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13 pages, 2737 KiB  
Article
Design of a Wideband Loaded Sleeve Monopole Embedded with Filtering High–Low Impedance Structure
by Jiansen Ma, Weiping Cao and Xinhua Yu
Electronics 2025, 14(15), 3137; https://doi.org/10.3390/electronics14153137 (registering DOI) - 6 Aug 2025
Abstract
In this paper, a compact wideband filtering monopole is presented for remote terrestrial omnidirectional communication systems. The presented antenna features a sleeve monopole structure integrating with two key components: the lumped parallel RLC circuits and an embedded high–low impedance structure within the sleeve [...] Read more.
In this paper, a compact wideband filtering monopole is presented for remote terrestrial omnidirectional communication systems. The presented antenna features a sleeve monopole structure integrating with two key components: the lumped parallel RLC circuits and an embedded high–low impedance structure within the sleeve section. The integrated high–low impedance structure enables the monopole to achieve excellent filtering characteristics while maintaining the monopole compactly. Meanwhile, the combination of the RLC loads and the sleeve monopole ensures wideband omnidirectional radiation performance. To validate the design, a prototype operating from 200 to 1500 MHz is fabricated and tested. The measurement results demonstrate that the monopole achieves a VSWR below 3 across the entire operating band and a measured gain exceeding 0 dB. Furthermore, the monopole exhibits satisfactory out-of-band rejection from 1700 to 4000 MHz, confirming its effective filtering capability. Full article
14 pages, 950 KiB  
Article
Synthesis and Antifungal Evaluation Against Candida spp. of 5-Arylfuran-2-Carboxamide Derivatives
by Salvatore Mirabile, Giovanna Ginestra, Rosamaria Pennisi, Davide Barreca, Giuseppina Mandalari and Rosaria Gitto
Microorganisms 2025, 13(8), 1835; https://doi.org/10.3390/microorganisms13081835 (registering DOI) - 6 Aug 2025
Abstract
Candidiasis arises from the proliferation of Candida species in the human body, especially in individuals with compromised immune systems. Efficient therapeutic management of candidiasis is often hampered by the limited availability of potent antifungal drugs and the emergence of drug-resistant strains. We have [...] Read more.
Candidiasis arises from the proliferation of Candida species in the human body, especially in individuals with compromised immune systems. Efficient therapeutic management of candidiasis is often hampered by the limited availability of potent antifungal drugs and the emergence of drug-resistant strains. We have previously identified the N-[(4-sulfamoylphenyl)methyl][1,1′-biphenyl]-4-carboxamide to have fungistatic and fungicidal properties, likely due to the hydrophobic biphenyl–chemical features affecting the structural organization of Candida spp. cell membrane. Here, we designed and synthesized a novel series of twelve 5-arylfuran-2-carboxamide derivatives bearing a new hydrophobic tail as bioisosteric replacement of the diphenyl fragment. Its antifungal effectiveness against C. albicans, C. glabrata, and C. parapsilosis, including ATCC and clinically isolated strains, was assessed for all compounds. The most active compound was N-benzyl-5-(3,4-dichlorophenyl)furan-2-carboxamide (6), with fungistatic and fungicidal effects against C. glabrata and C. parapsilosis strains (MIC = 0.062–0.125 and 0.125–0.250 mg/mL, respectively). No synergistic effects were observed when combined with fluconazole. Interestingly, fluorescent microscopy analysis after staining with SYTO 9 and propidium iodide revealed that compound 6 affected the cell membrane integrity in C. albicans strain 16. Finally, carboxamide 6 exhibited a dose-dependent cytotoxicity on erythrocytes, based on assessing the LDH release. Full article
(This article belongs to the Collection Feature Papers in Antimicrobial Agents and Resistance)
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38 pages, 10941 KiB  
Review
Recent Advances in Numerical Modeling of Aqueous Redox Flow Batteries
by Yongfu Liu and Yi He
Energies 2025, 18(15), 4170; https://doi.org/10.3390/en18154170 (registering DOI) - 6 Aug 2025
Abstract
Aqueous redox flow batteries (ARFBs) have attracted significant attention in the field of electrochemical energy storage due to their high intrinsic safety, low cost, and flexible system configuration. However, the advancement of this technology is still hindered by several critical challenges, including capacity [...] Read more.
