BACKGROUND:The accelerated diagnostic protocol(ADP)using the Emergency Department Assessment of Chest pain Score(EDACS-ADP),a tool to identify patients at low risk of a major adverse cardiac event(MACE)among patients ...BACKGROUND:The accelerated diagnostic protocol(ADP)using the Emergency Department Assessment of Chest pain Score(EDACS-ADP),a tool to identify patients at low risk of a major adverse cardiac event(MACE)among patients presenting with chest pain to the emergency department,was developed using a contemporary troponin assay.This study was performed to validate and compare the performance of the EDACS-ADP incorporating high-sensitivity cardiac troponin I between patients who had a 30-day MACE with and without unstable angina(MACE I and II,respectively).METHODS:A single-center prospective observational study of adult patients presenting with chest pain suggestive of acute coronary syndrome was performed.The performance of EDACS-ADP in predicting MACE was assessed by calculating the sensitivity and negative predictive value.RESULTS:Of the 1,304 patients prospectively enrolled,399(30.6%;95%confidence interval[95%CI]:27.7%–33.8%)were considered low-risk using the EDACS-ADP.Among them,the rates of MACE I and II were 1.3%(5/399)and 1.0%(4/399),respectively.The EDACS-ADP showed sensitivities and negative predictive values of 98.8%(95%CI:97.2%–99.6%)and 98.7%(95%CI:97.0%–99.5%)for MACE I and 98.7%(95%CI:96.8%–99.7%)and 99.0%(95%CI:97.4%–99.6%)for MACE II,respectively.CONCLUSION:EDACS-ADP could help identify patients as safe for early discharge.However,when unstable angina was added to the outcome,the 30-day MACE rate among the designated lowrisk patients remained above the level acceptable for early discharge without further evaluation.展开更多
Using the daily precipitation data of 740 stations in China from 1960 to 2000, the analysis on the variations and distributions of the frequency and the percentage of extreme precipitation to the annual rainfall have ...Using the daily precipitation data of 740 stations in China from 1960 to 2000, the analysis on the variations and distributions of the frequency and the percentage of extreme precipitation to the annual rainfall have been performed in this paper. Results indicate that the percentage of heavy rains （above 25mm/day） in the annual rainfall has increased, while on average the day number of heavy rains has slightly reduced during the past 40 years. In the end of 1970s and the beginning of 1980s, both the number of days with extreme precipitation and the percentage of extreme precipitation abruptly changed over China, especially in the northern China. By moving t test, the abrupt change year of extreme precipitation for each station and its spatial distribution over the whole country are also obtained. The abrupt change years concentrated in 1978-1982 for most regions of northern China while occurred at various stations in southern China in greatly different/diverse years. Besides the abrupt change years of extreme precipitation at part stations of Northwest China happened about 5 years later in comparison with that of the country＇s average.展开更多
Legal language is a pretty formal language.As part of legal language,legislative language has all the basic features of legal language and legislative language has an accurate,plain,solemn,rigorous style.People interp...Legal language is a pretty formal language.As part of legal language,legislative language has all the basic features of legal language and legislative language has an accurate,plain,solemn,rigorous style.People interprete legislative language and act in accordance with laws.On the contrary,behaviors and certain events also influence the characteristics of legislative language,even trigger some conflicts with it.Confronted with some advantaged influence,legislators have to make some compromises or change the characteristics of legislative language.However,legislators should adhere to remain represantations of laws to resist disadvantaged impacts.As a result,it is need to research how behaviors and certain events influence legislative language.展开更多
This paper studies English training for student volunteers at large scale sports events with a comprehensive investigation of the undergraduate student volunteers from Capital University of Physical Education who have...This paper studies English training for student volunteers at large scale sports events with a comprehensive investigation of the undergraduate student volunteers from Capital University of Physical Education who have taken part in large scale sports events.By examining the current volunteer training situation,the author finds that there is a sever lack of professional and systematical English training for student volunteers at large scale sports events.The study shows focusing on sports events knowledge and requirements of the volunteers’specific job is crucial to the service level of the volunteers.The study concludes that the problem can be solved by developing new course books,innovating new flexible training methods,and offering more comprehensive training content.The recommended training methods include intensive group training,computer aided teaching,task training and on-the-spot training to make them fit their work soon.展开更多
Background The left atrial size has been considered as a useful marker of adverse cardiovascular outcomes. However, it is not well known whether left atrial area index （LAAI） has predictive value for prognosis in pa...Background The left atrial size has been considered as a useful marker of adverse cardiovascular outcomes. However, it is not well known whether left atrial area index （LAAI） has predictive value for prognosis in patients with unstable angina pectoris （UAP）. This study was aimed to assess the association between LAAI and outcomes in UAP patients. Methods We enrolled a total of 391 in-hospital patients diag- nosed as UAP. Clinical and echocardiographic data at baseline were collected. The patients were followed for the development of ad- verse cardiovascular （CV） events, including hospital readmission for angina pectoris, acute myocardial infarction （AMI）, congestive heart failure （CHF）, stroke and all-cause mortality. Results During a mean follow-up time of 26.3±8.6 months, 98 adverse CV events occurred （84 hospital readmission for angina pectoris, four AMI, four CHF, one stroke and five all-cause mortality）. In a multivariate Cox model, LAAI [OR： 1.140, 95% CI： 1.01±1.279, P = 0.026], diastolic blood pressure （OR： 0.976, 95% CI： 0.956-0.996, P = 0.020） and pulse pressure （OR 1.020, 95% CI： 1.007-1.034, P = 0.004） were independent predictors for adverse CV events in UAP patients. Conclusions LAAI is a predictor of adverse CV events independent of clinical and other echocardiographic parameters in UAP patients.展开更多
