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
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
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
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
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
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
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
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
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
Extrapolation on Temporal Knowledge Graphs(TKGs)aims to predict future knowledge from a set of historical Knowledge Graphs in chronological order.The temporally adjacent facts in TKGs naturally form event sequences,ca...Extrapolation on Temporal Knowledge Graphs(TKGs)aims to predict future knowledge from a set of historical Knowledge Graphs in chronological order.The temporally adjacent facts in TKGs naturally form event sequences,called event evolution patterns,implying informative temporal dependencies between events.Recently,many extrapolation works on TKGs have been devoted to modelling these evolutional patterns,but the task is still far from resolved because most existing works simply rely on encoding these patterns into entity representations while overlooking the significant information implied by relations of evolutional patterns.However,the authors realise that the temporal dependencies inherent in the relations of these event evolution patterns may guide the follow-up event prediction to some extent.To this end,a Temporal Relational Context-based Temporal Dependencies Learning Network(TRenD)is proposed to explore the temporal context of relations for more comprehensive learning of event evolution patterns,especially those temporal dependencies caused by interactive patterns of relations.Trend incorporates a semantic context unit to capture semantic correlations between relations,and a structural context unit to learn the interaction pattern of relations.By learning the temporal contexts of relations semantically and structurally,the authors gain insights into the underlying event evolution patterns,enabling to extract comprehensive historical information for future prediction better.Experimental results on benchmark datasets demonstrate the superiority of the model.展开更多
Predicting information dissemination on social media,specifcally users’reposting behavior,is crucial for applications such as advertising campaigns.Conventional methods use deep neural networks to make predictions ba...Predicting information dissemination on social media,specifcally users’reposting behavior,is crucial for applications such as advertising campaigns.Conventional methods use deep neural networks to make predictions based on features related to user topic interests and social preferences.However,these models frequently fail to account for the difculties arising from limited training data and model size,which restrict their capacity to learn and capture the intricate patterns within microblogging data.To overcome this limitation,we introduce a novel model Adapt pre-trained Large Language model for Reposting Prediction(ALL-RP),which incorporates two key steps:(1)extracting features from post content and social interactions using a large language model with extensive parameters and trained on a vast corpus,and(2)performing semantic and temporal adaptation to transfer the large language model’s knowledge of natural language,vision,and graph structures to reposting prediction tasks.Specifcally,the temporal adapter in the ALL-RP model captures multi-dimensional temporal information from evolving patterns of user topic interests and social preferences,thereby providing a more realistic refection of user attributes.Additionally,to enhance the robustness of feature modeling,we introduce a variant of the temporal adapter that implements multiple temporal adaptations in parallel while maintaining structural simplicity.Experimental results on real-world datasets demonstrate that the ALL-RP model surpasses state-of-the-art models in predicting both individual user reposting behavior and group sharing behavior,with performance gains of 2.81%and 4.29%,respectively.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
Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking ro...Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.展开更多
Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 1...Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.展开更多
Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However...Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However,the spatiotemporal variations of tenebrionid beetle assemblages in the Gobi desert remain poorly understood.In this study,the monthly dynamics of tenebrionid beetles in the central part of the Hexi Corridor,Northwest China,a representative area of the Gobi desert ecosystems,were monitored using pitfall trapping during 2015-2020.The following results were showed:(1)monthly activity of tenebrionid beetles was observed from March to October,with monthly activity peaking in spring and summer,and monthly activity periods and peak of tenebrionid beetle species exhibited interspecific differences that varied from year to year;(2)spatial distribution of tenebrionid beetle community was influenced by structural factors.Specifically,at a spatial scale of 24.00 m,tenebrionid beetle community was strongly and positively correlated with the dominant species,with distinct spatial distribution patterns observed for Blaps gobiensis and Microdera kraatzi alashanica;(3)abundance of tenebrionid beetles was positively correlated with monthly mean precipitation and monthly mean temperature,whereas monthly abundance of B.gobiensis and M.kraatzi alashanica was positively correlated with monthly mean precipitation;and(4)the cover of Reaumuria soongarica(Pall.)Maxim.and Nitraria sphaerocarpa Maxim.had a positive influence on the number of tenebrionid beetles captured.In conclusion,monthly variation in precipitation significantly influences the community dynamic of tenebrionid beetles,with precipitation and shrub cover jointly determining the spatial distribution pattern of these beetles in the Gobi desert ecosystems.展开更多
Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and ...Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and rely on single indicators to assess startups’roles in predicting future success,failing to comprehensively capture topological variations and structural diversity.To address these limitations,we construct a temporal information network using 14547 investment records from 1013 global blockchain startups between 2004 and 2020,sourced from Crunchbase.We propose two dynamic methods to characterize the information flow:temporal random walk(sTRW)for modeling information flow trajectories and temporal betweenness centrality(tTBET)for identifying key information hubs.These methods enhance walk coverage while ensuring random stability,allowing for more effective identification of influential startups.By integrating sTRW and tTBET,we develop a comprehensive metric to evaluate a startup’s influence within the network.In experiments assessing startups’potential for future success—where successful startups are defined as those that have undergone M&A or IPO—incorporating this metric improves accuracy,recall,and F1 score by 0.035,0.035,and 0.042,respectively.Our findings indicate that information flow from key startups to others diminishes as the network distance increases.Additionally,successful startups generally exhibit higher information inflows than outflows,suggesting that actively seeking investment-related information contributes to startup growth.Our research provides valuable insights for formulating startup development strategies and offers practical guidance for market regulators.展开更多
BACKGROUND Gastric bezoars are masses of indigestible material that accumulate in the stomach,causing nausea,abdominal pain,and vomiting.Persimmon bezoars(diospyrobezoars),which comprise tannins and fibers from persim...BACKGROUND Gastric bezoars are masses of indigestible material that accumulate in the stomach,causing nausea,abdominal pain,and vomiting.Persimmon bezoars(diospyrobezoars),which comprise tannins and fibers from persimmons,are relatively rare but may cause significant gastric complications,including gastric outlet obstruction or ileus.Although computed tomography(CT)is a useful ima-ging tool,diagnosing bezoars can be challenging because their density is similar to that of food debris and gastric content.CASE SUMMARY Here,we report the case of a 72-year-old woman with a persimmon bezoar that was diagnosed using serial CT imaging and confirmed by endoscopy.CT perfor-med over several months revealed changes in the internal structure and density of the bezoar,suggesting progressive hardening.The patient had a history of a par-tial gastrectomy and excessive persimmon consumption,both of which are risk factors for bezoar formation.Endoscopic fragmentation of the bezoar successfully resolved symptoms.CONCLUSION Gastric bezoars,particularly persimmon bezoars,present diagnostic challenges because of their variable imaging characteristics.Serial CT can document tem-poral changes in bezoar density,potentially reflecting changes in hardness.Early diagnosis and endoscopic treatment are essential for effective management,particularly in patients with predisposing factors.This case underscores the im-portance of considering bezoars in the differential diagnosis of gastric masses,and highlights the value of CT for monitoring changes in bezoar characteristics over time.展开更多
Eutrophic shallow lakes are generally considered as a contributor to the emission of nitrous oxide(N_(2)O),while regional and global estimates have remained imprecise.This due to a lack of data and insufficient unders...Eutrophic shallow lakes are generally considered as a contributor to the emission of nitrous oxide(N_(2)O),while regional and global estimates have remained imprecise.This due to a lack of data and insufficient understanding of the multiple contributing factors.This study characterized the spatiotemporal variability in N_(2)O concentrations and N_(2)O diffusive fluxes and the contributing factors in LakeWuliangsuhai,a typical shallow eutrophic and seasonally frozen lake in Inner Mongolia with cold and arid climate.Dissolved N_(2)O concentrations of the lake exhibited a range of 4.5 to 101.2 nmol/L,displaying significant spatiotemporal variations.The lowest and highest concentrations were measured in summer and winter,respectively.The spatial distribution of N_(2)Ofluxwas consistent with that of N_(2)O concentrations.Additionally,the hotspots of N_(2)O emissions were detected within close to the main inflow of lake.The wide spatial and temporal variation in N_(2)O emissions indicate the complexity and its relative importance of factors influencing emissions.N_(2)O emissions in different lake zones and seasons were regulated by diverse factors.Factors influencing the spatial and temporal distribution of N_(2)O concentrations and fluxes were identified as WT,WD,DO,Chl-a,SD and COD.Interestingly,the same factor demonstrated opposing effects on N_(2)O emission in various seasons or zones.This research improves our understanding of N_(2)O emissions in shallow eutrophic lakes in cold and arid areas.展开更多
Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune d...Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune deficiency syndrome.An estimated 10.8 million TB cases were reported globally in 2023,with approximately 1.25 million associated deaths.In China,which ranks third in the global TB burden,there were approximately 741,000 new cases and 25,000 deaths in 2023^([1]).TB poses a significant threat to human health worldwide.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.
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 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.
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.
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.
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 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.
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 in part by the National Natural Science Foundation of China(No.62302507)and the funding of Harbin Institute of Technology(Shenzhen)(No.20210035).
