Giant Panda National Park, China
by Xinyu Li, Gaoru Zhu, Jiaqi Sun, Leyao Wu and Yuting Peng
Land 2025, 14(7), 1465; https://doi.org/10.3390/land14071465 - 14 Jul 2025
Cited by 1 | Viewed by 529
Abstract
National parks serve as critical spatial units for conserving ecological baselines, maintaining genetic diversity, and delivering essential ecosystem services. However, accelerating socio-economic development has increasingly intensified the conflict between ecological protection and transportation infrastructure. Ecologically sustainable transportation planning is, therefore, essential to mitigate [...] Read more.
National parks serve as critical spatial units for conserving ecological baselines, maintaining genetic diversity, and delivering essential ecosystem services. However, accelerating socio-economic development has increasingly intensified the conflict between ecological protection and transportation infrastructure. Ecologically sustainable transportation planning is, therefore, essential to mitigate habitat fragmentation, facilitate species migration, and conserve biodiversity. This study examines the Giant Panda National Park and its buffer zone, focusing on six mammal species: giant panda, Sichuan snub-nosed monkey, leopard cat, forest musk deer, rock squirrel, and Sichuan takin. By integrating Maxent ecological niche modeling with circuit theory, it identified ecological source areas and potential corridors, and employed a two-step screening approach to design species-specific wildlife crossings. In total, 39 vegetated overpasses were proposed to serve all target species; 34 underpasses were integrated using existing bridge and culvert structures to minimize construction costs; and 27 canopy bridges, incorporating suspension cables and elevated pathways, were designed to connect forest canopies for arboreal species. This study established a multi-species and multi-scale conservation framework, providing both theoretical insights and practical strategies for ecologically integrated transportation planning in national parks, contributing to the synergy between biodiversity conservation and sustainable development goals. Full article
(This article belongs to the Special Issue Territorial Space and Transportation Coordinated Development)
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23 pages, 7744 KB  
Article
Optimization and Design of Built-In U-Shaped Permanent Magnet and Salient-Pole Electromagnetic Hybrid Excitation Generator for Vehicles
by Keqi Chen, Shilun Ma, Changwei Li, Yongyi Wu and Jianwei Ma
Symmetry 2025, 17(6), 897; https://doi.org/10.3390/sym17060897 - 6 Jun 2025
Cited by 1 | Viewed by 585
Abstract
In this paper, the concept of symmetry is utilized to optimize the structural parameters and output characteristics of the generator design—that is, the construction and solution of the equivalent magnetic circuit method for the hybrid excitation generator are symmetrical. To address the issues [...] Read more.
In this paper, the concept of symmetry is utilized to optimize the structural parameters and output characteristics of the generator design—that is, the construction and solution of the equivalent magnetic circuit method for the hybrid excitation generator are symmetrical. To address the issues of high excitation loss and low power density in purely electrically excited generators, as well as the difficulty in adjusting the magnetic field in purely permanent magnet generators, a new topology for a built-in permanent magnet and salient-pole electromagnetic hybrid excitation generator is proposed. Firstly, an equivalent magnetic circuit model of the generator is established. Secondly, expressions are derived to describe the relationships between the dimensions of the salient-pole rotor and the permanent magnets and the generator’s no-load induced electromotive force, cogging torque, and air gap flux density. These expressions are then used to analyze the structural parameters that influence the generator’s performance. Thirdly, optimization targets are selected through sensitivity analysis, with the no-load induced electromotive force, cogging torque, and air gap flux density serving as the optimization objectives. A multi-objective genetic algorithm is employed