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
This study presents a hybrid CNN-Transformer model for real-time recognition of affective tactile biosignals.The proposed framework combines convolutional neural networks(CNNs)to extract spatial and local temporal fea...This study presents a hybrid CNN-Transformer model for real-time recognition of affective tactile biosignals.The proposed framework combines convolutional neural networks(CNNs)to extract spatial and local temporal features with the Transformer encoder that captures long-range dependencies in time-series data through multi-head attention.Model performance was evaluated on two widely used tactile biosignal datasets,HAART and CoST,which contain diverse affective touch gestures recorded from pressure sensor arrays.TheCNN-Transformer model achieved recognition rates of 93.33%on HAART and 80.89%on CoST,outperforming existing methods on both benchmarks.By incorporating temporal windowing,the model enables instantaneous prediction,improving generalization across gestures of varying duration.These results highlight the effectiveness of deep learning for tactile biosignal processing and demonstrate the potential of theCNN-Transformer approach for future applications in wearable sensors,affective computing,and biomedical monitoring.展开更多
A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate t...A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate the 1F of a multi-component Chirp signal accurately. Wigner distribution maxima （WDM） are usually utilized for this estimation. But in practice, estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal 1F estimation named Wigner Viterbi fit （WVF）, based on Wigner-Ville distribution （WVD） and the Viterbi algorithm. First, we transform the WVD of the Chirp signal into digital image, and apply the Viterbi algorithm to separate the components and estimate their IF. At last, we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments, and better suppression of interference and the edge effect. Compared with WDM, WVF can reduce the mean square error （MSE） by 50% when the signal to noise ration （SNR） is in the range of-15dB to -11dB. WVF is an effective and promising 1F estimation method.展开更多
To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least sq...To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.展开更多
Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-compone...Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.展开更多
Tumor stroma,or tumor microenvironment(TME),has been in the spotlight during recent years for its role in tumor development,growth,and metastasis.It consists of a myriad of elements,including tumor-associated macropha...Tumor stroma,or tumor microenvironment(TME),has been in the spotlight during recent years for its role in tumor development,growth,and metastasis.It consists of a myriad of elements,including tumor-associated macrophages,cancer-associated fibroblasts,a deregulated extracellular matrix,endothelial cells,and vascular vessels.The release of proinflammatory molecules,due to the inflamed microenvironment,such as cytokines and chemokines is found to play a pivotal role in progression of cancer and response to therapy.This review discusses the major key players and important chemical inflammatory signals released in the TME.Furthermore,the latest breakthroughs in cytokine-mediated crosstalk between immune cells and cancer cells have been highlighted.In addition,recent updates on alterations in cytokine signaling between chronic inflammation and malignant TME have also been reviewed.展开更多
Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w ...Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w hich corrupted by w hite Gaussian noise is proposed based on the discrete fractional Fourier transform(DFrFT) and the differential evolution( DE) algorithm. The proposed algorithm uses the DE algorithm instead of the conventional fine search algorithm to detect the peak of the signals in the FrFD. The paper simulated the influence of the noise and the resolution of the proposed algorithm. The results of the simulation show the proposed method does not only improve the estimation accuracy of the peak coordinate,but also reduces time consuming.展开更多
Hydrogels,owing to their porous network structure resembling the extracellular matrix(ECM),have become essential scaffold materials in the field of cartilage tissue engineering.Among them,gelatin methacrylate(GelMA)hy...Hydrogels,owing to their porous network structure resembling the extracellular matrix(ECM),have become essential scaffold materials in the field of cartilage tissue engineering.Among them,gelatin methacrylate(GelMA)hydrogels are widely used in bioink development due to their excellent biocompatibility,biodegradability,and tunable photo-crosslinking properties.However,the high biocompatibility of pure GelMA often comes at the cost of mechanical strength,limiting its applicability in cartilage regeneration.To overcome this trade-off,this study developed composite bioinks based on GelMA,silk fibroin(SF),and polyethylene oxide(PEO)for fabricating porous hydrogel scaffolds,which were then systematically characterized in terms of morphology,porosity,hydrophilicity,mechanical strength,rheological behavior,printability,and cytocompatibility.In this design,PEO serves as a porogen to generate highly porous structures(porosity up to 88%),while SF compensates for the mechanical loss caused by PEO,enabling the scaffold to retain a compression strength of up to 29.10 kPa.Among the tested formulations,the 10%GelMA/1%SF/1.5%PEO(1%=0.01 g/mL)bioink exhibited excellent printability,mechanical integrity,and cytocompatibility,and it supported a robust deposition of collagenⅡand aggrecan by chondrocytes after printing.This work provides a versatile strategy for balancing the biocompatibility and mechanical robustness in bioinks,offering a promising platform for next-generation cartilage tissue engineering scaffolds.展开更多
In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrabilit...In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.展开更多
Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current method...Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current methods,however,are complicated and time-consuming,the mass production remains a chal-lenge.Herein,we proposed a new high-efficiency strategy for synthesis of MMB_(2)using molten aluminum as the medium for the first time.The prepared Al-containing multi-component borides(TiZrHfNbTa)B_(2)microcrystals had a homogeneous composition with a hexagonal AlB_(2)structure and ultra-high hardness value of∼35.3 GPa,which was much higher than data reported in the literature and the rule of mix-ture estimations.Furthermore,combined with the First-principles calculation results,we found that the Poisson’s ratio(v)values exhibit a clearly ascending trend from 0.17 at VEC=3.5 to 0.18 at VEC=3.4,then to 0.201 at VEC=3.2 with the increasing of Al content.This indicates that the intrinsic toughness of multi-component boride microcrystals is obviously enhanced by the trace-doped Al elements.Besides,the fabricated Al-containing multi-component boride microcrystals have superior oxidation activation en-ergy and structural stability.The enhanced oxidation resistance is mainly attributed to the formation of a protective Al2 O3 oxide layer and the lattice distortion,both of which lead to sluggish diffusion of O_(2).These findings propose a new unexplored avenue for the fabrication of MMB_(2)materials with supe-rior comprehensive performance including ultra-hardness and intrinsically improved thermo-mechanical properties.展开更多
This reviewpresents a comprehensive technical analysis of deep learning(DL)methodologies in biomedical signal processing,focusing on architectural innovations,experimental validation,and evaluation frameworks.We syste...This reviewpresents a comprehensive technical analysis of deep learning(DL)methodologies in biomedical signal processing,focusing on architectural innovations,experimental validation,and evaluation frameworks.We systematically evaluate key deep learning architectures including convolutional neural networks(CNNs),recurrent neural networks(RNNs),transformer-based models,and hybrid systems across critical tasks such as arrhythmia classification,seizure detection,and anomaly segmentation.The study dissects preprocessing techniques(e.g.,wavelet denoising,spectral normalization)and feature extraction strategies(time-frequency analysis,attention mechanisms),demonstrating their impact on model accuracy,noise robustness,and computational efficiency.Experimental results underscore the superiority of deep learning over traditional methods,particularly in automated feature extraction,real-time processing,cross-modal generalization,and achieving up to a 15%increase in classification accuracy and enhanced noise resilience across electrocardiogram(ECG),electroencephalogram(EEG),and electromyogram(EMG)signals.Performance is rigorously benchmarked using precision,recall,F1-scores,area under the receiver operating characteristic curve(AUC-ROC),and computational complexitymetrics,providing a unified framework for comparing model efficacy.Thesurvey addresses persistent challenges:synthetic data generationmitigates limited training samples,interpretability tools(e.g.,Gradient-weighted Class Activation Mapping(Grad-CAM),Shapley values)resolve model opacity,and federated learning ensures privacy-compliant deployments.Distinguished from prior reviews,this work offers a structured taxonomy of deep learning architectures,integrates emerging paradigms like transformers and domain-specific attention mechanisms,and evaluates preprocessing pipelines for spectral-temporal trade-offs.It advances the field by bridging technical advancements with clinical needs,such as scalability in real-world settings(e.g.,wearable devices)and regulatory alignment with theHealth Insurance Portability and Accountability Act(HIPAA)and General Data Protection Regulation(GDPR).By synthesizing technical rigor,ethical considerations,and actionable guidelines for model selection,this survey establishes a holistic reference for developing robust,interpretable biomedical artificial intelligence(AI)systems,accelerating their translation into personalized and equitable healthcare solutions.展开更多
Ca^(2+)signaling plays crucial roles in plant stress responses,including defense against insects.To counteract insect feeding,different parts of a plant deploy systemic signaling to communicate and coordinate defense ...Ca^(2+)signaling plays crucial roles in plant stress responses,including defense against insects.To counteract insect feeding,different parts of a plant deploy systemic signaling to communicate and coordinate defense responses,but little is known about the underlying mechanisms.In this study,micrografting,in vivo imaging of Ca^(2+)and reactive oxygen species(ROS),quantification of jasmonic acid(JA)and defensive metabolites,and bioassay were used to study how Arabidopsis seedlings regulate systemic responses in leaves after hypocotyls are wounded.We show that wounding hypocotyls rapidly activated both Ca^(2+)and ROS signals in leaves.RBOHD,which functions to produce ROS,along with two glutamate receptors GLR3.3 and GLR3.6,but not individually RBOHD or GLR3.3 and GLR3.6,in hypocotyls regulate the dynamics of systemic Ca^(2+)signals in leaves.In line with the systemic Ca^(2+)signals,after wounding hypocotyl,RBOHD,GLR3.3,and GLR3.6 in hypocotyl also cooperatively regulate the transcriptome,hormone jasmonic acid,and defensive secondary metabolites in leaves of Arabidopsis seedlings,thus controlling the systemic resistance to insects.Unlike leaf-to-leaf systemic signaling,this study reveals the unique regulation of wounding-induced hypocotyl-to-leaf systemic signaling and sheds new light on how different plant organs use complex signaling pathways to modulate defense responses.展开更多
