To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask produc...To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask products,group test products according to the differences of sensory attributions via Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC),pick up the representative products.Freeze-dried facial mask users evaluate satisfaction degree of picked up products and participate survey of usage behavior/cognition.Analyze consumer data by AHC to get consumer segmentations and their profile.The test results show that,sensory data and consumer data,which is from consumers test of screened representative products by performing PCA and AHC on sensory data,can be verified mutually.It is helpful to understand the needs of consumer segmentations and reason to buy by combining sensory data and consumer test.展开更多
The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This regio...The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.展开更多
Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differ...Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differentiate between legal and malicious modifications. In this paper, we introduce a novel lossless semi-fragile scheme based on prediction-error expansion for content protection of relational database. In the proposed method, all attributes in a database relation are first classified according to their sensitivity to legitimate updates. Then, the watermark is embedded by expanding the prediction error of the two least significant digits of securely selected attributes. At watermark extraction, the proposed method has the ability to fully restore the original data while detecting and localizing tampering. The applicability of our method is demonstrated theoretically and experimentally.展开更多
The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy ...The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.展开更多
In this paper, the solution of the matrix second semi-tensor product equation A∘lX∘lB=Cis studied. Firstly, the solvability of the matrix-vector second semi-tensor product equation is investigated. At the same time,...In this paper, the solution of the matrix second semi-tensor product equation A∘lX∘lB=Cis studied. Firstly, the solvability of the matrix-vector second semi-tensor product equation is investigated. At the same time, the compatibility conditions, the sufficient and necessary conditions and the specific solution methods for the matrix solution are given. Secondly, we further consider the solvability of the second semi-tensor product equation of the matrix. For each part, several examples are given to illustrate the validity of the results.展开更多
As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and furth...As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.展开更多
Membrane characteristics are determined by the fatty acids composition,which affects survival rates after freeze-drying.However,it is unknown which composition provides the greatest effect.In this study,we found that ...Membrane characteristics are determined by the fatty acids composition,which affects survival rates after freeze-drying.However,it is unknown which composition provides the greatest effect.In this study,we found that the addition of Tween 80 and Tween 20 significantly increased survival rates of Lactiplantibacillus plantarum,which reached a maximum of 93.1%.Conversely,Tween 60 caused a significant decrease.We further found that the difference between the effects of adding Tween 80 and Tween 60 was the change in oleic acid contents.To verify the role of oleic acid,we used CRISPR-Cas9 to knock-out the key synthesis gene cla-er.The survival rates of L.plantarum AR113Δcla-er declined to 5.48%.The addition of oleic acid restored the rates to those of wild type strains.Moreover,the membrane integrity and fl uidity of knockout strains markedly decreased.This is the fi rst confi rmation that Tween 80 or Tween 20 increases the survival rate by increasing the content of oleic acid in the cell membrane.These fi ndings also indicated that oleic acid in cell membranes has a substantial protective effect on L.plantarum during freeze-drying.展开更多
Introduction: Grand multiparity is a known risk factor for maternal and fetal complications. Materials and Methods: We carried out a cross-sectional descriptive study on the delivery of grand multiparas at the materni...Introduction: Grand multiparity is a known risk factor for maternal and fetal complications. Materials and Methods: We carried out a cross-sectional descriptive study on the delivery of grand multiparas at the maternity of the regional hospital annex of Ayos, a semi-rural locality in the Center region of Cameroon. The study covered the period from January 2012 through December 2020, and the objective was to assess the frequency, the determinants and the outcome of delivery in grand multiparas. Results: We recorded 1384 deliveries and enrolled 137 cases of delivery of grand multiparas. This gives a frequency of grand multipara delivery of 9.89%. The mean age of the women was 34.96 ± 4.45 years. Married parturients accounted for 65% of the cases and 16.8% were HIV positive. Delivery occurred at term in 89.9%. In 35.8%, no antenatal consultation was done. The use of the partograph during labor was reported in 11.7%. Per vaginal delivery was noted in 88.3%, emergency cesarean in 10.2% and elective cesarean in 1.5%. The most frequent maternal complications included post-partum hemorrhage (19.9%), genital tract tears (12.4%), endometritis (9.5%) and surgical wound infection (8.7%). No maternal death was recorded. The mean birth weight of the newborns was 3336.8 ± 550 g. Fetal complications were mostly represented by neonatal infection (20.1%), perinatal death (7.9%) and neonatal asphyxia (9.5%). Conclusion: The frequency of grand multiparous delivery in the semi-rural locality of Ayos, Cameroon, was 9.89%. The mean age of parturients was 38.96 years and the proportion of vaginal delivery was 88.3%.展开更多
Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition...Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.展开更多
