Porcine epidemic diarrhea virus (PEDV) is a significant pathogen affecting swine, causing severe economic losses worldwide. This study explores the regulatory role of miRNA-328-3p to ZO-1 expression and its impact on PEDV proliferation via the PLC-β1-PKC pathway in IPEC-J2 cells. We found that miRNA-328-3p can target ZO-1, influencing its expression and subsequently affecting the integrity of tight junctions in the cells. Overexpression of PLC-β1, combined with miRNA-328-3p silencing, enhanced ZO-1 expression, while PLC-β1 knockdown combined with miRNA-328-3p overexpression inhibited ZO-1 expression. Furthermore, PLC-β1 overexpression increased both viral genome expression and PEDV titers, whereas its silencing had the opposite effect. Notably, our data indicated a negative correlation between PLC-β1 and PKC expression, and PKC silencing attenuated the upregulatory effect of PLC-β1 on ZO-1. These findings suggest that PLC-β1 modulates ZO-1 expression through the PKC pathway, providing new insights into the molecular mechanisms of PEDV infection and potential therapeutic targets.

Objective: The rupture of intracranial aneurysms leads to subarachnoid hemorrhage. Detecting intracranial aneurysms before rupture and stratifying their risk is critical in guiding preventive measures. Point-based aneurysm segmentation provides a plausible pathway for automatic aneurysm detection. However, challenges in existing segmentation methods motivate the proposed work. Methods: We propose a dual-branch network model (JGTA-Net) for accurately detecting aneurysms. JGTA-Net employs a hierarchical geometric feature learning framework to extract local contextual geometric information from the point cloud representing intracranial vessels. Building on this, we integrated a topological analysis module that leverages persistent homology to capture complex structural details of 3D objects, filtering out short-lived noise to enhance the overall topological invariance of the aneurysms. Moreover, we refined the segmentation output by quantitatively computing multi-scale topological features and introducing a topological loss function to preserve the correct topological relationships better. Finally, we designed a feature fusion module that integrates information extracted from different modalities and receptive fields, enabling effective multi-source information fusion. Results: Experiments conducted on the IntrA dataset demonstrated the superiority of the proposed network model, yielding state-of-the-art segmentation results (e.g., Dice and IOU are approximately 0.95 and 0.90, respectively). Our IntrA results were confirmed by testing on two independent datasets: One with comparable lengths to the IntrA dataset and the other with longer and more complex vessels. Conclusions: The proposed JGTA-Net model outperformed other recently published methods (>10% in DSC), showing our model's strong generalization capabilities. Significance: The proposed work can be integrated into a large deep-learning-based system for assessing brain aneurysms in the clinical workflow.

ETHNOPHARMACOLOGICAL RELEVANCE:Natural products represent a unique medical approach to treating disease and have been used in clinical practice for thousands of years in cardiovascular disease (CVDs). In recent years, natural products have received increasing attention for their high efficiency, safety, and low toxicity, and their targeted regulation of mitochondria offers promising strategies for the treatment of CVDs. However, the potential mechanisms by which natural products target mitochondria for cardiovascular treatment have not been fully elucidated. AIM OF THE STUDY:Literature from the past decade is reviewed to emphasize the therapeutic efficacy and potential mechanisms of natural products targeting mitochondria in the treatment of CVDs. MATERIALS AND METHODS:In the NCBI PubMed database, relevant literature was searched using 'natural products', 'mitochondria' and 'cardiovascular disease' as search terms, and review papers were excluded. The remaining articles were screened for relevance. Priority was given to articles using rat models, in vivo, ex vivo or in vitro assays. The resulting articles were categorized into natural product categories, including saponins, alkaloids, plant extracts and preparations. This article reviews the research progress on mitochondria as potential therapeutic targets for CVDs and summarizes the application of mitochondria-targeted natural products in the treatment of CVDs. RESULTS:Mitochondrial damage may be attributed to impairment of biogenesis (mitochondrial number and mitochondrial DNA damage), dynamics disruption (mitophagy inhibition and overpromotion, fusion and fission),disruption of optimal function including Adenosine triphosphate generation, Reactive oxygen species (ROS) production, fatty acid β oxidation, mitochondrial membrane permeability, calcium homeostasis imbalance, and membrane potential depolarization. Mitochondrial dysfunction or damage leads to cardiomyocyte dysfunction, ion disorders, cell death, and ultimately CVDs, such as myocardial infarction, heart failure, ischemia reperfusion, and diabetic heart disease. Natural products, which include flavonoids, saponins, phenolic acids, alkaloids, polysaccharides, extracts, and formulations, are seen to have significant clinical efficacy in the treatment of CVDs. Mechanistically, natural products regulate mitophagy, mitochondrial fusion and fission, while improving mitochondrial respiratory function, reducing ROS production, and inhibiting mitochondria-dependent apoptosis in cardiomyocytes, thereby protecting myocardial cells and heart function. CONCLUSIONS:This paper reviews the potential and mechanism of natural products to regulate mitochondria for the treatment of CVDs, creating more opportunities for understanding their therapeutic targets and derivatization of lead compounds, and providing a scientific basis for advancing CVDs drug research.