Non-cooperative communication detection is a key technology for locating radio interfer-ence sources and conducting reconnaissance on adversary radiation sources.To meet the require-ments of wide-area monitoring,a sin...Non-cooperative communication detection is a key technology for locating radio interfer-ence sources and conducting reconnaissance on adversary radiation sources.To meet the require-ments of wide-area monitoring,a single interception channel often contains mixed multi-source sig-nals and interference,resulting in generally low signal-to-noise ratio(SNR)of the received signals;meanwhile,improving detection quality urgently requires either high frequency resolution or high-time resolution,which poses severe challenges to detection techniques based on time-frequency rep-resentations(TFR).To address this issue,this paper proposes a fixed-frame-structure signal detec-tion algorithm that integrates image enhancement and multi-scale template matching:first,the Otsu-Sauvola hybrid thresholding algorithm is employed to enhance TFR features,suppress noise interference,and extract time-frequency parameters of potential target signals(such as bandwidth and occurrence time);then,by exploiting the inherent time-frequency characteristics of the fixed-frame structure,the signal is subjected to multi-scale transformation(with either high-frequency resolution or high-time resolution),and accurate detection is achieved through the corresponding multi-scale template matching.Experimental results demonstrate that under 0 dB SNR conditions,the proposed algorithm achieves a detection rate greater than 87%,representing a significant improvement over traditional methods.展开更多
The hardening mechanism of multi-component carbide ceramic has been investigated in detail through a combination of experiments,first-principles calculations,and ab initio molecular dynamics(AIMD).Eight dense carbide ...The hardening mechanism of multi-component carbide ceramic has been investigated in detail through a combination of experiments,first-principles calculations,and ab initio molecular dynamics(AIMD).Eight dense carbide ceramics were prepared by spark plasma sintering.Compulsorily,all the multi-component carbide samples have similar carbon content,grain size,and uniform compositional distribution by optimizing the sintering process and adjusting the initial raw materials.Hence the interference of other factors on the hardness of multi-component carbide ceramics is minimized.The effects of changes in the elemental species on the lattice distortion,bond strength,bonding properties,and electronic structure of multi-component carbide ceramics were thoroughly analyzed.These results show that the hardening of multi-component carbide ceramic can be attributed to the coupling of solid solution strengthening caused by lattice distortion and covalent bond strengthening.Besides,the“host lattice”of multi-component carbide ceramics is defined based on the concept of supporting lattice.The present work is of great significance for a deeper understanding of the hardening mechanism of multi-component carbide ceramics and the design of superhard multi-component carbides.展开更多
A convenient photocatalytic multi-component reaction of alkenes,quinoxalin-2(1H)-ones,and diazo compounds has been developed in the presence of water.A number of ester-containing quinoxalin-2(1H)-ones could be efficie...A convenient photocatalytic multi-component reaction of alkenes,quinoxalin-2(1H)-ones,and diazo compounds has been developed in the presence of water.A number of ester-containing quinoxalin-2(1H)-ones could be efficiently obtained in moderate to good yields at room temperature.This metal-free visiblelight-driven tandem reaction was conducted through proton-coupled electron transfer(PCET)process using water as the hydrogen donor and 1,2,3,5-tetrakis(carbazol-9-yl)-4,6-dicyanobenzene(4CzIPN)as the photocatalyst.展开更多
Traditionally,a continuous-wave(CW)signal is used to simulate RF circuits during the design procedure,while the fabricated circuits are measured by modulated signals in the test phase,because modulated signals are use...Traditionally,a continuous-wave(CW)signal is used to simulate RF circuits during the design procedure,while the fabricated circuits are measured by modulated signals in the test phase,because modulated signals are used in reality.It is almost impossible to use a CW signal to predict system performances,such as error vector magnitude(EVM),bit error rate(BER),etc.,of a transceiver front-end when dealing with complex modulated signals.This paper develops an integrated system evaluation engine(ISEE)to evaluate the system performances of a transceiver front-end or its sub-circuits.This crossdomain simulation platform is based on Matlab,advanced design system(ADS),and Cadence simulators to link the baseband signals and transceiver frond-end.An orthogonal frequency division multiplex(OFDM)modem is implemented in Matlab for evaluating the system performances.The modulated baseband signal from Matlab is dynamically fed into ADS,which includes transceiver front-end for co-simulation.The sub-block circuits of the transceiver front-end can be implemented using ADS and Cadence simulators.After system-level circuit simulation in ADS,the output signal is dynamically delivered to Matlab for demodulation.To simplify the use of the co-simulation platform,a graphical user interface(GUI)is constructed using Matlab.The parameters of the OFDM signals can be easily reconfigured on the GUI to simulate RF circuits with different modulation schemes.To demonstrate the effectiveness of the ISEE,a 3.5 GHz power amplifier is simulated and characterized using 20 MHz 16-and 64-QAM OFDM signals.展开更多
The gravitational memory effect manifests gravitational nonlinearity,degenerate vacua,and asymptotic symmetries;its detection is considered challenging.We propose using a space-borne interferometer to detect memory si...The gravitational memory effect manifests gravitational nonlinearity,degenerate vacua,and asymptotic symmetries;its detection is considered challenging.We propose using a space-borne interferometer to detect memory signals from stellar-mass binary black holes(BBHs),typically targeted by ground-based detectors.We use DECIGO detector as an example.Over 5 years,DECIGO is estimated to detect approximately 2,036 memory signals(SNRs>3)from stellar-mass BBHs.Simulations used frequency-domain memory waveforms for direct SNR estimation.Predictions utilized a GWTC-3 constrained BBH population model(Power law+Peak mass,DEFAULT spin,Madau-Dickinson merger rate).The analysis used conservative lower merger rate limits and considered orbital eccentricity.The high detection rate stems from strong memory signals within DECIGO’s bandwidth and the abundance of stellar-mass BBHs.This substantial and conservative detection count enables statistical use of the memory effect for fundamental physics and astrophysics.DECIGO exemplifies that space interferometers may better detect memory signals from smaller mass binaries than their typical targets.Detectors in lower frequency bands are expected to find strong memory signals from∼10^(4)M⊙binaries.展开更多
