The acquisition of reliable kinetic parameters for the characterization of biomolecular interactions is an important component of the drug discovery and development process. While several benchmark studies have explored the variability of kinetic rate constants obtained from multiple laboratories and biosensors, a direct comparison of these instruments' performance has not been undertaken, and systematic factors contributing to data variability from these systems have not been discussed. To address these questions, a panel of ten high-affinity monoclonal antibodies was simultaneously evaluated for their binding kinetics against the same antigen on four biosensor platforms: GE Healthcare's Biacore T100, Bio-Rad's ProteOn XPR36, ForteBio's Octet RED384, and Wasatch Microfluidics's IBIS MX96. We compared the strengths and weaknesses of these systems and found that despite certain inherent systematic limitations in instrumentation, the rank orders of both the association and dissociation rate constants were highly correlated between these instruments. Our results also revealed a trade-off between data reliability and sample throughput. Biacore T100, followed by ProteOn XPR36, exhibited excellent data quality and consistency, whereas Octet RED384 and IBIS MX96 demonstrated high flexibility and throughput with compromises in data accuracy and reproducibility. Our results support the need for a "fit-for-purpose" approach in instrument selection for biosensor studies.

Ad vanced Imaging Group Siemens Corporate Research Princeton. New Jersey Image-flow is a major source of three-dimensional information. This paper describes a new framework for computing image-flow from time-varying imagery. In this framework. image-flow information is classified into two categories-conservation information and ueighborhood information. Each type of information is recovered in the form of an estimate accompanied by a covariance-matrix. Image-flow is then computed by fusing the two estimates using estimation-theoretic techniques. This framework offers the following principal advantages. Firstly. it allows estimation of certain types of discontinuous flow-fields without any a-priori knowledge about the location of discontinuities. The flow-fields thus recovered are not blurred at motion-boundaries. Secondly. covariance matrices (or alternatively. confidence-measures) are associated with the estimate of image-flow at. each stage of computation. The estimation-theoretic nature of the framework and its ability to provide covariance matrices make it very useful in the context of applications such as incremental estimation of scene-depth using techniques based 011 Kalman filtering. In this paper. an algorithm based on this framework is used to recover image-flow from two image-sequences. To illllstratf> an application, the image-flow estimates and their covariance matrices thus obtained are also used to recow'r scene-depth.

Abstract-Software measurement is a key factor in managing, controlling, and improving the software development processes. Software quality is one of the most important factors for assessing the global competitive position of any software company. Thus the quantification of quality parameters and integrating them into quality models is very essential. Software quality criteria are not very easily measured and quantified. Many attempts have been made to exactly quantify the software quality parameters using various models such as ISO/IEC 9126 Quality Model, Boehm's Model, McCall's model, etc. In this paper an attempt has been made to provide a tool for precisely quantifying software quality factors with the help of quality factors stated in ISO/IEC 9126 model. Due to the unpredictable nature of the software quality attributes, the fuzzy multi criteria approach has been used to evolve the quality of the software.

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This paper presents an Interactive Fuzzy Multi-Objective Linear Programming (IFMOLP) model for water quality management in a river basin. The IFMOLP model formulated will first evaluate dissolved oxygen (DO) concentrations or DO deficits at a point in different reaches depending on the overall Biochemical Oxygen Demand (BOD) concentration present in the respective drain. Subsequently, the model incorporates the aspirations and conflicting objectives of the decision maker (DM) by taking into consideration the aspects relevant for pollution control boards as well as dischargers responsible for generating wastewater. The uncertainty associated with specifying the water quality criteria (based on DO concentration or DO deficit) and treatment cost to remove pollution level is incorporated by interacting the decision maker. In this process DM is asked to specify the reference aspiration levels of achievement for the values of all membership functions generated with respect to each objective. This provides flexibility for the pollution control authorities and dischargers to specify their aspirations. IFMOLP model developed herein is then used in a case study for the evaluation of optimal BOD removal in different drains located across the river Yamuna at New Delhi, India. The presented model will simulate the allocation of waste load efficiencies with satisfactory results which will indicate usefulness of the model in managing more complex river basins along with better flexible policies of water management.Springer 516 Water Resour Manage (2007) 21: [515][516][517][518][519][520][521][522][523][524][525][526][527][528][529][530][531][532]

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