Background Cervical cancer is the only cancer that can be eliminated worldwide.Tracking the latest burden of cervical cancer is critical toward the targets set by World Health Organization(WHO)to eliminate cervical ca...Background Cervical cancer is the only cancer that can be eliminated worldwide.Tracking the latest burden of cervical cancer is critical toward the targets set by World Health Organization(WHO)to eliminate cervical cancer as a major public health problem.Methods All data were extracted from the Global Cancer Observatory(GLOBOCAN)2022.Age-standardized incidence rate(ASIR)and mortality rates(ASMR)of cervical cancer were compared and linked to Human Development Index(HDI)between populations.The estimated annual percentage changes(EAPCs)were used to characterize the temporal trend in ASIR/ASMR,and demographic estimates were projected up to 2050.Results Globally,an estimated 662,044 cases(ASIR:14.12/100,000)and 348,709 deaths(ASMR:7.08/100,000)from cervical cancer occurred in 2022,corresponding to the fourth cause of cancer morbidity and mortality in women worldwide.Specifically,42%of cases and 39%of deaths occurred in China(23%and 16%)and India(19%and 23%).Both ASIR and ASMR of cervical cancer decreased with HDI,and similar decreasing links were observed for both early-onset(0–39 years)and late-onset(≥40 years)cervical cancer.Both ASIR and ASMR of overall cervical cancer showed decreasing trends during 2003–2012(EAPC:0.04%and-1.03%);however,upward trends were observed for early-onset cervical cancer(EAPC:1.16%and 0.57%).If national rates in 2022 remain stable,the estimated cases and deaths from cervical cancer are projected to increase by 56.8%and 80.7%up to 2050.Moreover,the projected increase of early-onset cervical cancer is mainly observed in transitioning countries,while decreased burden is expected in transitioned countries.Conclusions Cervical cancer remains a common cause of cancer death in many countries,especially in transitioning countries.Unless scaling-up preventive interventions,human papillomavirus(HPV)vaccination and cervical cancer screening,as well as systematic cooperation within government,civil societies,and private enterprises,the global burden of cervical cancer would be expected to increase in the future.展开更多
Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude...Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.展开更多
Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Si...Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.展开更多
Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric ma...Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station...This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.展开更多
In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accurac...In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.展开更多
Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devi...Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.展开更多
Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smo...Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.展开更多
Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action...Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.展开更多
The online version of the original article can be found at:https://www.sciopen.com/article/10.26599/JOTO.2025.9540018 Erratum to Journal of Otology,2025,20(2):123-126.https://doi.org/10.26599/JOTO.2025.9540018 The sur...The online version of the original article can be found at:https://www.sciopen.com/article/10.26599/JOTO.2025.9540018 Erratum to Journal of Otology,2025,20(2):123-126.https://doi.org/10.26599/JOTO.2025.9540018 The surnames and given names of these authors are reversed:Saro-Buendía Miguel,Andresen-Lorca Belén,Pérez-García Alberto,Llópez Carratala Nacho,Carreres Polo Joan,Armengot Carceller Miguel,Perolada Valmaña Jose María.It should be Miguel Saro-Buendía,Belén Andresen-Lorca,Alberto Pérez-García,Nacho Llópez Carratala,Joan Carreres Polo,Miguel Armengot Carceller,Jose María Perolada Valmaña.展开更多
Background Given the relatively unfavorable prognosis and significant geographic differences in lung cancer burden,it is critical to update the global landscape of lung cancer to inform local strategies.Methods Based ...Background Given the relatively unfavorable prognosis and significant geographic differences in lung cancer burden,it is critical to update the global landscape of lung cancer to inform local strategies.Methods Based on the GLOBOCAN 2022,the age-standardized incidence rate(ASIR)and mortality rate(ASMR)were compared and linked to the Human Development Index(HDI)across different populations.The temporal trends in ASIR/ASMR were characterized as estimated annual percentage change(EAPC),and demographic projections were performed up to 2050.Results Globally,an estimated 2,480,675 cases and 1,817,469 deaths from lung cancer occurred in 2022.Both ASIR and ASMR of lung cancer varied widely by world region,with ASIR ranging from 2.06 to 39.38 per 100,000 and ASMR from 1.95 to 31.70 per 100,000.China alone accounted for>40%of cases and deaths worldwide.Both ASIR and ARMR of lung cancer increased with HDI(R2:0.54 and 0.47,all P values<0.001),regardless of gender.Based on available data,both ASIR during 2001–2010 and ASMR during 2001–2015 