This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting S...This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS).By analyzing this extensive pharmacovigilance database,the study aimed to offer meaningful insights for improving the clinical safety of eltrombopag in children.Data covering eltrombopag-related ADEs from Q12004 to Q42023 were extracted from FAERS,and signal detection was conducted using both the reporting odds ratio(ROR)and proportional reporting ratio(PRR)methods.ADEs were categorized based on the System Organ Class(SOC)classification in MedDRA version 25.0.A total of 582 reports involving pediatric patients receiving eltrombopag were identified,encompassing 21 SOC categories.The analysis revealed that,in addition to the known ADEs listed in the drug label,clinicians should remain vigilant for potential off-label ADE signals.These included abnormal platelet counts,thrombocytosis,antiphospholipid syndrome,myelofibrosis,reduced serum iron levels,myelodysplastic syndrome,hepatic infections,and other related conditions.Given these findings,it is strongly recommended that serum iron and ferritin levels should be routinely monitored in pediatric patients undergoing eltrombopag therapy,particularly during long-term treatment.Such proactive surveillance may help prevent the onset of iron deficiency anemia and enhance overall treatment safety.展开更多
There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are di...There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are difficult to discover unknown signals while recognizing known ones.In this paper,a compact manifold mixup feature-based open-set recognition approach(OR-CMMF)is proposed to address the above problem.First,the proposed approach utilizes the center loss to constrain decision boundaries so that it obtains the compact latent signal feature representations and extends the low-confidence feature space.Second,the latent signal feature representations are used to construct synthetic representations as substitutes for unknown categories of signals.Then,these constructed representations can occupy the extended low-confidence space.Finally,the proposed approach applies the distillation loss to adjust the decision boundaries between the known categories signals and the constructed unknown categories substitutes so that it accurately discovers unknown signals.The OR-CMMF approach outperformed other state-of-the-art open-set recognition methods in comprehensive recognition performance and running time,as demonstrated by simulation experiments on two public datasets RML2016.10a and ORACLE.展开更多
Terahertz(THz) and millimeter Wave(mmWave) have been considered as potential frequency bands for 6G cellular systems to meet the need of ultra-high data rates. However, indoor communications could be blocked in THz/mm...Terahertz(THz) and millimeter Wave(mmWave) have been considered as potential frequency bands for 6G cellular systems to meet the need of ultra-high data rates. However, indoor communications could be blocked in THz/mmW cellular systems due to the high free-space propagation loss. Deploying a large number of small base stations indoors has been considered as a promising solution for solving indoor coverage problems. However, base station dense deployment leads to a significant increase in system energy consumption. In this paper, we develop a novel ultra-efficient energy-saving mechanism with the aim of reducing energy consumption in 6G distributed indoor base station scenarios. Unlike the existing relevant protocol framework of 3GPP, which operates the cellular system based on constant system signaling messages(including cell ID, cell reselection information, etc.), the proposed mechanism eliminates the need for system messages. The intuition comes from the observation that the probability of having no users within the coverage area of an indoor base station is high, hence continuously sending system messages to guarantee the quality of service is unnecessary in indoor scenarios. Specifically, we design a dedicated beacon signal to detect whether there are users in the coverage area of the base station and switch off the main communication module when there are no active users for energy saving. The beacon frame structure is carefully designed based on the existing 3GPP specifications with minimal protocol modifications, and the protocol parameters involved are optimized. Simulation results show that the proposed mechanism can reduce the system energy from the order of tens of watts to the order of hundreds of milliwatts. Compared to traditional energy-saving schemes, the proposed mechanism achieves an average energy-saving gain of 58%, with a peak energy-saving gain of 90%.展开更多
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.
文摘This study presents a hybrid CNN-Transformer model for real-time recognition of affective tactile biosignals.The proposed framework combines convolutional neural networks(CNNs)to extract spatial and local temporal features with the Transformer encoder that captures long-range dependencies in time-series data through multi-head attention.Model performance was evaluated on two widely used tactile biosignal datasets,HAART and CoST,which contain diverse affective touch gestures recorded from pressure sensor arrays.TheCNN-Transformer model achieved recognition rates of 93.33%on HAART and 80.89%on CoST,outperforming existing methods on both benchmarks.By incorporating temporal windowing,the model enables instantaneous prediction,improving generalization across gestures of varying duration.These results highlight the effectiveness of deep learning for tactile biosignal processing and demonstrate the potential of theCNN-Transformer approach for future applications in wearable sensors,affective computing,and biomedical monitoring.
基金Supported by the National Natural Science Foundation of China under Grant No. 60572098.