The ultralow detection threshold,ultralow intrinsic background,and excellent energy resolution of ptype point-contact germanium detectors are important for rare-event searches,in particular for the detection of direct...The ultralow detection threshold,ultralow intrinsic background,and excellent energy resolution of ptype point-contact germanium detectors are important for rare-event searches,in particular for the detection of direct dark matter interactions,coherent elastic neutrino-nucleus scattering,and neutrinoless double beta decay.Anomalous bulk events with an extremely fast rise time are observed in the CDEX-1B detector.We report a method of extracting fast bulk events from bulk events using a pulse shape simulation and reconstructed source experiment signature.Calibration data and the distribution of X-rays generated by intrinsic radioactivity verified that the fast bulk experienced a single hit near the passivation layer.The performance of this germanium detector indicates that it is capable of single-hit bulk spatial resolution and thus provides a background removal technique.展开更多
Background There are limited data on the prevalence of electrocardiographic (ECG) abnormalities, and their value for predicting a major adverse cardiovascular event (MACE) in patients at high cardiovascular risk. This...Background There are limited data on the prevalence of electrocardiographic (ECG) abnormalities, and their value for predicting a major adverse cardiovascular event (MACE) in patients at high cardiovascular risk. This study aimed to determine the prevalence of ECG abnormalities in patients at high risk for cardiovascular events, and to identify ECG abnormalities that significantly predict MACE. Methods Patients aged ≥ 45 years with established atherosclerotic disease (EAD) were consecutively enrolled from the outpatient clinics of the six participating hospitals during April 2011 to March 2014. The following data were collected: demographic data, cardiovascular risk factors, history of cardiovascular event, physical examination, ECG and medications. ECG was analyzed using Minnesota Code criteria. MACE included cardiovascular death, non-fatal myocardial infarction, and hospitalization due to unstable angina or heart failure. Results A total of 2009 patients were included, 1048 patients (52.2%) had established EAD, and 961 patients (47.8%) had multiple risk factors (MRF). ECG abnormalities included atrial fibrillation (6.7%), premature ventricular contraction (5.4%), pathological Q-wave (Q/QS)(21.3%), T-wave inversion (20.0%), intraventricular ventricular conduction delay (IVCD)(7.3%), left ventricular hypertrophy (LVH)(12.2%), and AV block (12.5%). MACE occurred in 88 patients (4.4%). Independent predictors of MACE were chronic kidney disease, EAD, and the presence of atrial fibrillation, Q/QS, IVCD or LVH by ECG. Conclusions A high prevalence of ECG abnormalities was found. The prevalence of ECG abnormalities was high even among those with risk factors without documented cardiovascular disease.展开更多
Background This prospective study integrated multiple clinical indexes and inflammatory markers associated with coronary atherosclerotic vulnerable plaque to establish a risk prediction model that can evaluate a patie...Background This prospective study integrated multiple clinical indexes and inflammatory markers associated with coronary atherosclerotic vulnerable plaque to establish a risk prediction model that can evaluate a patient with certain risk factors for the likelihood of the occurrence of a coronary heart disease event within one year. Methods This study enrolled in 2686 patients with mild to moderate coronary artery lesions. Eighty-five indexes were recorded, included baseline clinical data, laboratory studies, and procedural characteristics. During the 1-year follow-up, 233 events occurred, five patients died, four patients suffered a nonfatal myocardial infarction, four patients underwent revascularization, and 220 patients were readmitted for angina pectoris. The Risk Estimation Model and the Simplified Model were conducted using Bayesian networks and compared with the Single Factor Models. Results The area under the curve was 0.88 for the Bayesian Model and 0.85 for the Simplified Model, while the Single Factor Model had a maximum area under the curve of 0.65. Conclusion The new models can be used to assess the short-term risk of individual coronary heart disease events and may assist in guiding preventive care.展开更多
Background and objective To assess the predictive value of C-reactive protein(CRP) for major adverse cardiac events and the association between CRP level and the coronary lesion morphology and extent in patients with ...Background and objective To assess the predictive value of C-reactive protein(CRP) for major adverse cardiac events and the association between CRP level and the coronary lesion morphology and extent in patients with coronary heart disease (CHD).Methods CRP was measured on admission in 177 consecutive elderly (age≥60 years) patients with CHD who underwent coronary angiography. Patients were divided into high CRP group (CRP≥3mg/L) and normal CRP group (CRP ＜3mg/L). The association between CRP levels and the coronary lesion features, including severity of stenosis (mild, moderate, severe), extent of lesion (diffused or nondiffused), eccentricity of the plaque (eccentric or non-eccentric) were analyzed. Patients were followed up for a mean of 8 months for the occurrences of major adverse cardiac events (MACE). Results Compared with patients in normal CRP group, patients in high CRP group were more frequently to have unstable angina, multi-vessel, diffuse, eccentric lesions, positive remodeling, and non-smooth plaques (P＜0.01). Kaplan-Meier analysis showed patients in high CRP group had a significantly lower MACE-free survival rate than patients in normal CRP group (Log-rank = 12.0, P＜0.01); Cox regression analysis indicated CRP level as an independent predictor for the occurrence of MACE (OR=3.16, P＜0.05) Conclusions High CRP level is associated with more extend, severe and eccentric coronary lesions and is an independent predictor for MACE in elderly patients with CHD.展开更多