Aqueous redox flow batteries (ARFBs) have attracted significant attention in the field of electrochemical energy storage due to their high intrinsic safety, low cost, and flexible system configuration. However, the advancement of this technology is still hindered by several critical challenges, including capacity decay, structural optimization, and the design and application of key materials as well as their performance within battery systems. Addressing these issues requires systematic theoretical foundations and scientific guidance. Numerical modeling has emerged as a powerful tool for investigating the complex physical and electrochemical processes within flow batteries across multiple spatial and temporal scales. It also enables predictive performance analysis and cost-effective optimization at both the component and system levels, thus accelerating research and development. This review provides a comprehensive overview of recent progress in the modeling of ARFBs. Taking the all-vanadium redox flow battery as a representative example, we summarize the key multiphysics phenomena involved and introduce corresponding multi-scale modeling strategies. Furthermore, specific modeling considerations are discussed for phase-change ARFBs, such as zinc-based ones involving solid–liquid phase transition, and hydrogen–bromine systems characterized by gas–liquid two-phase flow, highlighting their distinctive features compared to vanadium systems. Finally, this paper explores the major challenges and potential opportunities in the modeling of representative ARFB systems, aiming to provide theoretical guidance and technical support for the continued development and practical application of ARFB technology. Full article
(This article belongs to the Special Issue Advanced Energy Storage Technologies)
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15 pages, 4886 KiB  
Article
Fabrication of Diffractive Optical Elements to Generate Square Focal Spots via Direct Laser Lithography and Machine Learning
by Hieu Tran Doan Trung, Young-Sik Ghim and Hyug-Gyo Rhee
Photonics 2025, 12(8), 794; https://doi.org/10.3390/photonics12080794 (registering DOI) - 6 Aug 2025
Abstract
Recently, diffractive optics systems have garnered increasing attention due to their myriad benefits in various applications, such as creating vortex beams, Bessel beams, or optical traps, while refractive optics systems still exhibit some disadvantages related to materials, substrates, and intensity shapes. The manufacturing [...] Read more.
Recently, diffractive optics systems have garnered increasing attention due to their myriad benefits in various applications, such as creating vortex beams, Bessel beams, or optical traps, while refractive optics systems still exhibit some disadvantages related to materials, substrates, and intensity shapes. The manufacturing of diffractive optical elements has become easier due to the development of lithography techniques such as direct laser writing, photo lithography, and electron beam lithography. In this paper, we improve the results from previous research and propose a new methodology to design and fabricate advanced binary diffractive optical elements that achieve a square focal spot independently, reducing reliance on additional components. By integrating a binary square zone plate with an axicon zone plate of the same scale, we employ machine learning for laser path optimization and direct laser lithography for manufacturing. This streamlined approach enhances simplicity, accuracy, efficiency, and cost effectiveness. Our upgraded binary diffractive optical elements are ready for real-world applications, marking a significant improvement in optical capabilities. Full article
(This article belongs to the Section Lasers, Light Sources and Sensors)
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50 pages, 6488 KiB  
Article
A Bio-Inspired Adaptive Probability IVYPSO Algorithm with Adaptive Strategy for Backpropagation Neural Network Optimization in Predicting High-Performance Concrete Strength
by Kaifan Zhang, Xiangyu Li, Songsong Zhang and Shuo Zhang
Biomimetics 2025, 10(8), 515; https://doi.org/10.3390/biomimetics10080515 (registering DOI) - 6 Aug 2025
Abstract
Accurately predicting the compressive strength of high-performance concrete (HPC) is critical for ensuring structural integrity and promoting sustainable construction practices. However, HPC exhibits highly complex, nonlinear, and multi-factorial interactions among its constituents (such as cement, aggregates, admixtures, and curing conditions), which pose significant [...] Read more.