Polydimethylsiloxane (PDMS) has been widely used in various fields due to its appealing physical and chemical properties. However, its high hydrophobicity not only yields poor adhesion to substrates but also facilitates undesired adsorption of substances such as proteins, biofoulers, etc., which limits the performance and lifetime of PDMS. Moreover, traditional surface modification techniques are often not efficient on PDMS surfaces because of the surface reconstruction. Although new methods involving chemical modification have been developed, most of them require complicated procedures and equipment. To overcome this challenge, we incorporate metal-ligand coordination, a non-covalent interaction bearing polar functionality, into PDMS, which exposes the hydrophilicity progressively upon dynamic bond breakage and reformation. We demonstrate that the hydrophilicity of coordinated PDMS can be tailored by the choice of network structure, counter anions, and metal cations, which yield distinct network dynamics. The wetting mechanism is discussed in the context of chain reconfiguration and surface reconstruction. We also show that a properly designed metal-ligand coordinated PDMS has potential as a superior marine fouling release coating by weakening diatom attachment. Through this paper, we introduce a new concept for tuning material hydrophilicity via dynamic polar functionalities, which is applicable to a wide range of polymers.

Aim of the study：We studied the metabolites in the brain tissue of Alzheimer's Disease (AD) transgenic mice to investigate how Jiedu Yizhi Formula (JDYZF) protects against AD and to validate the scientific basis of the prescription using the "Marrow deficiency and toxin damage" theory. Materials and methods: The effect of JDYZF treatment on cognitive dysfunction was evaluated using the Morris water maze test in the APP/PS1 transgenic mouse model. Furthermore, the impact of JDYZF on typical AD pathology was assessed through Hematoxylin-eosin staining. Additionally, the protective effect of JDYZF on AD neurons was studied using Nissl staining. Moreover, potential mechanisms of action were analyzed through LC-MS/MS-based untargeted metabolomics of mouse brain tissue. Results: The administration of JDYZF significantly ameliorated memory deficits and mitigated typical histopathological changes in AD mice. Upon comparison of the differential metabolites between the model control group and the blank control group with those between the JDYZF group and the model control group, 17 endogenous metabolites, including 1-methyluric acid, were found to be significantly different. These differential metabolites were primarily involved in the pathways of caffeine metabolism and glycerophospholipid metabolism. Conclusion: In this study, we have effectively illustrated the neuroprotective effect of JDYZF on AD through experimentation with the APP/PS1 transgenic mouse model. The findings indicate that the utilization of JDYZF can ameliorate the metabolic disruptions in brain tissue and serve as a viable therapeutic intervention for AD.

The medical and health industry is evolving from traditional single management to modern scientific and systematic management. From the perspective of medical management, medical consumer electronics have developed rapidly. Various medical consumer electronics have been widely used, and the security of medical electronic networks has gradually become the focus of researchers. Traffic intrusion detection is a network security system running at all times, and its importance is self-evident. Traditional intrusion detection mainly relies on expert experience, which leads to the limitations of intrusion detection technology. To address this issue, this work designs a medical consumer electronic traffic intrusion detection network via deep learning and integrated learning. First, this work proposes a classification model (NDR-BiLSTM) based on the combination of the nonlinear dimensionality reduction method and BiLSTM. Secondly, this work proposes a processing model for unbalanced data problems (SMOTE-IAdaboost). This model can promote classification effect of minority data in intrusion detection. SMOTE-IAdaboost uses NDR-BiLSTM intrusion detection model as a weak classifier in ensemble learning. This eventually forms an intrusion detection model that improves the ability of unbalanced data processing. Finally, this work conducts systemic experiments, the data verify the superiority of SMOTE-IAdaboost for medical consumer electronic traffic intrusion detection.

