Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the sout...Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.展开更多
An in-depth understanding of the fracture behavior and mechanism of metallic shells under internal explosive loading can help develop material designs for warheads and regulate the quantity and mass distribution of th...An in-depth understanding of the fracture behavior and mechanism of metallic shells under internal explosive loading can help develop material designs for warheads and regulate the quantity and mass distribution of the fragments formed.This study investigated the fragmentation performance of a new high-carbon silicon-manganese(HCSiMn)steel cylindrical shell through fragment recovery experiments.Compared with the conventional 45Cr steel shell,the number of small mass fragments produced by the HCSi Mn steel shell was significantly increased with a scale parameter of 0.57 g fitted by the Weibull distribution model.The fragmentation process of the HCSi Mn shell exhibited more brittle tensile fracture characteristics,with the microcrack damage zone on the outer surface being the direct cause of its high fragmentation.On the one hand,the doping of alloy elements resulted in grain refinement by forming metallographic structure of tempered sorbite,so that microscopic intergranular fracture reduces the characteristic mass of the fragments;on the other hand,the distribution of alloy carbides can exert a"pinning"effect on the substrate grains,causing more initial cracks to form and propagate along the brittle carbides,further improving the shell fragmentation.Although the killing power radius for light armored vehicles was slightly reduced by about 6%,the dense killing radius of HCSiMn steel projectile against personnel can be significantly increased by about 26%based on theoretical assessment.These results provided an experimental basis for high fragmentation warhead design,and to some extent,revealed the correlation mechanism between metallographic structure and shell fragmentation.展开更多
This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological population.ABO is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and ...This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological population.ABO is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and eliminating.The foraging behavior prompts the bison to seek a richer food source for survival.When bison find a food source,they stick around for a while by bathing behavior.The jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating behavior.The eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent individuals.The above behaviors are translated into ABO by mathematical modeling.To assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with constraints.The findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.展开更多
The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces ...The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.展开更多
Recent experimental and theoretical work has focused on two-dimensional van der Waals(2D vdW)magnets due to their potential applications in sensing and spintronics devises.In measurements of these emerging materials,c...Recent experimental and theoretical work has focused on two-dimensional van der Waals(2D vdW)magnets due to their potential applications in sensing and spintronics devises.In measurements of these emerging materials,conventional magnetometry often encounters challenges in characterizing the magnetic properties of small-sized vdW materials,especially for antiferromagnets with nearly compensated magnetic moments.Here,we investigate the magnetism of 2D antiferromagnet CrPS_(4)with a thickness of 8nm by using dynamic cantilever magnetometry(DCM).展开更多
Biological specimens play an important role in cultural exchange, science popularization, scientific research and economic window, but the preparation and preservation technology system of biological specimens is rela...Biological specimens play an important role in cultural exchange, science popularization, scientific research and economic window, but the preparation and preservation technology system of biological specimens is relatively unsafe and inefficient. Mold grows seriously on animal specimens, which is not only harmful to human beings’ health and environment, but also is one of the factors that restricts the development of the natural history museums where these specimens are kept. This paper identified the mold species of animal specimens by PCR with ITS primers, bio-micro-scopic observation, sequencing and phylogenetic tree analysis. The results showed the mold of animal specimens mainly belonged to Aspergillus and Neurospora. This study established the foundations of controlling and restoring the mold that infected animal specimens and guided a new methodology of preparation and environmental friendly exhibition for animal specimens.展开更多