Accurately predicting the compressive strength of high-performance concrete (HPC) is critical for ensuring structural integrity and promoting sustainable construction practices. However, HPC exhibits highly complex, nonlinear, and multi-factorial interactions among its constituents (such as cement, aggregates, admixtures, and curing conditions), which pose significant challenges to conventional predictive models. Traditional approaches often fail to adequately capture these intricate relationships, resulting in limited prediction accuracy and poor generalization. Moreover, the high dimensionality and noisy nature of HPC mix data increase the risk of model overfitting and convergence to local optima during optimization. To address these challenges, this study proposes a novel bio-inspired hybrid optimization model, AP-IVYPSO-BP, which is specifically designed to handle the nonlinear and complex nature of HPC strength prediction. The model integrates the ivy algorithm (IVYA) with particle swarm optimization (PSO) and incorporates an adaptive probability strategy based on fitness improvement to dynamically balance global exploration and local exploitation. This design effectively mitigates common issues such as premature convergence, slow convergence speed, and weak robustness in traditional metaheuristic algorithms when applied to complex engineering data. The AP-IVYPSO is employed to optimize the weights and biases of a backpropagation neural network (BPNN), thereby enhancing its predictive accuracy and robustness. The model was trained and validated on a dataset comprising 1,030 HPC mix samples. Experimental results show that AP-IVYPSO-BP significantly outperforms traditional BPNN, PSO-BP, GA-BP, and IVY-BP models across multiple evaluation metrics. Specifically, it achieved an R2 of 0.9542, MAE of 3.0404, and RMSE of 3.7991 on the test set, demonstrating its high accuracy and reliability. These results confirm the potential of the proposed bio-inspired model in the prediction and optimization of concrete strength, offering practical value in civil engineering and materials design. Full article
18 pages, 5831 KiB  
Article
Cure Kinetics-Driven Compression Molding of CFRP for Fast and Low-Cost Manufacturing
by Xintong Wu, Ming Zhang, Zhongling Liu, Xin Fu, Haonan Liu, Yuchen Zhang and Xiaobo Yang
Polymers 2025, 17(15), 2154; https://doi.org/10.3390/polym17152154 (registering DOI) - 6 Aug 2025
Abstract
Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their excellent strength-to-weight ratio and tailorable properties. However, these properties critically depend on the CFRP curing cycle. The commonly adopted manufacturer-recommended curing cycle (MRCC), designed to accommodate the most conservative conditions, [...] Read more.
Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their excellent strength-to-weight ratio and tailorable properties. However, these properties critically depend on the CFRP curing cycle. The commonly adopted manufacturer-recommended curing cycle (MRCC), designed to accommodate the most conservative conditions, involves prolonged curing times and high energy consumption. To overcome these limitations, this study proposes an efficient and adaptable method to determine the optimal curing cycle. The effects of varying heating rates on resin dynamic and isothermal–exothermic behavior were characterized via reaction kinetics analysis using differential scanning calorimetry (DSC) and rheological measurements. The activation energy of the reaction system was substituted into the modified Sun–Gang model, and the parameters were estimated using a particle swarm optimization algorithm. Based on the curing kinetic behavior of the resin, CFRP compression molding process orthogonal experiments were conducted. A weighted scoring system incorporating strength, energy consumption, and cycle time enabled multidimensional evaluation of optimized solutions. Applying this curing cycle optimization method to a commercial epoxy resin increased efficiency by 247.22% and reduced energy consumption by 35.7% while meeting general product performance requirements. These results confirm the method’s reliability and its significance for improving production efficiency. Full article
(This article belongs to the Special Issue Advances in High-Performance Polymer Materials, 2nd Edition)
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30 pages, 16226 KiB  
Article
A Dual-Stage and Dual-Population Algorithm Based on Chemical Reaction Optimization for Constrained Multi-Objective Optimization
by Tianyu Zhang, Xin Guo, Yan Li, Na Li, Ruochen Zheng, Wenbo Dong and Weichao Ding
Processes 2025, 13(8), 2484; https://doi.org/10.3390/pr13082484 (registering DOI) - 6 Aug 2025
Abstract
Constrained multi-objective optimization problems (CMOPs) require optimizing multiple conflicting objectives while satisfying complex constraints. These constraints generate infeasible regions that challenge traditional algorithms in balancing feasibility and Pareto frontier diversity. chemical reaction optimization (CRO) effectively balances global exploration and local exploitation through molecular [...] Read more.