to optimize these parameters and determine the optimal structural matching parameters for the generator. As a result, the optimized no-load induced electromotive force increased from 18.96 V to 20.14 V, representing a 6.22% improvement; the cogging torque decreased from 177.08 mN·m to 90.52 mN·m, a 48.88% reduction; the air gap flux density increased from 0.789 T to 0.829 T, a 5.07% improvement; and the air gap flux density waveform distortion rate decreased from 6.22% to 2.38%, a 39.3% reduction. Finally, a prototype is fabricated and experimentally tested, validating the accuracy of the simulation analysis, the feasibility of the optimization method, and the rationality of the generator design. Therefore, the proposed topology and optimization method can effectively enhance the output performance of the generator, providing a valuable theoretical reference for the design of hybrid excitation generators for vehicles. Full article
(This article belongs to the Section Engineering and Materials)
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33 pages, 1176 KB  
Review
GLP-1 Analogues in the Neurobiology of Addiction: Translational Insights and Therapeutic Perspectives
by Juan David Marquez-Meneses, Santiago Arturo Olaya-Bonilla, Samuel Barrera-Carreño, Lucía Catalina Tibaduiza-Arévalo, Sara Forero-Cárdenas, Liliana Carrillo-Vaca, Luis Carlos Rojas-Rodríguez, Carlos Alberto Calderon-Ospina and Jesús Rodríguez-Quintana
Int. J. Mol. Sci. 2025, 26(11), 5338; https://doi.org/10.3390/ijms26115338 - 1 Jun 2025
Cited by 2 | Viewed by 3511
Abstract
Glucagon-like peptide-1 receptor agonists, originally developed for the treatment of metabolic disorders, have recently emerged as promising candidates for the management of substance use disorders. This review synthesizes preclinical, clinical, and translational evidence on the effects of glucagon-like peptide-1 receptor agonists across addiction [...] Read more.
Glucagon-like peptide-1 receptor agonists, originally developed for the treatment of metabolic disorders, have recently emerged as promising candidates for the management of substance use disorders. This review synthesizes preclinical, clinical, and translational evidence on the effects of glucagon-like peptide-1 receptor agonists across addiction models involving alcohol, nicotine, psychostimulants, and opioids. In animal studies, glucagon-like peptide-1 receptor agonists consistently reduce drug intake, attenuate dopamine release in reward circuits, and decrease relapse-like behavior. Clinical and observational studies provide preliminary support for these findings, particularly among individuals with comorbid obesity or insulin resistance. However, several translational barriers remain, including limited blood–brain barrier penetration, species differences in pharmacokinetics, and variability in treatment response due to genetic and metabolic factors. Ethical considerations and methodological heterogeneity further complicate clinical translation. Future directions include the development of central nervous system penetrant analogues, personalized medicine approaches incorporating pharmacogenomics, and rigorously designed trials in diverse populations. Glucagon-like peptide-1 receptor agonists may offer a novel therapeutic strategy that addresses both metabolic and neuropsychiatric dimensions of addiction, warranting further investigation to define their role in the evolving landscape of substance use disorder treatment. Full article
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20 pages, 733 KB  
Article
Energy Optimization in Hotels: Strategies for Efficiency in Hot Water Systems
by Yarelis Valdivia Nodal, Luis Angel Iturralde Carrera, Araceli Zapatero-Gutiérrez, Mario Antonio Álvarez Guerra Plasencia, Royd Reyes Calvo, José M. Álvarez-Alvarado and Juvenal Rodríguez-Reséndiz
Algorithms 2025, 18(6), 301; https://doi.org/10.3390/a18060301 - 22 May 2025
Cited by 1 | Viewed by 958
Abstract
This paper presents a procedure for the energy optimization of domestic hot water (DHW) systems in hotels located in tropical climates that use centralized air conditioning systems. The study aims to maximize heat recovery from chillers and reduce the fuel consumption of auxiliary [...] Read more.