Background:Inflammation-based indexes have been used to predict survival and recurrence in cancer patients.Systemic immune-inflammation index(Sll) was reported to be associated with prognosis in some malignant tumors....Background:Inflammation-based indexes have been used to predict survival and recurrence in cancer patients.Systemic immune-inflammation index(Sll) was reported to be associated with prognosis in some malignant tumors.In the present study,we aimed to explore the association between Sll and the prognosis of patients with gastric cancer.Methods:We retrospectively analyzed data from 444 gastric cancer patients who underwent gastrectomy at the First Affiliated Hospital of Sun Yat-sen University between January 1994 and December 2005.Preoperative Sll was calculated.The Chi square test or Fisher's exact test was used to determine the relationship between preoperative Sll and clinicopathologic characteristics.Overall survival(OS) rates were estimated using the Kaplan-Meier method,and the effect of Sll on OS was analyzed using the Cox proportional hazards model.Receiver operating characteristic(ROC)curves were used to compare the predictive ability of Sll,NLR,and PLR.Results:Sll equal to or higher than 660 was significantly associated with old age,large tumor size,unfavorable Borrmann classification,advanced tumor invasion,lymph node metastasis,distant metastasis,advanced TNM stage,and high carcino-embryonic antigen level,high neutrophil-lymphocyte ratio,and high platelet-lymphocyte ratio(all P<0.05).High Sll was significantly associated with unfavorable prognosis(P<0.001) and Sll was an independent predictor for OS(P=0.015).Subgroups analysis further showed significant associations between high Sll and short OS in stage Ⅰ,Ⅱ,Ⅲ subgroups(all P<0.05).Sll was superior to NLR and PLR for predicting OS in patients with gastric cancer.Conclusion:Preoperative Sll level is an independent prognostic factor for OS in patients with gastric cancer.展开更多
Facile preparation of cost-effective and durable porous carbon-supported non-precious-metal/nitrogen electrocatalysts for oxygen reduction reaction(ORR)is extremely important for promoting the commercialized applicati...Facile preparation of cost-effective and durable porous carbon-supported non-precious-metal/nitrogen electrocatalysts for oxygen reduction reaction(ORR)is extremely important for promoting the commercialized applications of such catalysts.In this work,the FeCl3-containing porphyrinato iron-based covalent porous polymer(FeCl3·FeP or-CPP)was fabricated in-situ onto porous corncob biomass supports via a simple one-pot method.Subsequent thermal-reduction pyrolysis at 700℃-900℃with CO2 gas as an activating agent resulted in Fe2O3-decorated and N-doped graphitic carbon composite Fe2O3@NC&bio-C with a high degree of graphitization of Fe-involved promotion during pyrolysis(Fe2O3=FeCl3·FePor-CPP derived Fe2O3;NC=N-doped graphene analog;bio-C=the corncob-derived hierarchically porous graphitic biomass carbon framework).The derivedα-Fe2O3 andγ-Fe2O3 nanocrystals(5-10 nm particle diameter)were all immobilized on the N-doped bio-C micro/nanofibers.Notably,the Fe2O3@NC&bio-C obtained at the pyrolysis temperature of 800℃(Fe2O3@NC&bio-C-800),exhibited unusual ORR catalytic efficiency via a 4-electron pathway with the onset and half-wave potentials of 0.96 V and 0.85 V vs.RHE,respectively.In addition,Fe2O3@NC&bio-C-800 also exhibited a high and stable limiting current density of-6.0 mA cm-2,remarkably stability(larger than 91%retention after 10000 s),and good methanol tolerance.The present work represents one of the best results for iron-based biomass material ORR catalysts reported to date.The high ORR activity is attributed to the uniformly distributedα-Fe2O3 andγ-Fe2O3 nanoparticles on the N-enriched carbon matrix with a large specific surface area of 772.6 m^2 g^-1.This facilitates favor faster electron movement and better adsorption of oxygen molecules on the surface of the catalyst.Nevertheless,comparative studies on the structure and ORR catalytic activity of Fe2O3@NC&bioC-800 with Fe2O3@bio-C-800 and NC&bio-C-800 clearly highlight the synergistic effect of the coexisting Fe2O3 nanocrystals,NC,and bio-C on the ORR performance.展开更多
基金the financial support of the National Key R&D Program of China(2021YFC3000701)the China Seismic Experimental Site in Sichuan-Yunnan(CSES-SY)。
文摘Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses.In this study,we propose an automatic workflow based on machine learning(ML)to monitor seismicity in the southern Sichuan Basin of China.This workflow includes coherent event detection,phase picking,and earthquake location using three-component data from a seismic network.By combining Phase Net,we develop an ML-based earthquake location model called Phase Loc,to conduct real-time monitoring of the local seismicity.The approach allows us to use synthetic samples covering the entire study area to train Phase Loc,addressing the problems of insufficient data samples,imbalanced data distribution,and unreliable labels when training with observed data.We apply the trained model to observed data recorded in the southern Sichuan Basin,China,between September 2018 and March 2019.The results show that the average differences in latitude,longitude,and depth are 5.7 km,6.1 km,and 2 km,respectively,compared to the reference catalog.Phase Loc combines all available phase information to make fast and reliable predictions,even if only a few phases are detected and picked.The proposed workflow may help real-time seismic monitoring in other regions as well.