Constrained multi-objective optimization problems (CMOPs) require optimizing multiple conflicting objectives while satisfying complex constraints. These constraints generate infeasible regions that challenge traditional algorithms in balancing feasibility and Pareto frontier diversity. chemical reaction optimization (CRO) effectively balances global exploration and local exploitation through molecular collision reactions and energy management, thereby enhancing search efficiency. However, standard CRO variants often struggle with CMOPs due to the absence of specialized constraint-handling mechanisms. To address these challenges, this paper integrates the CRO collision reaction mechanism with an existing evolutionary computational framework to design a dual-stage and dual-population chemical reaction optimization (DDCRO) algorithm. This approach employs a staged optimization strategy, which divides population evolution into two phases. The first phase focuses on objective optimization to enhance population diversity, and the second prioritizes constraint satisfaction to accelerate convergence toward the constrained Pareto front. Furthermore, to leverage the infeasible solutions’ guiding potential during the search, DDCRO adopts a two-population strategy. At each stage, the main population tackles the original constrained problem, while the auxiliary population addresses the corresponding unconstrained version. A weak complementary mechanism facilitates information sharing between populations, which enhances search efficiency and algorithmic robustness. Comparative tests on multiple test suites reveal that DDCRO achieves optimal IGD/HV values in 53% of test problems. The proposed algorithm outperforms other state-of-the-art algorithms in both convergence and population diversity. Full article
(This article belongs to the Section Chemical Processes and Systems)
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22 pages, 734 KiB  
Article
An Assembly Accuracy Analysis Method for Weak Rigid Components
by Dongping Zhao, Zhe Yuan, Xiaosong Zhao and Gangfeng Wang
Machines 2025, 13(8), 694; https://doi.org/10.3390/machines13080694 (registering DOI) - 6 Aug 2025
Abstract
Most existing assembly accuracy analysis methods focus on rigid assemblies or assume assemblies to be rigid bodies, neglecting the influence of assembly deformation in weak rigid components (WRCs) such as thin-walled structures, cantilever structures, etc. As a result, the assembly accuracy analysis becomes [...] Read more.
Most existing assembly accuracy analysis methods focus on rigid assemblies or assume assemblies to be rigid bodies, neglecting the influence of assembly deformation in weak rigid components (WRCs) such as thin-walled structures, cantilever structures, etc. As a result, the assembly accuracy analysis becomes inaccurate, and the accuracy of key components cannot be effectively controlled. This may lead to serious issues such as forced assembly, repair, and rework. To address these problems, this study proposes a rigid–flexible coupling-based assembly accuracy analysis method for WRCs. The stiffness matrix and assembly deformation of WRCs are calculated, and by coupling assembly deformation with other assembly deviations, a rigid–flexible coupling assembly accuracy data model is established. This model incorporates multiple deviation sources, including assembly process variations, design tolerances, and assembly deformations. Assembly deviation transfer modeling and accumulation calculation methods for WRCs are investigated, enabling assembly accuracy simulation and statistical analysis. A case study on WRC assembly accuracy analysis is conducted, and the results demonstrate that the proposed method improves the accuracy of assembly analysis for WRCs, verifying its reliability. Full article
30 pages, 2099 KiB  
Article
SABE-YOLO: Structure-Aware and Boundary-Enhanced YOLO for Weld Seam Instance Segmentation
by Rui Wen, Wu Xie, Yong Fan and Lanlan Shen
J. Imaging 2025, 11(8), 262; https://doi.org/10.3390/jimaging11080262 (registering DOI) - 6 Aug 2025
Abstract
Accurate weld seam recognition is essential in automated welding systems, as it directly affects path planning and welding quality. With the rapid advancement of industrial vision, weld seam instance segmentation has emerged as a prominent research focus in both academia and industry. However, [...] Read more.
