The time-varying difference-in-difference model is used to identify the impact of payment technology on residents’consumption,and the moderation effect analysis method is used to identify its mechanism.It is found th...The time-varying difference-in-difference model is used to identify the impact of payment technology on residents’consumption,and the moderation effect analysis method is used to identify its mechanism.It is found that payment technology promotes consumption capacity expansion and quality improvement(CEQI)through three pathways of alleviating liquidity constraints,reducing transaction costs and weakening the payment of pain.The parallel and serial mechanisms of the three are further explored.The effect of payment technology on the CEQI of residents’consumption shows obvious heterogeneity due to differences in urban and rural household registration and financial literacy.Based on the empirical research results and the national conditions of China,targeted policy recommendations are proposed from the demand side,the supply side and the technological side.展开更多
By using fixed point index theory of cone mapping and extension method, this paper discusses the existence of multiple positive solution of nonlinear neutral integral equatious modeling infectious disease.
Objective： To systematically analyze and summarize non-thyrogenous masses of the neck （NTMN） by consideration of new areas, a large sample size and multiple-aspect analysis. Methods： Our research involved 3125 NTM...Objective： To systematically analyze and summarize non-thyrogenous masses of the neck （NTMN） by consideration of new areas, a large sample size and multiple-aspect analysis. Methods： Our research involved 3125 NTMN cases. We summarized the proportion of various NTMN and the distribution of the neck diseases based on the new international classification. The clinical traits such as sexual proportion and age, etc, were analyzed along with the unknown primary cervical metastatic carcinomas （UPCMC）, and built up a mathematical model based on the data above. Results： There were 68 different diseases identified. Among all the NTMN, the percentage of metastatic carcinomas was 63.3%. The neck masses with a focus above the clavicle comprised 62.3% of the metastatic carcinomas whose focuses were clear. Moreover, other results almost supported the ＂rule of 80%＂. There was an obvious distribution of traits at every sub level. For example, there were 23 different diseases in level Ⅲ, of which the most common was lymphoma. UPCMC made up 12.3% of all metastatic carcinomas. The clinic cases could be analyzed by our model even to form a primary diagnosis which showed a high coincident rate with clinic diagnosis. Conclusion： NTMN are complex and various, with a definite distribution in each neck level. Data relating component character, sex ratio and UPCMC et al to the clinical traits of NTMN will provide vigorous support for clinical applications. The mathematical model could be an efficient method to synthetically analyze complicate data of NTMN.展开更多
Geological structures often exhibit smooth characteristics away from sharp discontinuities. One aim of geophysical inversion is to recover information about the smooth structures as well as about the sharp discontinui...Geological structures often exhibit smooth characteristics away from sharp discontinuities. One aim of geophysical inversion is to recover information about the smooth structures as well as about the sharp discontinuities. Because no specific operator can provide a perfect sparse representation of complicated geological models, hyper-parameter regularization inversion based on the iterative split Bregman method was used to recover the features of both smooth and sharp geological structures. A novel preconditioned matrix was proposed, which counteracted the natural decay of the sensitivity matrix and its inverse matrix was calculated easily. Application of the algorithm to synthetic data produces density models that are good representations of the designed models. The results show that the algorithm proposed is feasible and effective.展开更多
The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multi...The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.展开更多
AIM:To develop a novel endoscopic severity model of intestinal Behcet's disease(BD) and to evaluate its feasibility by comparing it with the actual disease activity index for intestinal Behcet's disease(DAIBD)...AIM:To develop a novel endoscopic severity model of intestinal Behcet's disease(BD) and to evaluate its feasibility by comparing it with the actual disease activity index for intestinal Behcet's disease(DAIBD).METHODS:We reviewed the medical records of 167 intestinal BD patients between March 1986 and April 2011.We also investigated the endoscopic parameters including ulcer locations,distribution,number,depth,shape,size and margin to identify independent factors associated with DAIBD.An endoscopic severity model was developed using significant colonoscopic variables identified by multivariate regression analysis and its correlation with the DAIBD was evaluated.To determine factors related to the discrepancy between endoscopic severity and clinical activity,clinical characteristics and laboratory markers of the patients were analyzed.RESULTS:A multivariate regression analysis revealed that the number of intestinal ulcers(≥ 2,P = 0.031) and volcanoshaped ulcers(P = 0.001) were predictive factors for the DAIBD.An endoscopic severity model(Y) was developed based on selected endoscopic variables as follows:Y = 47.44 + 9.04 × non-Ileocecal area + 11.85 ×≥ 2 of intestinal ulcers + 5.03 × shallow ulcers + 12.76 × deep ulcers + 4.47 × geographicshaped ulcers + 26.93 × volcano-shaped ulcers + 8.65 ×≥ 20 mm of intestinal ulcers.However,endoscopic parameters used in the multivariate analysis explained only 18.9% of the DAIBD variance.Patients with severe DAIBD scores but with moderately predicted disease activity by the endoscopic severity model had more symptoms of irritable bowel syndrome(21.4% vs 4.9%,P = 0.026) and a lower rate of corticosteroid use(50.0% vs 75.6%,P = 0.016) than those with severe DAIBD scores and accurately predicted disease by the model.CONCLUSION:Our study showed that the number of intestinal ulcers and volcano-shaped ulcers were predictive factors for severe DAIBD scores.However,the correlation between endoscopic severity and DAIBD(r = 0.434) was weak.展开更多
Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in th...Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in this field. A procedure is proposed in this paper to diagnose nitrogen nutrition non-destructively for rapeseed qualitatively based on the multifractal theory. Twelve texture parameters are given by the method of multifractal detrended fluctuation （MF-DFA）, which contains six generalized Hurst exponents and six relative multifractal parameters that are used as features of the rapeseed leaf images for identifying the two nitrogen levels, namely, the N-mezzo and the N-wane. For the base leaves, central leaves and top leaves of the rapeseed plant and the three-section mixed samples, three parameters combinations are selected to conduct the work. Five classifiers of Fisher＇s linear discriminant algorithm （LDA）, extreme learning machine （ELM）, support vector machine and kernel method （SVMKM）, random decision forests （RF） and K-nearest neighbor algorithm （KNN） are employed to calculate the diagno- sis accuracy. An interesting finding is that the best diagnose accuracy is from the base leaves of the rapeseed plant. It is explained that the base leaf is the most sensitive to the nitrogen deficiency. The diagnose effect by the base leaves samples is outshining the existing result significantly for the same leaves samples. For the mixed samples, the aver- aged discriminant accuracy reaches 97.12% and 97.56% by SVMKM and RF methods with the 10-fold cross-validation respectively. The resulting high accuracy on N-levels identification shows the feasibility and efficiency of our method.展开更多
基金Foundation items:National Natural Science Foundation of China(No.71874027)Ministry of Education Humanities and Social Sciences Research Youth Fund Project(No.23YJC760028)。
文摘The time-varying difference-in-difference model is used to identify the impact of payment technology on residents’consumption,and the moderation effect analysis method is used to identify its mechanism.It is found that payment technology promotes consumption capacity expansion and quality improvement(CEQI)through three pathways of alleviating liquidity constraints,reducing transaction costs and weakening the payment of pain.The parallel and serial mechanisms of the three are further explored.The effect of payment technology on the CEQI of residents’consumption shows obvious heterogeneity due to differences in urban and rural household registration and financial literacy.Based on the empirical research results and the national conditions of China,targeted policy recommendations are proposed from the demand side,the supply side and the technological side.
文摘By using fixed point index theory of cone mapping and extension method, this paper discusses the existence of multiple positive solution of nonlinear neutral integral equatious modeling infectious disease.
文摘Objective： To systematically analyze and summarize non-thyrogenous masses of the neck （NTMN） by consideration of new areas, a large sample size and multiple-aspect analysis. Methods： Our research involved 3125 NTMN cases. We summarized the proportion of various NTMN and the distribution of the neck diseases based on the new international classification. The clinical traits such as sexual proportion and age, etc, were analyzed along with the unknown primary cervical metastatic carcinomas （UPCMC）, and built up a mathematical model based on the data above. Results： There were 68 different diseases identified. Among all the NTMN, the percentage of metastatic carcinomas was 63.3%. The neck masses with a focus above the clavicle comprised 62.3% of the metastatic carcinomas whose focuses were clear. Moreover, other results almost supported the ＂rule of 80%＂. There was an obvious distribution of traits at every sub level. For example, there were 23 different diseases in level Ⅲ, of which the most common was lymphoma. UPCMC made up 12.3% of all metastatic carcinomas. The clinic cases could be analyzed by our model even to form a primary diagnosis which showed a high coincident rate with clinic diagnosis. Conclusion： NTMN are complex and various, with a definite distribution in each neck level. Data relating component character, sex ratio and UPCMC et al to the clinical traits of NTMN will provide vigorous support for clinical applications. The mathematical model could be an efficient method to synthetically analyze complicate data of NTMN.
