In the paper, two nonlinear parameter estimation methods based on chaotic theory, surrogate data method and Lyapunov exponents, are used to distinguish the difference of non-stationary signals. After brief introductin...In the paper, two nonlinear parameter estimation methods based on chaotic theory, surrogate data method and Lyapunov exponents, are used to distinguish the difference of non-stationary signals. After brief introducting of the corresponding algorithms, two typical different non-stationary signals with different nonlinear constraining boundaries are taken to be compared by using the above two methods respectively. The obtained results demonstrate that the apparently similar signals are distinguished effectively in a quantitative way by applying above nonlinear chaotic analyses.展开更多
A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference cha...A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics.However,it suffers from heavy computational overhead and large execution time.The paper,therefore,uses a novel fast discrete sparse S-transform(SST)suitable for extracting time frequency response to monitor non-stationary signal parameters,which can be ultimately used for disturbance detection,and their pattern classification.From the sparse S-transform matrix,some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier.This algorithm is robust under noisy conditions.Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well.Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm.All the simulation results imply that the proposed technique is very much efficient.展开更多
Previously, fault diagnosis of fixed or steady state mechanical failures (e.g., pumps in nuclear power plant turbines, engines or other key equipment) applied spectrum analysis (e.g., fast Fourier transform, FFT) to e...Previously, fault diagnosis of fixed or steady state mechanical failures (e.g., pumps in nuclear power plant turbines, engines or other key equipment) applied spectrum analysis (e.g., fast Fourier transform, FFT) to extract the frequency features as the basis for identifying the causes of failure types. However, mechanical equipment for increasingly instant speed variations (e.g., wind turbine transmissions or the mechanical arms used in 3C assemblies, etc.) mostly generate non-stationary signals, and the signal features must be averaged with analysis time which makes it difficult to identify the causes of failures. This study proposes a time frequency order spectrum method combining the short-time Fourier transform (STFT) and speed frequency order method to capture the order features of non-stationary signals. Such signal features do not change with speed, and are thus effective in identifying faults in mechanical components under non-stationary conditions. In this study, back propagation neural networks (BPNN) and time frequency order spectrum methods were used to verify faults diagnosis and obtained superior diagnosis results in non-stationary signals of gear-rotor systems.展开更多
A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non...A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non-stationary signal decomposition treatment, and uses the Wigner-Ville distribution(WVD) analysis for signal reconstruction. The method presented in this study can effectively resolves the time and frequency resolution issue for non-stationary signal analysis and the cross-term issue typically encountered in time-frequency analysis.The feasibility and accuracy of the proposed method are evaluated and verified in a numerical simulation.展开更多
This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two class...This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two classes of time-frequency analysis techniques are chosen for this study. One is short-time Fourier Transform (STFT) technique from linear time-frequency analysis and the other is the Wigner-Ville Distribution (WVD) from Quadratic time-frequency analysis technique. Algorithms for both these techniques are developed and implemented on non-stationary signals for spectrum analysis. The results of this study revealed that the WVD and its classes are most suitable for time-frequency analysis.展开更多
Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, t...Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments.展开更多
The possibility of describing the time-dependent processes of scattering by underlying surfaces and the clear sky, as well as the seasonal behaviour of the refractive index of troposphere by using nested semi-Markov p...The possibility of describing the time-dependent processes of scattering by underlying surfaces and the clear sky, as well as the seasonal behaviour of the refractive index of troposphere by using nested semi-Markov processes has been consid- ered. Local Gaussian models can be used to describe the process inside each phase state. The possibility of describing the sta- tistics of reflections from the sea and the refractive index by using Kravchenko finite functions has been shown for the first time.展开更多
Cell competition is an evolutionarily ancient mechanism that functions to remove unfit or dangerous clonal cells in a multicellular community.A classical model is the removal of polarity-deficient clones,such as the p...Cell competition is an evolutionarily ancient mechanism that functions to remove unfit or dangerous clonal cells in a multicellular community.A classical model is the removal of polarity-deficient clones,such as the precancerous scribble(scrib)mutant clones,in Drosophila imaginal discs.The activation of Ras,Yki,or Notch signaling robustly reverses the scrib mutant clonal fate from elimination to tumorous growth.Whether these signals converge to adopt a common mechanism to overcome the elimination pressure posed by cell competition remains unclear.Using single-cell transcriptomics,we find that a critical converging point downstream of Ras,Yki,and Notch signals is the upregulation of Upd2,an IL-6 family cytokine.Overexpression of Upd2 is sufficient to rescue the scrib mutant clones from elimination.Depletion of Upd2 blocks the growth of the scrib mutant clones with active Ras,Yki,and Notch signals.Moreover,Upd2 overexpression promotes robust intestinal stem cell(ISC)proliferation,while Upd2 is intrinsically required in ISCs for the growth of the adult intestine.Together,these results identify Upd2 as a crucial cell fitness factor that sustains tissue growth but can potentiate tumorigenesis when deregulated.展开更多
