Antibiotic residues in aquaculture wastewater are considered as an emerging environmental problem, as they are not efficiently removed in wastewater treatment plants. To address this issue, we fabricated TiO2 nanotube arrays (TNAs), TiO2 nanowires on nanotube arrays (TNWs/TNAs), Au nanoparticle (NP)-decorated-TNAs, and TNWs/TNAs, which were applied for assessing the photocatalytic degradation of eight antibiotics, simultaneously. The TNAs and TNWs/TNAs were synthesized by anodization using an aqueous NH4F/ethylene glycol solution. Au NPs were synthesized by chemical reduction method, and used to decorate on TNAs and TNWs/TNAs. All the TiO2 nanostructures exhibited anatase phase and well-defined morphology. The photocatalytic performance of TNAs, TNWs/TNAs, Au-TNAs and Au-TNWs/TNAs was studied by monitoring the degradation of amoxicillin, ampicillin, doxycycline, oxytetracycline, lincomycin, vancomycin, sulfamethazine, and sulfamethoxazole under ultraviolet (UV)-visible (VIS), or VIS illumination by LC-MS/MS method. All the four kinds of nanomaterials degraded the antibiotics effectively and rapidly, in which most antibiotics were removed completely after 20 min treatment. The Au-TNWs/TNAs exhibited the highest photocatalytic activity in degradation of the eight antibiotics. For example, reaction rate constants of Au-TNWs/TNAs for degradation of lincomycin reached 0.26 min−1 and 0.096 min−1 under UV-VIS and VIS irradiation, respectively; and they were even higher for the other antibiotics. The excellent photocatalytic activity of Au-TNWs/TNAs was attributed to the synergistic effects of: (1) The larger surface area of TNWs/TNAs as compared to TNAs, and (2) surface plasmonic effect in Au NPs to enhance the visible light harvesting.
Background: In pregnant women with gestational diabetes mellitus (GDM), insulin resistance (IR) increases the risk of developing manifest type 2 diabetes mellitus and is associated with complications in both mother and fetus. Objectives: This research aimed to evaluate the associations between IR evaluated by 3 indices (namely updated homeostasis model assessment model (HOMA2), QUICKI, and McAuley’s index) and the diabetes risk factors and the fetal growth indices in Vietnamese women with GDM. Methods: A cross-sectional descriptive study was conducted on 370 women with GDM and 40 healthy pregnant women from January 2015 to May 2019. IR was calculated by HOMA2 (HOMA2-IR), QUICKI, and McAuley’s index. Fetal anthropometric measurements were assessed via ultrasound which was performed and interpreted by ultrasound experts. Results: In the simple regression analysis, McAuley’s index illustrated had statistically significant correlations to the highest number of risk factors of diabetes mellitus compared with HOMA2-IR and QUICKI indices. Moreover, McAuley’s index correlated statistically significantly to the highest number of fetal ultrasound measurements factors such as including biparietal diameter (BPD) ( r = −0.271, P < .001), head circumference (HC) ( r = −0.225, P < .001), abdominal circumference (AC) ( r = −0.214, P < .001), femur length (FL) ( r = −0.231, P < .001), estimated fetal weight (EFW) ( r = −0.239, P < .001) and fetal estimated age ( r = −0.299, P < .001). In the multivariable analysis, the McAuley’s index contributed the greatest to AC (Standardized B of −0.656, P < .001). Conclusion: The McAuley’s index was significantly associated with a higher number of more risk factors for diabetes mellitus as well as fetal ultrasound sonography findings measurements than compared with HOMA2-IR and QUICKI indices.
This paper addresses the problem of modifying the edge lengths of a tree in minimum total cost such that a prespecified vertex becomes the 1-center of the perturbed tree. This problem is called the inverse 1-center problem on trees. We focus on the problem under Chebyshev norm and Hamming distance. From special properties of the objective functions, we can develop combinatorial algorithms to solve the problem. Precisely, if there does not exist any vertex coinciding with the prespecified vertex during the modification of edge lengths, the problem under Chebyshev norm or bottleneck Hamming distance is solvable in O(n log n) time, where n + 1 is the number of vertices of the tree. Dropping this condition, the problem can be solved in O(n 2 ) time.
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