In order to effectively decrease the safety accidents caused by coal miners’human errors,this paper probes into the causality between human errors and life events,coping,psychological stress,psychological function,ph...In order to effectively decrease the safety accidents caused by coal miners’human errors,this paper probes into the causality between human errors and life events,coping,psychological stress,psychological function,physiological function based on life events’vital influence on human errors,establishing causation mechanism model of coal miners’human errors in the perspective of life events by the researching method of structural equation.The research findings show that life events have significantly positive influence on human errors,with a influential effect value of 0.7945 and a influential effect path of‘‘life events—psychological stress—psychological function—physiological function—human errors’’and‘‘life events—psychological stress—physiological function—human errors’’.展开更多
Objective To investigate whether plasma big endothelin-1(ET-1) predicts ventricular arrythmias(VAs) and end-stage events in primary prevention implantable cardioverter-defibrillator(ICD) indication patigents. Methods ...Objective To investigate whether plasma big endothelin-1(ET-1) predicts ventricular arrythmias(VAs) and end-stage events in primary prevention implantable cardioverter-defibrillator(ICD) indication patigents. Methods In total, 207 patients fulfilling the inclusion criteria from Fuwai Hospital between January 2013 and December 2015 were retrospectively analyzed. The cohort was divided into three groups according to baseline plasma big ET-1 tertiles: tertile 1(< 0.38 pmol/L, n = 68), tertile 2(0.38–0.7 pmol/L, n = 69), and tertile 3(> 0.7 pmol/L, n = 70). The primary endpoints were VAs. The secondary endpoints were end-stage events comprising all-cause mortality and heart transplantation. Results During a mean follow-up period of 25.6 ± 13.9 months, 38(18.4%) VAs and 78(37.7%) end-stage events occurred. Big ET-1 was positively correlated with NYHA class(r = 0.165, P = 0.018), serum creatinine concentration(Scr;r = 0.147, P = 0.034), high-sensitivity C-reactive protein(hs-CRP;r = 0.217, P = 0.002), Lg NT-pro BNP(r = 0.463, P < 0.001), left ventricular end diastolic diameter(LVEDD;r = 0.234, P = 0.039) and negatively correlated with left ventricular ejection fraction(LVEF;r =-0.181, P = 0.032). Kaplan-Meier analysis showed that elevated big ET-1 was associated with increased risk of VAs and end-stage events(P < 0.05). In multivariate Cox regression models, big ET-1 was an independent risk factor for VAs(hazard ratio(HR) = 3.477, 95% confidence interval(CI): 1.352–8.940, P = 0.010, tertile 2 vs. tertile 1;HR = 4.112, 95% CI: 1.604–10.540, P = 0.003, tertile 3 vs. tertile 1) and end-stage events(HR = 2.804, 95% CI: 1.354–5.806, P = 0.005, tertile 2 vs. tertile 1;HR = 4.652, 95% CI: 2.288–9.459, P < 0.001, tertile 3 vs. tertile 1). Conclusions In primary prevention ICD indication patients, plasma big ET-1 levels can predict VAs and end-stage events and may facilitate ICD-implantation risk stratification.展开更多
The existing approaches for identifying events in horizontal well fracturing are difficult, time-consuming, inaccurate, and incapable of real-time warning. Through improvement of data analysis and deep learning algori...The existing approaches for identifying events in horizontal well fracturing are difficult, time-consuming, inaccurate, and incapable of real-time warning. Through improvement of data analysis and deep learning algorithm, together with the analysis on data and information of horizontal well fracturing in shale gas reservoirs, this paper presents a method for intelligent identification and real-time warning of diverse complex events in horizontal well fracturing. An identification model for "point" events in fracturing is established based on the Att-BiLSTM neural network, along with the broad learning system (BLS) and the BP neural network, and it realizes the intelligent identification of the start/end of fracturing, formation breakdown, instantaneous shut-in, and other events, with an accuracy of over 97%. An identification model for "phase" events in fracturing is established based on enhanced Unet++ network, and it realizes the intelligent identification of pump ball, pre-acid treatment, temporary plugging fracturing, sand plugging, and other events, with an error of less than 0.002. Moreover, a real-time prediction model for fracturing pressure is built based on the Att-BiLSTM neural network, and it realizes the real-time warning of diverse events in fracturing. The proposed method can provide an intelligent, efficient and accurate identification of events in fracturing to support the decision-making.展开更多
Extreme weather events were analyzed based on the meteorological data from the year of 1967 to 2007 for Yamaguchi, Japan. The responses from landscape trees were also investigated mainly by the analysis of image pixel...Extreme weather events were analyzed based on the meteorological data from the year of 1967 to 2007 for Yamaguchi, Japan. The responses from landscape trees were also investigated mainly by the analysis of image pixel and spectral reflectance. Results show that after the dry, hot and windy summer in 2007, many landscape trees in Yamaguchi City tended to respond the extreme weather events by reducing their leaf surface area and receiving less radiation energy. Premature leaf discoloration or defoliation appeared on some landscape tree species and leaf necrosis occurred on tip and margin of many Kousa dogwood (Cornus kousa) trees at unfavorable sites. Described by image pixel analysis method, the leaf necrotic area percentage (LNAP) of sampled dogwood trees averaged 41.6% and the sampled Sasanqua camellia (Camelia sasanqua) tree also showed fewer flowers in flower season of 2007 than that in 2006. By differential analysis of partial discolored crown, it presented a logistic differential equation of crown color for sweet gum (Liquidambar styraciflua) trees. It suggested that the persistent higher temperature and lower precipitation could be injurious to the sensitive landscape trees at poor sites, even in relative humid area like Yamaguchi.展开更多