In this paper,we propose a novel graph signal processing convolution recurrent network(GSP CRN)for signal enhancement against high suppressive interference(HSI)in wireless communications.GSPCRN consists of the short-t...In this paper,we propose a novel graph signal processing convolution recurrent network(GSP CRN)for signal enhancement against high suppressive interference(HSI)in wireless communications.GSPCRN consists of the short-time graph signal processing(SGSP)approach and a modified convolution recurrent network.Similar to the traditional shorttime time-frequency transformation,SGSP frames the complex-valued communication signal and transforms it to the graph-domain representations,where the connection and weight flexibility of each vertex are fully taken into account.In the presence of HSI,SGSP can extract signal features from new graph-domain dimensions and empower neural networks for weak signal enhancement.Two SGSP methods,adjacency singular value decomposition and implicit graph transformation,are designed to capture relationships among the sampling points in the segmented signals.Simulation results demonstrate that our proposed GSPCRN outperforms existing classic methods in extracting weak signals from the HSI environment.When the interference-to-signal ratio exceeds 27dB,only our proposed GSPCRN can achieve the interference mitigation.展开更多
Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging ...Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.展开更多
Tooth morphogenesis is orchestrated by a complex interplay of signaling pathways and transcription factors that control cell proliferation,apoptosis,and differentiation,with the Wnt/β-catenin signaling pathway playin...Tooth morphogenesis is orchestrated by a complex interplay of signaling pathways and transcription factors that control cell proliferation,apoptosis,and differentiation,with the Wnt/β-catenin signaling pathway playing a pivotal role.However,the comprehensive regulatory mechanisms of Wnt/β-catenin signaling remain largely unclear.Smad7,a key antagonist of the TGF-βsuperfamily,is essential for maintaining tissue homeostasis and ensuring proper cellular function.Our previous study has demonstrated that Smad7 knockout in mice leads to impaired proliferative property of tooth germ cells,resulting in small molars.Here,we identified SMAD7 expression in human dental papilla and dental pulp,colocalized with β-CATENIN and cell proliferationrelated proteins.RNA sequencing analysis revealed a significant reduction in Wnt signaling activity in Smad7-deficient mouse tooth germs.Using lentivirus transfection,we established SMAD7-knockdown human dental papilla stem cells,which manifested remarkably blunt proliferation rate,along with diminished Wnt signaling activity.In vivo transplantation investigations further revealed the indispensable role of SMAD7 in dentin formation.Mechanistically,we revealed that β-CATENIN interacts with P-SMAD2/3 and SMAD7 through co-immunoprecipitation and yeast two-hybrid assays.Inhibition of TGF-β pathway or disruption of SMAD7/β-CATENIN transcription factor complex formation potently impacted Wnt/β-catenin activities,indicating both direct and indirect regulatory mechanisms.These findings highlight the critical role of SMAD7 in the proliferation and diffe rentiation of human dental stem cells,which could contribute to dental tissue regeneration and engineering.展开更多
The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading ...The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.展开更多
Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies...Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies.This study aimed to evaluate the potential of hederagenin(Hed)for treating osteoporosis and to elucidate its underlying mechanisms of action.Methods:The anti-osteoporotic potential of Hed was assessed by investigating its effects on ovariectomy(OVX)-induced bone loss in mice and on receptor activator of NF-kappaB ligand(RANKL)-induced osteoclast differentiation in RAW264.7 cells.Network pharmacology analysis and molecular docking were employed to identify key targets,which were subsequently validated experimentally.Results:In vitro,Hed suppressed osteoclastogenesis by inhibiting the formation of osteoclasts and F-actin rings and by down-regulating osteoclastspecific genes(Atp6v0d2 and Acp5).In vivo,Hed significantly amelioratedOVX-induced bone loss,restoring trabecular bone volume fraction(BV/TV)and trabecular number(Tb.N),while reducing trabecular separation(Tb.Sp).Network pharmacology analysis identified 142 overlapping targets linking Hed to osteoporosis,including tumor necrosis factor alpha(TNF-α),interleukin-6(IL-6),and IL-1β,with enrichment in innate immune signaling and osteoclast differentiation.Molecular docking analysis indicated strong binding affinities between Hed and targets such as TNF-α,IL-6,and IL-1β.Experimentally,Hed was found to decrease RANKL,elevate osteoprotegerin(OPG),and suppress intestinalmRNA levels of pro-inflammatory cytokines such as IL-1β,IL-6,IL-17A,and TNF-α.Conclusion:Hed exerts significant anti-osteoporotic effects inOVX-induced osteoporosis through a dualmechanism involving the suppression of both osteoclastogenesis and innate immune signaling pathways.These findings highlighted Hed’s novel role in modulating immune-bone crosstalk,offering a promising strategy for treating osteolytic diseases without estrogenic side effects.展开更多
