A Probabilistic Modelling Approach for Rational Belief in Meta-Epistemic Contexts

This work is part of the larger project INTEGRITY. Integrity develops a conceptual frame integrating beliefs with individual (and consensual group) decision making and action based on belief awareness. Comments and criticisms are most welcome via email. Starting with a thorough discussion of the conceptual embedding in existing schools of thought and liter- ature we develop a framework that aims to be empirically adequate yet scalable to epistemic states where an agent might testify to uncertainly believe a propositional formula based on the acceptance that a propositional formula is possible, called accepted truth. The familiarity of human agents with probability assignments make probabilism particularly appealing as quantitative modelling framework for defeasible reasoning that aspires empirical adequacy for gradual belief expressed as credence functions. We employ the inner measure induced by the probability measure, going back to Halmos, interpreted as estimate for uncertainty. Doing so omits generally requiring direct probability assignments testi�ed as strength of belief and uncertainty by a human agent. We provide a logical setting of the two concepts uncertain belief and accepted truth, completely relying on the the formal frameworks of 'Reasoning about Probabilities' developed by Fagin, Halpern and Megiddo and the 'Metaepistemic logic MEL' developed by Banerjee and Dubois. The purport of Probabilistic Uncertainty is a framework allowing with a single quantitative concept (an inner measure induced by a probability measure) expressing two epistemological concepts: possibilities as belief simpliciter called accepted truth, and the agents' credence called uncertain belief for a criterion of evaluation, called rationality. The propositions accepted to be possible form the meta-epistemic context(s) in which the agent can reason and testify uncertain belief or suspend judgement

A Probabilistic Modelling Approach for Rational Belief in Meta-Epistemic Contexts

This work is part of the larger project INTEGRITY. Integrity develops a conceptual frame integrating beliefs with individual (and consensual group) decision making and action based on belief awareness. Comments and criticisms are most welcome via email. The text introduces the conceptual (internalism, externalism), quantitative (probabilism) and logical perspectives (logics for reasoning about probabilities by Fagin, Halpern, Megiddo and MEL by Banerjee, Dubois) for the framework

A Probabilistic Modelling Approach for Rational Belief in Meta-Epistemic Contexts

This work is part of the larger project INTEGRITY. Integrity develops a conceptual frame integrating beliefs with individual (and consensual group) decision making and action based on belief awareness. Comments and criticisms are most welcome via email. Starting with a thorough discussion of the conceptual embedding in existing schools of thought and liter- ature we develop a framework that aims to be empirically adequate yet scalable to epistemic states where an agent might testify to uncertainly believe a propositional formula based on the acceptance that a propositional formula is possible, called accepted truth. The familiarity of human agents with probability assignments make probabilism particularly appealing as quantitative modelling framework for defeasible reasoning that aspires empirical adequacy for gradual belief expressed as credence functions. We employ the inner measure induced by the probability measure, going back to Halmos, interpreted as estimate for uncertainty. Doing so omits generally requiring direct probability assignments testi�ed as strength of belief and uncertainty by a human agent. We provide a logical setting of the two concepts uncertain belief and accepted truth, completely relying on the the formal frameworks of 'Reasoning about Probabilities' developed by Fagin, Halpern and Megiddo and the 'Metaepistemic logic MEL' developed by Banerjee and Dubois. The purport of Probabilistic Uncertainty is a framework allowing with a single quantitative concept (an inner measure induced by a probability measure) expressing two epistemological concepts: possibilities as belief simpliciter called accepted truth, and the agents' credence called uncertain belief for a criterion of evaluation, called rationality. The propositions accepted to be possible form the meta-epistemic context(s) in which the agent can reason and testify uncertain belief or suspend judgement

A Probabilistic Modelling Approach for Rational Belief in Meta-Epistemic Contexts

This work is part of the larger project INTEGRITY. Integrity develops a conceptual frame integrating beliefs with individual (and consensual group) decision making and action based on belief awareness. Comments and criticisms are most welcome via email. The text introduces the conceptual (internalism, externalism), quantitative (probabilism) and logical perspectives (logics for reasoning about probabilities by Fagin, Halpern, Megiddo and MEL by Banerjee, Dubois) for the framework

Defining Multiple Characteristic Raman Bands of α-Amino Acids as Biomarkers for Planetary Missions Using a Statistical Method