showed decreasing trends in males(EAPC:1.50%and−2.22%)but increasing trends in females(EAPC:1.08%and 0.07%).Similar trends in ASIR and ASMR were observed among the elder population(≥50 years);however,downward trends were observed in the younger population(<50 years).Alongside the aging and growth of the population,estimated cases and deaths from overall lung cancer would increase by 86.2%and 95.2%up to 2050 as compared with estimates in 2022,respectively.Notably,increased early-onset lung cancer was only observed in transitioning countries,while decreased early-onset lung cancer was observed in transitioned countries.Conclusion Lung cancer maintained as the leading cancer burden worldwide.Unless timely preventive interventions in tobacco mitigation,early screening,and precise treatment,the global lung cancer burden is expected to increase in the future,especially for transitioning countries.展开更多
Objectives:The prevalence of cyber-aggression is increasing worldwide,resulting in significant negative impacts on both perpetrators and victims.This study aimed to investigate the relationship between cyber-ostracism...Objectives:The prevalence of cyber-aggression is increasing worldwide,resulting in significant negative impacts on both perpetrators and victims.This study aimed to investigate the relationship between cyber-ostracism and cyber-aggression among college students,clarify the role of various types of rumination in this dynamic.Methods:A total of 1198 Chinese college students(67.4%female;mean age 20.78 years;SD=1.12)were recruited through cluster random sampling and completed the Cyber-ostracism Experience Scale(COES),Positive and Negative Rumination Scale(PANRS),and Adolescent Online Aggression Behavior Scale(AOABS).Thestructural equation model(SEM)was employed to examine the relationship between cyber-ostracism,negative rumination,and cyber-aggression,as well as the moderating effect of positive rumination.Results:The results indicate that cyber-ostracism(β=0.128,p<0.001)positively predicts cyber-aggression.Negative ruminationmediates this relationship(effect size=0.027,95%CI=[0.007,0.014]).Positive rumination moderates the direct effect of cyber-ostracism on cyber-aggression(β=0.103,p<0.001).It alsomoderates both the first half(β=0.148,p<0.001)and the second half(β=0.138,p<0.001)of themediating pathway.Conclusion:This study suggests that cyber-ostracism influences cyber-aggression through negative rumination among Chinese college students.Positive rumination moderates this effect,although its impact is relatively limited.These findings offer valuable guidance for preventing and intervening in cyber-aggression among college students.展开更多
Osteoradionecrosis of the temporal bone(ORN-TB)is usually controlled with conservative measures.However,a temporal bone resection may be required in unresponsive cases.The reconstruction of the resulting defects may b...Osteoradionecrosis of the temporal bone(ORN-TB)is usually controlled with conservative measures.However,a temporal bone resection may be required in unresponsive cases.The reconstruction of the resulting defects may be challenging because of the radiation damage to regional tissues.As a result,distant free flaps may be an optimal choice.For instance,the gracilis muscular free flap(GMFF)has consistent vascular anatomy and can be used to reconstruct small defects.We report three cases of uncontrolled ORN-TB requiring an extensive temporal bone resection followed by vascularized obliteration with a GMFF.The patients reported complete control of the main otologic symptoms(otorrhea,otalgia,and aural fullness)and optimal functional and aesthetic outcomes.Finally,the patients reported significant improvement in quality of life despite early postoperative complications.To our knowledge,the GMFF had not been used to obliterate temporal bone defects in patients with ORN-TB.展开更多
Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on ...Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on a four-wave mixing(FWM)time lens and constructed a full quantum theoretical model for the resulting temporal SU(1,1)interferometer.This interferometer has high temporal resolution,can impose interference in both time and frequency domains,and is sensitive to the phase derivative.By introducing linear time-varying phase modulation,we achieved sub-picosecond precision in temporal autocorrelation measurements and generatedan optical frequency comb with a fixed interval based on a feedback iteration mechanism.Theoretical analysis revealsthe crucial regulatory role of time-frequency coupling in quantum interference,providing novel solutions for ultrafast quantum imaging,temporal mode encoding,and the generation of optical frequency quantization.展开更多
