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The pyrolysis characteristics of four different types of conditioned sludge were ascertained, and PAM, CaO, K2FeO4, and K2FeO4-CaO-PAM (KCP) conditioners were employed as sludge dewatering conditioners. The sludge pyrolysis reaction's activation energy (E) dropped with the addition of four conditioners. CaO, PAM, KCP, and K2FeO4 were the sequences of E needed for the pyrolysis of four different types of conditioned sludge. The addition of K2FeO4, CaO, and KCP resulted in an increase in the yields of H2 and CO. Except for the K2FeO4 conditioning sludge carbon, the pyrolytic carbon of the other three groups of samples showed an increase in S contents, while the pyrolytic carbon of the four groups of samples treated with conditioners clearly showed lower C and N contents compared to the raw sludge carbon. Protein-N made up the majority of N in sludge pyrolytic carbon. After adding conditioner, the level of organic sulfur decreased. Organic sulfur could then be broken down by K2FeO4 and CaO. The four conditioners efficiently mitigated the ecological and environmental risks posed by heavy metals. Alkynes were the most abundant result in pyrolytic volatiles of sludge pyrolysis; the other products included acids, alcohols, lipids, furans, ketones, phenols, hydrocarbons, N-components, and so on. All samples' acids, alcohols, and ketones from pyrolysis were decreased once the conditioner was added. The acid reduction rate reached 66.7 %, and the alkynes clearly increased during the KCP conditioned sludge's pyrolysis. The sulfur level of the bio-oil was decreased by all four conditioners. Everything mentioned above indicated that the KCP aided in the subsequent pyrolysis of the sludge, leading to the production of an advantageous pyrolysis bio-oil.
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Neoplasias da Mama , Recidiva Local de Neoplasia , Humanos , Feminino , Estudos Retrospectivos , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/patologia , Pessoa de Meia-Idade , Carcinoma Intraductal não Infiltrante/patologia , Carcinoma Intraductal não Infiltrante/tratamento farmacológico , China , Adulto , Antineoplásicos Hormonais/uso terapêutico , IdosoRESUMO
Wearable thermoelectric generators have great potential to provide power for smart electronic wearable devices and miniature sensors by harnessing the temperature difference between the human body and the environment. However, the Thomson effect, the Joule effect, and heat conduction can cause a decrease in the temperature difference across the thermoelectric generator during operation. In this paper, phase change materials (PCMs) were employed as the heat sink for the thermoelectric generator, and the COMSOL software 6.1 was utilized to simulate and optimize the power generation processes within the heat sink. The results indicated that with a PCM height of 40 mm, phase transition temperature of 293 K, latent heat of 200 kJ/kg, phase transition temperature interval of 5 K, thermal conductivity of 50 W/(m·K), isobaric heat capacity of 2000 J/(Kg·K), density of 1000 kg/m3, and convective heat transfer coefficient of 10 W/(m·K), the device can maintain a temperature difference of 18-10 K for 1930 s when the thermoelectric leg height is 1.6 mm, and 3760 s when the thermoelectric leg height is 2.7 mm. These results demonstrate the correlation between the device's output performance and the dimensions and performance parameters of the PCM heat sink, thereby validating the feasibility of employing the PCM heat sink and the necessity for systematic investigations.
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Flexible perovskite solar cells (pero-SCs) have the potential to overturn the application scenario of silicon photovoltaic technology. However, their mechanical instability severely impedes their practical applicability, and the corresponding intrinsic degradation mechanism remains unclear. In this study, the degradation behavior of flexible pero-SCs is systematically analyzed under mechanical stress and it is observed that the structural failure first occurs in the polycrystal perovskite film, then extend to interfaces. To suppress the structural failure, pentaerythritol triacrylate, a crosslinked molecule with three stereoscopic crosslink sites, is employed to establish a 3D polymer network in both the interface and bulk perovskite. This network reduced the Young's modulus of the perovskite and simultaneously enhanced the interfacial toughness. As a result, the formation of cracks and delamination, which occur under a high mechanical stress, is significantly suppressed in the flexible pero-SC, which consequently retained 92% of its initial power conversion efficiency (PCE) after 20 000 bending cycles. Notably, the flexible device also shows a record PCE of 24.9% (certified 24.48%).
