Removal of imidacloprid and acetamiprid in tea infusions by microfiltration membrane using dead‐end model was investigated in the present study. The results showed that microfiltration significantly promoted the removal of both pesticides (P < 0.05) in tea infusions. Furthermore, the extent of removal was strongly influenced by the pore size of membrane, operational pressure and the concentrations of tea infusions. The initial concentration of imidacloprid and acetamiprid showed no significant effect on their removal rates. The maximum removal rates were 79.7% for imidacloprid and 81.9% acetamiprid. The changes in major chemical components of tea infusions after microfiltration were evaluated. The results indicated that microfiltration caused no considerable changes in total polyphenols and total free amino acids, and small but statistically significant losses (6.3–18.0%) of eight catechins and three methylxanthines when filtration volume reached to 200 mL. The present study validated the application of microfiltration as a potentially feasible and promising method for the removal of imidacloprid and acetamiprid residues from tea infusions. 相似文献
This work proposed a new path to synthesize Ni-phyllosilicate through the reaction of nickel hydroxide and silica sol on the surface of Ni-foam to form the monolithic Ni-phyllosilicate/Ni-foam catalyst. Ni-phyllosilicate could reprint the morphology of nickel hydroxid and firmly anchor on the framework of Ni-foam, which obtained fine Ni particles of 2.8 nm after reduction in H2 at 650 °C, resulting in high catalytic activity for CO2 methanation. In addition, the Ni-phyllosilicate/Ni-foam catalyst showed high long-term stability in a 100 h-lifetime test owing to the combined effects of surface confinement of Ni-phyllosilicate, firm anchoring between Ni-phyllosilicate and Ni-foam, as well as the high heat transfer property of Ni-foam.
Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.
Climate change raises many concerns for urban water management because of the effects on all aspects of the hydrological cycle. Urban water infrastructure has traditionally been designed using historical observations and assuming stationary climatic conditions. The capability of this infrastructure, whether for storm-water drainage, or water supply, may be over- or under-designed for future climatic conditions. In particular, changes in the frequency and intensity of extreme rainfall events will have the most acute effect on storm-water drainage systems. Therefore, it is necessary to take future climatic conditions into consideration in engineering designs in order to enhance water infrastructure investment planning practices in a long time horizon. This paper provides the initial results of a study that is examining ways to enhance urban infrastructure investment planning practices against changes in hydrologic regimes for a changing climate. Design storms and intensity-duration-frequency curves that are used in the engineering design of storm-water drainage systems are developed under future climatic conditions by empirically adjusting the general circulation model output, and using the Gumbel distribution and the Chicago method. Simulations are then performed on an existing storm-water drainage system from NE Calgary to investigate the resiliency of the system under climate change. 相似文献