Potassium(K)is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution,indirectly leading to variations in the leaf potassium content(LKC,%)...Potassium(K)is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution,indirectly leading to variations in the leaf potassium content(LKC,%)at different leaf positions.However,due to the interaction between light and leaf age,leaf sensitivity to this change varies at different positions,including the reflection and absorption of the spectrum.Selecting the optimal leaf position for monitoring is a crucial factor in the rapid and accurate evaluation of cotton LKC using spectral remote sensing technology.Therefore,this study proposes a comprehensive multi-leaf position estimation model based on the vertical distribution characteristics of LKC from top to bottom,aiming to achieve an accurate estimation of cotton LKC and optimize the strategy for selecting the monitored leaf position.Between 2020 and 2021,we collected hyperspectral imaging data of the main stem leaves at different positions from top to bottom(Li,i=1,2,3,...,n)during the cotton budding,flowering,and boll-setting stages.Vertical distribution characteristics,sensitivity differences,and spectral correlations of LKC at different leaf positions were investigated.Additionally,the optimal range of the dominant leaf position for monitoring was determined.Partial least squares regression(PLSR),random forest regression(RFR),support vector machine regression(SVR),and the entropy weight method(EWM)were employed to develop LKC estimation models for single-and multi-leaf positions.The results showed a vertical heterogeneous distribution of cotton LKC,with LKC initially increasing and then gradually decreasing from top to bottom;the average LKC of cotton reached its maximum value at the flowering stage.The upper leaf position demonstrated greater sensitivity to K and exhibited a stronger correlation with the spectrum.The selected dominant leaf positions for the three growth stages were L1-L5,L1-L4,and L1-L2,respectively.Based on the dominant leaf position monitoring range,the optimal single leaf position models for estimating LKC during the three growth stages were PLSR-L4,PLSR-L1,and SVR-L2,with the coefficient of determination of the validation set(R2val)being 0.786,0.580,and 0.768,and the root-mean-square error of the validation set(RMSEval)being 0.168,0.197,and 0.191,respectively.The multi-leaf position LKC estimation model was constructed by EWM with R2val being 0.887,0.728,and 0.703,and RMSEval being 0.134,0.172,and 0.209,respectively.In contrast,the newly developed multi-leaf position comprehensive estimation model yielded superior results,improving the model’s stability based on high accuracy,especially during the budding and flowering stages.These findings hold significant importance for investigating cotton LKC spectral models and selecting suitable leaf positions for field monitoring.展开更多
Introduction: Cystic lymphangiomas are rare benign malformative tumors of the lymphatic system of obscure etiopathogenesis. The cervico-facial location remains the most common (75%). Although benign, these tumors rema...Introduction: Cystic lymphangiomas are rare benign malformative tumors of the lymphatic system of obscure etiopathogenesis. The cervico-facial location remains the most common (75%). Although benign, these tumors remain potentially fatal, due to possible compression of the upper aero-digestive tract. The aim of this work is to study the epidemiological, diagnostic and therapeutic characteristics of cervico-mandibular congenital cystic lymphangiomas in the pediatric surgery department of the Donka National Hospital (HND) Conakry. Patients and methods: This is a retrospective and descriptive study of 13 files lasting 7 years from January 2015 to December 31, 2021. The files of children whose age is less than or equal to 15 years operated on cervical tumor with histological evidence of cystic lymphangioma were retained. The data were analyzed using SPSS statistical software 21 and anonymously. Results: The incidence of this study was 1.86 cases per year and a sex ratio of 0.62 in favor of girls. The average age was 8 months 19 days. In the antecedents, we only find poorly monitored pregnancies. The average size of the tumors was 11.85 cm. Cervical ultrasound and standard x-ray of the cervical mass were the only examinations performed. Total surgical excision of the cervical tumor was performed in all patients. The mass was polycystic on exploration. The histological examination of the surgical specimens was in favor of a cystic lymphangioma. The surgical consequences were simple in 11 patients (84.62%) and complicated by parietal suppuration in 2 cases (15.38%). There were no cases of recurrence after one year of follow-up. Conclusion: Cervico-mandibular cystic lymphangiomas are the most frequent locations of congenital lymphangiomas in children. Their severity is linked to the risk of compression of the aero-digestive tracts. Their diagnosis must be confirmed by the histology of the surgical specimen. Despite the therapeutic arsenal, excision of the cystic mass remains the only effective alternative in our socio-economic conditions to avoid recurrences and loss of follow-up of patients.展开更多
基金supported by the Corps Leading Talents Program,China(2023YZ01)the Tianshan Talent Training Program,China(2023TS05)the Crop Smart Production Innovation Team,China(2023TD01).