This paper presents a procedure for the energy optimization of domestic hot water (DHW) systems in hotels located in tropical climates that use centralized air conditioning systems. The study aims to maximize heat recovery from chillers and reduce the fuel consumption of auxiliary heaters by optimizing operational variables such as water mass flow in the primary and secondary DHW circuits and outlet temperature of the backup system. The optimization is implemented using genetic algorithms (GA), which enable the identification of the most efficient flow configurations under variable thermal demand conditions. The proposed methodology integrates a thermoenergetic model validated with real operational data and considers the dynamic behavior of hotel occupancy and water demand. The results show that the optimized strategy reduces auxiliary heating use by up to 75%, achieving annual energy savings of 8244 kWh, equivalent to 2.3 tons of fuel, and preventing the emission of 10.5 tons of CO2. This study contributes to the design of sustainable energy systems in the hospitality sector and provides replicable strategies for similar climatic and operational contexts. Full article
(This article belongs to the Section Combinatorial Optimization, Graph, and Network Algorithms)
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18 pages, 4153 KB  
Article
Analysis of Electromagnetic Characteristics of Outer Rotor Type BLDC Motor Based on Analytical Method and Optimal Design Using NSGA-II
by Tae-Seong Kim, Jun-Won Yang, Kyung-Hun Shin, Gang-Hyeon Jang, Cheol Han and Jang-Young Choi
Machines 2025, 13(6), 440; https://doi.org/10.3390/machines13060440 - 22 May 2025
Cited by 1 | Viewed by 783
Abstract
This study investigates the electromagnetic analysis and optimal design of outer rotor type brushless DC (BLDC) motors for fan filter applications. The primary objective is to develop a method that integrates three-dimensional (3D) structural effects with efficient two-dimensional (2D) equivalent analysis. This study [...] Read more.
This study investigates the electromagnetic analysis and optimal design of outer rotor type brushless DC (BLDC) motors for fan filter applications. The primary objective is to develop a method that integrates three-dimensional (3D) structural effects with efficient two-dimensional (2D) equivalent analysis. This study proposes a 2D equivalent analysis method that addresses the unique features of outer rotor type BLDC motors, particularly the permanent magnet (PM) overhang structure. This approach transforms the operating point on the B–H curve to facilitate accurate modeling in a 2D framework, overcoming traditional analysis limitations. An analytical method using spatial harmonics is introduced to derive essential electromagnetic quantities, namely flux linkage and back electromotive force (EMF). The method compensates for slot effects using the Carter coefficient, ensuring precise evaluation of circuit parameters and electromagnetic losses. To optimize motor performance, a multi-objective optimization technique is implemented using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), aiming to maximize both efficiency and power density. The research validates the proposed analytical approach against the finite element analysis method (FEM) results to confirm its accuracy. Full article
(This article belongs to the Special Issue Recent Developments in Machine Design, Automation and Robotics)
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22 pages, 1739 KB  
Article
Design of a Lorentz Force Magnetic Bearing Group Steering Law Based on an Adaptive Weighted Pseudo-Inverse Law
by Chenyu Wang, Lei Li, Weijie Wang, Yanbin Zhao, Baiqi Li and Yuan Ren
Sensors 2025, 25(10), 3242; https://doi.org/10.3390/s25103242 - 21 May 2025
Viewed by 720
Abstract
Aiming at the high-precision torque output and saturation singularity avoidance problems in Lorentz force magnetic bearing (LFMB) swarms for magnetic levitation spacecraft, this study designs a manipulation law based on an adaptive weighted pseudo-inverse law. The system monitors each magnetic bearing’s working state [...] Read more.
