The advent of artificial intelligence(AI)in recent years has brought about transformative changes across various sectors,including healthcare.In nursing practice,education,and research,AI has the potential to revoluti...The advent of artificial intelligence(AI)in recent years has brought about transformative changes across various sectors,including healthcare.In nursing practice,education,and research,AI has the potential to revolutionize traditional methodologies,enhance learning experiences,and improve patient outcomes.Integrating AI tools and techniques can provide clinicians with smarter clinical solutions and nursing students with more robust and interactive learning environments,while also advancing research capabilities in the field.Despite the promising prospects,the incorporation of AI into nursing practice,education,and research presents several challenges.Firstly,there is a concern about the potential displacement of human roles in nursing due to automation,which may affect the human-centric nature of nursing care.Secondly,there are issues related to the lag in AI competency among nurses.Many current nursing curricula do not include comprehensive AI training,leading to a lack of preparedness in utilizing these technologies effectively.Lastly,the ethical implications of AI in healthcare,such as data privacy,patient consent,and the potential for biased algorithms,need to be meticulously addressed.To harness the full potential of AI in nursing practice,education,and research,several strategic actions including reinvesting in humanistic practice,revising core competencies and curriculum,and developing new ethical guidelines.展开更多
The presence of heterozygous individuals in a population is crucial for maintaining genetic diversity,which can positively affect fitness and adaptability to environmental changes.While inbreeding generally reduces th...The presence of heterozygous individuals in a population is crucial for maintaining genetic diversity,which can positively affect fitness and adaptability to environmental changes.While inbreeding generally reduces the proportion of heterozygous individuals in a population,polyploidy tends to increase the proportion.North American Populus tremuloides is one of the most widely distributed and ecologically important tree species in the Northern Hemisphere.However,genetic variation in Mexican populations of P.tremuloides,including the genetic signatures of their adaptation to a variety of environments,remains largely uncharacterized.The aim of this study was to analyze how inbreeding coefficient(FIS)and ploidy are associated with clonal richness,population cover,climate and soil traits in 91 marginal to small,isolated populations of this tree species throughout its entire distribution in Mexico.Genetic variables were determined using 36,810 filtered SNPs derived from genome re-sequencing.We found that FIS was approximately between 0 and e1,indicating an extreme heterozygosity excess.One key contributor to the observed extreme heterozygosity excess was asexual reproduction,although ploidy levels cannot explain this excess.Analysis of all neutral SNPs showed that asexual reproduction was positively correlated with observed heterozygosity(Ho)but negatively correlated with expected heterozygosity(He).Analysis of outlier SNPs also showed that asexual reproductionwas positively correlated with Ho and negatively correlated with He,although this latter correlation was not significant.These findings support the presence of a Meselson effect.展开更多
BACKGROUND The accurate classification of focal liver lesions(FLLs)is essential to properly guide treatment options and predict prognosis.Dynamic contrast-enhanced computed tomography(DCE-CT)is still the cornerstone i...BACKGROUND The accurate classification of focal liver lesions(FLLs)is essential to properly guide treatment options and predict prognosis.Dynamic contrast-enhanced computed tomography(DCE-CT)is still the cornerstone in the exact classification of FLLs due to its noninvasive nature,high scanning speed,and high-density resolution.Since their recent development,convolutional neural network-based deep learning techniques has been recognized to have high potential for image recognition tasks.AIM To develop and evaluate an automated multiphase convolutional dense network(MP-CDN)to classify FLLs on multiphase CT.METHODS A total of 517 FLLs scanned on a 320-detector CT scanner using a four-phase DCECT imaging protocol(including precontrast phase,arterial phase,portal venous phase,and delayed phase)from 2012 to 2017 were retrospectively enrolled.FLLs were classified into four categories:Category A,hepatocellular carcinoma(HCC);category B,liver metastases;category C,benign non-inflammatory FLLs including hemangiomas,focal nodular hyperplasias and adenomas;and category D,hepatic abscesses.Each category was split into a training set and test set in an approximate 8:2 ratio.An MP-CDN classifier with a sequential input of the fourphase CT images was developed to automatically classify FLLs.The classification performance of the model was evaluated on the test set;the accuracy and specificity were calculated from the confusion matrix,and the area under the receiver operating characteristic curve(AUC)was calculated from the SoftMax probability outputted from the last layer of the MP-CDN.RESULTS A total of 410 FLLs were used for training and 107 FLLs were used for testing.The mean classification accuracy of the test set was 81.3%(87/107).The accuracy/specificity of distinguishing each category from the others were 0.916/0.964,0.925/0.905,0.860/0.918,and 0.925/0.963 for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.The AUC(95%confidence interval)for differentiating each category from the others was 0.92(0.837-0.992),0.99(0.967-1.00),0.88(0.795-0.955)and 0.96(0.914-0.996)for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.CONCLUSION MP-CDN accurately classified FLLs detected on four-phase CT as HCC,metastases,benign non-inflammatory FLLs and hepatic abscesses and may assist radiologists in identifying the different types of FLLs.展开更多