Biomarker molecules, such as amino acids, are key to discovering whether life exists elsewhere in the Solar System. Raman spectroscopy, a technique capable of detecting biomarkers, will be on board future planetary missions including the ExoMars rover. Generally, the position of the strongest band in the spectra of amino acids is reported as the identifying band. However, for an unknown sample, it is desirable to define multiple characteristic bands for molecules to avoid any ambiguous identification. To date, there has been no definition of multiple characteristic bands for amino acids of interest to astrobiology. This study examinedL-alanine, L-aspartic acid, L-cysteine, L-glutamine and glycine and defined several Raman bands per molecule for reference as characteristic identifiers. Per amino acid, 240 spectra were recorded and compared using established statistical tests including ANOVA. The number of characteristic bands defined were 10, 12, 12, 14 and 19 for L-alanine (strongest intensity band: 832 cm-1), L-aspartic acid (938 cm-1), L-cysteine (679 cm-1),L-glutamine (1090 cm−1) and glycine (875 cm-1), respectively. The intensity of bands differed by up to six times when several points on the crystal sample were rotated through 360 °; to reduce this effect when defining characteristic bands for other molecules, we find that spectra should be recorded at a statistically significant number of points per sample to remove the effect of sample rotation. It is crucial that sets of characteristic Raman bands are defined for biomarkers that are targets for future planetary missions to ensure a positive identification can be made

Uncertainty analysis using Bayesian Model Averaging: a case study of input variables to energy models and inference to associated uncertainties of energy scenarios

Background Energy models are used to illustrate, calculate and evaluate energy futures under given assumptions. The results of energy models are energy scenarios representing uncertain energy futures. Methods The discussed approach for uncertainty quantification and evaluation is based on Bayesian Model Averaging for input variables to quantitative energy models. If the premise is accepted that the energy model results cannot be less uncertain than the input to energy models, the proposed approach provides a lower bound of associated uncertainty. The evaluation of model-based energy scenario uncertainty in terms of input variable uncertainty departing from a probabilistic assessment is discussed. Results The result is an explicit uncertainty quantification for input variables of energy models based on well-established measure and probability theory. The quantification of uncertainty helps assessing the predictive potential of energy scenarios used and allows an evaluation of possible consequences as promoted by energy scenarios in a highly uncertain economic, environmental, political and social target system. Conclusions If societal decisions are vested in computed model results, it is meaningful to accompany these with an uncertainty assessment. Bayesian Model Averaging (BMA) for input variables of energy models could add to the currently limited tools for uncertainty assessment of model-based energy scenarios

Mechanisms and Specificity of Phenazine Biosynthesis Protein PhzF

Phenazines are bacterial virulence and survival factors with important roles in infectious disease. PhzF catalyzes a key reaction in their biosynthesis by isomerizing (2 S,3 S)-2,3-dihydro-3-hydroxy anthranilate (DHHA) in two steps, a [1,5]-hydrogen shift followed by tautomerization to an aminoketone. While the [1,5]-hydrogen shift requires the conserved glutamate E45, suggesting acid/base catalysis, it also shows hallmarks of a sigmatropic rearrangement, namely the suprafacial migration of a non-acidic proton. To discriminate these mechanistic alternatives, we employed enzyme kinetic measurements and computational methods. Quantum mechanics/molecular mechanics (QM/MM) calculations revealed that the activation barrier of a proton shuttle mechanism involving E45 is significantly lower than that of a sigmatropic [1,5]-hydrogen shift. QM/MM also predicted a large kinetic isotope effect, which was indeed observed with deuterated substrate. For the tautomerization, QM/MM calculations suggested involvement of E45 and an active site water molecule, explaining the observed stereochemistry. Because these findings imply that PhzF can act only on a limited substrate spectrum, we also investigated the turnover of DHHA derivatives, of which only O-methyl and O-ethyl DHHA were converted. Together, these data reveal how PhzF orchestrates a water-free with a water-dependent step. Its unique mechanism, specificity and essential role in phenazine biosynthesis may offer opportunities for inhibitor development

Detection of pigments of halophilic endoliths from gypsum: Raman portable instrument and European Space Agency's prototype analysis

NoA prototype instrument, under development at the University of Leicester, for the future European Space Agency (ESA) ExoMars mission, was used for the analysis of microbial pigments within a stratified gypsum crust from a hypersaline saltern evaporation pond at Eilat (Israel). Additionally, the same samples were analysed using a miniaturized Raman spectrometer, featuring the same 532 nm excitation. The differences in the position of the specific bands, attributed to carotenoid pigments from different coloured layers, were minor when analysed by the ESA prototype instrument; therefore, making it difficult to distinguish among the different pigments. The portable Delta Nu Advantage instrument allowed for the discrimination of microbial carotenoids from the orange/green and purple layers. The purpose of this study was to complement previous laboratory results with new data and experience with portable or handheld Raman systems, even with a dedicated prototype Raman system for the exploration of Mars. The latter is equipped with an excitation wavelength falling within the carotenoid polyene resonance region. The ESA prototype Raman instrument detected the carotenoid pigments (biomarkers) with ease, although further detailed distinctions among them were not achieved