Compared with first-order surface-related multiples from marine data,the onshore internal multiples are weaker and are always combined with a hazy and occasionally strong interference pattern.It is usually difficult t...Compared with first-order surface-related multiples from marine data,the onshore internal multiples are weaker and are always combined with a hazy and occasionally strong interference pattern.It is usually difficult to discriminate these events from complex targets and highly scattering overburdens,especially when the primary energy from deep layers is weaker than that from shallow layers.The internal multiple elimination is even more challenging due to the fact that the velocity and energy difference between primary reflections and internal multiples is tiny.In this study,we propose an improved method which formulates the elimination of the internal multiples as an optimization problem and develops a convolution factor T.The generated internal multiples at all interfaces are obtained using the convolution factor T through iterative inversion of the initial multiple model.The predicted internal multiples are removed from seismic data through subtraction.Finally,several synthetic experiments are conducted to validate the effectiveness of our approach.The results of our study indicate that compared with the traditional virtual events method,the improved method simplifies the multiple prediction process in which internal multiples generated from each interface are built through iterative inversion,thus reducing the calculation cost,improving the accuracy,and enhancing the adaptability of field data.展开更多
Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor do...Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.展开更多
Video events recognition is a challenging task for high-level understanding of video se- quence. At present, there are two major limitations in existing methods for events recognition. One is that no algorithms are av...Video events recognition is a challenging task for high-level understanding of video se- quence. At present, there are two major limitations in existing methods for events recognition. One is that no algorithms are available to recognize events which happen alternately. The other is that the temporal relationship between atomic actions is not fully utilized. Aiming at these problems, an algo- rithm based on an extended stochastic context-free grammar （SCFG） representation is proposed for events recognition. Events are modeled by a series of atomic actions and represented by an extended SCFG. The extended SCFG can express the hierarchical structure of the events and the temporal re- lationship between the atomic actions. In comparison with previous work, the main contributions of this paper are as follows： ① Events （include alternating events） can be recognized by an improved stochastic parsing and shortest path finding algorithm. ② The algorithm can disambiguate the detec- tion results of atomic actions by event context. Experimental results show that the proposed algo- rithm can recognize events accurately and most atomic action detection errors can be corrected sim- ultaneously.展开更多
The occurrence of microseismic is not random but is related to the physical properties of the underground medium.Due to the low intensity and the influence of noise,microseismic eventually lead to poor signal-to-noise...The occurrence of microseismic is not random but is related to the physical properties of the underground medium.Due to the low intensity and the influence of noise,microseismic eventually lead to poor signal-to-noise ratio.We proposed a method for automatic detection of microseismic events by adoption of multiscale top-hat transformation.The method is based on the difference between the signal and noise in the multiscale top-hat transform section and achieves the detection on a specific section.The microseismic data are decomposed into different scales by multiscale morphology top-hat transformation firstly.Then the potential microseismic events could be detected by picking up the peak value in the multiscale top-hat section,and the characteristic profile obtains the start point with a specific threshold value.Finally,the synthetic data experiences demonstrate the advantages of this method under strong and weak noisy conditions,and the filed data example also shows its reliability and adaptability.展开更多
The ability to recognise video events has become increasingly more popular owing to its extensive practical applications.Most events will occur in certain scene with certain people,and the scene context and group cont...The ability to recognise video events has become increasingly more popular owing to its extensive practical applications.Most events will occur in certain scene with certain people,and the scene context and group context provide important information for event recognition.In this paper,we present an algorithm to recognise video events in different scenes in which there are multiple agents.First,we recognise events for each agent based on Stochastic Context Sensitive Grammar(SCSG).Then we propose the model of a scene in order to infer the scene in which the events occur,and we use a co-occurrence matrix of events to represent the group context.Finally,the scene and group context are exploited to distinguish events having similar structures.Experimental results show that by adding the scene and group context,the performance of events recognition can be significantly improved.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government Ministry of Science and ICT(NRF-2021R1G1A101056711)。