We present a new hybrid numerical scheme for two-dimensional(2D)ideal magnetohydrodynamic(MHD)equations.A simple conservation element and solution element(CESE)method is used to calculate the flow variables,and the un...We present a new hybrid numerical scheme for two-dimensional(2D)ideal magnetohydrodynamic(MHD)equations.A simple conservation element and solution element(CESE)method is used to calculate the flow variables,and the unknown first-order spatial derivatives involved in the CESE method are computed with a finite volume scheme that uses the solution of the derivative Riemann problem with limited reconstruction to evaluate the numerical flux at cell interface position.To show the validation and capacity of its application to 2D MHD problems,we study several benchmark problems.Numerical results verify that the hybrid scheme not only performs well,but also can retain the solution quality even if the Courant number ranges from close to 1 to less than 0.01.展开更多
Our newly developed CESE MHD model is used to simulate sun-earth connection event with the well-studied 12 May 1997 CME event as an example. The main features and approximations of our numerical model are as follows：...Our newly developed CESE MHD model is used to simulate sun-earth connection event with the well-studied 12 May 1997 CME event as an example. The main features and approximations of our numerical model are as follows： （1） The modifed conservation element and solution element （CESE） numerical scheme in spherical geometry is implemented in our code. （2） The background solar wind is derived from a 3D time-dependent numerical MHD model by input measured photospheric magnetic fields. （3） Transient disturbances are derived from solar surface by introducing a mass flow of hot plasma. The numerical simulation has enabled us to predict the arrival of the interplanetary shock and provided us with a relatively satisfactory comparison with the WIND spacecraft observations.展开更多
The sun-grazing comet C/2011 W3(Lovejoy)showed a distorted,unconventional tail morphology near its perihelion(1.2Rs).Based on the“Solar Corona and Inner Heliosphere”modeling result of the magnetic field and plasma d...The sun-grazing comet C/2011 W3(Lovejoy)showed a distorted,unconventional tail morphology near its perihelion(1.2Rs).Based on the“Solar Corona and Inner Heliosphere”modeling result of the magnetic field and plasma dynamics in the solar corona,we use the Runge-Kutta method to simulate the moving trajectory of charged dust and ion particles released at different positions from the C/2011 W3 orbit.We find that the dust particles near the sun,which are subject to a strong magnetic Lorentz force,travel differently from their counterparts distant from the sun,where the latter are mainly affected by the solar gravitational force and radiation pressure.According to the simulation results,we propose that the magnetic mirror effect can rebound the charged dust particles back away from the sun and be regarded as one crucial cause of the dust-free zone formation.We find that ions mainly move along magnetic field lines at an acute angle to the comet's direction of motion.The cometary ions'movement direction was determined by the comet's velocity and the coronal magnetic field,which are responsible for the C/2011 W3’s unique comet tail shape near perihelion.Additionally,the ion particles also experience perpendicular drift motion,mainly dominated by the electric field drift,which is similar to and can be used to approximate the solar wind's transverse velocity at its source region.展开更多
文摘The advent of artificial intelligence(AI)in recent years has brought about transformative changes across various sectors,including healthcare.In nursing practice,education,and research,AI has the potential to revolutionize traditional methodologies,enhance learning experiences,and improve patient outcomes.Integrating AI tools and techniques can provide clinicians with smarter clinical solutions and nursing students with more robust and interactive learning environments,while also advancing research capabilities in the field.Despite the promising prospects,the incorporation of AI into nursing practice,education,and research presents several challenges.Firstly,there is a concern about the potential displacement of human roles in nursing due to automation,which may affect the human-centric nature of nursing care.Secondly,there are issues related to the lag in AI competency among nurses.Many current nursing curricula do not include comprehensive AI training,leading to a lack of preparedness in utilizing these technologies effectively.Lastly,the ethical implications of AI in healthcare,such as data privacy,patient consent,and the potential for biased algorithms,need to be meticulously addressed.To harness the full potential of AI in nursing practice,education,and research,several strategic actions including reinvesting in humanistic practice,revising core competencies and curriculum,and developing new ethical guidelines.
