Modulation Capacity Research Articles

Innovative encapsulation of alkali activators in alkali-activated slag concrete: A sustainable strategy for regulating setting time and durability

The scientific community has devoted considerable attention to alkali-activated slag binder systems, due to the low-carbon footprint and eco-friendly attributes. However, the regulation of setting time poses significant challenges to the widespread application in practical engineering environments. This study proposes an innovative approach to encapsulate alkali activators in capsules or tablets, followed by the incorporation into the alkali slag concrete matrix. This strategy aims to regulate and control the early dissolution and hydration rate of slag, thereby altering the setting time of the alkali-activated material. Specifically, this method can prolong the setting time by approximately 40%. Importantly, this intervention does not significantly damage the mechanical properties of materials over the 28 days due to the continuous outward diffusion of the active ingredients of the alkali activator. This encapsulation technique harbors the capacity for quantitative modulation of the setting time in alkali-activated slag concrete. The findings of this research offer valuable theoretical insights, paving the way for the application of alkali-activated hydration systems in diverse engineering domains.

Kir4.1 channels contribute to astrocyte CO2/H+-sensitivity and the drive to breathe

Astrocytes in the retrotrapezoid nucleus (RTN) stimulate breathing in response to CO2/H+, however, it is not clear how these cells detect changes in CO2/H+. Considering Kir4.1/5.1 channels are CO2/H+-sensitive and important for several astrocyte-dependent processes, we consider Kir4.1/5.1 a leading candidate CO2/H+ sensor in RTN astrocytes. To address this, we show that RTN astrocytes express Kir4.1 and Kir5.1 transcripts. We also characterized respiratory function in astrocyte-specific inducible Kir4.1 knockout mice (Kir4.1 cKO); these mice breathe normally under room air conditions but show a blunted ventilatory response to high levels of CO2, which could be partly rescued by viral mediated re-expression of Kir4.1 in RTN astrocytes. At the cellular level, astrocytes in slices from astrocyte-specific inducible Kir4.1 knockout mice are less responsive to CO2/H+ and show a diminished capacity for paracrine modulation of respiratory neurons. These results suggest Kir4.1/5.1 channels in RTN astrocytes contribute to respiratory behavior.

The Mechanism of the Semi-Transparent Coverings Affecting the Power Generation Capacity of the Photovoltaic Module and Array

Shading on photovoltaic (PV) modules due to shadows, covering, dust, etc., usually characterized as semi-transparent, will significantly affect the power generation capacity. No systematic study has considered the impact of semi-transparent coverings on the power generation capacity of PV modules. This paper covers a single cell in the PV module using a covering with a transmittance of 18.55% and systematically investigates its impact on the power generation capacity. The open-circuit voltage (Voc) of the PV module is nearly unaffected by semi-transparent coverings because the covered cell can be considered as working at a lower irradiance and thus can output a voltage close to that of the uncovered cell. The short-circuit current (Isc) is significantly affected by coverings because it is co-contributed by the photocurrent (evaluated based on the covering ratio R and transmittance) and the reverse bias current ΔIsc (the covered cell is in a reverse bias state). The ΔIsc increases with R because more charge accumulates at the bi-ends of the covered cell; but, it decreases at full covering, which implies that in a partially covered case the uncovered part contributes more to ΔIsc than the covered part. The fill factor (FF) of the PV module first increases and then decreases with R, as the equivalent resistance of the covered cell increases rapidly with R, which replaces the wire resistance in dominating the series resistance of the PV module when R > 0.6. This work is of great theoretical significance in analyzing the output characteristics of PV modules under real conditions.