Co-infection with oncogenic retrovirus and herpesvirus significantly facilitates tumor metastasis in human and animals. Co-infection with avian leukosis virus subgroup J (ALV-J) and Marek's disease virus (MDV), which are typical oncogenic retrovirus and herpesvirus, respectively, leads to enhanced oncogenicity and accelerated tumor formation, resulting in increased mortality of affected chickens. Previously, we found that ALV-J and MDV cooperatively promoted tumor metastasis. However, the molecular mechanism remains elusive. Here, we found that doublecortin-like kinase 1 (DCLK1) mediated cooperative acceleration of epithelial-mesenchymal transition (EMT) by ALV-J and MDV promoted tumor metastasis. Mechanistically, DCLK1 induced EMT via activating Wnt/β-catenin pathway by interacting with β-catenin, thereby cooperatively promoting tumor metastasis. Initially, we screened and found that DCLK1 was a potential mediator for the cooperative activation of EMT by ALV-J and MDV, and enhanced cell proliferation, migration, and invasion. Subsequently, we revealed that DCLK1 physically interacted with β-catenin to promote the formation of the β-catenin-TCF4 complex, inducing transcription of the Wnt target gene, c-Myc, promoting EMT by increasing the expression of N-cadherin, Vimentin, and Snail, and decreasing the expression of E-cadherin. Taken together, we discovered that jointly activated DCLK1 by ALV-J and MDV accelerated cell proliferation, migration and invasion, and ultimately activated EMT, paving the way for tumor metastasis. This study elucidated the molecular mechanism underlying cooperative metastasis induced by co-infection with retrovirus and herpesvirus. IMPORTANCE:Tumor metastasis, a complex phenomenon in which tumor cells spread to new organs, is one of the greatest challenges in cancer research and is the leading cause of cancer-induced death. Numerous studies have shown that oncoviruses and their encoded proteins significantly affect metastasis, especially the EMT process. ALV-J and MDV are classic tumorigenic retrovirus and herpesvirus, respectively. We found that ALV-J and MDV synergistically promoted EMT. Further, we identified the tumor stem cell marker DCLK1 in ALV-J and MDV co-infected cells. DCLK1 directly interacted with β-catenin, promoting the formation of the β-catenin-TCF4 complex. This interaction activated the Wnt/β-catenin pathway, thereby inducing EMT and paving the way for synergistic tumor metastasis. Exploring the molecular mechanisms by which ALV-J and MDV cooperate during EMT will contribute to our understanding of tumor progression and metastasis. This study provides new insights into the cooperative induced tumor metastasis by retroviruses and herpesviruses.

The construction of mutual conversion mechanisms for environmental interest products (EIP) is crucial to enhance connectivity and promote the synergistic development among multiple market systems including power, carbon emissions trading (CET) and tradable green certificate (TGC). In this paper, static and dynamic TGC‑carbon allowance (CA)-Chinese certified emission reduction (CCER) conversion mechanisms are designed from the perspective of physical and economic values. Based on the multi-agent dynamic game model considering Weber-Fechner's law, the transaction behavior for various generation companies (GENCOs) and power purchasers in power, CET and TGC markets under different conversion mechanisms are analyzed. The results demonstrate that TGC-CA-CCER conversion mechanisms further expand the transaction space for low-carbon GENCOs, and effectively reflect the differentiated value of each EIP in diverse scenarios and time periods. Compared with other conversion mechanisms, the dynamic TGC-CA-CCER conversion mechanism based on physical values has better economic as well as environmental benefits, and enhances the competitiveness and liquidity of markets, which is the optimal solution to realize the mutual conversion of EIP. These insights can make up for the research gap of mutual conversion mechanisms on different EIP and provide mechanism options for realizing favorable interaction among power, CET and TGC markets.