基金We thank the Mexican Consejo Nacional de Humanidades,Ciencias y Tecnologías(CONAHCYT)for the financial support provided to the first author to carry out his training in the Institutional Doctoral Program in Agricultural and Forestry Sciences(PIDCAFUJED)with Scholarship No.334852financial support with agreement number CONACYT-FRQ-2016:279459 for the project“Genome-wide scans for detecting adaptation to climate and soil in Populus tremuloides as the most widely distributed tree species in North America”Dr.Jesús M.Olivas-García assisted in the sampling in the state of Chihuahua,Mexico,and Katrin Groppe,Thünen Institute of Forest Genetics,Germany,provided excellent lab work.The Emerging Leaders of the Americas Program(ELAP)of the Government of Canada awarded a scholarship and the Institute of Integrative and Systems Biology(IBIS)of Laval University allowed the use of its campus and contributed to the training of the first author.
文摘The presence of heterozygous individuals in a population is crucial for maintaining genetic diversity,which can positively affect fitness and adaptability to environmental changes.While inbreeding generally reduces the proportion of heterozygous individuals in a population,polyploidy tends to increase the proportion.North American Populus tremuloides is one of the most widely distributed and ecologically important tree species in the Northern Hemisphere.However,genetic variation in Mexican populations of P.tremuloides,including the genetic signatures of their adaptation to a variety of environments,remains largely uncharacterized.The aim of this study was to analyze how inbreeding coefficient(FIS)and ploidy are associated with clonal richness,population cover,climate and soil traits in 91 marginal to small,isolated populations of this tree species throughout its entire distribution in Mexico.Genetic variables were determined using 36,810 filtered SNPs derived from genome re-sequencing.We found that FIS was approximately between 0 and e1,indicating an extreme heterozygosity excess.One key contributor to the observed extreme heterozygosity excess was asexual reproduction,although ploidy levels cannot explain this excess.Analysis of all neutral SNPs showed that asexual reproduction was positively correlated with observed heterozygosity(Ho)but negatively correlated with expected heterozygosity(He).Analysis of outlier SNPs also showed that asexual reproductionwas positively correlated with Ho and negatively correlated with He,although this latter correlation was not significant.These findings support the presence of a Meselson effect.
基金Supported by National Natural Science Foundation of China,No.91959118Science and Technology Program of Guangzhou,China,No.201704020016+1 种基金SKY Radiology Department International Medical Research Foundation of China,No.Z-2014-07-1912-15Clinical Research Foundation of the 3rd Affiliated Hospital of Sun Yat-Sen University,No.YHJH201901.