Birdsong is an important secondary sexual trait which may vary between but also within species.Intraspecific variation is generally studied either on the geographical or on the temporal scale;most of the studies explo...Birdsong is an important secondary sexual trait which may vary between but also within species.Intraspecific variation is generally studied either on the geographical or on the temporal scale;most of the studies exploring the variation of song over time,however,focused on species with rather simple songs.In this study,we explored the temporal changes in song of a complex songster,the Thrush Nightingale(Luscinia luscinia),recorded after 33 years(in 1986 and 2019)at the same locality in south-eastern Finland.Our analysis revealed a complete turnover of song types over the study period,with no song type shared between the two recording years.In contrast,40%of the originally recorded syllable types were still found in the repertoires of recently recorded males.Their song type repertoires were significantly smaller but the songs themselves were on average longer compared to the 1986 recordings.Repertoires of both syllables and song types were more shared between males recorded in 1986 than between those from 2019.We discuss the processes that may have contributed to these temporal changes in song and call for more detailed studies of song evolution in wild populations.展开更多
Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications(ASMs),a condition known as pharmacoresistant epilepsy.The management of pharmacoresistant epilepsy remains an intract...Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications(ASMs),a condition known as pharmacoresistant epilepsy.The management of pharmacoresistant epilepsy remains an intractable issue in the clinic.Its early prediction is important for prevention and diagnosis.However,it still lacks effective predictors and approaches.Here,a classical model of pharmacoresistant temporal lobe epilepsy(TLE)was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats.Ictal electroencephalograms(EEGs)recorded before phenytoin treatment were analyzed.Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats,a convolutional neural network predictive model was constructed to predict pharmacoresistance,and achieved 78% prediction accuracy.We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power,which was verified in seizure EEGs from pharmacoresistant TLE patients.Prospectively,therapies targeting the subiculum in those predicted as“pharmacoresistant”individual rats significantly reduced the subsequent occurrence of pharmacoresistance.These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model.This may be of translational importance for the precise management of pharmacoresistant TLE.展开更多
Brain lesions,such as those caused by stroke or traumatic brain injury(TBI),frequently result in persistent motor and cognitive impairments that significantly affect the individual patient's quality of life.Despit...Brain lesions,such as those caused by stroke or traumatic brain injury(TBI),frequently result in persistent motor and cognitive impairments that significantly affect the individual patient's quality of life.Despite differences in the mechanisms of injury,both conditions share a high prevalence of motor and cognitive impairments.These deficits show only limited natural recovery.展开更多
Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy t...Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.展开更多
基金supported by the National Key R&D Program of China(grant number:2021YFC2500400)National Natural Science Foundation of China(grant numbers:82172894,82073028,82204121)China Postdoctoral Science Foundation(grant number:2023M742617).
文摘Background Cervical cancer is the only cancer that can be eliminated worldwide.Tracking the latest burden of cervical cancer is critical toward the targets set by World Health Organization(WHO)to eliminate cervical cancer as a major public health problem.Methods All data were extracted from the Global Cancer Observatory(GLOBOCAN)2022.Age-standardized incidence rate(ASIR)and mortality rates(ASMR)of cervical cancer were compared and linked to Human Development Index(HDI)between populations.The estimated annual percentage changes(EAPCs)were used to characterize the temporal trend in ASIR/ASMR,and demographic estimates were projected up to 2050.Results Globally,an estimated 662,044 cases(ASIR:14.12/100,000)and 348,709 deaths(ASMR:7.08/100,000)from cervical cancer occurred in 2022,corresponding to the fourth cause of cancer morbidity and mortality in women worldwide.Specifically,42%of cases and 39%of deaths occurred in China(23%and 16%)and India(19%and 23%).Both ASIR and ASMR of cervical cancer decreased with HDI,and similar decreasing links were observed for both early-onset(0–39 years)and late-onset(≥40 years)cervical cancer.Both ASIR and ASMR of overall cervical cancer showed decreasing trends during 2003–2012(EAPC:0.04%and-1.03%);however,upward trends were observed for early-onset cervical cancer(EAPC:1.16%and 0.57%).If national rates in 2022 remain stable,the estimated cases and deaths from cervical cancer are projected to increase by 56.8%and 80.7%up to 2050.Moreover,the projected increase of early-onset cervical cancer is mainly observed in transitioning countries,while decreased burden is expected in transitioned countries.Conclusions Cervical cancer remains a common cause of cancer death in many countries,especially in transitioning countries.Unless scaling-up preventive interventions,human papillomavirus(HPV)vaccination and cervical cancer screening,as well as systematic cooperation within government,civil societies,and private enterprises,the global burden of cervical cancer would be expected to increase in the future.