The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payl...The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payloads is a transponder-type interstellar laser interferometer,designed to measure relative displacement changes at the pico-meter level.Among its components,phasemeter is tasked with extracting the phase and frequency of the interference signal.Currently,phase-locked loop(PLL)phasemeters are commonly employed.However,the second harmonic signal generated by the mixer can restrict both the dynamic range and phase measurement accuracy of the phasemeter.This paper analyzes the interstellar laser interferometer and the impact of the second harmonic signal on the phasemeter's performance.To address these challenges,a phasemeter incorporating a second harmonic signal filter is proposed.This new design mitigates second harmonic disturbances within the phasemeter's bandwidth by dynamically adjusting the filter's cutoff frequency to track the input signal frequency,thereby suppressing the second harmonic signal in real time.Theoretical and simulation analyses demonstrate that the proposed phasemeter with a second harmonic filter significantly enhances the dynamic range.Finally,experimental results verify that the phasemeter can achieve the tracking of sudden frequency changes up to4.8 MHz.展开更多
Hearing and balance disorders are significant health issues primarily caused by developmental defects or the irreversible loss of sensory hair cells(HCs).ldentifying the underlying genes involved in the morphogenesis ...Hearing and balance disorders are significant health issues primarily caused by developmental defects or the irreversible loss of sensory hair cells(HCs).ldentifying the underlying genes involved in the morphogenesis and development of HCs is crucial.Our current study highlights rhpn2,a member of rho-binding proteins,as essential for vestibular HC development.The rhpn2 gene is highly expressed in the crista and macula HCs.Loss of rhpn2 function in zebrafish reduces the otic vesicle area and vestibular HC number,accompanied by vestibular dysfunction.Shorter stereocilia and compromised mechanotransduction channel function are found in the crista HCs of rhpn2 mutants.Transcriptome RNA sequencing analysis predicts the potential interaction of rhpn2 with rhoab.Furthermore,co-immunoprecipitation confirms that Rhpn2 directly binds to RhoA,validating the interaction of the two proteins.rhpn2 knockout leads to a decreased expression of rock2b,a canonical RhoA signaling pathway gene.Treatment with the RhoA activator or exogenous rock2b mRNA injection mitigates crista HC stereocilia defects in rhpn2 mutants.This study uncovers the role of rhpn2 in vestibular HC development and stereocilia formation via mediating the RhoA signaling pathway,providing a target for the treatment of balance disorders.展开更多
Muscle atrophy can be induced by high doses or prolonged use of glucocorticoids.Kaempferol(Kae)is a naturally occurring flavonoid with a variety of biological activities and the effect of Kae on dexamethasone(Dex)indu...Muscle atrophy can be induced by high doses or prolonged use of glucocorticoids.Kaempferol(Kae)is a naturally occurring flavonoid with a variety of biological activities and the effect of Kae on dexamethasone(Dex)induced muscle atrophy in animals has not been elucidated.To explore this issue,the present experiments used a computationally assisted drug design scheme combining network pharmacology,molecular docking and in vivo experiments to investigate the mechanism of Kae against muscle atrophy.Network pharmacological analyses revealed 275 potential targets for Kae and 12294 potential targets for muscle atrophy,with a total of 228 crosstargets for Kae and muscle atrophy.GO and KEGG analyses were performed based on the protein-protein interaction(PPI)network of muscle atrophy and Kae component targets.The GO results showed that the biological processes were mainly related to the metabolic process of reactive oxygen species,and the response to oxidative stress;the cellular components were mainly focused on membrane microdomains,and membrane regions;the molecular functions mainly worked on phosphatase binding;and the KEGG pathway enrichment analyses identified the pathways of interaction between Kae and muscle atrophy.Finally,as verified by in vivo experiments,Kae may reduce the onset of muscle atrophy by activating the PI3K/AKT/m TOR/signalling pathway,inhibiting Foxo1/Foxo3 activity,and inhibiting downstream production of the ubiquitination 3 ligases Atrogin1 and Mu RF1;Kae also promotes the expression of NRF2/HO-1/KEAP1 signalling pathway,enhances muscle antioxidant capacity,inhibits the release of COX-2 and TNF-αinflammatory factors,and reduces the damage caused by oxidative stress and inflammatory factors to muscles.Therefore,there may be a synergistic effect of PI3K/AKT/m TOR and NRF2/HO-1/KEAP1 in Kae working together to prevent muscle atrophy.The binding energy and stability of Kae to potential targets were examined by molecular docking and molecular dynamics simulations,implying that Kae could be used for the prevention and treatment of muscle atrophy in patients.展开更多
V-raf-leukemia viral oncogene 1(RAF1),a serine/threonine protein kinase,is well established to play a crucial role in tumorigenesis and cell development.However,the specific role of hypothalamic RAF1 in regulating ene...V-raf-leukemia viral oncogene 1(RAF1),a serine/threonine protein kinase,is well established to play a crucial role in tumorigenesis and cell development.However,the specific role of hypothalamic RAF1 in regulating energy metabolism remains unknown.In this study,we found that the expression of RAF1 was significantly increased in hypothalamic AgRP neurons of diet-induced obesity(DIO)mice.Under normal chow diet feeding,overexpression of Raf1 in AgRP neurons led to obesity in mice characterized by increased body weight,fat mass,and impaired glucose tolerance.Conversely,Raf1 knockout in AgRP neurons protected against diet-induced obesity,reducing fat mass and improving glucose tolerance.Mechanistically,Raf1 activated the MAPK signaling pathway,culminating in the phosphorylation of cAMP response element-binding protein(CREB),which enhanced transcription of Agrp and Npy.Insulin stimulation further potentiated the RAF1-MEK1/2-ERK1/2-CREB axis,highlighting RAF1's role in integrating hormonal and nutritional signals to regulate energy balance.Collectively,these findings underscore the important role of RAF1 in AgRP neurons in maintaining energy homeostasis and obesity pathogenesis,positioning it and its downstream pathways as potential therapeutic targets for innovative strategies to combat obesity and related metabolic diseases.展开更多