文摘BACKGROUND The accurate classification of focal liver lesions(FLLs)is essential to properly guide treatment options and predict prognosis.Dynamic contrast-enhanced computed tomography(DCE-CT)is still the cornerstone in the exact classification of FLLs due to its noninvasive nature,high scanning speed,and high-density resolution.Since their recent development,convolutional neural network-based deep learning techniques has been recognized to have high potential for image recognition tasks.AIM To develop and evaluate an automated multiphase convolutional dense network(MP-CDN)to classify FLLs on multiphase CT.METHODS A total of 517 FLLs scanned on a 320-detector CT scanner using a four-phase DCECT imaging protocol(including precontrast phase,arterial phase,portal venous phase,and delayed phase)from 2012 to 2017 were retrospectively enrolled.FLLs were classified into four categories:Category A,hepatocellular carcinoma(HCC);category B,liver metastases;category C,benign non-inflammatory FLLs including hemangiomas,focal nodular hyperplasias and adenomas;and category D,hepatic abscesses.Each category was split into a training set and test set in an approximate 8:2 ratio.An MP-CDN classifier with a sequential input of the fourphase CT images was developed to automatically classify FLLs.The classification performance of the model was evaluated on the test set;the accuracy and specificity were calculated from the confusion matrix,and the area under the receiver operating characteristic curve(AUC)was calculated from the SoftMax probability outputted from the last layer of the MP-CDN.RESULTS A total of 410 FLLs were used for training and 107 FLLs were used for testing.The mean classification accuracy of the test set was 81.3%(87/107).The accuracy/specificity of distinguishing each category from the others were 0.916/0.964,0.925/0.905,0.860/0.918,and 0.925/0.963 for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.The AUC(95%confidence interval)for differentiating each category from the others was 0.92(0.837-0.992),0.99(0.967-1.00),0.88(0.795-0.955)and 0.96(0.914-0.996)for HCC,metastases,benign non-inflammatory FLLs,and abscesses on the test set,respectively.CONCLUSION MP-CDN accurately classified FLLs detected on four-phase CT as HCC,metastases,benign non-inflammatory FLLs and hepatic abscesses and may assist radiologists in identifying the different types of FLLs.
基金Supported by the National Basic Research Program of China under Grant No 2012CB825601the National Natural Science Foundation of China under Grant Nos 40921063,41031066,40890162,40904050,41074121 and 41074122the Specialized Research Fund for State Key Laboratories.
文摘We present a new hybrid numerical scheme for two-dimensional(2D)ideal magnetohydrodynamic(MHD)equations.A simple conservation element and solution element(CESE)method is used to calculate the flow variables,and the unknown first-order spatial derivatives involved in the CESE method are computed with a finite volume scheme that uses the solution of the derivative Riemann problem with limited reconstruction to evaluate the numerical flux at cell interface position.To show the validation and capacity of its application to 2D MHD problems,we study several benchmark problems.Numerical results verify that the hybrid scheme not only performs well,but also can retain the solution quality even if the Courant number ranges from close to 1 to less than 0.01.
基金Supported by the National Natural Science Foundation of China under Grant Nos 40621003, 40536029, 40504020, and 40523006, the National Basic Research Programme of China under Grant No 2006CB806304, and the CAS International Partnership Programme for Creative Research Teams. Dr S. T. Wu is supported by AFOSR under Grant No FA 9550-07-1-0468 and NSF ATM036115.
文摘Our newly developed CESE MHD model is used to simulate sun-earth connection event with the well-studied 12 May 1997 CME event as an example. The main features and approximations of our numerical model are as follows： （1） The modifed conservation element and solution element （CESE） numerical scheme in spherical geometry is implemented in our code. （2） The background solar wind is derived from a 3D time-dependent numerical MHD model by input measured photospheric magnetic fields. （3） Transient disturbances are derived from solar surface by introducing a mass flow of hot plasma. The numerical simulation has enabled us to predict the arrival of the interplanetary shock and provided us with a relatively satisfactory comparison with the WIND spacecraft observations.
基金supported by NSFC under contracts No.41874200 and 41421003supported by CNSA under contracts No.D020301 and D020302.
文摘The sun-grazing comet C/2011 W3(Lovejoy)showed a distorted,unconventional tail morphology near its perihelion(1.2Rs).Based on the“Solar Corona and Inner Heliosphere”modeling result of the magnetic field and plasma dynamics in the solar corona,we use the Runge-Kutta method to simulate the moving trajectory of charged dust and ion particles released at different positions from the C/2011 W3 orbit.We find that the dust particles near the sun,which are subject to a strong magnetic Lorentz force,travel differently from their counterparts distant from the sun,where the latter are mainly affected by the solar gravitational force and radiation pressure.According to the simulation results,we propose that the magnetic mirror effect can rebound the charged dust particles back away from the sun and be regarded as one crucial cause of the dust-free zone formation.We find that ions mainly move along magnetic field lines at an acute angle to the comet's direction of motion.The cometary ions'movement direction was determined by the comet's velocity and the coronal magnetic field,which are responsible for the C/2011 W3’s unique comet tail shape near perihelion.Additionally,the ion particles also experience perpendicular drift motion,mainly dominated by the electric field drift,which is similar to and can be used to approximate the solar wind's transverse velocity at its source region.