文摘Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.
基金supported by the Humanities and Social Sciences Project of the Ministry of Education of the Peoples Republic(No.21YJCZH099)the National Natural Science Foundation of China(Nos.41401089 and 41741014)the Science and Technology Project of Sichuan Province(No.2023NSFSC1979).
文摘Majority of carbon emissions originate from fossil energy consumption,thus necessitating calculation and monitoring of carbon emissions from energy consumption.In this study,we utilized energy consumption data from Sichuan Province and Chongqing Municipality for the years 2000 to 2019 to estimate their statistical carbon emissions.We then employed nighttime light data to downscale and infer the spatial distribution of carbon emissions at the county level within the Chengdu-Chongqing urban agglomeration.Furthermore,we analyzed the spatial pattern of carbon emissions at the county level using the coefficient of variation and spatial autocorrelation,and we used the Geographically and Temporally Weighted Regression(GTWR)model to analyze the influencing factors of carbon emissions at this scale.The results of this study are as follows:(1)from 2000 to 2019,the overall carbon emissions in the Chengdu-Chongqing urban agglomeration showed an increasing trend followed by a decrease,with an average annual growth rate of 4.24%.However,in recent years,it has stabilized,and 2012 was the peak year for carbon emissions in the Chengdu-Chongqing urban agglomeration;(2)carbon emissions exhibited significant spatial clustering,with high-high clustering observed in the core urban areas of Chengdu and Chongqing and low-low clustering in the southern counties of the Chengdu-Chongqing urban agglomeration;(3)factors such as GDP,population(Pop),urbanization rate(Ur),and industrialization structure(Ic)all showed a significant influence on carbon emissions;(4)the spatial heterogeneity of each influencing factor was evident.
基金supported by funds from the Ministry of Science and Technology of the People's Republic of China(No.2019YFA0708603)NSFC(Nos.41973050,42288201,41930215)the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)(No.GML2019ZD0202)。
文摘Mineralogical data are presented for the peridotite xenoliths from Miocene(~19 Ma)Qingyuan basalts in the eastern North China Craton(NCC),with the aim of constraining on property of the sub-continental lithospheric mantle(SCLM)beneath the northern Tan-Lu fault zone(TLFZ)during the Cenozoic.The Qingyuan peridotites are dominated by spinel lherzolites with moderate-Mg^(#)olivines(89.4 to 91.2),suggesting that the regional SCLM is mainly transitional and fertile.Light rare earth element(LREE)-depleted,slightly depleted and enriched clinopyroxenes(Cpx)are identified in different peridotites.Chemical compositions of the LREE-enriched Cpx and the presence of phlogopite suggest that the Qingyuan SCLM has experienced silicate-related metasomatism.The synthesis of available mineral chemical data of the mantle xenoliths across the NCC confirms the SCLM beneath the NCC is highly heterogeneous in time and space.The Mesozoic–Cenozoic SCLM beneath the TLFZ and neighboring regions are more fertile and thinner than that beneath the region away from the fault zone.The fertile and refractory peridotite xenoliths experienced varying degrees of silicate and carbonatite metasomatism,respectively.The spatial-temporal lithospheric mantle heterogeneity in composition,age and thickness suggest that the trans-lithosphere fault zone played an important role in heterogeneous replacement of refractory cratonic lithospheric mantle.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
基金The National Key Research and Development Program of China(No.2022YFC3800201).