Currently, designing materials and structures is the main means of improving their energy-absorption properties; however, optimization methods based on structural design can only be applied to specific structures. In this study, two optimization methods of energy-absorbing structures (EASs) are proposed from the material system and manufacturing method for fabricating gradient stiffness and hierarchical cellular structures, respectively. The gradient stiffness structure was prepared using different ratios of thermoplastic polyurethane (TPU)/polyvinylidene fluoride (PVDF) filaments in different locations in the EAS. The gradient stiffness structure exhibited energy-absorption behavior corresponding to the strength of the printed material; this behavior decreased in the order of material strength from low to high, thus achieving controlled yield deformation behavior. Hierarchical honeycomb structures were prepared by combining three-dimensional (3D) printing with supercritical CO2 foaming technology, which facilitated the simultaneous formation of both centimeter and micron-scale cellular structures. When the PVDF content was 30%, the average cellular size of the microcellular structure was only 3 μm, and the prepared hierarchical honeycomb structures exhibited higher energy-absorption efficiencies compared with the general honeycomb structure. The energy absorption per unit mass values in three different compression directions of the hierarchical honeycomb structures were 152.75%, 67.33%, and 56.91% higher, respectively, than that of the TPU honeycomb without foaming. Therefore, the gradient stiffness and hierarchical honeycomb structures prepared from TPU/PVDF blends have various applications in energy absorption, personal protection, and transportation.

In this investigation, we successfully synthesized a series of Swedenborgite-type Y1-xPrxBaCo3ZnO7+s 1-x Pr x BaCo 3 ZnO 7+s (x = 0.0, 0.1, 0.2, 0.3, 0.4, and 0.5, abbreviated as YPxBCZ) x BCZ) oxides by a solid-state reaction method. The results show that YPxBCZ x BCZ (x = 0.0, 0.1, 0.2, and 0.3) are single-phase structures, but YP0.4BCZ 0.4 BCZ and YP0.5BCZ 0.5 BCZ show interesting self- assembled composite phases. After long-term phase stability testing, YP0.3BCZ 0.3 BCZ showed the best thermal stability. All samples show good chemical and thermal compatibility with La 0.9 Sr 0.1 Ga 0.8 Mg 0.2 O 3-s electrolyte. The thermal expansion coefficients in the temperature range from 30 degrees C to 1000 degrees C are equal to 9.8-13.1 x 10-6 K-1 , close to that of the LSGM electrolyte. It is also found that Pr doping improves high temperature conductivity of YPxBCZ. x BCZ. The conductivity of YP0.3BCZ, 0.3 BCZ, YP0.4BCZ, 0.4 BCZ, and YP0.5BCZ 0.5 BCZ reach 15.1, 18.5, and 22.5 S cm-1 at 800 degrees C. In addition, the area specific resistance (ASR) value decreases as the Pr content increases (0.038, 0.033, and 0.027 Omega cm2 2 at 800 degrees C for YP0.3BCZ, 0.3 BCZ, YP0.4BCZ, 0.4 BCZ, and YP0.5BCZ), 0.5 BCZ), improving the catalytic activity of the material. Another interesting finding was that the ASR of samples subjected to high temperature thermal decomposition was not adversely affected by the presence of decomposition products. The maximum power densities of YP0.3BCZ, 0.3 BCZ, YP0.4BCZ, 0.4 BCZ, and YP0.5BCZ 0.5 BCZ in the single cells at 800 degrees C were 845, 930, and 1044 mW cm2, 2 , respectively. These results indicate that YP0.3BCZ, 0.3 BCZ, YP0.4BCZ, 0.4 BCZ, and YP0.5BCZ 0.5 BCZ are promising cathode materials for intermediate- temperature solid oxide fuel cell.