Introduction: The delivery of a primipara, a woman giving birth for the first time, is challenging and may lead to complications and influence the obstetrical future of a woman. Materials and Methods: We carried out a...Introduction: The delivery of a primipara, a woman giving birth for the first time, is challenging and may lead to complications and influence the obstetrical future of a woman. Materials and Methods: We carried out a cross-sectional and analytical study at the maternity of the regional hospital annex of Ayos, a semi-rural locality in Cameroon, for the period between January 2012 and December 2020. The objective was to determine the frequency and the determinants of primipara delivery. Results: We recruited 440 cases. The frequency of primipara delivery was 31.8%. The ages of the participants ranged from 12 to 35 years with a mean age of 18.01 ± 3.52 years. Single women contributed to 95.5% of cases while 97.5% were unemployed. The delivery occurred at term in 90.2% and 98.4% of pregnancies were singleton. The delivery was vaginal in 91.6%, while caesarean delivery was done in 8.4% (8% emergency and 0.4% elective). The most frequent maternal complications were genital tract tears (15.7%), post-partum hemorrhage (12.5%) and endometritis (2.7%). The birth weight of newborns ranged from 1070 to 4500 g with a mean of 3024.5 ± 511.4 g. The single marital status, a gestational age between 37 and 42 weeks and a birth weight between 1500 g and 2499 g were significantly associated with vaginal delivery. Conclusion: The frequency of primiparous delivery was relatively high (31.8%) in the Ayos semi-rural health district of Cameroon. Major complications associated with delivery included genital tract tears, post-partum hemorrhage, cesarean section and neo-natal infection.展开更多
We establish the links between the lightlike geometry and basics invariants of the associated semi-Riemannian geometry on r-lightlike submanifold and semi-Riemannian constructed from a semi-Riemannian ambient. Then we...We establish the links between the lightlike geometry and basics invariants of the associated semi-Riemannian geometry on r-lightlike submanifold and semi-Riemannian constructed from a semi-Riemannian ambient. Then we establish some basic inequalities, involving the scalar curvature and shape operator on r-lightlike coisotropic submanifold in semi-Riemannian manifold. Equality cases are also discussed.展开更多
文摘To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask products,group test products according to the differences of sensory attributions via Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC),pick up the representative products.Freeze-dried facial mask users evaluate satisfaction degree of picked up products and participate survey of usage behavior/cognition.Analyze consumer data by AHC to get consumer segmentations and their profile.The test results show that,sensory data and consumer data,which is from consumers test of screened representative products by performing PCA and AHC on sensory data,can be verified mutually.It is helpful to understand the needs of consumer segmentations and reason to buy by combining sensory data and consumer test.
文摘The economy of most rural locations in the semi-arid region of Llano Estacado in the southern United States is predominantly based on agriculture, primarily beef and wheat (Triticum aestivum L.) production. This region is prone to drought and is projected to experience a drier climate. Droughts that coincide with the critical phenological phases of a crop can be remarkably costly. Although drought cannot be prevented, its losses can be minimized through mitigation measures if it is predicted in advance. Predicting yield loss from an imminent drought is an important need of stakeholders. One way to fulfill this need is using an agricultural drought index, such as the Agricultural Reference Index for Drought (ARID). Being plant physiology-based, ARID can represent drought-yield relationships accurately. This study developed an ARID-based yield model for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to water stress. The reasonable values of the drought sensitivity coefficients of the yield model indicated that it could reflect the phenomenon of water stress decreasing the winter wheat yields in this region reasonably. The values of the various metrics used to evaluate the model, including Willmott Index (0.86), Nash-Sutcliffe Index (0.61), and percentage error (26), indicated that the yield model performed fairly well at predicting the drought-induced yield loss for winter wheat. The yield model may be useful for predicting the drought-induced yield loss for winter wheat in the study region and scheduling irrigation allocation based on phenological phase-specific drought sensitivity.
文摘Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differentiate between legal and malicious modifications. In this paper, we introduce a novel lossless semi-fragile scheme based on prediction-error expansion for content protection of relational database. In the proposed method, all attributes in a database relation are first classified according to their sensitivity to legitimate updates. Then, the watermark is embedded by expanding the prediction error of the two least significant digits of securely selected attributes. At watermark extraction, the proposed method has the ability to fully restore the original data while detecting and localizing tampering. The applicability of our method is demonstrated theoretically and experimentally.
文摘The aim of this paper is to broaden the application of Stochastic Configuration Network (SCN) in the semi-supervised domain by utilizing common unlabeled data in daily life. It can enhance the classification accuracy of decentralized SCN algorithms while effectively protecting user privacy. To this end, we propose a decentralized semi-supervised learning algorithm for SCN, called DMT-SCN, which introduces teacher and student models by combining the idea of consistency regularization to improve the response speed of model iterations. In order to reduce the possible negative impact of unsupervised data on the model, we purposely change the way of adding noise to the unlabeled data. Simulation results show that the algorithm can effectively utilize unlabeled data to improve the classification accuracy of SCN training and is robust under different ground simulation environments.
