The High-energy Fragment Separator(HFRS),which is currently under construction,is a leading international radioactive beam device.Multiple sets of position-sensitive twin time projection chamber(TPC)detectors are dist...The High-energy Fragment Separator(HFRS),which is currently under construction,is a leading international radioactive beam device.Multiple sets of position-sensitive twin time projection chamber(TPC)detectors are distributed on HFRS for particle identification and beam monitoring.The twin TPCs'readout electronics system operates in a trigger-less mode due to its high counting rate,leading to a challenge of handling large amounts of data.To address this problem,we introduced an event-building algorithm.This algorithm employs a hierarchical processing strategy to compress data during transmission and aggregation.In addition,it reconstructs twin TPCs'events online and stores only the reconstructed particle information,which significantly reduces the burden on data transmission and storage resources.Simulation studies demonstrated that the algorithm accurately matches twin TPCs'events and reduces more than 98%of the data volume at a counting rate of 500 kHz/channel.展开更多
Polyhedral boranes are a class of well-known boron molecular clusters with unique physical and chemical properties,and great efforts have been made in the past decades to find more effective synthetic methods.However,...Polyhedral boranes are a class of well-known boron molecular clusters with unique physical and chemical properties,and great efforts have been made in the past decades to find more effective synthetic methods.However,the established synthetic methods suffer from low efficiency and low selectivity because the mechanism of the B-H bond condensation reaction,critical for the synthesis of the polyhedral boranes,is not well understood.Here we report highly selective and efficient synthetic methods of the salts of the tetradecahydridoundecaborate(1-)(B_(11)H^(-)_(14)) and dodecahydrido-dodecaborates(2-)(B_(12)H_(12)^(2-)) anions by employing commercially available and inexpensive starting materials.Both theoretical and experimental investigations are carried out to elucidate the reaction mechanisms.We have found that the nature of the B-H bond condensation is the dihydrogen bonding interaction in which the positively charged hydrogens(bridged hydrogens) play a crucial role.The current study has not only led to more effective and selective synthetic methods for B_(11)H^(-)_(14) and B_(12)H_(12)^(2-) but also unveiled the nature of the B-H bond condensation and the general formation mechanisms of polyhedral boranes.This finding will facilitate the development of more effective synthetic methods for polyhedral boranes and spur their wide application.展开更多
Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospita...Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospitalized or intensive care patients are currently available,prognostic models developed for large cohorts of thousands of individuals are still lacking.Methods Between February 4 and April 16,2020,we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital,Hubei Province,China.(1)Screening of key prognostic factors:A univariate Cox regression analysis was performed on 2,649 patients in the training set,and factors affecting prognosis were initially screened.Subsequently,a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis.Finally,multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis.(2)Establishment of a scoring system:The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors,calculated the C index,drew calibration curves and drew training set patient survival curves.(3)Verification of the scoring system:The scoring system assessed 1,325 patients in the test set,splitting them into high-and low-risk groups,calculated the C-index,and drew calibration and survival curves.Results The cross-sectional study found that age,clinical classification,sex,pulmonary insufficiency,hypoproteinemia,and four other factors(underlying diseases:blood diseases,malignant tumor;complications:digestive tract bleeding,heart dysfunction)have important significance for the prognosis of the enrolled patients with COVID-19.Herein,we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19.Meanwhile,the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high-and low-risk groups(using a scoring threshold of 117.77,a score below which is considered low risk).The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines(C indexes,0.95 vs.0.89).Conclusions Age,clinical typing,sex,pulmonary insufficiency,hypoproteinemia,and four other factors were important for COVID-19 survival.Compared with general statistical methods,this method can quickly and accurately screen out the relevant factors affecting prognosis,provide an order of importance,and establish a scoring system based on the nomogram model,which is of great clinical significance.展开更多
基金partially supported by the Strategic Priority Research Program of Chinese Academy of Science(No.XDB 34030000)the National Natural Science Foundation of China(Nos.11975293 and 12205348)。
文摘The High-energy Fragment Separator(HFRS),which is currently under construction,is a leading international radioactive beam device.Multiple sets of position-sensitive twin time projection chamber(TPC)detectors are distributed on HFRS for particle identification and beam monitoring.The twin TPCs'readout electronics system operates in a trigger-less mode due to its high counting rate,leading to a challenge of handling large amounts of data.To address this problem,we introduced an event-building algorithm.This algorithm employs a hierarchical processing strategy to compress data during transmission and aggregation.In addition,it reconstructs twin TPCs'events online and stores only the reconstructed particle information,which significantly reduces the burden on data transmission and storage resources.Simulation studies demonstrated that the algorithm accurately matches twin TPCs'events and reduces more than 98%of the data volume at a counting rate of 500 kHz/channel.