Accurate weld seam recognition is essential in automated welding systems, as it directly affects path planning and welding quality. With the rapid advancement of industrial vision, weld seam instance segmentation has emerged as a prominent research focus in both academia and industry. However, existing approaches still face significant challenges in boundary perception and structural representation. Due to the inherently elongated shapes, complex geometries, and blurred edges of weld seams, current segmentation models often struggle to maintain high accuracy in practical applications. To address this issue, a novel structure-aware and boundary-enhanced YOLO (SABE-YOLO) is proposed for weld seam instance segmentation. First, a Structure-Aware Fusion Module (SAFM) is designed to enhance structural feature representation through strip pooling attention and element-wise multiplicative fusion, targeting the difficulty in extracting elongated and complex features. Second, a C2f-based Boundary-Enhanced Aggregation Module (C2f-BEAM) is constructed to improve edge feature sensitivity by integrating multi-scale boundary detail extraction, feature aggregation, and attention mechanisms. Finally, the inner minimum point distance-based intersection over union (Inner-MPDIoU) is introduced to improve localization accuracy for weld seam regions. Experimental results on the self-built weld seam image dataset show that SABE-YOLO outperforms YOLOv8n-Seg by 3 percentage points in the AP(50–95) metric, reaching 46.3%. Meanwhile, it maintains a low computational cost (18.3 GFLOPs) and a small number of parameters (6.6M), while achieving an inference speed of 127 FPS, demonstrating a favorable trade-off between segmentation accuracy and computational efficiency. The proposed method provides an effective solution for high-precision visual perception of complex weld seam structures and demonstrates strong potential for industrial application. Full article
(This article belongs to the Section Image and Video Processing)
9 pages, 1406 KiB  
Proceeding Paper
Disaster-Based Mobile Learning System Using Technology Acceptance Model
by John A. Bacus
Eng. Proc. 2025, 103(1), 5; https://doi.org/10.3390/engproc2025103005 (registering DOI) - 6 Aug 2025
Abstract
Recently, the usage of mobile phone-based games has increased due to the growing accessibility and convenience they provide. Using a descriptive-quantitative design, a disaster-based mobile application was developed in this study to enhance disaster literacy among the private senior high schools in science, [...] Read more.
Recently, the usage of mobile phone-based games has increased due to the growing accessibility and convenience they provide. Using a descriptive-quantitative design, a disaster-based mobile application was developed in this study to enhance disaster literacy among the private senior high schools in science, technology, engineering, and mathematics (STEM) education in Davao City, the Philippines. The developed application was provided together with survey questionnaires to 364 students randomly selected from different schools in Davao City usingF a simple random sampling method. The technology acceptance (TAM) model was used to explain how users accepted the new technology. The mobile application was designed with features in four disaster scenarios—fire, flood, volcano, and earthquake. The results revealed a high acceptance, with an average score of the perceived usefulness (PE) of 4.52, perceived ease of use (PEOU) of 4.44, and a behavioral intention (BI) of 4.12. The students accepted the application to enhance disaster risk reduction and management. Aligned with SDG 4 and SDG 11, the application can be used to equip users with the knowledge to respond to disasters and ensure community resilience. Full article
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21 pages, 19752 KiB  
Article
Phase Characterisation for Recycling of Shredded Waste Printed Circuit Boards
by Laurance Donnelly, Duncan Pirrie, Matthew Power and Andrew Menzies
Recycling 2025, 10(4), 157; https://doi.org/10.3390/recycling10040157 (registering DOI) - 6 Aug 2025
Abstract
In this study, we adopt a geometallurgical analytical approach common in mineral processing in the characterization of samples of shredded waste printed circuit board (PCB) E-waste, originating from Europe. Conventionally, bulk chemical analysis provides a value for E-waste; however, chemical analysis alone does [...] Read more.
