Health damage of air pollution and benefits and costs of ammonia control in the Netherlands

The paper gives a benefit-cost analysis of ammonia emission control policy in TheNetherlands. Particular care has been given to calculation of the health benefits. Adose-response relationship between air pollution and the number of work loss dayshas been estimated by applying the one-way fixed-effects method to data on workloss days due to illness and average year concentrations of air pollution in 29districts. A significant relationship is found between ammonia (NH3) and thenumber of work loss days (WLDs) and also for sulphate aerosol(SO4). The dose-responserelationship for ammonia has been used to calculate the health benefits ofreducing ammonia deposition in The Netherlands in the periods 1987-1995 and1995-2000. Together with information on other benefits and costs of ammoniaemission control the health benefits are incorporated in a benefit-cost analysis ofrecent and current ammonia control policy in The Netherlands. The benefit cost ratioturns out to be 1/3 from a national point of view and 2/3 if transfrontier benefits areincluded.

Development Of The Science Of Thermodynamics

[No abstract available]The author is grateful to the Turkish Academy of Sciences for financial support and to his assistant Berk Cevrim for participation in editing

Derivation Reduction of Metarules in Meta-interpretive Learning

Meta-interpretive learning (MIL) is a form of inductive logic programming. MIL uses second-order Horn clauses, called metarules, as a form of declarative bias. Metarules define the structures of learnable programs and thus the hypothesis space. Deciding which metarules to use is a trade-off between efficiency and expressivity. The hypothesis space increases given more metarules, so we wish to use fewer metarules, but if we use too few metarules then we lose expressivity. A recent paper used Progol’s entailment reduction algorithm to identify irreducible, or minimal, sets of metarules. In some cases, as few as two metarules were shown to be sufficient to entail all hypotheses in an infinite language. Moreover, it was shown that compared to non-minimal sets, learning with minimal sets of metarules improves predictive accuracies and lowers learning times. In this paper, we show that entailment reduction can be too strong and can remove metarules necessary to make a hypothesis more specific. We describe a new reduction technique based on derivations. Specifically, we introduce the derivation reduction problem, the problem of finding a finite subset of a Horn theory from which the whole theory can be derived using SLD-resolution. We describe a derivation reduction algorithm which we use to reduce sets of metarules. We also theoretically study whether certain sets of metarules can be derivationally reduced to minimal finite subsets. Our experiments compare learning with entailment and derivation reduced sets of metarules. In general, using derivation reduced sets of metarules outperforms using entailment reduced sets of metarules, both in terms of predictive accuracies and learning times

On the willingness to pay to reduce risks of small losses

Willingness to pay, Small loss, Risk aversion, Background risk, D81,

Euclid preparation: XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong-lensing events

Forthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-learning techniques are particularly suitable for finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong-lensing systems on the basis of their morphological characteristics. In particular, we implemented a classical CNN architecture, an inception network, and a residual network. We trained and tested our networks on different subsamples of a data set of 40 000 mock images whose characteristics were similar to those expected in the wide survey planned with the ESA mission Euclid, gradually including larger fractions of faint lenses. We also evaluated the importance of adding information about the color difference between the lens and source galaxies by repeating the same training on single- and multiband images. Our models find samples of clear lenses with 90% precision and completeness. Nevertheless, when lenses with fainter arcs are included in the training set, the performance of the three models deteriorates with accuracy values of ~0.87 to ~0.75, depending on the model. Specifically, the classical CNN and the inception network perform similarly in most of our tests, while the residual network generally produces worse results. Our analysis focuses on the application of CNNs to high-resolution space-like images, such as those that the Euclid telescope will deliver. Moreover, we investigated the optimal training strategy for this specific survey to fully exploit the scientific potential of the upcoming observations. We suggest that training the networks separately on lenses with different morphology might be needed to identify the faint arcs. We also tested the relevance of the color information for the detection of these systems, and we find that it does not yield a significant improvement. The accuracy ranges from ~0.89 to ~0.78 for the different models. The reason might be that the resolution of the Euclid telescope in the infrared bands is lower than that of the images in the visual band

Spectroscopic and photometric observations of SN1987A. V - Days 386-616

Spectroscopic and photometric observations are presented of SN1987A in the Large Magellanic Cloud made between days 386 and 616 after the Kamiokande-II neutrino event. During this period the bolometric flux from the supernova measured over the U to M wavelength range has continued to decline faster than the Co-56 decay rate. By day 560 the flux in this wavelength range accounts for only half of that expected from Co-56 decay. The estimated total flux is consistent with Co-56 remaining the sole energy source of the supernova over the period considered

Vacancy-oxygen defects in silicon: the impact of isovalent doping

Silicon is the mainstream material for many nanoelectronic and photovoltaic applications. The understanding of oxygen related defects at a fundamental level is essential to further improve devices, as vacancy-oxygen defects can have a negative impact on the properties of silicon. In the present review we mainly focus on the influence of isovalent doping on the properties of A-centers in silicon. Wherever possible, we make comparisons with related materials such as silicon germanium alloys and germanium. Recent advanced density functional theory studies that provide further insights on the charge state of the A-centers and the impact of isovalent doping are also discussed in detail

Comparative immunological characterization of type-specific and conserved B-cell epitopes of pinniped, felid and canid herpesviruses.

Murine monoclonal antibodies (MAbs) were generated against phocid herpesviruses (PhHV 2557/Han88 and 7848/Han90) isolated from European harbour seals (Phoca vitulina), and against strains of both felid (FHV strain FVR 605) and canid herpesviruses (CHV isolate 5105/Han89). MAbs were characterized with respect to certain biological properties and used to outline antigenicity profiles of isolates of PhHV (n = 8), FHV (n = 7) and CHV (n = 3) in enzyme immunoassays employing fixed infected c