文摘A classical time-varying signal, the multi-component Chirp signal has been widely used and the ability to estimate its instantaneous frequency （IF） is very useful. But in noisy environments, it is hard to estimate the 1F of a multi-component Chirp signal accurately. Wigner distribution maxima （WDM） are usually utilized for this estimation. But in practice, estimation bias increases when some points deviate from the true IF in high noise environments. This paper presents a new method of multi-component Chirp signal 1F estimation named Wigner Viterbi fit （WVF）, based on Wigner-Ville distribution （WVD） and the Viterbi algorithm. First, we transform the WVD of the Chirp signal into digital image, and apply the Viterbi algorithm to separate the components and estimate their IF. At last, we establish a linear model to fit the estimation results. Theoretical analysis and simulation results prove that this new method has high precision and better performance than WDM in high noise environments, and better suppression of interference and the edge effect. Compared with WDM, WVF can reduce the mean square error （MSE） by 50% when the signal to noise ration （SNR） is in the range of-15dB to -11dB. WVF is an effective and promising 1F estimation method.
基金Doctoral Programme Foundation of Institution of Higher Education of China.
文摘To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.
基金Sponsored by the National Natural Science Foundation of China (60232010 ,60572094)the National Science Foundation of China for Distin-guished Young Scholars (60625104)
文摘Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.
文摘Tumor stroma,or tumor microenvironment(TME),has been in the spotlight during recent years for its role in tumor development,growth,and metastasis.It consists of a myriad of elements,including tumor-associated macrophages,cancer-associated fibroblasts,a deregulated extracellular matrix,endothelial cells,and vascular vessels.The release of proinflammatory molecules,due to the inflamed microenvironment,such as cytokines and chemokines is found to play a pivotal role in progression of cancer and response to therapy.This review discusses the major key players and important chemical inflammatory signals released in the TME.Furthermore,the latest breakthroughs in cytokine-mediated crosstalk between immune cells and cancer cells have been highlighted.In addition,recent updates on alterations in cytokine signaling between chronic inflammation and malignant TME have also been reviewed.
文摘Chirp signals show energy aggregation in the fractional Fourier domain(FrFD) w hich can be used to estimate the parameter of the signals. In this paper,a parameter estimation method for multi-component chirp signal w hich corrupted by w hite Gaussian noise is proposed based on the discrete fractional Fourier transform(DFrFT) and the differential evolution( DE) algorithm. The proposed algorithm uses the DE algorithm instead of the conventional fine search algorithm to detect the peak of the signals in the FrFD. The paper simulated the influence of the noise and the resolution of the proposed algorithm. The results of the simulation show the proposed method does not only improve the estimation accuracy of the peak coordinate,but also reduces time consuming.
基金supported by the Project(No.JCKY2024408C010)the Shanxi Province Key Research and Development Project(No.202302130501006)+4 种基金the National Natural Science Foundation of China(Nos.82403350,51975400,62031022)the Shanxi Provincial Key Medical Scientific Research Project(No.2020XM06)the Shanxi Provincial Basic Research Project(No.202103021223040)the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(No.2021L044)the Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering(No.2022SX-TD026),China.
文摘Hydrogels,owing to their porous network structure resembling the extracellular matrix(ECM),have become essential scaffold materials in the field of cartilage tissue engineering.Among them,gelatin methacrylate(GelMA)hydrogels are widely used in bioink development due to their excellent biocompatibility,biodegradability,and tunable photo-crosslinking properties.However,the high biocompatibility of pure GelMA often comes at the cost of mechanical strength,limiting its applicability in cartilage regeneration.To overcome this trade-off,this study developed composite bioinks based on GelMA,silk fibroin(SF),and polyethylene oxide(PEO)for fabricating porous hydrogel scaffolds,which were then systematically characterized in terms of morphology,porosity,hydrophilicity,mechanical strength,rheological behavior,printability,and cytocompatibility.In this design,PEO serves as a porogen to generate highly porous structures(porosity up to 88%),while SF compensates for the mechanical loss caused by PEO,enabling the scaffold to retain a compression strength of up to 29.10 kPa.Among the tested formulations,the 10%GelMA/1%SF/1.5%PEO(1%=0.01 g/mL)bioink exhibited excellent printability,mechanical integrity,and cytocompatibility,and it supported a robust deposition of collagenⅡand aggrecan by chondrocytes after printing.This work provides a versatile strategy for balancing the biocompatibility and mechanical robustness in bioinks,offering a promising platform for next-generation cartilage tissue engineering scaffolds.
基金sponsored by the National Natural Science Foundations of China under Grant Nos.12301315,12235007,11975131the Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ20A010009。
文摘In the realm of nonlinear integrable systems,the presence of decompositions facilitates the establishment of linear superposition solutions and the derivation of novel coupled systems exhibiting nonlinear integrability.By focusing on single-component decompositions within the potential BKP hierarchy,it has been observed that specific linear superpositions of decomposition solutions remain consistent with the underlying equations.Moreover,through the implementation of multi-component decompositions within the potential BKP hierarchy,successful endeavors have been undertaken to formulate linear superposition solutions and novel coupled Kd V-type systems that resist decoupling via alterations in dependent variables.
基金financially supported by the National Natural Science Foundation of China(Nos.52271033 and 52071179)the Key program of National Natural Science Foundation of China(No.51931003)+2 种基金Natural Science Foundation of Jiangsu Province,China(No.BK20221493)Jiangsu Province Leading Edge Technology Basic Research Major Project(No.BK20222014)Foundation of“Qinglan Project”for Colleges and Universities in Jiangsu Province.