文摘Potassium(K)is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution,indirectly leading to variations in the leaf potassium content(LKC,%)at different leaf positions.However,due to the interaction between light and leaf age,leaf sensitivity to this change varies at different positions,including the reflection and absorption of the spectrum.Selecting the optimal leaf position for monitoring is a crucial factor in the rapid and accurate evaluation of cotton LKC using spectral remote sensing technology.Therefore,this study proposes a comprehensive multi-leaf position estimation model based on the vertical distribution characteristics of LKC from top to bottom,aiming to achieve an accurate estimation of cotton LKC and optimize the strategy for selecting the monitored leaf position.Between 2020 and 2021,we collected hyperspectral imaging data of the main stem leaves at different positions from top to bottom(Li,i=1,2,3,...,n)during the cotton budding,flowering,and boll-setting stages.Vertical distribution characteristics,sensitivity differences,and spectral correlations of LKC at different leaf positions were investigated.Additionally,the optimal range of the dominant leaf position for monitoring was determined.Partial least squares regression(PLSR),random forest regression(RFR),support vector machine regression(SVR),and the entropy weight method(EWM)were employed to develop LKC estimation models for single-and multi-leaf positions.The results showed a vertical heterogeneous distribution of cotton LKC,with LKC initially increasing and then gradually decreasing from top to bottom;the average LKC of cotton reached its maximum value at the flowering stage.The upper leaf position demonstrated greater sensitivity to K and exhibited a stronger correlation with the spectrum.The selected dominant leaf positions for the three growth stages were L1-L5,L1-L4,and L1-L2,respectively.Based on the dominant leaf position monitoring range,the optimal single leaf position models for estimating LKC during the three growth stages were PLSR-L4,PLSR-L1,and SVR-L2,with the coefficient of determination of the validation set(R2val)being 0.786,0.580,and 0.768,and the root-mean-square error of the validation set(RMSEval)being 0.168,0.197,and 0.191,respectively.The multi-leaf position LKC estimation model was constructed by EWM with R2val being 0.887,0.728,and 0.703,and RMSEval being 0.134,0.172,and 0.209,respectively.In contrast,the newly developed multi-leaf position comprehensive estimation model yielded superior results,improving the model’s stability based on high accuracy,especially during the budding and flowering stages.These findings hold significant importance for investigating cotton LKC spectral models and selecting suitable leaf positions for field monitoring.
文摘Introduction: Cystic lymphangiomas are rare benign malformative tumors of the lymphatic system of obscure etiopathogenesis. The cervico-facial location remains the most common (75%). Although benign, these tumors remain potentially fatal, due to possible compression of the upper aero-digestive tract. The aim of this work is to study the epidemiological, diagnostic and therapeutic characteristics of cervico-mandibular congenital cystic lymphangiomas in the pediatric surgery department of the Donka National Hospital (HND) Conakry. Patients and methods: This is a retrospective and descriptive study of 13 files lasting 7 years from January 2015 to December 31, 2021. The files of children whose age is less than or equal to 15 years operated on cervical tumor with histological evidence of cystic lymphangioma were retained. The data were analyzed using SPSS statistical software 21 and anonymously. Results: The incidence of this study was 1.86 cases per year and a sex ratio of 0.62 in favor of girls. The average age was 8 months 19 days. In the antecedents, we only find poorly monitored pregnancies. The average size of the tumors was 11.85 cm. Cervical ultrasound and standard x-ray of the cervical mass were the only examinations performed. Total surgical excision of the cervical tumor was performed in all patients. The mass was polycystic on exploration. The histological examination of the surgical specimens was in favor of a cystic lymphangioma. The surgical consequences were simple in 11 patients (84.62%) and complicated by parietal suppuration in 2 cases (15.38%). There were no cases of recurrence after one year of follow-up. Conclusion: Cervico-mandibular cystic lymphangiomas are the most frequent locations of congenital lymphangiomas in children. Their severity is linked to the risk of compression of the aero-digestive tracts. Their diagnosis must be confirmed by the histology of the surgical specimen. Despite the therapeutic arsenal, excision of the cystic mass remains the only effective alternative in our socio-economic conditions to avoid recurrences and loss of follow-up of patients.