文摘Extrapolation on Temporal Knowledge Graphs(TKGs)aims to predict future knowledge from a set of historical Knowledge Graphs in chronological order.The temporally adjacent facts in TKGs naturally form event sequences,called event evolution patterns,implying informative temporal dependencies between events.Recently,many extrapolation works on TKGs have been devoted to modelling these evolutional patterns,but the task is still far from resolved because most existing works simply rely on encoding these patterns into entity representations while overlooking the significant information implied by relations of evolutional patterns.However,the authors realise that the temporal dependencies inherent in the relations of these event evolution patterns may guide the follow-up event prediction to some extent.To this end,a Temporal Relational Context-based Temporal Dependencies Learning Network(TRenD)is proposed to explore the temporal context of relations for more comprehensive learning of event evolution patterns,especially those temporal dependencies caused by interactive patterns of relations.Trend incorporates a semantic context unit to capture semantic correlations between relations,and a structural context unit to learn the interaction pattern of relations.By learning the temporal contexts of relations semantically and structurally,the authors gain insights into the underlying event evolution patterns,enabling to extract comprehensive historical information for future prediction better.Experimental results on benchmark datasets demonstrate the superiority of the model.
文摘Predicting information dissemination on social media,specifcally users’reposting behavior,is crucial for applications such as advertising campaigns.Conventional methods use deep neural networks to make predictions based on features related to user topic interests and social preferences.However,these models frequently fail to account for the difculties arising from limited training data and model size,which restrict their capacity to learn and capture the intricate patterns within microblogging data.To overcome this limitation,we introduce a novel model Adapt pre-trained Large Language model for Reposting Prediction(ALL-RP),which incorporates two key steps:(1)extracting features from post content and social interactions using a large language model with extensive parameters and trained on a vast corpus,and(2)performing semantic and temporal adaptation to transfer the large language model’s knowledge of natural language,vision,and graph structures to reposting prediction tasks.Specifcally,the temporal adapter in the ALL-RP model captures multi-dimensional temporal information from evolving patterns of user topic interests and social preferences,thereby providing a more realistic refection of user attributes.Additionally,to enhance the robustness of feature modeling,we introduce a variant of the temporal adapter that implements multiple temporal adaptations in parallel while maintaining structural simplicity.Experimental results on real-world datasets demonstrate that the ALL-RP model surpasses state-of-the-art models in predicting both individual user reposting behavior and group sharing behavior,with performance gains of 2.81%and 4.29%,respectively.
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.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2025ZNSFSC0522partially supported by the National Natural Science Foundation of China under Grants No.61775030 and No.61571096.
文摘Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.
基金the Science and Technology Research Project of Shandong Meteorological Bureau(2022SDQN11)Science and Technology Research Project of Yantai Meteorological Bureau(2024ytcx07).
文摘Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.
基金funded by the National Natural Science Foundation of China(U23A2063)the Gansu Province Top-notch Leading Talents Project(E339040101)the National Natural Science Foundation of China(41771290,42377043,41773086).
文摘Tenebrionid beetles represent a crucial arthropod taxon in the Gobi desert ecosystems owing to their species richness and high biomass,both of which are essential for maintaining ecosystem health and stability.However,the spatiotemporal variations of tenebrionid beetle assemblages in the Gobi desert remain poorly understood.In this study,the monthly dynamics of tenebrionid beetles in the central part of the Hexi Corridor,Northwest China,a representative area of the Gobi desert ecosystems,were monitored using pitfall trapping during 2015-2020.The following results were showed:(1)monthly activity of tenebrionid beetles was observed from March to October,with monthly activity peaking in spring and summer,and monthly activity periods and peak of tenebrionid beetle species exhibited interspecific differences that varied from year to year;(2)spatial distribution of tenebrionid beetle community was influenced by structural factors.Specifically,at a spatial scale of 24.00 m,tenebrionid beetle community was strongly and positively correlated with the dominant species,with distinct spatial distribution patterns observed for Blaps gobiensis and Microdera kraatzi alashanica;(3)abundance of tenebrionid beetles was positively correlated with monthly mean precipitation and monthly mean temperature,whereas monthly abundance of B.gobiensis and M.kraatzi alashanica was positively correlated with monthly mean precipitation;and(4)the cover of Reaumuria soongarica(Pall.)Maxim.and Nitraria sphaerocarpa Maxim.had a positive influence on the number of tenebrionid beetles captured.In conclusion,monthly variation in precipitation significantly influences the community dynamic of tenebrionid beetles,with precipitation and shrub cover jointly determining the spatial distribution pattern of these beetles in the Gobi desert ecosystems.