文摘Multi-component transition group metal borides(MMB_(2))have become a research hotspot due to their new composition design concepts and superior properties compared with conventional ceramics.Most of the current methods,however,are complicated and time-consuming,the mass production remains a chal-lenge.Herein,we proposed a new high-efficiency strategy for synthesis of MMB_(2)using molten aluminum as the medium for the first time.The prepared Al-containing multi-component borides(TiZrHfNbTa)B_(2)microcrystals had a homogeneous composition with a hexagonal AlB_(2)structure and ultra-high hardness value of∼35.3 GPa,which was much higher than data reported in the literature and the rule of mix-ture estimations.Furthermore,combined with the First-principles calculation results,we found that the Poisson’s ratio(v)values exhibit a clearly ascending trend from 0.17 at VEC=3.5 to 0.18 at VEC=3.4,then to 0.201 at VEC=3.2 with the increasing of Al content.This indicates that the intrinsic toughness of multi-component boride microcrystals is obviously enhanced by the trace-doped Al elements.Besides,the fabricated Al-containing multi-component boride microcrystals have superior oxidation activation en-ergy and structural stability.The enhanced oxidation resistance is mainly attributed to the formation of a protective Al2 O3 oxide layer and the lattice distortion,both of which lead to sluggish diffusion of O_(2).These findings propose a new unexplored avenue for the fabrication of MMB_(2)materials with supe-rior comprehensive performance including ultra-hardness and intrinsically improved thermo-mechanical properties.
基金The Natural Sciences and Engineering Research Council of Canada(NSERC)funded this review study.
文摘This reviewpresents a comprehensive technical analysis of deep learning(DL)methodologies in biomedical signal processing,focusing on architectural innovations,experimental validation,and evaluation frameworks.We systematically evaluate key deep learning architectures including convolutional neural networks(CNNs),recurrent neural networks(RNNs),transformer-based models,and hybrid systems across critical tasks such as arrhythmia classification,seizure detection,and anomaly segmentation.The study dissects preprocessing techniques(e.g.,wavelet denoising,spectral normalization)and feature extraction strategies(time-frequency analysis,attention mechanisms),demonstrating their impact on model accuracy,noise robustness,and computational efficiency.Experimental results underscore the superiority of deep learning over traditional methods,particularly in automated feature extraction,real-time processing,cross-modal generalization,and achieving up to a 15%increase in classification accuracy and enhanced noise resilience across electrocardiogram(ECG),electroencephalogram(EEG),and electromyogram(EMG)signals.Performance is rigorously benchmarked using precision,recall,F1-scores,area under the receiver operating characteristic curve(AUC-ROC),and computational complexitymetrics,providing a unified framework for comparing model efficacy.Thesurvey addresses persistent challenges:synthetic data generationmitigates limited training samples,interpretability tools(e.g.,Gradient-weighted Class Activation Mapping(Grad-CAM),Shapley values)resolve model opacity,and federated learning ensures privacy-compliant deployments.Distinguished from prior reviews,this work offers a structured taxonomy of deep learning architectures,integrates emerging paradigms like transformers and domain-specific attention mechanisms,and evaluates preprocessing pipelines for spectral-temporal trade-offs.It advances the field by bridging technical advancements with clinical needs,such as scalability in real-world settings(e.g.,wearable devices)and regulatory alignment with theHealth Insurance Portability and Accountability Act(HIPAA)and General Data Protection Regulation(GDPR).By synthesizing technical rigor,ethical considerations,and actionable guidelines for model selection,this survey establishes a holistic reference for developing robust,interpretable biomedical artificial intelligence(AI)systems,accelerating their translation into personalized and equitable healthcare solutions.
基金National Natural Science Foundation of China(U23A20199)Yunnan Revitalization Talent Support Program“Yunling Scholar”and Yunnan Fundamental Research Projects(202201AS070056)。
文摘Ca^(2+)signaling plays crucial roles in plant stress responses,including defense against insects.To counteract insect feeding,different parts of a plant deploy systemic signaling to communicate and coordinate defense responses,but little is known about the underlying mechanisms.In this study,micrografting,in vivo imaging of Ca^(2+)and reactive oxygen species(ROS),quantification of jasmonic acid(JA)and defensive metabolites,and bioassay were used to study how Arabidopsis seedlings regulate systemic responses in leaves after hypocotyls are wounded.We show that wounding hypocotyls rapidly activated both Ca^(2+)and ROS signals in leaves.RBOHD,which functions to produce ROS,along with two glutamate receptors GLR3.3 and GLR3.6,but not individually RBOHD or GLR3.3 and GLR3.6,in hypocotyls regulate the dynamics of systemic Ca^(2+)signals in leaves.In line with the systemic Ca^(2+)signals,after wounding hypocotyl,RBOHD,GLR3.3,and GLR3.6 in hypocotyl also cooperatively regulate the transcriptome,hormone jasmonic acid,and defensive secondary metabolites in leaves of Arabidopsis seedlings,thus controlling the systemic resistance to insects.Unlike leaf-to-leaf systemic signaling,this study reveals the unique regulation of wounding-induced hypocotyl-to-leaf systemic signaling and sheds new light on how different plant organs use complex signaling pathways to modulate defense responses.