基金supported by the National Natural Science Foundation of China(22171246,U1804253 to X.C.and 21773214 to D.W.)the National Science Foundation(CHE-2053541 to L.-S.W.)。
文摘Polyhedral boranes are a class of well-known boron molecular clusters with unique physical and chemical properties,and great efforts have been made in the past decades to find more effective synthetic methods.However,the established synthetic methods suffer from low efficiency and low selectivity because the mechanism of the B-H bond condensation reaction,critical for the synthesis of the polyhedral boranes,is not well understood.Here we report highly selective and efficient synthetic methods of the salts of the tetradecahydridoundecaborate(1-)(B_(11)H^(-)_(14)) and dodecahydrido-dodecaborates(2-)(B_(12)H_(12)^(2-)) anions by employing commercially available and inexpensive starting materials.Both theoretical and experimental investigations are carried out to elucidate the reaction mechanisms.We have found that the nature of the B-H bond condensation is the dihydrogen bonding interaction in which the positively charged hydrogens(bridged hydrogens) play a crucial role.The current study has not only led to more effective and selective synthetic methods for B_(11)H^(-)_(14) and B_(12)H_(12)^(2-) but also unveiled the nature of the B-H bond condensation and the general formation mechanisms of polyhedral boranes.This finding will facilitate the development of more effective synthetic methods for polyhedral boranes and spur their wide application.
基金supported by National Key Research and Development Program of China(2020YFC2002706).
文摘Background The global spread of coronavirus disease 2019(COVID-19)continues to threaten human health security,exerting considerable pressure on healthcare systems worldwide.While prognostic models for COVID-19 hospitalized or intensive care patients are currently available,prognostic models developed for large cohorts of thousands of individuals are still lacking.Methods Between February 4 and April 16,2020,we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital,Hubei Province,China.(1)Screening of key prognostic factors:A univariate Cox regression analysis was performed on 2,649 patients in the training set,and factors affecting prognosis were initially screened.Subsequently,a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis.Finally,multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis.(2)Establishment of a scoring system:The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors,calculated the C index,drew calibration curves and drew training set patient survival curves.(3)Verification of the scoring system:The scoring system assessed 1,325 patients in the test set,splitting them into high-and low-risk groups,calculated the C-index,and drew calibration and survival curves.Results The cross-sectional study found that age,clinical classification,sex,pulmonary insufficiency,hypoproteinemia,and four other factors(underlying diseases:blood diseases,malignant tumor;complications:digestive tract bleeding,heart dysfunction)have important significance for the prognosis of the enrolled patients with COVID-19.Herein,we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19.Meanwhile,the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high-and low-risk groups(using a scoring threshold of 117.77,a score below which is considered low risk).The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines(C indexes,0.95 vs.0.89).Conclusions Age,clinical typing,sex,pulmonary insufficiency,hypoproteinemia,and four other factors were important for COVID-19 survival.Compared with general statistical methods,this method can quickly and accurately screen out the relevant factors affecting prognosis,provide an order of importance,and establish a scoring system based on the nomogram model,which is of great clinical significance.
