Ultrafast Non-Radiative Decay of Gas-Phase Nucleosides

The ultrafast photo-physical properties of DNA are crucial in providing a stable basis for life. Although the DNA bases efficiently absorb ultraviolet (UV) radiation, this energy can be dissipated to the surrounding environment by the rapid conversion of electronic energy to vibrational energy within about a picosecond. The intrinsic nature of this internal conversion process has previously been demonstrated through gas phase experiments on the bases, supported by theoretical calculations. De-excitation rates appear to be accelerated when individual bases are hydrogen bonded to solvent molecules or their complementary Watson-Crick pair. In this paper, the first gas-phase measurements of electronic relaxation in DNA nucleosides following UV excitation are reported. Using a pump-probe ionization scheme, the lifetimes for internal conversion to the ground state following excitation at 267 nm are found to be reduced by around a factor of two for adenosine, cytidine and thymidine compared with the isolated bases. These results are discussed in terms of a recent proposition that a charge transfer state provides an additional internal conversion pathway mediated by proton transfer through a sugar to base hydrogen bond.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Rural communities and wind farms: a contingent valuation investigation

Using the contingent valuation method, this study investigates the preferences of local people for a wind farm that is planned in the Province of Rome. We estimate the reductions in their bimonthly electrical bills over a period of time that respondents are willing to accept as compensation for the installation of the wind farm. Our results suggest that respondents who perceive that the wind farm generates substantial negative impacts on landscape beauty ask higher reductions than others, while respondents who believe that the wind farm produces economic benefits for local communities ask lower reductions than others. Finally, we find that the demand for compensative measures is influenced particularly by socio-economic factors such as age and education.

How many bad apples are in a bunch? An experimental investigation of perceived pesticide residue risks

Subjective risks of having contaminated apples elicited via the Exchangeability Method (EM) are examined in this study. In particular, as the experimental design allows us to investigate the validity of elicited risk measures, we examine the magnitude of differences between valid and invalid observations. In addition, using an econometric model, we also explore the effect of consumers’ socioeconomic status and attitudes toward food safety on subjects’ perceptions of pesticide residues in apples. Results suggest first, that consumers do not expect an increase in the number of apples containing only one pesticide residue, but, rather, in the number of those apples with traces of multiple residues. Second, we find that valid subjective risk measures do not significantly diverge from invalid ones, indicative of little effect of internal validity on the actual magnitude of subjective risks. Finally, we show that subjective risks depend on age, education, a subject’s ties to the apple industry, and consumer association membership.

Eliciting and estimating valid subjective probabilities: An experimental investigation of the Exchangeability Method.

Using a laboratory experiment, we investigate whether incentive compatibility affects subjective probabilities elicited via the exchangeability method (EM), an elicitation technique consisting of several chained questions. We hypothesize that subjects who are aware of the chaining strategically behave and provide invalid subjective probabilities, while subjects who are not aware of the chaining state their real beliefs and provide valid subjective probabilities. The validity of subjective probabilities is investigated using de Finetti's notion of coherence, under which probability estimates are valid if and only if they obey all axioms of probability theory.
Four experimental treatments are designed and implemented. Subjects are divided into two initial treatment groups: in the first, they are provided with real monetary incentives, and in the second, they are not. Each group is further sub-divided into two treatment groups, in the first, the chained structure of the experimental design is made clear to the subjects, while, in the second, the chained structure is hidden by randomizing the elicitation questions.
Our results suggest that subjects provided with monetary incentives and randomized questions provide valid subjective probabilities because they are not aware of the chaining which undermines the incentive compatibility of the exchangeability method.

Does climate change information affect stated risks of pine beetle impacts on forests? An application of the exchangeability method

Risks are an essential feature of future climate change impacts. We explore whether knowledge that climate change might be the source of increasing pine beetle impacts on public or private forests affects stated risk estimates of damage, elicited using the exchangeability method. We find that across subjects the difference between public and private forest status does not influence stated risks, but the group told that global warming is the cause of pine beetle damage has significantly higher risk perceptions than the group not given this information.

Confronto tra diverse localizzazioni di un impianto eolico contemperando produttività ed impatto visivo

This paper proposes a series of variations in designing the location of a wind farm on Monti della Tolfa. These project solutions aim at mitigating the visual impact caused by the wind aerogenerators. Besides the usual location of the wind aerogenerators on the skyline, these alternatives within the project design relate to the placement of wind turbines in the middle and at the bottom of the hillside. Other possible mitigation forms relate to the dimensions and the colour of the wind towers. This study proposes both a non-monetary and monetary analysis of the visual impact related to each project proposal. The final aim of the paper is to analyze economic and financial costs-benefits for each alternative to find out the economic optimal solution.