Taohong Siwu Decoction(THSWD), a traditional Chinese medicinal formulation, has been demonstrated to significantly modulate key signaling pathways implicated in atherosclerosis(AS). This review examines the complex me...Taohong Siwu Decoction(THSWD), a traditional Chinese medicinal formulation, has been demonstrated to significantly modulate key signaling pathways implicated in atherosclerosis(AS). This review examines the complex mechanisms through which THSWD influences critical pathways, including nuclear factor kappa-B(NF-κB), phosphatidylinositol 3-kinase(PI3K)/serine-threonine kinase(AKT), Toll-like receptor 4(TLR4), mitogen-activated protein kinase(MAPK), and mammalian target of rapamycin(mTOR), that play pivotal roles in AS pathogenesis. By synthesizing experimental evidence and existing literature, the review summarizes how THSWD and its bioactive constituents regulate these signaling cascades to ameliorate AS. Furthermore, it highlights the distinctive therapeutic advantages of traditional Chinese medicine(TCM) compounds in managing chronic diseases driven by multi-target and multifactorial mechanisms. Analyzing disease targets from the perspective of signaling pathways enhances the scientific validation of clinical efficacy for such formulations, thereby offering novel insights for future research.展开更多
Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique bas...Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique based on low rank tensor approximation is proposed for multichannel monitoring signal processing and utilization.Firstly,the affinity relationship of multichannel signals can be acquired based on the clustering results of each channel signal.Wherein an affinity tensor is constructed to integrate the diverse and consistent information of the clustering information among multichannel signals.Secondly,a low-rank tensor optimization model is built and the joint affinity matrix is optimized with the assistance of the strong confidence affinity matrix.Through solving the optimization model,the fused affinity relationship graph of multichannel signals can be obtained.Finally,the multichannel fused clustering results can be acquired though the updated joint affinity relationship graph.The multichannel signal utilization examples in health state assessment with public datasets and microwave detection with actual echoes verify the advantages and effectiveness of the proposed method.展开更多
Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements ...Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.展开更多
基金supported by the National Natural Science Foundation of China NSFC under Grant No.10972192
文摘In the paper, two nonlinear parameter estimation methods based on chaotic theory, surrogate data method and Lyapunov exponents, are used to distinguish the difference of non-stationary signals. After brief introducting of the corresponding algorithms, two typical different non-stationary signals with different nonlinear constraining boundaries are taken to be compared by using the above two methods respectively. The obtained results demonstrate that the apparently similar signals are distinguished effectively in a quantitative way by applying above nonlinear chaotic analyses.
文摘A Fourier kernel based time-frequency transform is a proven candidate for non-stationary signal analysis and pattern recognition because of its ability to predict time localized spectrum and global phase reference characteristics.However,it suffers from heavy computational overhead and large execution time.The paper,therefore,uses a novel fast discrete sparse S-transform(SST)suitable for extracting time frequency response to monitor non-stationary signal parameters,which can be ultimately used for disturbance detection,and their pattern classification.From the sparse S-transform matrix,some relevant features have been extracted which are used to distinguish among different non-stationary signals by a fuzzy decision tree based classifier.This algorithm is robust under noisy conditions.Various power quality as well as chirp signals have been simulated and tested with the proposed technique in noisy conditions as well.Some real time mechanical faulty signals have been collected to demonstrate the efficiency of the proposed algorithm.All the simulation results imply that the proposed technique is very much efficient.
文摘Previously, fault diagnosis of fixed or steady state mechanical failures (e.g., pumps in nuclear power plant turbines, engines or other key equipment) applied spectrum analysis (e.g., fast Fourier transform, FFT) to extract the frequency features as the basis for identifying the causes of failure types. However, mechanical equipment for increasingly instant speed variations (e.g., wind turbine transmissions or the mechanical arms used in 3C assemblies, etc.) mostly generate non-stationary signals, and the signal features must be averaged with analysis time which makes it difficult to identify the causes of failures. This study proposes a time frequency order spectrum method combining the short-time Fourier transform (STFT) and speed frequency order method to capture the order features of non-stationary signals. Such signal features do not change with speed, and are thus effective in identifying faults in mechanical components under non-stationary conditions. In this study, back propagation neural networks (BPNN) and time frequency order spectrum methods were used to verify faults diagnosis and obtained superior diagnosis results in non-stationary signals of gear-rotor systems.
基金the National Natural Science Foundation of China(No.61271387)the Shandong Provincial Government’s Taishan Scholar Program
文摘A new time-frequency analysis method is proposed in this study using a multi-rate signal decomposition technique for the analysis of non-stationary signals. The method uses a multi-rate filter bank for an improved non-stationary signal decomposition treatment, and uses the Wigner-Ville distribution(WVD) analysis for signal reconstruction. The method presented in this study can effectively resolves the time and frequency resolution issue for non-stationary signal analysis and the cross-term issue typically encountered in time-frequency analysis.The feasibility and accuracy of the proposed method are evaluated and verified in a numerical simulation.