文摘This study examined the influence of the built environment surrounding rail stations on rail transit ridership and its spatiotemporal variations,aiming to enhance rail transit operational efficiency and inform station planning and development.Data from 159 metro stations in Nanjing,collected over a 14-d period,were analyzed to identify changes in weekday and weekend ridership patterns.The analysis included explanatory variables grouped into three categories:urban spatial variables,socioeconomic vari-ables,and transit service variables.A geographically and temporally weighted regression(GTWR)model was developed,and its performance was compared with that of ordinary least squares(OLS)and geographically weighted regression(GWR)models.The results demonstrated that the GTWR model outperformed others in analyzing the relationship between rail transit ridership and the built environment.In addition,the coefficients of explanatory variables showed significant variation across spatiotemporal dimensions,revealing distinct patterns.Notably,the influence of commuter flows led to more pronounced temporal heterogeneity in the coefficients observed on weekdays.These findings offer valuable insights for optimizing urban public transportation systems and advancing integrated urban rail development.
基金supported by the National Natural Science Foundation of China(62272049,62236006,62172045)the Key Projects of Beijing Union University(ZKZD202301).
文摘In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.
文摘Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.
基金supported by the National Key R&D Program of China(No.2018YFB1305200)the Natural Science Foundation of Zhejiang Province(No.LGG21F030011)。
文摘Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.
基金Shanghai Municipal Commission of Economy and Information Technology,China (No.202301054)。
文摘Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.
文摘The online version of the original article can be found at:https://www.sciopen.com/article/10.26599/JOTO.2025.9540018 Erratum to Journal of Otology,2025,20(2):123-126.https://doi.org/10.26599/JOTO.2025.9540018 The surnames and given names of these authors are reversed:Saro-Buendía Miguel,Andresen-Lorca Belén,Pérez-García Alberto,Llópez Carratala Nacho,Carreres Polo Joan,Armengot Carceller Miguel,Perolada Valmaña Jose María.It should be Miguel Saro-Buendía,Belén Andresen-Lorca,Alberto Pérez-García,Nacho Llópez Carratala,Joan Carreres Polo,Miguel Armengot Carceller,Jose María Perolada Valmaña.
基金supported by the National Key Research and Development Program of China(grant number:2021YFC2500400)Tianjin Health Committee Foundation(grant number:TJWJ2021MS008)+2 种基金Tianjin Key Medical Discipline(Specialty)Construction Project(grant number:TYXZDXK-009A)Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences(grant number:2023GLLH0132)Scientific Research Fund for the Demonstration Project of Public Hospital Reform and Quality Development(Gastrointestinal Tumour)that is approved by Peking University Cancer Hospital(Inner Mongolia Campus)(grant number:2023SGGZ068)。
文摘Background Given the relatively unfavorable prognosis and significant geographic differences in lung cancer burden,it is critical to update the global landscape of lung cancer to inform local strategies.Methods Based on the GLOBOCAN 2022,the age-standardized incidence rate(ASIR)and mortality rate(ASMR)were compared and linked to the Human Development Index(HDI)across different populations.The temporal trends in ASIR/ASMR were characterized as estimated annual percentage change(EAPC),and demographic projections were performed up to 2050.Results Globally,an estimated 2,480,675 cases and 1,817,469 deaths from lung cancer occurred in 2022.Both ASIR and ASMR of lung cancer varied widely by world region,with ASIR ranging from 2.06 to 39.38 per 100,000 and ASMR from 1.95 to 31.70 per 100,000.China alone accounted for>40%of cases and deaths worldwide.Both ASIR and ARMR of lung cancer increased with HDI(R2:0.54 and 0.47,all P values<0.001),regardless of gender.Based on available data,both ASIR during 2001–2010 and ASMR during 2001–2015 showed decreasing trends in males(EAPC:1.50%and−2.22%)but increasing trends in females(EAPC:1.08%and 0.07%).Similar trends in ASIR and ASMR were observed among the elder population(≥50 years);however,downward trends were observed in the younger population(<50 years).Alongside the aging and growth of the population,estimated cases and deaths from overall lung cancer would increase by 86.2%and 95.2%up to 2050 as compared with estimates in 2022,respectively.Notably,increased early-onset lung cancer was only observed in transitioning countries,while decreased early-onset lung cancer was observed in transitioned countries.Conclusion Lung cancer maintained as the leading cancer burden worldwide.Unless timely preventive interventions in tobacco mitigation,early screening,and precise treatment,the global lung cancer burden is expected to increase in the future,especially for transitioning countries.