基金the funding from the National Natural Science Foundation of China(Grant Nos.42001236,71991481,and 71991480)Young Elite Scientist Sponsor-ship Program by Bast(Grant No.BYESS2023413)。
文摘Startups form an information network that reflects their growth trajectories through information flow channels established by shared investors.However,traditional static network metrics overlook temporal dynamics and rely on single indicators to assess startups’roles in predicting future success,failing to comprehensively capture topological variations and structural diversity.To address these limitations,we construct a temporal information network using 14547 investment records from 1013 global blockchain startups between 2004 and 2020,sourced from Crunchbase.We propose two dynamic methods to characterize the information flow:temporal random walk(sTRW)for modeling information flow trajectories and temporal betweenness centrality(tTBET)for identifying key information hubs.These methods enhance walk coverage while ensuring random stability,allowing for more effective identification of influential startups.By integrating sTRW and tTBET,we develop a comprehensive metric to evaluate a startup’s influence within the network.In experiments assessing startups’potential for future success—where successful startups are defined as those that have undergone M&A or IPO—incorporating this metric improves accuracy,recall,and F1 score by 0.035,0.035,and 0.042,respectively.Our findings indicate that information flow from key startups to others diminishes as the network distance increases.Additionally,successful startups generally exhibit higher information inflows than outflows,suggesting that actively seeking investment-related information contributes to startup growth.Our research provides valuable insights for formulating startup development strategies and offers practical guidance for market regulators.
文摘BACKGROUND Gastric bezoars are masses of indigestible material that accumulate in the stomach,causing nausea,abdominal pain,and vomiting.Persimmon bezoars(diospyrobezoars),which comprise tannins and fibers from persimmons,are relatively rare but may cause significant gastric complications,including gastric outlet obstruction or ileus.Although computed tomography(CT)is a useful ima-ging tool,diagnosing bezoars can be challenging because their density is similar to that of food debris and gastric content.CASE SUMMARY Here,we report the case of a 72-year-old woman with a persimmon bezoar that was diagnosed using serial CT imaging and confirmed by endoscopy.CT perfor-med over several months revealed changes in the internal structure and density of the bezoar,suggesting progressive hardening.The patient had a history of a par-tial gastrectomy and excessive persimmon consumption,both of which are risk factors for bezoar formation.Endoscopic fragmentation of the bezoar successfully resolved symptoms.CONCLUSION Gastric bezoars,particularly persimmon bezoars,present diagnostic challenges because of their variable imaging characteristics.Serial CT can document tem-poral changes in bezoar density,potentially reflecting changes in hardness.Early diagnosis and endoscopic treatment are essential for effective management,particularly in patients with predisposing factors.This case underscores the im-portance of considering bezoars in the differential diagnosis of gastric masses,and highlights the value of CT for monitoring changes in bezoar characteristics over time.
基金supported by the National Natural Science Foundation of China(Nos.52260028,52060022,52260029,and 52160021)the National Key Research and Development Program of China(Nos.2017YFE0114800 and 2019YFC0409200)+1 种基金Inner Mongolia Autonomous Region Science and Technology Plan(No.2021GG0089)personal grant to Guohua Li by China Scholarship Council(CSC).
文摘Eutrophic shallow lakes are generally considered as a contributor to the emission of nitrous oxide(N_(2)O),while regional and global estimates have remained imprecise.This due to a lack of data and insufficient understanding of the multiple contributing factors.This study characterized the spatiotemporal variability in N_(2)O concentrations and N_(2)O diffusive fluxes and the contributing factors in LakeWuliangsuhai,a typical shallow eutrophic and seasonally frozen lake in Inner Mongolia with cold and arid climate.Dissolved N_(2)O concentrations of the lake exhibited a range of 4.5 to 101.2 nmol/L,displaying significant spatiotemporal variations.The lowest and highest concentrations were measured in summer and winter,respectively.The spatial distribution of N_(2)Ofluxwas consistent with that of N_(2)O concentrations.Additionally,the hotspots of N_(2)O emissions were detected within close to the main inflow of lake.The wide spatial and temporal variation in N_(2)O emissions indicate the complexity and its relative importance of factors influencing emissions.N_(2)O emissions in different lake zones and seasons were regulated by diverse factors.Factors influencing the spatial and temporal distribution of N_(2)O concentrations and fluxes were identified as WT,WD,DO,Chl-a,SD and COD.Interestingly,the same factor demonstrated opposing effects on N_(2)O emission in various seasons or zones.This research improves our understanding of N_(2)O emissions in shallow eutrophic lakes in cold and arid areas.
文摘Tuberculosis(TB)remained the first leading cause of death from a single infectious agent worldwide in 2023,resulting in nearly twice as many deaths as those caused by the human immunodeficiency virus/acquired immune deficiency syndrome.An estimated 10.8 million TB cases were reported globally in 2023,with approximately 1.25 million associated deaths.In China,which ranks third in the global TB burden,there were approximately 741,000 new cases and 25,000 deaths in 2023^([1]).TB poses a significant threat to human health worldwide.