文摘In this paper, the solution of the matrix second semi-tensor product equation A∘lX∘lB=Cis studied. Firstly, the solvability of the matrix-vector second semi-tensor product equation is investigated. At the same time, the compatibility conditions, the sufficient and necessary conditions and the specific solution methods for the matrix solution are given. Secondly, we further consider the solvability of the second semi-tensor product equation of the matrix. For each part, several examples are given to illustrate the validity of the results.
文摘As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.
基金funded by National Natural Science Foundation of China(32172186)National Science Foundation for Distinguished Young Scholars of China(32025029)+1 种基金Shanghai Education committee scientific research innovation projects,China(2101070007800120)Shanghai Engineering Research Center of Food Microbiology(19DZ2281100).
文摘Membrane characteristics are determined by the fatty acids composition,which affects survival rates after freeze-drying.However,it is unknown which composition provides the greatest effect.In this study,we found that the addition of Tween 80 and Tween 20 significantly increased survival rates of Lactiplantibacillus plantarum,which reached a maximum of 93.1%.Conversely,Tween 60 caused a significant decrease.We further found that the difference between the effects of adding Tween 80 and Tween 60 was the change in oleic acid contents.To verify the role of oleic acid,we used CRISPR-Cas9 to knock-out the key synthesis gene cla-er.The survival rates of L.plantarum AR113Δcla-er declined to 5.48%.The addition of oleic acid restored the rates to those of wild type strains.Moreover,the membrane integrity and fl uidity of knockout strains markedly decreased.This is the fi rst confi rmation that Tween 80 or Tween 20 increases the survival rate by increasing the content of oleic acid in the cell membrane.These fi ndings also indicated that oleic acid in cell membranes has a substantial protective effect on L.plantarum during freeze-drying.
文摘Introduction: Grand multiparity is a known risk factor for maternal and fetal complications. Materials and Methods: We carried out a cross-sectional descriptive study on the delivery of grand multiparas at the maternity of the regional hospital annex of Ayos, a semi-rural locality in the Center region of Cameroon. The study covered the period from January 2012 through December 2020, and the objective was to assess the frequency, the determinants and the outcome of delivery in grand multiparas. Results: We recorded 1384 deliveries and enrolled 137 cases of delivery of grand multiparas. This gives a frequency of grand multipara delivery of 9.89%. The mean age of the women was 34.96 ± 4.45 years. Married parturients accounted for 65% of the cases and 16.8% were HIV positive. Delivery occurred at term in 89.9%. In 35.8%, no antenatal consultation was done. The use of the partograph during labor was reported in 11.7%. Per vaginal delivery was noted in 88.3%, emergency cesarean in 10.2% and elective cesarean in 1.5%. The most frequent maternal complications included post-partum hemorrhage (19.9%), genital tract tears (12.4%), endometritis (9.5%) and surgical wound infection (8.7%). No maternal death was recorded. The mean birth weight of the newborns was 3336.8 ± 550 g. Fetal complications were mostly represented by neonatal infection (20.1%), perinatal death (7.9%) and neonatal asphyxia (9.5%). Conclusion: The frequency of grand multiparous delivery in the semi-rural locality of Ayos, Cameroon, was 9.89%. The mean age of parturients was 38.96 years and the proportion of vaginal delivery was 88.3%.
文摘Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.
文摘Introduction: The delivery of a primipara, a woman giving birth for the first time, is challenging and may lead to complications and influence the obstetrical future of a woman. Materials and Methods: We carried out a cross-sectional and analytical study at the maternity of the regional hospital annex of Ayos, a semi-rural locality in Cameroon, for the period between January 2012 and December 2020. The objective was to determine the frequency and the determinants of primipara delivery. Results: We recruited 440 cases. The frequency of primipara delivery was 31.8%. The ages of the participants ranged from 12 to 35 years with a mean age of 18.01 ± 3.52 years. Single women contributed to 95.5% of cases while 97.5% were unemployed. The delivery occurred at term in 90.2% and 98.4% of pregnancies were singleton. The delivery was vaginal in 91.6%, while caesarean delivery was done in 8.4% (8% emergency and 0.4% elective). The most frequent maternal complications were genital tract tears (15.7%), post-partum hemorrhage (12.5%) and endometritis (2.7%). The birth weight of newborns ranged from 1070 to 4500 g with a mean of 3024.5 ± 511.4 g. The single marital status, a gestational age between 37 and 42 weeks and a birth weight between 1500 g and 2499 g were significantly associated with vaginal delivery. Conclusion: The frequency of primiparous delivery was relatively high (31.8%) in the Ayos semi-rural health district of Cameroon. Major complications associated with delivery included genital tract tears, post-partum hemorrhage, cesarean section and neo-natal infection.
文摘We establish the links between the lightlike geometry and basics invariants of the associated semi-Riemannian geometry on r-lightlike submanifold and semi-Riemannian constructed from a semi-Riemannian ambient. Then we establish some basic inequalities, involving the scalar curvature and shape operator on r-lightlike coisotropic submanifold in semi-Riemannian manifold. Equality cases are also discussed.