基金supported by the Key Research Base Project of Humanities and Social Sciences in Jiangxi Colleges and Universities(JD23056)the Characteristic Programmers of Mental Health Education for Students,University of Tibetan Medicine(2024XLJKZD01).
文摘Objectives:The prevalence of cyber-aggression is increasing worldwide,resulting in significant negative impacts on both perpetrators and victims.This study aimed to investigate the relationship between cyber-ostracism and cyber-aggression among college students,clarify the role of various types of rumination in this dynamic.Methods:A total of 1198 Chinese college students(67.4%female;mean age 20.78 years;SD=1.12)were recruited through cluster random sampling and completed the Cyber-ostracism Experience Scale(COES),Positive and Negative Rumination Scale(PANRS),and Adolescent Online Aggression Behavior Scale(AOABS).Thestructural equation model(SEM)was employed to examine the relationship between cyber-ostracism,negative rumination,and cyber-aggression,as well as the moderating effect of positive rumination.Results:The results indicate that cyber-ostracism(β=0.128,p<0.001)positively predicts cyber-aggression.Negative ruminationmediates this relationship(effect size=0.027,95%CI=[0.007,0.014]).Positive rumination moderates the direct effect of cyber-ostracism on cyber-aggression(β=0.103,p<0.001).It alsomoderates both the first half(β=0.148,p<0.001)and the second half(β=0.138,p<0.001)of themediating pathway.Conclusion:This study suggests that cyber-ostracism influences cyber-aggression through negative rumination among Chinese college students.Positive rumination moderates this effect,although its impact is relatively limited.These findings offer valuable guidance for preventing and intervening in cyber-aggression among college students.
文摘Osteoradionecrosis of the temporal bone(ORN-TB)is usually controlled with conservative measures.However,a temporal bone resection may be required in unresponsive cases.The reconstruction of the resulting defects may be challenging because of the radiation damage to regional tissues.As a result,distant free flaps may be an optimal choice.For instance,the gracilis muscular free flap(GMFF)has consistent vascular anatomy and can be used to reconstruct small defects.We report three cases of uncontrolled ORN-TB requiring an extensive temporal bone resection followed by vascularized obliteration with a GMFF.The patients reported complete control of the main otologic symptoms(otorrhea,otalgia,and aural fullness)and optimal functional and aesthetic outcomes.Finally,the patients reported significant improvement in quality of life despite early postoperative complications.To our knowledge,the GMFF had not been used to obliterate temporal bone defects in patients with ORN-TB.
文摘Temporal optics,which enables lossless manipulation of ultrafast pulses,offers a new dimension for the regulation of quantum optical fields.In this paper,we established a temporal Fourier transform(TF)system based on a four-wave mixing(FWM)time lens and constructed a full quantum theoretical model for the resulting temporal SU(1,1)interferometer.This interferometer has high temporal resolution,can impose interference in both time and frequency domains,and is sensitive to the phase derivative.By introducing linear time-varying phase modulation,we achieved sub-picosecond precision in temporal autocorrelation measurements and generatedan optical frequency comb with a fixed interval based on a feedback iteration mechanism.Theoretical analysis revealsthe crucial regulatory role of time-frequency coupling in quantum interference,providing novel solutions for ultrafast quantum imaging,temporal mode encoding,and the generation of optical frequency quantization.