Development of porous structure for broadening Bragg-peak in scanning carbon-ion radiotherapy: Monte Carlo simulation and experimental validation

PurposeThe present study aimed to develop a porous structure with plug-ins (PSP) to broaden the Bragg peak width (BPW, defined as the distance in water between the proximal and distal 80% dose) of the carbon ion beam while maintaining a sharp distal falloff width (DFW, defined as the distance along the beam axis where the dose in water reduces from 80% to 20%). MethodsThe binary voxel models of porous structure (PS) and PSP were established in the Monte Carlo code FLUKA and the corresponding physical models were manufactured by 3D printing. Both experiment and simulation were performed for evaluating the modulation capacity of PS and PSP. BPWs and DFWs derived from each integral depth dose curves were compared. Fluence homogeneity of 430 MeV/u carbon-ion beam passing through the PSP was recorded by analyzing radiochromic films at six different locations downstream the PSP in the experiment. Additionally, by changing the beam spot size and incident position on the PSP, totally 48 different carbon-ion beams were simulated and corresponding deviations of beam metrics were evaluated to test the modulating stability of PSP. ResultsAccording to the measurement data, the use of PSP resulted in an average increase of 0.63 mm in BPW and a decrease of 0.74 mm in DFW compared to PS. The 2D radiation field inhomogeneities were lower than 3 % when the beam passing through a ≥ 10 cm PMMA medium. Furthermore, employing a spot size of ≥ 6 mm ensures that beam metric deviations, including BPW, DFW, and range, remain within a deviation of 0.1 mm across various incident positions. ConclusionThe developed PSP demonstrated its capability to effectively broaden the BPW of carbon ion beams while maintaining a sharp DFW comparing to PS. The superior performance of PSP, indicates its potential for clinical use in the future.

Review on allosteric modulators of dopamine receptors so far.

Background Contemporary research is predominantly directed towards allosteric modulators, a class of compounds designed to interact with specific sites distinct from the orthosteric site on G protein-coupled receptors. These allosteric modulators play a pivotal role in influencing diverse pharmacological effects, such as agonism/inverse agonism, efficacy modulation, and affinity modulation. One particularly intriguing aspect is the demonstrated capacity of allosteric modulation to enhance drug selectivity for therapeutic purposes, potentially leading to a reduction in serious side effects associated with traditional approaches. Allosteric ligands, a majority of which fall into the categories of negative allosteric modulators or positive allosteric modulators, exhibit the unique ability to either diminish or enhance the effects of endogenous ligands. Negative allosteric modulators weaken the response, while positive allosteric modulators intensify it. Additionally, silent allosteric modulators represent a distinct class that neither activates nor blocks the effects of endogenous ligands, adding complexity to the spectrum of allosteric modulation. In the broader context of central nervous system disorders, allosteric modulation takes center stage, particularly in the realm of dopamine receptors specifically, D1, D2, and D3 receptors. These receptors hold immense therapeutic potential for a range of conditions spanning neurodegenerative disorders to neurobehavioral and psychiatric disorders. The intricate modulation of dopamine receptors through allosteric mechanisms offers a nuanced and versatile approach to drug development. As research endeavors continue to unfold, the exploration of allosteric modulation stands as a promising frontier, holding the potential to reshape the landscape of drug discovery and therapeutic interventions in the field of neurology and psychiatry.

Study on overvoltage suppression method of phase modulation of hydroelectric generating units and its cooperative optimization in new energy grid

When a significant portion of renewable energy is transmitted to the power grid through high voltage direct current, when the monopolar blocking occurs, as a result of the converter station’s filter and reactive power compensation equipment’s influence, overvoltage will be generated, which will cause harm to the new energy station, and even lead to large-scale new energy grid disconnection. This paper initially examines the mechanism behind overvoltage in a new energy power grid and then puts forward a method to restrain overvoltage by using phase modulation operation of hydroelectric generating units. To improve the phase modulation capability of hydroelectric generating units and optimize the utilization of new energy sources, this paper proposes a particle swarm optimization to determine the optimal phase modulation capacity. Finally, this paper builds an example of the PSASP platform to verify the correctness and effectiveness of collaborative optimization.