文摘This paper presents the methodology, properties and processing of the time-frequency techniques for non-stationary signals, which are frequently used in biomedical, communication and image processing fields. Two classes of time-frequency analysis techniques are chosen for this study. One is short-time Fourier Transform (STFT) technique from linear time-frequency analysis and the other is the Wigner-Ville Distribution (WVD) from Quadratic time-frequency analysis technique. Algorithms for both these techniques are developed and implemented on non-stationary signals for spectrum analysis. The results of this study revealed that the WVD and its classes are most suitable for time-frequency analysis.
文摘Multi-components sinusoidal engineering signals who are non-stationary signals were considered in this study since their separation and segmentations are of great interests in many engineering fields. In most cases, the segmentation of non-stationary or multi-component signals is conducted in time domain. In this paper, we explore the advantages of applying joint time-frequency (TF) distribution of the multi-component signals to identify their segments. The Spectrogram that is known as Short-Time Fourier Transform (STFT) will be used for obtaining the time-frequency kernel. Time marginal of the computed kernel is optimally used for the signal segmentation. In order to obtain the desirable segmentation, it requires first to improve time marginal of the kernel by using two-dimensional Wiener mask filter applied to the TF kernel to mitigate and suppress non-stationary noise or interference. Additionally, a proper choice of the sliding window and its overlaying has enhanced our scheme to capture the discontinuities corresponding to the boundaries of the candidate segments.
基金The Joint Grant of the National Academy of Sciences of Ukraine(NASU)and the Russian Foundation for Basic Research(RFBR)2012-2013(No.12-02-90425)The Task Comprehensive Program of NAS U on the Scientific Space Research 2012-2016
文摘The possibility of describing the time-dependent processes of scattering by underlying surfaces and the clear sky, as well as the seasonal behaviour of the refractive index of troposphere by using nested semi-Markov processes has been consid- ered. Local Gaussian models can be used to describe the process inside each phase state. The possibility of describing the sta- tistics of reflections from the sea and the refractive index by using Kravchenko finite functions has been shown for the first time.
基金supported by grants to Yan Yan from the Research Grants Council of the Hong Kong Special Administrative Region(GRF16103620,GRF16104324,T13-602/21N)from Shenzhen Science and Technology Innovation Commission(JCYJ20200109140201722)+1 种基金to Toyotaka Ishibashi from the National Natural Science Foundation of China(32170548)to Zongzhao Zhai from the National Natural Science Foundation of China(32170509 and 31871469).
文摘Cell competition is an evolutionarily ancient mechanism that functions to remove unfit or dangerous clonal cells in a multicellular community.A classical model is the removal of polarity-deficient clones,such as the precancerous scribble(scrib)mutant clones,in Drosophila imaginal discs.The activation of Ras,Yki,or Notch signaling robustly reverses the scrib mutant clonal fate from elimination to tumorous growth.Whether these signals converge to adopt a common mechanism to overcome the elimination pressure posed by cell competition remains unclear.Using single-cell transcriptomics,we find that a critical converging point downstream of Ras,Yki,and Notch signals is the upregulation of Upd2,an IL-6 family cytokine.Overexpression of Upd2 is sufficient to rescue the scrib mutant clones from elimination.Depletion of Upd2 blocks the growth of the scrib mutant clones with active Ras,Yki,and Notch signals.Moreover,Upd2 overexpression promotes robust intestinal stem cell(ISC)proliferation,while Upd2 is intrinsically required in ISCs for the growth of the adult intestine.Together,these results identify Upd2 as a crucial cell fitness factor that sustains tissue growth but can potentiate tumorigenesis when deregulated.
基金supported by he National Social Science Found of China(2022-SKJJ-B-112).
文摘In this paper,we propose a novel graph signal processing convolution recurrent network(GSP CRN)for signal enhancement against high suppressive interference(HSI)in wireless communications.GSPCRN consists of the short-time graph signal processing(SGSP)approach and a modified convolution recurrent network.Similar to the traditional shorttime time-frequency transformation,SGSP frames the complex-valued communication signal and transforms it to the graph-domain representations,where the connection and weight flexibility of each vertex are fully taken into account.In the presence of HSI,SGSP can extract signal features from new graph-domain dimensions and empower neural networks for weak signal enhancement.Two SGSP methods,adjacency singular value decomposition and implicit graph transformation,are designed to capture relationships among the sampling points in the segmented signals.Simulation results demonstrate that our proposed GSPCRN outperforms existing classic methods in extracting weak signals from the HSI environment.When the interference-to-signal ratio exceeds 27dB,only our proposed GSPCRN can achieve the interference mitigation.
基金supported by the grants from the Key Research and Development Program of Xinjiang Uygur autonomous region in China(Grant No.2023B02017)the National Key Research and Development Program of China(Grant No.2024YFD2300703)+1 种基金the financial support from the Beijing Rural Revitalization Agricultural Science and Technology Project(Grant No.NY2401080000),BAIC01-2025the 2115 Talent Development Program of China Agricultural University.
文摘Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.
