Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 ...Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.展开更多
The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wo...The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n<sub>0</sub> (number of zeros) and n<sub>1</sub> (number of ones), as well as the number of runs. Fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using Friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.展开更多
The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software w...The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.展开更多
BACKGROUND Giant congenital biliary dilation(CBD)is a rare condition observed in clinical practice.Infants born with this condition often experience a poor overall health status,and the disease progresses rapidly,lead...BACKGROUND Giant congenital biliary dilation(CBD)is a rare condition observed in clinical practice.Infants born with this condition often experience a poor overall health status,and the disease progresses rapidly,leading to severe biliary obstruction,infections,pressure exerted by the enlarged CBD on abdominal organs,disturbances in the internal environment,and multiple organ dysfunction.The treatment of giant CBD using laparoscopy is challenging due to the high degree of variation in the shape of the bile duct and other organs,making it difficult to separate the bile duct wall from adjacent tissues or to control bleeding.CASE SUMMARY Herein,we present the details of an 11-d-old male newborn who was diagnosed with giant CBD.The patient was admitted to the neonatal surgery department of our hospital due to a history of common bile duct cyst that was detected more than 3 mo ago,and also because the patient had been experiencing yellowish skin for the past 9 d.The abnormal echo in the fetal abdomen was first noticed by the patient’s mother during a routine ultrasound examination at a local hospital,when the patient was at 24 wk+6 d of pregnancy.This finding raised concerns about the possibility of congenital biliary dilatation(22 mm×21 mm).Subsequent ultrasound examinations at different hospitals consistently confirmed the presence of a congenital biliary dilatation.No specific treatment was administered for biliary dilatation during this period.A computed tomography scan conducted during the hospitalization revealed a large cystic mass in the right upper quadrant and pelvis,measuring approximately 9.2 cm×7.4 cm×11.3 cm.Based on the CONCLUSION The analysis reveals that prenatal imaging techniques,such as ultrasound and magnetic resonance imaging,play a crucial role in the early diagnosis,fetal prognosis,and treatment plan for giant CBD.Laparoscopic surgery for giant CBD presents certain challenges,including difficulties in separating the cyst wall,anastomosis,and hemostasis,as well as severe biliary system infection and ulceration.Consequently,there is a high likelihood of converting to laparotomy.The choice between surgical methods like hepaticojejunostomy(HJ)or hepaticoduodenostomy has not been standardized yet.However,we have achieved favorable outcomes using HJ.Preoperative management of inflammation,biliary drainage,liver function protection,and supportive treatment are particularly vital in improving children’s prognosis.After discharge,it is essential to conduct timely reexamination and close follow-up to identify potential complications.展开更多
Lithospheric structure beneath the northeastern Qinghai-Xizang Plateau is of vital significance for studying the geodynamic processes of crustal thickening and expansion of the Qinghai-Xizang Plateau. We conducted a j...Lithospheric structure beneath the northeastern Qinghai-Xizang Plateau is of vital significance for studying the geodynamic processes of crustal thickening and expansion of the Qinghai-Xizang Plateau. We conducted a joint inversion of receiver functions and surface wave dispersions with P-wave velocity constraints using data from the Chin Array Ⅱ temporary stations deployed across the Qinghai-Xizang Plateau. Prior to joint inversion, we applied the H-κ-c method(Li JT et al., 2019) to the receiver function data in order to correct for the back-azimuthal variations in the arrival times of Ps phases and crustal multiples caused by crustal anisotropy and dipping interfaces. High-resolution images of vS, crustal thickness, and vP/vSstructures in the Qinghai-Xizang Plateau were simultaneously derived from the joint inversion. The seismic images reveal that crustal thickness decreases outward from the Qinghai-Xizang Plateau. The stable interiors of the Ordos and Alxa blocks exhibited higher velocities and lower crustal vP/vSratios. While, lower velocities and higher vP/vSratios were observed beneath the Qilian Orogen and Songpan-Ganzi terrane(SPGZ), which are geologically active and mechanically weak, especially in the mid-lower crust.Delamination or thermal erosion of the lithosphere triggered by hot asthenospheric flow contributes to the observed uppermost mantle low-velocity zones(LVZs) in the SPGZ. The crustal thickness, vS, and vP/vSratios suggest that whole lithospheric shortening is a plausible mechanism for crustal thickening in the Qinghai-Xizang Plateau, supporting the idea of coupled lithospheric-scale deformation in this region.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11971291)the National Social Science Foundation of China(Grant No.19BTJ032)+1 种基金Fujian Alliance of Mathematics(Grant No.2023SXLMMS10)Scientific Research Climbing Program of Xiamen University of Technology(Grant No.XPDKT20037).
基金supported by the Projects for National Natural Science Foundation of China(U22A20554)the Natural Science Foundation of Fujian Province(2023J01285)+1 种基金the Public Welfare Scientific Institutions of Fujian Province(2022R1002005)the Scientific Project from Fujian Provincial Department of Science and Technology(2022Y0007).