Performance analytics of adaptive subcarrier intensity modulated free-space optical communications over general Málaga turbulence links

In this paper, we study the performance analysis of free-space optical (FSO) system employing a constant-power variable-rate adaptive subcarrier intensity modulation (SIM) and utilizing phase-shift keying (PSK) over the Málaga atmospheric turbulence with pointing errors. According to a target bit-error rate (BER) and the instantaneous signal-to-noise ratio (SNR), the adaptive strategy adopts the subcarrier PSK modulation order. More precisely, we develop new analytical expressions for the average BER, the upper bound on ergodic channel capacity for non-adaptive modulation, and the attainable spectral efficiency (SE) of an adaptive SIM-FSO communication system. According to the simulation results, it is possible to achieve an increase in SE under weak-to-strong turbulence conditions without the need to increase the average optical power transmitted or compromise the BER requirements.

Naringin-induced M2 macrophage polarization facilitates osteogenesis of BMSCs and improves cranial bone defect healing in rat

Osteoimmunology has uncovered the critical role of the immune microenvironment in the bone healing process, with macrophages playing a central part in generating immune responses via chemokine production. Naringin, a flavanone glycoside extracted from various plants, has been shown to promote osteoblast differentiation, thereby enhancing bone formation and mitigating osteoporosis progression. Current research on the osteogenic mechanism primarily focuses on the direct impact of naringin on mesenchymal stem cells, while its indirect immunoregulatory effects remain elusive. In this study, we investigated the bone defect-enhancing effects of varying naringin concentrations in vivo using a cranial bone defect model in Sprague-Dawley rats. We assessed the osteoimmune modulation capacity of naringin by exposing lipopolysaccharide (LPS)-induced RAW 264.7 macrophages to different doses of naringin. To further elucidate the underlying osteogenic enhancement mechanism, Bone Marrow Stromal Cells (BMSCs) derived from mice were treated with conditioned media from naringin-treated macrophages. Our findings indicated that naringin promotes M2 phenotype polarization in macrophages, as evidenced by the downregulation of pro-inflammatory cytokines Inducible Nitric Oxide Synthase (iNOS), interleukin (IL)-1β, and Tumor Necrosis Factor (TNF)-α, and the upregulation of anti-inflammatory cytokine Transforming growth factor (TGF)-β. Transcriptome analysis revealed that differentially expressed genes were significantly enriched in osteoblast differentiation and anti-inflammatory response pathways in naringin-pretreated macrophages, with the cytokines signaling pathway being upregulated. The conditioned media from naringin-treated macrophages stimulated the expression of osteogenic-related genes Alkaline phosphatase (Alp), osteocalcin (Ocn), osteopontin (Opn), and Runt-related transcription factor (Runx) 2, as well as protein expression in BMSCs. In conclusion, naringin alleviates macrophage inflammation by promoting M2 phenotype polarization, which in turn enhances the osteogenic differentiation of BMSCs, contributing to its bone healing effects in vivo. These results suggest that naringin holds significant potential for improving bone defect healing through osteoimmune modulation.

Advancements and Innovative Strategies in Induced Pluripotent Stem Cell-Derived Mesenchymal Stem Cell Therapy: A Comprehensive Review.

The effectiveness and safety of mesenchymal stem cell (MSC) therapy have been substantiated across various diseases. Nevertheless, challenges such as the restricted in vitro expansion capacity of tissue-derived MSCs and the clinical instability due to the high heterogeneity of isolated cells require urgent resolution. The induced pluripotent stem cell-derived MSCs (iPSC-MSCs), which is differentiated from iPSCs via specific experimental pathways, holds considerable potential as a substitute for tissue derived MSCs. Multiple studies have demonstrated that iPSCs can be differentiated into iPSC-MSCs through diverse differentiation strategies. Research suggests that iPSC-MSCs, when compared to tissue derived MSCs, exhibit superior characteristics in terms of proliferation ability, immune modulation capacity, and biological efficiency. In this review, we meticulously described and summarized the experimental methods of iPSC differentiation into iPSC-MSCs, the application of iPSC-MSCs in various disease models, the latest advancements in clinically relevant iPSC-derived cell products, and the development strategies for the next generation of iPSC-derived therapy products (not only cell products but also their derivatives).