文摘BACKGROUND:The accelerated diagnostic protocol(ADP)using the Emergency Department Assessment of Chest pain Score(EDACS-ADP),a tool to identify patients at low risk of a major adverse cardiac event(MACE)among patients presenting with chest pain to the emergency department,was developed using a contemporary troponin assay.This study was performed to validate and compare the performance of the EDACS-ADP incorporating high-sensitivity cardiac troponin I between patients who had a 30-day MACE with and without unstable angina(MACE I and II,respectively).METHODS:A single-center prospective observational study of adult patients presenting with chest pain suggestive of acute coronary syndrome was performed.The performance of EDACS-ADP in predicting MACE was assessed by calculating the sensitivity and negative predictive value.RESULTS:Of the 1,304 patients prospectively enrolled,399(30.6%;95%confidence interval[95%CI]:27.7%–33.8%)were considered low-risk using the EDACS-ADP.Among them,the rates of MACE I and II were 1.3%(5/399)and 1.0%(4/399),respectively.The EDACS-ADP showed sensitivities and negative predictive values of 98.8%(95%CI:97.2%–99.6%)and 98.7%(95%CI:97.0%–99.5%)for MACE I and 98.7%(95%CI:96.8%–99.7%)and 99.0%(95%CI:97.4%–99.6%)for MACE II,respectively.CONCLUSION:EDACS-ADP could help identify patients as safe for early discharge.However,when unstable angina was added to the outcome,the 30-day MACE rate among the designated lowrisk patients remained above the level acceptable for early discharge without further evaluation.
基金Project supported by the National Natural Science Foundation of China (Grant No 40675044)the State Key Development Program for Basic Research of China (Grant No 2006CB400503)the Laboratory for Climate Studies of China Meteorological Administration Climate Research Program (Grant No LCS-2006-04)
文摘Using the daily precipitation data of 740 stations in China from 1960 to 2000, the analysis on the variations and distributions of the frequency and the percentage of extreme precipitation to the annual rainfall have been performed in this paper. Results indicate that the percentage of heavy rains （above 25mm/day） in the annual rainfall has increased, while on average the day number of heavy rains has slightly reduced during the past 40 years. In the end of 1970s and the beginning of 1980s, both the number of days with extreme precipitation and the percentage of extreme precipitation abruptly changed over China, especially in the northern China. By moving t test, the abrupt change year of extreme precipitation for each station and its spatial distribution over the whole country are also obtained. The abrupt change years concentrated in 1978-1982 for most regions of northern China while occurred at various stations in southern China in greatly different/diverse years. Besides the abrupt change years of extreme precipitation at part stations of Northwest China happened about 5 years later in comparison with that of the country＇s average.
文摘Legal language is a pretty formal language.As part of legal language,legislative language has all the basic features of legal language and legislative language has an accurate,plain,solemn,rigorous style.People interprete legislative language and act in accordance with laws.On the contrary,behaviors and certain events also influence the characteristics of legislative language,even trigger some conflicts with it.Confronted with some advantaged influence,legislators have to make some compromises or change the characteristics of legislative language.However,legislators should adhere to remain represantations of laws to resist disadvantaged impacts.As a result,it is need to research how behaviors and certain events influence legislative language.
文摘This paper studies English training for student volunteers at large scale sports events with a comprehensive investigation of the undergraduate student volunteers from Capital University of Physical Education who have taken part in large scale sports events.By examining the current volunteer training situation,the author finds that there is a sever lack of professional and systematical English training for student volunteers at large scale sports events.The study shows focusing on sports events knowledge and requirements of the volunteers’specific job is crucial to the service level of the volunteers.The study concludes that the problem can be solved by developing new course books,innovating new flexible training methods,and offering more comprehensive training content.The recommended training methods include intensive group training,computer aided teaching,task training and on-the-spot training to make them fit their work soon.
文摘Background The left atrial size has been considered as a useful marker of adverse cardiovascular outcomes. However, it is not well known whether left atrial area index （LAAI） has predictive value for prognosis in patients with unstable angina pectoris （UAP）. This study was aimed to assess the association between LAAI and outcomes in UAP patients. Methods We enrolled a total of 391 in-hospital patients diag- nosed as UAP. Clinical and echocardiographic data at baseline were collected. The patients were followed for the development of ad- verse cardiovascular （CV） events, including hospital readmission for angina pectoris, acute myocardial infarction （AMI）, congestive heart failure （CHF）, stroke and all-cause mortality. Results During a mean follow-up time of 26.3±8.6 months, 98 adverse CV events occurred （84 hospital readmission for angina pectoris, four AMI, four CHF, one stroke and five all-cause mortality）. In a multivariate Cox model, LAAI [OR： 1.140, 95% CI： 1.01±1.279, P = 0.026], diastolic blood pressure （OR： 0.976, 95% CI： 0.956-0.996, P = 0.020） and pulse pressure （OR 1.020, 95% CI： 1.007-1.034, P = 0.004） were independent predictors for adverse CV events in UAP patients. Conclusions LAAI is a predictor of adverse CV events independent of clinical and other echocardiographic parameters in UAP patients.