文摘Birdsong is an important secondary sexual trait which may vary between but also within species.Intraspecific variation is generally studied either on the geographical or on the temporal scale;most of the studies exploring the variation of song over time,however,focused on species with rather simple songs.In this study,we explored the temporal changes in song of a complex songster,the Thrush Nightingale(Luscinia luscinia),recorded after 33 years(in 1986 and 2019)at the same locality in south-eastern Finland.Our analysis revealed a complete turnover of song types over the study period,with no song type shared between the two recording years.In contrast,40%of the originally recorded syllable types were still found in the repertoires of recently recorded males.Their song type repertoires were significantly smaller but the songs themselves were on average longer compared to the 1986 recordings.Repertoires of both syllables and song types were more shared between males recorded in 1986 than between those from 2019.We discuss the processes that may have contributed to these temporal changes in song and call for more detailed studies of song evolution in wild populations.
基金supported by grants from the National Key R&D Program of China(2020YFA0803900)the National Natural Science Foundation of China(82173796 and U21A20418)+1 种基金the Natural Science Foundation of Zhejiang Province(LD22H310003)the Key R&D Plan of Zhejiang Province(2021C03116).
文摘Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications(ASMs),a condition known as pharmacoresistant epilepsy.The management of pharmacoresistant epilepsy remains an intractable issue in the clinic.Its early prediction is important for prevention and diagnosis.However,it still lacks effective predictors and approaches.Here,a classical model of pharmacoresistant temporal lobe epilepsy(TLE)was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats.Ictal electroencephalograms(EEGs)recorded before phenytoin treatment were analyzed.Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats,a convolutional neural network predictive model was constructed to predict pharmacoresistance,and achieved 78% prediction accuracy.We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power,which was verified in seizure EEGs from pharmacoresistant TLE patients.Prospectively,therapies targeting the subiculum in those predicted as“pharmacoresistant”individual rats significantly reduced the subsequent occurrence of pharmacoresistance.These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model.This may be of translational importance for the precise management of pharmacoresistant TLE.
基金supported by the Defitech Foundation(Morges,CH)to FCHthe Bertarelli Foundation-Catalyst program(Gstaad,CH)to FCH+2 种基金the Wyss Center for Bio and Neuroengineering the Lighthouse Partnership for AI-guided Neuromodulation to FCHthe Fonds de recherche du Quebec-Sante(FRQS#342969)to CEPthe Neuro X Postdoctoral Fellowship Program to CEP。
文摘Brain lesions,such as those caused by stroke or traumatic brain injury(TBI),frequently result in persistent motor and cognitive impairments that significantly affect the individual patient's quality of life.Despite differences in the mechanisms of injury,both conditions share a high prevalence of motor and cognitive impairments.These deficits show only limited natural recovery.
基金extend their appreciation to the King Salman Center for Disability Research for funding this work through Research Group No.KSRG-2024-223.
文摘Epilepsy is a long-term neurological condition marked by recurrent seizures,which result from abnormal electrical activity in the brain that disrupts its normal functioning.Traditional methods for detecting epilepsy through machine learning typically utilize discrete-time models,which inadequately represent the continuous dynamics of electroencephalogram(EEG)signals.To overcome this limitation,we introduce an innovative approach that employs Neural Ordinary Differential Equations(NODEs)to model EEG signals as continuous-time systems.This allows for effective management of irregular sampling and intricate temporal patterns.In contrast to conventional techniques,such as Convolutional Neural Networks(CNNs)and Recurrent Neural Networks(RNNs),which necessitate fixedlength inputs and often struggle with long-term dependencies,our framework incorporates:(1)a NODE block to capture continuous-time EEG dynamics,(2)a feature extraction module tailored for seizure-specific patterns,and(3)an attention-based fusion mechanism to enhance interpretability in classification.When evaluated on three publicly accessible EEG datasets,including those from Boston Children’s Hospital and the Massachusetts Institute of Technology(CHB-MIT)and the Temple University Hospital(TUH)EEG Corpus,the model demonstrated an average accuracy of 98.2%,a sensitivity of 97.8%,a specificity of 98.3%,and an F1-score of 97.9%.Additionally,the inference latency was reduced by approximately 30%compared to standard CNN and Long Short-Term Memory(LSTM)architectures,making it well-suited for real-time applications.The method’s resilience to noise and its adaptability to irregular sampling enhance its potential for clinical use in real-time settings.