基金supported by the National Key Research and Development Program of China to W.Tian (2022YFA1104400)the National Natural Science Foundation of China to T.Chen (82100959)a grant from the Sichuan Science and Technology Program to Z.Liu (2024YFFK0068)。
文摘Tooth morphogenesis is orchestrated by a complex interplay of signaling pathways and transcription factors that control cell proliferation,apoptosis,and differentiation,with the Wnt/β-catenin signaling pathway playing a pivotal role.However,the comprehensive regulatory mechanisms of Wnt/β-catenin signaling remain largely unclear.Smad7,a key antagonist of the TGF-βsuperfamily,is essential for maintaining tissue homeostasis and ensuring proper cellular function.Our previous study has demonstrated that Smad7 knockout in mice leads to impaired proliferative property of tooth germ cells,resulting in small molars.Here,we identified SMAD7 expression in human dental papilla and dental pulp,colocalized with β-CATENIN and cell proliferationrelated proteins.RNA sequencing analysis revealed a significant reduction in Wnt signaling activity in Smad7-deficient mouse tooth germs.Using lentivirus transfection,we established SMAD7-knockdown human dental papilla stem cells,which manifested remarkably blunt proliferation rate,along with diminished Wnt signaling activity.In vivo transplantation investigations further revealed the indispensable role of SMAD7 in dentin formation.Mechanistically,we revealed that β-CATENIN interacts with P-SMAD2/3 and SMAD7 through co-immunoprecipitation and yeast two-hybrid assays.Inhibition of TGF-β pathway or disruption of SMAD7/β-CATENIN transcription factor complex formation potently impacted Wnt/β-catenin activities,indicating both direct and indirect regulatory mechanisms.These findings highlight the critical role of SMAD7 in the proliferation and diffe rentiation of human dental stem cells,which could contribute to dental tissue regeneration and engineering.
文摘The increasing integration of electric vehicle(EV)loads into power systems necessitates understanding their impact on stability.Small-magnitude perturbations,if persistent,can cause low-frequency oscillations,leading to synchronism loss and mechanical stress.This work analyzes the effect of voltage-dependent EV loads on this small-signal stability.The study models an EV load within a Single-Machine Infinite Bus(SMIB)system.It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller(UPFC),a key device for damping oscillations.The system’s performance is compared to a modified version equipped with both a UPFC and a Linear Quadratic Regulator(LQR)controller.Results confirm the significant influence of EV charging on the power network.The analysis demonstrates that the best performance is achieved with the SMIB system utilizing the combined UPFC and LQR controller.This configuration effectively dampens low-frequency oscillations,yielding superior results by reducing the system’s rise time,settling time,and peak overshoot.
基金supported by the Scientific Research Project of Anhui ProvincialHealth Commission(Grant No.AHWJ2021b063)National Natural Scientific Foundation of China(Grant No.82160048)+1 种基金Natural Science Foundation Project of Anhui Province(Grant No.2308085MH265)Major Scientific Research Project of Anhui Provincial Department of Education(Grant No.2024AH040205).
文摘Objectives:Postmenopausal osteoporosis is the most common form of osteoporosis in clinical practice,affecting millions of postmenopausal women worldwide.Postmenopausal osteoporosis demands safe and effective therapies.This study aimed to evaluate the potential of hederagenin(Hed)for treating osteoporosis and to elucidate its underlying mechanisms of action.Methods:The anti-osteoporotic potential of Hed was assessed by investigating its effects on ovariectomy(OVX)-induced bone loss in mice and on receptor activator of NF-kappaB ligand(RANKL)-induced osteoclast differentiation in RAW264.7 cells.Network pharmacology analysis and molecular docking were employed to identify key targets,which were subsequently validated experimentally.Results:In vitro,Hed suppressed osteoclastogenesis by inhibiting the formation of osteoclasts and F-actin rings and by down-regulating osteoclastspecific genes(Atp6v0d2 and Acp5).In vivo,Hed significantly amelioratedOVX-induced bone loss,restoring trabecular bone volume fraction(BV/TV)and trabecular number(Tb.N),while reducing trabecular separation(Tb.Sp).Network pharmacology analysis identified 142 overlapping targets linking Hed to osteoporosis,including tumor necrosis factor alpha(TNF-α),interleukin-6(IL-6),and IL-1β,with enrichment in innate immune signaling and osteoclast differentiation.Molecular docking analysis indicated strong binding affinities between Hed and targets such as TNF-α,IL-6,and IL-1β.Experimentally,Hed was found to decrease RANKL,elevate osteoprotegerin(OPG),and suppress intestinalmRNA levels of pro-inflammatory cytokines such as IL-1β,IL-6,IL-17A,and TNF-α.Conclusion:Hed exerts significant anti-osteoporotic effects inOVX-induced osteoporosis through a dualmechanism involving the suppression of both osteoclastogenesis and innate immune signaling pathways.These findings highlighted Hed’s novel role in modulating immune-bone crosstalk,offering a promising strategy for treating osteolytic diseases without estrogenic side effects.
