Direct collection of uranium from low uranium systems via adsorption remains challenging.Fibrous sorbent materials with amidoxime(AO)groups are promising adsorbents for uranium extraction from seawater.However,low AO ...Direct collection of uranium from low uranium systems via adsorption remains challenging.Fibrous sorbent materials with amidoxime(AO)groups are promising adsorbents for uranium extraction from seawater.However,low AO adsorption group utilization remains an issue.We herein fabricated a branched structure containing AO groups on polypropylene/polyethylene spun-laced nonwoven(PP/PE SNW)fibers using grafting polymerization induced by radiation(RIGP)to improve AO utilization.The chemical structures,thermal properties,and surface morphologies of the raw and treated PP/PE SNW fibers were studied.The results show that an adsorptive functional layer with a branching structure was successfully anchored to the fiber surface.The adsorption properties were investigated using batch adsorption experiments in simulated seawater with an initial uranium concentration of 500μg·L^(−1)(pH 4,25℃).The maximum adsorption capacity of the adsorbent material was 137.3 mg·g^(−1)within 24 h;moreover,the uranyl removal reached 96%within 240 min.The adsorbent had an AO utilization rate of 1/3.5 and was stable over a pH range of 4–10,with good selectivity and reusability,demonstrating its potential for seawater uranium extraction.展开更多
AIM: To investigate and compare the efficacy of two machine-learning technologies with deep-learning(DL) and support vector machine(SVM) for the detection of branch retinal vein occlusion(BRVO) using ultrawide-field f...AIM: To investigate and compare the efficacy of two machine-learning technologies with deep-learning(DL) and support vector machine(SVM) for the detection of branch retinal vein occlusion(BRVO) using ultrawide-field fundus images. METHODS: This study included 237 images from 236 patients with BRVO with a mean±standard deviation of age 66.3±10.6 y and 229 images from 176 non-BRVO healthy subjects with a mean age of 64.9±9.4 y. Training was conducted using a deep convolutional neural network using ultrawide-field fundus images to construct the DL model. The sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) and area under the curve(AUC) were calculated to compare the diagnostic abilities of the DL and SVM models. RESULTS: For the DL model, the sensitivity, specificity, PPV, NPV and AUC for diagnosing BRVO was 94.0%(95%CI: 93.8%-98.8%), 97.0%(95%CI: 89.7%-96.4%), 96.5%(95%CI: 94.3%-98.7%), 93.2%(95%CI: 90.5%-96.0%) and 0.976(95%CI: 0.960-0.993), respectively. In contrast, for the SVM model, these values were 80.5%(95%CI: 77.8%-87.9%), 84.3%(95%CI: 75.8%-86.1%), 83.5%(95%CI: 78.4%-88.6%), 75.2%(95%CI: 72.1%-78.3%) and 0.857(95%CI: 0.811-0.903), respectively. The DL model outperformed the SVM model in all the aforementioned parameters(P<0.001). CONCLUSION: These results indicate that the combination of the DL model and ultrawide-field fundus ophthalmoscopy may distinguish between healthy and BRVO eyes with a high level of accuracy. The proposed combination may be used for automatically diagnosing BRVO in patients residing in remote areas lacking access to an ophthalmic medical center.展开更多
As a transportation hub along the Maritime Silk Road,Xiamen has unique advantages in its location,resources and technological prowess.In recent years,a lot of achievements have been made by the CCPIT Xiamen Branch in ...As a transportation hub along the Maritime Silk Road,Xiamen has unique advantages in its location,resources and technological prowess.In recent years,a lot of achievements have been made by the CCPIT Xiamen Branch in the development of restructuring and expansion of functions.Su Yuqun。展开更多
基金supported by the National Natural Science Foundation of China(Nos.11675247,22176194).
文摘Direct collection of uranium from low uranium systems via adsorption remains challenging.Fibrous sorbent materials with amidoxime(AO)groups are promising adsorbents for uranium extraction from seawater.However,low AO adsorption group utilization remains an issue.We herein fabricated a branched structure containing AO groups on polypropylene/polyethylene spun-laced nonwoven(PP/PE SNW)fibers using grafting polymerization induced by radiation(RIGP)to improve AO utilization.The chemical structures,thermal properties,and surface morphologies of the raw and treated PP/PE SNW fibers were studied.The results show that an adsorptive functional layer with a branching structure was successfully anchored to the fiber surface.The adsorption properties were investigated using batch adsorption experiments in simulated seawater with an initial uranium concentration of 500μg·L^(−1)(pH 4,25℃).The maximum adsorption capacity of the adsorbent material was 137.3 mg·g^(−1)within 24 h;moreover,the uranyl removal reached 96%within 240 min.The adsorbent had an AO utilization rate of 1/3.5 and was stable over a pH range of 4–10,with good selectivity and reusability,demonstrating its potential for seawater uranium extraction.
文摘AIM: To investigate and compare the efficacy of two machine-learning technologies with deep-learning(DL) and support vector machine(SVM) for the detection of branch retinal vein occlusion(BRVO) using ultrawide-field fundus images. METHODS: This study included 237 images from 236 patients with BRVO with a mean±standard deviation of age 66.3±10.6 y and 229 images from 176 non-BRVO healthy subjects with a mean age of 64.9±9.4 y. Training was conducted using a deep convolutional neural network using ultrawide-field fundus images to construct the DL model. The sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) and area under the curve(AUC) were calculated to compare the diagnostic abilities of the DL and SVM models. RESULTS: For the DL model, the sensitivity, specificity, PPV, NPV and AUC for diagnosing BRVO was 94.0%(95%CI: 93.8%-98.8%), 97.0%(95%CI: 89.7%-96.4%), 96.5%(95%CI: 94.3%-98.7%), 93.2%(95%CI: 90.5%-96.0%) and 0.976(95%CI: 0.960-0.993), respectively. In contrast, for the SVM model, these values were 80.5%(95%CI: 77.8%-87.9%), 84.3%(95%CI: 75.8%-86.1%), 83.5%(95%CI: 78.4%-88.6%), 75.2%(95%CI: 72.1%-78.3%) and 0.857(95%CI: 0.811-0.903), respectively. The DL model outperformed the SVM model in all the aforementioned parameters(P<0.001). CONCLUSION: These results indicate that the combination of the DL model and ultrawide-field fundus ophthalmoscopy may distinguish between healthy and BRVO eyes with a high level of accuracy. The proposed combination may be used for automatically diagnosing BRVO in patients residing in remote areas lacking access to an ophthalmic medical center.
文摘As a transportation hub along the Maritime Silk Road,Xiamen has unique advantages in its location,resources and technological prowess.In recent years,a lot of achievements have been made by the CCPIT Xiamen Branch in the development of restructuring and expansion of functions.Su Yuqun。