文摘Detecting changes in surface air temperature in mid-and low-altitude mountainous regions is essential for a comprehensive understanding of warming trend with altitude.We use daily surface air temperature data from 64 meteorological stations in Wuyi Mountains and its adjacent regions to analyze the spatio-temporal patterns of temperature change.The results show that Wuyi Mountains have experienced significant warming from 1961 to 2018.The warming trend of the mean temperature is 0.20℃/decade,the maximum temperature is 0.17℃/decade,and the minimum temperature is 0.26℃/decade.In 1961-1990,more than 63%of the stations showed a decreasing trend in annual mean temperature,mainly because the maximum temperature decreased during this period.However,in 1971-2000,1981-2010 and 1991-2018,the maximum,minimum and mean temperatures increased.The fastest increasing trend of mean temperature occurred in the southeastern coastal plains,the quickest increasing trend of maximum temperature occurred in the northwestern mountainous region,and the increase of minimum temperature occurred faster in the southeastern coastal and northwestern mountainous regions than that in the central area.Meanwhile,this study suggests that elevation does not affect warming in the Wuyi Mountains.These results are beneficial for understanding climate change in humid subtropical middle and low mountains.
文摘The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n<sub>0</sub> (number of zeros) and n<sub>1</sub> (number of ones), as well as the number of runs. Fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using Friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.
文摘The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two state-of-the-art methods.
基金Supported by National Natural Science Foundation of China,No.82170676Natural Science Foundation of Shaanxi Provincial Key Industries Innovation Chain(Cluster)-Social Development Project,No.2020ZDLSF02-03Xi’an Talents Plan Project:Clinical Application of Minimally Invasive Treatment of Alimentary Tract Malformation in Children by Combining Medical and Industrial Innovative Technology of Magnetic Surgery,No.XAYC210064.
文摘BACKGROUND Giant congenital biliary dilation(CBD)is a rare condition observed in clinical practice.Infants born with this condition often experience a poor overall health status,and the disease progresses rapidly,leading to severe biliary obstruction,infections,pressure exerted by the enlarged CBD on abdominal organs,disturbances in the internal environment,and multiple organ dysfunction.The treatment of giant CBD using laparoscopy is challenging due to the high degree of variation in the shape of the bile duct and other organs,making it difficult to separate the bile duct wall from adjacent tissues or to control bleeding.CASE SUMMARY Herein,we present the details of an 11-d-old male newborn who was diagnosed with giant CBD.The patient was admitted to the neonatal surgery department of our hospital due to a history of common bile duct cyst that was detected more than 3 mo ago,and also because the patient had been experiencing yellowish skin for the past 9 d.The abnormal echo in the fetal abdomen was first noticed by the patient’s mother during a routine ultrasound examination at a local hospital,when the patient was at 24 wk+6 d of pregnancy.This finding raised concerns about the possibility of congenital biliary dilatation(22 mm×21 mm).Subsequent ultrasound examinations at different hospitals consistently confirmed the presence of a congenital biliary dilatation.No specific treatment was administered for biliary dilatation during this period.A computed tomography scan conducted during the hospitalization revealed a large cystic mass in the right upper quadrant and pelvis,measuring approximately 9.2 cm×7.4 cm×11.3 cm.Based on the CONCLUSION The analysis reveals that prenatal imaging techniques,such as ultrasound and magnetic resonance imaging,play a crucial role in the early diagnosis,fetal prognosis,and treatment plan for giant CBD.Laparoscopic surgery for giant CBD presents certain challenges,including difficulties in separating the cyst wall,anastomosis,and hemostasis,as well as severe biliary system infection and ulceration.Consequently,there is a high likelihood of converting to laparotomy.The choice between surgical methods like hepaticojejunostomy(HJ)or hepaticoduodenostomy has not been standardized yet.However,we have achieved favorable outcomes using HJ.Preoperative management of inflammation,biliary drainage,liver function protection,and supportive treatment are particularly vital in improving children’s prognosis.After discharge,it is essential to conduct timely reexamination and close follow-up to identify potential complications.
基金supported by the Natural Science Basic Research Program of Shaanxi(No.2023-JC-QN-0306)the Special Fund of the Institute of Geophysics,China Earthquake Administration(No.DQJB21B32)the National Natural Science Foundation of China(No.42174069).
文摘Lithospheric structure beneath the northeastern Qinghai-Xizang Plateau is of vital significance for studying the geodynamic processes of crustal thickening and expansion of the Qinghai-Xizang Plateau. We conducted a joint inversion of receiver functions and surface wave dispersions with P-wave velocity constraints using data from the Chin Array Ⅱ temporary stations deployed across the Qinghai-Xizang Plateau. Prior to joint inversion, we applied the H-κ-c method(Li JT et al., 2019) to the receiver function data in order to correct for the back-azimuthal variations in the arrival times of Ps phases and crustal multiples caused by crustal anisotropy and dipping interfaces. High-resolution images of vS, crustal thickness, and vP/vSstructures in the Qinghai-Xizang Plateau were simultaneously derived from the joint inversion. The seismic images reveal that crustal thickness decreases outward from the Qinghai-Xizang Plateau. The stable interiors of the Ordos and Alxa blocks exhibited higher velocities and lower crustal vP/vSratios. While, lower velocities and higher vP/vSratios were observed beneath the Qilian Orogen and Songpan-Ganzi terrane(SPGZ), which are geologically active and mechanically weak, especially in the mid-lower crust.Delamination or thermal erosion of the lithosphere triggered by hot asthenospheric flow contributes to the observed uppermost mantle low-velocity zones(LVZs) in the SPGZ. The crustal thickness, vS, and vP/vSratios suggest that whole lithospheric shortening is a plausible mechanism for crustal thickening in the Qinghai-Xizang Plateau, supporting the idea of coupled lithospheric-scale deformation in this region.