Cu is doped to La(4)Ni(3-x)CuxO(10 +/-delta) to improve its electrochemical performance as a potential intermediate-temperature solid oxide fuel cell (IT-SOFC) cathode material. A new higher-order Ruddlesden-Popper (R-P) phase composition La(4)Ni(3-x)CuxO(10 +/-delta), (L4N3-xCx, 0.0 < x < 0.7) is synthesized using an EDTA-citrate process. The L4N3-xCx cathode has a good chemical compatibility with the La0.9Sr0.1Ga0.8Mg0.2O3-delta (LSGM) electrolyte. A thermodynamic stability test shows that L4N3-xCx is stable after 72 h exposure to 600, 700, and 800 degrees C in air. The L4N3-xCx cathode shows chemical stability against CO2, and a stable structure over 12 h in CO2 has been demonstrated. The thermal expansion coefficients (TECs) have been determined to be in the range of 14.1-14.6 x 10(-6) K-1, close to that of the LSGM electrolyte. The Cu content (x) significantly affects the electrical conductivity and sinter density of L(4)N(3-x)Cx. La4Ni2.7Cu0.3O10 (L4N2.7C0.3) displays the highest electrical conductivity value of which reaches about 383 to 319 S cm(-1) at 600-800 degrees C. In addition, Cu doping improves the electrochemical performance of L4N3-xCx. The area specific resistance (ASR) of the La(4)Ni(2.5)Cu(0.5)O10 (L4N2.5C0.5) cathode was found to be 0.045 Omega cm(2) at 800 degrees C, which is significantly better than that of L4N3. The peak power density of a single cell using the L(4)N(2.5)C(0.5 )cathode is 526 mW cm(-2) at 800 C-degrees, and a 200 h long-term test demonstrates good stability. These results indicate that La4Ni3-xCuxO10 +/-delta cathode is a promising cathode material for IT-SOFCs.

Due to the stricter emission reduction and renewable energy consumption goals in China, the carbon emissions trading (CET) market and tradable green certificate (TGC) market, as key means to achieve these goals, urgently need to adjust the current operating mode timely and maximize market effectiveness by introducing adaptive incentive mechanisms. Therefore, taking the power industry as an example, an incentive-oriented power-CET-TGC integrated market simulation framework based on multi-agent deep reinforcement learning is constructed. The impact of consignment auction mechanism, traditional auction mechanism, and voluntary TGC trading mechanism on the transaction situation of each market is prospectively analyzed. The results demonstrate that with the introduction of various incentive mechanisms, the transaction scale and prices of CET and TGC markets increase, and the effectiveness of carbon reduction and renewable energy consumption is significant. Among them, auction mechanisms are valid way to promote the explicit cost of carbon emissions, and the voluntary TGC trading mechanism is an important means to enhance the clean value of green energy. In addition, it is recommended to adopt consignment auction mechanism under the short-term goal “carbon peak” of pursuing economic benefits and stable emission reduction, while traditional auction mechanisms are recommended under the long-term goal of “carbon neutrality” of urgently requiring large-scale emission reduction. Moreover, the voluntary TGC trading mechanism can achieve synergy and connection between the TGC market and the green electricity market to a certain extent. These insights can provide mechanism reference for the sustainable development and construction of CET and TGC markets.

Background and Objective: Coronary artery segmentation is a pivotal field that has received increasing attention in recent years. However, this task remains challenging because of the inhomogeneous distributions of the contrast agent and dim light, resulting in noise, vascular breakages and small vessel losses in the obtained segmentation results. Methods: To acquire better automatic blood vessel segmentation results for coronary angiography images, a UNet-based segmentation network (SARC-UNet) is constructed for coronary artery segmentation; this approach is based on residual convolution and spatial attention. First, we use the low-light image enhancement (LIME) approach to increase the contrast and clarity levels of coronary angiography images. Then, we design two residual convolution fusion modules (RCFM1 and RCFM2) that can successfully fuse the local and global information of coronary images while also capturing the characteristics of finer-grained blood vessels, hence preventing the loss of tiny blood vessels in the segmentation findings. Finally, using a cascaded waterfall structure, we create a new location-enhanced spatial attention (LESA) mechanism that can efficiently improve the long-distance dependencies between coronary vascular pixel features, eradicating vascular ruptures and noise in the segmentation results. Results: This article subjectively and objectively evaluates the experimental results. This method has performed well on five general indicators. Furthermore, it outperforms the connectivity indicators proposed in this article. This method can effectively segment blood vessels and obtain higher accuracy results. Conclusions: Numerous experiments have shown that the suggested method outperforms the state-of-the-art approaches, particularly in terms of vessel connectivity and small blood vessel segmentation.

