Multi-objective global optimization for hydrologic models

The development of automated (computer-based) calibration methods has focused mainly on the selection of a single-objective measure of the distance between the model-simulated output and the data and the selection of an automatic optimization algorithm to search for the parameter values which minimize that distance. However, practical experience with model calibration suggests that no single-objective function is adequate to measure the ways in which the model fails to match the important characteristics of the observed data. Given that some of the latest hydrologic models simulate several of the watershed output fluxes (e.g. water, energy, chemical constituents, etc.), there is a need for effective and efficient multi-objective calibration procedures capable of exploiting all of the useful information about the physical system contained in the measurement data time series. The MOCOM-UA algorithm, an effective and efficient methodology for solving the multiple-objective global optimization problem, is presented in this paper. The method is an extension of the successful SCE-UA single-objective global optimization algorithm. The features and capabilities of MOCOM-UA are illustrated by means of a simple hydrologic model calibration study

Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information

Several contributions to the hydrological literature have brought into question the continued usefulness of the classical paradigm for hydrologic model calibration. With the growing popularity of sophisticated 'physically based' watershed models (e.g., landsurface hydrology and hydrochemical models) the complexity of the calibration problem has been multiplied many fold. We disagree with the seemingly widespread conviction that the model calibration problem will simply disappear with the availability of more and better field measurements. This paper suggests that the emergence of a new and more powerful model calibration paradigm must include recognition of the inherent multiobjective nature of the problem and must explicitly recognize the role of model error. The results of our preliminary studies are presented. Through an illustrative case study we show that the multiobjective approach is not only practical and relatively simple to implement but can also provide useful information about the limitations of a model

Subdural Hematoma in Grave’s Disease Induced Thrombocytopenia.

Subdural hematoma (SDH) usually occurs secondary to trauma, in bleeding disorders it may occur spontaneously. It is a rare complication of immune thrombocytopenia. Here we report a case of 45 years female presenting with presenting with complaints of headache, palpitation and menorrhagia and later diagnosed to be a case of Grave's disease with thrombocytopenia with sub dural hematoma. No such case reports are available in literature

Calibrated Langevin dynamics simulations of intrinsically disordered proteins

We perform extensive coarse-grained (CG) Langevin dynamics simulations of intrinsically disordered proteins (IDPs), which possess fluctuating conformational statistics between that for excluded volume random walks and collapsed globules. Our CG model includes repulsive steric, attractive hydrophobic, and electrostatic interactions between residues and is calibrated to a large collection of single-molecule fluorescence resonance energy transfer data on the inter-residue separations for 36 pairs of residues in five IDPs: $\alpha$-, $\beta$-, and $\gamma$-synuclein, the microtubule-associated protein $\tau$, and prothymosin $\alpha$. We find that our CG model is able to recapitulate the average inter-residue separations regardless of the choice of the hydrophobicity scale, which shows that our calibrated model can robustly capture the conformational dynamics of IDPs. We then employ our model to study the scaling of the radius of gyration with chemical distance in 11 known IDPs. We identify a strong correlation between the distance to the dividing line between folded proteins and IDPs in the mean charge and hydrophobicity space and the scaling exponent of the radius of gyration with chemical distance along the protein.Comment: 16 pages, 10 figure

Floating-disk parylene microvalve for self-regulating biomedical flow controls

A novel self-regulating parylene micro valve is presented in this paper with potential applications for biomedical flow controls. Featuring a free-floating bendable valve disk and two-level valve seat, this surface-micromachined polymeric valve accomplishes miniature pressure/flow rate regulation in a band-pass profile stand-alone without the need of power sources or active actuation. Experimental data of underwater testing results have successfully demonstrated that the microfabricated in-channel valve can regulate water flow at 0-80 mmHg and 0-10 µL/min pressure/flow rate level, which is perfectly suitable for biomedical and lab-on-a-chip applications. For example, such biocompatible microvalve can be incorporated in ocular implants for control of eye fluid drainage to fulfill intraocular pressure (IOP) regulation in glaucoma patients