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nanomaterials and their application in the biomedicine. [7] Indeed, over the past decades, formation of protein corona onto surfaces of NPs has attracted great attentions in the nanotechnology and biology community, and impressive progress has been achieved. [8,9] Nevertheless, a quantitative analysis on the formation process of the protein corona is very difficult and complicated, owing to the highly dynamic NP-protein interaction process and too many influencing factors.Among various types of nanomaterials, ultrasmall NPs with sizes smaller than 10 nm (i.e., quantum dots, [10] metal nanoclusters, [11] and carbon dots) [12] show unique properties and great potential in molecular imaging for disease diagnosis and cancer treatment. Particularly, compared with large NPs, these ultrasmall NPs can more readily escape from macrophages, pass biological barriers, show longer blood circulation times, and be easily degraded or excreted in the living systems. [13,14] Thus, these ultrasmall NPs have been widely employed in various biomedical applications. However, a deep and comprehensive understanding of their biological behavior, i.e., NP-protein interactions, remains largely unclear yet mainly due to the lack of appropriate in situ characterization tools for these ultrasmall NPs. While researchers have developed several techniques such as fluorescence correlation spectroscopy, [15] dynamic light scattering, [16] synchrotron radiation-based techniques, [17] and nuclear magnetic resonance spectroscopy [18] enabling quantitative analysis of protein corona, it still requires the development of new approaches to monitor the protein-NP interactions in a highly sensitive and quantitative manner owing to the diversity of nanomaterials and complexity of biological systems. [19] Fluorescence resonance energy transfer (FRET) is the process of nonradiative transmission of excitation energy from an excited state donor to a ground state acceptor, resulting from the dipole-dipole interactions. [20] The efficiency of this energy transfer process is inversely proportional to the sixth power of the distance between donor and acceptor, making FRET extremely sensitive to small changes in distance. Therefore, FRET has been widely exploited as a "spectroscopic ruler" in many biological and biophysical researches. For example, FRET can be employed for monitoring conformational changes of biomolecules, [21] developing highly sensitive fluorescence A fundamental understanding of nanoparticle-protein corona and its interactions with biological systems is essential for future application of engineered nanomaterials. In this work, fluorescence resonance energy transfer (FRET) is employed for studying the protein adsorption behavior of nanoparticles. The adsorption of human serum albumin (HSA) onto the surface of InP@ZnS quantum dots (QDs) with different chirality (dand l-penicillamine) shows strong discernible differences in the binding behaviors including affinity and adsorption orientation that are obtained upon quantitative analysis of FRET data...

Calibration is a process of comparing model results with field data and making the appropriate adjustments so that both results agree. Calibration methods can involve formal optimization methods or manual methods in which the modeler informally examines alternative model parameters. The development of a calibration framework typically involves the following: (1) definition of the model variables, coefficients, and equations; (2) selection of an objective function to measure the quality of the calibration; (3) selection of the set of data to be used for the calibration process; and (4) selection of an optimization/manual scheme for altering the coefficient values in the direction of reducing the objective function. Hydraulic calibration usually involves the modification of system demands, fine-tuning the roughness values of pipes, altering pump operation characteristics, and adjusting other model attributes that affect simulation results, in particular those that have significant uncertainty associated with their values. From the previous steps, it is clear that model calibration is neither unique nor a straightforward technical task. The success of a calibration process depends on the modeler's experience and intuition, as well as on the mathematical model and procedures adopted for the calibration process. This paper provides a summary of the Battle of the Water Calibration Networks (BWCN), the goal of which was to objectively compare the solutions of different approaches to the calibration of water distribution systems through application to a real water distribution system. Fourteen teams from academia, water utilities, and private consultants participated. The BWCN outcomes were presented and assessed at the 12th Water Distribution Systems Analysis conference in Tucson, Arizona, in September 2010. This manuscript summarizes the BWCN exercise and suggests future research directions for the calibration of water distribution systems.

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The robust optimization method has progressively become a research hot spot as a valuable means for dealing with parameter uncertainty in optimization problems. Based on the asymmetric cost consensus model, this paper considers the uncertainties of the experts' unit adjustment costs under the background of group decision making. At the same time, four uncertain level parameters are introduced. For three types of minimum cost consensus models with direction restrictions, including MCCM-DC, -MCCM-DC and threshold-based (TB)-MCCM-DC, the robust cost consensus models corresponding to four types of uncertainty sets (Box set, Ellipsoid set, Polyhedron set and Interval-Polyhedron set) are established. Sensitivity analysis is carried out under different parameter conditions to determine the robustness of the solutions obtained from robust optimization models. The robust optimization models are then compared to the minimum cost models for consensus. The example results show that the Interval-Polyhedron set's robust models have the smallest total costs and strongest robustness. Decision makers can choose the combination of uncertainty sets and uncertain levels according to their risk preferences to minimize the total cost. Finally, in order to reduce the conservatism of the classical robust optimization method, the pricing information of the new product MACUBE 550 is used to build a data-driven robust optimization model. Ellipsoid uncertainty set is proved to better trade-off the average performance and robust performance through different measurement indicators. Therefore, the uncertainty set can be selected according to the needs of the group.