基金supported by the National Key Research and Development Program of China(No.2017YFA0402203)the National Natural Science Foundation of China(No.11975162)the SPARK project of the research and innovation program of Sichuan University(No.2018SCUH0051)。
文摘The ultralow detection threshold,ultralow intrinsic background,and excellent energy resolution of ptype point-contact germanium detectors are important for rare-event searches,in particular for the detection of direct dark matter interactions,coherent elastic neutrino-nucleus scattering,and neutrinoless double beta decay.Anomalous bulk events with an extremely fast rise time are observed in the CDEX-1B detector.We report a method of extracting fast bulk events from bulk events using a pulse shape simulation and reconstructed source experiment signature.Calibration data and the distribution of X-rays generated by intrinsic radioactivity verified that the fast bulk experienced a single hit near the passivation layer.The performance of this germanium detector indicates that it is capable of single-hit bulk spatial resolution and thus provides a background removal technique.
基金supported by the Heart Association of Thailand under the Royal Patronage of H.M. the King, National Research Council of Thailand
文摘Background There are limited data on the prevalence of electrocardiographic (ECG) abnormalities, and their value for predicting a major adverse cardiovascular event (MACE) in patients at high cardiovascular risk. This study aimed to determine the prevalence of ECG abnormalities in patients at high risk for cardiovascular events, and to identify ECG abnormalities that significantly predict MACE. Methods Patients aged ≥ 45 years with established atherosclerotic disease (EAD) were consecutively enrolled from the outpatient clinics of the six participating hospitals during April 2011 to March 2014. The following data were collected: demographic data, cardiovascular risk factors, history of cardiovascular event, physical examination, ECG and medications. ECG was analyzed using Minnesota Code criteria. MACE included cardiovascular death, non-fatal myocardial infarction, and hospitalization due to unstable angina or heart failure. Results A total of 2009 patients were included, 1048 patients (52.2%) had established EAD, and 961 patients (47.8%) had multiple risk factors (MRF). ECG abnormalities included atrial fibrillation (6.7%), premature ventricular contraction (5.4%), pathological Q-wave (Q/QS)(21.3%), T-wave inversion (20.0%), intraventricular ventricular conduction delay (IVCD)(7.3%), left ventricular hypertrophy (LVH)(12.2%), and AV block (12.5%). MACE occurred in 88 patients (4.4%). Independent predictors of MACE were chronic kidney disease, EAD, and the presence of atrial fibrillation, Q/QS, IVCD or LVH by ECG. Conclusions A high prevalence of ECG abnormalities was found. The prevalence of ECG abnormalities was high even among those with risk factors without documented cardiovascular disease.
文摘Background This prospective study integrated multiple clinical indexes and inflammatory markers associated with coronary atherosclerotic vulnerable plaque to establish a risk prediction model that can evaluate a patient with certain risk factors for the likelihood of the occurrence of a coronary heart disease event within one year. Methods This study enrolled in 2686 patients with mild to moderate coronary artery lesions. Eighty-five indexes were recorded, included baseline clinical data, laboratory studies, and procedural characteristics. During the 1-year follow-up, 233 events occurred, five patients died, four patients suffered a nonfatal myocardial infarction, four patients underwent revascularization, and 220 patients were readmitted for angina pectoris. The Risk Estimation Model and the Simplified Model were conducted using Bayesian networks and compared with the Single Factor Models. Results The area under the curve was 0.88 for the Bayesian Model and 0.85 for the Simplified Model, while the Single Factor Model had a maximum area under the curve of 0.65. Conclusion The new models can be used to assess the short-term risk of individual coronary heart disease events and may assist in guiding preventive care.
文摘Background and objective To assess the predictive value of C-reactive protein(CRP) for major adverse cardiac events and the association between CRP level and the coronary lesion morphology and extent in patients with coronary heart disease (CHD).Methods CRP was measured on admission in 177 consecutive elderly (age≥60 years) patients with CHD who underwent coronary angiography. Patients were divided into high CRP group (CRP≥3mg/L) and normal CRP group (CRP ＜3mg/L). The association between CRP levels and the coronary lesion features, including severity of stenosis (mild, moderate, severe), extent of lesion (diffused or nondiffused), eccentricity of the plaque (eccentric or non-eccentric) were analyzed. Patients were followed up for a mean of 8 months for the occurrences of major adverse cardiac events (MACE). Results Compared with patients in normal CRP group, patients in high CRP group were more frequently to have unstable angina, multi-vessel, diffuse, eccentric lesions, positive remodeling, and non-smooth plaques (P＜0.01). Kaplan-Meier analysis showed patients in high CRP group had a significantly lower MACE-free survival rate than patients in normal CRP group (Log-rank = 12.0, P＜0.01); Cox regression analysis indicated CRP level as an independent predictor for the occurrence of MACE (OR=3.16, P＜0.05) Conclusions High CRP level is associated with more extend, severe and eccentric coronary lesions and is an independent predictor for MACE in elderly patients with CHD.