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Brain-computer interfaces (BCIs) have been widely focused and extensively studied in recent years for their huge prospect of medical rehabilitation and commercial applications. Transfer learning exploits the information in the source domain and applies in another different but related domain (target domain), and is therefore introduced into the BCIs to figure out the inter-subject variances of electroencephalography (EEG) signals. In this article, a novel transfer learning method is proposed to preserve the Riemannian locality of data structure in both the source and target domains and simultaneously realize the joint distribution adaptation of both domains to enhance the effectiveness of transfer learning. Specifically, a Riemannian graph is first defined and constructed based on the Riemannian distance to represent the Riemannian geometry information. To simultaneously align the marginal and conditional distribution of source and target domains and preserve the Riemannian locality of data structure in both domains, the Riemannian graph is embedded in the joint distribution adaptation (JDA) framework and forms the proposed Riemannian locality preserving-based transfer learning (RLPTL). To validate the effect of the proposed method, it is compared with several existing methods on two open motor imagery datasets, and both multi-source domains (MSD) and single-source domains (SSD) experiments are considered. Experimental results show that the proposed method achieves the highest accuracies in MSD and SSD experiments on three datasets and outperforms eight baseline methods, which demonstrates that the proposed method creates a feasible and efficient way to realize transfer learning.
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Algoritmos , Interfaces Cérebro-Computador , Eletroencefalografia , Aprendizado de Máquina , Processamento de Sinais Assistido por Computador , Humanos , Eletroencefalografia/métodos , Encéfalo/fisiologiaRESUMO
As an essential cognitive function, attention has been widely studied and various indices based on EEG have been proposed for its convenience and easy availability for real-time attention monitoring. Although existing indices based on spectral power of empirical frequency bands are able to describe the attentional state in some way, the reliability still needs to be improved. This paper proposed a subject-specific attention index based on the weighted spectral power. Unlike traditional indices, the ranges of frequency bands are not empirical but obtained from subject-specific change patterns of spectral power of electroencephalograph (EEG) to overcome the great inter-subject variance. In addition, the contribution of each frequency component in the frequency band is considered different. Specifically, the ratio of power spectral density (PSD) function in attentional and inattentional state is utilized to calculate the weight to enhance the effectiveness of the proposed index. The proposed subject-specific attention index based on the weighted spectral power is evaluated on two open datasets including EEG data of a total of 44 subjects. The results of the proposed index are compared with 3 traditional attention indices using various statistical analysis methods including significance tests and distribution variance measurements. According to the experimental results, the proposed index can describe the attentional state more accurately. The proposed index respectively achieves accuracies of 86.21% and 70.00% at the 1% significance level in both the t-test and Wilcoxon rank-sum test for two datasets, which obtains improvements of 41.38% and 20.00% compared to the best result of the traditional indices. These results indicate that the proposed index provides an efficient way to measure attentional state.
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Algoritmos , Atenção , Eletroencefalografia , Humanos , Atenção/fisiologia , Eletroencefalografia/métodos , Reprodutibilidade dos Testes , Masculino , Feminino , Adulto , Adulto JovemRESUMO
GeTe and Ge0.99-xIn0.01SnxTe0.94Se0.06 (x = 0, 0.01, 0.03, and 0.06) samples were prepared by vacuum synthesis combined with spark plasma sintering (SPS). The thermoelectric properties of GeTe were coordinated by multiple doping of Sn, In, and Se. In this work, a maximum zT(zT = S2σT/κ) of 0.9 and a power factor (PF = S2σ) of 3.87 µWmm-1 K-2 were obtained in a sample of Ge0.99In0.01Te0.94Se0.06 at 723K. The XRD results at room temperature show that all samples are rhombohedral phase structures. There is a peak (~27°) of the Ge element in GeTe and the sample (x = 0), but it disappears after Sn doping, indicating that Sn doping can promote the dissolution of Ge. The scattering mechanism of the doped samples was calculated by the conductivity ratio method. The results show that phonon scattering Is dominant in all samples, and alloy scattering is enhanced with the increase in the Sn doping amount. In doping can introduce resonance energy levels and increase the Seebeck coefficient, and Se doping can introduce point defects to suppress phonon transmission and reduce lattice thermal conductivity. Therefore, the thermoelectric properties of samples with x = 0 improved. Although Sn doping will promote the dissolution of Ge precipitation, the phase transition of the samples near 580 K deteriorates the thermoelectric properties. The thermoelectric properties of Sn-doped samples improved only at room temperature to ~580 K compared with pure GeTe. The synergistic effect of multi-element doping is a comprehensive reflection of the interaction between elements rather than the sum of all the effects of single-element doping.
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Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC) with a high mortality rate, and few effective therapeutic strategies are available. CCL5/CCR5 is an appealing immunotherapeutic target for TNBC. However, its signaling mechanism is poorly understood and its direct antagonists have not been reported. Here, we developed a high-throughput screening (HTS) assay for discovering its antagonists. Verteporfin was identified as a more selective and potent antagonist than the known CCR5 antagonist maraviroc. Without photodynamic therapy, verteporfin demonstrated significant inhibition on TNBC tumor growth through immune regulation, remarkable suppression of lung metastasis by cell-intrinsic mechanism, and a significant extension of overall survival in vivo. Mechanistically, CCR5 was found to be essential for expression of the key hippo effector YAP1. It promoted YAP1 transcription via HIF-1α and exerted further control over the migration of CD8+ T, NK, and MDSC immune cells through chemokines CXCL16 and CXCL8 which were identified from RNA-seq. Moreover, the CCR5-YAP1 axis played a vital role in promoting metastasis by modulating ß-catenin and core epithelial-mesenchymal transition transcription factors ZEB1 and ZEB2. It is noteworthy that the regulatory relationship between CCR5 and YAP1 was observed across various BC subtypes, TNBC patients, and showed potential relevance in fifteen additional cancer types. Overall, this study introduced an easy-to-use HTS assay that streamlines the discovery of CCL5/CCR5 axis antagonists. Verteporfin was identified as a specific molecular probe of this axis with great potentials as a therapeutic agent for treating sixteen malignant diseases characterized by heightened CCR5 and YAP1 levels.
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Neoplasias de Mama Triplo Negativas , Humanos , Neoplasias de Mama Triplo Negativas/patologia , Verteporfina/farmacologia , Quimiocina CCL5 , Transdução de Sinais , Maraviroc/farmacologia , Linhagem Celular Tumoral , Movimento Celular , Receptores CCR5/metabolismoRESUMO
BACKGROUND: The widespread use of vaccines against the novel coronavirus disease (COVID-19) has become one of the most effective means to establish a population immune barrier. Patients with cancer are vulnerable to COVID-19 infection, adverse events, and high mortality, and should be the focus of epidemic prevention and treatment. However, real-world data on the safety of vaccines for patients with breast cancer are still scarce. OBJECTIVE: This study aims to compare the safety of COVID-19 vaccines between patients vaccinated before or after being diagnosed with breast cancer. METHODS: Patients with breast cancer who sought medical advice from October 2021 to December 2021 were screened. Those who received COVID-19 vaccines were enrolled in this study to analyze the safety of the vaccines. The primary outcome was patient-reported adverse events (AEs). All events after vaccine injection were retrospectively documented from the patients. RESULTS: A total of 15,455 patients with breast cancer from 41 hospitals in 20 provinces in China were screened, and 5766 patients who received COVID-19 vaccines were enrolled. Of those enrolled, 45.1% (n=2599) of patients received vaccines before breast cancer diagnosis, 41.3% (n=2379) were vaccinated after diagnosis, and 13.6% (n=784) did not known the accurate date of vaccination or cancer diagnosis. Among the patients vaccinated after diagnosis, 85.4% (n=2032) were vaccinated 1 year after cancer diagnosis and 95.4% (n=2270) were vaccinated during early-stage cancer. Of all 5766 vaccinated patients, 93.9% (n=5415) received an inactivated vaccine, 3.7% (n=213) received a recombinant subunit vaccine, and 2.4% (n=138) received other vaccines, including adenovirus and mRNA vaccines. In the first injection of vaccines, 24.4% (n=10, 95% CI 11.2-37.5) of patients who received an adenovirus vaccine reported AEs, compared to only 12.5% (n=677, 95% CI 11.6-13.4) of those who received an inactivated vaccine. Patients with metastatic breast cancer reported the highest incidence of AEs (n=18, 16.5%, 95% CI 9.5-23.5). Following the second injection, patients who received an inactivated vaccine (n=464, 8.7%, 95% CI 8.0-9.5) and those who received a recombinant vaccine (n=25, 8.7%, 95% CI 5.5-12.0) reported the same incidence of AEs. No significant differences in patient-reported AEs were found between the healthy population and patients with breast cancer (16.4% vs 16.9%, respectively); the most common AEs were local pain (11.1% vs 9.1%, respectively), fatigue (5.5% vs 6.3%, respectively), and muscle soreness (2.3% vs 3.6%, respectively). The type of vaccine and time window of vaccination had little impact on patient-reported AEs. CONCLUSIONS: Compared with patients vaccinated before breast cancer diagnosis, there were no significant differences in patient-reported AEs in the patients vaccinated after diagnosis. Thus, it is safe for patients with breast cancer, especially for those in the early stage, to receive COVID-19 vaccines. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2200055509; https://tinyurl.com/33zzj882.
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Neoplasias da Mama , COVID-19 , Humanos , Feminino , Neoplasias da Mama/epidemiologia , Vacinas contra COVID-19/efeitos adversos , Estudos Transversais , Estudos Retrospectivos , COVID-19/epidemiologia , COVID-19/prevenção & controle , Vacinação/efeitos adversos , China/epidemiologia , Vacinas de Produtos InativadosRESUMO
As a significant aspect of cognition, attention has been extensively studied and numerous measurements have been developed based on brain signal processing. Although existing attentional state classification methods have achieved good accuracy by extracting a variety of handcrafted features, spatial features have not been fully explored. This paper proposes an attentional state classification method based on Riemannian manifold to utilize spatial information. Based on the concept of Riemannian manifold of symmetric positive definite (SPD) matrix, the proposed method exploits the structure of covariance matrix to extract spatial features instead of using spatial filters. Specifically, Riemannian distances from intra-class Riemannian means are extracted as features for their robustness. To fully extend the potential of electroencephalograph (EEG) signal, both amplitude and phase information is utilized. In addition, to solve the variance of frequency bands, a filter bank is employed to process the signal of different frequency bands separately. Finally, features are fed into a support vector machine with a polynomial kernel to obtain classification results. The proposed attentional state classification using amplitude and phase feature extraction method based on filter bank and Riemannian manifold (AP-FBRM) method is evaluated on two open datasets including EEG data of 29 and 26 subjects. According to the experimental results, the optimal set of filter bank and the optimal technique to extract features containing both amplitude and phase information are determined. The proposed method respectively achieves accuracies of 88.06% and 80.00% and outperforms 8 baseline methods, which manifests that the proposed method creates an efficient way to recognize attentional state.
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Interfaces Cérebro-Computador , Humanos , Algoritmos , Eletroencefalografia/métodos , Processamento de Sinais Assistido por Computador , EncéfaloRESUMO
Traditional single-modality brain-computer interface (BCI) systems are limited by their reliance on a single characteristic of brain signals. To address this issue, incorporating multiple features from EEG signals can provide robust information to enhance BCI performance. In this study, we designed and implemented a novel hybrid paradigm that combined illusion-induced visual evoked potential (IVEP) and steady-state visual evoked potential (SSVEP) with the aim of leveraging their features simultaneously to improve system efficiency. The proposed paradigm was validated through two experimental studies, which encompassed feature analysis of IVEP with a static paradigm, and performance evaluation of hybrid paradigm in comparison with the conventional SSVEP paradigm. The characteristic analysis yielded significant differences in response waveforms among different motion illusions. The performance evaluation of the hybrid BCI demonstrates the advantage of integrating illusory stimuli into the SSVEP paradigm. This integration effectively enhanced the spatio-temporal features of EEG signals, resulting in higher classification accuracy and information transfer rate (ITR) within a short time window when compared to traditional SSVEP-BCI in four-command task. Furthermore, the questionnaire results of subjective estimation revealed that proposed hybrid BCI offers less eye fatigue, and potentially higher levels of concentration, physical condition, and mental condition for users. This work first introduced the IVEP signals in hybrid BCI system that could enhance performance efficiently, which is promising to fulfill the requirements for efficiency in practical BCI control systems.
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Interfaces Cérebro-Computador , Ilusões , Humanos , Potenciais Evocados Visuais , Eletroencefalografia/métodos , Estimulação Luminosa , AlgoritmosRESUMO
Conventional thermoelectric generators, predominantly based on the π-type structure, are severely limited in their applications due to the relatively low conversion efficiency. In response to the challenge, in this work, a Bi2Te3-based thermoelectric transistor driven by laser illumination is demonstrated. Under laser illumination, a temperature difference of 46.7 °C is produced between the two ends of the transistor structure. Further, the hole concentrations in each region redistribute and the built-in voltages decrease due to the temperature difference, leading to the formation of the transistor circuit. Additionally, the operation condition of the thermoelectric transistor is presented. The calculation results demonstrate that the maximum output power of such a designed thermoelectric transistor is 0.7093 µW.
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Thermoelectric (TE) materials are an important class of energy materials that can directly convert thermal energy into electrical energy. Screening high-performance thermoelectric materials and improving their TE properties are important goals of TE materials research. Based on the objective relationship among the molar Gibbs free energy (Gm), the chemical potential, the Fermi level, the electronegativity (X) and the TE property of a material, a new method for screening TE materials with high throughput is proposed. This method requires no experiments and no first principle or Ab initio calculation. It only needs to find or calculate the molar Gibbs free energy and electronegativity of the material. Here, by calculating a variety of typical and atypical TE materials, it is found that the molar Gibbs free energy of Bi2Te3 and Sb2Te3 from 298 to 600 K (Gm = -130.20~-248.82 kJ/mol) and the electronegativity of Bi2Te3 and Sb2Te3 and PbTe (X = 1.80~2.21) can be used as criteria to judge the potential of materials to become high-performance TE materials. For good TE compounds, Gm and X are required to meet the corresponding standards at the same time. By taking Gm = -130.20~-248.82 kJ/mol and X = 1.80~2.21 as screening criteria for high performance TE materials, it is found that the Gm and X of all 15 typical TE materials and 9 widely studied TE materials meet the requirement very well, except for the X of Mg2Si, and 64 pure substances are screened as potential TE materials from 102 atypical TE materials. In addition, with reference to their electronegativity, 44 pure substances are selected directly from a thermochemical data book as potential high-performance TE materials. A particular finding is that several carbides, such as Be2C, CaC2, BaC2, SmC2, TaC and NbC, may have certain TE properties. Because the Gm and X of pure substances can be easily found in thermochemical data books and calculated using the X of pure elements, respectively, the Gm and X of materials can be used as good high-throughput screening criteria for predicting TE properties.
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Cu2Se is a promising thermoelectric (TE) material due to its low cost, Earth abundance, and high thermoelectric properties. However, the biggest problem of Cu2Se is its unstable chemical properties. In particular, under the action of an electric field or gradient temperature field, the chemical potential of copper ions inside the material increases. When the external field is strong enough, the chemical potential of copper ions at the negative end of the material reaches the chemical potential of elemental copper. Under these conditions, copper ions must precipitate out, causing Cu2Se to be unstable, and making it unsuitable for use in applications. In this study, we prepared Cu2-xMnxSe (x = 0, 0.02, 0.04 and 0.06) series bulk materials by vacuum melting-annealing and sintered by spark plasma sintering (SPS). We investigated the effects of Mn doping on the composition, microstructure, band structure, scattering mechanism, thermoelectric properties, and stability of Cu2Se. The results show that Mn doping can adjust the carrier concentration, promote the stabilization of the ß-phase structure and improve the electrical properties of Cu2Se. When x = 0.06, the highest power factor (PF) value of Cu1.94Mn0.06Se at 873 K was 1.62 mW m-1 K-2. The results of carrier scattering mechanism analysis based on the conductivity ratio method show that the sample doped with Mn and pure Cu2Se had the characteristics of ionization impurity scattering, and the scattering factor was 3/2. However, the deterioration in thermal conductivity was large, and a superior zT value needs to be obtained. The cyclic test results of high-temperature thermoelectric properties show that Mn doping can hinder Cu+ migration and improve its thermoelectric stability, which preliminarily verifies the feasibility of using the stable zirconia mechanism to improve the thermoelectric stability of Cu2Se.
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Manipulating and integrating the microstructures at different scales is crucial to tune the electrical and thermal properties of a given compound. High-pressure sintering can modify the multiscale microstructures and thus empower the cutting-edge thermoelectric performance. In this work, the high-pressure sintering technique followed by annealing is adopted to prepare Gd-doped p-type (Bi0.2Sb0.8)2(Te0.97Se0.03)3 alloys. First, the high energy of high-pressure sintering promotes the reduction of grain size, thus increasing the content of 2D grain boundaries. Next, high-pressure sintering induces strong interior strain, where 1D dense dislocations are generated near the strain field. More interestingly, the rare-earth element Gd with a high melting temperature is dissolved into the matrix via high-pressure sintering, thus promoting the formation of 0D extrinsic point defects. This concurrently improves the carrier concentration and density-of-state effective mass, resulting in an enhanced power factor. In addition, the integrated 0D point defects, 1D dislocations, and 2D grain boundaries by high-pressure sintering strengthen phonon scattering, thereby achieving a low lattice thermal conductivity of 0.5 Wm-1 K-1 at 348 K. Consequently, a maximum zT value of â¼1.1 at 348 K is achieved in the 0.4 at % Gd-doped (Bi0.2Sb0.8)2(Te0.97Se0.03)3 sample. This work demonstrates that high-pressure sintering enables microstructure modification to enhance the thermoelectric performance of Bi2Te3-based and other bulk materials.
