Weakly useful sequences

An infinite binary sequence x is defined to be

(i) strongly useful if there is a computable time bound within which every decidable sequence is Turing reducible to x; and

(ii) weakly useful if there is a computable time bound within which all the sequences in a non-measure 0 subset of the set of decidable sequences are Turing reducible to x.

Juedes, Lathrop, and Lutz [Theorectical Computer Science 132 (1994) 37] proved that every weakly useful sequence is strongly deep in the sense of Bennett [The Universal Turing Machine: A Half-Century Survey, 1988, 227] and asked whether there are sequences that are weakly useful but not strongly useful. The present paper answers this question affirmatively. The proof is a direct construction that combines the martingale diagonalization technique of Lutz [SIAM Journal on Computing 24 (1995) 1170] with a new technique, namely, the construction of a sequence that is “computably deep” with respect to an arbitrary, given uniform reducibility. The abundance of such computably deep sequences is also proven and used to show that every weakly useful sequence is computably deep with respect to every uniform reducibility.

Predicting methyl tert-butyl ether, tert-butyl formate, and tert-butyl alcohol levels in the environment using the fugacity approach

Through its extensive use as a fuel oxygenate, methyl tert-butyl ether (MTBE) is found nearly ubiquitouslythroughout the environment. To better understand the environmental fate of MTBE, fugacity models are commonly used. However, models developed by the scientific community and by governmental bodies differ in their predictions of relative MTBE concentrations for relevant environmental compartments and of seasonal concentration variations; further, to date they have not considered the formation of transformation products. In this study, the sensitivity of predicted environmental concentrations of MTBE and its two major degradation products, tert-butyl formate (TBF) and tert-butyl alcohol (TBA), to all types of model input parameters is analyzed in a probabilistic sensitivity analysis. This analysis allowed for an assessment of the most influential parameters for predicting soil, water, and air concentrations and thereby provided insight into why previous modeling studies on MTBE differed. Further, the information from the sensitivity analysis was used to parametrize a multispecies transformation model for predicting European concentration levels of MTBE and, for the first time, TBF and TBA. Water and air concentrations of MTBE predicted with the transformation model were in good agreement with measurements of environmental samples. No studies are available on environmental TBF and TBA levels to compare with model predictions; however, the modeling results indicate that, in the water phase, TBA concentrations may reach appreciable levels. One major uncertainty identified regarding the prediction of TBA levels was the fraction of TBA formed from atmospheric MTBE and TBF.     

Effect of sterol alterations on conjugation in Saccharomyces cerevisiae.

Sterol auxotrophic strains of Saccharomyces cerevisiae were grown and allowed to conjugate on media supplemented with various sterols. The mating efficiency of the auxotrophs is perturbed by the replacement of the normal yeast sterol, ergosterol, with other sterols. After 4 h of mating, cells grown on ergosterol exhibited a 30-fold higher productive mating efficiency than those cells grown in stigmasterol. Aberrant budding by the conjugants was enhanced following incubation on stigmasterol and other non-ergosterol sterols. Using light and electron microscopy, we demonstrated that there is a reduced ability for stigmasterol-grown cells to undergo cytoplasmic fusion during conjugation. Many of the mated pairs remained adherent but prezygotic even after 12 h of incubation. The addition of ergosterol to cells previously grown on stigmasterol rescued the organisms, allowing for zygote formation and normal budding.     

Characterisation of the $$\chi$$χ-index and the rec-index

Scientometrics - Axiomatic characterisation of a bibliometric index provides insight into the properties that the index satisfies and facilitates the comparison of different indices. A geometric...     

Images of a First‐Order Spin‐Reorientation Phase Transition in a Metallic Kagome Ferromagnet

First‐order phase transitions, where one phase replaces another by virtue of a simple crossing of free energies, are best known between solids, liquids, and vapors, but they also occur in a wide range of other contexts, including even elemental magnets. The key challenges are to establish whether a phase transition is indeed first order, and then to determine how the new phase emerges because this will determine thermodynamic and electronic properties. Here it is shown that both challenges are met for the spin reorientation transition in the topological metallic ferromagnet Fe₃Sn₂. The magnetometry and variable temperature magnetic force microscopy experiments reveal that, analogous to the liquid–gas transition in the temperature–pressure plane, this transition is centered on a first‐order line terminating in a critical end point in the field‐temperature plane. The nucleation and growth associated with the transition is directly imaged, indicating that the new phase emerges at the most convoluted magnetic domain walls for the high temperature phase and then moves to self‐organize at the domain centers of the high temperature phase. The dense domain patterns and phase coexistence imply a complex inhomogenous electronic structure, which can yield anomalous contributions to the electrical conductivity.     