Prediction of thermal boundary layer thickness and bidirectional effect of dust deposition on the output of photovoltaic modules

Photovoltaic power generation was one of the fastest-growing and most promising forms of solar energy utilization, and dust deposition had an important effect on the output capacity of photovoltaic modules. However, the law and mechanism of dust deposition influence the output performance of the PV modules was still not perfect and deep enough at present. In this paper, the prediction model of the thermal boundary layer thickness (δT) was constructed, and the influence laws of dust deposition on the total attenuation rate (rt) of the top surface and the average temperature (TW) of the backplane surface were explored. Besides, the bidirectional effect of dust deposition on the output performance was researched. The results show that the main components of the dust on the top surface of the PV modules were the quartz or aluminosilicate transported remotely by atmospheric circulation and deposited. The δT at any position of the photovoltaic module decreased with the increase of parallel wind speed (v∥) by the law of −0.49800 power function, and convective heat transfer coefficient (h) changed positively with Re by the law of 0.48752 power function. In the total solar irradiance (G) decreases period and dust deposition amount (A) was 2.024201 g/m2, the influence rate of dust deposition (r) had a maximum value of 0.015363. The dust deposition attenuation rate (rdA) and the temperature gain rate (rtE) all changed positively with A by power function law, and the increase rate of rtE and rdA eventually tends to 0 and infinity, respectively. The theoretical dust removal point of the rooftop PV modules in Hohhot Urban was 5.82661 g/m2.

Epigallocatechin-3-gallate attenuates arsenic-induced fibrogenic changes in human kidney epithelial cells through reversal of epigenetic aberrations and antioxidant activities.

Renal fibrosis is a pathogenic intermediate stage of chronic kidney disease (CKD). Nephrotoxicants including arsenic can cause kidney fibrosis through induction of oxidative stress and epigenetic aberrations. Epigallocatechin-3-gallate (EGCG), a green tea polyphenol, is known to have antioxidant and epigenetic modulation properties. Whether EGCG, through its antioxidant and epigenetic modulating activities, can attenuate fibrogenesis is not known. Therefore, the objective of this study was to determine whether EGCG can attenuate arsenic-induced acute injury and long-term exposure associated fibrogenicity in kidney epithelial cells. To address this question, two human kidney epithelial cell lines Caki-1 and HK-2 exposed to arsenic for both acute and long-term durations were treated with EGCG. The protective effect of EGCG on arsenic-induced cytotoxicity and fibrogenicity were evaluated by measuring the cell growth, reactive oxygen species (ROS) production, genes expression, and epigenetic changes in histone marks. Results revealed that EGCG has a protective effect in arsenic-induced acute cytotoxicity in these cells. EGCG scavenges the increased levels of ROS in arsenic exposed cells. Aberrant expression of fibrogenic genes in arsenic exposed cells were restored by EGCG. Abrogation of arsenic-induced fibrogenic changes was also associated with EGCG-mediated restoration of arsenic-induced aberrant expression of epigenetic regulatory proteins and histone marks. Novel findings of this study suggest that EGCG, through its antioxidant and epigenetic modulation capacities, has protective effects against arsenic-induced cytotoxicity and fibrogenic changes in kidney epithelial cells.

Operationalizing modular autonomous customised buses based on different demand prediction scenarios

ABSTRACT This paper presents a novel framework for customised modular bus systems that leverages travel demand prediction and modular autonomous vehicles to optimise services proactively. The proposed framework addresses two prediction scenarios with different forward-looking operations: optimistic operation and pessimistic operation. A mixed integer programming model in a space-time-state network is developed for the optimistic operation to determine module routes, schedules, formations and passenger-to-module assignments. For the pessimistic case, a two-stage optimisation procedure is introduced. The first stage involves two formulations (i.e., deterministic and robust) to generate cost-saving plans, and the second stage adapts plans with control strategies periodically. A Lagrangian heuristic approach is proposed to solve formulations efficiently. The performance of the proposed framework is evaluated using smartcard data from Beijing and two state-of-the-art machine learning algorithms. Results indicate that the proposed framework outperforms the real-time approach in operating costs and highlights the role of module capacity and time dependency.