基金the National Key Research&Development Program of China(Grant No.2022YFC2203901)the State Key Laboratory of Spatial Datum(Grant No.SKLSD2025-KF-03)+1 种基金Fundamental Research Funds for the Central UniversitiesSun Yat-sen University for the support。
文摘The space gravitational wave detection aims to detect gravitational waves in the mHz band in order to study supermassive black hole mergers,galaxy evolution and the structure of the early universe.One of its core payloads is a transponder-type interstellar laser interferometer,designed to measure relative displacement changes at the pico-meter level.Among its components,phasemeter is tasked with extracting the phase and frequency of the interference signal.Currently,phase-locked loop(PLL)phasemeters are commonly employed.However,the second harmonic signal generated by the mixer can restrict both the dynamic range and phase measurement accuracy of the phasemeter.This paper analyzes the interstellar laser interferometer and the impact of the second harmonic signal on the phasemeter's performance.To address these challenges,a phasemeter incorporating a second harmonic signal filter is proposed.This new design mitigates second harmonic disturbances within the phasemeter's bandwidth by dynamically adjusting the filter's cutoff frequency to track the input signal frequency,thereby suppressing the second harmonic signal in real time.Theoretical and simulation analyses demonstrate that the proposed phasemeter with a second harmonic filter significantly enhances the dynamic range.Finally,experimental results verify that the phasemeter can achieve the tracking of sudden frequency changes up to4.8 MHz.
基金supported by grants from the Natural Science Foundation of Jiangsu Province(BK20221377 and BK20220607)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB180023)the National Natural Science Foundation of China Grants(32200783,32350017,and 92368104),and the Qing Lan Project of Jiangsu Province.
文摘Hearing and balance disorders are significant health issues primarily caused by developmental defects or the irreversible loss of sensory hair cells(HCs).ldentifying the underlying genes involved in the morphogenesis and development of HCs is crucial.Our current study highlights rhpn2,a member of rho-binding proteins,as essential for vestibular HC development.The rhpn2 gene is highly expressed in the crista and macula HCs.Loss of rhpn2 function in zebrafish reduces the otic vesicle area and vestibular HC number,accompanied by vestibular dysfunction.Shorter stereocilia and compromised mechanotransduction channel function are found in the crista HCs of rhpn2 mutants.Transcriptome RNA sequencing analysis predicts the potential interaction of rhpn2 with rhoab.Furthermore,co-immunoprecipitation confirms that Rhpn2 directly binds to RhoA,validating the interaction of the two proteins.rhpn2 knockout leads to a decreased expression of rock2b,a canonical RhoA signaling pathway gene.Treatment with the RhoA activator or exogenous rock2b mRNA injection mitigates crista HC stereocilia defects in rhpn2 mutants.This study uncovers the role of rhpn2 in vestibular HC development and stereocilia formation via mediating the RhoA signaling pathway,providing a target for the treatment of balance disorders.
基金funded by Yunnan Youth Top-notch Talent Support Program(YNWR-QNBJ2018-173)Agricultural Joint project of Yunnan Provincial S&T Programs(202301BD070001-195)+2 种基金S&T project of Yunnan provincial finance(K212020001-01)supported by Yunnan Province Education Department’s Engineering Research Center of Eco-friendly Products from Yunnan Characteristic Edible FungiYunnan Province Yongsheng County Farmer Academician Technology service station.
文摘Muscle atrophy can be induced by high doses or prolonged use of glucocorticoids.Kaempferol(Kae)is a naturally occurring flavonoid with a variety of biological activities and the effect of Kae on dexamethasone(Dex)induced muscle atrophy in animals has not been elucidated.To explore this issue,the present experiments used a computationally assisted drug design scheme combining network pharmacology,molecular docking and in vivo experiments to investigate the mechanism of Kae against muscle atrophy.Network pharmacological analyses revealed 275 potential targets for Kae and 12294 potential targets for muscle atrophy,with a total of 228 crosstargets for Kae and muscle atrophy.GO and KEGG analyses were performed based on the protein-protein interaction(PPI)network of muscle atrophy and Kae component targets.The GO results showed that the biological processes were mainly related to the metabolic process of reactive oxygen species,and the response to oxidative stress;the cellular components were mainly focused on membrane microdomains,and membrane regions;the molecular functions mainly worked on phosphatase binding;and the KEGG pathway enrichment analyses identified the pathways of interaction between Kae and muscle atrophy.Finally,as verified by in vivo experiments,Kae may reduce the onset of muscle atrophy by activating the PI3K/AKT/m TOR/signalling pathway,inhibiting Foxo1/Foxo3 activity,and inhibiting downstream production of the ubiquitination 3 ligases Atrogin1 and Mu RF1;Kae also promotes the expression of NRF2/HO-1/KEAP1 signalling pathway,enhances muscle antioxidant capacity,inhibits the release of COX-2 and TNF-αinflammatory factors,and reduces the damage caused by oxidative stress and inflammatory factors to muscles.Therefore,there may be a synergistic effect of PI3K/AKT/m TOR and NRF2/HO-1/KEAP1 in Kae working together to prevent muscle atrophy.The binding energy and stability of Kae to potential targets were examined by molecular docking and molecular dynamics simulations,implying that Kae could be used for the prevention and treatment of muscle atrophy in patients.