基金Projects(41174061,41374120)supported by the National Natural Science Foundation of China
文摘Geological structures often exhibit smooth characteristics away from sharp discontinuities. One aim of geophysical inversion is to recover information about the smooth structures as well as about the sharp discontinuities. Because no specific operator can provide a perfect sparse representation of complicated geological models, hyper-parameter regularization inversion based on the iterative split Bregman method was used to recover the features of both smooth and sharp geological structures. A novel preconditioned matrix was proposed, which counteracted the natural decay of the sensitivity matrix and its inverse matrix was calculated easily. Application of the algorithm to synthetic data produces density models that are good representations of the designed models. The results show that the algorithm proposed is feasible and effective.
基金supported by the National Natural Science Foundation of China (61202208)
文摘The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.
文摘AIM:To develop a novel endoscopic severity model of intestinal Behcet's disease(BD) and to evaluate its feasibility by comparing it with the actual disease activity index for intestinal Behcet's disease(DAIBD).METHODS:We reviewed the medical records of 167 intestinal BD patients between March 1986 and April 2011.We also investigated the endoscopic parameters including ulcer locations,distribution,number,depth,shape,size and margin to identify independent factors associated with DAIBD.An endoscopic severity model was developed using significant colonoscopic variables identified by multivariate regression analysis and its correlation with the DAIBD was evaluated.To determine factors related to the discrepancy between endoscopic severity and clinical activity,clinical characteristics and laboratory markers of the patients were analyzed.RESULTS:A multivariate regression analysis revealed that the number of intestinal ulcers(≥ 2,P = 0.031) and volcanoshaped ulcers(P = 0.001) were predictive factors for the DAIBD.An endoscopic severity model(Y) was developed based on selected endoscopic variables as follows:Y = 47.44 + 9.04 × non-Ileocecal area + 11.85 ×≥ 2 of intestinal ulcers + 5.03 × shallow ulcers + 12.76 × deep ulcers + 4.47 × geographicshaped ulcers + 26.93 × volcano-shaped ulcers + 8.65 ×≥ 20 mm of intestinal ulcers.However,endoscopic parameters used in the multivariate analysis explained only 18.9% of the DAIBD variance.Patients with severe DAIBD scores but with moderately predicted disease activity by the endoscopic severity model had more symptoms of irritable bowel syndrome(21.4% vs 4.9%,P = 0.026) and a lower rate of corticosteroid use(50.0% vs 75.6%,P = 0.016) than those with severe DAIBD scores and accurately predicted disease by the model.CONCLUSION:Our study showed that the number of intestinal ulcers and volcano-shaped ulcers were predictive factors for severe DAIBD scores.However,the correlation between endoscopic severity and DAIBD(r = 0.434) was weak.
基金This work was supported by National Natural Science Foundation of China （Grant No. 31501227）, the Key R＆D Project Funds of Hunan Province, China （Grant No. 2015JC3098） and the Young Scholar Project and Key Project Funds of the Department of Education of Hunan Province, China （Grant No. 14B087, 151083）.
文摘Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in this field. A procedure is proposed in this paper to diagnose nitrogen nutrition non-destructively for rapeseed qualitatively based on the multifractal theory. Twelve texture parameters are given by the method of multifractal detrended fluctuation （MF-DFA）, which contains six generalized Hurst exponents and six relative multifractal parameters that are used as features of the rapeseed leaf images for identifying the two nitrogen levels, namely, the N-mezzo and the N-wane. For the base leaves, central leaves and top leaves of the rapeseed plant and the three-section mixed samples, three parameters combinations are selected to conduct the work. Five classifiers of Fisher＇s linear discriminant algorithm （LDA）, extreme learning machine （ELM）, support vector machine and kernel method （SVMKM）, random decision forests （RF） and K-nearest neighbor algorithm （KNN） are employed to calculate the diagno- sis accuracy. An interesting finding is that the best diagnose accuracy is from the base leaves of the rapeseed plant. It is explained that the base leaf is the most sensitive to the nitrogen deficiency. The diagnose effect by the base leaves samples is outshining the existing result significantly for the same leaves samples. For the mixed samples, the aver- aged discriminant accuracy reaches 97.12% and 97.56% by SVMKM and RF methods with the 10-fold cross-validation respectively. The resulting high accuracy on N-levels identification shows the feasibility and efficiency of our method.