Research on design and multi-frequency scheduling optimization method for flexible green ammonia system

As an important chemical product and energy carrier, green ammonia is a way to consume large quantities of green hydrogen produced from renewable electricity. For the optimization of the green ammonia production systems, a primary problem is to solve the electricity-hydrogen-ammonia matching problem under multi-frequency and multi-amplitude load fluctuations. In this work, a method for capacity designing and scheduling optimization of a hybrid multi-frequency flexible green ammonia system is constructed. The method can be applied to design the whole green ammonia system in grid-connected and isolated scenarios. The established model can accurately describe the electricity-hydrogen-ammonia matching characteristics of each module. Furthermore, many important practical engineering constraints are taken into account, such as the operating time of the chemical device, and the flexibility of the ammonia device. This work verifies the effectiveness of the proposed method based on a real case, and the impact of load range, adjustment speed, and adjustment frequency of the ammonia synthesis process on the product cost and module capacity.

MiRNAs and Substances Abuse: Clinical and Forensic Pathological Implications: A Systematic Review

Substance addiction is a chronic and relapsing brain disorder characterized by compulsive seeking and continued substance use, despite adverse consequences. The high prevalence and social burden of addiction are indisputable; however, the available intervention is insufficient. The modulation of gene expression and aberrant adaptation of neural networks are attributed to the changes in brain functions under repeated exposure to addictive substances. Considerable studies have demonstrated that miRNAs are strong modulators of post-transcriptional gene expression in substance addiction. The emerging role of microRNA (miRNA) provides new insights into many biological and pathological processes in the central nervous system: their variable expression in different regions of the brain and tissues may play a key role in regulating the pathophysiological events of addiction. This work provides an overview of the current literature on miRNAs involved in addiction, evaluating their impaired expression and regulatory role in neuroadaptation and synaptic plasticity. Clinical implications of such modulatory capacities will be estimated. Specifically, it will evaluate the potential diagnostic role of miRNAs in the various stages of drug and substance addiction. Future perspectives about miRNAs as potential novel therapeutic targets for substance addiction and abuse will also be provided.

Cross-kingdom regulation by plant-derived miRNAs in mammalian systems.

MicroRNAs (miRNAs) are small noncoding RNA molecules ubiquitously distributed across diverse organisms, serving as pivotal regulators of genetic expression. Notably, plant-derived miRNAs have been demonstrated to have unique bioactivity and certain stability in mammalian systems, thereby facilitating their capacity for cross-kingdom modulation of gene expression. While there is substantial evidence supporting the regulation of mammalian cells by plant-derived miRNAs, several questions remain unanswered. Specifically, a comprehensive investigation of the mechanisms underlying the stability and transport of plant miRNAs and their cross-kingdom regulation of gene expression in mammals remains to be done. In this review, we summarized the origin, processing, and functional mechanisms of plant miRNAs in mammalian tissues and circulation, emphasizing their greater resistance to mammalian digestion and circulation systems compared to animal miRNAs. Additionally, we introduce four well-known plant miRNAs that have been extensively studied for their functions and mechanisms in mammalian systems. By delving into these aspects, we aim to offer a fundamental understanding of this intriguing field and shed light on the complex interactions between plant miRNAs and mammalian biology.