基金support from various sources,including the National Natural Science Foundation of China(Grant Nos.81570774,82070872,92049118,and 82370854)the Junior Thousand Talents Program of China,and the Nanjing Medical University Startup Fund(All awarded to J.L.)support provided by Jiangsu Province's Innovation Personal as well as Innovative and Entrepreneurial Team of Jiangsu Province(Grant No.JSSCTD2021)(All awarded to J.L.).
文摘V-raf-leukemia viral oncogene 1(RAF1),a serine/threonine protein kinase,is well established to play a crucial role in tumorigenesis and cell development.However,the specific role of hypothalamic RAF1 in regulating energy metabolism remains unknown.In this study,we found that the expression of RAF1 was significantly increased in hypothalamic AgRP neurons of diet-induced obesity(DIO)mice.Under normal chow diet feeding,overexpression of Raf1 in AgRP neurons led to obesity in mice characterized by increased body weight,fat mass,and impaired glucose tolerance.Conversely,Raf1 knockout in AgRP neurons protected against diet-induced obesity,reducing fat mass and improving glucose tolerance.Mechanistically,Raf1 activated the MAPK signaling pathway,culminating in the phosphorylation of cAMP response element-binding protein(CREB),which enhanced transcription of Agrp and Npy.Insulin stimulation further potentiated the RAF1-MEK1/2-ERK1/2-CREB axis,highlighting RAF1's role in integrating hormonal and nutritional signals to regulate energy balance.Collectively,these findings underscore the important role of RAF1 in AgRP neurons in maintaining energy homeostasis and obesity pathogenesis,positioning it and its downstream pathways as potential therapeutic targets for innovative strategies to combat obesity and related metabolic diseases.
基金supported by the National Natural Science Foundation of China (Nos. 82104430 and 82274133)the Shanghai Sailing Program (No. 21YF1447600)the Future Plan for Traditional Chinese Medicine Development of Science and Technology of Shanghai Municipal Hospital of Traditional Chinese Medicine (No. WL-HBQN-2022002K)。
文摘Taohong Siwu Decoction(THSWD), a traditional Chinese medicinal formulation, has been demonstrated to significantly modulate key signaling pathways implicated in atherosclerosis(AS). This review examines the complex mechanisms through which THSWD influences critical pathways, including nuclear factor kappa-B(NF-κB), phosphatidylinositol 3-kinase(PI3K)/serine-threonine kinase(AKT), Toll-like receptor 4(TLR4), mitogen-activated protein kinase(MAPK), and mammalian target of rapamycin(mTOR), that play pivotal roles in AS pathogenesis. By synthesizing experimental evidence and existing literature, the review summarizes how THSWD and its bioactive constituents regulate these signaling cascades to ameliorate AS. Furthermore, it highlights the distinctive therapeutic advantages of traditional Chinese medicine(TCM) compounds in managing chronic diseases driven by multi-target and multifactorial mechanisms. Analyzing disease targets from the perspective of signaling pathways enhances the scientific validation of clinical efficacy for such formulations, thereby offering novel insights for future research.
基金supported by Shanghai Aerospace Science and Technology Innovation Foundation(SAST2023-075)。
文摘Multichannel signals have the characteristics of information diversity and information consistency.To better explore and utilize the affinity relationship within multichannel signals,a new graph learning technique based on low rank tensor approximation is proposed for multichannel monitoring signal processing and utilization.Firstly,the affinity relationship of multichannel signals can be acquired based on the clustering results of each channel signal.Wherein an affinity tensor is constructed to integrate the diverse and consistent information of the clustering information among multichannel signals.Secondly,a low-rank tensor optimization model is built and the joint affinity matrix is optimized with the assistance of the strong confidence affinity matrix.Through solving the optimization model,the fused affinity relationship graph of multichannel signals can be obtained.Finally,the multichannel fused clustering results can be acquired though the updated joint affinity relationship graph.The multichannel signal utilization examples in health state assessment with public datasets and microwave detection with actual echoes verify the advantages and effectiveness of the proposed method.
基金the support of the Major Science and Technology Project of Yunnan Province,China(Grant No.202502AD080007)the National Natural Science Foundation of China(Grant No.52378288)。
文摘Vehicle-induced response separation is a crucial issue in structural health monitoring(SHM).This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data.To extend the separation target from a fixed dataset to a continuously updating data stream,a block-wise sliding framework is first developed.This framework is further optimized considering the characteristics of real-time data streams,and its advantage in computational efficiency is theoretically demonstrated.During the decomposition and reconstruction processes,information from neighboring data blocks is fully utilized to reduce algorithmic complexity.In addition,a delay-setting strategy is introduced for each processing window to mitigate boundary effects,thereby balancing accuracy and efficiency.Simulated signal experiments are conducted to determine the optimal delay configuration and to verify the algorithm’s superior performance,achieving a lower Root Mean Square Error(RMSE)and only 0.0249 times the average computational time compared with the original algorithm.Furthermore,strain signals from the Lieshi River Bridge are employed to validate the method.The proposed algorithm successfully separates the static trend from vehicle-induced responses in real time across different sampling frequencies,demonstrating its effectiveness and applicability in real-time bridge monitoring.