基金funded by the National Natural Science Foundation of China (Grant Nos.12302444 and 12202349)。
文摘An in-depth understanding of the fracture behavior and mechanism of metallic shells under internal explosive loading can help develop material designs for warheads and regulate the quantity and mass distribution of the fragments formed.This study investigated the fragmentation performance of a new high-carbon silicon-manganese(HCSiMn)steel cylindrical shell through fragment recovery experiments.Compared with the conventional 45Cr steel shell,the number of small mass fragments produced by the HCSi Mn steel shell was significantly increased with a scale parameter of 0.57 g fitted by the Weibull distribution model.The fragmentation process of the HCSi Mn shell exhibited more brittle tensile fracture characteristics,with the microcrack damage zone on the outer surface being the direct cause of its high fragmentation.On the one hand,the doping of alloy elements resulted in grain refinement by forming metallographic structure of tempered sorbite,so that microscopic intergranular fracture reduces the characteristic mass of the fragments;on the other hand,the distribution of alloy carbides can exert a"pinning"effect on the substrate grains,causing more initial cracks to form and propagate along the brittle carbides,further improving the shell fragmentation.Although the killing power radius for light armored vehicles was slightly reduced by about 6%,the dense killing radius of HCSiMn steel projectile against personnel can be significantly increased by about 26%based on theoretical assessment.These results provided an experimental basis for high fragmentation warhead design,and to some extent,revealed the correlation mechanism between metallographic structure and shell fragmentation.
基金the National Natural Science Foundation of China(Grant No.U1731128)the Natural Science Foundation of Liaoning Province(Grant No.2019-MS-174)+1 种基金the Foundation of Liaoning Province Education Administration(Grant No.LJKZ0279)the Team of Artificial Intelligence Theory and Application for the financial support.
文摘This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological population.ABO is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and eliminating.The foraging behavior prompts the bison to seek a richer food source for survival.When bison find a food source,they stick around for a while by bathing behavior.The jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating behavior.The eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent individuals.The above behaviors are translated into ABO by mathematical modeling.To assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with constraints.The findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.
基金the financial support of the National Key R&D Program of China(2021YFC3000701)the China Seismic Experimental Site in Sichuan-Yunnan(CSES-SY)for providing data for this study.
文摘The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.
基金supported by the National Key R&D Program of China(Grant No.2022YFA1602602)the National Natural Science Foundation of China(Grant Nos.12122411 and 12474053)+4 种基金CAS Project for Young Scientists in Basic Research(Grant No.YSBR-084)HFIPS Director’s Fund(Grant Nos.2023BR,YZJJ-GGZX-2022-03,and YZJJ202403TS)HFIPS Director’s Fud(Grant No.BJPY2021B05)the Basic Research Program of the Chinese Academy of Sciences Based on Major Scientific Infrastructures(Grant No.JZHKYPT-2021-08)the High Magnetic Field Laboratory of Anhui Province(Grant No.AHHM-FX2020-02)。
文摘Recent experimental and theoretical work has focused on two-dimensional van der Waals(2D vdW)magnets due to their potential applications in sensing and spintronics devises.In measurements of these emerging materials,conventional magnetometry often encounters challenges in characterizing the magnetic properties of small-sized vdW materials,especially for antiferromagnets with nearly compensated magnetic moments.Here,we investigate the magnetism of 2D antiferromagnet CrPS_(4)with a thickness of 8nm by using dynamic cantilever magnetometry(DCM).
基金Scientific Research Project of Department of Education of Zhejiang Province(Y201635204)the Construction Project of Bilingual Courses of Hangzhou Municipal Bureau of Education(HJGS [2013]55_23)the Research Project of the Collaborative Innovation Center of Application Technology of Hangzhou Vocational and Technical College(MT2017_01)~~
文摘Biological specimens play an important role in cultural exchange, science popularization, scientific research and economic window, but the preparation and preservation technology system of biological specimens is relatively unsafe and inefficient. Mold grows seriously on animal specimens, which is not only harmful to human beings’ health and environment, but also is one of the factors that restricts the development of the natural history museums where these specimens are kept. This paper identified the mold species of animal specimens by PCR with ITS primers, bio-micro-scopic observation, sequencing and phylogenetic tree analysis. The results showed the mold of animal specimens mainly belonged to Aspergillus and Neurospora. This study established the foundations of controlling and restoring the mold that infected animal specimens and guided a new methodology of preparation and environmental friendly exhibition for animal specimens.