Research on frequency modulation capacity configuration and control strategy of multiple energy storage auxiliary thermal power unit

The rapid development of new energy sources has had an enormous impact on the existing power grid structure to support the “dual carbon” goal and the construction of a new type of power system, make thermal power units better cope with the impact on the original grid structure under the background of the rapid development of new energy sources, promote the consumption of new energy sources such as solar and wind energy, and further expand the channels for upgrading and flexibility transformation of thermal power energy storage, improve the stability, safety and economy of thermal power unit operation. Therefore, based on the research status at home and abroad, a hybrid energy storage system is added to solve the above problems. The lithium battery-flywheel control strategy and the regional dynamic primary frequency modulation model of thermal power units are proposed, and study the capacity configuration scheme of flywheel‑lithium battery hybrid energy storage system under a certain energy storage capacity, the frequency modulation performance is evaluated by the system frequency fluctuation degree, fluctuation peak range and other indicators. Study under a certain energy storage capacity thermal power unit coupling hybrid energy storage system to participate in a frequency modulation of the optimal capacity configuration scheme, and perform simulation verification using MATLAB/Simulink. When the thermal power unit is coupled with a 10.8612 MW/2.7151 MWh flywheel energy storage system and a 4.1378 MW/16.5491 MWh lithium battery energy storage system, while adaptive variable coefficient droop control is adopted, the system frequency range is 0.00328 p.u.Hz, and the fluctuation degree of the output power of the thermal power units is 0.00498 p.u.MW, compared to the individual frequency regulation of thermal power units, it reduces 52.07 % and. The results show that when the thermal power unit is disturbed by external load, hybrid energy storage assisted thermal power unit frequency modulation reduces the mechanical loss of thermal power unit to a certain extent and extends the service life of the unit, effectively improve the operation stability and economy of thermal power units, further reduce the phenomenon of abandoning wind and light, and better promote the utilization of new energy.

SwinCross: Cross-modal Swin transformer for head-and-neck tumor segmentation in PET/CT images.

Radiotherapy (RT) combined with cetuximab is the standard treatment for patients with inoperable head and neck cancers. Segmentation of head and neck (H&N) tumors is a prerequisite for radiotherapy planning but a time-consuming process. In recent years, deep convolutional neural networks (DCNN) have become the de facto standard for automated image segmentation. However, due to the expensive computational cost associated with enlarging the field of view in DCNNs, their ability to model long-range dependency is still limited, and this can result in sub-optimal segmentation performance for objects with background context spanning over long distances. On the other hand, Transformer models have demonstrated excellent capabilities in capturing such long-range information in several semantic segmentation tasks performed on medical images. Despite the impressive representation capacity of vision transformer models, current vision transformer-based segmentation models still suffer from inconsistent and incorrect dense predictions when fed with multi-modal input data. We suspect that the power of their self-attention mechanism may be limited in extracting the complementary information that exists in multi-modal data. To this end, we propose a novel segmentation model, debuted, Cross-modal Swin Transformer (SwinCross), with cross-modal attention (CMA) module to incorporate cross-modal feature extraction at multiple resolutions. We propose a novel architecture for cross-modal 3D semantic segmentation with two main components: (1) a cross-modal 3D Swin Transformer for integrating information from multiple modalities (PET and CT), and (2) a cross-modal shifted window attention block for learning complementary information from the modalities. To evaluate the efficacy of our approach, we conducted experiments and ablation studies on the HECKTOR 2021 challenge dataset. We compared our method against nnU-Net (the backbone of the top-5 methods in HECKTOR 2021) and other state-of-the-art transformer-based models, including UNETR and Swin UNETR. The experiments employed a five-fold cross-validation setup using PET and CT images. Empirical evidence demonstrates that our proposed method consistently outperforms the comparative techniques. This success can be attributed to the CMA module's capacity to enhance inter-modality feature representations between PET and CT during head-and-neck tumor segmentation. Notably, SwinCross consistently surpasses Swin UNETR across all five folds, showcasing its proficiency in learning multi-modal feature representations at varying resolutions through the cross-modal attention modules. We introduced a cross-modal Swin Transformer for automating the delineation of head and neck tumors in PET and CT images. Our model incorporates a cross-modality attention module, enabling the exchange of features between modalities at multiple resolutions. The experimental results establish the superiority of our method in capturing improved inter-modality correlations between PET and CT for head-and-neck tumor segmentation. Furthermore, the proposed methodology holds applicability to other semantic segmentation tasks involving different imaging modalities like SPECT/CT or PET/MRI. Code:https://github.com/yli192/SwinCross_CrossModalSwinTransformer_for_Medical_Image_Segmentation.

