Revealed Preference and Choice under Uncertainty

We employ the theory of rational choice to examine whether observable choices from feasible sets of prospects can be generated by the optimization of some underlying decision criterion under uncertainty. Rather than focusing on a specific theory of choice, our objective is to formulate a general approach that is designed to cover the various decision criteria that have been proposed in the literature. We use a mild dominance property to define a class of suitable choice criteria. In addition to rationalizability per se, we characterize transitive and Suzumura consistent rationalizability in the presence of dominance.

Contracting for innovation under knightian uncertainty

At any given point in time, the collection of assets existing in the economy is observable. Each asset is a function of a set of contingencies. The union taken over all assets of these contingencies is what we call the set of publicly known states. An innovation is a set of states that are not publicly known along with an asset (in a broad sense) that pays contingent on those states. The creator of an innovation is an entrepreneur. He is represented by a probability measure on the set of new states. All other agents perceive the innovation as ambiguous: each of them is represented by a set of probabilities on the new states. The agents in the economy are classified with respect to their attitude towards this Ambiguity: the financiers are (locally) Ambiguity-seeking while the consumers are Ambiguity-averse. An entrepreneur and a financier come together when the former seeks funds to implement his project and the latter seeks new profit opportunities. The resulting contracting problem does not fall within the standard theory due to the presence of Ambiguity (on the financier’s side) and to the heterogeneity in the parties’ beliefs. We prove existence and monotonicity (i.e., truthful revelation) of an optimal contract. We characterize such a contract under the additional assumption that the financiers are globally Ambiguity-seeking. Finally, we re-formulate our results in an insurance framework and extend the classical result of Arrow [4] and the more recent one of Ghossoub. In the case of an Ambiguity-averse insurer, we also show that an optimal contract has the form of a generalized deductible.

Marine yeast isolates from Arabian Sea and Bay of Bengal :Biochemical, Molecular and Phylogenetic Analysis

the present study was undertaken with the following objectives: 1. Isolation and identification of yeasts from Arabian Sea and Bay of Bengal. 2. Molecular characterization of yeast isolates and phylogenetic analysis 3. Physiological and biochemical characterization of the isolates. 4. Proximate composition of yeast biomass and bioactive compounds. The Thesis is comprised of six chapters. A general introduction to the topic is given in Chapter1. Isolation and identification of marine yeasts are presented in Chapter 2. Chapter 3 deals with molecular identification and physiological characterization of Non- pigmented yeasts. Molecular identification and physiological characterization of pigmented yeast is presented in Chapter 4. Proximate composition of yeast biomass of various genera and their bioactive compounds are illustrated in Chapter 5. A summary of the results of the present study is given in Chapter 6. References and Appendices are followed

Molecular characterization and phylogenetic analysis of a penaeidin-like antimicrobial peptide, Fi-penaeidin from Fenneropenaeus indicus

Antimicrobial peptides (AMPs) play a major role in innate immunity. Penaeidins are a family of AMPs that appear to be expressed in all penaeid shrimps. Penaeidins are composed of an N-terminal proline-rich domain, followed by a C-terminal domain containing six cysteine residues organized in two doublets. This study reports the first penaeidin AMP sequence, Fi-penaeidin (GenBank accession number HM243617) from the Indian white shrimp, Fenneropenaeus indicus. The full length cDNA consists of 186 base pairs encoding 61 amino acidswith an ORF of 42 amino acids and contains a putative signal peptide of 19 amino acids. Comparison of F. indicus penaeidin (Fi-penaeidin) with other known penaeidins showed that it shared maximum similarity with penaeidins of Farfantepenaeus paulensis and Farfantepenaeus subtilis (96% each). Fi-penaeidin has a predicted molecular weight (MW) of 4.478 kDa and theoretical isoelectric point (pI) of 5.3

Molecular Characterisation and Phylogenetic Analysis of a Novel Isoform of Hepatic Antimicrobial Peptide, Hepcidin (Zc-hepc1), from the Coral Fish Moorish idol, Zanclus cornutus (Linnaeus,1758)