In this study, we adopt a geometallurgical analytical approach common in mineral processing in the characterization of samples of shredded waste printed circuit board (PCB) E-waste, originating from Europe. Conventionally, bulk chemical analysis provides a value for E-waste; however, chemical analysis alone does not provide information on the textural variability, phase complexity, grain size, particle morphology, phase liberation and associations. To address this, we have integrated analysis using binocular microscopy, manual scanning electron microscopy, phase, textural and compositional analyses by automated (SEM-EDS), phase analysis based on (Automated Material Identification and Classification System (AMICS) software, and elemental analysis using micro-XRF. All methods used have strengths and limitations, but an integration of these analytical tools allows the detailed characterization of the texture and composition of the E-waste feeds, ahead of waste reprocessing. These data can then be used to aid the design of optimized processing circuits for the recovery of the key payable components, and assist in the commercial trading of e-scrap. Full article
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15 pages, 1458 KiB  
Article
Effect of Precipitation Change on Desert Steppe Aboveground Productivity
by Yonghong Luo, Jiming Cheng, Ziyu Cao, Haixiang Zhang, Pengcuo Danba, Jiazhi Wang, Ying Wang, Rong Zhang, Chao Zhang, Yingqun Feng and Shuhua Wei
Biology 2025, 14(8), 1010; https://doi.org/10.3390/biology14081010 (registering DOI) - 6 Aug 2025
Abstract
Precipitation changes have significant impacts on biodiversity and ecosystem productivity. However, the effects of precipitation changes on species diversity have been the focus of most previous studies. Little is known about the contributions of different dimensions of biodiversity (species, functional, and phylogenetic diversity) [...] Read more.
Precipitation changes have significant impacts on biodiversity and ecosystem productivity. However, the effects of precipitation changes on species diversity have been the focus of most previous studies. Little is known about the contributions of different dimensions of biodiversity (species, functional, and phylogenetic diversity) in linking long-term precipitation changes to ecosystem functions. In this study, a randomized design was conducted in the desert steppes of Ningxia, which included three treatments: natural rainfall, precipitation reduced by 50%, and precipitation increased by 50%. After 4 years of treatment, the effects of precipitation changes on aboveground productivity and its underlying mechanisms were explored. The results showed that (1) reduced precipitation significantly decreased phylogenetic diversity and species diversity, but had no significant effect on functional diversity; (2) reduced precipitation significantly decreased aboveground productivity, while increased precipitation significantly enhanced aboveground productivity; and (3) changes in precipitation primarily regulated aboveground productivity by altering soil nitrogen availability and the size of dominant plant species. This study provides important theoretical and practical guidance for the protection and management of desert steppe vegetation under future climate change. Full article
(This article belongs to the Section Ecology)
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31 pages, 16823 KiB  
Article
Simulation Analysis and Research on the Separation and Screening of Adherent Foreign Substances in Raisins Based on Discrete Elements
by Rui Zhang, Meng Ning, Hongrui Ma and Ziheng Zhan
Appl. Sci. 2025, 15(15), 8695; https://doi.org/10.3390/app15158695 (registering DOI) - 6 Aug 2025
Abstract
To address the issue that existing raisin foreign object removal equipment cannot eliminate surface contaminants adhered to raisins through non-washing methods, this paper proposes an adhesive foreign object removal method based on “rapid freezing–rolling extrusion separation-airflow screening”. A raisin adhesive foreign object removal [...] Read more.