Elevated atmospheric carbon dioxide (CO2) concentration generally stimulates nitrous oxide (N2O) emissions from upland soils, leading to a promoted feedback on climate change. However, the underlying mechanisms on how elevated CO2 (eCO2) stimulates N2O emissions from nitrogen (N)-fertilized upland soils remain poorly known. Here, we investigated the effects of eCO2 on soil N2O production pathways and associated gross N transformation rates, as well as on nitrifying and denitrifying microbes. Based on a 13 years of free-air CO2 enrichment (FACE) platform, we found that N2O emissions were significantly increased by 46.7% under eCO2 in a typical summer-maize field. The 15N tracing experiment showed that autotrophic nitrification rate was significantly increased by 11.6% under eCO2, coincided with the significantly higher abundance and shift composition of ammonia-oxidizing bacteria (AOB) under eCO2. Also, eCO2 enhanced gross ammonium (NH4+) immobilization rate but reduced gross nitrate (NO3−) immobilization rate. Autotrophic nitrification accounted for approximately 78% of N2O emissions, followed by heterotrophic nitrification (about 19%) and denitrification (about 3%). It was found that eCO2 increased carbon (C) deposition in soil, which could affect the availability of soil labile organic C and N and alter the composition and activity of nitrifiers. These changes promoted the N2O production derived from autotrophic nitrification, resulting in higher N2O emissions under eCO2. We could deduce that nitrifier denitrification contributed to the increased N2O emissions greatly under eCO2, derived by strongly stimulated ammonia oxidation and microbial respiration (i.e. higher soil CO2 emissions) caused suboxic conditions (i.e. lower soil oxygen (O2) concentration), along with higher abundance ratios of (nirK+nirS)/nosZ. Our results suggest that controlling autotrophic nitrification appropriately is crucial for mitigating N2O emissions from upland soils under rising atmospheric CO2 concentration.

With China's grid-connected large-scale variable renewable energy, coal-fired power system is progressively changing from being the main supplier of electric energy to providing flexibility services. The coal-fired power system must increase operating efficiency during this transition process by considering the technical characteristics of various coal-fired power units. Additionally, the trading strategies of coal-fired power units in the electricity-carbon market are impacted differently depending on the extent of VRE penetration. This paper innovatively considers these two factors and proposes a two-stage bi-level clearing model in electricity-carbon joint market to coordinate the synergistic development of variable renewable energy and coal-fired power. The upper level of the model aims to maximize the total profits of the coal-fired power system and variable renewable energy units, while the lower level of the model minimizes the total purchasing costs. Coal-fired power units and variable renewable energy units compete to sell electric energy, with the latter buying peaking regulation from the former. The research results indicate that the proposed model can significantly reduce 66.79 % carbon emissions, increase 33.96 % non-fossil variable renewable energy integration and optimize the generation structure of coal-fired power system.

Ensuring reliability is vital for the efficient operation, maintenance, and cost-effectiveness of LCL-type photovoltaic (PV) inverters. The resonant currents triggered by the filter may transmit and couple between the grid and the PV system, thereby amplifying the electrothermal stresses on capacitors and resulting in notable inaccuracies in lifetime predictions. This article thoroughly analyzes capacitor lifetime to quantify estimation errors arising from resonant currents. Differing from conventional analysis, the electrical stresses with resonances are obtained by Fourier series and impedance characteristics of the LCL filter. This method ensures that the model analysis remains independent of simulations, making it easy to modify and optimize. Furthermore, the capacitor's electrical stresses are validated experimentally. The findings indicate that resonant current significantly reduces capacitor lifetime. The damping method's failure leads to a 24% reduction in the capacitor bank's lifetime, with a notable 60% decrease observed particularly when utilizing a 15 mu F individual capacitor. Ultimately, the comparison of average lifetime costs among various capacitor banks is conducted based on the proposed analytical model and reliability estimation method, aiming to optimize economic performance from a reliability perspective. The results of the lifetime investigation provide further insights into the LCL-type PV system design.