Aiming at the high-precision torque output and saturation singularity avoidance problems in Lorentz force magnetic bearing (LFMB) swarms for magnetic levitation spacecraft, this study designs a manipulation law based on an adaptive weighted pseudo-inverse law. The system monitors each magnetic bearing’s working state in real time using high-precision position and current sensors. As the key input for the adaptive weighted pseudo-inverse control law, the sensor data’s measurement accuracy directly determines torque distribution effectiveness and attitude control precision. First, considering electromagnetic back-EMF effects, individual LFMB dynamics are modeled via the equivalent magnetic circuit method, with working principles elucidated. Subsequently, saturation coefficients for LFMB swarms are designed. Incorporating spacecraft maneuvering requirements, a genetic optimization algorithm establishes the optimal mounting configuration under task constraints. Considering the LFMB swarm configuration characteristics, this study proposes an adaptive weighted pseudo-inverse maneuvering law tailored to operational constraints. By designing an adaptive weighting matrix, the maneuvering law adjusts each LFMB’s torque output in real time, reducing residual saturation effects on attitude control speed and accuracy. Simulation results demonstrate that the proposed mounting configuration and adaptive weighted pseudo-inverse maneuvering law effectively mitigate saturation singularity’s impact on attitude control accuracy while reducing total energy consumption by 22%, validating the method’s effectiveness and superiority. Full article
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20 pages, 10584 KB  
Perspective
Phytochelatins and Cadmium Mitigation: Harnessing Genetic Avenues for Plant Functional Manipulation
by Deyvid Novaes Marques, Cássio Carlette Thiengo and Ricardo Antunes Azevedo
Int. J. Mol. Sci. 2025, 26(10), 4767; https://doi.org/10.3390/ijms26104767 - 16 May 2025
Cited by 1 | Viewed by 1122
Abstract
Among the highly toxic heavy metals, cadmium (Cd) is highlighted as a persistent environmental pollutant, posing serious threats to plants and broader ecological systems. Phytochelatins (PCs), which are synthesized by phytochelatin synthase (PCS), are peptides that play a central role in Cd mitigation [...] Read more.
Among the highly toxic heavy metals, cadmium (Cd) is highlighted as a persistent environmental pollutant, posing serious threats to plants and broader ecological systems. Phytochelatins (PCs), which are synthesized by phytochelatin synthase (PCS), are peptides that play a central role in Cd mitigation through metal chelation and vacuolar sequestration upon formation of Cd-PC complexes. PC synthesis interacts with other cellular mechanisms to shape detoxification outcomes, broadening the functional scope of PCs beyond classical stress responses. Plant Cd-related processes have has been extensively investigated within this context. This perspective article presents key highlights of the panorama concerning strategies targeting the PC pathway and PC synthesis to manipulate Cd-exposed plants. It discusses multiple advances on the topic related to genetic manipulation, including the use of mutants and transgenics, which also covers gene overexpression, PCS-deficient and PCS-overexpressing plants, and synthetic PC analogs. A complementary bibliometric analysis reveals emerging trends and reinforces the need for interdisciplinary integration and precision in genetic engineering. Future directions include the design of multigene circuits and grafting-based innovations to optimize Cd sequestration and regulate its accumulation in plant tissues, supporting both phytoremediation efforts and food safety in contaminated agricultural environments. Full article
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24 pages, 1223 KB  
Article
Parallel Sort Implementation and Evaluation in a Dataflow-Based Polymorphic Computing Architecture
by David Hentrich, Erdal Oruklu and Jafar Saniie
Computers 2025, 14(5), 181; https://doi.org/10.3390/computers14050181 - 7 May 2025
Viewed by 560
Abstract
This work presents two variants of an odd–even sort algorithm that are implemented in a dataflow-based polymorphic computing architecture. The two odd–even sort algorithms are the “fully unrolled” variant and the “compact” variant. They are used as test kernels to evaluate the polymorphic [...] Read more.
This work presents two variants of an odd–even sort algorithm that are implemented in a dataflow-based polymorphic computing architecture. The two odd–even sort algorithms are the “fully unrolled” variant and the “compact” variant. They are used as test kernels to evaluate the polymorphic computing architecture. Incidentally, these two odd–even sort algorithm variants can be readily adapted to ASIC (Application-Specific Integrated Circuit) and FPGA (Field Programmable Gate Array) designs. Additionally, two methods of placing the sort algorithms’ instructions in different configurations of the polymorphic computing architecture to achieve performance gains are furnished: a genetic-algorithm-based instruction placement method and a deterministic instruction placement method. Finally, a comparative study of the odd–even sort algorithm in several configurations of the polymorphic computing architecture is presented. The results show that scaling up the number of processing cores in the polymorphic architecture to the maximum amount of instantaneously exploitable parallelism improves the speed of the sort algorithms. Additionally, the sort algorithms that were placed in the polymorphic computing architecture configurations by the genetic instruction placement algorithm generally performed better than when they were placed by the deterministic instruction placement algorithm. Full article
(This article belongs to the Section Cloud Continuum and Enabled Applications)
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27 pages, 12122 KB  
Article
An Investigation into the Saliency Ratio of Fractional-Slot Concentrated-Winding Generators for Offshore Wind Power
by Isaac Rudden, Guang-Jin Li, Zi-Qiang Zhu, Alexander Duke and Richard Clark
Energies 2025, 18(8), 2057; https://doi.org/10.3390/en18082057 - 17 Apr 2025
Viewed by 492
Abstract
This paper investigates the nature of the low saliency ratio of large permanent magnet generators with fractional-slot concentrated windings (FSCWs). A saliency ratio of at least 1.2 is typically required to enable sensorless control of large generators—a value naturally achieved in integer slot [...] Read more.