文摘Non-cooperative communication detection is a key technology for locating radio interfer-ence sources and conducting reconnaissance on adversary radiation sources.To meet the require-ments of wide-area monitoring,a single interception channel often contains mixed multi-source sig-nals and interference,resulting in generally low signal-to-noise ratio(SNR)of the received signals;meanwhile,improving detection quality urgently requires either high frequency resolution or high-time resolution,which poses severe challenges to detection techniques based on time-frequency rep-resentations(TFR).To address this issue,this paper proposes a fixed-frame-structure signal detec-tion algorithm that integrates image enhancement and multi-scale template matching:first,the Otsu-Sauvola hybrid thresholding algorithm is employed to enhance TFR features,suppress noise interference,and extract time-frequency parameters of potential target signals(such as bandwidth and occurrence time);then,by exploiting the inherent time-frequency characteristics of the fixed-frame structure,the signal is subjected to multi-scale transformation(with either high-frequency resolution or high-time resolution),and accurate detection is achieved through the corresponding multi-scale template matching.Experimental results demonstrate that under 0 dB SNR conditions,the proposed algorithm achieves a detection rate greater than 87%,representing a significant improvement over traditional methods.
基金financially supported by the National Natural Science Foundation of China(Nos.52032002,52372060,51972081,and U22A20128)the National Safety Academic Foundation(No.U2130103)+1 种基金the National Key Laboratory of Precision Hot Processing of Metals(No.61429092300305)Heilongjiang Touyan Team Program are gratefully acknowledged.
文摘The hardening mechanism of multi-component carbide ceramic has been investigated in detail through a combination of experiments,first-principles calculations,and ab initio molecular dynamics(AIMD).Eight dense carbide ceramics were prepared by spark plasma sintering.Compulsorily,all the multi-component carbide samples have similar carbon content,grain size,and uniform compositional distribution by optimizing the sintering process and adjusting the initial raw materials.Hence the interference of other factors on the hardness of multi-component carbide ceramics is minimized.The effects of changes in the elemental species on the lattice distortion,bond strength,bonding properties,and electronic structure of multi-component carbide ceramics were thoroughly analyzed.These results show that the hardening of multi-component carbide ceramic can be attributed to the coupling of solid solution strengthening caused by lattice distortion and covalent bond strengthening.Besides,the“host lattice”of multi-component carbide ceramics is defined based on the concept of supporting lattice.The present work is of great significance for a deeper understanding of the hardening mechanism of multi-component carbide ceramics and the design of superhard multi-component carbides.
基金supported by Sichuan Science and Technology Program(No.2023NSFSC0101)the 2024 Provincial platform project of Chengdu Normal University(No.GNFZ202404)+1 种基金Natural Science Foundation of Shandong Province(No.ZR2021MB065)National Natural Science Foundation of China(No.22101237)。
文摘A convenient photocatalytic multi-component reaction of alkenes,quinoxalin-2(1H)-ones,and diazo compounds has been developed in the presence of water.A number of ester-containing quinoxalin-2(1H)-ones could be efficiently obtained in moderate to good yields at room temperature.This metal-free visiblelight-driven tandem reaction was conducted through proton-coupled electron transfer(PCET)process using water as the hydrogen donor and 1,2,3,5-tetrakis(carbazol-9-yl)-4,6-dicyanobenzene(4CzIPN)as the photocatalyst.
基金supported by the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone(No.HZQB-KCZYB-2020083).
文摘Traditionally,a continuous-wave(CW)signal is used to simulate RF circuits during the design procedure,while the fabricated circuits are measured by modulated signals in the test phase,because modulated signals are used in reality.It is almost impossible to use a CW signal to predict system performances,such as error vector magnitude(EVM),bit error rate(BER),etc.,of a transceiver front-end when dealing with complex modulated signals.This paper develops an integrated system evaluation engine(ISEE)to evaluate the system performances of a transceiver front-end or its sub-circuits.This crossdomain simulation platform is based on Matlab,advanced design system(ADS),and Cadence simulators to link the baseband signals and transceiver frond-end.An orthogonal frequency division multiplex(OFDM)modem is implemented in Matlab for evaluating the system performances.The modulated baseband signal from Matlab is dynamically fed into ADS,which includes transceiver front-end for co-simulation.The sub-block circuits of the transceiver front-end can be implemented using ADS and Cadence simulators.After system-level circuit simulation in ADS,the output signal is dynamically delivered to Matlab for demodulation.To simplify the use of the co-simulation platform,a graphical user interface(GUI)is constructed using Matlab.The parameters of the OFDM signals can be easily reconfigured on the GUI to simulate RF circuits with different modulation schemes.To demonstrate the effectiveness of the ISEE,a 3.5 GHz power amplifier is simulated and characterized using 20 MHz 16-and 64-QAM OFDM signals.
基金supported by the National Natural Science Foundation of China(Grant Nos.11633001,11920101003,and 12205222 for S.H.)the Key Program of the National Natural Science Foundation of China(Grant No.12433001)+1 种基金the Strate-gic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB23000000)the National Key Research and Development Program of China(Grant No.2021YFC2203001 for Z.C.Z.).