Hepcidin is a family of short cysteine-rich antimicrobial peptides (AMPs) participating in various physiological functions with inevitable role in host immune responses. Present study deals with identification and characterisation of a novel hepcidin isoform from coral fish Zanclus cornutus. The 81 amino acid (aa) preprohepcidin obtained from Z. cornutus consists of a hydrophobic aa rich 22 mer signal peptide, a highly variable proregion of 35 aa and a bioactive mature peptide with 8 conserved cysteine residues which contribute to the disulphide back bone. The mature hepcidin, Zc-hepc1 has a theoretical isoelectric point of 7.46, a predicted molecular weight of 2.43 kDa and a net positive charge of ?1. Phylogenetic analysis grouped Z. cornutus hepcidin with HAMP2 group hepcidins confirming the divergent evolution of hepcidin-like peptide in fishes. Zc-hepc1 can attain a b-hairpin-like structure with two antiparallel b-sheets. This is the first report of an AMP from the coral fish Z. cornutus.

Black yeasts from the slope sediments of Bay of Bengal: phylogenetic and functional characterization

Occurrence of black yeasts in the slope sediments of Bay of Bengal was investigated during FORV Sagar Sampada cruises 236 and 245. The black yeast population was found to be very scanty in the area and the isolates could be obtained from 200m to 1000m depth regions in the slope sediments. The isolates were identified as Hortaea werneckii by Internal Transcribed Spacer (ITS) sequencing. The biodegradation potential of these strains was found to be very high with all the strains exhibiting protease, lipase and amylase production. The optimum growth conditions were pH 8, salinity 30 ppt and temperature 30oC. The pigment melanin, in these organisms was identified to be of dihydroxynaphthalene type by NMR. The melanin was found to exhibit inhibitory activity against different human and fish pathogens. Melanin degrading enzyme could also be extracted from these organisms

Regional climate model applications on sub-regional scales over the Indian monsoon region: The role of domain size on downscaling uncertainty

Regional climate models are becoming increasingly popular to provide high resolution climate change information for impacts assessments to inform adaptation options. Many countries and provinces requiring these assessments are as small as 200,000 km2 in size, significantly smaller than an ideal domain needed for successful applications of one-way nested regional climate models. Therefore assessments on sub-regional scales (e.g., river basins) are generally carried out using climate change simulations performed for relatively larger regions. Here we show that the seasonal mean hydrological cycle and the day-to-day precipitation variations of a sub-region within the model domain are sensitive to the domain size, even though the large scale circulation features over the region are largely insensitive. On seasonal timescales, the relatively smaller domains intensify the hydrological cycle by increasing the net transport of moisture into the study region and thereby enhancing the precipitation and local recycling of moisture. On daily timescales, the simulations run over smaller domains produce higher number of moderate precipitation days in the sub-region relative to the corresponding larger domain simulations. An assessment of daily variations of water vapor and the vertical velocity within the sub-region indicates that the smaller domains may favor more frequent moderate uplifting and subsequent precipitation in the region. The results remained largely insensitive to the horizontal resolution of the model, indicating the robustness of the domain size influence on the regional model solutions. These domain size dependent precipitation characteristics have the potential to add one more level of uncertainty to the downscaled projections.

Uncertainty Propagation in Model-Based Recognition

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

The efficiency of direct payments versus tax reductions under uncertainty

This paper analyzes the optimal behavior of farmers in the presence of direct payments and uncertainty. In an empirical analysis for Switzerland, it confirms previously obtained theoretical results and determines the magnitude of the theoretical predicted effects. The results show that direct payments increase agricultural production between 3.7% to 4.8%. Alternatively to direct payments, the production effect of tax reductions is evaluated in order to determine its magnitude. The empirical analysis corroborates the theoretical results of the literature and demonstrates that tax reductions are also distorting, but to a substantially lesser degree if losses are not offset. However, tax reductions, independently whether losses are offset or not, lead to higher government spending than pure direct payments

Reaction times as a measure of uncertainty. 'Tiempo de reacci??n como una medida de incertidumbre'

Resumen tomado de la publicaci??n

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented