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Surface chemistry and bulk structure jointly play crucial roles in achieving high-performance supercapacitors. Here, the synergistic effect of surface chemistry properties (vacancy and phosphorization) and structure-derived properties (hollow hydrangea-like structure) on energy storage is explored by the surface treatment and architecture design of the nanostructures. The theoretical calculations and experiments prove that surface chemistry modulation is capable of improving electronic conductivity and electrolyte wettability. The structural engineering of both hollow and nanosheets produces a high specific surface area and an abundant pore structure, which is favorable in exposing more active sites and shortens the ion diffusion distance. Benefiting from its admirable physicochemical properties, the surface phosphorylated MnCo2O4.5 hollow hydrangea-like structure (P-MnCoO) delivers a high capacitance of 425 F g−1 at 1 A g−1, a superior capability rate of 63.9%, capacitance retention at 10 A g−1, and extremely long cyclic stability (91.1% after 10,000 cycles). The fabricated P-MnCoO/AC asymmetric supercapacitor achieved superior energy and power density. This work opens a new avenue to further improve the electrochemical performance of metal oxides for supercapacitors.

Studying the distribution and transport dynamics of cations in plants is crucial for understanding their response mechanisms to saline–alkali stress conditions. However, our current understanding of how restoration measures affect cation distribution and transport in plants is surprisingly limited. To address this gap, we conducted a split-plot experiment using Medicago sativa L. cv. “Zhongmu No. 1” to investigate the combined effects of biological and chemical restoration measures—with bio-fertilizer as the primary zone and flue gas desulfurization (FGD) gypsum and with humic acid as the secondary zone—on soil properties, plant growth, and the content, distribution, and transport of cations in plants. The results revealed that bio-fertilizers exhibited positive effects on the plant growth, yield, and translocation of key ionic components to leaves. On the contrary, FGD gypsum with humic acid reduced the soil’s pH level, exchangeable sodium percentage (ESP), and sodium adsorption ratio (SAR) while increasing the contents of K+, Ca2+, and Mg2+ in the soil. The combination of bio-fertilizer, FGD gypsum, and humic acid increased the biomass and enhanced the translocation of Mg2+ to leaves. The distribution and transport of Mg2+ within the plant constituted pivotal elements for enhancing plant growth through restoration strategies. The application of bio-fertilizer, FGD gypsum, and humic acid reduced Na+ transport in M. sativa by enhancing the selective absorption of beneficial ions in leaves and by facilitating the transport of Ca2+ and Mg2+ from stems to the leaves. This, in turn, increases the salt tolerance of plants and promotes their growth. Our results offer new insights into the interactions among measures, soil, and plants in saline–alkali land restoration, providing practical solutions for the restoration of saline–alkali soil.

DEAD-box decapping enzyme 20 (DDX20) is a putative RNA-decapping enzyme that can be identified by the conserved motif Asp–Glu–Ala–Asp (DEAD). Cellular processes involve numerous RNA secondary structure alterations, including translation initiation, nuclear and mitochondrial splicing, and assembly of ribosomes and spliceosomes. DDX20 reportedly plays an important role in cellular transcription and post-transcriptional modifications. On the one hand, DDX20 can interact with various transcription factors and repress the transcriptional process. On the other hand, DDX20 forms the survival motor neuron complex and participates in the assembly of snRNP, ultimately affecting the RNA splicing process. Finally, DDX20 can potentially rely on its RNA-unwinding enzyme function to participate in microRNA (miRNA) maturation and act as a component of the RNA-induced silencing complex. In addition, although DDX20 is not a key component in the innate immune system signaling pathway, it can affect the nuclear factor kappa B (NF-κB) and p53 signaling pathways. In particular, DDX20 plays different roles in tumorigenesis development through the NF-κB signaling pathway. This process is regulated by various factors such as miRNA. DDX20 can influence processes such as viral replication in cells by interacting with two proteins in Epstein–Barr virus and can regulate the replication process of several viruses through the innate immune system, indicating that DDX20 plays an important role in the innate immune system. Herein, we review the effects of DDX20 on the innate immune system and its role in transcriptional and post-transcriptional modification processes, based on which we provide an outlook on the future of DDX20 research in innate immunity and viral infections.

Micro/nano-heterostructure with subtle structural design is an effective strategy to reduce the self-aggregation of 2D structure and maintain a large specific surface area to achieve high-performance supercapacitors. Herein, we report a rationally designed micro/nano-heterostructure of complex ternary transition metal oxides (TMOs) by a two-step hydrothermal method. Microflake-assembled island-like CuCo2O4 frameworks and secondary inserted units of NiMoO4 nanosheets endow CuCo2O4/NiMoO4 composites with desired micro/nanostructure features. Three-dimensional architectures constructed from CuCo2O4 microflakes offer a robust skeleton to endure structural change during cycling and provide efficient and rapid pathways for ion and electron transport. Two-dimensional NiMoO4 nanosheets possess numerous active sites and multi-access ion paths. Benefiting from above-mentioned advantages, the CuCo2O4/NiMoO4 heterostructures exhibit superior pseudocapacitive performance with a high specific capacitance of 2350 F/g at 1 A/g as well as an excellent cycling stability of 91.5% over 5000 cycles. A solid-state asymmetric supercapacitor based on the CuCo2O4/NiMoO4 electrode as a positive electrode and activated carbon as a negative electrode achieves a high energy density of 51.7 Wh/kg at a power density of 853.7 W/kg. These results indicate that the hybrid micro/nanostructured TMOs will be promising for high-performance supercapacitors.

Obesity represents a major health challenge because it substantially increases the risk of metabolic diseases. Capsaicin, the major active ingredient of Capsicum spp., has been reported to possess anti-obesity activity. Hereon, the effect of capsaicin on glucose uptake and consumption in hepatocytes was extensively studied. Capsaicin was shown to accelerate the glucose uptake/consumption and the ATP production of hepatocytes. The elevation of intracellular Ca2+ was thought to be a potential mechanism. By transcriptome analysis, 78, 146 and 507 differentially expressed genes (DEGs) were identified between capsaicin and the control group for 4 h, 12 h and 24 h treatments. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that most of the DEGs were involved in canonical pathways, like MAPK and PI3K-AKT signaling pathways. Clustering analysis showed that many DEGs were associated with glucose and amino acid metabolism. The variation trend in genes related to glucose and amino acid metabolism (like CTH, VEGFA, PCK2 and IGFBP3) in the quantitative PCR (q-PCR) assay was consistent with the transcriptome data. These results demonstrated that capsaicin efficiently accelerated the glucose uptake and consumption of hepatocytes.

Adding time delay to nonlinear systems can significantly improve their performance, making it possible to construct image-encryption algorithms with higher security. In this paper, we propose a time-delayed nonlinear combinatorial hyperchaotic map (TD-NCHM) with a wide hyperchaotic interval. Based on TD-NCHM, we develop a fast and secure image-encryption algorithm that includes a plaintext-sensitive key-generation method and a simultaneous row-column shuffling-diffusion encryption process. Plenty of experiments and simulations demonstrate the superiority of the algorithm in terms of efficiency, security, and practical value in secure communications.

A reliable constitutive model is a prerequisite to simulate a new complex forming technique, which is represented by the near-net shape forging process of aluminum wheels in this study. The aim of the present work was to identify the physical-based constitutive model parameters of Al-Zn-Mg alloy via the inverse analysis method based on experimental data and numerical analysis: the stress–strain curves at different temperatures and strain rates were obtained based on hot compression tests. On the basis of the shape of the compressed specimens and experimental force–displacement data, the friction coefficients and the optimized physical-based constitutive model were determined by using two-times inverse analysis techniques. Results showed that the global average error between the predicted and experimental force–displacement curves was only 3.8%. Then, thermo-mechanical finite element models were built in the Deform-3D software to simulate the two-stage forging processes of the near-net shape forging of aluminum alloy wheels, and the results showed that the predicted load–stroke curves were in good agreement with the experimental ones in all forging stages, which verified the prediction accuracy of the optimized physical-based constitutive model. In addition, the identification of the physical-based constitutive model parameters by the inverse analysis method provides a theoretical basis for formulating and optimizing the near-net shape forging process parameters of aluminum alloy wheels.

2A12 aluminum alloy is a high-strength aerospace alloy. During its extrusion process, the extrusion process parameters have a great impact on the microstructure evolution of the extruded products. There are three extrusion process parameters controlled in the actual project, which are the initial temperature of billet, the initial temperature of die and the extrusion speed. Combined with a back propagation (BP) neural network and finite element method (FEM) simulation, based on the constitutive equation and recrystallization evolution process of 2A12 aluminum alloy, this paper establishes a prediction model for the grain size of extruded pipe by these three extrusion process parameters. This paper used a 35MN extruding machine for a production verification of 2A12 pipe. The results show that the predicted grain size is 3% smaller than the actual size.

Ni–Co–P alloy coatings were successfully fabricated by jet electrodeposition with varying pulse frequencies and duty cycles in order to prolong the longevity of steel C1045 substrates. The results showed that the microstructures and properties of samples were significantly affected by pulse frequencies and duty cycles. All the samples with varying pulse frequencies and duty cycles exhibited a face-centered cubic (FCC) structure. Additionally, the average grain size of the samples reached 20.6 nm. The microhardness of the coatings was observed to first increase, and then decrease, with a rise in pulse frequencies and duty cycles. The microhardness reached 656.2 HV0.1, and the wear scar width of the coatings reached 414.4 µm at 4 kHz pulse frequency and 80% duty cycle. Additionally, the corrosion current densities (Icorr) of samples reached a minimum value of 0.74 µA·cm−2, the corrosion rates (Rcorr) reached a minimum value of 8.9 µm·year−1, and the charge transfer resistance (Rct) reached a maximum value of 8.36 × 104 Ω·cm−2, which indicated the optimal seawater corrosion resistance of the deposited coatings.

The parametric representation and aerodynamic shape optimization of a three-dimensional circular-to-rectangular transition nozzle designed and built using control lines distributed along the circumferential direction were investigated in this study. A surrogate model based on class/shape transformation, principal component analysis and radial basis neural network was proposed with fewer design parameters for parametric representation and performance parameter prediction of the three-dimensional circular-to-rectangular transition nozzle. The surrogate model was combined with Non-dominated Sorting Genetic Algorithm-II to optimize the aerodynamic shape of the nozzle. The results showed that the surrogate model effectively achieved the parametric representation and aerodynamic shape optimization of the three-dimensional circular-to-rectangular transition nozzle. The geometric dimensions and performance parameters of the parametric reconstructed model were comparable to that of the initial model, implying that they can meet the needs of optimal design. The axial thrust coefficient and lift of the optimized nozzle were increased by approximately 0.742% and 15.707%, respectively.

Piceatannol (PIC) is a natural stilbene extracted from grape skins that exhibits biological activities such as antibacterial, antitumor, and antioxidant activities. The present study was carried out to further investigate the effect of PIC on the antibacterial activity of different antibiotics and to reveal the antibacterial mechanism of PIC. We found that PIC had an inhibitory effect against Staphylococcus aureus (S. aureus); its minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were 128 μg/mL and 256 μg/ mL, respectively. Additionally, we measured the fractional inhibitory concentration (FIC) of PIC combined with antibiotics via the checkerboard method. The results showed that when PIC and ciprofloxacin (CIP) were combined, they displayed a synergistic effect against S. aureus. Moreover, this synergistic effect was verified by time–kill assays. Further, the results of the membrane permeability assay and proton motive force assay revealed that PIC could enhance the sensitivity of S. aureus to CIP by dissipating the bacterial proton motive force (PMF), particularly the ∆ψ component, rather than increasing membrane permeability. PIC also inhibited bacterial adenosine triphosphate (ATP) synthesis and was less likely to induce bacterial resistance but exhibited slight hemolytic activity on mammalian erythrocytes. In summary, the combination of PIC and CIP is expected to become a new drug combination to combat S. aureus.

In this study, we developed a fluorescent aptasensor based on Fe3O4/Au/g-C3N4 and a FAM-labeled aptamer (FAM-SMZ1S) against sulfamethazine (SMZ) for the specific and sensitive detection of SMZ in food matrix. The FAM-SMZ1S was adsorbed by the Fe3O4/Au/g-C3N4 via π–π stacking and electrostatic adsorption, serving as a basis for the ultrasensitive detection of SMZ. Molecular dynamics was used to explain the reasons why SMZ1S and SMZ were combined. This aptasensor presented sensitive recognition performance, with a limit of detection of 0.16 ng/mL and a linear range of 1–100 ng/mL. The recovery rate ranged from 91.6% to 106.8%, and the coefficient of variation (CV) ranged from 2.8% to 13.4%. In addition, we tested the aptasensor for the monitoring of SMZ in various matrix samples, and the results were well-correlated (R2 ≥ 0.9153) with those obtained for HPLC detection. According to these results, the aptasensor was sensitive and accurate, representing a potentially useful tool for the detection of SMZ in food matrix.

Z-conformation nucleic acid binding protein 1 (ZBP1), a powerful innate immune sensor, has been identified as the important signaling initiation factor in innate immune response and the multiple inflammatory cell death known as PANoptosis. The initiation of ZBP1 signaling requires recognition of left-handed double-helix Z-nucleic acid (includes Z-DNA and Z-RNA) and subsequent signaling transduction depends on the interaction between ZBP1 and its adapter proteins, such as TANK-binding kinase 1 (TBK1), interferon regulatory factor 3 (IRF3), receptor-interacting serine/threonine-protein kinase 1 (RIPK1), and RIPK3. ZBP1 activated innate immunity, including type-I interferon (IFN-I) response and NF-κB signaling, constitutes an important line of defense against pathogenic infection. In addition, ZBP1-mediated PANoptosis is a double-edged sword in anti-infection, auto-inflammatory diseases, and tumor immunity. ZBP1-mediated PANoptosis is beneficial for eliminating infected cells and tumor cells, but abnormal or excessive PANoptosis can lead to a strong inflammatory response that is harmful to the host. Thus, pathogens and host have each developed multiplex tactics targeting ZBP1 signaling to maintain strong virulence or immune homeostasis. In this paper, we reviewed the mechanisms of ZBP1 signaling, the effects of ZBP1 signaling on host immunity and pathogen infection, and various antagonistic strategies of host and pathogen against ZBP1. We also discuss existent gaps regarding ZBP1 signaling and forecast potential directions for future research.

Block of proliferation 1 (BOP1) is a key protein that helps in the maturation of ribosomes and promotes the progression of the cell cycle. However, its role in the leaf morphogenesis of cotton remains unknown. Herein, we report and study the function of GhBOP1 isolated from Gossypium hirsutum. The sequence alignment revealed that BOP1 protein was highly conserved among different species. The yeast two-hybrid experiments, bimolecular fluorescence complementation, and luciferase complementation techniques revealed that GhBOP1 interact with GhPES and GhWDR12. Subcellular localization experiments revealed that GhBOP1, GhPES and GhWDR12 were localized at the nucleolus. Suppression of GhBOP1 transcripts resulted in the uneven bending of leaf margins and the presence of young wrinkled leaves by virus-induced gene silencing assay. Abnormal palisade arrangements and the presence of large upper epidermal cells were observed in the paraffin sections of the wrinkled leaves. Meanwhile, a jasmonic acid-related gene, GhOPR3, expression was increased. In addition, a negative effect was exerted on the cell cycle and the downregulation of the auxin-related genes was also observed. These results suggest that GhBOP1 plays a critical role in the development of wrinkled cotton leaves, and the process is potentially modulated through phytohormone signaling.

The Tibetan Plateau is among the region’s most sensitive areas to global climate change. The observation data from 113 meteorological stations on the Tibetan Plateau and surrounding regions in China for 1971–2017 were used to analyze the periodic oscillations and trends in precipitation and extreme precipitation on multiple time scales to ensemble empirical mode decomposition. The relationship between extreme precipitation and sea-surface temperature (SST) anomalies was also explored. The results were as follows. (1) The timing of extreme-precipitation events in the highlands is consistent, with increased total precipitation and increased frequency, intensity, and extreme values of extreme precipitation. (2) Changes in temperature and precipitation are not completely synchronized. The total extreme precipitation, number of extreme-precipitation days, maximum single-day precipitation, and extreme single-day precipitation intensity all showed increases with fluctuations; the quasi-3-year oscillation contributes the most to the extreme precipitation. PRCPTOT is most strongly correlated with R10 and R95p. (3) The spatiotemporal patterns of the first and second empirical orthogonal function modes of the indices differed significantly and were not spatiotemporally uniform, but exhibited local clustering. (4) The Indian Ocean Warm Pool Strength and Western Pacific Warm Pool Strength indices were most highly correlated with each extreme-precipitation index, and the timings of the extreme-precipitation events lagged behind those of the SST anomalies. This study improves our understanding of extreme precipitation events in the context of climate warming and provides a basic analysis for the further assessment and prediction of extreme precipitation on the Tibetan Plateau and the surrounding ecologically fragile areas.

Herein, we developed a novel truncation technique for aptamer sequences to fabricate highly sensitive aptasensors based on molecular docking and molecular dynamics simulations. The binding mechanism and energy composition of the aptamer/sulfaquinoxaline (SQX) complexes were investigated. We successfully obtained a new SQX-specific aptamer (SBA28-1: CCCTAGGGG) with high affinity (Kd = 27.36 nM) and high specificity determined using graphene oxide. This aptamer has a unique stem-loop structure that can bind to SQX. Then, we fabricated a fluorescence aptasensor based on SBA28-1, gold nanoparticles (AuNPs), and rhodamine B (RhoB) that presented a good linear range of 1.25–160 ng/mL and a limit of detection of 1.04 ng/mL. When used to analyze water samples, the aptasensor presented acceptable recovery rates of 93.1–100.1% and coefficients of variation (CVs) of 2.2–10.2%. In conclusion, the fluorescence aptasensor can accurately and sensitively detect SQX in water samples and has good application prospects.

Ovate family proteins (OFPs) are valued as a family of transcription factors that are unique to plants, and they play a pluripotent regulatory role in plant growth and development, including secondary-cell-wall synthesis, DNA repair, gibberellin synthesis, and other biological processes, via their interaction with TALE family proteins. In this study, CHIP-SEQ was used to detect the potential target genes of AtOFP1 and its signal-regulation pathways. On the other hand, Y2H and BIFC were employed to prove that AtOFP1 can participate in ABA signal transduction by interacting with one of the TALE family protein called AtKNAT3. ABA response genes are not only significantly upregulated in the 35S::HAOFP1 OE line, but they also show hypersensitivity to ABA in terms of seed germination and early seedling root elongation. In addition, the AtOFP1-regulated target genes are mainly mitochondrial membranes that are involved in the oxidative–phosphorylation pathway. Further qRT-PCR results showed that the inefficient splicing of the respiratory complex I subunit genes NAD4 and NAD7 may lead to ROS accumulation in 35S::HA-AtOFP1 OE lines. In conclusion, we speculated that the overexpression of AtOFP1 may cause the ABA hypersensitivity response by increasing the intracellular ROS content generated from damage to the intima systems of mitochondria.

Nano-enabled agriculture is now receiving increasing attentions. Among the used nanomaterials, carbon-based nanomaterials are good candidates for sustainable agriculture. Previous review papers about the role of carbon-based nanomaterials in agriculture are either focused on one type of carbon-based nanomaterial or lack systematic discussion of the potential wide applications in agriculture. In this review, different types of carbon-based nanomaterials and their applications in light converters, nanosensors, and delivery tools in agriculture are summarized. Possible knowledge gaps are discussed. Overall, this review helps to better understand the role and the potential of carbon-based nanomaterials for nano-enabled agriculture.

White clover (Trifolium repens L.) is cultivated as a forage crop and planted in various landscapes for soil conservation. There are numerous reports of failed white clover stands each year. A good understanding of the seed germination biology of white clover in relation to environmental factors is essential to achieve successful stand establishment. A series of experiments were conducted to investigate the impacts of light, temperature, planting depth, drought, and salt stress on seed germination and the emergence of white clover. White clover is negatively photoblastic, and seed germination averaged 63 and 66% under light and complete dark conditions 4 weeks after planting (WAP), respectively. Temperature affected the seed germination speed and rate. At 1 WAP, seeds incubated at 15 to 25 °C demonstrated a significantly higher germination rate than the low temperatures at 5 and 10 °C; however, the germination rate did not differ among the temperature treatments at 4 WAP. The results suggest that white clover germination decreases with increasing sowing depths, and the seeds should be sown on the soil surface or shallowly buried at a depth ≤1 cm to achieve an optimal emergence. White clover seeds exhibited high sensitivity to drought and salinity stress. The osmotic potential and NaCl concentration required to inhibit 50% seed germination were −0.19 MPa and 62.4 mM, respectively. Overall, these findings provide quantifiable explanations for inconsistent establishment observed in field conditions. The results obtained in this research can be used to develop effective planting strategies and support the successful establishment of white clover stands.

Predatory species comprise a small but important and often overlooked component of the Thysanoptera. A case in point, the ant-mimicking Franklinothrips are widely distributed in the tropics and are considered important generalist natural enemies for thrips and some other small arthropod prey. Franklinothrips present an addition to biocontrol applications, i.e., greenhouse or commercial application for certain target pests and situations. Current knowledge, including distribution, biological features, life history pa rameters, prey specificity, host plant associations and lass production is yet insufficient to decide to what extent Franklinothrips could contribute for biological control programs. In this review, we summarized the geographical background, morphology, and prey associations, with a focus on F. vespiformis, the most widely distributed species of predatory thrips. This literature review serves as the basis for future research into the use of Franklinothrips as biocontrol agents for economically significant insect and mite pests in China and elsewhere.

Soft dielectric elastomers can quickly achieve large deformations when they are subjected to electromechanical loads. They are widely used to fabricate a number of soft functional devices. However, the functions of soft devices are limited to the failure modes of soft dielectric elastomers. In this paper, we use graded dielectric elastomers to produce a soft energy harvester with a strong ability of energy harvesting. Compared to the conventional energy harvester with homogeneous dielectric films, our new energy harvester is made of graded elastomers and can increase both the specific energy from 2.70 J/g to 2.93 J/g and the maximum energy from 6.3 J/g to 8.6 J/g by just using a stiffer outer radius. By optimizing the material parameters in graded dielectric films, the soft energy harvester can reach better performance, and our results can provide guidance for designing powerful energy harvesters.

In this paper, we use satellite-assisted and multi-group multicast mechanisms to relieve ground traffic pressure and improve data transmission efficiency of cell-free massive MIMO systems. We propose to estimate channel state information (CSI) by common pilot scheme. Given the estimated CSI, we derive the closed-form expressions of achievable rate with maximum ratio transmission (MRT) and zero-forcing (ZF) precoding. The correctness of the closed-form expressions is verified through simulations. The results show that with the help of satellite and multicast, the average system spectrum efficiency (SE) can be significantly improved.

Pulpal and periapical diseases account for a large proportion of dental visits, the current treatments for which are root canal therapy (RCT) and pulp revascularisation. Despite the clinical signs of full recovery and histological reconstruction, true regeneration of pulp tissues is still far from being achieved. The goal of regenerative endodontics is to promote normal pulp function recovery in inflamed or necrotic teeth that would result in true regeneration of the pulpodentinal complex. Recently, rapid progress has been made related to tissue engineering-mediated pulp regeneration, which combines stem cells, biomaterials, and growth factors. Since the successful isolation and characterisation of dental pulp stem cells (DPSCs) and other applicable dental mesenchymal stem cells, basic research and preclinical exploration of stem cell-mediated functional pulp regeneration via cell transplantation and cell homing have received considerably more attention. Some of this effort has translated into clinical therapeutic applications, bringing a ground-breaking revolution and a new perspective to the endodontic field. In this article, we retrospectively examined the current treatment status and clinical goals of pulpal and periapical diseases and scrutinized biological studies of functional pulp regeneration with a focus on DPSCs, biomaterials, and growth factors. Then, we reviewed preclinical experiments based on various animal models and research strategies. Finally, we summarised the current challenges encountered in preclinical or clinical regenerative applications and suggested promising solutions to address these challenges to guide tissue engineering-mediated clinical translation in the future.

The intelligent prosthesis driven by electromyography (EMG) signal provides a solution for the movement of the disabled. The proper position of EMG sensors can improve the prosthesis’s motion recognition ability. To exert the amputee’s action-oriented ability and the prosthesis’ control ability, the EMG spatial distribution and internal connection of the prosthetic wearer is analyzed in three kinds of movement conditions: appropriate angle, excessive angle, and angle too small. Firstly, the correlation characteristics between the EMG channels are analyzed by mutual information to construct a muscle functional network. Secondly, the network’s features of different movement conditions are analyzed by calculating the characteristic of nodes and evaluating the importance of nodes. Finally, the convergent cross-mapping method is applied to construct a directed network, and the critical muscle groups which can reflect the user’s movement intention are determined. Experiment shows that this method can accurately determine the EMG location and simplify the distribution of EMG sensors inside the prosthetic socket. The network characteristics of key muscle groups can distinguish different movements effectively and provide a new strategy for decoding the relationship between limb nerve control and body movement.

Background: Dryopteris fragrans, which is densely covered with glandular trichomes, is considered to be one of the ferns with the most medicinal potential. The transcriptomes from selected tissues of D. fragrans were collected and analyzed for functional and comparative genomic studies. The aim of this study was to determine the transcriptomic characteristics of wild D. fragrans sporangium in tissues from the SR (root), SL (sporophyll), and TRL (sporophyll with glandular trichomes removed). Results: Cluster analysis identified genes that were highly expressed in an organ-specific manner according to read mapping, feature counting, and normalization. The functional map identified gene clusters that can uniquely describe the function of each tissue. We identified a group of three tissue-specific transcription factors targeting the SL, SR, and TRL. In addition, highly expressed transcription factors (TFs) were found in each tissue-specific gene cluster, where ERF and bHLH transcription factors were the two types showing the most distinct expression patterns between the three different tissues. The specific expression of transcription factor genes varied between the different types of tissues. The numbers of transcription factors specifically expressed in the roots and sporophylls were 60 and 30, respectively, while only seven were found for the sporophylls with glandular trichomes removed. The expression of genes known to be associated with the development of glandular trichomes in flowering plants, including MIXTA, ATML1, and MYB106, were also validated and are discussed. In particular, a unigene encoding MIXTA was identified and exhibited the highest expression level in SL in D. fragrans. Conclusions: This study is the first report of global transcriptomic analysis in different tissues of D. fragrans, and the first to discuss these findings in the context of the development of homologous glandular trichomes. These results set the stage for further research on the development, stress resistance, and secondary metabolism of D. fragrans glandular trichomes.

Aiming at a pneumatic artificial muscle (PAM) lower extremity exoskeleton, a control mechanism based on hybrid phase sliding mode control (SMC) is proposed. First of all, the human gait cycle is mainly divided into the swing phase and stance phase, and the lower extremity exoskeleton phase models are established by the Euler−Lagrange method, respectively. Secondly, the lower limb exoskeleton is inevitably affected in the diverse working environment, and the exoskeleton model has nonlinear and strong coupling characteristics, which both increase the control difficulty. In this situations, a robust sliding mode control method is designed based on an Extended State Observer (ESO). Thirdly, the pneumatic muscle takes time to contract and relax, and then the joint input torque cannot jump when the gait phase changes, hence, the smoothing switching of the assistive control scheme is introduced to solve it. The smoothing switching time is detected by a phase detector, and the phase detector is designed by the plantar pressure information. Finally the comparative simulation shows that this control strategy has the advantages of fast time, high control precision and no jump during control torque switching. Pneumatic artificial muscle contraction rate curve shows that the pneumatic muscles’ motion range meets the control requirement of the exoskeleton.

Sensor-based human activity recognition (HAR) has attracted interest both in academic and applied fields, and can be utilized in health-related areas, fitness, sports training, etc. With a view to improving the performance of sensor-based HAR and optimizing the generalizability and diversity of the base classifier of the ensemble system, a novel HAR approach (pairwise diversity measure and glowworm swarm optimization-based selective ensemble learning, DMGSOSEN) that utilizes ensemble learning with differentiated extreme learning machines (ELMs) is proposed in this paper. Firstly, the bootstrap sampling method is utilized to independently train multiple base ELMs which make up the initial base classifier pool. Secondly, the initial pool is pre-pruned by calculating the pairwise diversity measure of each base ELM, which can eliminate similar base ELMs and enhance the performance of HAR system by balancing diversity and accuracy. Then, glowworm swarm optimization (GSO) is utilized to search for the optimal sub-ensemble from the base ELMs after pre-pruning. Finally, majority voting is utilized to combine the results of the selected base ELMs. For the evaluation of our proposed method, we collected a dataset from different locations on the body, including chest, waist, left wrist, left ankle and right arm. The experimental results show that, compared with traditional ensemble algorithms such as Bagging, Adaboost, and other state-of-the-art pruning algorithms, the proposed approach is able to achieve better performance (96.7% accuracy and F1 from wrist) with fewer base classifiers.

Sensor-based human activity recognition can benefit a variety of applications such as health care, fitness, smart homes, rehabilitation training, and so forth. In this paper, we propose a novel two-layer diversity-enhanced multiclassifier recognition method for single wearable accelerometer-based human activity recognition, which contains data-based and classifier-based diversity enhancement. Firstly, we introduce the kernel Fisher discriminant analysis (KFDA) technique to spatially transform the training samples and enhance the discrimination between activities. In addition, bootstrap resampling is utilized to increase the diversities of the dataset for training the base classifiers in the multiclassifier system. Secondly, a combined diversity measure for selecting the base classifiers with excellent performance and large diversity is proposed to optimize the performance of the multiclassifier system. Lastly, majority voting is utilized to combine the preferred base classifiers. Experiments showed that the data-based diversity enhancement can improve the discriminance of different activity samples and promote the generation of base classifiers with different structures and performances. Compared with random selection and traditional ensemble methods, including Bagging and Adaboost, the proposed method achieved 92.3% accuracy and 90.7% recall, which demonstrates better performance in activity recognition.

The reliability and performance of high-voltage circuit breakers (HVCBs) will directly affect the safety and stability of the power system itself, and mechanical failures of HVCBs are one of the important factors affecting the reliability of circuit breakers. Moreover, the existing fault diagnosis methods for circuit breakers are complex and inefficient in feature extraction. To improve the efficiency of feature extraction, a novel mechanical fault feature selection and diagnosis approach for high-voltage circuit breakers, using features extracted without signal processing is proposed. Firstly, the vibration signal of the HVCBs’ operating system, which collects the amplitudes of signals from normal vibration signals, is segmented by a time scale, and obviously changed. Adopting the ensemble learning method, features were extracted from each part of the divided signal, and used for constructing a vector. The Gini importance of features is obtained by random forest (RF), and the feature is ranked by the features’ importance index. After that, sequential forward selection (SFS) is applied to determine the optimal subset, while the regularized Fisher’s criterion (RFC) is used to analyze the classification ability. Then, the optimal subset is input to the hierarchical hybrid classifier, and based on a one-class support vector machine (OCSVM) and RF for fault diagnosis, the state is accurately recognized by OCSVM. The known fault types are identified using RF, and the identification results are calibrated with OCSVM of a particular fault type. The experimental proves that the new method has high feature extraction efficiency and recognition accuracy by the measured HVCBs vibration signal, while the unknown fault type data of the untrained samples is effectively identified.