To address the issue that existing raisin foreign object removal equipment cannot eliminate surface contaminants adhered to raisins through non-washing methods, this paper proposes an adhesive foreign object removal method based on “rapid freezing–rolling extrusion separation-airflow screening”. A raisin adhesive foreign object removal device was designed based on this method. The separation and removal processes of adhesive foreign objects were analyzed and optimized through simulation, followed by device fabrication and performance testing. Starting from the separation process of raisins and adhesive foreign objects, we conducted experimental studies on quick-freezing separation, determined the most suitable separation method based on experimental results, and performed structural design of the equipment accordingly. To conduct simulation analysis and optimization, material parameters were calibrated. The working process of foreign object separation was simulated and optimized using discrete element method (DEM) simulation, verifying the equipment’s separation capability for different adhesive foreign objects while determining the optimal rotational speed of 600 r/min. Through EDEM-Fluent coupled simulation, the working process of foreign object removal was analyzed and optimized, validating the influence of flow field on foreign object removal and determining the optimal air velocity of 11 m/s. The equipment was ultimately fabricated, with further parameter optimization and comprehensive performance testing conducted. The final optimal rotational speed and air velocity were determined as 650 r/min and 11 m/s, respectively. In terms of comprehensive performance, the equipment achieved a separation rate of 93.76%, damage rate of 3.05%, residue rate of 4.28%, removal rate of 94.52%, carry-over ratio of 71:1, and processing capacity of 120 kg/h. Full article
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23 pages, 3036 KiB  
Article
Research on the Synergistic Mechanism Design of Electricity-CET-TGC Markets and Transaction Strategies for Multiple Entities
by Zhenjiang Shi, Mengmeng Zhang, Lei An, Yan Lu, Daoshun Zha, Lili Liu and Tiantian Feng
Sustainability 2025, 17(15), 7130; https://doi.org/10.3390/su17157130 (registering DOI) - 6 Aug 2025
Abstract
In the context of the global response to climate change and the active promotion of energy transformation, a number of low-carbon policies coupled with the development of synergies to help power system transformation is an important initiative. However, the insufficient articulation of the [...] Read more.
In the context of the global response to climate change and the active promotion of energy transformation, a number of low-carbon policies coupled with the development of synergies to help power system transformation is an important initiative. However, the insufficient articulation of the green power market, tradable green certificate (TGC) market, and carbon emission trading (CET) mechanism, and the ambiguous policy boundaries affect the trading decisions made by its market participants. Therefore, this paper systematically analyses the composition of the main players in the electricity-CET-TGC markets and their relationship with each other, and designs the synergistic mechanism of the electricity-CET-TGC markets, based on which, it constructs the optimal profit model of the thermal power plant operators, renewable energy manufacturers, power grid enterprises, power users and load aggregators under the electricity-CET-TGC markets synergy, and analyses the behavioural decision-making of the main players in the electricity-CET-TGC markets as well as the electric power system to optimise the trading strategy of each player. The results of the study show that: (1) The synergistic mechanism of electricity-CET-TGC markets can increase the proportion of green power grid-connected in the new type of power system. (2) In the selection of different environmental rights and benefits products, the direct participation of green power in the market-oriented trading is the main way, followed by applying for conversion of green power into China certified emission reduction (CCER). (3) The development of independent energy storage technology can produce greater economic and environmental benefits. This study provides policy support to promote the synergistic development of the electricity-CET-TGC markets and assist the low-carbon transformation of the power industry. Full article
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28 pages, 1211 KiB  
Review
Phosphorus in Salmonid Aquaculture: Sources, Requirements, and System-Level Implications
by Vegard Øvstetun Flo, Torbjørn Åsgård and Odd-Ivar Lekang
Fishes 2025, 10(8), 388; https://doi.org/10.3390/fishes10080388 (registering DOI) - 6 Aug 2025
Abstract
This review provides a comprehensive synthesis of phosphorus (P) dynamics relevant to salmonid aquaculture, with a particular focus on Atlantic salmon. It explores the global P cycle, the chemical forms of P in aquatic systems, and the implications of P sourcing, processing, and [...] Read more.
This review provides a comprehensive synthesis of phosphorus (P) dynamics relevant to salmonid aquaculture, with a particular focus on Atlantic salmon. It explores the global P cycle, the chemical forms of P in aquatic systems, and the implications of P sourcing, processing, and availability in aquafeeds. The review distinguishes between digestibility and availability of P, summarizes requirement studies, and evaluates the contribution of marine, animal, vegetable, and inorganic sources to dietary P. It also examines how aquaculture system design, particularly recirculating aquaculture systems (RASs), influences P accumulation and emissions. By integrating nutritional, physiological, and environmental perspectives, this review offers a uniquely holistic view of P efficiency and sustainability in salmonid aquaculture. Full article
(This article belongs to the Section Sustainable Aquaculture)
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