A series of cathode materials of Pr 2-x Sr x NiO 4 (x = 0, 0.3, 0.5, 0.7, 1, 1.5) are synthesized by the EDTA-citric acid route. The results show that the Pr 1.7 Sr 0.3 NiO 4 , Pr 1.5 Sr 0.5 NiO 4 , Pr 1.3 Sr 0.7 NiO 4 and PrSrNiO 4 exhibit excellent structural stability and carbon dioxide resistance, and also exhibit good chemical compatibility and thermal matching with the SDC electrolyte. It is also found that the Sr doping is beneficial in improving the high temperature conductivity of Pr 2-x Sr x NiO 4 . At 800 degrees C, the electrical conductivity of Pr 1.5 Sr 0.5 NiO 4 and Pr 1.3 Sr 0.7 NiO 4 reaches 185 S cm - 1 and 317 S cm -1 , respectively. In addition, the area-specific resistance (ASR) value increases significantly with Sr doping, which reduces the catalytic activity of the material. Acceptable ASR values are obtained for Pr 1.5 Sr 0.5 NiO 4 and Pr 1.3 Sr 0.7 NiO 4 , with ASR values of 0.079 Omega cm 2 and 0.082 Omega cm 2 at 800 degrees C, respectively. Additionally, the most interesting result is the ASR value obtained after high-temperature thermal decomposition of Pr 2 NiO 4 , where Pr 2 NiO 4 * (decomposed) has the lowest ASR value of only 0.027 Omega cm 2 at 800 degrees C, showing the best catalytic activity. The maximum power densities of Pr 2-x Sr x NiO 4 (x = 0.5 and 0.7) and Pr 2 NiO 4 * are found to be 515, 430, and 548 mW cm -2 at 800 degrees C, respectively. These results show that when the Sr doping amount is less than 1.5, the stability of the Pr 2-x Sr x NiO 4 cathode material can be effectively improved, but its catalytic performance is partially sacrificed.

Multi-energy systems with carbon capture system (CCS) and power to gas (P2G) can reduce carbon emissions while increasing the consumption of renewable energy. This paper proposed a long-term equilibrium including electricity, gas and carbon markets to study the price effect of the system and its impact on the carbon-gas- electricity sector. The simulation results indicate that the main impact of the system on the electricity sector is to reduce energy curtailment and provide flexible resource for the electric system. P2G used an excess of 22.21 TWh of renewable energy, while CCS used 2.65 TWh of electricity to operate the capture system. The multi-energy system will reduce the market clearing price in the gas market (the annual average gas price decreased from 276.90 to 276.30 yuan/MWh). However, the partial transfer of flexibility to the electricity sector may increase cost in the gas industry, which in turn will be transferred back to the electricity sector again. In addition, through the operation of multi-energy system, carbon elements will circulate in the three sectors. CCS will become a carbon price-maker when electricity scarcity and carbon quota tightening, and increase carbon prices, which will increase the utilization hours of CCS and P2G and their profitability.

Human articular cartilage, a nonlinear, viscoelastic solid-liquid biphasic tissue, has different mechanical properties and undertakes different functions in different layer. The compression deformation and fatigue damage mechanism of each layer of cartilage is also different when in injury. Compression properties of cartilage can predict cartilage integrity and the likelihood of osteoarthritis. Therefore, the confined and unconfined compression of cartilage is taken to systematically study the dynamic mechanical properties of each layer and reveal the relationship between the dynamic mechanical properties of each cartilage layer and the function of the corresponding cartilage layer. Under confined and unconfined compression conditions, the larger the cyclic loading rate, the greater the deformation rate of each layer. In addition, under the same cyclic loading rate, the superficial layer had the highest deformation rate, followed by the middle layer and the deep layer, which indicates that the deep layer mainly assumes the compression load. Furthermore, under the same loading displacement, the loading stress of cartilage and the deformation rate of each layer in confined compression were greater than those in unconfined compression. Simultaneously, with the increase in the number of loading cycles, the deformation rate in different layers increased first and then stabilized.

LCL filters are critical in PV inverter systems, and its resonant currents brings more electrothermal stresses on filter capacitors. This paper investigates the influence of resonant currents on damage of capacitors. Different from conventional methods, this paper predicts the lifetime of individual capacitors by comparing the dynamic hot spot temperatures with and without the damping method and using annual mission profiles. Then, based on Monte Carlo simulations and Weibull analysis, reliability curves are connected from the component level of the individual capacitor to the system level of the capacitor bank with help from the reliability block diagrams. The results show that without damping method, the resonant currents have a significant impact on capacitor lifetime. In the case that electrothermal stress concentrates on an individual capacitor, its lifetime is shorter than that of a capacitor bank. Furthermore, the average lifetime costs of different capacitor bank configurations are compared to provide a reference for capacitor selection.