Application of multimedia models for screening assessment of long-range transport potential and overall persistence

We propose a multimedia model-based methodology to evaluate whether a chemical substance qualifies as POP-like based on overall persistence (Pov) and potential for long-range transport (LRTP). It relies upon screening chemicals against the Pov and LRTP characteristics of selected reference chemicals with well-established environmental fates. Results indicate that chemicals of high and low concern in terms of persistence and long-range transport can be consistently identified by eight contemporary multimedia models using the proposed methodology. Model results for three hypothetical chemicals illustrate that the model-based classification of chemicals according to Pov and LRTP is not always consistent with the single-media half-life approach proposed by the UNEP Stockholm Convention and thatthe models provide additional insight into the likely long-term hazards associated with chemicals in the environment. We suggest this model-based classification method be adopted as a complement to screening against defined half-life criteria at the initial stages of tiered assessments designed to identify POP-like chemicals and to prioritize further environmental fate studies for new and existing chemicals.     

Pesticide nonextractable residue formation in soil: insights from inverse modeling of degradation time series

Formation of soil nonextractable residues (NER) is central to the fate and persistence of pesticides. To investigate pools and extent of NER formation, an established inverse modeling approach for pesticide soil degradation time series was evaluated with a Monte Carlo Markov Chain (MCMC) sampling procedure. It was found that only half of 73 pesticide degradation time series from a homogeneous soil source allowed for well-behaved identification of kinetic parameters with a four-pool model containing a parent compound, a metabolite, a volatile, and a NER pool. A subsequent simulation indeed confirmed distinct parameter combinations of low identifiability. Taking the resulting uncertainties into account, several conclusions regarding NER formation and its impact on persistence assessment could nonetheless be drawn. First, rate constants for transformation of parent compounds to metabolites were correlated to those for transformation of parent compounds to NER, leading to degradation half-lives (DegT50) typically not being larger than disappearance half-lives (DT50) by more than a factor of 2. Second, estimated rate constants were used to evaluate NER formation over time. This showed that NER formation, particularly through the metabolite pool, may be grossly underestimated when using standard incubation periods. It further showed that amounts and uncertainties in (i) total NER, (ii) NER formed from the parent pool, and (iii) NER formed from the metabolite pool vary considerably among data sets at t→∞, with no clear dominance between (ii) and (iii). However, compounds containing aromatic amine moieties were found to form significantly more total NER when extrapolating to t→∞ than the other compounds studied. Overall, our study stresses the general need for assessing uncertainties, identifiability issues, and resulting biases when using inverse modeling of degradation time series for evaluating persistence and NER formation.     

Pleiotropic mutations in Saccharomyces cerevisiae affecting sterol uptake and metabolism

Sterol uptake control mutants (upc-) have been isolated via ethylmethanesulfonate mutagenesis from wild-type Saccharomyces cerevisiae. These mutants are heme and sterol competent but possess the ability to accumulate exogenous sterol(s) under aerobic conditions. Previous studies demonstrate sterol uptake only in a hem-, erg- background; however, the Upc- strains described here are Hem+ and do not require exogenous sterol for growth. We were unable to obtain viable hem+, erg-, upc+ recombinants; such combinations appear to be lethal. Isolates of Upc mutants demonstrated different levels of sterol uptake, and sterol analysis revealed a broad phenotypic range with regard to amounts and accumulation of ergosterol and non-ergosterol sterols. Assays of acyl CoA: ergosterol acyltransferase and sterol ester hydrolase showed no apparent difference in activity between Upc mutants and the wild type.     

Assessing exposure to transformation products of soil-applied organic contaminants in surface water: comparison of model predictions and field data

Transformation products (TPs) of chemicals released to soil, for example, pesticides, are regularly detected in surface and groundwater with some TPs even dominating observed pesticide levels. Given the large number of TPs potentially formed in the environment, straightforward prioritization methods based on available data and simple, evaluative models are required to identify TPs with a high aquatic exposure potential. While different such methods exist, none of them has so far been systematically evaluated against field data. Using a dynamic multimedia, multispecies model for TP prioritization, we compared the predicted relative surface water exposure potential of pesticides and their TPs with experimental data for 16 pesticides and 46 TPs measured in a small river draining a Swiss agricultural catchment. Twenty TPs were determined quantitatively using solid-phase extraction liquid chromatography mass spectrometry (SPE-LC-MS/MS), whereas the remaining 26 TPs could only be detected qualitatively because of the lack of analytical reference standards. Accordingly, the two sets of TPs were used for quantitative and qualitative model evaluation, respectively. Quantitative comparison of predicted with measured surface water exposure ratios for 20 pairs of TPs and parent pesticides indicated agreement within a factor of 10, except for chloridazon-desphenyl and chloridazon-methyl-desphenyl. The latter two TPs were found to be present in elevated concentrations during baseflow conditions and in groundwater samples across Switzerland, pointing toward high concentrations in exfiltrating groundwater. A simple leaching relationship was shown to qualitatively agree with the observed baseflow concentrations and to thus be useful in identifying TPs for which the simple prioritization model might underestimate actual surface water concentrations. Application of the model to the 26 qualitatively analyzed TPs showed that most of those TPs categorized as exhibiting a high aquatic exposure potential could be confirmed to be present in the majority of water samples investigated. On the basis of these results, we propose a generally applicable, model-based approach to identify those TPs of soil-applied organic contaminants that exhibit a high aquatic exposure potential to prioritize them for higher-tier, experimental investigations.