基金supported by the National Natural Science Foundation of China (No. 71271206)
文摘In order to effectively decrease the safety accidents caused by coal miners’human errors,this paper probes into the causality between human errors and life events,coping,psychological stress,psychological function,physiological function based on life events’vital influence on human errors,establishing causation mechanism model of coal miners’human errors in the perspective of life events by the researching method of structural equation.The research findings show that life events have significantly positive influence on human errors,with a influential effect value of 0.7945 and a influential effect path of‘‘life events—psychological stress—psychological function—physiological function—human errors’’and‘‘life events—psychological stress—physiological function—human errors’’.
基金supported by Natural Science Foundation of China(81470466)。
文摘Objective To investigate whether plasma big endothelin-1(ET-1) predicts ventricular arrythmias(VAs) and end-stage events in primary prevention implantable cardioverter-defibrillator(ICD) indication patigents. Methods In total, 207 patients fulfilling the inclusion criteria from Fuwai Hospital between January 2013 and December 2015 were retrospectively analyzed. The cohort was divided into three groups according to baseline plasma big ET-1 tertiles: tertile 1(< 0.38 pmol/L, n = 68), tertile 2(0.38–0.7 pmol/L, n = 69), and tertile 3(> 0.7 pmol/L, n = 70). The primary endpoints were VAs. The secondary endpoints were end-stage events comprising all-cause mortality and heart transplantation. Results During a mean follow-up period of 25.6 ± 13.9 months, 38(18.4%) VAs and 78(37.7%) end-stage events occurred. Big ET-1 was positively correlated with NYHA class(r = 0.165, P = 0.018), serum creatinine concentration(Scr;r = 0.147, P = 0.034), high-sensitivity C-reactive protein(hs-CRP;r = 0.217, P = 0.002), Lg NT-pro BNP(r = 0.463, P < 0.001), left ventricular end diastolic diameter(LVEDD;r = 0.234, P = 0.039) and negatively correlated with left ventricular ejection fraction(LVEF;r =-0.181, P = 0.032). Kaplan-Meier analysis showed that elevated big ET-1 was associated with increased risk of VAs and end-stage events(P < 0.05). In multivariate Cox regression models, big ET-1 was an independent risk factor for VAs(hazard ratio(HR) = 3.477, 95% confidence interval(CI): 1.352–8.940, P = 0.010, tertile 2 vs. tertile 1;HR = 4.112, 95% CI: 1.604–10.540, P = 0.003, tertile 3 vs. tertile 1) and end-stage events(HR = 2.804, 95% CI: 1.354–5.806, P = 0.005, tertile 2 vs. tertile 1;HR = 4.652, 95% CI: 2.288–9.459, P < 0.001, tertile 3 vs. tertile 1). Conclusions In primary prevention ICD indication patients, plasma big ET-1 levels can predict VAs and end-stage events and may facilitate ICD-implantation risk stratification.
基金Supported by the National Key R&DPlan Project(2022YFE0129900)National Natural Science Foundation of China(52074338).
文摘The existing approaches for identifying events in horizontal well fracturing are difficult, time-consuming, inaccurate, and incapable of real-time warning. Through improvement of data analysis and deep learning algorithm, together with the analysis on data and information of horizontal well fracturing in shale gas reservoirs, this paper presents a method for intelligent identification and real-time warning of diverse complex events in horizontal well fracturing. An identification model for "point" events in fracturing is established based on the Att-BiLSTM neural network, along with the broad learning system (BLS) and the BP neural network, and it realizes the intelligent identification of the start/end of fracturing, formation breakdown, instantaneous shut-in, and other events, with an accuracy of over 97%. An identification model for "phase" events in fracturing is established based on enhanced Unet++ network, and it realizes the intelligent identification of pump ball, pre-acid treatment, temporary plugging fracturing, sand plugging, and other events, with an error of less than 0.002. Moreover, a real-time prediction model for fracturing pressure is built based on the Att-BiLSTM neural network, and it realizes the real-time warning of diverse events in fracturing. The proposed method can provide an intelligent, efficient and accurate identification of events in fracturing to support the decision-making.