A Novel Multi-Channel Tandem Applicator for Direction Modulated Brachytherapy

Intracavitary brachytherapy is a fundamental part of the treatment of cervical cancer that would be applied as boost therapy. However, the coverage of non-uniform targets is very challenging for this technique when dealing with the lateral extension of tumor, particularly when the tumor is too far superiorly to be covered by radiation dose from the ovoids or rings. In such situations, the conventional (single channel) tandem applicator would need to effectively provide the entire dose to the region yet have a very limited capacity for the intensity modulation due to the isotropic nature of radiation from the 192Ir HDR source. This limitation would require development of state-of-the-art interstitial-intercavitary applicators. In this study we aim to introduce a novel multi-channel tandem applicator design in alignment with the direction modulated brachytherapy (DMBT) concept to address this important issue. The novel multi-channel tandem applicator was designed using GEANT4 Monte Carlo simulations to consist of a base, made of MR compatible PEEK plastic, with a diameter of 6.5 mm and 19 channels each 1.1 mm in diameter, and in a honeycomb arrangement. The design also incorporated 18 iridium wires with a diameter of 0.9 mm that can actively enter the channels to provide intensity modulation at desired directions. A dosimetry study was then performed with different configurations of the 192Ir HDR source, also 0.9 mm in diameter, and up to 18 iridium wires inside the base. While offering the symmetrical dose distribution of the conventional tandem, the honeycomb design could produce a variety of directional dose distributions with different degree of extended lateral coverage. Additionally, this novel design with the configuration of 18 iridium wires inside the base covering the HDR source could reduce the radiation dose to approximately 15 % behind the shielded side at 1 cm from the tandem compared to the unshielded side. The results indicated that the honeycomb DMBT tandem design, as a noninvasive intracavitary approach, could be a promising solution for covering targets with lateral asymmetry/extension. Utilizing high-density material such as tungsten as the base material could reduce the radiation leakage through the base, improve the intensity modulation and hence lateral coverage.

Supercapacitive Swing Adsorption of Carbon Dioxide: Current Status and Perspectives

AbstractSupercapacitive swing adsorption (SSA) is a newly discovered electrochemically driven carbon dioxide capture method using the principle of electric double‐layer capacitor, which achieves the purpose of adsorption and desorption of CO2 by charging and discharging the supercapacitive electrodes. Based on this method, gas separation devices were designed which could adsorb CO2 from a mixture of carbon dioxide and nitrogen, and a series of factors affecting the CO2 adsorption capacity were explored. This review briefly introduces the SSA mechanism and the structural design of SSA modules, and analyzes the factors influencing the performance of SSA from multiple aspects, with emphasis on electrode materials, in order to find ways to improve the CO2 adsorption capacity of SSA modules.

Optimal Allocation of Primary Frequency Modulation Capacity of Battery Energy Storage Based on Antlion Algorithm

Currently, the integration of new energy sources into the power system poses a significant challenge to frequency stability. To address the issue of capacity sizing when utilizing storage battery systems to assist the power grid in frequency control, a capacity optimal allocation model is proposed for the primary frequency regulation of energy storage. Due to the requirement of a large number of actual parameters for the optimal allocation model, a simulation model of energy storage capacity is constructed based on the characteristics of primary frequency control to provide the necessary parameters. Subsequently, the primary frequency modulation output model of energy storage is established by considering the basic action output, the action in the frequency modulation dead zone, and a certain capacity margin. The antlion algorithm is employed to solve the capacity optimal allocation model. Finally, three groups of experiments are designed and compared to demonstrate the effectiveness of the proposed method in setting the capacity margin, which can increase profit to a certain extent.