文摘The gravitational memory effect manifests gravitational nonlinearity,degenerate vacua,and asymptotic symmetries;its detection is considered challenging.We propose using a space-borne interferometer to detect memory signals from stellar-mass binary black holes(BBHs),typically targeted by ground-based detectors.We use DECIGO detector as an example.Over 5 years,DECIGO is estimated to detect approximately 2,036 memory signals(SNRs>3)from stellar-mass BBHs.Simulations used frequency-domain memory waveforms for direct SNR estimation.Predictions utilized a GWTC-3 constrained BBH population model(Power law+Peak mass,DEFAULT spin,Madau-Dickinson merger rate).The analysis used conservative lower merger rate limits and considered orbital eccentricity.The high detection rate stems from strong memory signals within DECIGO’s bandwidth and the abundance of stellar-mass BBHs.This substantial and conservative detection count enables statistical use of the memory effect for fundamental physics and astrophysics.DECIGO exemplifies that space interferometers may better detect memory signals from smaller mass binaries than their typical targets.Detectors in lower frequency bands are expected to find strong memory signals from∼10^(4)M⊙binaries.
文摘This study sought to investigate adverse drug event(ADE)signals associated with eltrombopag use in pediatric patients aged 0–18 years,utilizing data from the U.S.Food and Drug Administration Adverse Event Reporting System(FAERS).By analyzing this extensive pharmacovigilance database,the study aimed to offer meaningful insights for improving the clinical safety of eltrombopag in children.Data covering eltrombopag-related ADEs from Q12004 to Q42023 were extracted from FAERS,and signal detection was conducted using both the reporting odds ratio(ROR)and proportional reporting ratio(PRR)methods.ADEs were categorized based on the System Organ Class(SOC)classification in MedDRA version 25.0.A total of 582 reports involving pediatric patients receiving eltrombopag were identified,encompassing 21 SOC categories.The analysis revealed that,in addition to the known ADEs listed in the drug label,clinicians should remain vigilant for potential off-label ADE signals.These included abnormal platelet counts,thrombocytosis,antiphospholipid syndrome,myelofibrosis,reduced serum iron levels,myelodysplastic syndrome,hepatic infections,and other related conditions.Given these findings,it is strongly recommended that serum iron and ferritin levels should be routinely monitored in pediatric patients undergoing eltrombopag therapy,particularly during long-term treatment.Such proactive surveillance may help prevent the onset of iron deficiency anemia and enhance overall treatment safety.
基金fully supported by National Natural Science Foundation of China(61871422)Natural Science Foundation of Sichuan Province(2023NSFSC1422)Central Universities of South west Minzu University(ZYN2022032)。
文摘There are all kinds of unknown and known signals in the actual electromagnetic environment,which hinders the development of practical cognitive radio applications.However,most existing signal recognition models are difficult to discover unknown signals while recognizing known ones.In this paper,a compact manifold mixup feature-based open-set recognition approach(OR-CMMF)is proposed to address the above problem.First,the proposed approach utilizes the center loss to constrain decision boundaries so that it obtains the compact latent signal feature representations and extends the low-confidence feature space.Second,the latent signal feature representations are used to construct synthetic representations as substitutes for unknown categories of signals.Then,these constructed representations can occupy the extended low-confidence space.Finally,the proposed approach applies the distillation loss to adjust the decision boundaries between the known categories signals and the constructed unknown categories substitutes so that it accurately discovers unknown signals.The OR-CMMF approach outperformed other state-of-the-art open-set recognition methods in comprehensive recognition performance and running time,as demonstrated by simulation experiments on two public datasets RML2016.10a and ORACLE.
基金supported by the National Natural Science Foundation of China under Grant No. 62201121the Fundamental Research Funds for Central Universities under Grant No. ZYGX2024XJ070.
文摘Terahertz(THz) and millimeter Wave(mmWave) have been considered as potential frequency bands for 6G cellular systems to meet the need of ultra-high data rates. However, indoor communications could be blocked in THz/mmW cellular systems due to the high free-space propagation loss. Deploying a large number of small base stations indoors has been considered as a promising solution for solving indoor coverage problems. However, base station dense deployment leads to a significant increase in system energy consumption. In this paper, we develop a novel ultra-efficient energy-saving mechanism with the aim of reducing energy consumption in 6G distributed indoor base station scenarios. Unlike the existing relevant protocol framework of 3GPP, which operates the cellular system based on constant system signaling messages(including cell ID, cell reselection information, etc.), the proposed mechanism eliminates the need for system messages. The intuition comes from the observation that the probability of having no users within the coverage area of an indoor base station is high, hence continuously sending system messages to guarantee the quality of service is unnecessary in indoor scenarios. Specifically, we design a dedicated beacon signal to detect whether there are users in the coverage area of the base station and switch off the main communication module when there are no active users for energy saving. The beacon frame structure is carefully designed based on the existing 3GPP specifications with minimal protocol modifications, and the protocol parameters involved are optimized. Simulation results show that the proposed mechanism can reduce the system energy from the order of tens of watts to the order of hundreds of milliwatts. Compared to traditional energy-saving schemes, the proposed mechanism achieves an average energy-saving gain of 58%, with a peak energy-saving gain of 90%.