文摘Extreme weather events were analyzed based on the meteorological data from the year of 1967 to 2007 for Yamaguchi, Japan. The responses from landscape trees were also investigated mainly by the analysis of image pixel and spectral reflectance. Results show that after the dry, hot and windy summer in 2007, many landscape trees in Yamaguchi City tended to respond the extreme weather events by reducing their leaf surface area and receiving less radiation energy. Premature leaf discoloration or defoliation appeared on some landscape tree species and leaf necrosis occurred on tip and margin of many Kousa dogwood (Cornus kousa) trees at unfavorable sites. Described by image pixel analysis method, the leaf necrotic area percentage (LNAP) of sampled dogwood trees averaged 41.6% and the sampled Sasanqua camellia (Camelia sasanqua) tree also showed fewer flowers in flower season of 2007 than that in 2006. By differential analysis of partial discolored crown, it presented a logistic differential equation of crown color for sweet gum (Liquidambar styraciflua) trees. It suggested that the persistent higher temperature and lower precipitation could be injurious to the sensitive landscape trees at poor sites, even in relative humid area like Yamaguchi.
基金the National Natural Science Foundation of China under Grant Nos.41974116 and 41930431Local Universities Reformation and Development Personnel Training Supporting Project from Central Authorities under Grant No.140119001 for supporting this work
文摘Compared with first-order surface-related multiples from marine data,the onshore internal multiples are weaker and are always combined with a hazy and occasionally strong interference pattern.It is usually difficult to discriminate these events from complex targets and highly scattering overburdens,especially when the primary energy from deep layers is weaker than that from shallow layers.The internal multiple elimination is even more challenging due to the fact that the velocity and energy difference between primary reflections and internal multiples is tiny.In this study,we propose an improved method which formulates the elimination of the internal multiples as an optimization problem and develops a convolution factor T.The generated internal multiples at all interfaces are obtained using the convolution factor T through iterative inversion of the initial multiple model.The predicted internal multiples are removed from seismic data through subtraction.Finally,several synthetic experiments are conducted to validate the effectiveness of our approach.The results of our study indicate that compared with the traditional virtual events method,the improved method simplifies the multiple prediction process in which internal multiples generated from each interface are built through iterative inversion,thus reducing the calculation cost,improving the accuracy,and enhancing the adaptability of field data.
基金This study was funded by the International Science and Technology Cooperation Program of the Science and Technology Department of Shaanxi Province,China(No.2021KW-16)the Science and Technology Project in Xi’an(No.2019218114GXRC017CG018-GXYD17.11),Thesis work was supported by the special fund construction project of Key Disciplines in Ordinary Colleges and Universities in Shaanxi Province,the authors would like to thank the anonymous reviewers for their helpful comments and suggestions.
文摘Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.
基金Supported by the National Natural Science Foundation of China(60805028,60903146)Natural Science Foundation of Shandong Province of China (ZR2010FM027)+1 种基金SDUST Research Fund(2010KYTD101)China Postdoctoral Science Foundation(2012M521336)
文摘Video events recognition is a challenging task for high-level understanding of video se- quence. At present, there are two major limitations in existing methods for events recognition. One is that no algorithms are available to recognize events which happen alternately. The other is that the temporal relationship between atomic actions is not fully utilized. Aiming at these problems, an algo- rithm based on an extended stochastic context-free grammar （SCFG） representation is proposed for events recognition. Events are modeled by a series of atomic actions and represented by an extended SCFG. The extended SCFG can express the hierarchical structure of the events and the temporal re- lationship between the atomic actions. In comparison with previous work, the main contributions of this paper are as follows： ① Events （include alternating events） can be recognized by an improved stochastic parsing and shortest path finding algorithm. ② The algorithm can disambiguate the detec- tion results of atomic actions by event context. Experimental results show that the proposed algo- rithm can recognize events accurately and most atomic action detection errors can be corrected sim- ultaneously.
基金supported in part by the National Natural Science Foundation of China under Grant 41904098Fundamental Research Funds for the Central Universities,under Grant 2462018YJRC020 and Grant 2462020YXZZ006。
文摘The occurrence of microseismic is not random but is related to the physical properties of the underground medium.Due to the low intensity and the influence of noise,microseismic eventually lead to poor signal-to-noise ratio.We proposed a method for automatic detection of microseismic events by adoption of multiscale top-hat transformation.The method is based on the difference between the signal and noise in the multiscale top-hat transform section and achieves the detection on a specific section.The microseismic data are decomposed into different scales by multiscale morphology top-hat transformation firstly.Then the potential microseismic events could be detected by picking up the peak value in the multiscale top-hat section,and the characteristic profile obtains the start point with a specific threshold value.Finally,the synthetic data experiences demonstrate the advantages of this method under strong and weak noisy conditions,and the filed data example also shows its reliability and adaptability.
基金partially supported by the National Natural Science Foundation of China under Grant No.61203291the Specialised Research Fund for the Doctoral Program under Grant No.20121101110035
文摘The ability to recognise video events has become increasingly more popular owing to its extensive practical applications.Most events will occur in certain scene with certain people,and the scene context and group context provide important information for event recognition.In this paper,we present an algorithm to recognise video events in different scenes in which there are multiple agents.First,we recognise events for each agent based on Stochastic Context Sensitive Grammar(SCSG).Then we propose the model of a scene in order to infer the scene in which the events occur,and we use a co-occurrence matrix of events to represent the group context.Finally,the scene and group context are exploited to distinguish events having similar structures.Experimental results show that by adding the scene and group context,the performance of events recognition can be significantly improved.