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Omicron variants of SARS-CoV-2 have spread rapidly worldwide; however, most infected patients have mild or no symptoms. This study aimed to understand the host response to Omicron infections by performing metabolomic profiling of plasma. We observed that Omicron infections triggered an inflammatory response and innate immune, and adaptive immunity was suppressed, including reduced T-cell response and immunoglobulin antibody production. Similar to the original SARS-CoV-2 strain circulating in 2019, the host developed an anti-inflammatory response and accelerated energy metabolism in response to Omicron infection. However, differential regulation of macrophage polarization and reduced neutrophil function has been observed in Omicron infections. Interferon-induced antiviral immunity was not as strong in Omicron infections as in the original SARS-CoV-2 infections. The host response to Omicron infections increased antioxidant capacity and liver detoxification more than in the original strain. Hence, these findings suggest that Omicron infections cause weaker inflammatory alterations and immune responses than the original SARS-CoV-2 strain.
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COVID-19 , Humanos , SARS-CoV-2 , Imunidade Adaptativa , AnticorposRESUMO
The stability-related issues arising from the perovskite precursor inks, films, device structures and interdependence remain severely under-explored to date. Herein, we designed an ionic-liquid polymer (poly[Se-MI][BF4 ]), containing functional moieties like carbonyl (C=O), selenium (Se+ ), and tetrafluoroborate (BF4 - ) ions, to stabilize the whole device fabrication process. The C=O and Se+ can coordinate with lead and iodine (I- ) ions to stabilize lead polyhalide colloids and the compositions of the perovskite precursor inks for over two months. The Se+ anchored on grain boundaries and the defects passivated by BF4 - efficiently suppress the dissociation and migration of I- in perovskite films. Benefiting from the synergistic effects of poly[Se-MI][BF4 ], high efficiencies of 25.10 % and 20.85 % were exhibited by a 0.062-cm2 device and 15.39-cm2 module, respectively. The devices retained over 90 % of their initial efficiency under operation for 2200â h.
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OBJECTIVE: Visual evoked potentials (VEPs) have been commonly applied in brain-computer interfaces (BCIs) due to their satisfactory classification performance recently. However, most existing methods with flickering or oscillating stimuli will induce visual fatigue under long-term training, thus restricting the implementation of VEP-based BCIs. To address this issue, a novel paradigm adopting static motion illusion based on illusion-induced visual evoked potential (IVEP) is proposed for BCIs to enhance visual experience and practicality. APPROACH: This study explored the responses to baseline and illusion tasks including the Rotating-Tilted-Lines (RTL) illusion and Rotating-Snakes (RS) illusion. The distinguishable features were examined between different illusions by analyzing the event-related potentials (ERPs) and amplitude modulation of evoked oscillatory responses. MAIN RESULTS: The illusion stimuli elicited VEPs in an early time window encompassing a negative component (N1) from 110 to 200 ms and a positive component (P2) between 210 and 300 ms. Based on the feature analysis, a filter bank was designed to extract discriminative signals. The task-related component analysis (TRCA) was used to evaluate the binary classification task performance of the proposed method. Then the highest accuracy of 86.67% was achieved with a data length of 0.6 s. SIGNIFICANCE: The results of this study demonstrate that the static motion illusion paradigm has the feasibility of implementation and is promising for VEP-based BCI applications.
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Metal-organic frameworks (MOFs) with diverse composition, tunable structure, and unique physicochemical properties have emerged as promising materials in various fields. The tunable pore structure, abundant active sites, and ultrahigh specific surface area can facilitate mass transport and provide outstanding capacity, making MOFs an ideal active material for electrochemical energy storage and conversion. However, the poor electrical conductivity of pristine MOFs severely limits their applications in electrochemistry. Developing conductive MOFs has proved to be an effective solution to this problem. This review focuses on the design and synthesis of conductive MOF composites with judiciously chosen conducting materials, pristine MOFs, and assembly methods, as well as the preparation of intrinsically conductive MOFs based on building 2D π-conjugated structures, introducing mixed-valence metal ions/redox-active ligands, designing π-π stacked pathways, and constructing infinite metal-sulfur chains (-M-S-)∞ . Furthermore, recent progress and challenges of conductive MOFs for energy storage and conversion (supercapacitors, Li-ion batteries, Li-S batteries, and electrochemical water splitting) are summarized.