This paper investigates the nature of the low saliency ratio of large permanent magnet generators with fractional-slot concentrated windings (FSCWs). A saliency ratio of at least 1.2 is typically required to enable sensorless control of large generators—a value naturally achieved in integer slot winding topologies but absent in FSCW surface-mounted permanent magnet machines reported in the literature. The low saliency ratio in FSCW designs is attributed to larger teeth, which reduce magnetic saturation and increase d-axis inductance. This work explores methods to enhance the saliency ratio of FSCW machines for offshore wind turbines, facilitating sensorless rotor position estimation. The proposed approaches are categorized into two groups: (1) those that preserve the conventional machine geometry with minimal modification to the magnetic circuit and (2) those involving magnetic circuit alterations. The results show that significant improvement in saliency ratio is only achievable through magnetic circuit modifications, such as rotor shoes, albeit with some performance trade-offs. A multi-objective genetic algorithm is employed to design two optimized 3 MW FSCW machine topologies, achieving saliency ratios of 1.15 and 1.2 with minimal performance loss. Compared to a 3 MW FSCW baseline, the optimized designs show stator power reductions of 3.40% and 6.16% for saliency ratios of 1.15 and 1.2, respectively. Full article
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25 pages, 5044 KB  
Review
Recent Developments and Perspectives on Optimization Design Methods for Analog Integrated Circuits
by Yunqi Yang, Jiaming Su, Xiaoran Lai, Dongdong Chen, Di Li and Yintang Yang
Symmetry 2025, 17(4), 529; https://doi.org/10.3390/sym17040529 - 31 Mar 2025
Cited by 2 | Viewed by 2215
Abstract
As the cornerstone of the modern information industry, designing a high-performance circuit is crucial. Due to the influence of external environmental and asymmetric arrangements, non-ideal factors in analog integrated circuits (ICs) cannot be ignored, which makes the design process heavily reliant on human [...] Read more.
As the cornerstone of the modern information industry, designing a high-performance circuit is crucial. Due to the influence of external environmental and asymmetric arrangements, non-ideal factors in analog integrated circuits (ICs) cannot be ignored, which makes the design process heavily reliant on human experience, and the design efficiency is low. Recently, scholars have conducted extensive research on optimization design methods for analog ICs by combining artificial intelligence and optimization algorithms. In this article, the developments and perspectives on optimization design methods for analog ICs are reviewed. In traditional design methods, particle swarm optimization (PSO), the genetic algorithm (GA), and reinforcement learning (RL) have been applied with different computer-aided design (CAD) tools. A variety of circuit simulation software have been developed, such as Cadence, Ngspice, Pspice, etc. Due to its high precision, comprehensive functionality, and full-process simulation, Cadence has been widely used in the design of analog ICs. These methods can improve the design efficiency to a certain extent. In the iterative process, running the simulation software to obtain performance metrics can waste a lot of time. Thus, efficient optimization design methods have been proposed to improve the design efficiency by establishing a proxy model of the circuit, which can replace simulation software. Accordingly, three research directions in this field are proposed. In summary, this article can aid scholars in quickly understanding the current status of optimization design methods for analog ICs and provide guidance for future research. Full article
(This article belongs to the Section Engineering and Materials)
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