基金supported by the National Key Research and Development Program of China(2017YFA0700500)the National Natural Science Foundation of China(No.21635004,No.21627806)the Excellent Research Program of Nanjing University(No.ZYJH004)。
基金supported by the National Natural Science Foundation of China(Grant No.81372341)the PhD Start-up Fund of the Natural Science Foundation of Guangdong Province,China(Grant No.2014A030310111)the"3&3"project of the First Affiliated Hospital of Sun Yat-sen University
文摘Background:Inflammation-based indexes have been used to predict survival and recurrence in cancer patients.Systemic immune-inflammation index(Sll) was reported to be associated with prognosis in some malignant tumors.In the present study,we aimed to explore the association between Sll and the prognosis of patients with gastric cancer.Methods:We retrospectively analyzed data from 444 gastric cancer patients who underwent gastrectomy at the First Affiliated Hospital of Sun Yat-sen University between January 1994 and December 2005.Preoperative Sll was calculated.The Chi square test or Fisher's exact test was used to determine the relationship between preoperative Sll and clinicopathologic characteristics.Overall survival(OS) rates were estimated using the Kaplan-Meier method,and the effect of Sll on OS was analyzed using the Cox proportional hazards model.Receiver operating characteristic(ROC)curves were used to compare the predictive ability of Sll,NLR,and PLR.Results:Sll equal to or higher than 660 was significantly associated with old age,large tumor size,unfavorable Borrmann classification,advanced tumor invasion,lymph node metastasis,distant metastasis,advanced TNM stage,and high carcino-embryonic antigen level,high neutrophil-lymphocyte ratio,and high platelet-lymphocyte ratio(all P<0.05).High Sll was significantly associated with unfavorable prognosis(P<0.001) and Sll was an independent predictor for OS(P=0.015).Subgroups analysis further showed significant associations between high Sll and short OS in stage Ⅰ,Ⅱ,Ⅲ subgroups(all P<0.05).Sll was superior to NLR and PLR for predicting OS in patients with gastric cancer.Conclusion:Preoperative Sll level is an independent prognostic factor for OS in patients with gastric cancer.
基金the National Natural Science Foundation of China(Nos.21771192,21631003,21871024)the Major Program of Shandong Province Natural Science Foundation(No.ZR2017ZB0315)+2 种基金Fundamental Research Funds for the Central Universities(Nos.18CX06001A,19CX05001A)Research Foundation from China University of Petroleum(East China)(No.Y1510051)Taishan Scholar Program of Shandong Province(ts201712019,ts201511019).
文摘Facile preparation of cost-effective and durable porous carbon-supported non-precious-metal/nitrogen electrocatalysts for oxygen reduction reaction(ORR)is extremely important for promoting the commercialized applications of such catalysts.In this work,the FeCl3-containing porphyrinato iron-based covalent porous polymer(FeCl3·FeP or-CPP)was fabricated in-situ onto porous corncob biomass supports via a simple one-pot method.Subsequent thermal-reduction pyrolysis at 700℃-900℃with CO2 gas as an activating agent resulted in Fe2O3-decorated and N-doped graphitic carbon composite Fe2O3@NC&bio-C with a high degree of graphitization of Fe-involved promotion during pyrolysis(Fe2O3=FeCl3·FePor-CPP derived Fe2O3;NC=N-doped graphene analog;bio-C=the corncob-derived hierarchically porous graphitic biomass carbon framework).The derivedα-Fe2O3 andγ-Fe2O3 nanocrystals(5-10 nm particle diameter)were all immobilized on the N-doped bio-C micro/nanofibers.Notably,the Fe2O3@NC&bio-C obtained at the pyrolysis temperature of 800℃(Fe2O3@NC&bio-C-800),exhibited unusual ORR catalytic efficiency via a 4-electron pathway with the onset and half-wave potentials of 0.96 V and 0.85 V vs.RHE,respectively.In addition,Fe2O3@NC&bio-C-800 also exhibited a high and stable limiting current density of-6.0 mA cm-2,remarkably stability(larger than 91%retention after 10000 s),and good methanol tolerance.The present work represents one of the best results for iron-based biomass material ORR catalysts reported to date.The high ORR activity is attributed to the uniformly distributedα-Fe2O3 andγ-Fe2O3 nanoparticles on the N-enriched carbon matrix with a large specific surface area of 772.6 m^2 g^-1.This facilitates favor faster electron movement and better adsorption of oxygen molecules on the surface of the catalyst.Nevertheless,comparative studies on the structure and ORR catalytic activity of Fe2O3@NC&bioC-800 with Fe2O3@bio-C-800 and NC&bio-C-800 clearly highlight the synergistic effect of the coexisting Fe2O3 nanocrystals,NC,and bio-C on the ORR performance.
